Biology subjects

Foster, L. J.

Publications and source records attributed to Foster, L. J..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Climatic predictors of prominent honey bee (Apis mellifera) disease agents: Varroa destructor, Melissococcus plutonius, and Vairimorpha spp.

Improving our understanding of how climate influences honey bee parasites and pathogens is critical as weather patterns continue to shift under climate change. While the prevalence of diseases vary according to regional and seasonal patterns, the influence of specific climatic predictors has rarely been formally assessed. To address this gap, we analyzed how occurrence and intensity of three prominent honey bee disease agents (Varroa destructor [-] hereon Varroa [-] Melissococcus plutonius, and Vairimorpha spp.) varied according to regional, temporal, and climatic factors in honey bee colonies across five Canadian provinces. We found strong regional effects for all disease agents, with consistently high Varroa intensity and infestation probabilities and high M. plutonius infection probabilities in British Columbia, and year-dependent regional patterns of Vairimorpha spp. spore counts. Increasing wind speed and precipitation were linked to lower Varroa infestation probabilities, whereas warmer temperatures were linked to higher infestation probabilities. Analysis of an independent dataset shows that these trends for Varroa are consistent within a similar date range, but temperature is the strongest climatic predictor of season-long patterns. Vairimorpha spp. intensity decreased over the course of the summer, with the lowest spore counts found at later dates when temperatures were warm. Vairimorpha spp. intensity increased with wind speed and precipitation, consistent with inclement weather limiting defecation flights. Probability of M. plutonius infection generally increased across the spring and summer, and was also positively associated with inclement weather. These data contribute to building a larger dataset of honey bee disease agent occurrence that is needed in order to predict how epidemiology may change in our future climate.

molecular biology↗

bioRxiv2024

HumanIslets: An integrated platform for human islet data access and analysis

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

systems biology↗

bioRxiv2024

Population origin, body mass, and viral infections influence drone honey bee (Apis mellifera) heat tolerance

Extreme temperatures associated with climate change are expected to impact the physiology and fertility of a variety of insects, including honey bees. Most previous work has focused on female honey bees, and comparatively little research has investigated how heat exposure affects males (drones). To address this gap, we tested how body mass, viral infections, Africanization, and geographic origin (including stocks from Australia, California, and Ukraine as well as diverse locations within British Columbia, Canada) influenced drone and sperm heat tolerance. We found that individual body size was highly influential, with heavier drones being more likely to survive a heat challenge than smaller drones. Drones originating from feral colonies in Southern California (which are enriched for African genetics) were also more likely to survive a heat challenge than drones originating from commercially-supplied Californian stock. We found no association between drone mass and thermal tolerance of sperm over time in an in vitro challenge assay, but experimental viral infection decreased the heat tolerance of sperm. Overall, there is ample variation in sperm heat tolerance, with sperm from some groups displaying remarkable heat resilience and sperm from others being highly sensitive, with additional factors influencing heat tolerance of the drones themselves.

physiology↗

bioRxiv2024

Parallel pheromone, metabolite, and lipid analyses reveal patterns associated with early life transitions and ovary activation in honey bee (Apis mellifera) queens

Eusocial insects exist in a state of reproductive conflict in which workers forgo reproduction in favor of helping relatives, typically queens, rear offspring. The honest signal hypothesis posits that queens emit pheromonal signals that convey information about their fecundity, which workers use to make decisions around investing in direct vs. indirect fitness and queen acceptance. We evaluated this idea using liquid chromatography-tandem mass spectrometry to measure honey bee queen retinue pheromone (QRP) components in relation to queen age, laying status, and likelihood of acceptance using a protocol that enables QRP to be measured concurrently with metabolomic and lipidomic analyses. We found that older mated queens (>1 month) were more readily accepted by colonies than younger queens (10-12 d), regardless of the queens prior laying status. This is despite non-laying queens having significantly smaller ovaries at the time of introduction. Older queens produced higher levels of the QRP components 9(R)-HDA, LEA, and HVA compared to younger queens, with HVA also positively correlating with ovary mass. However, these data suggest that ovary mass is not an influential fertility metric for worker decision-making; therefore, the relationship between HVA and ovary mass is merely an honest signal of a non-influential metric. Metabolomic and lipidomic analyses showed that samples cluster strongly according to queen age and mating status, but not ovary mass. These data also reveal some of the first hints of the importance of prostanoids in queen maturation, along with many other physiological changes that occur in the first month of a queens life. Significance statementInsect pheromones have historically been evaluated using gas chromatography-mass spectrometry, a technique that is incompatible with parallel lipidomics and metabolomics inquests. Here, we repurposed an established two-phase extraction protocol and optimized a liquid chromatography-tandem mass spectrometry method to acquire pheromone, metabolite, and lipid data concurrently from a single sample. We applied this technique to interrogate the honest signal hypothesis, which relates queen pheromone profiles to reproductive quality, but the approach is broadly applicable to any question in which simultaneous determination of complex pheromone profiles and lipidomics or metabolomics data is asset. Such applications may help uncover new pheromones and reveal relationships between pheromones, hormones, and physiology in diverse biological systems.

molecular biology↗

bioRxiv2024

Higher prevalence of sacbrood virus in highbush blueberry pollination units

Highbush blueberry pollination depends on managed honey bees (Apis mellifera) for adequate fruit set; however, beekeepers have raised concerns about poor health of colonies after pollinating this crop. Postulated causes include agrochemical exposure, nutritional deficits, and interactions with parasites and pathogens, particularly Melisococcus plutonius(the causal agent of European foulbrood disease), but other pathogens could be involved. To broadly investigate common honey bee pathogens in relation to blueberry pollination, we sampled adult honey bees from colonies at time points corresponding to before (t1), during (t2), at the end (t3), and after (t4) highbush blueberry pollination in British Columbia (BC), Canada, across two years (2020 and 2021). Nine viruses as well as M. plutonius, Vairimorpha ceranae and V. apis (formerly Nosema ceranae and N. apis) were detected by PCR and microscopy and compared among colonies located near and far from blueberry fields. We found a significant interactive effect of time and blueberry proximity on the multivariate pathogen community, mainly due to differences at t4 (corresponding to roughly six weeks after the beginning of the pollination period). Post-hoc comparisons of pathogens in near and far groups at t4 showed that detections of sacbrood virus (SBV), which was significantly higher in the exposed group, was the primary driver. The association of SBV with highbush blueberry pollination may be contributing to the health decline that beekeepers observe after pollinating this crop, likely in combination with other factors.

zoology↗

bioRxiv2024

Glutathione metabolism impacts fungal virulence by modulating the redox environment

Pathogens must overcome the hostile conditions of their hosts to survive, proliferate and cause disease. The fungal pathogen Cryptococcus neoformans is particularly adept at mitigating challenges in the host environment and has developed an arsenal of defense mechanisms to evade oxidative and nitrosative agents released by phagocytic cells during infection. Among these mechanisms, melanin production is crucially linked to both fungal virulence and defense against harmful free radicals that facilitate host innate immunity and clearance of invading pathogens. Here, we employed comparative global metabolomics to demonstrate that metabolism of the antioxidant glutathione (GSH) is inextricably linked to redox-active processes that facilitate melanin production, and that genetic perturbations in GSH biosynthesis affect fungal growth and virulence in a murine model of cryptococcosis. Furthermore, we show that disruption of GSH biosynthesis leads to overaccumulation of reducing and acidic compounds in the extracellular environment of mutant cells. These changes not only impacted melanin formation but also influenced titan cell and urease production as well as survival in macrophages. Overall, these findings highlight the importance of redox homeostasis and metabolic compensation in pathogen adaptation to the host environment and suggest new avenues for antifungal drug development.

microbiology↗

bioRxiv2023

No trade-off between ovary activation and immune protein expression in female bumble bees (Bombus impatiens)

Evidence for a trade-off between reproduction and immunity has manifested in many animal species, including social insects. However, investigations in social insect queens present a conundrum: new gynes of many social hymenopterans, such as bumble bees and ants, must first mate, then transition from being solitary to social as they establish their nests, thus experiencing confounding shifts in environmental conditions. Worker bumble bees offer an opportunity to investigate patterns of immune protein expression associated with ovary activation while minimizing extraneous environmental factors and genetic differences. Here, we use proteomics to interrogate the patterns of immune protein expression of female bumble bees (Bombus impatiens) by 1) sampling queens at different stages of their life cycle, then 2) by sampling workers with different degrees of ovary activation. Patterns of immune protein expression in the hemolymph of queens are consistent with a reproduction-immunity trade-off, but equivalent samples from workers are not. This brings into question whether queen bumble bees really experience a reproduction-immunity trade-off, or if patterns of immune protein expression may actually be due to the selective pressure of the different environmental conditions they are exposed to during their life cycle.

physiology↗

bioRxiv2022

Cleavage of 14-3-3ϵ by the enteroviral 3C protease dampens RIG-I mediated antiviral signaling

Viruses have evolved diverse strategies to evade the host innate immune response and promote infection. The RIG-I-like-receptors RIG-I and MDA5 (RLRs) are antiviral factors that sense viral RNA and signal downstream via mitochondrial antiviral-signaling protein (MAVS) to activate type I interferon (IFN) expression. 14-3-3{varepsilon} is a key component of the RIG-I translocon complex that interacts with MAVS at the mitochondrial membrane; however, the exact role of 14-3-3{varepsilon} in this pathway is not well understood. In this study, we demonstrate that 14-3-3{varepsilon} is a direct substrate of both the poliovirus and coxsackievirus B3 (CVB3) 3C proteases (3Cpro), and that it is cleaved at Q236{downarrow}G237, resulting in the generation of N- and C-terminal fragments of 27.0 and 2.1 kDa, respectively. Expression of the N-terminal cleavage fragment in cells reduces IFNB mRNA production during poly(I:C) stimulation, thus suggesting an antagonistic effect in the presence of the endogenous 14-3-3{varepsilon} protein. The N-terminal 14-3-3{varepsilon} fragment does not interact with RIG-I in co-immunoprecipitation assays, nor can it facilitate RIG-I translocation to the mitochondria. Probing the intrinsically disordered C-terminal region identifies key residues responsible for RIG-I signaling. Finally, overexpression of the N-terminal fragment promotes CVB3 infection and influenza A virus (H1N1) RNA production and reduces IFNB mRNA production during infection. The strategic enterovirus 3Cpro-mediated cleavage of 14-3-3{varepsilon} antagonizes RIG-I signaling by disrupting critical interactions within the RIG-I translocon complex, thus contributing to evasion of the host antiviral response. Author SummaryHost antiviral factors work to sense virus infection through various mechanisms, including a complex signaling pathway known as the RIG-I like receptor (RLR) pathway. This pathway drives the production of antiviral molecules known as interferons, which are necessary to establish an antiviral state in the cellular environment. Key to this antiviral signaling pathway is the small chaperone protein 14-3-3{varepsilon}, which facilitates the delivery of a viral sensor protein, RIG-I, to the mitochondria. In this study, we show that the enteroviral 3C protease cleaves 14-3-3{varepsilon} during infection, rendering it incapable of facilitating this antiviral response. We also find that the cleavage fragment inhibits RIG-I signaling and promotes virus infection. Our findings reveal a novel viral strategy that restricts the antiviral host response and provides insights into the mechanisms underlying 14-3-3{varepsilon} function in RIG-I antiviral signaling.

microbiology↗

bioRxiv2022

Multiple viral protein genome-linked proteins compensate viral translation in +ssRNA virus infection

Viral protein genome-linked (VPg) protein plays an essential role in protein-primed replication of plus stranded RNA viruses. VPg is covalently linked to the 5 end of the viral RNA genome via a phosphodiester bond typically at a conserved amino acid. Whereas most viruses have a single VPg, some viruses encode multiple VPgs that are proposed to have redundant yet undefined roles in viral replication. Here, we use the dicistrovirus, cricket paralysis virus (CrPV), which encodes four non-identical copies of VPg, as a model to characterize the role of VPg copies in infection. Dicistroviruses encode two main open reading frames (ORFs) that are driven by distinct IRESs. We systematically generated single and combinatorial deletions and mutations of VPg1-4 within the CrPV infectious clone and monitored viral yield in Drosophila S2 cells. Deletion of one to three VPg copies progressively decreased viral yield and delayed viral replication, suggesting a threshold number of VPgs for productive infection. Mass spectrometry analysis of CrPV VPg-linked RNAs revealed viral RNA linkage to either a serine or threonine in VPg, from which mutations in all VPgs attenuated infection. Mutating serine 4 in a single VPg abolished viral infection, indicating a dominant-negative effect. Using viral minigenome reporters that monitor dicistrovirus 5 untranslated (UTR) and intergenic internal ribosome entry site (IRES) translation revealed a relationship between VPg copy number and the ratio of distinct IRES translation. We uncover a novel viral strategy whereby VPg copies in dicistrovirus genomes compensate for the relative IRES translation efficiencies to promote infection. ImportanceGenetic duplication is exceedingly rare in small RNA viral genomes as there is selective pressure to prevent RNA genomes from expanding. However, some small RNA viruses encode multiple copies of a viral protein, most notably an unusual viral protein that is linked to the viral RNA genome. Here, we investigate a family of viruses that contains multiple viral protein genome-linked proteins and reveal a novel viral strategy whereby viral protein copy number counterbalances differences in viral protein synthesis mechanisms.

microbiology↗

bioRxiv2022

Development of a Method Combining Peptidiscs and Proteomics to Identify, Stabilize and Purify a Detergent-Sensitive Membrane Protein Assembly

The peptidisc membrane mimetic enables global reconstitution of the bacterial membrane proteome into water-soluble detergent-free particles, termed peptidisc libraries. We present here a method that combines peptidisc libraries and chromosomal-level gene tagging technology with affinity purification and mass spectrometry (AP/MS) to stabilize and identify fragile membrane protein complexes that exist at native expression levels. This method circumvents common artifacts caused by bait protein overproduction and protein complex dissociation due to lengthy exposure to detergents during protein isolation. Using the E. coli Sec system as a case study, we identify an expanded version of the translocon, termed the HMD complex, consisting of 9 different integral membrane subunits. This complex is stable in peptidiscs but dissociates in detergent. Guided by this native-level proteomic information, we design and validate a procedure that enables purification of the HMD complex with minimal protein dissociation. These results highlight the utility of peptidiscs and AP/MS to discover and stabilize fragile membrane protein assemblies.

biochemistry↗

bioRxiv2021

Synaptic Activity-Dependent Changes in the Hippocampal Palmitoylome

Dynamic protein S-palmitoylation is critical for neuronal function, development, and synaptic plasticity. Activity-dependent changes in palmitoylation have been observed for several neuronal substrates, however a full characterization of the activity-regulated palmitoylome is lacking. Here, we use an unbiased approach to identify differentially palmitoylated proteins in the mouse hippocampus following context-dependent fear conditioning. Of the 121 differentially palmitoylated proteins identified 63 were synaptic proteins, while others were associated with metabolic functions, cytoskeletal organization, and signal transduction. The vast majority of synaptic proteins exhibited increased palmitoylation following fear conditioning, whereas proteins that exhibited decreased palmitoylation were predominantly associated with metabolic processes. We show a link between dynamic palmitoylation and synapse plasticity by demonstrating that the palmitoylation of one of our identified proteins, PRG-1/LPPR4, is essential for activity-induced insertion of AMPA receptors into the postsynaptic membrane. Together, this study identifies networks of synaptic proteins whose dynamic palmitoylation may play a central role in learning and memory. SUMMARYThis study identifies networks of proteins that undergo dynamic post-translational palmitoylation in response to fear conditioning and demonstrates that palmitoylation of one of these proteins is essential for synapse plasticity. Together, this illustrates the importance of palmitoylation in learning/memory and synapse plasticity.

neuroscience↗

bioRxiv2021

Nanodiscs-based proteomics identify Caj1 as an Hsp40 with affinity for phosphatidic acid lipids

Many soluble proteins interact with membranes to perform important biological functions, including signal transduction, regulation, transport, trafficking and biogenesis. Despite their importance, these protein-membrane interactions are difficult to characterize due to their often-transient nature as well as phospholipids poor solubility in aqueous solution. Here, we employ nanodiscs - small, water-soluble patches of lipid bilayer encircled with amphipathic scaffold proteins - along with quantitative proteomics to identify lipid-binding proteins in S. cerevisiae. Using nanodiscs reconstituted with yeast total lipid extracts or only phosphatidylethanolamine (PE-nanodiscs), we capture several known membrane-interacting proteins, including the Rab GTPases Sec4 and Ypt1, which play key roles in vesicle trafficking. Utilizing PE-nanodiscs enriched with phosphatidic acid (PEPA-nanodiscs), we specifically capture a member of the Hsp40/J-protein family, Caj1, whose function has recently been linked to membrane protein quality control. We show that Caj1 interaction with liposomes containing PA is modulated by pH and PE lipids, and depends on two patches of positively charged residues near the C-terminus of the protein. The protein Caj1 is the first example of an Hsp40/J-domain protein with affinity for membranes and phosphatidic acid lipid specificity. These findings highlight the utility of the nanodisc system to identify and characterize protein-lipid interactions that may not be evident using other methods.

biochemistry↗

bioRxiv2021

Proteomic portraits reveal evolutionarily conserved and divergent responses to spinal cord injury

Despite the emergence of promising therapeutic approaches in preclinical studies, the failure of large-scale clinical trials leaves clinicians without effective treatments for acute spinal cord injury (SCI). These trials are hindered by their reliance on detailed neurological examinations to establish outcomes, which inflate the time and resources required for completion. Moreover, therapeutic development takes place in animal models whose relevance to human injury remains unclear. Here, we address these challenges through targeted proteomic analyses of CSF and serum samples from 111 acute SCI patients and, in parallel, a large animal (porcine) model of SCI. We develop protein biomarkers of injury severity and recovery, including a prognostic model of neurological improvement at six months with an AUC of 0.91, and validate these in an independent cohort. Through cross-species proteomic analyses, we dissect evolutionarily conserved and divergent aspects of the SCI response, and establish the CSF abundance of glial fibrillary acidic protein (GFAP) as a biochemical outcome measure in both humans and pigs. Our work opens up new avenues to catalyze translation by facilitating the evaluation of novel SCI therapies, while also providing a resource from which to direct future preclinical efforts.

neuroscience↗

bioRxiv2020

Proteomic analysis of metabolic pathways shows chloroplast-mitochondria cross-talk in a Cu-limited diatom

Diatoms are one of the most successful phytoplankton groups in our oceans, being responsible for over 20% of the Earths photosynthetic productivity. Their chimeric genomes have genes derived from red algae, green algae, bacteria and heterotrophs, resulting in multiple isoenzymes targeted to different cellular compartments with the potential for differential regulation under nutrient limitation. The resulting interactions between metabolic pathways are not yet fully understood. We previously showed how acclimation to Cu limitation enhanced susceptibility to overreduction of the photosynthetic electron transport chain and its reorganization to favor photoprotection over light-harvesting in the oceanic diatom Thalassiosira oceanica (Hippmann et al., 2017). In order to gain a better understanding of the overall metabolic changes that help alleviate the stress of Cu limitation, we have further analyzed the comprehensive proteomic datasets generated in that study to identify differentially expressed proteins involved in carbon, nitrogen and oxidative stress-related metabolic pathways. Metabolic pathway analysis showed integrated responses to Cu limitation. The up-regulation of ferredoxin (Fdx) was correlated with up-regulation of plastidial Fdx-dependent isoenzymes involved in nitrogen assimilation as well as enzymes involved in glutathione synthesis, thus integrating nitrogen uptake and metabolism with photosynthesis and oxidative stress resistance. The differential expression of glycolytic isoenzymes located in the chloroplast and mitochondria may enable them to channel both excess electrons and/or ATP between these compartments. Additional evidence for chloroplast-mitochondrial cross-talk is the increased expression of chloroplast and mitochondrial proteins involved in the proposed malate shunt under Cu limitation. One sentence summaryDiatoms adapt to Cu limitation by regulating their large repertoire of isoenzymes to channel electrons away from the chloroplast, enhance nitrogen uptake, and integrate the oxidative stress response. 123

microbiology↗

bioRxiv2020

Frequent assembly of chimeric complexes in the protein interaction network of an interspecies hybrid

Hybrids between species often show extreme phenotypes, including some that take place at the molecular level. In this study, we investigated the phenotypes of an interspecies diploid hybrid in terms of protein-protein interactions inferred from protein correlation profiling. We used two yeast species, Saccharomyces cerevisiae and Saccharomyces uvarum, which are interfertile, but yet have proteins diverged enough to be differentiated using mass spectrometry. Most of the protein-protein interactions are similar between hybrid and parents, and are consistent with the assembly of chimeric complexes, which we validated using an orthogonal approach for prefoldin complex. We also identify instances of altered protein-protein interactions in the hybrid, for instance in complexes related to proteostasis and in mitochondrial protein complexes. Overall, this study uncovers likely frequent occurrence of chimeric protein complexes with few exceptions, which may result from incompatibilities or imbalances between the parental proteins.

evolutionary biology↗

bioRxiv2020

On the robustness of graph-based clustering to random network alterations

Biological functions emerge from complex and dynamic networks of protein-protein interactions. Because these protein-protein interaction networks, or interactomes, represent pairwise connections within a hierarchically organized system, it is often useful to identify higher-order associations embedded within them, such as multi-member protein-complexes. Graph-based clustering techniques are widely used to accomplish this goal, and dozens of field-specific and general clustering algorithms exist. However, interactomes can be prone to errors, especially interactomes that infer interactions using high-throughput biochemical assays. Therefore, robustness to network-level variability is an important criterion for any clustering algorithm that aims to generate robust, reproducible clusters. Here, we tested the robustness of a range of graph-based clustering algorithms in the presence of network-level noise, including algorithms common across domains and those specific to protein networks. We found that the results of all clustering algorithms measured were profoundly sensitive to injected network noise. Randomly rewiring 1% of network edges yielded up to a 57% change in clustering results, indicating that clustering markedly amplified network-level noise. However, the impact of network noise on individual clusters was not uniform. We found that some clusters were consistently robust to injected network noise while others were not. Therefore, we developed the clust.perturb R package and Shiny web application, which measures the reproducibility of clusters by randomly perturbing the network. We show that clust.perturb results are predictive of real-world cluster stability: poorly reproducible clusters as identified by clust.perturb are significantly less likely to be reclustered across experiments. We conclude that quantifying the robustness of a cluster to network noise, as implemented in clust.perturb, provides a powerful tool for ranking the reproducibility of clusters, and separating stable protein complexes from spurious associations.

bioinformatics↗

bioRxiv2020

Candidate stress biomarkers for queen failure diagnostics

BackgroundQueen failure is a persistent problem in beekeeping operations, but in the absence of overt symptoms it is often difficult, if not impossible, to ascertain the root cause. Stressors like heat-shock, cold-shock, and sublethal pesticide exposure can reduce stored sperm viability and lead to cryptic queen failure. Previously, we suggested candidate protein markers indicating heat-shock in queens, which we investigate further here, and tested new stressors to identify additional candidate protein markers. ResultsWe found that heat-shocking queens for upwards of one hour at 40 {degrees}C was necessary to induce significant changes in the two strongest candidate heat-shock markers, and that relative humidity significantly influenced the degree of activation. In blind heat-shock experiments, we tested the efficiency of these markers at assigning queens to their respective treatment groups and found that one marker was sufficient to correctly assign queens 75% of the time. Finally, we compared cold-shocked queens at 4 {degrees}C and pesticide-exposed queens to controls to identify candidate markers for these additional stressors, and compared relative abundances of all markers to queens designated as healthy and failing by beekeepers. ConclusionsThis work offers some of the first steps towards developing molecular diagnostic tools to aid in determining cryptic causes of queen failure. Further work will be necessary to determine how long after the stress event a markers expression remains changed and how accurate these could be in the field.

biochemistry↗

bioRxiv2019

Cell type prioritization in single-cell data

We present a machine-learning method to prioritize the cell types most responsive to biological perturbations within high-dimensional single-cell data. We validate our method, Augur (https://github.com/neurorestore/Augur), on a compendium of single-cell RNA-seq, chromatin accessibility, and imaging transcriptomics datasets. We apply Augur to expose the neural circuits that enable walking after paralysis in response to spinal cord neurostimulation.

genomics↗