Biology subjects

Srivastava, P.

Publications and source records attributed to Srivastava, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Integrative Cross-Cohort Meta-Analysis Reveals a Conserved Dysbiotic Signature of Streptococcaceae and Lachnospiraceae in Multiple Sclerosis

BackgroundMultiple Sclerosis (MS) is a chronic autoimmune disorder characterized by inflammation and demyelination in central nervous system (CNS). Although increasing evidence suggests that gut microbial dysbiosis contributes to MS pathogenesis through the microbiota-gut-brain axis, reproducible microbial signatures associated with disease progression across independent clinical cohorts remain incompletely characterized. ObjectiveThis study aimed to identify conserved gut microbial alterations associated with Multiple Sclerosis by integrating publicly available human gut microbiome datasets and characterizing disease-associated microbial signatures linked to immune dysregulation. DesignHuman gut metagenomic 16S rRNA sequencing data from MS patients and healthy controls obtained from publicly available repositories (NCBI, Bioproject). Raw sequencing reads were processed using a standardized microbiome analysis workflow, including quality control, denoising, taxonomic assignment, phylogenetic reconstruction, diversity analyses, and differential abundance testing. Microbial community structure was evaluated using alpha- and beta-diversity analyses, while statistically significant differences between study groups were assessed using PERMANOVA, Kruskal-Wallis, and ANCOM to identify disease-associated bacterial taxa. ResultsIntegration of independent cohorts revealed consistent alterations in the gut microbial composition of MS patients compared with healthy controls. Significant reductions in microbial diversity and distinct microbial community structures were observed in MS. Differential abundance analysis demonstrated enrichment of the pro-inflammatory family Streptococcaceae, whereas beneficial short-chain fatty acid-producing taxa, particularly Lachnospiraceae, were significantly depleted in MS patients. These conserved microbial alterations indicate disruption of immune-regulatory bacterial communities and support the involvement of gut microbial dysbiosis in MS-associated neuroinflammation. ConclusionThis study identifies a reproducible gut microbial dysbiosis signature associated with Multiple Sclerosis, characterized by expansion of pro-inflammatory bacterial taxa and depletion of beneficial SCFA-producing microorganisms. These findings strengthen the evidence supporting the microbiota-gut-brain axis in MS pathogenesis and highlight microbial community signatures that may contribute to future biomarker development and microbiome- based therapeutic strategies.

microbiology↗

bioRxiv2025

Transcriptome Network Biology Reveals the Neuroprotective Potential of Rosmarinic Acid Against Frontotemporal Dementia

Frontotemporal dementia (FTD) is a neurodegenerative disorder characterised by impaired behaviour and language. It affects individuals between 45 and 65 years of age. The present study aims to identify potential phytochemicals against target receptor of FTD. Transcriptome data analysis guided computer-aided drug design (CADD) was conducted to investigate molecular interactions between active phytochemicals present in Indian spices and differentially expressed genes. In present study, samples for patients with FTD were obtained from GEO dataset [GSE92340]. The samples were pre-processed followed by differential gene expression analysis using DESeq2. The patient sample was analyzed for 1882 upregulated genes. Hub gene out of DEGs was identified using CytoHubba Plugin of Cytoscape based on eleven parameters (Degree, Edge Percolated Component (EPC), Maximum Neighbourhood Component (MNC), Density of Maximum Neighbourhood Component (DMNC), Maximal Clique Centrality (MCC), Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress). HDAC1 gene was identified as hub gene and key target in case of FTD. CADD pipeline was used to identify phytochemicals against HDAC1 gene. A list of eighty-one phytochemicals found in Indian spices was analyzed for their drug likeness abilities using molinspiration and toxicity prediction using ProTox-II, which identified twenty-three phytochemicals as safe drug-like compounds. PatchDock was employed to examine interactions between phytochemical compounds and HDAC1. Molecular interactions revealed rosmarinic acid derived from rosemary (Salvia rosmarinus) as the most effective drug for FTD having lowest ACE value of -395 kcal/mol. In conclusion, this study demonstrates essential role of HDAC1 in pathogenesis of FTD and demonstrates the neuroprotective potential of rosmarinic acid against FTD.

bioinformatics↗

bioRxiv2025

U1 snRNP and RNA polymerase II interaction is predominantly mediated by Prp40 rather than U1-70K in yeast

Transcription and splicing are coupled both temporally and physically. A previous cryo-EM structure of the human U1 snRNP and RNA polymerase pol II complex has shown that U1 snRNP uses predominantly the RRM domain of U1-70K to directly interact with the RPB2 subunit of pol II. However, residues on U1-70K involved in the interaction with pol II are not conserved in yeast U1-70K, raising the question whether yeast U1 snRNP interacts with pol II in a similar manner. We found that yeast pol II associates with both U1 and U2 snRNPs, but U1-70K makes a minimal contribution to U1 snRNPs interaction with pol II. On the other hand, multiple domains of yeast Prp40 interact with pol II and the removal of the C-terminal domain (CTD) of pol II does not affect this interaction. Although yeast Prp40 is stably associated with U1 snRNP, its human homologs, PRPF40a and PRPF40b, are alternative splicing factors that are not integral components of U1 snRNP. This shift of function of Prp40 homologs may have led to the evolution of U1-70K to be the main interactor with pol II in the human system.

biochemistry↗

bioRxiv2025

Discovery of Prognostic Biomarkers in Gastric Cancer Through Machine Learning and Bioinformatics Analysis of Gene Expression Data

Gastric cancer (GC) often gets diagnosed in its advanced stages, resulting in poorer prognoses. To identify potential biomarkers in GC, we used fifteen datasets from NCBI-GEO and integrated them into a complete dataset. From the complete dataset, we extracted a subset of only the known cancer driver genes. Using Recursive Feature Elimination (RFE), mutual information (MI), and tree-based (TB) method (SelectFromModel), we extracted top gene features using RFE (10, 20, 30, 40, and 50) and 50 features each from MI and TB method. Subsequently, we applied machine learning classifiers to these selected gene features to classify cancer and normal samples. The SVC classifiers demonstrated better performance when utilizing the top 50 gene features using RFE and MI, while the AB classifier achieved the highest performance using TB for the complete dataset and for driver datasets, RF performed well using 40 features using RFE and SVC, and ET showed up better performance using 50 features using MI and TB feature selection for the test dataset. After combining all the genes from both datasets from and from all three feature selection methods, only 115 showed differentially expressed genes. A Lasso-penalized Cox regression model was applied to narrow down the gene selection to fourteen. This study highlights the effectiveness of integrating machine learning and bioinformatics analysis to identify new biomarkers for GC.

bioinformatics↗

bioRxiv2025

Discrimination of Normal from Slow-Aging Mice by Plasma Metabolomic and Proteomic Features

Tests that can predict whether a drug is likely to extend mouse lifespan could speed up the search for anti-aging drugs. We have applied a machine learning algorithm, XGBoost regression, to seek sets of plasma metabolites that can discriminate control mice from mice treated with an anti-aging diet (caloric restriction) or any of four anti-aging drugs. When the model is trained on any four of these five interventions, it predicts significantly higher lifespan extension in mice exposed to the intervention which was not included in the training set. Plasma peptide data sets also succeed at this task. Models trained on drug-treated normal mice also discriminate long-lived mutant mice from their respective controls, and models trained on males can discriminate drug-treated from control females. Triglycerides are over-represented among the most influential features in the regression models. Triglycerides with longer fatty acid chains tend to be higher in the slow-aging mice, while triglycerides with shorter fatty acid chains tend to decrease. Plasma metabolite patterns may help to select the most promising anti-aging drugs in mice or in humans, and may give new leads into physiological and enzymatic targets relevant to discovery of new anti-aging drugs.

bioinformatics↗

bioRxiv2024

Chemical degradation identified Human p38-MAPK as a host target to combat parasitic infections

The interplay between host and parasite determines parasite burden and disease outcome. Parasite exploits host signaling pathways like p38-MAPK for its survival and pathogenesis. NR-7h, a proteolysis-targeting chimera (PROTAC) targeting human p38-MAPK was used to assess p38-MAPKs role in Leishmania donovani and Plasmodium falciparum infection in their respective hosts. NR-7h degraded host p38-MAPK in a time- and dose-dependent manner. Degradation of host p38-MAPK by NR-7h reduced parasite load in host cells dose-dependently, implicating the role of p38-MAPK in parasite survival. The modulation of cytokine profiling and oxidative burst upon NR-7h mediated degradation of host p38-MAPK was further correlated with parasite death. The synergistic effect of host p38-MAPK degradation by NR-7h with Amphotericin B enhances the efficacy of parasite-directed therapy. This study underscores the importance of host p38-MAPK for L. donovani and P. falciparum progression and highlights NR-7hs potential in antiparasitic therapy by targeting this pathway.

microbiology↗

bioRxiv2024

The Oviposition Inhibitory Neuron is a potential hub of multi-circuit integration in the Drosophila brain

Understanding how neural circuits integrate sensory and state information to support context-dependent behavior is a central challenge in neuroscience. Oviposition is a complex process during which a fruit fly integrates context and sensory information to choose an optimal location to lay her eggs. The circuit that controls oviposition is known, but how the oviposition circuit integrates multiple sensory modalities and internal states is not. Using the Hemibrain connectome, we identified the Oviposition Inhibitory Neuron (oviIN) as a key hub in the oviposition circuit and analyzed its inputs to uncover potential parallel pathways that may be responsible for computations related to sensory integration and decision-making. We applied a network analysis to the subconnectome of inputs to the oviIN to identify clusters of interconnected neurons - many of which are uncharacterized cell types. Our findings indicate that the inputs to oviIN form multiple parallel pathways through the unstructured neuropils of the Superior Protocerebrum, a region implicated in context-dependent processing. Significance StatementThe recent advent of the Drosophila connectome enables researchers to probe the connectivity of uncharacterized cell types in the parts of the fruit fly brain that are responsible for cognitive-level computations. Our study analyzed the connectivity of the oviposition circuit which controls a complex behavior that depends on sensory and context integration and decision-making computations. Using graph theoretic and computational methods, we found that the sole inhibitory neuron in the circuit is a hub that integrates information from multiple clusters of uncharacterized neurons with potentially novel functions. Our work presents a new and timely perspective by demonstrating how new targets for study can be identified from the vast trove of uncharacterized neurons and cell types in the connectome.

neuroscience↗

bioRxiv2024

Immunogenicity and protection efficacy of self-amplifying and circular mRNA vaccines for SARS-CoV-2

Recent advances in vaccine technology have positioned messenger RNA (mRNA) vaccines as safe and reliable options for human use. Conventionally, mRNA vaccines were designed using linear or self-amplifying mRNA (SAM), the latter considered to be superior. However, limited success was achieved with SAM vaccines during the COVID-19 pandemic. Further, studies on Circular mRNA (Circ-RNA) vaccines against the SARS-CoV-2, Ebola and monkey pox proved their efficacy. Circ-RNAs are highly stable, neither they induce inflammatory response nor require any extracellular protein for their function. Here, we compared the efficacy of SAM- and Circ-RNA vaccines using the SARS-CoV-2-RBD (receptor binding domain) as the antigen. Both SAM-RBD and Circ-RBD induced a comparable anti-RBD IgG titer and virus-neutralizing antibody titer. However, the latter induced a significantly higher memory T-cell response. Immunization with SAM- and Circ-RBD showed no mortality and improved lung pathophysiology against acute SARS-CoV-2 infection in mice. The Circ-RBD vaccine is stable for 4 weeks at 40C. A bivalent vaccine containing Circ-RBD of both delta and omicron SARS-CoV-2 variants potently neutralized these viruses. These findings demonstrate Circ-RNA-RBD as an excellent vaccine candidate against COVID-19 and also provide a platform for developing bivalent Circ-RNA vaccine candidates against SARS-CoV-2 or other viruses with rapidly emerging variants.

microbiology↗

bioRxiv2024

Cone bipolar cell synapses generate transient versus sustained signals in parallel ON pathways of the mouse retina

Parallel processing is a fundamental organizing principle in the nervous system and understanding how parallel neural circuits generate distinct outputs from common inputs is a key goal of neuroscience. In the mammalian retina, divergence of cone signals into multiple feedforward bipolar cell pathways forms the initial basis for parallel retinal circuits dedicated to specific visual functions. Here, we used patch-clamp electrophysiology, electron microscopy and two photon imaging of a fluorescent glutamate sensor to examine how kinetically-distinct responses arise in transient versus sustained ON alpha RGCs (ON-T and ON-S RGCs) of the mouse retina. We directly compared the visual response properties of these RGCs with their presynaptic bipolar cell partners, which we identified using 3D electron microscopy reconstruction. Different ON bipolar cell subtypes (type 5i, type 6 and type 7) had indistinguishable light-driven responses whereas extracellular glutamate signals around RGC dendrites and postsynaptic excitatory currents measured in ON-T and ON-S RGCs in response to the identical stimuli used to probe bipolar cells were kinetically distinct. Anatomical examination of the bipolar cell axon terminals presynaptic to ON-T and ON-S RGCs suggests that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools may contribute to transient versus sustained kinetics. Our findings indicate that feedforward bipolar cell synapses are a primary point of divergence in kinetically distinct visual pathways.

neuroscience↗

bioRxiv2023

Identification of merozoite secreted repertoire and immuno-pharmacological inhibition of a novel host-parasite interaction to block malarial infection

BackgroundDuring the intra-erythrocytic proliferation of Plasmodium falciparum, the host erythrocyte invasion is regarded as a complex and tightly regulated process comprising multiple receptor-ligand interactions, and numerous secretory molecules. Proteins secreted sequentially from apical organelles of merozoites serve as adhesins that play a crucial role in RBC invasion and can serve as vaccine and therapeutic targets. MethodsPurified merozoites were triggered to discharge apical organelle contents by exposure to ionic conditions mimicking that of blood plasma. The secreted proteins were subjected to tandem mass spectrometry, and a well-characterized invasion ligand, RhopH3, was identified. A novel RhopH3 receptor, 14-3-3{square} was unearthed using a Bacterial two-hybrid approach. This interaction was confirmed using multiple biophysical and biochemical approaches. We were successful in disrupting this interaction using a de novo peptide binder of 14-3-3{square}, and we subsequently assessed its effect on merozoite invasion. ResultsA total of 66 proteins were identified in the secretory fraction with apical organellar or merozoite membrane localization. The well-known adhesin, RhopH3 was also identified and its interaction with the host phosphopeptide-binding protein, 14-3-3{square} was established. We also discovered a de novo peptide with the potency to disrupt this crucial interaction, thereby blocking merozoite invasion. ConclusionWe, for the first time, report the secretory repertoire of plasmodium merozoite. Our study shows the importance of the erythrocyte protein, 14-3-3{square} during the invasion process and paves the way for developing anti-malarial peptides or small molecules that inhibit the host-pathogen interaction, hence abrogating the invasion process.

microbiology↗

bioRxiv2023

ProT-VAE: Protein Transformer Variational AutoEncoder for Functional Protein Design

The data-driven design of protein sequences with desired function is challenged by the absence of good theoretical models for the sequence-function mapping and the vast size of protein sequence space. Deep generative models have demonstrated success in learning the sequence to function relationship over natural training data and sampling from this distribution to design synthetic sequences with engineered functionality. We introduce a deep generative model termed the Protein Transformer Variational AutoEncoder (ProT-VAE) that furnishes an accurate, generative, fast, and transferable model of the sequence-function relationship for data-driven protein engineering by blending the merits of variational autoencoders to learn interpretable, low-dimensional latent embeddings and fully generative decoding for conditional sequence design with the expressive, alignment-free featurization offered by transformers. The model sandwiches a lightweight, task-specific variational autoencoder between generic, pre-trained transformer encoder and decoder stacks to admit alignment-free training in an unsupervised or semi-supervised fashion, and interpretable low-dimensional latent spaces that facilitate understanding, optimization, and generative design of functional synthetic sequences. We implement the model using NVIDIAs BioNeMo framework and validate its performance in retrospective functional prediction and prospective design of novel protein sequences subjected to experimental synthesis and testing. The ProT-VAE latent space exposes ancestral and functional relationships that enable conditional generation of novel sequences with high functionality and substantial sequence diversity. We anticipate that the model can offer an extensible and generic platform for machine learning-guided directed evolution campaigns for the data-driven design of novel synthetic proteins with "super-natural" function.

synthetic biology↗

bioRxiv2022

Motile Living Biobots Self-Construct from Adult Human Somatic Progenitor Seed Cells

Fundamental knowledge gaps exist with respect to the plasticity of cells from adult soma and the potential diversity of body shape and behavior in living constructs derived from such genetically wild-type cells. Here we introduce Anthrobots, a spheroid-shaped multicellular biological robot (biobot) platform with diameters ranging from 30 to 500 microns. Anthrobots have an inherent capacity for motility in aqueous environments, via cilia covering their surface. Each Anthrobot starts out as a single cell, derived from the adult human lung, and self-constructs into a multicellular motile biobot after having been cultured in extra cellular matrix for 2 weeks and transferred into a minimally viscous habitat. Anthrobots exhibit a wide range of behaviors with motility patterns ranging from tight loops to straight lines and speeds ranging from 5-50 microns/second. Our anatomical investigations reveal that this behavioral diversity is significantly correlated with their morphological diversity. Anthrobots can assume diverse morphologies from fully polarized to wholly ciliated bodies with spherical or ellipsoidal shapes, each correlating with a distinct movement type. Remarkably, as a function of these different movement types, Anthrobots were found to be capable of traversing live human tissues in various ways. Furthermore, Anthrobots were able to induce rapid repair of wounds in human neural cell sheets in vitro. By controlling microenvironmental cues in bulk, entirely novel structure, behavior, and biomedically-relevant capabilities can be discovered in morphogenetic processes without direct genetic editing or manual sculpting. Significance StatementWe demonstrate that normal, non-genetically-modified human tracheal cells can be induced to form a new proto-organism - Anthrobots - which exhibit spontaneous behavior, swimming around in one of several patterns, demonstrating plasticity for novel form and function inherent in even elderly human somatic cells. Moreover, Anthrobots are able to traverse over cultured neurons, settling down and causing repair under them: the nerves knit together across the wound gap due to the presence of the Anthrobot. A patients own cells can be harnessed to make a motile biological robot that can traverse human tissue and induce repair. In the future, this platform can deliver pro-regenerative therapeutics for a range of biomedical applications that will not trigger rejection or require immune suppression.

bioengineering↗

bioRxiv2022

Dynamic changes in the niche and transcription trigger early murine and human pluripotent stem cell-derived liver organogenesis

The shift from collective migration to differentiation is a crucial process in epithelial biology but recreating this intricate transition has thus far proved elusive. We provide experimental, mechanistic, in vivo, and bioinformatic data supporting an undoubtable link between human pluripotent stem cell (hPSC)- derived collectively migrating hepatoblasts (MHB), and transcriptionally mature, functional hPSC- hepatocytes (HEPs), which incorporates two unrecognized steps. The protocol induces FOXA-dependent induction of HBs, leading to TBX3-positive, YAP-TEAD active MHBs which provide a transcriptional match with murine liver E9.5 MHBs. Simple cultivation changes trigger MHBs to rapidly form functional day 18 HEPs, predicted by a deep-learning designed gene circuit, resulting in a [~]236% fold- increase in maturation (PACNet), on par with the highest score, but with enhanced global transcriptional shaping. Overall, incorporating the MHB to HEP transition establishes a new, unrecognized, and highly efficient mechanism for differentiation that can be cumulatively integrated with existing methods to overcome barriers to maturation.

bioengineering↗

bioRxiv2022

Spatiotemporal properties of glutamate input support direction selectivity in the dendrites of retinal starburst amacrine cells

AO_SCPLOWBSTRACTC_SCPLOWThe asymmetric summation of kinetically distinct glutamate inputs across the dendrites of retinal "starburst" amacrine cells is proposed to underlie their direction selective properties, but experimentally verifying input kinetics has been a challenge. Here, we used two-photon glutamate sensor (iGluSnFR) imaging to directly measure the input kinetics across individual starburst dendrites. We found that signals measured from proximal dendrites were relatively sustained compared to those measured from distal dendrites. These differences were observed across a range of stimulus sizes and appeared to be shaped mainly by excitatory rather than inhibitory network interactions. Temporal deconvolution analysis suggests that the steady-state vesicle release rate was [~] 3 times larger at proximal sites compared to distal sites. Using a connectomics-inspired computational model, we demonstrate that input kinetics play an important role in shaping direction selectivity at low stimulus velocities. Together, these results provide direct support for the space-time wiring model for direction selectivity.

neuroscience↗

bioRxiv2022

The slowdown of growth rate controls the single-cell distribution of biofilm matrix production via a SinI-SinR-SlrR network

In Bacillus subtilis, a master regulator Spo0A controls several cell-differentiation pathways. Under moderate starvation, phosphorylated Spo0A (Spo0A~P) induces biofilm formation by indirectly activating genes controlling matrix production in a subpopulation of cells via a SinI-SinR-SlrR network. Under severe starvation, Spo0A~P induces sporulation by directly and indirectly regulating sporulation gene expression. However, what determines the heterogeneity of individual cell fates is not fully understood. In particular, it is still unclear why, despite being controlled by a single master regulator, biofilm matrix production and sporulation are mutually exclusive on a single-cell level. In this work, with mathematical modeling, we showed that the fluctuations in the growth rate and the intrinsic noise amplified by the bistability in the SinI-SinR-SlrR network could explain the single-cell distribution of matrix production. Moreover, we predicted an incoherent feed-forward loop: the decrease in the cellular growth rate activates matrix production by increasing in Spo0A phosphorylation level but represses it via changing the relative concentrations of SinR and SlrR. Experimental data provide evidence to support model predictions. In particular, we demonstrate how the degree to which matrix production and sporulation appear mutually exclusive is affected by genetic perturbations. ImportanceThe mechanisms of cell-fate decisions are fundamental to our understanding of multicellular organisms and bacterial communities. However, even for the best-studied model systems we still lack a complete picture of how phenotypic heterogeneity of genetically identical cells is controlled. Here, using B. subtilis as a model system, we employ a combination of mathematical modeling and experiments to explain the population-level dynamics and single-cell level heterogeneity of biofilm gene expression. The results demonstrate how the two cell fates, biofilm matrix production and sporulation, can appear mutually exclusive without explicitly inhibiting one another. Such a mechanism could be used in a wide range of other biological systems.

systems biology↗

bioRxiv2022

A novel consensus-based computational pipeline for rapid screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including omicron variant

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike proteins receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with three-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero-dimeric and -trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concern (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variants RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118) -- that may likely neutralize the recently emerged omicron variant -- facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.

bioinformatics↗

bioRxiv2022

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes

Understanding the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unsolved challenge for the scientific communities across the world. A key to dissect the susceptibility profiles of animal species to SARS-CoV-2 is to understand how virus enters into the cells. The interaction of SARS-CoV-2 ligands (RBD on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the spike protein of SARS-CoV-2 can bind to many vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Additionally, the present study facilitated the identification of genetic determinants that may differentiate susceptible from the resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified susceptibility of bat species to SARS-CoV-2. The findings from current study highlight the importance of intensive surveillance programs aimed at identifying susceptible hosts, particularly those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

bioinformatics↗

bioRxiv2021

Defined microenvironments trigger in vitro gastrulation in human pluripotent stem cells

Embryogenesis is orchestrated through local morphogen gradients and endometrial constraints that give rise to the three germ layers in a well-defined assembly. In vitro models of embryogenesis have been demonstrated by treating pluripotent stem cells in adherent or suspension culture with soluble morphogens and small molecules, which leads to tri-lineage differentiation. However, treatment with exogenous agents override the subtle spatiotemporal changes observed in vivo that ultimately underly the human body plan. Here we demonstrate how microconfinement of pluripotent stem cells on hydrogel substrates catalyses gastrulation-like events without the need for supplements. Within six hours of initial seeding, cells at the boundary show elevated cytoskeletal tension and yes-associated protein (YAP) activity, which leads to changes in cell and nuclear morphology, epithelial to mesenchymal transition, and emergence of defined patterns of primitive streak containing SRY-Box Transcription Factor 17 (SOX17)+ T/BRACHYURY+ cells. Immunofluorescence staining, transcript analysis, and the use of pharmacological modulators reveal a role for mechanotransduction-coupled non-canonical wingless-type (WNT) signalling in promoting epithelial to mesenchymal transition and multilayered organization within the colonies. These microscale gastruloids were removed from the substrate and encapsulated in 3D hydrogels, where biomaterials properties correspond to maintenance and spatial positioning of the primitive streak. Together, this approach demonstrates how materials alone can nurture embryonic gastrulation, thereby providing an in vitro model of early development.

bioengineering↗