Biology subjects

Jain, S.

Publications and source records attributed to Jain, S..

At least 181 records · Page 10Linked to original sources

bioRxiv2021

Systematic dissection of a complex gut bacterial community

Efforts to model the gut microbiome have yielded important insights into the mechanisms of interspecies interactions, the impact of priority effects on ecosystem dynamics, and the role of diet and nutrient availability in determining community composition. However, the model communities studied to date have been defined or complex but not both, limiting their utility. Here, we construct a defined community of 104 bacterial strains composed of the most common taxa from the human gut microbiota. By propagating this community in growth media missing one amino acid at a time, we show that branched-chain amino acids have an outsize impact on community structure and identify a pathway in Clostridium sporogenes for generating ATP from arginine. We constructed and propagated the complete set of single-strain dropout communities, revealing a sparse network of strain-strain interactions including a novel interaction between C. sporogenes and Lactococcus lactis driven by metabolism. This work forms a foundation for studying strain-strain and strain-nutrient interactions in highly complex defined communities, and it provides a starting point for interrogating the rules of synthetic ecology at the 100+ strain scale.

microbiology↗

bioRxiv2021

In vivo augmentation of a complex gut bacterial community

Efforts to model the human gut microbiome in mice have led to important insights into the mechanisms of host-microbe interactions. However, the model communities studied to date have been defined or complex but not both, limiting their utility. In accompanying work, we constructed a complex synthetic community (104 strains, hCom1) containing the most common taxa in the human gut microbiome. Here, we used an iterative experimental process to improve hCom1 by filling open metabolic and/or anatomical niches. When we colonized germ-free mice with hCom1 and then challenged it with a human fecal sample, the consortium exhibited surprising stability; 89% of the cells and 58% of the taxa derive from the original community, and the pre- and post-challenge communities share a similar overall structure. We used these data to construct a second version of the community, adding 22 strains that engrafted following fecal challenge and omitting 7 that dropped out (119 strains, hCom2). In gnotobiotic mice, hCom2 exhibited increased stability to fecal challenge and robust colonization resistance against pathogenic Escherichia coli. Mice colonized by hCom2 versus human feces are similar in terms of microbiota-derived metabolites, immune cell profile, and bacterial density in the gut, suggesting that this consortium is a prototype of a model system for the human gut microbiome.

microbiology↗

bioRxiv2021

A genetic shift in an escaped transmitted/founder virus guides combinatorial vaccine design against HIV-1

A productive HIV-1 infection in humans is often established by transmission and propagation of a single transmitted/founder (T/F) virus, which then evolves into a complex mixture of variants during the lifetime of infection. An effective HIV-1 vaccine should elicit broad immune responses in order to block the entry of diverse T/F viruses. Currently, no such vaccine exists. An in-depth study of escape variants emerging under host immune pressure during very early stages of infection might provide insights into such a HIV-1 vaccine design. Here, in a rare longitudinal study involving HIV-1 infected individuals just days after infection in the absence of antiretroviral therapy, we discovered a remarkable genetic shift that resulted in near complete disappearance of the original T/F virus and appearance of a variant with H173Y mutation in the variable V2 domain of the HIV-1 envelope protein. This coincided with the disappearance of the first wave of strictly H173-specific antibodies and emergence of a second wave of Y173-specific antibodies with increased breadth. Structural analyses indicated conformational dynamism of the envelope protein which likely allowed selection of escape variants with a conformational switch in the V2 domain from an -helix (H173) to a {beta}-strand (Y173) and induction of broadly reactive antibody responses. This differential breadth due to a single mutational change was also recapitulated in a mouse model. Rationally designed combinatorial libraries containing 54 conformational variants of V2 domain around position 173 further demonstrated increased breadth of antibody responses elicited to diverse HIV-1 envelope proteins. These results offer new insights into designing broadly effective HIV-1 vaccines.

microbiology↗

bioRxiv2021

A hybrid in silico approach reveals novel inhibitors of multiple SARS-CoV-2 variants

The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytophatic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (~16% of predicted hits) active compounds (Efficacy > 30%, IC50 [≤] 15 M). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further analysis identified allosteric binders to host receptor angiotensin-converting enzyme 2, which were able to inhibit the entry of pseudoparticles bearing spike protein of wild type SARS-CoV-2 as well as South African B.1.351 and UK B.1.1.7 variants.

cell biology↗

bioRxiv2021

Anatomical Structures, Cell Types, and Biomarkers Tables Plus 3D Reference Organs in Support of a Human Reference Atlas

1.This paper reviews efforts across 16 international consortia to construct human anatomical structures, cell types, and biomarkers (ASCT+B) tables and three-dimensional reference organs in support of a Human Reference Atlas. We detail the ontological descriptions and spatial three-dimensional anatomical representations together with user interfaces that support the registration and exploration of human tissue data. Four use cases are presented to demonstrate the utility of ASCT+B tables for advancing biomedical research and improving health.

cell biology↗

bioRxiv2021

Identification of Cancer-Associated Fibroblasts in Glioblastoma and Defining Their Pro-tumoral Effects

Despite their identification in some cancers, pro-tumoral cancer-associated fibroblasts (CAFs) were presumed absent in glioblastoma given the lack of brain fibroblasts. Serial trypsinization of primary glioblastoma cultures yielded cells with CAF morphology, CAF transcriptomic profile, and mesenchymal lineage in single-cell RNA-seq. Glioblastoma CAFs were attracted to glioblastoma stem cells (GSCs) and CAFs enriched GSCs. We created a resource of inferred crosstalk by mapping expression of receptors to their cognate ligands, identifying PDGF-{beta} and TGF-{beta} as mediators of GSC effects on CAFs, and osteopontin and hepatocyte growth factor as mediators of CAF-induced GSC enrichment. Glioblastoma CAFs also induced M2 macrophage polarization by producing the EDA fibronectin variant. Glioblastoma CAFs were enriched in the subventricular zone which houses neural stem cells that produce GSCs. Including CAFs in GSC-derived xenografts induced in vivo growth. These findings are among the first to identify glioblastoma CAFs and their GSC interactions, making them an intriguing target.

cancer biology↗

bioRxiv2021

To knot and not: Multiple conformations of the SARS-CoV-2 frameshifting RNA element

The SARS-CoV-2 frameshifting RNA element (FSE) is an excellent target for therapeutic intervention against Covid-19. This small gene element employs a shifting mechanism to pause and backtrack the ribosome during translation between Open Reading Frames 1a and 1b, which code for viral polyproteins. Any interference with this process has profound effect on viral replication and propagation. Pinpointing the structures adapted by the FSE and associated structural transformations involved in frameshifting has been a challenge. Using our graph-theory-based modeling tools for representing RNA secondary structures, "RAG" (RNA-As-Graphs), and chemical structure probing experiments, we show that the 3-stem H-type pseudoknot (3_6 dual graph), long assumed to be the dominant structure has a viable alternative, an HL-type 3-stem pseudoknot (3_3) for longer constructs. In addition, an unknotted 3-way junction RNA (3_5) emerges as a minor conformation. These three conformations share Stems 1 and 3, while the different Stem 2 may be involved in a conformational switch and possibly associations with the ribo-some during translation. For full-length genomes, a stem-loop motif (2_2) may compete with these forms. These structural and mechanistic insights advance our understanding of the SARS-CoV-2 frameshifting process and concomitant virus life cycle, and point to three avenues of therapeutic intervention.

biochemistry↗

bioRxiv2021

A Multiscale Immuno-Oncology on-Chip System (MIOCS) establishes that collective T cell behaviors govern tumor regression

T cell-based tumor immunotherapies such as CAR T cells or immune checkpoint inhibitors harness the cytotoxic potential of T cells to promote tumor regression. However, patient response to immunotherapy remains heterogeneous, highlighting the need to better understand the rules governing a successful T cell attack. Here, we develop a microfluidic-based method to track the outcome of T cell activity on many individual cancer spheroids simultaneously, with a high spatiotemporal resolution. By combining these parallel measurements of T cell behaviors and tumor fate with probabilistic modeling, we establish that the first recruited T cells initiate a positive feedback loop leading to an accelerated effector accumulation on the spheroid. We also provide evidence that cooperation between T cells on the spheroid during the killing phase facilitates tumor destruction. We propose that tumor destruction does not simply reflect the sum of individual T cell activities but relies instead on collective behaviors promoting both T cell accumulation and function. The possibility to track many replicates of immune-tumor interactions with such a level of detail should help delineate the mechanisms and efficacy of various immunotherapeutic strategies.

biophysics↗

bioRxiv2021

A highly accurate model for screening prostate cancer using propensity index panel of ten genes

Prostate-specific antigen (PSA) is a key biomarker, which is commonly used to screen patients of prostate cancer. There is a significant number of unnecessary biopsies that are performed every year, due to poor accuracy of PSA based biomarker. In this study, we identified alternate biomarkers based on gene expression that can be used to screen prostate cancer with high accuracy. All models were trained and test on gene expression profile of 500 prostate cancer and 51 normal samples. Numerous feature selection techniques have been used to identify potential biomarkers. These biomarkers have been used to develop various models using different machine learning techniques for predicting samples of prostate cancer. Our logistic regression-based model achieved highest AUROC 0.91 with accuracy 82.42% on validation dataset. We introduced a new approach called propensity index, where expression of gene is converted into propensity. Our propensitybased approach improved the performance of classification models significantly and achieved AUROC 0.99 with accuracy 96.36% on validation dataset. We also identified and ranked selected genes which can be used to discriminate prostate cancer patients from health individuals with high accuracy. It was observed that single gene-based biomarkers can only achieve accuracy around 90%. In this study, we got best performance using a panel of 10 genes; random forest model using propensity index. HighlightsO_LIApplication of Machine learning techniques to identify Biomarkers for PRAD cancer. C_LIO_LIHighly accurate models developed for classifying prostate cancer vs. normal sample. C_LIO_LIIntroducing Propensity index concept for enhancing model performance. C_LIO_LITop 10 genes identified using feature selection techniques. C_LI

bioinformatics↗

bioRxiv2021

Immune characterization and profiles of SARS-CoV-2 infected patients

The spread of SARS-CoV-2 and the increasing mortality rates of COVID-19 create an urgent need for treatments, which are currently lacking. Although vaccines have been approved by the FDA for emergency use in the U.S., patients will continue to require pharmacologic intervention to reduce morbidity and mortality as vaccine availability remains limited. The rise of new variants makes the development of therapeutic strategies even more crucial to combat the current pandemic and future outbreaks. Evidence from several studies suggests the host immune response to SARS-CoV-2 infection plays a critical role in disease pathogenesis. Consequently, host immune factors are becoming more recognized as potential biomarkers and therapeutic targets for COVID-19. To develop therapeutic strategies to combat current and future coronavirus outbreaks, understanding how the coronavirus hijacks the host immune system during and after the infection is crucial. In this study, we investigated immunological patterns or characteristics of the host immune response to SARS-CoV-2 infection that may contribute to the disease severity of COVID-19 patients. We analyzed large bulk RNASeq and single cell RNAseq data from COVID-19 patient samples to immunoprofile differentially expressed gene sets and analyzed pathways to identify human host protein targets. We observed an immunological profile of severe COVID-19 patients characterized by upregulated cytokines, interferon-induced proteins, and pronounced T cell lymphopenia, supporting findings by previous studies. We identified a number of host immune targets including PERK, PKR, TNF, NF-kB, and other key genes that modulate the significant pathways and genes identified in COVID-19 patients. Finally, we identified genes modulated by COVID-19 infection that are implicated in oncogenesis, including E2F transcription factors and RB1, suggesting a mechanism by which SARS-CoV-2 infection may contribute to oncogenesis. Further clinical investigation of these targets may lead to bonafide therapeutic strategies to treat the current COVID-19 pandemic and protect against future outbreaks and viral escape variants.

immunology↗

bioRxiv2021

A Universal Bacteriophage T4 Nanoparticle Platform to Design Multiplex SARS-CoV-2 Vaccine Candidates by CRISPR Engineering

A "universal" vaccine design platform that can rapidly generate multiplex vaccine candidates is critically needed to control future pandemics. Here, using SARS-CoV-2 pandemic virus as a model, we have developed such a platform by CRISPR engineering of bacteriophage T4. A pipeline of vaccine candidates were engineered by incorporating various viral components into appropriate compartments of phage nanoparticle structure. These include: expressible spike genes in genome, spike and envelope epitopes as surface decorations, and nucleocapsid proteins in packaged core. Phage decorated with spike trimers is found to be the most potent vaccine candidate in mouse and rabbit models. Without any adjuvant, this vaccine stimulated robust immune responses, both TH1 and TH2 IgG subclasses, blocked virus-receptor interactions, neutralized viral infection, and conferred complete protection against viral challenge. This new type of nanovaccine design framework might allow rapid deployment of effective phage-based vaccines against any emerging pathogen in the future.

microbiology↗

bioRxiv2021

Voxelwise encoding models show that cerebellar language representations are highly conceptual

There is a growing body of research demonstrating that the cerebellum is involved in language understanding. Early theories assumed that the cerebellum is involved in low-level language processing. However, those theories are at odds with recent work demonstrating cerebellar activation during cognitive tasks. Using natural language stimuli and an encoding model framework, we performed an fMRI experiment where subjects passively listened to five hours of natural language stimuli which allowed us to analyze language processing in the cerebellum with higher precision than previous work. We used this data to fit voxelwise encoding models with five different feature spaces that span the hierarchy of language processing from acoustic input to high-level conceptual processing. Examining the prediction performance of these models on separate BOLD data shows that cerebellar responses to language are almost entirely explained by high-level conceptual language features rather than low-level acoustic or phonemic features. Additionally, we found that the cerebellum has a higher proportion of voxels that represent social semantic categories, which include "social" and "people" words, and lower representations of all other semantic categories, including "mental", "concrete", and "place" words, than cortex. This suggests that the cerebellum is representing language at a conceptual level with a preference for social information. Significance StatementRecent work has demonstrated that, beyond its typical role in motor planning, the cerebellum is implicated in a wide variety of tasks including language. However, little is known about the language representations in the cerebellum, or how those representations compare to cortex. Using voxelwise encoding models and natural language fMRI data, we demonstrate here that language representations are significantly different in the cerebellum as compared to cortex. Cerebellum language representations are almost entirely semantic, and the cerebellum contains over-representation of social semantic information as compared to cortex. These results suggest that the cerebellum is not involved in language processing per se, but cognitive processing more generally.

neuroscience↗

bioRxiv2021

Structural Brain Correlates of Creative Personality

Creative individuals and their enigmatic personalities have always been a subject of fascination. The current study explored the neuroanatomical basis of creative personality using voxel-based morphometry. The sample comprised of two groups - Creative (CR) group (professional creative artists) and matched controls with no demonstrated artistic creativity (NC) with 20 participants in each group, in the age range of 20-40 years, right-handed, and had minimum average intelligence (IQ > 90). Participants in CR were selected using the creativity achievement questionnaire, creativity was assessed using the Wallach & Kogan test of creativity, and personality was administered using NEO-FFI. Results indicated significantly higher openness to new experiences in CR which positively correlates with the right middle frontal gyrus. An increased grey matter volume in the inferior frontal gyrus, anterior cingulate gyrus in CR, pointing towards the integration of cognitive and imaginative processes that might be implicated in creative personality.

neuroscience↗

bioRxiv2021

Distribution of Huntington's disease Haplogroups in Indian population

Huntingtons disease (HD), a rare neurodegenerative disorder, is inherited in an autosomal dominant manner, and caused by a pathological trinucleotide expansion at exon1 of the HTT locus. Previous studies have described the haplogroups at the HTT locus that can explain the differences in prevalence of HD. We have selected three informative SNPs (rs762855, rs3856973 and rs4690073) to study these haplogroups in an Indian sample. Our results show that the genotype frequencies are significantly different between cases and controls for these SNPs. More than 90% of both cases and controls belong to Haplogroup A which is the predominant European haplogroup.

neuroscience↗

bioRxiv2020

Non-covalent TMPRSS2 inhibitors identified from virtual screening

The SARS-CoV-2 pandemic has prompted researchers to pivot their efforts to finding antiviral compounds and vaccines. In this study, we focused on the human host cell transmembrane protease serine 2 (TMPRSS2), which plays an important role in the viral life cycle by cleaving the spike protein to initiate membrane fusion. TMPRSS2 is an attractive target and has received attention for the development of drugs against SARS and MERS. Starting with comparative structural modeling and binding model analysis, we developed an efficient pharmacophore-based approach and applied a large-scale in silico database screening for small molecule inhibitors against TMPRSS2. The hits were evaluated in the TMPRSS2 biochemical assay and the SARS-CoV-2 pseudotyped particle (PP) entry assay. A number of novel inhibitors were identified, providing starting points for further development of drug candidates for the treatment of COVID-19.

bioinformatics↗

bioRxiv2020

Tetravalent SARS-CoV-2 Neutralizing Antibodies Show Enhanced Potency and Resistance to Escape Mutations

Neutralizing antibodies (nAbs) hold promise as effective therapeutics against COVID-19. Here, we describe protein engineering and modular design principles that have led to the development of synthetic bivalent and tetravalent nAbs against SARS-CoV-2. The best nAb targets the host receptor binding site of the viral S-protein and its tetravalent versions can block entry with a potency that exceeds the bivalent nAbs by an order of magnitude. Structural studies show that both the bivalent and tetravalent nAbs can make multivalent interactions with a single S-protein trimer, observations consistent with the avidity and potency of these molecules. Significantly, we show that the tetravalent nAbs show much increased tolerance to potential virus escape mutants. Bivalent and tetravalent nAbs can be produced at large-scale and are as stable and specific as approved antibody drugs. Our results provide a general framework for developing potent antiviral therapies against COVID-19 and related viral threats, and our strategy can be readily applied to any antibody drug currently in development.

synthetic biology↗

bioRxiv2020

Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech

Natural language contains information at multiple timescales. To understand how the human brain represents this information, one approach is to build encoding models that predict fMRI responses to natural language using representations extracted from neural network language models (LMs). However, these LM-derived representations do not explicitly separate information at different timescales, making it difficult to interpret the encoding models. In this work we construct interpretable multi-timescale representations by forcing individual units in an LSTM LM to integrate information over specific temporal scales. This allows us to explicitly and directly map the timescale of information encoded by each individual fMRI voxel. Further, the standard fMRI encoding procedure does not account for varying temporal properties in the encoding features. We modify the procedure so that it can capture both short- and long-timescale information. This approach outperforms other encoding models, particularly for voxels that represent long-timescale information. It also provides a finer-grained map of timescale information in the human language pathway. This serves as a framework for future work investigating temporal hierarchies across artificial and biological language systems.

neuroscience↗

bioRxiv2020

A Global Temporal Genetic Program for Neural Circuit Formation

The assembly of neural circuits is dependent upon precise spatiotemporal expression of cell recognition molecules1-6. Factors controlling cell-type specificity have been identified7-9, but how timing is determined remains unknown. Here we describe the induction of a cascade of transcription factors by a steroid hormone (Ecdysone) in all fly visual system neurons spanning target recognition and synaptogenesis. We demonstrate through single cell sequencing that the Ecdysone pathway regulates the expression of a common set of targets required for synaptic maturation and cell-type specific targets enriched for cell surface proteins regulating wiring specificity. Transcription factors in the cascade regulate the expression of the same wiring genes in complex ways, including activation in one cell-type and repression in another. We show that disruption of the Ecdysone-pathway generates specific defects in dendritic and axonal processes and synaptic connectivity, with the order of transcription factor expression correlating with sequential steps in wiring. We also identify shared targets of a cell-type specific transcription factor and the Ecdysone pathway which regulate specificity. We propose neurons integrate a global temporal transcriptional module with cell-type specific transcription factors to generate different cell-type specific patterns of cell recognition molecules regulating wiring.

neuroscience↗