sentences
stringlengths 139
8.91k
| labels
stringclasses 26
values |
|---|---|
Targeted gene correction and functional recovery in achondroplasia patient-derived iPSCs BackgroundAchondroplasia (ACH) is the most common genetic form of dwarfism and belongs to dominant monogenic disorder caused by a gain-of-function point mutation in the transmembrane region of FGFR3. There are no effective treatments for ACH. Stem cells and gene-editing technology provide us with effective methods and ideas for ACH research and treatment.
MethodsWe generated non-integrated iPSCs from an ACH girls skin and an ACH boys urine by Sendai virus. The mutation of ACH iPSCs was precisely corrected by CRISPR-Cas9.
ResultsChondrogenic differentiation ability of ACH iPSCs was confined compared with that of healthy iPSCs. Chondrogenic differentiation ability of corrected ACH iPSCs could be restored. These corrected iPSCs displayed pluripotency, maintained normal karyotype, and demonstrated none of off-target indels.
ConclusionsThis study may provide an important theoretical and experimental basis for the ACH research and treatment. | developmental biology |
PLETHORA-WOX5 interaction and subnuclear localisation control Arabidopsis root stem cell maintenance Maintenance and homeostasis of the stem cell niche (SCN) in the Arabidopsis root is essential for growth and development of all root cell types. The SCN is organized around a quiescent center (QC) maintaining the stemness of cells in direct contact. The key transcription factors (TFs) WUSCHEL-RELATED HOMEOBOX 5 (WOX5) and PLETHORAs (PLTs) are expressed in the SCN where they maintain the QC and regulate distal columella stem cell (CSC) fate. Here, we describe the concerted mutual regulation of the key TFs WOX5 and PLTs on a transcriptional and protein interaction level. Additionally, by applying a novel SCN staining method, we demonstrate that both WOX5 and PLTs regulate root SCN homeostasis as they control QC quiescence and CSC fate interdependently. Moreover, we uncover that some PLTs, especially PLT3, contain intrinsically disordered prion-like domains (PrDs) that are necessary for complex formation with WOX5 and its recruitment to subnuclear microdomains/nuclear bodies (NBs) in the CSCs. We propose that this partitioning of PLT-WOX5 complexes to NBs, possibly by phase separation, is important for CSC fate determination. | plant biology |
High-Throughput Translational Profiling with riboPLATE-seq Protein synthesis is dysregulated in many diseases, but we lack a systems-level picture of how signaling molecules and RNA binding proteins interact with the translational machinery, largely due to technological limitations. Here we present riboPLATE-seq, a scalable method for generating paired libraries of ribosome-associated and total mRNA. As an extension of the PLATE-seq protocol, riboPLATE-seq utilizes barcoded primers for pooled library preparation, but additionally leverages rRNA immunoprecipitation on whole polysomes to measure ribosome association (RA). We compare RA to its analogue in ribosome profiling and RNA sequencing, translation efficiency, and demonstrate both the performance of riboPLATE-seq and its utility in detecting translational alterations induced by specific inhibitors of protein kinases. | systems biology |
Incorporating Gene Expression in Genome-wide Prediction of Chromatin Accessibility via Deep Learning Although computational approaches have been complementing high-throughput biological experiments for the identification of functional regions in the human genome, it remains a great challenge to systematically decipher interactions between transcription factors and regulatory elements to achieve interpretable annotations of chromatin accessibility across diverse cellular contexts. Towards this problem, we propose DeepCAGE, a deep learning framework that integrates sequence information and binding status of transcription factors, for the accurate prediction of chromatin accessible regions at a genome-wide scale in a variety of cell types. DeepCAGE takes advantage of a densely connected deep convolutional neural network architecture to automatically learn sequence signatures of known chromatin accessible regions, and then incorporates such features with expression levels and binding activities of human core transcription factors to predict novel chromatin accessible regions. In a series of systematic comparisons with existing methods, DeepCAGE exhibits superior performance in not only the classification but also the regression of chromatin accessibility signals. In detailed analysis of transcription factor activities, DeepCAGE successfully extracts novel binding motifs and measures the contribution of a transcription factor to the regulation with respect to a specific locus in a certain cell type. When applied to whole-genome sequencing data analysis, our method successfully prioritizes putative deleterious variants underlying a human complex trait, and thus provides insights into the understanding of disease-associated genetic variants. DeepCAGE can be downloaded from https://github.com/kimmo1019/DeepCAGE. | bioinformatics |
Identification of neural oscillations and epileptiform changes in human brain organoids Brain organoids represent a powerful tool for the study of human neurological diseases, particularly those impacting brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes. This raises the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network behaviors reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from MECP2 mutant patients compared to isogenic controls accompanied by modest transcriptomic differences revealed by single cell analyses. We also rescue key physiological activities with an unconventional neuromodulatory drug, Pifithrin-. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery. | neuroscience |
Coordination through inhibition: control of stabilizing and updating circuits in spatial orientation working memory Spatial orientation memory plays a crucial role in animal navigation. Recent studies of tethered Drosophila melanogaster (fruit fly) in a virtual reality setting showed that the head direction is encoded in the form of an activity bump, i.e. localized neural activity, in the torus-shaped ellipsoid body (EB). However, how this system is involved in orientation working memory is not well understood. We investigated this question using free moving flies (Drosophila melanogaster) in a spatial orientation memory task by manipulating two EB subsystems, C and P circuits, which are hypothesized for stabilizing and updating the activity bump, respectively. To this end, we suppressed or activated two types of inhibitory ring neurons (EIP and P) which innervate EB, and we discovered that manipulating the two inhibitory neuron types produced distinct behavioral deficits, suggesting specific roles of the inhibitory neurons in coordinating the stabilization and updating functions of the EB circuits. We further elucidate the neural mechanisms underlying such control circuits using a connectome-constrained spiking neural network model.
Significance statementHead-direction (HD) system has been discovered in rodents for decades. But the detailed neural circuit mechanisms underlying the HD system were only described recently by studies of fruit flies on the similar HD system. However, how this fruit fly HD system involves in orientation memory was not well investigated. The present study addresses this question by investigating free moving flies in a spatial orientation working memory task. By combining neural functional experiments and neural circuit modelling, the study shows how disrupting either of the two subcircuits, one stabilizing and the other updating the neural activity, in the HD system leads to different behavioral impairments. The result suggests specific roles of the HD subcircuits in the spatial orientation working memory.
Visual Abstract
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/819185v2_ufig1.gif" ALT="Figure 1">
View larger version (22K):
[email protected]@b7ac8borg.highwire.dtl.DTLVardef@a10a41org.highwire.dtl.DTLVardef@a8691e_HPS_FORMAT_FIGEXP M_FIG C_FIG | neuroscience |
The NTD of Eukaryotic Initiation Factor 4B Drives Yeast Translational Control in Response to Urea The yeast eukaryotic initiation factor 4B binds the 40S subunit in translation preinitiation complexes (PICs), promoting mRNA binding. Recent evidence suggests mRNAs have variable dependence on eIF4B, suggesting this factor could promote changes in mRNA selection for translation, in order to adapt to stressors. However, the importance of eIF4B and its constituent domains for mRNA selection under diverse cellular and environmental conditions remain undefined. Here we compared the effects of disrupting eIF4B RNA- and ribosome-binding motifs under ~1400 growth conditions. The RNA-Recognition Motif (RRM) was dispensable for stress responses, but the 40S-binding N-terminal Domain (NTD) promoted growth in response to various stressors. In particular, the NTD conferred a strong growth advantage in the presence of urea. Ribosome profiling revealed that the NTD promoted translation of mRNAs with long and highly structured 5-prime untranslated regions, both with and without urea exposure. Our results suggest eIF4B controls mRNA loading and scanning as a part of the PIC, rather than by activating mRNPs prior to ribosome binding. Furthermore, our data indicate the yeast response to urea includes a translational component, driven by production of proteins associated with the cellular periphery. Together our analyses suggest general eIFs can promote diverse cellular responses. | molecular biology |
Ten-eleven translocation 1 Mediated-DNA Hydroxymethylation is Required for Myelination and Remyelination in the Mouse Brain Ten-eleven translocation (TET) proteins, the dioxygenase for DNA hydroxymethylation, are important players in nervous system development and diseases. However, their role in myelination and remyelination after injury remains elusive. Here, we identify a genome-wide and locus-specific DNA hydroxymethylation landscape shift during differentiation of oligodendrocyte-progenitor cells (OPC). Ablation of Tet1 results in stage-dependent defects in oligodendrocyte (OL) development and myelination in the mouse brain. The mice lacking Tet1 in the oligodendrocyte lineage develop behavioral deficiency. We also show that TET1 is required for remyelination in adulthood. Transcriptomic, genomic occupancy, and DNA hydroxymethylation profiling reveal a critical TET1-regulated epigenetic program for oligodendrocyte differentiation that includes genes associated with myelination, cell division, and calcium transport. Tet1-deficient OPCs exhibit reduced calcium activity, increasing calcium activity rescues the differentiation defects in vitro. Deletion of a TET1-5hmC target gene, Itpr2 impairs the onset of OPC differentiation. Together, our results suggest that stage-specific TET1-mediated epigenetic programming and intracellular signaling are important for proper myelination and remyelination in mice. | neuroscience |
Roles of adenine methylation and genetic mutations in adaptation to different temperatures in Serratia marcescens Epigenetic modifications can contribute to adaptation, but the relative contributions of genetic and epigenetic variation are unknown. Previous studies on the role of epigenetic changes in adaptation in eukaryotes have nearly exclusively focused on cytosine methylation (m5C), while prokaryotes exhibit a richer system of methyltransferases targetting adenines (m6A) or cytosines (m4C, m5C). DNA methylation in prokaryotes has many roles, but its potential role in adaptation still needs further investigation. We collected phenotypic, genetic, and epigenetic data using single molecule real-time sequencing of clones of the bacterium Serratia marcescens that had undergone experimental evolution in contrasting temperatures to investigate the relationship between environment and genetic, epigenetic, and phenotypic changes. This data provided a detailed description of the methylation landscape of S. marcescens and allowed us to examine the potential contributions of genetic and epigenetic changes to phenotypic adaptation. The genomic distribution of GATC motifs, which are the main target for m6A methylation, and of partially methylated epiloci pointed to a link between m6A methylation and regulation of gene expression in S. marcescens. Evolved strains, while genetically homogeneous, exhibited many polymorphic m6A epiloci. There was no strong support for a genetic control of methylation changes in our experiment, and no clear evidence of parallel environmentally-induced or environmentally-selected methylation changes at specific epiloci was found. Both some genetic and epigenetic variants were associated with some phenotypic traits. Overall, our results suggest that both genetic and adenine methylation changes have potential to contribute to phenotypic adaptation in S. marcescens, but that any environmentally-induced epigenetic change occurring in our experiment would probably have been quite labile. | evolutionary biology |
Broadband Signal Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography (ECoG) was carried out in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFP) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamical states which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.
Significance StatementThis study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity - an auditory prediction error response - is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of non-oscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information. | neuroscience |
Cerebellar lesions disrupt spatial and temporal visual attention. The current study represents the first comprehensive examination of spatial, temporal and sustained attention following cerebellar damage. Results indicated that, compared to controls, cerebellar damage resulted in a larger cueing effect at the longest SOA - possibly reflecting a slowed the onset of inhibition of return (IOR) during a reflexive covert attention task, and reduced the ability to detect successive targets during an attentional blink task. However, there was little evidence to support the notion that cerebellar damage disrupted voluntary covert attention or the sustained attention to response task (SART). Lesion overlay data and supplementary voxel-based lesion symptom mapping (VLSM) analyses indicated that impaired performance on the reflexive covert attention and attentional blink tasks were related to damage to Crus II of the left posterior cerebellum. In addition, subsequent analyses indicated our results are not due to either general motor impairments or to damage to the deep cerebellar nuclei. Collectively these data demonstrate, for the first time, that the same cerebellar regions may be involved in both spatial and temporal visual attention. | neuroscience |
Host-microbiome protein-protein interactions capture mechanisms in human disease Host-microbe interactions are crucial for normal physiological and immune system development and are implicated in a wide variety of diseases, including inflammatory bowel disease (IBD), colorectal cancer (CRC), obesity, and type 2 diabetes (T2D). Despite large-scale case-control studies aimed at identifying microbial taxa or specific genes involved in pathogeneses, the mechanisms linking them to disease have thus far remained elusive. To identify potential mechanisms through which human-associated bacteria impact host health, we leveraged publicly-available interspecies protein-protein interaction (PPI) data to find clusters of microbiome-derived proteins with high sequence identity to known human protein interactors. We observe differential targeting of putative human-interacting bacterial genes in metagenomic case-control microbiome studies. In nine independent case studies, we find evidence that the microbiome broadly targets human proteins involved in immune, oncogenic, apoptotic, and endocrine signaling pathways in relation to IBD, CRC, obesity and T2D diagnoses. This host-centric analysis strategy provides a mechanistic hypothesis-generating platform for any metagenomics cohort study and extensively adds human functional annotation to commensal bacterial proteins.
One-sentence summaryMicrobiome-derived proteins are linked to disease-associated human pathways by metagenomic and protein-protein interaction analyses. | microbiology |
Species richness increases fitness differences, but does not affect niche differences A key question in ecology is what limits species richness. Modern coexistence theory presents the persistence of species as a balance between niche differences and fitness differences that favor and hamper coexistence, respectively. With most applications focusing on species pairs, however, we know little about if and how this balance changes with species richness. Here, we present the first mathematical proof that the average fitness difference among species increases with richness, while the average niche difference stays constant. Extensive simulations with more complex models and analyses of empirical data confirmed these mathematical results. Taken together, our work suggests that, as species accumulate in ecosystems, ever-increasing fitness differences will at some point exceed constant niche differences, limiting species richness. Our results contribute to the expansion of modern coexistence theory towards multi-species communities. | ecology |
Non-selective response inhibition in Go/NoGo task: Bayesian analysis of fMRI data Response inhibition is typically considered a brain mechanism selectively triggered by particular "inhibitory" stimuli or events. Based on recent research, an alternative non-selective mechanism was proposed by several authors. Presumably, the inhibitory brain activity may be triggered not only by the presentation of "inhibitory" stimuli but also by any imperative stimuli, including Go stimuli, when the context is uncertain. Earlier support for this notion was mainly based on the absence of a significant difference between neural activity evoked by equiprobable Go and NoGo stimuli. Equiprobable Go/NoGo design with a simple response time task limits potential confounds between response inhibition and accompanying cognitive processes while not preventing prepotent automaticity. However, previous neuroimaging studies utilized classical null hypothesis significance testing, making it impossible to accept the null hypothesis. Therefore, the current research aimed to provide evidence for practical equivalence of neuronal activity in Go and NoGo trials using Bayesian analysis of functional magnetic resonance imaging (fMRI) data. Thirty-four healthy participants performed a cued Go/NoGo task with an equiprobable presentation of Go and NoGo stimuli. To independently localize brain areas associated with response inhibition in similar experimental conditions, we performed a meta-analysis of fMRI studies using equal probability Go/NoGo tasks. As a result, we observed overlap between response inhibition areas and areas demonstrating the practical equivalence of neuronal activity located in the right dorsolateral prefrontal cortex, parietal cortex, premotor cortex, and left inferior frontal gyrus. Thus, obtained results favour the existence of non-selective response inhibition, which can act in settings of contextual uncertainty induced by the equal probability of Go and NoGo stimuli.
Highlights O_LINon-selective response inhibition was assessed by equiprobable Go/NoGo task
C_LIO_LIBayesian analysis of fMRI data was combined with a meta-analysis of fMRI studies
C_LIO_LISeveral nodes of response inhibition system were equally involved in Go and NoGo trials
C_LIO_LIEvidence for non-selective response inhibition in uncertain context was found
C_LI | neuroscience |
Activation of G-protein coupled estradiol receptor 1 in the dorsolateral striatum attenuates preference for cocaine and saccharin in male but not female rats There are sex differences in the response to psychomotor stimulants, where females exhibit a greater response than males, due to the presence of the gonadal hormone estradiol (E2). Extensive research has shown that E2 enhances drug-seeking and the rewarding properties of cocaine for females. The role of E2 in male drug-seeking, however, is not well understood. The current study investigated pharmacological manipulation of E2 receptors in the dorsolateral striatum (DLS) on preference for cocaine in gonad-intact male and female rats. In males, activation of G-protein coupled E2 receptor 1 (GPER1), via administration of ICI 182,780 or G1, attenuated conditioned place preference for 10mg/kg cocaine, while inhibition of GPER1, via G15, enhanced preference at a 5mg/kg cocaine dose. Similarly, GPER1 activation, via G1, prevented males from forming a preference for 0.1% saccharin (SACC) versus plain water. Surprisingly, activation of GPER1 did not alter preference for cocaine or SACC in females. These studies also examined the quantity of E2 receptor mRNA in the dorsal striatum, using qPCR. No sex differences in relative mRNA expression of ER, ER{beta}, and GPER1 were observed. However, there was greater GPER1 mRNA, relative to ER and ER{beta}, in both males and females. The results presented here indicate that E2, acting via GPER1, may be protective against drug preference in male rats. | neuroscience |
NHR-8 regulated P-glycoproteins uncouple xenobiotic stress resistance from longevity in chemosensory C. elegans mutants Longevity is often associated with stress resistance, but whether they are causally linked is incompletely understood. Here we investigate chemosensory defective Caenorhabditis elegans mutants that are long-lived and stress resistant. We find that mutants in the intraflagellar transport protein gene osm-3 were significantly protected from tunicamycin-induced ER stress. While osm-3 lifespan extension is dependent on the key longevity factor DAF-16/FOXO, tunicamycin resistance was not. osm-3 mutants are protected from bacterial pathogens, which is pmk-1 p38 MAP kinase dependent while TM resistance was pmk-1 independent. Expression of P-glycoprotein (PGP) xenobiotic detoxification genes was elevated in osm-3 mutants and their knockdown or inhibition with verapamil suppressed tunicamycin resistance. The nuclear hormone receptor nhr-8 was necessary to regulate PGPs and tunicamycin resistance in a cholesterol-dependent fashion. We thus identify a cell-nonautonomous regulation of xenobiotic detoxification and show that separate pathways are engaged to mediate longevity, pathogen resistance, and xenobiotic detoxification in osm-3 mutants. | genetics |
Distinct roles for dopamine clearance mechanisms in regulating behavioral flexibility Dopamine plays a crucial role in adaptive behavior, and dysfunctional dopamine is implicated in multiple psychiatric conditions characterized by inflexible or inconsistent choices. However, the precise relationship between dopamine and flexible decision making remains unclear. One reason is that, while many studies have focused on the activity of dopamine neurons, efficient dopamine signaling also relies on clearance mechanisms, notably the dopamine transporter (DAT), which predominates in striatum, and catechol-O-methyltransferase (COMT), which predominates in cortex. The exact locus, extent, and timescale of the effects of DAT and COMT are uncertain. Moreover, there is limited data on how acute disruption of either mechanism affects flexible decision making strategies mediated by cortico-striatal networks. To address these issues, we combined pharmacological modulation of DAT and COMT with electrochemistry and behavior in mice. DAT blockade, but not COMT inhibition, regulated sub-second dopamine release in the nucleus accumbens core, but surprisingly neither clearance mechanism affected evoked release in prelimbic cortex. This was not due to a lack of sensitivity, as both amphetamine and atomoxetine changed the kinetics of sub-second release. In a multi-step decision making task where mice had to respond to reversals in either reward probabilities or the choice sequence to reach the goal, DAT blockade selectively impaired, and COMT inhibition improved, performance after reward reversals, but neither manipulation affected the adaptation of choices after actionstate transition reversals. Together, our data suggest that DAT and COMT shape specific aspects of behavioral flexibility by regulating striatal and cortical dopamine, respectively, at fast and slow timescales. | neuroscience |
Using the Tea Bag Index to determine how two human pharmaceuticals affect litter decomposition by aquatic microorganisms. This study demonstrates that independent additive effects of two human pharmaceuticals, the antibiotic trimethoprim and the artificial estrogen 17a-Ethinylestradiol (EE2), inhibit plant litter decomposition by aquatic microorganisms. The constant release of pharmaceuticals, such as these, has the potential to affect aquatic microbial metabolism and alter biogeochemical cycling of carbon and nutrients. Here we advance the Tea Bag Index (TBI) for decomposition by using it in a series of contaminant exposure experiments testing how interactions between trimethoprim and EE2 affect aquatic microbial activity. The TBI is a citizen science tool used to test microbial activity by measuring the differential degradation of green and rooibos tea as proxies for respectively labile and recalcitrant litter decomposition. Exposure to either trimethoprim or EE2 decreased decomposition of green tea, suggesting additive effects upon microbial activity. Exposure to EE2 alone decreased rooibos tea decomposition. Consequently, trimethoprim and EE2 stabilized labile organic matter against microbial degradation and restricted decomposition. We propose that the method outlined could provide a powerful tool for testing the impacts of multiple interacting pollutants upon microbial activity, at a range of scales, across aquatic systems and over ecologically relevant time scales. | microbiology |
CloneSig: Joint inference of intra-tumor heterogeneity and mutational signatures' activity in tumor bulk sequencing data Systematic DNA sequencing of cancer samples has highlighted the importance of two aspects of cancer genomics: intra-tumor heterogeneity (ITH) and mutational processes. These two aspects may not always be independent, as different mutational processes could be involved in different stages or regions of the tumor, but existing computational approaches to study them largely ignore this potential dependency. Here, we present CloneSig, a computational method to jointly infer ITH and mutational processes in a tumor from bulk-sequencing data. Extensive simulations show that CloneSig outperforms current methods for ITH inference and detection of mutational processes when the distribution of mutational signatures changes between clones. Applied to a large cohort of 8,951 tumors with whole-exome sequencing data from The Cancer Genome Atlas, and on a pan-cancer dataset of 2,632 whole-genome sequencing tumor samples from the Pan-Cancer Analysis of Whole Genomes initiative, CloneSig obtains results overall coherent with previous studies. | bioinformatics |
A rationally designed oral vaccine induces Immunoglobulin A in the murine gut that directs the evolution of attenuated Salmonella variants Introductory paragraphThe ability of gut bacterial pathogens to escape immunity by antigenic variation, particularly via changes to surface-exposed antigens, is a major barrier to immune clearance1. However, not all variants are equally fit in all environments2, 3. It should therefore be possible to exploit such immune escape mechanisms to direct an evolutionary trade-off. Here we demonstrated this phenomenon using Salmonella enterica subspecies enterica serovar Typhimurium (S.Tm). A dominant surface antigen of S.Tm is its O-antigen: A long, repetitive glycan that can be rapidly varied by mutations in biosynthetic pathways or by phase-variation4, 5. We quantified the selective advantage of O-antigen variants in the presence and absence of O-antigen specific IgA and identified a set of evolutionary trajectories allowing immune escape without an associated fitness cost in naive mice. Through the use of oral vaccines, we rationally induced IgA responses blocking all of these trajectories, which selected for Salmonella mutants carrying deletions of the O-antigen polymerase wzyB. Due to their short O-antigen, these evolved mutants were more susceptible to environmental stressors (detergents, complement), predation (bacteriophages), and were impaired in gut colonization and virulence in mice. Therefore, a rationally induced cocktail of intestinal antibodies can direct an evolutionary trade-off in S.Tm. This lays the foundations for the exploration of mucosal vaccines capable of setting evolutionary traps as a prophylactic strategy. | immunology |
Regulation of apical constriction via microtubule- and Rab11-dependent apical transport during tissue invagination The formation of an epithelial tube is a fundamental process for organogenesis. During Drosophila embryonic salivary gland (SG) invagination, Folded gastrulation (Fog)- dependent Rho-associated kinase (Rok) promotes contractile apical myosin formation to drive apical constriction. Microtubules (MTs) are also crucial for this process and are required for forming and maintaining apicomedial myosin. However, the underlying mechanism that coordinates actomyosin and MT networks still remains elusive. Here, we show that MT-dependent intracellular trafficking regulates apical constriction during SG invagination. Key components involved in protein trafficking, such as Rab11 and Nuclear fallout (Nuf), are apically enriched near the SG invagination pit in a MT-dependent manner. Disruption of the MT networks or knockdown of Rab11 impairs apicomedial myosin formation and apical constriction. We show that MTs and Rab11 are required for apical enrichment of the Fog ligand and the continuous distribution of the apical determinant protein Crumbs (Crb) and the key adherens junction protein E-Cadherin (E-Cad) along junctions. Targeted knockdown of crb or E-Cad in the SG disrupts apical myosin networks and results in apical constriction defects. Our data suggest a role of MT- and Rab11-dependent intracellular trafficking in regulating actomyosin networks and cell junctions, to coordinate cell behaviors during tubular organ formation. | developmental biology |
Ebselen attenuates mycobacterial virulence through inhibition of ESX-1 secretion The type VII secretion system ESX-1 mediates virulence in Mycobacterium tuberculosis and Mycobacterium marinum. We find that in M. marinum, the synthetic organoselenium compound ebselen inhibits secretion of ESAT-6, a major ESX-1 substrate. We find that ebselen inhibits the in vitro activity of the ESX-1 AAA+ ATPase EccA1, which potentiates ESX-1 substrate secretion and function. Ebselen modifies a cysteine in its N-terminal tetratricopeptide repeat domain that is required for EccA1s in vitro ATPase activity. Surprisingly, mutational analyses show this this cysteine is not required for ESX-1 secretion or ebselens activity, showing that ebselen inhibits ESX-1 secretion independently of inhibiting EccA1 activity in vitro. While the mechanism by which ebselen inhibits ESX-1 secretion remains elusive, we show that it attenuates ESX-1-mediated damage of M. marinum-containing macrophage phagosomes and inhibits intramacrophage growth. Extending our studies to M. tuberculosis, we find that ebselen inhibits ESX-1 secretion and phagosomal membrane damage in this organism. This work provides insight into EccA1 biology. Ebselen is an orally active drug in clinical trials for other conditions and this work suggests its potential in tuberculosis therapy. | microbiology |
Low-disturbance Farming Regenerates Healthy Deep Soil towards Sustainable Agriculture Intensive conventional farming has degraded farmland topsoil and seriously threaten food and environment security globally. Although low-disturbance practices have been widely adapted to restore soil health, whether this measure in a long run can potentially recover the critical deep soil to meet sustainable intensification of crop production are still unclear. Here we compared soil microbiome, physicochemical parameters along 3-m deep soil profiles, and crop yield in Northeast China subjected to ten years of farming practices at 3 levels of disturbance, including conventional tillage (CT), no-tillage without stover mulching (NTNS), and no-tillage with stover mulching (NTSM). We found that low-disturbance practices (NTNS and NTSM) promoted the ability of the deep soil to retain water, nitrogen and salt-extractable organic, regenerated whole-soil microbial diversity and metabolic function, improved topsoil organic carbon stock and corn yield in the drought year, showed the potential to reduce energy consumption and greenhouse gas emissions, thus regenerating highly efficient, sustainable agriculture. | ecology |
Population structure of chum salmon and selection on the markers collected for stock identification Genetic stock identification (GSI) is a major management tool of Pacific salmon (Oncorhynchus Spp.) that has provided rich genetic baseline data of allozymes, microsatellites, and single nucleotide polymorphisms (SNPs) across the Pacific Rim. Here, we analyzed published data sets for adult chum salmon (Oncorhynchus keta), namely 10 microsatellites, 53 SNPs, and a mitochondrial DNA locus (mtDNA3, control region and NADH-3 combined) from 495 locations in the same distribution range (n = 61,813). TreeMix analysis of the microsatellite loci identified the highest level of genetic drift towards Japanese/Korean populations and suggested two admixture events from Japan/Korea to Russia and the Alaskan Peninsula. The SNPs had been purposively collected from rapidly evolving genes to increase the power of GSI. The highest expected heterozygosity was observed in Japanese/Korean populations for microsatellites, whereas it was highest in Western Alaskan populations for SNPs, reflecting the SNP discovery process. By regressing the SNP population structures on those of the microsatellites, we estimated the selection on the SNP loci according to deviations from the predicted structures. Specifically, we matched the sampling locations of the SNPs with those of the microsatellites according to geographical information and performed regression analyses of SNP allele frequencies on the two coordinates of multi-dimensional scaling (MDS) of matched locations obtained from microsatellite pairwise FST values. The MDS first axis indicated a latitudinal cline in American and Russian populations, whereas the second axis found a differentiation of Japanese/Korean populations. The top five outlier SNPs were mtDNA3 (combined locus of the control region and NADH-3), U502241 (unknown), GnRH373, ras1362, and TCP178, which were consistently identified by principal component analysis. We summarized the functions of the 53 nuclear SNPs and mtDNA3 locus by referring to a gene database system and discussed the functions of the outlier SNPs and fitness of chum salmon. | evolutionary biology |
Stability of neocortical synapses across sleep and wake Sleep is important for brain plasticity, but its exact function remains mysterious. An influential but controversial idea is that a crucial function of sleep is to drive widespread downscaling of excitatory synaptic strengths. Here we used real-time sleep classification, ex vivo measurements of postsynaptic strength, and in vivo optogenetic monitoring of thalamocortical synaptic efficacy to ask whether sleep and wake states can constitutively drive changes in synaptic strength within the neocortex of juvenile rats. We found that miniature EPSC amplitudes onto L4 and L2/3 pyramidal neurons were stable across sleep and wake dense epochs in both primary visual (V1) and prefrontal cortex (PFC). Further, chronic monitoring of thalamocortical synaptic efficacy in V1 of freely behaving animals revealed stable responses across even prolonged periods of natural sleep and wake. Together these data demonstrate that neocortical synaptic strengths are remarkably stable across sleep and wake states, and provide strong evidence against the view that sleep drives widespread synaptic downscaling at neocortical synapses. | neuroscience |
Prefrontal deep projection neurons enable cognitive flexibility via persistent feedback monitoring Cognitive flexibility, the ability to alter ones strategy according to changing stimulus-response-reward relationships, is critical for acquiring and updating learned behavior. Attentional set-shifting, a test of cognitive flexibility, depends on the activity of prefrontal cortex (PFC). It remains unclear, however, what specific role PFC neurons play and how they interact to support set-shifting. One widely held view is that prefrontal activity biases sensorimotor responses by mediating attention. Using optogenetics and 2-photon calcium imaging, we demonstrate that, while PFC activity does encode attentional sets, this activity does not bias sensorimotor responses. Rather, PFC activity enables set-shifting by encoding trial feedback information, a role it has been known to play in other contexts. We identify a circuit-level mechanism that supports feedback monitoring through persistent, recurring activity bridging multiple trials. Unexpectedly, the functional properties of PFC cells did not vary with their efferent projection targets in this context. Instead, representations of trial feedback formed a topological gradient, with cells more strongly selective for feedback information located further from the pial surface and receiving denser afferent inputs from the anterior cingulate cortex. Together, these findings identify a critical role for deep PFC projection neurons in enabling set-shifting through behavioral feedback monitoring. | neuroscience |
Dietary fat promotes antibiotic-induced Clostridioides difficile mortality in mice Clostridioides difficile infection (CDI), is the leading cause of hospital-acquired diarrhea and emerging evidence has linked dietary components with CDI pathogenesis, suggesting that dietary modulation may be an effective strategy for prevention. Here, we show that mice fed a high-fat/low-fiber "Western type" diet (WD) had dramatically increased mortality in a murine model of antibiotic-induced CDI compared to a low-fat/low-fiber (LF/LF) diet and standard mouse chow controls. We found that the WD had a pro- C. difficile bile acid composition that was driven in part by higher levels of primary bile acids that are produced to digest fat, and a lower level of secondary bile acids that are produced by the gut microbiome. This lack of secondary bile acids was associated with a greater disturbance to the gut microbiome with antibiotics in both the WD and LF/LF diet compared to mouse chow. Mice fed the WD also had the highest level of toxin TcdA just prior to the onset of mortality, but not of TcdB or increased inflammation. These findings indicate that dietary intervention to decrease fat may complement previously proposed dietary intervention strategies to prevent CDI in high-risk individuals.
One Sentence SummaryA high-fat/low-fiber Western type diet promoted mortality in a mouse model of antibiotic-induced C. difficile infection compared to a low-fat/low-fiber diet and chow diet, suggesting that lower dietary fat may be an effective strategy for preventing C. difficile pathology. | microbiology |
Automaticity in the reading circuitry Skilled reading requires years of practice associating visual symbols with speech sounds. Over the course of the learning process, this association becomes effortless and automatic. Here we test whether automatic activation of spoken-language circuits in response to visual words is a hallmark of skilled reading. Magnetoencephalography was used to measure word-selective responses under multiple cognitive tasks (N = 42, 7-12 years of age). Even when attention was drawn away from the words by performing an attention-demanding fixation task, strong word-selective responses were found in a language region (i.e., superior temporal gyrus) starting at ~300 ms after stimulus onset. Critically, this automatic word-selective response was indicative of reading skill: the magnitude of word-selective responses correlated with individual reading skill. Our results suggest that automatic recruitment of spoken-language circuits is a hallmark of skilled reading; with practice, reading becomes effortless as the brain learns to automatically translate letters into sounds and meaning. | neuroscience |
Towards Practical and Robust DNA-based Data Archiving Using "Yin-Yang Codec" System DNA is a promising data storage medium due to its remarkable durability and space-efficient storage. Early bit-to-base transcoding schemes have primarily pursued information density, at the expense however of introducing biocompatibility challenges or at the risk of decoding failure. Here, we propose a robust transcoding algorithm named the "Yin-Yang Codec" (YYC), using two rules to encode two binary bits into one nucleotide, to generate DNA sequences highly compatible with synthesis and sequencing technologies. We encoded two representative file formats and stored them in vitro as 200-nt oligo pools and in vivo as an ~54-kb DNA fragment in yeast cells. Sequencing results show that YYC exhibits high robustness and reliability for a wide variety of data types, with an average recovery rate of 99.94% at 104 molecule copies and an achieved recovery rate of 87.53% at 100 copies. In addition, the in vivo storage demonstration achieved for the first time an experimentally measured physical information density of 198.8 EB per gram of DNA (44% of the theoretical maximum for DNA). | synthetic biology |
Mutations in Auxilin cause parkinsonism via impaired clathrin-mediated trafficking at the Golgi apparatus and synapse Parkinsons disease (PD) is a common neurodegenerative motor disorder characterized in part by neuropathological lesions in the nigrostriatal pathway. Loss of function mutations in Auxilin, the major neuronal clathrin uncoating protein, cause an aggressive form of juvenile onset PD. How mutations in Auxilin cause PD, is currently not understood. Here, we generated a novel mouse model carrying an endogenous pathogenic Auxilin mutation that phenocopies neurological features observed in patients, including motor impairments and seizures. Unbiased mapping of the Auxilin interactome identified synaptic and Golgi-resident clathrin adaptor proteins as novel interactors. Impaired clathrin-mediated trafficking in mutant Auxilin mice, both at the Golgi and the synapse, results in neuropathological lesions in the nigrostriatal pathway. Collectively, these results provide molecular mechanisms of PD pathogenesis in Auxilin mutation carriers, reinforcing a key role for clathrin-mediated trafficking in PD, and expand our understanding of the cellular function of Auxilin. | neuroscience |
Genomic Background Governs Opposing Responses to Nalidixic Acid Upon Megaplasmid Acquisition in Pseudomonas Horizontal gene transfer is a significant driver of evolutionary dynamics across microbial populations. Although the benefits of the acquisition of new genetic material are often quite clear, experiments across systems have demonstrated that gene transfer events can cause significant phenotypic changes and entail fitness costs in a way that is dependent on the genomic and environmental context. Here we test for the generality of one previously identified cost, sensitization of cells to the antibiotic nalidixic acid after acquisition of a [~]1Mb megaplasmid, across Pseudomonas strains and species. Overall, we find that the presence of this megaplasmid sensitizes many different Pseudomonas strains to nalidixic acid, but that this same horizontal gene transfer event increases resistance of Pseudomonas putida KT2440 to nalidixic acid across assays as well as to ciprofloxacin under competitive conditions. These phenotypic results are not easily explained away as secondary consequences of overall fitness effects and appear to occur independently of another cost associated with this megaplasmid, sensitization to higher temperatures. Lastly, we draw parallels between these reported results and the phenomenon of sign epistasis for de novo mutations and explore how context dependence of effects of plasmid acquisition could impact overall evolutionary dynamics and the evolution of antimicrobial resistance.
ImportanceNumerous studies have demonstrated that gene transfer events (e.g. plasmid acquisition) can entail a variety of costs that arise as byproducts of the incorporation of foreign DNA into established physiological and genetic systems. These costs can be ameliorated through evolutionary time by the occurrence of compensatory mutations, which stabilize presence of a horizontally transferred region within the genome but which also may skew future adaptive possibilities for these lineages. Here we demonstrate another possible outcome, that phenotypic changes arising as a consequence of the same horizontal gene transfer event are costly to some strains but may actually be beneficial in other genomic backgrounds under the right conditions. These results provide new a new viewpoint for considering conditions that promote plasmid maintenance and highlight the influence of genomic and environmental contexts when considering amelioration of fitness costs after HGT events. | microbiology |
Attenuated directed exploration during reinforcement learning in gambling disorder Gambling disorder is a behavioral addiction associated with impairments in value-based decision-making and behavioral flexibility and might be linked to changes in the dopamine system. Maximizing long-term rewards requires a flexible trade-off between the exploitation of known options and the exploration of novel options for information gain. This exploration-exploitation trade-off is thought to depend on dopamine neurotransmission. We hypothesized that human gamblers would show a reduction in directed (uncertainty-based) exploration, accompanied by changes in brain activity in a fronto-parietal exploration-related network.
Twenty-three frequent, non-treatment seeking gamblers and twenty-three healthy matched controls (all male) performed a four-armed bandit task during functional magnetic resonance-imaging. Computational modeling using hierarchical Bayesian parameter estimation revealed signatures of directed exploration, random exploration, and perseveration in both groups. Gamblers showed a reduction in directed exploration, whereas random exploration and perseveration were similar between groups.
Neuroimaging revealed no evidence for group differences in neural representations of basic task variables (expected value, prediction errors). Our hypothesis of reduced frontal pole recruitment in gamblers was not supported. Exploratory analyses revealed that during directed exploration, gamblers showed reduced parietal cortex and substantia-nigra / ventral-tegmental-area activity. Cross-validated classification analyses revealed that connectivity in an exploration-related network was predictive of group status, suggesting that connectivity patterns might be more predictive of problem gambling than univariate effects.
Findings reveal specific reductions in strategic exploration gamblers that might be linked to altered processing in a fronto-parietal network and/or changes in dopamine neurotransmission implicated in gambling disorder.
Significance statementWiehler et al. report that gamblers rely less on the strategic exploration of unknown, but potentially better rewards during reward learning. This is reflected in a related network of brain activity. Parameters of this network can be used to predict the presence of problem gambling behavior in participants. | neuroscience |
LiGIoNs: A Computational Method for the Detection and Classification of Ligand-Gated Ion Channels Ligand-Gated Ion Channels (LGICs) are one of the largest groups of transmembrane proteins. Due to their major role in synaptic transmission, both in the nervous system and the somatic neuromuscular junction, LGICs present attractive therapeutic targets. During the last few years several computational methods for the detection of LGICs have been developed. These methods are based on machine learning approaches utilizing features extracted solely from amino acid composition. Here we report the development of LiGIoNs, a profile Hidden Markov Model (pHMM) method for the prediction and ligand-based classification of LGICs. The method consists of a library of 10 pHMMs, one per LGIC subfamily, built from the alignment of representative LGIC sequences. In addition, 14 Pfam pHMMs are used to further annotate and classify unknown protein sequences into one of the 10 LGIC subfamilies. Evaluation of the method showed that it outperforms existent methods in the detection of LGICs. On top of that, LiGIoNs is the only currently available method that classifies LGICs into subfamilies.
The method is available online at http://bioinformatics.biol.uoa.gr/ligions/. | bioinformatics |
Blinking Statistics and Molecular Counting in direct Stochastic Reconstruction Microscopy (dSTORM) MotivationMany recent advancements in single molecule localisation microscopy exploit the stochastic photo-switching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation.
ResultsModelling the photo-switching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localisations from a single photo-switching fluorophore. This is then extended to provide the probability distribution for the number of localisations in a dSTORM experiment involving an arbitrary number of molecules. We demonstrate that when training data is available to estimate photo-switching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localisations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein Linker for Activation of T cells (LAT) on the cell surface of the T cell immunological synapse.
AvailabilitySoftware available at https://github.com/lp1611/mol_count_dstorm. | biophysics |
Linear B-cell epitope prediction for in silico vaccine design: a performance review of methods available via command-line interface Linear B-cell epitope prediction research has received a steadily growing interest ever since the first method was developed in 1981. B-cell epitope identification with the help of an accurate prediction method can lead to an overall faster and cheaper vaccine design process, a crucial necessity in the covid-19 era. Consequently, several B-cell epitope prediction methods have been developed over the past few decades, but without significant success. In this study, we review the current performance and methodology of some of the most widely used linear B-cell epitope predictors which are available via a command-line interface, namely BcePred, BepiPred, ABCpred, COBEpro, SVMTriP, LBtope, and LBEEP. Additionally, we attempted to remedy performance issues of the individual methods by developing a consensus classifier, which combines the separate predictions of these methods into a single output, accelerating the epitope-based vaccine design. While the method comparison was performed with some necessary caveats and individual methods might perform much better for specialized datasets, we hope that this update in performance can aid researchers towards the choice of a predictor, for the development of biomedical applications such as designed vaccines, diagnostic kits, immunotherapeutics, immunodiagnostic tests, antibody production, and disease diagnosis and therapy. | bioinformatics |
Matrix Inversion and Subset Selection (MISS): A novel pipeline for quantitative mapping of diverse cell types across the murine brain The advent of increasingly sophisticated imaging platforms has allowed for the visualization of the murine nervous system at single-cell resolution. However, current experimental approaches have not yet produced whole-brain maps of a comprehensive set of neuronal and nonneuronal types that approaches the cellular diversity of the mammalian cortex. Here we aim to fill in this gap in knowledge with an open-source computational pipeline, Matrix Inversion with Subset Selection (MISS), that can infer quantitatively validated distributions of diverse collections of neural cell types at 200m resolution using a combination of single-cell RNAseq and in situ hybridization datasets. We rigorously demonstrate the accuracy of MISS against literature expectations. Importantly, we show that gene subset selection, a procedure by which we filter out low-information genes prior to performing deconvolution, is a critical pre-processing step that distinguishes MISS from its predecessors and facilitates the production of cell type maps with significantly higher accuracy. We also show that MISS is generalizable by generating high-quality cell type maps from a second, independently curated single-cell RNAseq dataset. Together, our results illustrate the viability of computational approaches for determining the spatial distributions of a wide variety of cell types from genetic data alone. | neuroscience |
Estradiol-induced progesterone synthesis develops post-puberty in the rostral hypothalamus and coincides with post-pubertal changes in the steroidogenic pathway in female mouse hypothalamic astrocytes The development of estrogen positive feedback is a hallmark of female puberty. Both estrogen and progesterone signaling are required for the functioning of this neuroendocrine feedback loop but the physiological changes that underlie the emergence of positive feedback remain unknown. Only after puberty does estradiol (E2) facilitate progesterone synthesis in the rat female hypothalamus (neuroP), an event critical for positive feedback and the LH surge. We hypothesize that prior to puberty, these astrocytes have low levels of membrane estrogen receptor alpha (ER), which is needed for facilitation of neuroP synthesis. Thus, we hypothesized that prepubertal astrocytes are unable to respond to E2 with increased neuroP synthesis due a lack of membrane ER. To test this, hypothalamic tissues and enriched primary hypothalamic astrocyte cultures were acquired from pre-pubertal (postnatal week 3) and post- pubertal (week 8) female mice. E2-facilitated progesterone was measured in the hypothalamus pre- and post-puberty, and hypothalamic astrocyte responses were measured after treatment with E2. Prior to puberty, E2-facilitated progesterone synthesis did not occur in the hypothalamus, and mER expression was low in hypothalamic astrocytes, but E2-facilitated progesterone synthesis in the rostral hypothalamus and mER expression increased post- puberty. The increase in mER expression in hypothalamic astrocytes corresponded with an increase in caveolin-1 protein, PKA phosphorylation, and a more rapid [Ca2+]i flux in response to E2. Together, results from the present study indicate that E2-facilitated neuroP synthesis occurs in the rostral hypothalamus, develops during puberty, and corresponds to a post-pubertal increase in mER levels in hypothalamic astrocytes.
SIGNIFICANCE STATEMENTEstradiol facilitation of hypothalamic neuroprogesterone synthesis is necessary for the positive feedback of the LH surge. The present study localized the increase of neuroprogesterone to the rostral hypothalamus, a region that mediates estrogen positive feedback. Across pubertal development, hypothalamic astrocytes increase levels of membrane ER and the cell signaling responses needed to facilitate neuroprogesterone synthesis that triggers the LH surge demonstrating a mechanism for pubertal maturation resulting in reproductive competence. | neuroscience |
Unravelling the genetic architecture of musical rhythm: a large-scale genome-wide association study of beat synchronization Moving in synchrony to the beat is a fundamental component of musicality. Here, we conducted a genome-wide association study (GWAS) to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with sixty-nine loci reaching genome-wide significance (p<5x10-8) and SNP-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues, and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central nervous system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through internet-based experiments) and of the GWAS (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed, and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations. | genetics |
Integrative nascent RNA methods to reveal cell-type specific transcription programs in peripheral blood and its derivative cells Nascent RNA sequencing is a powerful method to measure transcription with high resolution, sensitivity, and directional information, which gives distinctive information about transcription from other methods such as chromatin immunoprecipitation or mRNA sequencing. We present an integrated package of nascent RNA-seq methods - ultrafast Precision Run On (uPRO) combined with computational procedures to discover cell type specific enhancers, promoters, and transcription factor networks. uPRO is composed of adaptor ligation and reverse transcription reactions, which is reduced to a one-day procedure and makes nascent RNA-seq more feasible and flexible for a widespread use. We generated genome-wide profiles of nascent transcription in human blood derived cell lines and clinical samples of ~1 ml of untreated whole blood. We integrated these data into deep learning and hierarchical network analysis to detect enhancers, promoters, and co-expression networks to define cell-type specific transcription programs. We found conservation of position but variation of expression in cell type specific enhancers and transcription start sites. Transcription factors (TFs) such as TCF-3 and OCT1 were pivotally associated with TF-enhancer-gene networks across cell types. Intriguingly, we also discovered that TFs related to cell stress and inflammation - such as SRF, ATF, CHOP, and NF-kB - are associated with inter-individual variation of leukocyte transcription in whole blood. Our integration of experimental and computational nascent RNA methods will provide an efficient strategy to identify specific transcriptional programs, both in cell-type and patient/disease-associated, with minimal sample requirements. | molecular biology |
Temperature predicts the maximum tree-species richness and water and frost shape the residual variation The kinetic hypothesis of biodiversity proposes that temperature is the main driver of variation in species richness, given its exponential effect on biological activity and, potentially, on rates of diversification. However, limited support for this hypothesis has been found to date. I tested the fit of this model on the variation of tree-species richness along a continuous latitudinal gradient in the Americas. I found that the kinetic hypothesis accurately predicts the upper bound of the relationship between the inverse of mean annual temperature (1/kK) and the natural logarithm of species richness, at a broad scale. In addition, I found that water availability and the number of days with freezing temperatures organize a part of the residual variation of the upper bound model. The finding of the model fitting on the upper bound rather than on the mean values suggest that the kinetic hypothesis is modeling the variation of the potential maximum species richness per unit of temperature. Likewise, the distribution of the residuals of the upper bound model in function of the number of days with freezing temperatures suggest the importance of environmental thresholds rather than gradual variation driving the observable variation in species richness. | ecology |
Trading Mental Effort for Confidence in the Metacognitive Control of Value-Based Decision-Making Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, and choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings. | neuroscience |
A multi-measure approach for assessing the performance of fMRI preprocessing strategies in resting-state functional connectivity It is well established that head motion and physiological processes (e.g. cardiac and breathing activity) should be taken into consideration when analyzing and interpreting results in fMRI studies. However, even though recent studies aimed to evaluate the performance of different preprocessing pipelines there is still no consensus on the optimal strategy. This is partly due to the fact that the quality control (QC) metrics used to evaluate differences in performance across pipelines have often yielded contradictory results. Furthermore, preprocessing techniques based on physiological recordings or data decomposition techniques (e.g. aCompCor) have not been comprehensively examined. Here, to address the aforementioned issues, we propose a framework that summarizes the scores from eight previously proposed and novel QC metrics to a reduced set of two QC metrics that reflect the signal-to-noise ratio and the reduction in motion artifacts and biases in the preprocessed fMRI data. Using this framework, we evaluate the performance of three commonly used practices on the quality of data: 1) Removal of nuisance regressors from fMRI data, 2) discarding motion-contaminated volumes (i.e., scrubbing) before regression, and 3) low-pass filtering the data and the nuisance regressors before their removal. Using resting-state fMRI data from the Human Connectome Project, we show that the scores of the examined QC metrics improve the most when the global signal (GS) and about 17% of principal components from white matter (WM) are removed from the data. Finally, we observe a small further improvement with low-pass filtering at 0.20 Hz and milder variants of WM denoising, but not with scrubbing. | neuroscience |
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient BackgroundThe last decade has seen a major increase in the availability of genomic data. This includes expert-curated databases that describe the biological activity of genes, as well as high-throughput assays that measure gene expression in bulk tissue and single cells. Integrating these heterogeneous data sources can generate new hypotheses about biological systems. Our primary objective is to combine population-level drug-response data with patient-level single-cell expression data to predict how any gene will respond to any drug for any patient.
MethodsWe take 2 approaches to benchmarking a "dual-channel" random walk with restart (RWR) for data integration. First, we evaluate how well RWR can predict known gene functions from single-cell gene co-expression networks. Second, we evaluate how well RWR can predict known drug responses from individual cell networks. We then present two exploratory applications. In the first application, we combine the Gene Ontology database with glioblastoma single cells from 5 individual patients to identify genes whose functions differ between cancers. In the second application, we combine the LINCS drug-response database with the same glioblastoma data to identify genes that may exhibit patient-specific drug responses.
ConclusionsOur manuscript introduces two innovations to the integration of heterogeneous biological data. First, we use a "dual-channel" method to predict up-regulation and down-regulation separately. Second, we use individualized single-cell gene co-expression networks to make personalized predictions. These innovations let us predict gene function and drug response for individual patients. Taken together, our work shows promise that single-cell co-expression data could be combined in heterogeneous information networks to facilitate precision medicine. | systems biology |
PharmOmics: A Species- and Tissue-specific Drug Signature Database and Online Tool for Drug Repurposing Drug development has been hampered by a high failure rate in clinical trials due to efficacy or safety issues not predicted by preclinical studies in model systems. A key contributor is our incomplete understanding of drug functions across organ systems and species. Therefore, elucidating species- and tissue-specific actions of drugs can provide systems level insights into therapeutic efficacy, potential adverse effects, and interspecies differences that are necessary for more effective translational medicine. Here, we present a comprehensive drug knowledgebase and analytical tool, PharmOmics, comprised of genomic footprints of drugs in individual tissues from human, mouse, and rat transcriptome data from GEO, ArrayExpress, TG-GATEs, and DrugMatrix. Using multi-species and multi-tissue gene expression signatures as molecular indicators of drug functions, we developed gene network-based approaches for drug repositioning. We demonstrate the potential of PharmOmics to predict drugs for new disease indications and validated two predicted drugs for non-alcoholic fatty liver disease in mice. We also examined the potential of PharmOmics to identify drugs related to hepatoxicity and nephrotoxicity. By combining tissue- and species-specific in vivo drug signatures with biological networks, PharmOmics serves as a complementary tool to support drug characterization. | systems biology |
A small-molecule antagonist for the Tudor domain of SMN disrupts the interaction between SMN and RNAP II Survival of motor neuron (SMN), a Tudor-domain-containing protein, plays an important role in diverse biological pathways via recognition of symmetrically dimethylated arginine (Rme2s) on proteins by its Tudor domain, and deficiency of SMN leads to the motor neuron degenerative disease spinal muscular atrophy (SMA). Here we report a potent and selective antagonist with a 4-iminopyridine scaffold targeting the Tudor domain of SMN. Our structural and mutagenesis studies indicate that the sandwich stacking interactions of SMN and compound 1 play a critical role in selective binding to SMN. Various on-target engagement assays support that compound 1 recognizes SMN specifically in a cellular context. In cell studies display that the SMN antagonist prevent the interaction of SMN with R1810me2s of DNA-directed RNA polymerase II subunit POLR2A and results in transcription termination and R-loop accumulation, mimicking depletion of SMN. Thus, in addition to the antisense, RNAi and CRISPR/Cas9 techniques, the potent SMN antagonist could be used as an efficient tool in understanding the biological functions of SMN and molecular etiology in SMA. | biochemistry |
Interrogating theoretical models of neural computation with emergent property inference 1A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon - whether behavioral or a pattern of neural activity - and thus can offer insights into neural computation. The operation of these circuits, like all models, critically depends on the choice of model parameters. A key step is then to identify the model parameters consistent with observed phenomena: to solve the inverse problem. In this work, we present a novel technique, emergent property inference (EPI), that brings the modern probabilistic modeling toolkit to theoretical neuroscience. When theorizing circuit models, theoreticians predominantly focus on reproducing computational properties rather than a particular dataset. Our method uses deep neural networks to learn parameter distributions with these computational properties. This methodology is introduced through a motivational example inferring conductance parameters in a circuit model of the stomatogastric ganglion. Then, with recurrent neural networks of increasing size, we show that EPI allows precise control over the behavior of inferred parameters, and that EPI scales better in parameter dimension than alternative techniques. In the remainder of this work, we present novel theoretical findings gained through the examination of complex parametric structure captured by EPI. In a model of primary visual cortex, we discovered how connectivity with multiple inhibitory subtypes shapes variability in the excitatory population. Finally, in a model of superior colliculus, we identified and characterized two distinct regimes of connectivity that facilitate switching between opposite tasks amidst interleaved trials, characterized each regime via insights afforded by EPI, and found conditions where these circuit models reproduce results from optogenetic silencing experiments. Beyond its scientific contribution, this work illustrates the variety of analyses possible once deep learning is harnessed towards solving theoretical inverse problems. | neuroscience |
Metabolic signatures of regulation by phosphorylation and acetylation Acetylation and phosphorylation are highly conserved post-translational modifications (PTMs) that regulate cellular metabolism, yet how metabolic control is shared between these PTMs is unknown. Here we analyze transcriptome, proteome, acetylome, and phosphoproteome datasets in E.coli, S.cerevisiae, and mammalian cells across diverse conditions using CAROM, a new approach that uses genome-scale metabolic networks and machine-learning to classify regulation by PTMs. We built a single machine-learning model that accurately distinguished reactions controlled by each PTM in a condition across all three organisms based on reaction attributes (AUC>0.8). Our model uncovered enzymes regulated by phosphorylation during a mammalian cell-cycle, which we validate using phosphoproteomics. Interpreting the machine-learning model using game-theory uncovered enzyme properties including network connectivity, essentiality, and condition-specific factors such as maximum flux that differentiate regulation by phosphorylation from acetylation. The conserved and predictable partitioning of metabolic regulation identified here between these PTMs can enable rational engineering of regulatory circuits.
Graphical Abstract
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/838243v2_ufig1.gif" ALT="Figure 1">
View larger version (37K):
[email protected]@d1fd3borg.highwire.dtl.DTLVardef@4852ddorg.highwire.dtl.DTLVardef@383bb9_HPS_FORMAT_FIGEXP M_FIG C_FIG | systems biology |
ERBB2 is a Key Mediator in Hearing Restoration in Noise-Deafened Young Adult Mice Noise-induced hearing loss (NIHL) affects over ten million adults in the United States, and has no biological treatment. We hypothesized that activation of signaling from ERBB2 receptors in cochlear supporting cells could mitigate cochlear damage. We adopted a new timeline for assessing mitigation that parallels hearing recovery from damage in avians. We drove expression of a constitutively active variant of ERBB2 (CA-ERBB2) in cochlear supporting cells three days after permanent noise damage in young adult mice. Between 100-200 supporting cells in the apical cochlea expressed a lineage marker, indicating competence to express CA-ERBB2. Hearing thresholds were assessed with auditory brainstem response tests, and hearing recovery was assessed over a ninety-day period. Mice harboring CA-ERBB2 capability had similar hearing thresholds to control littermates prior to noise exposure, immediately after, and 30-days after. Sixty and ninety days after noise exposure, CA-ERBB2+ mice demonstrated a partial but significant reversal of NIHL threshold shifts at one in five frequencies tested, which was in the region of CA-ERBB2 expression. We evaluated inner and outer hair cell (IHC and OHC) survival, synaptic preservation, stereociliary morphology, and IHC cytoskeletal alterations with histological techniques. Improved IHC and OHC survival were observed in the basal cochlea. No differences were seen in synaptic numbers or IHC cytoskeletal alterations, but more stereocilia may have been preserved. These data indicate, for the first time, that ERBB2 signaling in supporting cells can promote hair cell survival and partial functional recovery, and that permanent threshold shifts from noise may be partially reversed in mice. | neuroscience |
Privacy-preserving quality control of neuroimaging datasets in federated environments Privacy concerns for rare disease data, institutional or IRB policies, access to local computational or storage resources or download capabilities are among the reasons that may preclude analyses that pool data to a single site. A growing number of multi-site projects and consortia were formed to function in the federated environment to conduct productive research under constraints of this kind. In this scenario, a quality control tool that visualizes decentralized data in its entirety via global aggregation of local computations is especially important, as it would allow the screening of samples that cannot be jointly evaluated otherwise. To solve this issue, we present two algorithms: decentralized data stochastic neighbor embedding, dSNE, and its differentially private counterpart, DP-dSNE. We leverage publicly available datasets to simultaneously map data samples located at different sites according to their similarities. Even though the data never leaves the individual sites, dSNE does not provide any formal privacy guarantees. To overcome that, we rely on differential privacy: a formal mathematical guarantee that protects individuals from being identified as contributors to a dataset. We implement DP-dSNE with AdaCliP, a method recently proposed to add less noise to the gradients per iteration. We introduce metrics for measuring the embedding quality and validate our algorithms on these metrics against their centralized counterpart on two toy datasets. Our validation on six multi-site neuroimaging datasets shows promising results for the quality control tasks of visualization and outlier detection, highlighting the potential of our private, decentralized visualization approach. | neuroscience |
Long-term warming effects on the microbiome and nitrogen fixation of a common moss species in sub-Arctic tundra O_LIBacterial communities form the basis of biogeochemical processes and determine plant growth and health. Mosses, an abundant plant group in Arctic ecosystems, harbour diverse bacterial communities that are involved in nitrogen fixation and carbon cycling. Global climate change is causing changes in aboveground plant biomass and shifting species composition in the Arctic, but little is known about the response of moss microbiomes.
C_LIO_LIHere, we studied the total and potentially active bacterial community associated with Racomitrium lanuginosum, in response to 20-year in situ warming in an Icelandic heathland. We evaluated the effect of warming and warming-induced shrub expansion on the moss bacterial community composition and diversity, nifH gene abundance and nitrogen-fixation rates.
C_LIO_LIWarming changed both the total and the potentially active bacterial community structure, while litter abundance only affected the total bacterial community structure. The relative abundance of Proteobacteria increased, while the relative abundance of Cyanobacteria and Acidobacteria decreased. NifH gene abundance and nitrogen-fixation rates were negatively affected by litter and Betula nana abundance, respectively. We also found shifts in the potentially nitrogen-fixing community, with Nostoc decreasing and non-cyanobacterial diazotrophs increasing in relative abundance. Our data suggests that the moss microbial community including the potentially nitrogen-fixing taxa is sensitive to future warming.
C_LIO_LISynthesis. Long-term warming led to a shift in moss-associated bacterial community composition, while the abundance of nitrogen-fixing bacteria and nitrogen-fixation rates were negatively affected by increased litter and Betula nana abundance respectively. Warming and increased shrub abundance as a result of warming can affect moss-associated bacterial communities and nitrogen fixation rates in tundra ecosystems.
C_LI | microbiology |
How to characterise shared space use networks Studying the social behaviour of small or cryptic species often relies on constructing shared space use networks from sparse point-based observations of individuals (e.g. live trapping data). Such an approach assumes that individuals that have more observed space sharing events (e.g. detections in the same trapping location) will also have interacted more. However, there is very little guidance on how to construct shared space use networks, how much data are required for making such networks, or how to interpret the relationships they generate. In this study, we quantify the robustness of shared space use networks to different sampling regimes and network-generation algorithms. We first use empirical data to highlight that characteristics of how animals use space can help us to establish new ways to model the potential for individuals to co-occur. We then show that a method that explicitly models individuals home range and subsequent overlap in space among individuals (spatial overlap networks) requires fewer data for inferring observed networks that are correlated with the true shared space use network (relative to networks constructed from space sharing events). As a result, we show that shared space use networks based on estimating spatial overlap are also more powerful for detecting biological effects present in the true shared space use network. Finally, we discuss when it is appropriate to make inferences from shared space use about social interactions. Our study confirms the potential for using sparse trapping data from cryptic species to address a range of important questions in ecology and evolution. | ecology |
The minimum land area requiring conservation attention to safeguard biodiversity More ambitious conservation efforts are needed to stop the global biodiversity crisis. Here, we estimate the minimum land area to secure important sites for terrestrial fauna, ecologically intact areas, and the optimal locations for representation of species ranges and ecoregions. We discover that at least 64 million km2 (44% of terrestrial area) requires conservation attention. Over 1.8 billion people live on these lands so responses that promote agency, self-determination, equity, and sustainable management for safeguarding biodiversity are essential. Spatially explicit land-use scenarios suggest that 1.3 million km2 of land requiring conservation could be lost to intensive human land-uses by 2030, which requires immediate attention. However, there is a seven-fold difference between the amount of habitat converted under optimistic and pessimistic scenarios, highlighting an opportunity to avert this crisis. Appropriate targets in the post-2020 Global Biodiversity Framework to ensure conservation of the identified land would contribute substantially to safeguarding biodiversity. | ecology |
Astrocyte-like glia-specific gene deathstar is crucial for normal development, adult locomotion and lifespan of male Drosophila Drosophila melanogaster is a proper model organism for studying the development and function of the nervous system. The Drosophila nervous system consists of distinct cell types with significant homologies to various cell types of more advanced organisms, including human. Among all cell types of the nervous system, astrocyte-like glia (ALG) have conserved functions to mammals and are essential for normal physiology and behaviours of the fly.
In this study, we exploited the gene expression profile of single cells in Drosophila optic lobe to identify the genes with specific expression pattern in each cell type. Through a bioinformatical analysis of the data, a novel ALG-specific gene (here assigned as deathstar, dea) was identified. Immunostaining of deathstar in the central nervous system (CNS) showed its presence in specific regions of Drosophila ventral nerve cord, which previously has been characterized as ALG cells. Consistent with the bioinformatical analysis, deathstar-related signals were overlapped with the signals of the previously reported ALG marker, Eaat1, supporting its specific expression in ALG cells.
At the physiological level, RNAi-mediated suppression of deathstar gene impeded the normal development of male flies without any effects on females. Cell type-specific expression of deathstar RNAi showed that deathstar gene affects locomotion behaviour and lifespan of D. melanogaster, in an ALG-specific manner.
Taken together, we showed that bioinformatical analysis of a previously reported expression data of Drosophila optic lobe successfully predicted the ALG-specific expression pattern of deathstar gene. Moreover, it was consistent with the ALG-specific effects of this gene on locomotion and lifespan of D. melanogaster, in vivo. | genetics |
Mesmerize: a dynamically adaptable user-friendly analysis platform for 2D & 3D calcium imaging data. Calcium imaging is an increasingly valuable technique for understanding neural circuits, neuroethology, and cellular mechanisms. The analysis of calcium imaging data presents challenges in image processing, data organization, analysis, and accessibility. Tools have been created to address these problems independently, however a comprehensive user-friendly package does not exist. Here we present "Mesmerize", an efficient, expandable and user-friendly analysis platform, which uses a Findable, Accessible, Interoperable and Reproducible (FAIR) system to encapsulate the entire analysis process, from raw data to interactive visualizations for publication. Mesmerize provides a user-friendly graphical interface to state-of-the-art analysis methods for signal extraction & downstream analysis. We demonstrate the broad scientific scope of Mesmerizes applications by analyzing neuronal datasets from mouse and a volumetric zebrafish dataset. We also applied contemporary time-series analysis techniques to analyze a novel dataset comprising neuronal, epidermal, and migratory mesenchymal cells of the protochordate Ciona intestinalis. | neuroscience |
Targeting cellular DNA damage responses in cancer: An in vitro-calibrated agent-based model simulating monolayer and spheroid treatment responses to ATR-inhibiting drugs We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia telangiectasia mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately eight days post tumour injection.
Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development. | cancer biology |
Characterising sensorimotor adaptation in Complex Regional Pain Syndrome It has been suggested that sensorimotor conflict contributes to the maintenance of some pathological pain conditions, implying that there are problems with the adaptation processes that normally resolve such conflict. We tested whether sensorimotor adaptation is impaired in people with Complex Regional Pain Syndrome (CRPS) by characterising their adaption to lateral prismatic shifts in vision. People with unilateral upper-limb CRPS Type I (n = 17), and pain-free individuals (n = 18; matched for age, sex, and handedness) completed prism adaptation with their affected/non-dominant and non-affected/dominant arms. We examined 1) the rate at which participants compensated for the optical shift during prism exposure (i.e. strategic recalibration), 2) endpoint errors made directly after prism adaptation (sensorimotor realignment) and the retention of these errors, and 3) kinematic markers associated with strategic control. Direct comparisons between people with CRPS and controls revealed no evidence of any differences in strategic recalibration, including no evidence for differences in a kinematic marker associated with trial-by-trial changes in movement plans during prism exposure. All participants made significant endpoint errors after prism adaptation exposure, indicative of sensorimotor realignment. Overall, the magnitude of this realignment did not differ between people with CRPS and pain-free controls. However, when endpoint errors were considered separately for each hand, people with CRPS made greater errors (indicating more rather than less realignment) when using their affected hand than their non-affected hand. No such difference was seen in controls. Taken together, these findings provide no evidence of impaired strategic control or sensorimotor realignment in people with CRPS. In contrast, they provide some indication that there could be a greater propensity for sensorimotor realignment in the CRPS-affected arm, consistent with more flexible representations of the body and peripersonal space. Our study challenges an implicit assumption of the theory that sensorimotor conflict might underlie some pathological pain conditions. | neuroscience |
The genome of the zoonotic malaria parasite Plasmodium simium reveals adaptations to host-switching BackgroundPlasmodium simium, a malaria parasite of non-human primates (NHP) was recently shown to cause zoonotic infections in humans in Brazil. We sequenced the P. simium genome to investigate its evolutionary history and to identify any genetic adaptions that may underlie the ability of this parasite to switch between host species.
ResultsPhylogenetic analyses based on whole genome sequences of P. simium from humans and NHPs reveals that P. simium is monophyletic within the broader diversity of South American Plasmodium vivax, suggesting P. simium first infected NHPs as a result of a host-switch of P. vivax from humans. The P. simium isolates show the closest relationship to Mexican P. vivax isolates. Analysis of erythrocyte invasion genes reveals differences between P. vivax and P. simium, including large deletions in the Duffy Binding Protein 1 (DBP1) and Reticulocyte Binding Protein 2a genes of P. simium. Analysis of P. simium isolated from NHPs and humans revealed a deletion of 38 amino acids in DBP1 present in all human-derived isolates, whereas NHP isolates were multi-allelic.
ConclusionsAnalysis of the P. simium genome confirmed a close phylogenetic relationship between P. simium and P. vivax, and suggests a very recent American origin for P. simium. The presence of the DBP1 deletion in all human-derived isolates tested suggests that this deletion, in combination with other genetic changes in P. simium, may facilitate the invasion of human red blood cells and may explain, at least in part, the basis of the recent zoonotic infections. | genomics |
Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative syndrome of the human motor neuron system, for which no effective treatment exists. Variability in the rate of disease progression limits the efficacy of ALS clinical trials, suggesting that developing of better biomarkers for prognosis will facilitate therapeutic progress. Here, we applied unbiased next-generation sequencing to investigate the potential of plasma cell-free microRNAs as biomarkers of ALS prognosis, in 252 patients with detailed clinical-phenotyping. First, we identified miRNAs, whose plasma levels remain stable over the course of disease in a longitudinal cohort of 22 patients. Next, we demonstrated that high levels of miR-181, a miRNA enriched in neurons of the brain and spinal cord, predicts a >2 fold risk of death in discovery cohort (126 patients) and an independent replication cohort (additional 122 patients). miR-181 performance is comparable with the established neurofilament light chain (NfL) biomarker and when combined together, miR-181+NfL establish a novel RNA-protein biomarker pair with superior prediction capacity of ALS prognosis. Therefore, plasma miR-181 predicts ALS disease course, and a novel miRNA-protein biomarker approach, based on miR-181+NfL, boosts precision of patient stratification and may greatly enhance the power of clinical trials.
One Sentence Summaryplasma miR-181 levels indicate high mortality risk in ALS patients. | neuroscience |
Divergent sex-specific effects of an IgE receptor polymorphism: from immunity to health, and ultimately, fitness The genotype of an individual is an important predictor of their immune function, and subsequently, their ability to control or avoid infection and ultimately contribute offspring to the next generation. However, the same genotype, subjected to different environments, can also result in different outcomes. The sexes represent two such different environments. Sexual dimorphism is widespread across the animal kingdom. Despite this, very little is known about the importance of sex for the expression of genotype in the context of health and disease, particularly in natural populations. We identified a synonymous polymorphism in the high-affinity Immunoglobulin E (IgE) receptor (GC and non-GC haplotypes) that has sex-specific effects on immune gene expression, susceptibility to infection and reproductive success of individuals in a natural population of field voles (Microtus agrestis). We found that the effect of the GC haplotype on the expression of genes affecting inflammation displayed a significant interaction with sex. While males with the GC haplotype had upregulated pro-inflammatory genes, in particular the pro-inflammatory cytokine Il33, females had upregulated anti-inflammatory genes, in particular the anti-inflammatory cytokine inhibitor Socs3. Furthermore we found that the effect of the GC haplotype on the probability of infection with a common microparasite, Babesia microti, displayed a significant interaction with sex. While males with the GC haplotype did not differ significantly in their susceptibility to infection, females with the GC haplotype were more likely to be infected. Finally, we found that the effect of the GC haplotype on reproductive success also displayed a significant interaction with sex. While males with the GC haplotype had a lower reproductive success, females with the GC haplotype did not differ in the number of offspring they produced. To our knowledge, this is the first time that a polymorphism with sex-specific effects across all three levels (immune gene expression, susceptibility to infection and reproductive success) has been documented in a natural population. | ecology |
Cellular Fitness Phenotypes of Cancer Target Genes from On-cobiology to Cancer Therapeutics To define the growing significance of cellular targets of cancer drugs, we examined the fitness dependency of cellular targets or effectors of cancer drug targets across human cancer cells from 19 cancer types. We observed that the deletion of 35 out of 47 cellular mediators or targets of oncology drugs did not result in the expected loss of cell fitness in appropriate cancer types for which drugs targeting or utilizing these molecules were approved. Additionally, our analysis recognized 43 cellular targets as fitness genes in several cancer types in which these drugs were not approved, and thus, providing clues repurposing approved oncology drugs in cancer types. For example, we found the widespread upregulation and fitness dependency of the components of the mevalonate and purine biosynthesis pathways (currently targeted by bisphosphonates, statins, and pemetrexed in certain cancers) and an association between the overexpression of these targets and reduction in the overall survival duration of patients with breast and other hard-to-treat cancers, for which such drugs are not approved. In brief, the present analysis raised cautions about off-target and undesirable effects of certain oncology drugs in a subset of cancers where the in-tended cellular effectors of drug might not be fitness genes and offers a potential rationale for repurposing certain approved oncology drugs for targeted therapeutics in additional cancer types. | cancer biology |
A comprehensive survey of developmental programs reveals a dearth of tree-like lineage graphs and ubiquitous regeneration BackgroundMulticellular organisms are characterized by a wide diversity of forms and complexity despite a restricted set of key molecules and mechanisms at the base of organismal development. Development combines three basic processes -- asymmetric cell division, signaling and gene regulation -- in a multitude of ways to create this overwhelming diversity of multicellular life-forms. Here, we use a generative model to test the limits to which such processes can be combined to generate multiple differentiation paths during development, and attempt to chart the diversity of multicellular organisms generated.
ResultsWe sample millions of biologically feasible developmental schemes, allowing us to comment on the statistical properties of cell-differentiation trajectories they produce. We characterize model-generated organisms using the graph topology of their cell-type lineage maps. Remarkably, tree-type lineage differentiation maps are the rarest in our data. Additionally, a majority of the organisms generated by our model appear to be endowed with the ability to regenerate using pluripotent cells.
ConclusionsOur results indicate that, in contrast to common views, cell-type lineage graphs are unlikely to be tree-like. Instead, they are more likely to be directed acyclic graphs, with multiple lineages converging on the same terminal cell-type. Furthermore, the high incidence of pluripotent cells in model-generated organisms stands in line with the long-standing hypothesis that whole body regeneration is an epiphenomenon of development. We discuss experimentally testable predictions of our model, and some ways to adapt the generative framework to test additional hypotheses about general features of development. | developmental biology |
Advances in Spiral fMRI: A High-resolution Study with Single-shot Acquisition Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from imperfections in both static and dynamic magnetic fields.
Recently, these limitations have been overcome by the concerted application of an expanded signal model that accounts for such field imperfections, and its inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency.
In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8 mm in-plane resolution. We demonstrate that high-resolution spiral fMRI at 7 T is not only feasible, but delivers both excellent image quality, BOLD sensitivity, and spatial specificity of the activation maps, with little artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination.
HighlightsO_LIThis work reports the first fMRI study at 7T with high-resolution spiral readout gradient waveforms.
C_LIO_LIWe achieve spiral fMRI with sub-millimeter resolution (0.8 mm, FOV 230 mm), acquired in a single shot (36 slices in 3.3 s).
C_LIO_LISpiral images exhibit intrinsic geometric congruency to anatomical scans, and spatially specific activation patterns.
C_LIO_LIImage reconstruction rests on a signal model expanded by measured trajectories and static field maps, inverted by cg-SENSE.
C_LIO_LIWe assess generalizability of the approach for spiral in/out readouts, providing two images per shot (1.5 mm resolution).
C_LI | neuroscience |
Evidence for shared ancestry between Actinobacteria and Firmicutes bacteriophages Bacteriophages typically infect a small set of related bacterial strains. The transfer of bacteriophages between more distant clades of bacteria has often been postulated, but remains mostly unaddressed. In this work we leverage the sequencing of a novel cluster of phages infecting Streptomyces bacteria and the availability of large numbers of complete phage genomes in public repositories to address this question. Using phylogenetic and comparative genomics methods, we show that several clusters of Actinobacteria-infecting phages are more closely related between them, and with a small group of Firmicutes phages, than with any other actinobacteriophage lineage. These data indicate that this heterogeneous group of phages shares a common ancestor with well-defined genome structure. Analysis of genomic %GC content and codon usage bias shows that these actinobacteriophages are poorly adapted to their Actinobacteria hosts, suggesting that this phage lineage could have originated in an ancestor of the Firmicutes, adapted to the low %GC content members of this phylum, and later migrated to the Actinobacteria, or that selective pressure for enhanced translational throughput is significantly lower for phages infecting Actinobacteria hosts. | genomics |
Inhibition of both mutant and wild-type RAS-GTP in KRAS G12C colorectal cancer through cotreatment with G12C and EGFR inhibitors The combination of KRAS G12C inhibitors with EGFR inhibitors has reproducibly been shown to be beneficial. Here, we reveal a new benefit of this combination: it effectively inhibits both wild-type and mutant RAS. A role for WT RAS inhibition has not previously been reported for this important combination of targeted therapies. We believe that targeting both mutant and wild-type RAS helps explain why this combination of inhibitors is effective. | cancer biology |
Automated identification of maximal differential cell populations in flow cytometry data We introduce a new cell population score called SpecEnr (specific enrichment) and describe a method that discovers robust and accurate candidate biomarkers from flow cytometry data. Our approach identifies a new class of candidate biomarkers we define as driver cell populations, whose abundance is associated with a sample class (e.g. disease), but not as a result of a change in a related population. We show that the driver cell populations we find are also easily interpretable using a lattice-based visualization tool. Our method is implemented in the R package flowGraph, freely available on GitHub (github.com/aya49/flowGraph) and on BioConductor. | bioinformatics |
Beyond taxonomic identification: integration of ecological responses to a soil bacterial 16S rRNA gene database. High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalising syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterise taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth "CS") to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from the survey metadata. Specifically, we modelled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on putative landscape scale pH-abundance responses. We identify that most of the soil OTUs examined exhibit predictable abundance responses across soil pH gradients, though with the exception of known acidophilic lineages, the pH optima of OTU relative abundance was variable and could not be generalised by broad taxonomy. This highlights the need for tools and databases to predict ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER), and as a DADA2 database for use in bioinformatics pipelines. The further development of advanced informatics infrastructures incorporating modelled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios. | microbiology |
Effective downregulation of BCR-ABL tumorigenicity by RNA targeted CRISPR-Cas13a AimTo induce BCR-ABL gene silencing using CRISPR Cas13a.
BackgroundCML is a clonal myeloproliferative disorder of pluripotent stem cells driven by a reciprocal translocation between chromosome 9 and 22, forming a BCR-ABL fusion gene. Tyrosinekinase inhibitor drugs like imatinib are the mainstay of treatment and cases resistant to these drugs have a poor prognosis in the absence of a compatible stem-cell donor. However, with rapid advancements in gene-editing technologies, most studies are now focusing on developing a translational model targeting single-gene disorders with a prospective permanent cure.
ObjectiveTo explore the potential application of the RNA targeting CRISPR-Cas13a system for effective knockdown of BCR-ABL fusion transcript in a CML cell line, K562.
MethodCRISPR Cas13a crRNA was designed specific to the chimeric BCR-ABL gene and the system was transfected as a two-plasmid system into a CML cell line, K562. The effects were enumerated by evaluating the expression levels of downstream genes dependent on the expression of the BCR-ABL gene. Also, next-generation sequencing was used to ascertain the effects of CRISPR on the gene.
ResultsThe CRISPR system was successfully able to lower the expression of downstream genes (pCRKL and pCRK) dependent on the activated BCR-ABL kinase signal by up-to 4.3 folds. The viability of the CRISPR treated cells were also significantly lowered by 373.83-fold (p-value= 0.000891196). The time-dependent kinetics also highlighted the significant in-vitro suppressive activity to last up to 8 weeks (p-value: 0.025). As per the cDNA sequencing data from Oxford MinION next-generation sequencer, the CRISPR treated cells show 62.37% suspected cleaved reads.
ConclusionThese preliminary results highlight an excellent potential application of RNA targeting CRISPRs in Haematological neoplasms like CML and should pave way for further research in this direction. | molecular biology |
Adaptive divergence in shoot gravitropism creates hybrid sterility in an Australian wildflower Natural selection is a significant driver of speciation. Yet it remains largely unknown whether local adaptation can drive speciation through the evolution of hybrid sterility between populations. Here, we show that adaptive divergence in shoot gravitropism, the ability of a plants shoot to bend upwards in response to the downward pull of gravity, contributes to the evolution of hybrid sterility in an Australian wildflower, Senecio lautus. We find that shoot gravitropism has evolved multiple times in association with plant height between adjacent populations inhabiting contrasting environments, suggesting that these traits have evolved by natural selection. We directly tested this prediction using a hybrid population subjected to eight rounds of recombination and three rounds of selection in the field. It revealed that shoot gravitropism responds to natural selection in the expected direction of the locally adapted population. This provided an ideal platform to test whether genetic differences in gravitropism contribute to hybrid sterility in S. lautus. Using this advanced hybrid population, we discovered that crossing individuals with extreme differences in gravitropism reduce their ability to produce seed by 21%, providing strong evidence that this adaptive trait is genetically correlated with hybrid sterility. Our results suggest that natural selection can drive the evolution of locally adaptive traits that also create hybrid sterility, thus indicating an evolutionary connection between local adaptation and the origin of new species.
Significance statementNew species originate as populations become reproductively isolated from one another. Despite recent progress in uncovering the genetic basis of reproductive isolation, it remains unclear whether intrinsic reproductive barriers, such as hybrid sterility, evolve as a by-product of local adaptation to contrasting environments or evolve through non-ecological processes, such as meiotic drive. Here, we show that differences in a plants response to the pull of gravity have repeatedly evolved amongst coastal populations of an Australian wildflower, thus implicating a role of natural selection in their evolution. We found a strong genetic correlation between variation in this adaptive trait and hybrid sterility, suggesting that intrinsic reproductive barriers contribute to the origin of new species as populations adapt to heterogeneous environments. | evolutionary biology |
Frequency selectivity of persistent cortical oscillatory responses to auditory rhythmic stimulation Cortical oscillations have been proposed to play a functional role in speech and music perception, attentional selection and working memory, via the mechanism of neural entrainment. One of the most compelling arguments for neural entrainment is that its modulatory effect on ongoing oscillations outlasts rhythmic stimulation. We tested the existence of this phenomenon by studying cortical neural oscillations during and after presentation of melodic stimuli in a passive perception paradigm. Melodies were composed of [~]60 and [~]80 Hz tones embedded in a 2.5 Hz stream. Using intracranial and surface recordings in humans, we reveal consistent neural response properties throughout the cortex, well beyond the auditory regions. Persistent oscillatory activity in the high-gamma band was observed in response to the tones. By contrast, in response to the 2.5 Hz stream, no persistent activity in any frequency band was observed. We further show that our data are well-captured by a model of damped harmonic oscillator and can be classified into three classes of neural dynamics, with distinct damping properties and eigenfrequencies. This model provides a mechanistic and quantitative explanation of the frequency selectivity of auditory neural entrainment in the human cortex.
Significance statementIt has been proposed that the functional role of cortical oscillations is subtended by a mechanism of entrainment, the synchronisation in phase or amplitude of neural oscillations to a periodic stimulation. We tested whether the modulatory effect on ongoing oscillations outlasts the rhythmic stimulation, a phenomenon considered to be one of the most compelling arguments for entrainment. Using intracranial and surface recordings of human listening to rhythmic auditory stimuli, we reveal consistent oscillatory responses throughout the cortex, with persistent activity of high-gamma oscillations. On the contrary, neural oscillations do not outlast low-frequency acoustic dynamics. We interpret our results as reflecting harmonic oscillator properties - a model ubiquitous in physics but rarely used in neuroscience. | neuroscience |
Recombination and selection against introgressed DNA DNA introgressed from one species into another is typically deleterious at many genomic loci in the recipient species. It is therefore purged by selection over time. Here, we use mathematical modeling and whole-genome simulations to study the influence of recombination on the purging of introgressed DNA. We find that aggregate recombination controls the genome-wide rate of purging in the first few generations after admixture, when purging is most rapid. Aggregate recombination is quantified by [Formula], the average recombination rate across all locus pairs, and analogous metrics. It is influenced by the number of crossovers (i.e., the map length) and their locations along chromosomes, and by the number of chromosomes and heterogeneity in their size. A comparative prediction of our analysis is that species with fewer chromosomes should purge introgressed DNA more profoundly, and therefore should exhibit a weaker genomic signal of historical introgression. With regard to patterns across the genome, we show that, in heterogametic species with autosomal recombination in both sexes, more purging is expected on sex chromosomes than on autosomes, all else equal. The opposite prediction holds for species without autosomal recombination in the heterogametic sex. Finally, we show that positive genomic correlations between local recombination rate and introgressed ancestry, as recently observed in several taxa, are likely driven not by recombinations effect in unlinking neutral from deleterious introgressed alleles, but rather by its effect on the rate of purging of the deleterious alleles themselves.
Note on this versionAn earlier version of this manuscript had two parts: (1) Calculations of the variance of genetic relatedness between individuals with particular pedigree relationships, taking into account the randomness of recombination and segregation in their pedigree. (2) An investigation of the rate of purging of introgressed DNA following admixture, based in part on results from part (1). Part (1) has since been published as Veller et al. (2020). The present manuscript has been reconfigured to focus on part (2). | evolutionary biology |
Predictive Coding Models for Pain Perception Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats--two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out--thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain. | neuroscience |
Differential robustness to specific potassium channel deletions in midbrain dopaminergic neurons The authors have withdrawn this preprint titled "Differential robustness to specific potassium channel deletions in midbrain dopaminergic neurons". Upon review of breeding and genotyping data, Kcnn3-/- mice could not be trusted as representative of the expected genetic deletion. As a consequence data generated from these animals do not constitute a valid description of the Kcnn3-/- genotype in dopaminergic neurons. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. | neuroscience |
Strand asymmetry influences mismatch resolution during single-strand annealing BackgroundBiases of DNA repair can shape the nucleotide landscape of genomes at evolutionary timescales. However, such biases have not yet been measured in chromatin for lack of technologies.
ResultsHere we develop a genome-wide assay whereby the same DNA lesion is repaired in different chromatin contexts. We insert thousands of barcoded transposons carrying a reporter of DNA mismatch repair in the genome of mouse embryonic stem cells. Upon inducing a double-strand break between tandem repeats, a mismatch is generated when the single strand annealing repair pathway is used. Regardless of the mismatch, we observed a 60-80% bias in the resolution in favor of one strand. The location of the lesion in the genome and the type of mismatch had little influence on the bias in this context. Instead, changing the position of the double-strand break in the reporter gave a complete reversion of the bias.
ConclusionThese results suggest that the processing of the double-strand break has a major influence on the repair of mismatches during single-strand annealing, irrespective of the surrounding chromatin context. | genomics |
Rhomboid protease RHBDL4 promotes retrotranslocation of aggregation-prone proteins for degradation Protein degradation is fundamentally important to ensure cell homeostasis. In the endoplasmic reticulum (ER), the ER-associated degradation (ERAD) pathway targets incorrectly folded and unassembled proteins into the cytoplasm for turnover by the proteasome. In contrast, lysosomal degradation serves as a failsafe mechanism for removing proteins that resist ERAD by forming aggregates. Previously, we showed that the ER- resident rhomboid protease RHBDL4, together with p97, mediates membrane protein degradation. However, whether RHBDL4 acts in concert with additional ERAD components is unclear, and its full substrate spectrum remains to be defined. Here, we show that besides membrane proteins, RHBDL4 cleaves aggregation-prone luminal ERAD substrates. Because RHBDL4 with mutations in the rhomboid domain leads to stabilization of substrates at the cytoplasmic side, we hypothesize that analogue to the homologue ERAD factor derlin, RHBDL4 is directly involved in substrate retrotranslocation. RHBDL4s interaction with the erlin ERAD complex and reciprocal interaction of rhomboid substrates with erlins suggest that RHBDL4 and erlins form a complex that clips substrates and thereby rescues aggregation-prone peptides in the ER lumen from terminal aggregation. | cell biology |
RAF conformational autoinhibition and 14-3-3 proteins promote paradoxical activation RAF kinase inhibitors can, in some conditions, increase RAF kinase signaling. This process, which is commonly referred to as "paradoxical activation" (PA), is incompletely understood. RAF kinases are regulated by autoinhibitory conformational changes, and the role of these conformational changes in PA is unclear. Our mathematical investigations reveal that a dynamic equilibrium between autoinhibited and non-autoinhibited forms of RAF, along with the RAF inhibitor stabilization of the non-autoinhibited form, can be sufficient to create PA. Using both computational and experimental methods we demonstrate that 14-3-3 proteins, which stabilize both RAF autoinhibition and RAF dimerization, potentiate PA. Our model led us to hypothesize that increased 14-3-3 expression would amplify PA for the third generation RAF inhibitors that normally display minimal to no PA. Our subsequent experiments find that 14-3-3 overexpression increases PA, increases RAF dimerization, and promotes resistance to these inhibitors, effectively "breaking" these "paradox breaker" and pan-RAF inhibitors. Overall, this work reveals a robust mechanism for PA based solely on equilibrium dynamics of canonical interactions in RAF signaling and identifies conditions which allow PA to occur. | cancer biology |
Integration of Odor-Induced Activity of Kenyon Cells in an Electrotonically Compact Drosophila Mushroom Body Output Neuron (MBON) The formation of an ecologically useful lasting memory requires that the brain has an accurate internal representation of the surrounding environment. In addition, it must have the ability to integrate a variety of different sensory stimuli and associate them with rewarding and aversive behavioral outcomes. Over the previous years, a number of studies have dissected the anatomy and elucidated some of the working principles of the Drosophila mushroom body (MB), the flys center for learning and memory. As a consequence, we now have a functional understanding of where and how in the MB sensory stimuli converge and are associated. However, the molecular and cellular dynamics at the critical synaptic intersection for this process, the Kenyon cell-mushroom body output neuron (KC-MBON) synapse, are largely unknown. Here, we introduce a first approach to understand this integration process and the physiological changes occurring at the KC-MBON synapse during Kenyon cell (KC) activation. We use the published connectome of the Drosophila MB to construct a functional computational model of the MBON-3 dendritic structure. We simulate synaptic input by individual KC-MBON synapses by current injections into precisely (m) identified local dendritic sections, and the input from a model population of KCs representing an odor by a spatially distributed cluster of current injections. By recording the effect of the simulated current injections on the membrane potential of the neuron, we show that the MBON-3 is electrotonically compact. This suggests that odor-induced MBON activity is likely governed by input strength while the positions of KC input synapses are largely irrelevant. | neuroscience |
Effects of dopamine receptor antagonism and amphetamine-induced psychomotor sensitization on sign- and goal-tracking after extended training The dopamine system is important for incentive salience attribution, where motivational value is assigned to conditioned cues that predict appetitive reinforcers. However, the role of dopamine in this process may change with extended training. We tested the effects of dopamine D1-like and D2-like receptor antagonism on the expression of sign-tracking and goal-tracking conditioned responses following extended Pavlovian conditioned approach (PCA) training. We also tested if amphetamine-induced psychomotor sensitization accelerates the enhanced acquisition of sign-tracking that is observed with extended training. In experiment 1, 24 male Long-Evans rats received 20 PCA sessions in which one lever (CS+, 10 s) predicted 0.2 mL sucrose (10%, w/v) delivery and the other lever (CS-) did not. SCH-23390 (D1-like antagonist) or eticlopride (D2-like antagonist) were administered before non-reinforced behavioural tests at doses of 0, 0.01, and 0.1 mg/kg (s.c.). In experiment 2, rats received vehicle or 2 mg/kg amphetamine (i.p.) for 7 days (n = 12/group). Ten days later, they received 16 PCA training sessions. Both doses of SCH-23390 reduced sign- and goal-tracking, but also reduced locomotor behaviour. A low dose of eticlopride (0.01 mg/kg) selectively reduced goal-tracking, without affecting sign-tracking or locomotor behaviour. Amphetamine produced psychomotor sensitization, and this did not affect the acquisition of sign- or goal-tracking. Following extended PCA training, dopamine D2-like receptor activity is required for the expression of goal-tracking but not sign-tracking. Psychomotor sensitization to amphetamine did not impact incentive salience attribution; however, more selective manipulations of the dopamine system may be needed. | neuroscience |
Barley RIC157 is involved in RACB-mediated susceptibility to powdery mildew Successful obligate pathogens benefit from host cellular processes. For the biotrophic ascomycete fungus Blumeria graminis f.sp. hordei (Bgh) it has been shown that barley RACB, a small monomeric G-protein (ROP, RHO of plants), is required for full susceptibility to fungal penetration. The susceptibility function of RACB probably lies in its role in cell polarisation, which may be co-opted by the pathogen for invasive ingrowth of its haustorium. However, the actual mechanism of how RACB supports the fungal penetration success is little understood. RIC proteins (ROP-Interactive and CRIB-(Cdc42/Rac Interactive Binding) motif-containing) are considered scaffold proteins which can interact directly with ROPs via a conserved CRIB motif. Here we describe a yet uncharacterised RIC protein, RIC157, which can interact directly with RACB in planta. We show that RIC157 undergoes a recruitment from the cytoplasm to the cell periphery in the presence of activated RACB. During fungal infection, RIC157 and activated RACB colocalise at the penetration site, particularly at the haustorial neck. In a RACB-dependent manner, transiently overexpressed RIC157 renders barley epidermal cells more susceptible to fungal penetration. This suggests that RIC157 promotes fungal penetration into barley epidermal cells via its function downstream of RACB. | plant biology |
Using single visits into integrated occupancy models to make the most of existing monitoring programs A major challenge in statistical ecology consists of integrating knowledge from different datasets to produce robust ecological indicators. To estimate species distribution, occupancy models are a flexible framework that can accommodate several datasets obtained from different sampling methods. However, repeating visits at sampling sites is a prerequisite for using standard occupancy models. Occupancy models were recently developed to analyze detection/non-detection data collected during a single visit. To date, single-visit occupancy models have never been used to integrate several different datasets. Here, we showcase an approach that combines two datasets into an integrated single-visit occupancy model. As a case study, we estimated the distribution of Bottlenose dolphins (Tursiops truncatus) over the North-western Mediterranean Sea by combining 24,624 km of aerial surveys and 21,464 km of at-sea monitoring. We compared the outputs of single- vs. repeated-visit occupancy models into integrated occupancy models. Integrated models allowed a better sampling coverage of species home-range, which provided a better precision for occupancy estimates than occupancy models using datasets in isolation. Overall, single- and repeated-visit integrated occupancy models produced similar inference about the distribution of bottlenose dolphins. We suggest that single-visit occupancy models open promising perspectives for the use of existing ecological datasets. | ecology |
GraphProt2: A graph neural network-based method for predicting binding sites of RNA-binding proteins CLIP-seq is the state-of-the-art technique to experimentally determine transcriptome-wide binding sites of RNA-binding proteins (RBPs). However, it relies on gene expression which can be highly variable between conditions, and thus cannot provide a complete picture of the RBP binding landscape. This creates a demand for computational methods to predict missing binding sites. Here we present GraphProt2, a computational RBP binding site prediction framework based on graph convolutional neural networks (GCNs). In contrast to current CNN methods, GraphProt2 offers native support for the encoding of base pair information as well as variable length input, providing increased flexibility and the prediction of nucleotide-wise RBP binding profiles. We demonstrate its superior performance compared to GraphProt and two CNN-based methods on single as well as combined CLIP-seq datasets. Conceived as an end-to-end method, GraphProt2 includes all necessary functionalities, from dataset generation over model training to the evaluation of binding preferences and binding site prediction. Various input types and features are supported, accompanied by comprehensive statistics and visualizations to inform the user about datatset characteristics and learned model properties. All this makes GraphProt2 the most versatile and complete RBP binding site prediction method available so far. | bioinformatics |
Temperature-induced prophage dictates evolution of virulence in bacteria Viruses are key actors of ecosystems and have major impacts on global biogeochemical cycles. Prophages deserve particular attention as they are ubiquitous in bacterial genomes and can enter a lytic cycle when triggered by environmental conditions. We explored how temperature affects the interactions between prophages and other biological levels by using an opportunistic pathogen, the bacterium Serratia marcescens, that harbours several prophages and that had undergone an evolution experiment under several temperature regimes. We found that the release of one of the prophages was temperature-sensitive and malleable to evolutionary changes. We further discovered that the virulence of the bacterium in an insect model also evolved and was positively correlated with phage release rates. We determined through analysis of genetic and epigenetic data that changes in the outer cell wall structure possibly explain this phenomenon. We hypothezise that the temperature-dependent phage release rate acted as a selection pressure on S. marcescens and that it resulted in modified bacterial virulence in the insect host. Our study system illustrates how viruses can mediate the influence of abiotic environmental changes to other biological levels and thus be involved in ecosystem feedback loops. | evolutionary biology |
Bacterial quorum sensing allows graded and bimodal cellular responses to variations in population density Quorum sensing (QS) is a mechanism of cell-cell communication that connects gene expression to environmental conditions (e.g. density) in many bacterial species, mediated by diffusible signal molecules. Current functional studies focus on a dichotomy of QS on/off (or, quorate / sub-quorate) states, overlooking the potential for intermediate, graded responses to shifts in the environment. Here, we track QS regulated protease (lasB) expression and show that Pseudomonas aeruginosa can deliver a graded behavioral response to fine-scale variation in population density, on both the population and single-cell scales. On the population scale, we see a graded response to variation in environmental population density. On the single-cell scale, we see significant bimodality at higher densities, with separate OFF and ON sub-populations that respond differentially to changes in density; static OFF cells and increasing intensity of expression among ON cells. Together these results indicate that QS can tune gene expression to graded environmental change, with no critical cell mass or quorum at which behavioral responses are activated on either the individual cell or population scale. In an infection context, our results indicate there is not a hard threshold separating sub-quorate stealth mode and a quorate attack mode. | microbiology |
Family History of Depression is Associated with Alterations in Task-Dependent Connectivity between the Cerebellum and Ventromedial Prefrontal Cortex BackgroundA family history of major depressive disorder (MDD) increases the likelihood of a future depressive episode, which itself poses a significant risk for disruptions in reward processing and social cognition. However, it is unclear whether a family history of MDD is associated with alterations in the neural circuitry underlying reward processing and social cognition.
MethodsWe subdivided 279 participants from the Human Connectome Project into three groups: 71 with a lifetime history of MDD, 103 with a family history of MDD (FH), and 105 healthy controls (HC). We then evaluated task-based fMRI data on a social cognition and a reward processing task and found a region of the ventromedial prefrontal cortex (vmPFC) that responded to both tasks, independent of group. To investigate whether the vmPFC shows alterations in functional connectivity between groups, we conducted psychophysiological interaction (PPI) analyses using the vmPFC as a seed region.
ResultsWe found that FH (relative to HC) was associated with increased sadness scores, and MDD (relative to both FH and HC) was associated with increased sadness and MDD symptoms. Additionally, the FH group had increased vmPFC functional connectivity within the nucleus accumbens, left dorsolateral PFC, and subregions of the cerebellum relative to HC during the social cognition task.
ConclusionsThese findings suggest that aberrant neural mechanisms among those with a familial risk of MDD may underlie vulnerability to altered social cognition. | neuroscience |
Predator complementarity dampens variability of phytoplankton biomass in a diversity-stability trophic cascade Trophic cascades - indirect effects of predators that propagate down through food webs - have been extensively documented. It has also been shown that predator diversity can mediate these trophic cascades, and separately, that herbivore biomass can influence the stability of primary producers. However, whether predator diversity can cause cascading effects on the stability of lower trophic levels has not yet been studied. We conducted a laboratory microcosm experiment and a field mesocosm experiment manipulating the presence and coexistence of two heteropteran predators and measuring their effects on zooplankton herbivores and phytoplankton basal resources. We predicted that if the predators partitioned their zooplankton prey, for example by size, then co-presence of the predators would reduce zooplankton prey mass and lead to 1) increased average values and 2) decreased temporal variability of phytoplankton basal resources. We present evidence that the predators partitioned their zooplankton prey, leading to a synergistic suppression of zooplankton; and that in turn, this suppression of zooplankton reduced the variability of phytoplankton biomass. However, mean phytoplankton biomass was unaffected. Our results demonstrate that predator diversity may indirectly stabilize basal resource biomass via a "diversity-stability trophic cascade," seemingly dependent on predator complementarity, but independent of a classic trophic cascade in which average biomass is altered. Therefore predator diversity, especially if correlated with diversity of prey use, could play a role in regulating ecosystem stability. Furthermore, this link between predator diversity and producer stability has implications for potential biological control methods for improving the reliability of crop yields. | ecology |
Statistical power: implications for planning MEG studies Statistical power is key for robust, replicable science. Here, we systematically explored how numbers of trials and subjects affect statistical power in MEG sensor-level data. More specifically, we simulated "experiments" using the MEG resting-state dataset of the Human Connectome Project (HCP). We divided the data in two conditions, injected a dipolar source at a known anatomical location in the "signal condition", but not in the "noise condition", and detected significant differences at sensor level with classical paired t-tests across subjects, using amplitude, squared amplitude, and global field power (GFP) measures. Group-level detectability of these simulated effects varied drastically with anatomical origin. We thus examined in detail which spatial properties of the sources affected detectability, looking specifically at the distance from closest sensor and orientation of the source, and at the variability of these parameters across subjects. In line with previous single-subject studies, we found that the most detectable effects originate from source locations that are closest to the sensors and oriented tangentially with respect to the head surface. In addition, cross-subject variability in orientation also affected group-level detectability, boosting detection in regions where this variability was small and hindering detection in regions where it was large. Incidentally, we observed a considerable covariation of source position, orientation, and their cross-subject variability in individual brain anatomical space, making it difficult to assess the impact of each of these variables independently of one another. We thus also performed simulations where we controlled spatial properties independently of individual anatomy. These additional simulations confirmed the strong impact of distance and orientation and further showed that orientation variability across subjects affects detectability, whereas position variability does not. Importantly, our study indicates that strict unequivocal recommendations as to the ideal number of trials and subjects for any experiment cannot be realistically provided for neurophysiological studies and should be adapted according to the brain regions under study. | neuroscience |
Low membrane fluidity triggers lipid phase separation and protein segregation in vivo All living organisms adapt their membrane lipid composition in response to changes in their environment or diet. These conserved membrane-adaptive processes have been studied extensively. However, key concepts of membrane biology linked to regulation of lipid composition including homeoviscous adaptation maintaining stable levels of membrane fluidity, and gel-fluid phase separation resulting in domain formation, heavily rely upon in vitro studies with model membranes or lipid extracts. Using the bacterial model organisms Escherichia coli and Bacillus subtilis, we now show that inadequate in vivo membrane fluidity interferes with essential complex cellular processes including cytokinesis, envelope expansion, chromosome replication/segregation and maintenance of membrane potential. Furthermore, we demonstrate that very low membrane fluidity is indeed capable of triggering large-scale lipid phase separation and protein segregation in intact, protein-crowded membranes of living cells; a process that coincides with the minimal level of fluidity capable of supporting growth. Importantly, the in vivo lipid phase separation is not associated with a breakdown of the membrane diffusion barrier function, thus explaining why the phase-separation process induced by low fluidity is biologically reversible. | microbiology |
Energy Expenditure during Cell Spreading Regulates the Stem Cells Responses to Matrix Stiffness Cells respond to the mechanical properties of the extracellular matrix (ECM) through formation of focal adhesions (FAs), re-organization of the actin cytoskeleton and adjustment of cell contractility. These are energy-demanding processes, but a potential causality between mechanical cues (matrix stiffness) and cellular (energy) metabolism remains largely unexplored. Here, we culture human mesenchymal stem cells (hMSCs) on stiff (20 kPa) or soft (1 kPa) substrate and demonstrate that cytoskeletal reorganization and FA formation spreading on stiff substrates lead to a drop in intracellular ATP levels, correlates with the activation of AMP-activated protein kinase (AMPK). The resulting increase in ATP levels further facilitates cell spreading and reinforces cell tension of the steady state, and coincides with nuclear localization of YAP/TAZ and Runx2. While on soft substrates (1 kPa), lowered ATP levels limit these cellular mechanoresponses. Furthermore, genetic ablation of AMPK lowered cellular ATP levels on stiff substrate and strongly reduced responses to substrate stiffness. Together, these findings reveal a hitherto unidentified relationship between energy expenditure and the cellular mechanoresponse, and point to AMPK as a key mediator of stem cell fate in response to ECM mechanics. | cell biology |
The neural computation of human prosocial choices in complex motivational states Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modelling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors.
HighlightsO_LIActivating different social motives simultaneously can enhance prosocial choices
C_LIO_LIMulti-motive combinations change initial prosocial biases
C_LIO_LIDorso-striatal activation increases with larger increase of prosocial bias
C_LIO_LIMulti-motive combinations modulate relative response caution
C_LI | neuroscience |
Distinct Processing of Selection and Execution Errors in Neural Signatures of Outcome Monitoring Losing a point in tennis could result from poor shot selection or faulty stroke execution. To explore how the brain responds to these different types of errors, we examined feedback-locked EEG activity while participants completed a modified version of a standard three-armed bandit probabilistic reward task. Our task framed unrewarded outcomes as either the result of errors of selection or errors of execution. We examined whether amplitude of a medial frontal negativity (the Feedback-Related Negativity; FRN) was sensitive to the different forms of error attribution. Consistent with previous reports, selection errors elicited a large FRN relative to rewards and amplitude of this signal correlated behavioral adjustment following these errors. A different pattern was observed in response to execution errors. These outcomes produced a larger FRN, a frontocentral attenuation in activity preceding this component, and a subsequent enhanced error positivity in parietal sites. Notably, the only correlations with behavioral adjustment were with the early frontocentral attenuation and amplitude of the parietal signal; FRN differences between execution errors and rewarded trials did not correlate with subsequent changes in behavior. Our findings highlight distinct neural correlates of selection and execution error processing, providing insight into how the brain responds to the different classes of error that determine future action. | neuroscience |
Face familiarity detection with complex synapses Synaptic plasticity is a complex phenomenon involving multiple biochemical processes that operate on different timescales. We recently showed that this complexity can greatly increase the memory capacity of neural networks when the variables that characterize the synaptic dynamics have limited precision, as in biological systems. These types of complex synapses have been tested mostly on simple memory retrieval problems involving random and uncorrelated patterns. Here we turn to a real-world problem, face familiarity detection, and we show that also in this case it is possible to take advantage of synaptic complexity to store in memory a large number of faces that can be recognized at a later time. In particular, we show that the familiarity memory capacity of a system with complex synapses grows almost linearly with the number of the synapses and quadratically with the number of neurons. Complex synapses are superior to simple ones, which are characterized by a single variable, even when the total number of dynamical variables is matched. We further show that complex and simple synapses have distinct signatures that are testable in proposed experiments. Our results indicate that a memory system with complex synapses can be used in real-world tasks such as face familiarity detection.
SignificanceThe complexity of biological synapses is probably important for enabling us to remember the past for a long time and rapidly store new memories. The advantage of complex synapses in terms of memory capacity is significant when the variables that characterize the synaptic dynamics have limited precision. This advantage has been estimated under the simplifying assumption that the memories to be stored are random and uncorrelated. Here we show that synaptic complexity is important also in a more challenging and realistic face familiarity detection task. We built a simple neural circuit that can report whether a face has been previously seen or not. This circuit incorporates complex synapses that operate on multiple timescales. The memory performance of this circuit is significantly higher than in the case in which synapses are simple, indicating that the complexity of biological synapses can be important also in real-world memory tasks. | neuroscience |
The metastable brain associated with autistic-like traits of typically developing individuals Metastability in the brain is thought to be a mechanism involved in dynamic organization of cognitive and behavioral functions across multiple spatiotemporal scales. However, it is not clear how such organization is realized in underlying neural oscillations in a high-dimensional state space. It was shown that macroscopic oscillations often form phase-phase coupling (PPC) and phase-amplitude coupling (PAC) which result in synchronization and amplitude modulation, respectively, even without external stimuli. These oscillations can also make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalographic signals and the autism-spectrum quotient scores acquired from healthy humans, we show experimental evidence that the PAC combined with PPC allows amplitude modulation to be transient, and that the metastable dynamics with this transient modulation is associated with autistic-like traits. In individuals with a longer attention span, such dynamics tended to show fewer transitions between states by forming delta-alpha PAC. We identified these states as two-dimensional metastable states that could share consistent patterns across individuals. Our findings suggest that the human brain dynamically organizes inter-individual differences in a hierarchy of macroscopic oscillations with multiple timescales by utilizing metastability.
Author SummaryThe human brain organizes cognitive and behavioral functions dynamically. For decades, the dynamic organization of underlying neural oscillations has been a fundamental topic in neuroscience research. Even without external stimuli, macroscopic oscillations often form phase-phase coupling and phase-amplitude coupling (PAC) that result in synchronization and amplitude modulation, respectively, and can make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalography signals acquired from healthy humans, we show evidence that these two neural couplings enable amplitude modulation to be transient, and that this transient modulation can be viewed as the transition among oscillatory states with different PAC strengths. We also demonstrate that such transition dynamics are associated with the ability to maintain attention to detail and to switch attention, as measured by autism-spectrum quotient scores. These individual dynamics were visualized as a trajectory among states with attracting tendencies, and involved consistent brain states across individuals. Our findings have significant implications for unraveling variability in the individual brains showing typical and atypical development. | neuroscience |
Electrode pooling: How to boost the yield of switchable silicon probes for neuronal recordings State-of-the-art silicon probes for electrical recording from neurons have thousands of recording sites. However, due to volume limitations there are typically many fewer wires carrying signals off the probe, which restricts the number of channels that can be recorded simultaneously. To overcome this fundamental constraint, we propose a novel method called electrode pooling that uses a single wire to serve many recording sites through a set of controllable switches. Here we present the framework behind this method and an experimental strategy to support it. We then demonstrate its feasibility by implementing electrode pooling on the Neuropixels 1.0 electrode array and characterizing its effect on signal and noise. Finally we use simulations to explore the conditions under which electrode pooling saves wires without compromising the content of the recordings. We make recommendations on the design of future devices to take advantage of this strategy. | neuroscience |
Constricted migration is associated with stable 3D genome structure differences in cancer cells To spread from a localized tumor, metastatic cancer cells must squeeze through constrictions that cause major nuclear deformations. Since chromosome structure affects nucleus stiffness, gene regulation and DNA repair, here we investigate the relationship between 3D genome structure and constricted migration in cancer cells. Using melanoma (A375) cells, we identify phenotypic differences in cells that have undergone multiple rounds of constricted migration. These cells display a stably higher migration efficiency, elongated morphology, and differences in the distribution of Lamin A/C and heterochromatin. Hi-C experiments reveal differences in chromosome spatial compartmentalization specific to cells that have passed through constrictions and related alterations in expression of genes associated with migration and metastasis. Certain features of the 3D genome structure changes, such as a loss of B compartment interaction strength, are consistently observed after constricted migration in clonal populations of A375 cells and in MDA-MB-231 breast cancer cells. Our observations suggest that consistent types of chromosome structure changes are induced or selected by passage through constrictions and that these may epigenetically encode stable differences in gene expression and cellular migration phenotype. | systems biology |
Multi-Study Learning for Real-time Neurochemical Sensing in Humans using the "Study Strap Ensemble" We propose the "study strap ensemble," which combines advantages of two common approaches to fitting prediction models when multiple training datasets ("studies") are available: pooling studies and fitting one model versus averaging predictions from multiple models each fit to individual studies. The study strap ensemble fits models to bootstrapped datasets, or "pseudo-studies." These are generated by resampling from multiple studies with a hierarchical resampling scheme that generalizes the randomized cluster bootstrap. The study strap is controlled by a tuning parameter that determines the proportion of observations to draw from each study. When the parameter is set to its lowest value, each pseudo-study is resampled from only a single study. When it is high, the study strap ignores the multi-study structure and generates pseudo-studies by merging the datasets and drawing observations like a standard bootstrap. We empirically show the optimal tuning value often lies in between, and prove that special cases of the study strap draw the merged dataset and the set of original studies as pseudo-studies. We extend the study strap approach with an ensemble weighting scheme that utilizes information in the distribution of the covariates of the test dataset.
Our work is motivated by neuroscience experiments using real-time neurochemical sensing during awake behavior in humans. Current techniques to perform this kind of research require measurements from an electrode placed in the brain during awake neurosurgery and rely on prediction models to estimate neurotransmitter concentrations from the electrical measurements recorded by the electrode. These models are trained by combining multiple datasets that are collected in vitro under heterogeneous conditions in order to promote accuracy of the models when applied to data collected in the brain. A prevailing challenge is deciding how to combine studies or ensemble models trained on different studies to enhance model generalizability.
Our methods produce marked improvements in simulations and in this application. All methods are available in the studyStrap CRAN package. | neuroscience |
Linear reinforcement learning: Flexible reuse of computation in planning, grid fields, and cognitive control It is thought that the brains judicious reuse of previous computation underlies our ability to plan flexibly, but also that inappropriate reuse gives rise to inflexibilities like habits and compulsion. Yet we lack a complete, realistic account of either. Building on control engineering, we introduce a new model for decision making in the brain that reuses a temporally abstracted map of future events to enable biologically-realistic, flexible choice at the expense of specific, quantifiable biases. It replaces the classic nonlinear, model-based optimization with a linear approximation that softly maximizes around (and is weakly biased toward) a default policy. This solution exposes connections between seemingly disparate phenomena across behavioral neuroscience, notably flexible replanning with biases and cognitive control. It also gives new insight into how the brain can represent maps of long-distance contingencies stably and componentially, as in entorhinal response fields, and exploit them to guide choice even under changing goals. | neuroscience |
Network potential identifies therapeutic miRNA cocktails in Ewings Sarcoma MicroRNA (miRNA)-based therapies are an emerging class of targeted therapeutics with many potential applications. Ewing Sarcoma patients could benefit dramatically from personalized miRNA therapy due to inter-patient heterogeneity and a lack of druggable (to this point) targets. However, because of the broad effects miRNAs may have on different cells and tissues, trials of miRNA therapies have struggled due to severe toxicity and unanticipated immune response. In order to overcome this hurdle, a network science-based approach is well-equipped to evaluate and identify miRNA candidates and combinations of candidates for the repression of key oncogenic targets while avoiding repression of essential housekeeping genes. We first characterized 6 Ewing sarcoma cell lines using mRNA sequencing. We then estimated a measure of tumor state, which we term network potential, based on both the mRNA gene expression and the underlying protein-protein interaction network in the tumor. Next, we ranked mRNA targets based on their contribution to network potential. We then identified miRNAs and combinations of miRNAs that preferentially act to repress mRNA targets with the greatest influence on network potential. Our analysis identified TRIM25, APP, ELAV1, RNF4, and HNRNPL as ideal mRNA targets for Ewing sarcoma therapy. Using predicted miRNA-mRNA target mappings, we identified miR-3613-3p, let-7a-3p, miR-300, miR-424-5p, and let-7b-3p as candidate optimal miRNAs for preferential repression of these targets. Ultimately, our work, as exemplified in the case of Ewing sarcoma, describes a novel pipeline by which personalized miRNA cocktails can be designed to maximally perturb gene networks contributing to cancer progression.
Author SummaryPrecision medicine in cancer aims to find the right treatment, for the right patient, at the right time. Substantial variation between patient tumors, even of the same disease site, has limited the application of precision medicine in the clinic. In this study, we present novel computational tools for the identification of targets for cancer therapy using widely available sequencing data. We used a network-science based approach that leveraged multiple types of omic data to identify functionally relevant disease targets. Further, we developed algorithms to identify potential miRNA-based therapies that inhibit these predicted disease targets. We applied this pipeline to a novel Ewing Sarcoma transcriptomics data-set as well as publicly available patient data from the St. Jude Cloud. We identified a number of promising therapeutic targets for this rare disease, including EWSR1, the proposed driver of Ewing Sarcoma development. These novel data and methods will provide researchers with new tools for the development of precision medicine treatments in a variety of cancer systems. | systems biology |
Dopamine and stress signalling interplay patterns social organization in mice The rules leading to the emergence of a social organization and the role of social hierarchy on normal and pathological behaviours remain elusive. Here we show that groups of four isogenic male mice rapidly form enduring social ranks in a dominance hierarchy. Highest ranked individuals display enhanced anxiety and working memory, are more social and more susceptible to stress-related maladaptive behaviours. Are these differences causes or consequences to social life? We show that anxiety emerges from life in colony whereas sociability is a pre-existing trait. Strikingly, highest ranked individuals exhibit lower bursting activity of VTA dopamine neurons. Both pharmacogenetic inhibition of this neuronal population and the genetic inactivation of glucocorticoid receptor signalling in dopamine-sensing brain areas promote the accession to higher social ranks. Altogether, these results indicate that the shaping of social fate relies upon the interplay of dopamine system and stress response, impacting individual behaviour and potentially mental health. | animal behavior and cognition |
Mapping Human Pluripotent Stem Cell Derived Erythroid Differentiation by Single-Cell Transcriptome Analysis There is an imbalance between the supply and demand of functional red blood cells (RBCs) in clinical applications. This imbalance can be addressed by regenerating RBCs using several in vitro methods. Induced pluripotent stem cells (iPSCs) can handle the low supply of cord blood and the ethical issues in embryonic stem cell research and provide a promising strategy to eliminate immune rejection. However, no complete single-cell level differentiation pathway exists for the iPSC-derived RBC differentiation system. In this study, we used iPSC line BC1 to establish a RBCs regeneration system. The 10x genomics single-cell transcriptome platform was used to map the cell lineage and differentiation trajectories on day 14 of the regeneration system. We observed that iPSCs differentiation was not synchronized during embryoid body (EB) culture. The cells (day 14) mainly consisted of mesodermal and various blood cells, similar to the yolk sac hematopoiesis. We identified six cell classifications and characterized the regulatory transcription factors (TFs) networks and cell-cell contacts underlying the system. iPSCs undergo two transformations during the differentiation trajectory, accompanied by the dynamic expression of cell adhesion molecules and estrogen-responsive genes. We identified different stages of erythroid cells such as burst-forming unit erythroid (BFU-E) and orthochromatic erythroblasts (ortho-E) and found that the regulation of TFs (e.g., TFDP1 and FOXO3) is erythroid-stage specific. Immune erythroid cells were identified in our system. This study provides systematic theoretical guidance for optimizing the iPSCs-derived RBCs differentiation system, and this system is a useful model for simulating in vivo hematopoietic development and differentiation. | developmental biology |
Bacterial lipopolysaccharide induces settlement and metamorphosis in a marine larva How larvae of the many phyla of marine invertebrates find places appropriate for settlement, metamorphosis, growth and reproduction is an enduring question in marine science. Biofilm induced metamorphosis has been observed in marine invertebrate larvae from nearly every major marine phylum. Despite the widespread nature of this phenomenon the mechanism of induction remains poorly understood. The serpulid polychaete Hydroides elegans is a well-established model for investigating bacteria-induced larval development. A broad range of biofilm bacterial species elicit larval metamorphosis in H. elegans via at least two mechanisms, including outer membrane vesicles and phage-tail bacteriocins. We investigated the interaction between larvae of H. elegans and the inductive bacterium Cellulophaga lytica, which produces an abundance of OMVs but not phage-tail bacteriocins. We asked whether the OMVs of C. lytica induce larval settlement due to cell membrane components or through delivery of specific cargo. Employing a biochemical structure-function approach with a strong ecological focus, the cells and outer membrane vesicles produced by C. lytica were interrogated to determine the nature of the inductive molecule. Here we report that the cue produced by C. lytica that induces larvae of H. elegans to metamorphose is lipopolysaccharide (LPS). The widespread prevalence of LPS and its associated taxonomic and structural variability suggest it may be a broadly employed cue for bacterially induced larval settlement of marine invertebrates.
Significance StatementNew surfaces in the sea are quickly populated by dense communities of invertebrate animals, whose establishment and maintenance require site-specific settlement of larvae from the plankton. Although it is recognized that larvae selectively settle in sites where they can metamorphose and thrive, and that the biofilm bacteria residing on these surfaces supply inductive cues, the nature of the cues used to identify right places has remained enigmatic. In this paper, we reveal that lipopolysaccharide (LPS) from the outer membrane of a marine Gram-negative bacterium cue metamorphosis for a marine worm and discuss the likelihood that LPS provides the variation necessary to explain settlement site selectivity for many of the bottom-living invertebrate animals that metamorphose in response to bacterial biofilms. | ecology |
Cascading Epigenomic Analysis for Identifying Disease Genes from the Regulatory Landscape of GWAS Variants The majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, comprises two types of models: one for linking cis genetic effects to epigenomic variation and another for linking cis epigenomic variation to gene expression. Applying these models in cascade to GWAS summary statistics generates gene level statistics that reflect genetically-driven epigenomic effects. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes. CEWAS thus presents a novel means for exploring the regulatory landscape of GWAS variants in uncovering disease mechanisms.
SummaryThe majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, combines the effect of genetic variants on DNA methylation as well as gene expression. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes. | bioinformatics |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.