Biology subjects

Roy, S.

Publications and source records attributed to Roy, S..

At least 253 records · Page 14Linked to original sources

bioRxiv2021

Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants are typically unknown. Furthermore, a regulatory variant might influence a particular genes expression in a cell type or tissue-specific manner. Cell-type specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offers a powerful framework for understanding the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of model cell lines. To address this challenge, we have developed L-HiC-Reg, a Random Forests based regression method to predict high- resolution contact counts in new cell lines, and a network-based framework to identify candidate cell line-specific gene networks targeted by a set of variants from a Genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenome Consortium cell lines, which we used to interpret regulatory SNPs in the NHGRI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including Schizophrenia, Coronary Artery Disease (CAD) and Crohns disease. In CAD, we found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and associated network-based analysis pipeline offers a powerful resource to leverage long-range regulatory interactions to examine the context-specific impact of regulatory variation in complex phenotypes.

bioinformatics↗

bioRxiv2021

Experimental and mathematical models of intracellular calcium dynamics for evaluating combined anticancer effects of Afatinib and RP4010 in esophageal cancer

Targeting dysregulated Ca2+ signaling in cancer cells is an emerging chemotherapy approach. We previously reported that store-operated Ca2+ entry (SOCE) blockers, such as RP4010, are promising antitumor drugs for esophageal cancer. As a tyrosine kinase inhibitor (TKI), afatinib received FDA approval to be used in targeted therapy for patients with EGFR mutation-positive cancers. While preclinical studies and clinical trials have shown that afatinib has benefits for esophageal cancer patients, it is not known whether combination of afatinib and RP4010 could achieve better anticancer effects. Since TKI can alter intracellular Ca2+ dynamics through EGFR/phospholipase C-{gamma} pathway, in this study, we evaluated the inhibitory effect of afatinib and RP4010 on intracellular Ca2+ oscillations in esophageal cancer cells using both experimental and mathematical simulations. Our mathematical simulation of Ca2+ oscillations could fit well with experimental data responding to aftinib or RP4010, separately or in combination. The results showed that combination of afatinib and RP4010 presented synergistic anticancer effect. This intracellular Ca2+ dynamic-based mathematical simulation approach could be useful for a rapid and cost-effective evaluation of combined targeting therapy drugs.

cancer biology↗

bioRxiv2021

Temporal change in chromatin accessibility predicts regulators of nodulation in Medicago truncatula

Rhizobia can establish symbiotic associations with legumes to provide plants with nitrogen needed in agricultural systems. Symbiosis triggers extensive genome and transcriptome remodeling in the plant, yet the extent of chromatin changes and impact on gene expression is unknown. We profiled the temporal chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) dynamics of M. truncatula roots treated with rhizobia lipo-chitooligosaccharides. Using a novel approach, Dynamic Regulatory Module Networks, we predicted gene expression as a function of chromatin accessibility and accessible cis-regulatory elements. This approach identified the cis-regulatory elements and associated transcription factors that most significantly contribute to transcriptomic changes triggered by lipo-chitooligosaccharides. Regulators involved in auxin (IAA4-5,SHY2), ethylene (EIN3, ERF1) and abscisic acid (ABI5) hormone response, as well as histone and DNA methylation (IBM1), emerged among those most predictive of transcriptome dynamics. RNAi-based knockdown of EIN3 and ERF1 reduced nodule number in M. truncatula validating the role of these predicted regulators in symbiosis between legumes and rhizobia. Significance StatementLegumes can fix nitrogen through symbiosis with rhizobia in root nodules, a critical mutualistic relationship for crop productivity and agricultural sustainability. Introducing this symbiotic relationship into non-legume crops is of great interest, but limited knowledge of host genome modifications induced by rhizobia has hampered such efforts. We applied time-course analysis of chromatin accessibility and gene expression of M. truncatula roots treated with rhizobia lipochitooligosaccharides. We show that extensive remodeling of genome accessibility drives a large component of the temporal transcriptome dynamics. By predicting gene expression as a function of accessibility of regulatory features, we identified known and novel regulators that are associated with early nodule development, which may be critical for its engineering into crops.

plant biology↗

bioRxiv2021

Tankyrase interacts with the allosteric site of glucokinase and inhibits its glucose-sensing function in the beta cell

Insulin secretion in the pancreatic beta cell is rate-limited by glucokinase (GCK), the glucose sensor that catalyzes the first step of glucose metabolism. GCK consists of two lobes connected by a flexible hinge that allows the kinase to exhibit a spectrum of conformations ranging from the active, closed form to several inactive, less-compact forms. Activating GCK mutations can cause hyperinsulinemia and hypoglycemia in infants. A similar phenotype exhibited by tankyrase (TNKS)-deficient mice prompted us to investigate whether TNKS might modulate the glucose-sensing function of GCK. We found that TNKS colocalizes and directly interacts with GCK. Their interaction is mediated by two ankyrin-repeat clusters (ARC-2 and -5) in TNKS and a tankyrase-binding motif (TBM, aa 63-68) in the GCK hinge. This interaction is conformation sensitive, human GCK variants that cause hyperglycemia (V62M) or hypoglycemia (S64Y) enhance or diminish the interaction respectively, even though they have no impact on TNKS interaction in the context of a GCK peptide (V62M) or a peptide library (S64Y). Moreover, the TNKS-GCK interaction is inhibited by high glucose concentrations, which are known to stabilize GCK in the active (closed, glucose-avid) conformation. Conversely, glucose phosphorylation by GCK in vitro is inhibited by TNKS. To study this in vitro inhibitory effect in the MIN6 beta cells, we showed that glucose-stimulated insulin secretion is suppressed upon stabilization of the TNKS protein and is conversely enhanced upon TNKS knockdown. Based on these findings as well as by contrasting with hexokinase-2, we propose that TNKS is a physiological GCK inhibitor in pancreatic beta cells that acts by trapping the kinase in the open (inactive) conformation.

cell biology↗

bioRxiv2021

Functional and comparative genomics reveals conserved noncoding sequences in the nitrogen-fixing clade

Nitrogen is one of the most inaccessible plant nutrients, but certain species have overcome this limitation by establishing symbiotic interactions with nitrogen-fixing bacteria in the root nodule. This root nodule symbiosis (RNS) is restricted to species within a single clade of angiosperms, suggesting a critical evolutionary event at the base of this clade, which has not yet been determined. While genes implicated in the RNS are present in most plant species (nodulating or not), gene sequence conservation alone does not imply functional conservation - developmental or phenotypic differences can arise from variation in the regulation of transcription. To identify putative regulatory sequences implicated in the evolution of RNS, we aligned the genomes of 25 species capable of nodulation. We detected 3,091 conserved noncoding sequences (CNS) in the nitrogen-fixing clade that are absent from outgroup species. Functional analysis revealed that chromatin accessibility of 452 CNS significantly correlates with the differential regulation of genes responding to lipo-chitooligosaccharides in Medicago truncatula. These included 38 CNS in proximity to 19 known genes involved in RNS. Five such regions are upstream of MtCRE1, Cytokinin Response Element 1, required to activate a suite of downstream transcription factors necessary for nodulation in M. truncatula. Genetic complementation of a Mtcre1 mutant showed a significant association between nodulation and the presence of these CNS, when they are driving the expression of a functional copy of MtCRE1. Conserved noncoding sequences, therefore, may be required for the regulation of genes controlling the root nodule symbiosis in M. truncatula.

plant biology↗

bioRxiv2021

GIV/Girdin binds BRCA1 and links trimeric G-proteins to DNA damage response

Upon sensing DNA double-strand breaks (DSBs), eukaryotic cells either die or repair DSBs via one of two competing pathways, i.e., non-homologous end-joining (NHEJ) or homologous recombination (HR). We show that cell fate after DNA damage hinges on the guanine nucleotide-exchange modulator of heterotrimeric G-protein, Gi*{beta}{gamma}, GIV/Girdin. GIV suppresses HR by binding and sequestering BRCA1, a key coordinator of multiple steps within the HR pathway, away from DSBs; it does so using a C-terminal motif that binds BRCA1s BRCT-modules via both phospho-dependent and -independent mechanisms. GIV promotes NHEJ, and binds and activates Gi and enhances the free G{beta}{gamma}[->]PI-3-kinase[->]Akt pathway, thus revealing the enigmatic origin of prosurvival Akt signals during dsDNA repair. Absence of GIV, or the loss of either of its two functions impaired DNA repair, and induced cell death when challenged with numerous cytotoxic agents. That GIV selectively binds few other BRCT-containing proteins suggests convergent signaling such that heterotrimeric G-proteins may finetune sensing, repair, and outcome after DNA damage. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/452842v3_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@3d5202org.highwire.dtl.DTLVardef@1d32d89org.highwire.dtl.DTLVardef@152a85dorg.highwire.dtl.DTLVardef@1ab9953_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LINon-receptor G protein modulator, GIV/Girdin binds BRCA1 C_LIO_LIBinding occurs in both canonical and non-canonical modes C_LIO_LIGIV sequesters BRCA1 away from dsDNA breaks, suppresses HR C_LIO_LIActivation of Gi by GIV enhances Akt signals, favors NHEJ C_LI IN BRIEFIn this work, the authors show that heterotrimeric G protein signaling that is triggered by non-receptor GEF, GIV/Girdin, in response to double-stranded DNA breaks is critical for decisive signaling events which favor non-homologous end-joining (NHEJ) and inhibit homologous recombination (HR).

cancer biology↗

bioRxiv2021

Increased intestinal permeability in an orally-reactive peanut allergy model identifies Angiopoietin like-4 as a biomarker

Peanut allergy reaction severity correlates with increased intestinal epithelial cell (IEC) barrier permeability. CC027/GeniUnc mice develop peanut allergy by intragastric administration of peanut proteins without adjuvant. We report that peanut-allergic CC027/GeniUnc mice showed increased IEC barrier permeability and systemic peanut allergen Ara h 2 after challenge. Jejunal epithelial cell transcriptomics showed effects of peanut allergy on IEC proliferation, survival, and metabolism, and revealed IEC-predominant angiopoietin like-4 (Angptl4) as a unique feature of CC027/GeniUnc peanut allergy. CC027/GeniUnc mice and peanut-allergic pediatric patients demonstrated significantly higher serum Angptl4 and ANGPTL4 compared to control C3H/HeJ mice and non-peanut-allergic but atopic patients, respectively, highlighting its potential as a biomarker of peanut allergy.

cell biology↗

bioRxiv2021

Parallel Framework for Inferring Genome-Scale Gene Regulatory Networks

Genome-scale network inference is essential to understand comprehensive interaction patterns. Current methods are limited to the reconstruction of small to moderate-size networks. The most obvious alternative is to propose a novel method or alter existing methods that may leverage parallel computing paradigms. Very few attempts also have been made to re-engineer existing methods by executing selective iterative steps concurrently. We propose a generic framework in this paper that leverages parallel computing without re-engineering the original methods. The proposed framework uses state-of-the-art methods as a black box to infer sub-networks of the segmented data matrix. A simple merger was designed based on preferential attachment to generate the global network by merging the sub-networks. Fifteen (15) inference methods were considered for experimentation. Qualitative and speedup analysis was carried out using DREAM challenge networks. The proposed framework was implemented on all the 15 inference methods using large expression matrices. The results were auspicious as we could infer large networks in reasonable time without compromising the qualitative aspects of the original (serial) algorithm. CLR, the top performer, was then used to infer the network from the expression profiles of an Alzheimers disease (AD) affected mouse model consisting of 45,101 genes. We have also highlighted few hub genes from the network that are functionally related to various diseases.

bioinformatics↗

bioRxiv2021

Co-clinical FDG-PET Radiomic Signature in Predicting Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer

PurposeWe sought to exploit the heterogeneity afforded by patient-derived tumor xenografts (PDX) to optimize robust radiomic features associated with response to therapy in the context of a co-clinical trial and implement PDX-optimized image features in the corresponding clinical study to predict and assess response to therapy using machine-learning (ML) algorithms. MethodsTNBC patients and subtype-matched PDX were recruited into a co-clinical FDG-PET imaging study to predict response to therapy. One hundred thirty-one imaging features were extracted from PDX and human segmented tumors. Robust image features were identified based on reproducibility, cross-correlation, and volume independence. A rank importance of predictors using ReliefF was used to identify predictive radiomic features in the preclinical PDX trial in conjunction with ML algorithms: classification and regression tree (CART), Naive Bayes (NB), and support vector machines (SVM). The top four PDX-optimized image features, defined as radiomic signatures (RadSig), from each task were then used to predict or assess response to therapy. Performance of RadSig in predicting/assessing response was compared to SUVmean, SUVmax, and lean body mass normalized SULpeak measures. ResultsSixty-four out of 131 preclinical imaging features were identified as robust. NB-RadSig performed highest in predicting and assessing response to therapy in the preclinical PDX trial. In the clinical study, the performance of SVM-RadSig and NB-RadSig to predict and assess response was practically identical and superior to SUVmean, SUVmax, and SULpeak, measures. ConclusionsWe optimized robust FDG-PET radiomic signatures (RadSig) to predict and assess response to therapy in a context of a co-clinical imaging trial. DECLARATIONSO_ST_ABSFundingC_ST_ABSThis work was supported by NCI grants U24CA209837, U24CA253531, and U54CA224083; U2CCA233303, and K12CA167540; Siteman Cancer Center (SCC) Support Grant P30CA091842; and Internal funds provided by Mallinckrodt Institute of Radiology. Conflicts of interest/Competing interests.None. Availability of data and materialAll the co-clinical data will be available for download through the Washington University School of Medicine Co-Clinical Imaging Research Resource web portal at https://c2ir2.wustl.edu/, co-clinical database (CCDB). Code availabilityNot applicable. Authors contributionsConceptualization: SR, FOA, KIS; Methodology: SR, TDW, SL, KIS; Formal analysis and investigation: SR, KIS; Writing - original draft preparation: SR; Writing - review and editing: RLW, FD, KIS; Funding acquisition: RWL, FOA, SL, KIS; Resources: SL; Supervision: FD, KIS. All authors read and approved the final manuscript. Ethics approvalAll studies were performed with approval from the Washington University Humans subjects research committee and animal studies committee. Consent to participateInformed consent to participate in the study was obtained from all participants. Consent for publicationNot applicable.

bioinformatics↗

bioRxiv2021

Correlation in Domain Fluctuations Navigates Target Search of a Viral Peptide along RNA

Biological macromolecules often exhibit correlation in fluctuations involving distinct domains. This study decodes their functional implications in RNA-protein recognition and target-specific binding. The target search of a peptide along RNA in viral TAR-Tat complex is closely monitored using atomistic simulations, steered molecular dynamics simulations, free energy calculations, and a machine-learning-based clustering technique. An anti-correlated domain fluctuation is identified between the tetraloop and the bulge region in the apo form of TAR RNA that sets a hierarchy in the domain-specific fluctuations at each binding event and that directs succeeding binding footsteps. Thus, at each binding footstep, the dynamic partner selects an RNA location for binding where it senses higher fluctuation, which is conventionally reduced upon binding. This event stimulates an alternate domain-fluctuation which then dictates sequential binding footstep/s and thus, the search progresses. Our cross-correlation maps show that the fluctuations relay from one domain to another specific domain till the anti-correlation between that inter-domain fluctuations sustains. Artificial attenuation of that hierarchical domain fluctuation inhibits specific RNA binding. The binding is completed with the arrival of a few long-lived water molecules that mediate slightly distant RNA-protein sites and finally stabilizes the overall complex. The study underscores the functional importance of naturally designed fluctuating RNA motifs (bulge, tetraloop) and their interplay in dictating the directionality of the search in a highly dynamic environment.

biophysics↗

bioRxiv2021

Cytotoxic and micronuclei inducing effects of petroleum ether fraction of leaf aqueous extract of Clerodendrum viscosum Vent. in Allium cepa root tip cells

Clerodendrum viscosum is a traditionally used medicinal plant. The present study aimed to analyze a detailed cytotoxic effect of the nonpolar petroleum ether fraction (AQPEF) of leaf aqueous extract of C. viscosum Vent. (LAECV) in Allium cepa root tip cells. The LAECV was fractionated with petroleum ether and tested for A. cepa toxicity at early hours (2 and 4 h treatment) at concentrations 0, 50, 100, 150 and 200 {micro}g mL-1. The highest aberrant cell percentage (10.45{+/-}0.46%) was scored from 150 {micro}g mL-1 followed by100 {micro}g mL-1 (8.75{+/-}0.26%) concentration at 4 h treated samples. The AQPEF treatment induced a significant (p<0.0001) increase in micronuclei frequency; 4.31{+/-}0.33, 5.08{+/-}0.13, 5.05{+/-}0.22 and 3.05{+/-}0.37% respectively at concentrations 50, 100, 150, and 200 {micro}g mL-1. The highest polyploid frequency (20.14{+/-}0.68 %) induced with 100 {micro}g mL-1 of AQPEF at 16 h recovery. 150 {micro}g mL-1 is the most effective concentration of AQPEF to decipher its activity similar to colchicine (150 {micro}g mL-1). In summary, the present study indicates petroleum ether is suitable for extraction of the active phytochemicals of LAECV having cytotoxic effects on A. cepa root tip cells. The AQPEF has colchicine like micronuclei, polyploidy, and mitotic abnormality inducing potentials in A. cepa root apical meristem cells.

pharmacology and toxicology↗

bioRxiv2021

Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data

Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional programs of different cellular states by measuring the transcriptome of thousands of individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regulatory networks and a number of methods with different learning frameworks have been developed to address this problem. Here, we present an expanded benchmarking study of eleven recent network inference methods on six published scRNA-seq datasets in human, mouse, and yeast considering different types of gold standard networks and evaluation metrics. We evaluate methods based on their computing requirements as well as on their ability to recover the network structure. We find that, while most methods have a modest recovery of experimentally derived interactions based on global metrics such as Area Under the Precision Recall curve, methods are able to capture targets of regulators that are relevant to the system under study. Among the top performing methods that use only expression were SCENIC, PIDC, MERLIN or Correlation. Addition of prior biological knowledge and the estimation of transcription factor activities resulted in the best overall performance with the Inferelator and MERLIN methods that use prior knowledge outperforming methods that use expression alone. We found little to no benefit from imputation for network inference, which is further dataset-dependent. Comparisons of inferred networks for comparable bulk conditions showed that the networks inferred from scRNA-seq datasets are often better or at par with the networks inferred from bulk datasets. Our analysis should be beneficial in selecting methods for network inference. At the same time, this highlights the need for improved methods and better gold standards for regulatory network inference from scRNAseq datasets.

bioinformatics↗

bioRxiv2021

Multiview super-resolution microscopy

We enhance the performance of confocal microscopy over imaging scales spanning tens of nanometers to millimeters in space and milliseconds to hours in time, improving volumetric resolution more than 10-fold while simultaneously reducing phototoxicity. We achieve these gains via an integrated, four-pronged approach: 1) developing compact line-scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; 2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; 3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labeled, thick samples; 4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than twenty distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae, and adults; myoblasts in Drosophila wing imaginal disks; and mouse renal, esophageal, cardiac, and brain tissues.

bioengineering↗

bioRxiv2021

Inference of tissue relative proportions of the breast epithelial cell types luminal progenitor, basal, and luminal mature

Single-Cell Analysis has revolutionised genomic science in recent years. However, due to cost and other practical considerations, single-cell analyses are impossible for studies based on medium or large patient cohorts. For example, a single-cell analysis usually costs thousands of euros for one tissue sample from one volunteer, meaning that typical studies using single-cell analyses are based on very few individuals. While single-cell genomic data can be used to examine the phenotype of individual cells, cell-type deconvolution methods are required to track the quantities of these cells in bulk-tissue genomic data. Hormone receptor negative breast cancers are highly aggressive, and are thought to originate from a subtype of epithelial cells called the luminal progenitor. In this paper, we show how to quantify the number of luminal progenitor cells as well as other epithelial subtypes in breast tissue samples using DNA and RNA based measurements. We find elevated levels of cells which resemble these hormone receptor negative luminal progenitor cells in breast tumour biopsies of hormone receptor negative cancers, as well as in healthy breast tissue samples from BRCA1 (FANCS) mutation carriers. We also find that breast tumours from carriers of heterozygous mutations in non-BRCA Fanconi Anaemia pathway genes are much more likely to be hormone receptor negative. These findings have implications for understanding hormone receptor negative breast cancers, and for breast cancer screening in carriers of heterozygous mutations of Fanconi Anaemia pathway genes.

bioinformatics↗

bioRxiv2021

Evolution towards increasing complexity through functional diversification in a protocell model of the RNA world

The encapsulation of genetic material inside compartments together with the creation and sustenance of functionally diverse internal components are likely to have been key steps in the formation of live, replicating protocells in an RNA world. Several experiments have shown that RNA encapsulated inside lipid vesicles can lead to vesicular growth and division through physical processes alone. Replication of RNA inside such vesicles can produce a large number of RNA strands. Yet, the impact of such replication processes on the emergence of the first ribozymes inside such protocells and on the subsequent evolution of the protocell population remains an open question. In this paper, we present a model for the evolution of protocells with functionally diverse ribozymes. Distinct ribozymes can be created with small probabilities during the error-prone RNA replication process via the rolling circle mechanism. We identify the conditions that can synergistically enhance the number of different ribozymes inside a protocell and allow functionally diverse protocells containing multiple ribozymes to dominate the population. Our work demonstrates the existence of an effective pathway towards increasing complexity of protocells that might have eventually led to the origin of life in an RNA world.

biophysics↗

bioRxiv2021

Comparative in vitro antioxidant and antibacterial activities of leaf extract fractions of Crimson bottlebrush, Callistemon citrinus (Curtis.) Skeels

ObjectivesThe present study aimed to analyze a comparative in vitro free radical scavenging and antibacterial potentials of leaf aqueous and the successive extract fractions of Callistemon citrinus. MethodsFor in vitro antioxidant activity assessments, 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging activity, Fe3+ ion reducing antioxidant power (FRAP) assay, and total antioxidant capacity of the extracts were tested. Antibacterial potentials were tested through Agar well diffusion method using both gram-positive and gram-negative bacterial strains. ResultsData indicate the polar successive aqueous fraction (AQF) possesses the highest free radicals scavenging capacity, with lowest EC50 (the required extract concentration to scavenge half of the free radicals) for DPPH and FRAP assays, and contains the highest total phenolics (308.2{+/-}5.9 {micro}g tannic acid equivalent/mg dry extract, DE), flavonoids (516.7{+/-}3.5 {micro}g quercetin equivalent/mg DE), total antioxidant capacity (441.48{+/-}12.8 {micro}g ascorbic acid equivalent/mg DE). Phenolics and flavonoids contents were positively correlated with the in vitro antioxidant activities. The antibacterial study indicates the petroleum ether and chloroform are suitable solvents for extracting antibacterial phytochemicals from C. citrinus leaves that are effective against both gram-positive and negative bacterial strains. ConclusionThe most polar fraction i.e. the successive aqueous extract fraction of C. citrinus leaves exhibited the highest antioxidant activities while the most non-polar petroleum ether extract fraction showed the highest antibacterial potentials thus these extract fractions might have therapeutic importance.

pharmacology and toxicology↗

bioRxiv2021

In-vivo protein nitration and de-nitration facilitate Vibrio cholerae cell survival under anaerobic condition: Consequences of Nitrite induced protein nitration

Protein tyrosine nitration (PTN), a highly selective post translational modification, occurs in both prokaryotic and eukaryotic cells under nitrosative stress1. It is reported that the activities of many proteins are altered due to PTN2. PTN is found to be associated with many pathophysiological conditions like neurodegenerative and cardiac diseases etc.3. However, its physiological function is not yet clear. Like all other gut pathogens Vibrio cholerae also faces nitrosative stress in the gut environment which makes its proteome more vulnerable to PTN. Here, we report for the first time in-vivo PTN in V. cholerae. We show that in-vivo protein nitration is nitrite dependent and nitration-denitration phenomenon actually facilitates V. cholerae cell survival in anaerobic or hypoxic condition. In our study, we found that the extent of in-vivo nitration is negatively correlated with the intracellular nitrite content and maximum nitration occurs during log phase of V. cholerae. Most interestingly, a significant denitration was associated with increase in intracellular nitrate content during anaerobic incubation of aerobically grown late log phase cultures. In-vivo nitration could provide an avenue for toxic nitrite storage and nitrosative stress tolerance mechanism in many gut pathogens, whereas denitration could supply nitrate for cell survival in anaerobic nitrate deficient environment.

microbiology↗

bioRxiv2021

Behavior emerges from unstructured muscle activity in response to neuromodulation

Identifying neural substrates of behavior requires defining actions in terms that map onto brain activity. Brain and muscle activity naturally correlate via the output of motor neurons, but apart from simple movements it has been difficult to define behavior in terms of muscle contractions. By mapping the musculature of the pupal fruit fly and comprehensively imaging muscle activation at single cell resolution, we here describe a multiphasic behavioral sequence in Drosophila. Our characterization identifies a previously undescribed behavioral phase and permits extraction of major movements by a convolutional neural network. We deconstruct movements into a syllabary of co-active muscles and identify specific syllables that are sensitive to neuromodulatory manipulations. We find that muscle activity shows considerable variability, which reduces upon neuromodulation. Our work provides a platform for studying whole-animal behavior, quantifying its variability across multiple spatiotemporal scales, and analyzing its neuromodulatory regulation at cellular resolution.

neuroscience↗