Biology subjects

Sinha, S.

Publications and source records attributed to Sinha, S..

At least 181 records · Page 10Linked to original sources

bioRxiv2021

Sorting droplets into many outlets

Droplet microfluidics is a commercially successful technology, widely used in single cell sequencing and droplet PCR. Combining droplet making with droplet sorting has also been demonstrated, but so far found limited use, partly due to difficulties in scaling manufacture with injection molded plastics. We introduce a droplet sorting system with several new elements, including: 1) an electrode design combining metallic and ionic liquid parts, 2) a modular, multi-sorting fluidic design with features for keeping inter-droplet distances constant, 3) using timing parameters calculated from fluorescence or scatter signal triggers to precisely actuate dozens of sorting electrodes, 4) droplet collection techniques, including ability to collect a single droplet, and 5) a new emulsion breaking method to collect aqueous samples for downstream analysis. We use these technologies to build a fluorescence based cell sorter that sorts with high purity. We also show that these microfluidic designs can be translated into injection molded thermoplastic, suitable for industrial production. Finally, we tally the advantages and limitations of these devices.

bioengineering↗

bioRxiv2021

Using a recently approved tumor mutational burden biomarker to stratify patients for immunotherapy may introduce a sex bias

The U.S. Food and Drug Administration (FDA) recently approved the treatment with pembrolizumab, an immune checkpoint inhibitor (ICI) targeting PD1 (anti-PD1), for patients with advanced solid tumors with a high tumor mutational burden (TMB) (defined as TMB [≥]10 mutations/Mb). However, following recent studies suggest that TMB levels and response to ICI treatment may differ between male and female melanoma patients, we investigated whether using this high-TMB threshold for selecting patients for anti-PD1 treatment may induce a sex-dependent bias. We analyzed a large ICI cohort of 1,286 patients across nine cancer types treated with anti-PD1/PDL1. We find that using this threshold would indeed result in an unwarranted sex bias in melanoma, successfully stratifying female but not male patients. While this threshold is currently not a regulatory prerequisite for ICI treatment in melanoma, it is important to raise awareness to this bias. Notably, no sex-dependent significant differences were observed in the response of melanoma patients to anti-CTLA4 therapies, different chemotherapies or combination therapies. Beyond melanoma, the high-TMB threshold additionally introduces a sex bias of considerable magnitude in glioblastoma and in patients with cancers of unknown origin, however, these results are not statistically significant. A power analysis shows that these biases may become significant with larger sample size, warranting further careful testing in larger cohorts.

cancer biology↗

bioRxiv2021

Immune determinants of the association between tumor mutational burden and immunotherapy response across cancer types

The FDA has recently approved high tumor mutational burden (TMB), defined by [≥]10 mutations/Mb, as a biomarker for the treatment of solid tumors with pembrolizumab, an immune checkpoint inhibitor (ICI) that targets PD1. However, recent studies testify that high TMB levels are only able to stratify ICI responders in a subset of cancer types, where the mechanisms underlying this observation have remained unknown. We hypothesized that the tumor immune microenvironment (TME) may modulate the stratification power of TMB (termed TMB power) in a cancer type, leading to this observation. To systematically study this hypothesis, we analyzed TCGA expression data to infer the levels of 31 immune-related factors characteristic of the TME of different cancer types. We integrated this information with TMB and response data of 2,277 patients treated with anti-PD1 or anti-PD-L1 ICI to identify the key immune factors that can determine TMB power across 14 different cancer types. We find that high levels of M1 macrophages and low resting dendritic cells in the TME characterize cancer types with high TMB power. A model based on these two immune factors is strongly predictive of the TMB power in a given cancer type (Spearman Rho=0.76, P<3.6x10-04). Using this model, we provide predictions of the TMB power in nine additional cancer types, including rare cancers, for which TMB and ICI response data are not yet publicly available on a large scale. Our analysis indicates that TMB-High may be highly predictive of ICI response in cervical squamous cell carcinoma, suggesting that such a study should be prioritized.

cancer biology↗

bioRxiv2021

Human fetal neural stem cell-derived astrocytes maintain glutamate transport after hypoxic injury in vitro

Astrocytes are the most abundant glial cells that play many critical roles in the central nervous system physiology including the uptake of excess glutamate from the synapse by Excitatory Amino Acid Transporters (EAATs). Among the EAATs, EAAT2 are predominantly functional, astrocyte-specific glutamate transporters in the forebrain. Hypoxic brain injury is a pathological phenomenon seen in various clinical conditions including stroke and neonatal hypoxic ischemic encephalopathy. Glutamate excitotoxicity is an important cause of neuronal cell death in disorders involving hypoxic brain injury. As findings from rodent models cannot always be reliably extrapolated to humans, we aimed to develop a homogenous population of primary human astrocytes to study the effect of hypoxic injury on astrocyte function, especially glutamate uptake. We successfully isolated, established and characterized cultures of human fetal neural stem cells (FNSCs) from aborted fetal brains. FNSCs were differentiated into astrocytes, and characterized by increased expression of the astrocyte markers, glial fibrillary acidic protein (GFAP), EAAT1 and EAAT2. A concomitant decrease in neural stem cell marker, Nestin, was observed. Differentiated astrocytes were exposed to various oxygen concentrations mimicking normoxia (20% and 6%), moderate and severe hypoxia (2% and 0.2% respectively). Interestingly, no change was observed in the expression of glutamate transporter, EAAT2 and glutamate uptake by astrocytes, even after exposure to hypoxia. Our novel model of human FNSC derived astrocytes exposed to hypoxic injury, establishes that astrocytes are able to maintain glutamate uptake even after exposure to severe hypoxia for 48 hours, and thus provides evidence for the neuroprotective role of astrocytes in hypoxic injury.

neuroscience↗

bioRxiv2021

An Immune Cell Atlas Reveals Dynamic COVID-19 Specific Neutrophil Programming Amendable to Dexamethasone Therapy

SARS-CoV-2 is a novel coronavirus that causes acute respiratory distress syndrome (ARDS), death and long-term sequelae. Innate immune cells are critical for host defense but are also the primary drivers of ARDS. The relationships between innate cellular responses in ARDS resulting from COVID-19 compared to other causes of ARDS, such as bacterial sepsis is unclear. Moreover, the beneficial effects of dexamethasone therapy during severe COVID-19 remain speculative, but understanding the mechanistic effects could improve evidence-based therapeutic interventions. To interrogate these relationships, we developed an scRNA-Seq and plasma proteomics atlas (biernaskielab.ca/COVID_neutrophil). We discovered that compared to bacterial ARDS, COVID-19 was associated with distinct neutrophil polarization characterized by either interferon (IFN) or prostaglandin (PG) active states. Neutrophils from bacterial ARDS had higher expression of antibacterial molecules such as PLAC8 and CD83. Dexamethasone therapy in COVID patients rapidly altered the IFNactive state, downregulated interferon responsive genes, and activated IL1R2+ve neutrophils. Dexamethasone also induced the emergence of immature neutrophils expressing immunosuppressive molecules ARG1 and ANXA1, which were not present in healthy controls. Moreover, dexamethasone remodeled global cellular interactions by changing neutrophils from information receivers into information providers. Importantly, male patients had higher proportions of IFNactive neutrophils, a greater degree of steroid-induced immature neutrophil expansion, and increased mortality benefit compared to females in the dexamethasone era. Indeed, the highest proportion of IFNactive neutrophils was associated with mortality. These results define neutrophil states unique to COVID-19 when contextualized to other life-threatening infections, thereby enhancing the relevance of our findings at the bedside. Furthermore, the molecular benefits of dexamethasone therapy are also defined, and the identified pathways and plasma proteins can now be targeted to develop improved therapeutics.

immunology↗

bioRxiv2021

Membrane-Tethered Mucin 1 is Stimulated by Interferon in Multiple Cell Types and Antagonizes Influenza A Virus Infection in Human Airway Epithelium

Influenza A virus (IAV) causes seasonal epidemics and periodic pandemics, resulting in significant morbidity and mortality in the human population. Tethered mucin 1 (MUC1) is highly expressed in airway epithelium, the primary site of IAV replication, and also by other cell types that influence IAV infection, including macrophages. MUC1 has the potential to influence infection dynamics through physical interactions and/or signaling activity, and recent work suggests MUC1 acts as a releasable decoy receptor and anti-inflammatory molecule during IAV infection. Still, the modulation of MUC1 and its impact during viral pathogenesis remains unclear. Thus, we sought to further investigate the interplay between MUC1 and IAV in an in vitro model of primary human airway epithelium (HAE). Our data indicate that a recombinant IAV hemagglutinin (H3) and H3N2 virus can bind endogenous HAE MUC1. We find that infection of HAE cultures with H1N1 or H3N2 IAV strains does not trigger enhanced MUC1 shedding, but instead stimulates an increase in cell-associated MUC1 protein. We observed a similar increase after stimulation with either type I or type III interferon (IFN); however, inhibition of IFN signaling during H1N1 infection only partially abrogated this increase, indicating multiple soluble factors contribute to MUC1 upregulation during the antiviral response. We expanded these findings and demonstrate that in addition to HAE, primary human monocyte-derived macrophages also upregulate MUC1 protein in response to both IFN treatment and conditioned media from IAV-infected HAE cultures. We then developed HAE genetically depleted for MUC1 to determine its impact on IAV pathogenesis, finding that MUC1 knock-out cultures exhibited enhanced viral growth compared to control cultures for several IAV strains. Together, our data support a model whereby MUC1 antagonizes productive uptake of IAV in HAE. Infection then stimulates MUC1 expression on multiple cell types through IFN-dependent and -independent mechanisms that may further impact infection dynamics. Author SummaryThe mucosal surface of the respiratory epithelium is an important site of first contact for viral respiratory pathogens. Large and heavily glycosylated molecules known as tethered mucins extend from the cell surface and may physically restrict access to underlying cells. Recently, one of these tethered mucins, MUC1, has also been shown to influence cell signaling and inflammation. Still, despite its abundance in the airway and multifunctional capability, the role of MUC1 during influenza virus infection in the human respiratory tract remains unclear. Here, we demonstrate that influenza virus directly interacts with MUC1 in a physiologically-relevant model of human airway epithelium and find that MUC1 protein expression is elevated throughout the epithelium and in primary human monocyte-derived macrophages in response to important antiviral signals produced during infection. Using genetically-modified human airway cultures lacking MUC1, we then provide evidence of more efficient influenza virus infection in the absence of this mucin. Our data suggest that MUC1 not only physically restricts influenza virus uptake, but also represents a dynamic component of the host response that acts to further stem viral spread.

microbiology↗

bioRxiv2021

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks

Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression, and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer "grammar" in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.

bioinformatics↗

bioRxiv2021

Densified Collagen Tubular Grafts for Human Tissue Replacement and Disease Modelling Applications

There is a significant need across multiple indications for an off-the-shelf bioengineered tubular graft which fulfils the mechanical and biological requirements for implantation and function but does not necessarily require cells for manufacture or deployment. Herein, we present a tissue-like tubular construct using a cell-free, materials-based method of manufacture, utilizing densified collagen hydrogel. Our tubular grafts are seamless, mechanically strong, customizable in terms of lumen diameter and wall thickness, and display a uniform fibril density across the wall thickness and along the tube length. While the method enables acellular grafts to be generated rapidly, inexpensively, and to a wide range of specifications, the cell-compatible densification process also enables a high density of cells to be incorporated uniformly into the walls of the tubes, which we show can be maintained under perfusion culture. Additionally, the method enables tubes consisting of distinct cell domains with cellular configurations at the boundaries which may be useful for modelling aortic disease. Further, we demonstrate additional steps which allow for luminal surface patterning. These results highlight the universality of this approach and its potential for developing the next generation of bioengineered grafts.

bioengineering↗

bioRxiv2021

Genome-scale metabolic modeling reveals SARS-CoV-2-induced host metabolic reprogramming and identifies metabolic antiviral targets

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy.

systems biology↗

bioRxiv2021

Pancreatic cancer prognosis is predicted by a novel ATAC-array technology for assessing chromatin accessibility

We investigated tumor-cell-intrinsic chromatin accessibility patterns of pancreatic ductal adenocarcinoma (PDAC) by ATAC-seq on EpCAM+ PDAC malignant epithelial cells, sorted from 54 freshly resected human tumors, and discovered a signature of 1092 chromatin loci displaying differential accessibility between patients with disease free survival (DFS) < 1 year and patients with DFS > 1 year. Analyzing transcription factor (TF) binding motifs within these loci, we identified two TFs (ZKSCAN1 and HNF1b) displaying differential nuclear localization between patients with short vs. long DFS. We further developed a novel chromatin accessibility microarray methodology termed "ATAC-Array", an easy-to-use platform obviating the time and cost of next generation sequencing. Applying this novel methodology to the original ATAC-seq libraries as well as independent libraries generated from patient-derived organoids, we validated ATAC-array technology in both the original ATAC-Seq cohort as well as in an independent validation cohort. We conclude that PDAC prognosis can be predicted by ATAC-array, which represents a novel, lowcost, clinically feasible technology for assessing chromatin accessibility profiles.

cancer biology↗

bioRxiv2021

Human embryonic stem cell-derived cardiomyocytes express SARS-CoV-2 host entry proteins: screen to identify inhibitors of infection

Patients with cardiovascular comorbidities are more susceptible to severe infection with SARS-CoV-2, known to directly cause pathological damage to cardiovascular tissue. We outline a screening platform using human embryonic stem cell-derived cardiomyocytes, confirmed to express the protein machinery critical for SARS-CoV-2 infection, and a pseudotyped virus system. The method has allowed us to identify benztropine and DX600 as novel inhibitors of SARS-CoV-2 infection.

pharmacology and toxicology↗

bioRxiv2021

SARS-CoV-2 infection of circulating immune cells is not responsible for virus dissemination in severe COVID-19 patients

In late 2019 a novel coronavirus (SARS-CoV-2) emerged, and has since caused a global pandemic. Understanding the pathogenesis of COVID-19 disease is necessary to inform development of therapeutics, and management of infected patients. Using scRNAseq of blood drawn from SARS-CoV-2 patients, we asked whether SARS-CoV-2 may exploit immune cells as a Trojan Horse to disseminate and access multiple organ systems. Our data suggests that circulating cells are not actively infected with SARS-CoV-2, and do not appear to be a source of viral dissemination.

immunology↗

bioRxiv2020

VarSAn: Associating pathways with a set of genomic variants using network analysis

There is a pressing need today to mechanistically interpret sets of genomic variants associated with diseases. Here we present a tool called VarSAn that uses a network analysis algorithm to identify pathways relevant to a given set of variants. VarSAn analyzes a configurable network whose nodes represent variants, genes and pathways, using a Random Walk with Restarts algorithm to rank pathways for relevance to the given variants, and reports p-values for pathway relevance. It treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant and identifies relevant pathways even if many variants do not directly impact genes of the pathway. We use VarSAn to identify pathways relevant to variants related to cancer and several other diseases, as well as drug response variation. We find VarSAns pathway ranking to be complementary to the standard approach of enrichment tests on genes related to the query set. We adopt a novel benchmarking strategy to quantify its advantage over this baseline approach. Finally, we use VarSAn to discover key pathways, including the VEGFA-VEGFR2 pathway, related to de novo variants in patients of Hypoplastic Left Heart Syndrome, a rare and severe congenital heart defect.

bioinformatics↗

bioRxiv2020

Cross-neutralization of SARS-CoV-2 by HIV-1 specific broadly neutralizing antibodies and polyclonal plasma

Cross-reactive epitopes (CREs) are similar epitopes on viruses that are recognized or neutralized by same antibodies. The S protein of SARS-CoV-2, similar to type I fusion proteins of viruses such as HIV-1 envelope (Env) and influenza hemagglutinin, is heavily glycosylated. Viral Env glycans, though host derived, are distinctly processed and thereby recognized or accommodated during antibody responses. In recent years, highly potent and/or broadly neutralizing human monoclonal antibodies (bnAbs) that are generated in chronic HIV-1 infections have been defined. These bnAbs exhibit atypical features such as extensive somatic hypermutations, long complementary determining region (CDR) lengths, tyrosine sulfation and presence of insertions/deletions, enabling them to effectively neutralize diverse HIV-1 viruses despite extensive variations within the core epitopes they recognize. As some of the HIV-1 bnAbs have evolved to recognize the dense viral glycans and cross-reactive epitopes (CREs), we assessed if these bnAbs cross-react with SARS-CoV-2. Several HIV-1 bnAbs showed cross-reactivity with SARS-CoV-2 while one HIV-1 CD4 binding site bnAb, N6, neutralized SARS-CoV-2. Furthermore, neutralizing plasma antibodies of chronically HIV-1 infected children showed cross neutralizing activity against SARS-CoV-2. Collectively, our observations suggest that human monoclonal antibodies tolerating extensive epitope variability can be leveraged to neutralize pathogens with related antigenic profile. ImportanceIn the current ongoing COVID-19 pandemic, neutralizing antibodies have been shown to be a critical feature of recovered patients. HIV-1 bnAbs recognize extensively diverse cross-reactive epitopes and tolerate diversity within their core epitope. Given the unique nature of HIV-1 bnAbs and their ability to recognize and/or accommodate viral glycans, we reasoned that the glycan shield of SARS-CoV-2 spike protein can be targeted by HIV-1 specific bnAbs. Herein, we showed that HIV-1 specific antibodies cross-react and neutralize SARS-CoV-2. Understanding cross-reactive neutralization epitopes of antibodies generated in divergent viral infections will provide key evidence for engineering so called super-antibodies (antibodies that can potently neutralize diverse pathogens with similar antigenic features). Such cross-reactive antibodies can provide a blueprint upon which synthetic variants can be generated in the face of future pandemics.

immunology↗

bioRxiv2020

Mechanistic analysis of enhancer sequences in the Estrogen Receptor transcriptional program

BackgroundEstrogen Receptor (ER) is a major lineage determining transcription factor (TF) in mammary gland development, orchestrating the expression of thousands of genes. Dysregulation of ER-mediated transcriptional program results in abnormal cell proliferation and cancer. Transcriptomic and epigenomic profiling of breast cancer cell lines has revealed large numbers of enhancers involved in this regulatory program, but how these enhancers encode function in their sequence remains poorly understood. ResultsA subset of ER-bound enhancers are transcribed into short bidirectional RNA (enhancer RNA or eRNA), and this property is believed to be a reliable marker of active enhancers. We therefore analyze thousands of ER-bound enhancers and build quantitative, mechanism-aware models to discriminate eRNAs from non-transcribing enhancers based on their sequence. Our thermodynamics-based models provide insights into the roles of specific TFs in ER-mediated transcriptional program, many of which are supported by the literature. We use in silico perturbations to predict TF-enhancer regulatory relationships and integrate these findings with experimentally determined enhancer-promoter interactions to construct a gene regulatory network. We also demonstrate that the model can prioritize breast cancer-related sequence variants while providing mechanistic explanations for their function. Finally, we experimentally validate the model-proposed mechanisms underlying three such variants. ConclusionsWe modeled the sequence-to-expression relationship in ER-driven enhancers and gained mechanistic insights into the workings of a major transcriptional program. Our model is consistent with the current body of knowledge and its predictions are confirmed by experimental observations. We believe this to be a promising approach to analysis of regulatory sequences and variants.

bioinformatics↗

bioRxiv2020

Identification of potential inhibitory analogs of metastasis tumor antigens (MTAs) using bioactive compounds: revealing therapeutic option to prevent malignancy

The deeper understanding of metastasis phenomenon and detection of drug targets could be a potential approach to minimize cancer mortality. In this study, attempts were taken to unmask novel therapeutics to prevent metastasis and cancer progression. Initially, we explored the physiochemical, structural and functional insights of three metastasis tumor antigens (MTAs) and evaluated some plant based bioactive compounds as potent MTA inhibitors. From 50 plant metabolites screened, isoflavone, gingerol, citronellal and asiatic acid showed maximum binding affinity with all three MTA proteins. The ADME analysis detected no undesirable toxicity that could reduce the drug likeness properties of top plant metabolites. Moreover, molecular dynamics studies revealed that the complexes were stable and showed minimum fluctuation at molecular level. We further performed ligand based virtual screening to identify similar drug molecules using a large collection of 3,76,342 compounds from DrugBank. The results suggested that several structural analogs (e.g. Tramadol, Nabumetone, DGLA, Hydrocortisone) may act as agonist to block the MTA proteins and inhibit cancer progression at early stage. The study could be useful to develop effective medications against cancer metastasis in future. Due to encouraging results, we highly recommend further in vitro and in vivo trials for the experimental validation of the findings.

bioinformatics↗

bioRxiv2020

Beta-cell specific insulin resistance promotes glucose-stimulated insulin hypersecretion

Abstract Insulin receptor (Insr) protein can be found at higher levels in pancreatic {beta}-cells than in most other tissues, but the consequences of {beta}-cell insulin resistance remain enigmatic. Ins1cre allele was used to delete Insr specifically in {beta}-cells of both female and male mice. Experimental mice were compared to Ins1cre-containing littermate controls at multiple ages and on multiple diets. RNA-seq of purified recombined {beta}-cells revealed transcriptomic consequences of Insr loss, which differed between female and male mice. Action potential and calcium oscillation frequencies were increased in Insr knockout {beta}- cells from female, but not male mice, whereas only male {beta}InsrKO mice had reduced ATP-coupled oxygen consumption rate and reduced expression of genes involved in ATP synthesis. Female {beta}InsrKO and {beta}InsrHET mice exhibited elevated insulin release in perifusion experiments, during hyperglycemic clamps, and following i.p. glucose challenge. Deletion of Insr did not alter {beta}-cell area up to 9 months of age, nor did it impair hyperglycemia-induced proliferation. Based on our data, we adapted a mathematical model to include {beta}-cell insulin resistance, which predicted that {beta}-cell Insr knockout would improve glucose tolerance depending on the degree of whole-body insulin resistance. Indeed, glucose tolerance was significantly improved in female {beta}InsrKO and {beta}InsrHET mice when compared to controls at 9, 21 and 39 weeks, and also in insulin-sensitive 4-week old males. We did not observe improved glucose tolerance in older male mice or in high fat diet-fed mice, corroborating the prediction that global insulin resistance obscures the effects of {beta}-cell specific insulin resistance. The propensity for hyperinsulinemia was associated with mildly reduced fasting glucose and increased body weight. We further validated our main in vivo findings using the Ins1-CreERT transgenic line and found that male mice had improved glucose tolerance 4 weeks after tamoxifen-mediated Insr deletion. Collectively, our data show that loss of {beta}-cell Insr contributes to glucose-induced hyperinsulinemia, thereby improving glucose homeostasis in otherwise insulin sensitive dietary and age contexts.

physiology↗

bioRxiv2020

Individual differences in honey bee (Apis mellifera) behavior enabled by plasticity in brain gene regulatory networks

Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and "generalists" that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution.

genomics↗