Biology subjects

Srivastava, A.

Publications and source records attributed to Srivastava, A..

At least 127 records · Page 7Linked to original sources

bioRxiv2021

Enthalpic and Entropic Contributions to Interleaflet Coupling Drive Domain Registration and Anti-registration in Biological Membrane

Biological membrane is a complex self-assembly of lipids, sterols and proteins organized as a fluid bilayer of two closely stacked lipid leaflets. Differential molecular interactions among its diverse constituents give rise to heterogeneities in the membrane lateral organization. Under certain conditions, heterogeneities in the two leaflets can be spatially synchronised and exist as registered domains across the bilayer. Several contrasting theories behind mechanisms that induce registration of nanoscale domains have been suggested[1-3]. Following a recent study[4] showing the effect of position of lipid tail unsaturation on domain registration behavior, we decided to develop an analytical theory to elucidate the driving forces that create and maintain domain registry across leaflets. Towards this, we formulated a Hamiltonian for a stacked lattice system where site variables capture the lipid molecular properties such as the position of unsaturation and various other interactions that could drive phase separation and interleaflet coupling. We solve the Hamiltonian using Monte Carlo simulations and create a complete phase diagram that reports the presence or absence of registered domains as a function of various Hamiltonian parameters. We find that the interleaflet coupling should be described as a competing enthalpic contribution due to interaction of lipid tail termini, primarily due to saturated-saturated interactions, and an interleaflet entropic contribution from overlap of unsaturated tail termini. A higher position of unsaturation is seen to provide weaker interleaflet coupling. Thermodynamically stable nanodomains could also be observed for certain points in the parameter space in our bilayer model, which were further verified by carrying out extended Monte Carlo simulations. These persistent non-coalescing registered nanodomains close to the lower end of the accepted nanodomain size range also point towards a possible "nanoscale" emulsion description of lateral heterogeneities in biological membrane leaflets.

biophysics↗

bioRxiv2021

Characterizing cellular heterogeneity in chromatin state with scCUT&Tag-pro

New technologies that profile chromatin modifications at single-cell resolution offer enormous promise for functional genomic characterization. However, the sparsity of these measurements and the challenge of integrating multiple binding maps represent significant challenges. Here we introduce scCUT&Tag-pro, a multimodal assay for profiling protein-DNA interactions coupled with the abundance of surface proteins in single cells. In addition, we introduce scChromHMM, which integrates data from multiple experiments to infer and annotate chromatin states based on combinatorial histone modification patterns. We apply these tools to perform an integrated analysis across nine different molecular modalities in circulating human immune cells. We demonstrate how these two approaches can characterize dynamic changes in the function of individual genomic elements across both discrete cell states and continuous developmental trajectories, nominate associated motifs and regulators that establish chromatin states, and identify extensive and cell type-specific regulatory priming. Finally, we demonstrate how our integrated reference can serve as a scaffold to map and improve the interpretation of additional scCUT&Tag datasets.

genomics↗

bioRxiv2021

ASXL3 controls cortical neuron fate specification through extrinsic self-renewal pathways

During corticogenesis, transcription plasticity is fundamental to the restriction of neural progenitor cell (NPC) multipotency and production of cortical neuron heterogeneity. Human and mouse genetic studies have highlighted the role of Polycomb transcriptional regulation in this process. ASXL3, which encodes a component of the Polycomb repressive deubiquitination (PR-DUB) complex, has been identified as a high confidence autism spectrum disorder (ASD) risk gene. Genetic inactivation of Asxl3, in a mouse model that carries a clinically relevant ASXL3 frameshift (Asxl3fs) variant, disrupts lateral expansion of NPCs and delays cortical neuron differentiation. Single-cell RNA sequencing analysis implicates Notch signaling, which alters the composition of excitatory neurons and fidelity of cortical layer deposition. Our data provides a new link between extrinsic signaling cues and intrinsic epigenetic regulation that together control the timing of cell fate programs. Furthermore, transcriptomic analysis revealed dysregulation of other known ASD risk genes indicating that a convergent developmental pathway is affected. Collectively our work provides important insights about developmental mechanisms that contribute to ASD neuropathology.

neuroscience↗

bioRxiv2021

Alevin-fry unlocks rapid, accurate, and memory-frugal quantification of single-cell RNA-seq data

The rapid growth of high-throughput single-cell and single-nucleus RNA sequencing technologies has produced a wealth of data over the past few years. The available technologies continue to evolve and experiments continue to increase in both number and scale. The size, volume, and distinctive characteristics of these data necessitate the development of new software and associated computational methods to accurately and efficiently quantify single-cell and single-nucleus RNA-seq data into count matrices that constitute the input to downstream analyses. We introduce the alevin-fry framework for quantifying single-cell and single-nucleus RNA-seq data. Despite being faster and more memory frugal than other accurate and scalable quantification approaches, alevin-fry does not suffer from the false positive expression or memory scalability issues that are exhibited by other lightweight tools. We demonstrate how alevin-fry can be effectively used to quantify single-cell and single-nucleus RNA-seq data, and also how the spliced and unspliced molecule quantification required as input for RNA velocity analyses can be seamlessly extracted from the same pre-processed data used to generate regular gene expression count matrices.

bioinformatics↗

bioRxiv2021

Assessment of Genetic Diversity and Population Genetic Structure of Santalum album L. in India by Genic and Genomic SSR markers

Sandalwood (Santalum album L.) is highly valued aromatic tropical tree. It is known for its high quality heartwood and oil. In this study, 39 genic and genomic SSR markers were used to analyze the genetic diversity and population structure of 177 S. album accessions from 14 populations of three states in India. High genetic diversity was observed in terms of number of alleles 127, expected heterozygosity (He) ranged from 0.63-0.87 and the average PIC was 0.85. The selected population had relatively high genetic diversity with Shannons information index (I) >1.0. 0.02 mean coefficient of genetic differentiation (FST) and 10.55 gene flow were observed. AMOVA revealed that 92% of the variation observed within individuals. Based on cluster and Structure result, individuals were not clustered as per their geographical origin. Furthermore the clusters were clearly distinguished by principal component analysis analysis and the result revealed that PC1 reflected the moderate contribution in genetic variation (6%) followed by PC2 (5.5%). From this study, high genetic diversity and genetic differentiation was found in S. album populations. The genetic diversity information of S. album populations can be used for selection of superior genotypes and germplasm conservation to promote the tree improvement of S. album populations.

molecular biology↗

bioRxiv2021

Comparative Transcriptome Profiling of High and Low oil yielding Santalum album L.

East Indian Sandalwood (Santalum album L.) is highly valued for its heartwood and its oil. There have been no efforts to comparative study of high and low oil yielding genetically identical sandalwood trees grown in similar climatic condition. Thus we intend to study a genome wide transcriptome analysis to identify the corresponding genes involved in high oil biosynthesis in S. album. In this study, 15 years old S. album (SaSHc and SaSLc) genotypes were targeted for analysis to understand the contribution of genetic background on high oil biosynthesis in S. album. A total of 28,959187 and 25,598869 raw PE reads were generated by the Illumina sequencing. 2.12 million and 1.811 million coding sequences were obtained in respective accessions. Based on the GO terms, functional classification of the CDS 21262, & 18113 were assigned into 26 functional groups of three GO categories; (4,168; 3,641) for biological process (5,758;4,971) cellular component and (5,108;4,441) for molecular functions. Total 41,900 and 36,571 genes were functionally annotated and KEGG pathways of the DEGs resulted 213 metabolic pathways. In this, 14 pathways were involved in secondary metabolites biosynthesis pathway in S. album. Among 237 cytochrome families, nine groups of cytochromes were participated in high oil biosynthesis. 16,665 differentially expressed genes were commonly detected in both the accessions (SaHc and SaSLc). The results showed that 784 genes were upregulated and 339 genes were downregulated in SaHc whilst 635 upregulated 299 downregulated in SaSLc S. album. RNA-Seq results were further validated by quantitative RT-PCR. Maximum Blast hits were found to be against Vitis vinifera. From this study we have identified additional number of cytochrome family in SaHc. The accessibility of a RNA-Seq for high oil yielding sandalwood accessions will have broader associations for the conservation and selection of superior elite samples/populations for further genetic improvement program.

plant biology↗

bioRxiv2021

Evaluation of in vitro and in vivo toxicity of pristine molybdenum disulphide nanosheets in Swiss albino mice

The Molybdenum disulfide nanosheets (MoS2-NSs) thin films has received increasing attention recently due to their versatile multi functionality including catalytic properties, photoluminescence and flexibility, which suggests their future, uses for biomedical applications. However, there are no studies in detail related with biocompatibility of MoS2 thin sheets. Here, weevaluated the dose-dependent effects of MoS2-NSs on cell viability (MTT assay) and release of lactate dehydrogenase (LDH) into culture media using MG-63 cells, as well as haemolysis, hematological, serum biochemical, antioxidants and histopathological parameters in Swiss albino mice. The MoS2-NSs was synthesized via facile hydrothermal method and characterized using XRD, Raman, SEM, TEM and HRTEM. The in vitro study results suggest that at lower concentration MoS2-NSs does not causes any toxicity. The lethal dose (LD50) was evaluated by intraperitoneal administration with different concentrations and estimated as ~1.0 mg kg-1. The higher dose (1.5 mg kg-1) of MoS2-NSs showed significant alteration in hematological markers and serum biochemical enzymes, as compared to control. Lipid peroxidation also shows significant alteration with respect to the control. Histopathological, hematological and biochemical examination, revealed no remarkable changes at lower concentration (less than 1.0 mg kg-1), however, higher concentration (1.5 mg kg-1) causes significant histopathological, antioxidants and biochemical alterations in tissues and serum, respectively. The results suggest that the lower concentration of MoS2-NSs can be used in future biomedical applications.

bioengineering↗

bioRxiv2021

A like-for-like comparison of lightweight-mapping pipelines for single-cell RNA-seq data pre-processing

Recently, Booeshaghi and Pachter (1) published a benchmark comparing the kallisto-bustools pipeline (2) for single-cell data pre-processing to the alevin-fry pipeline (3). Their benchmarking adopted drastically dissimilar configurations for these two tools, and overlooked the time- and space-frugal configurations of alevin-fry previously benchmarked by Sarkar et al. (3). In this manuscript, we provide a small set of modifications to the benchmarking scripts of Booeshaghi and Pachter that are necessary to perform a like-for-like comparison between kallisto-bustools and alevin-fry. We also address some misuses of the alevin-fry commands and include important data on the exact reference transcriptomes used for processing1. Using the same benchmarking scripts of Booeshaghi and Pachter (1), we demonstrate that, when configured to match the computational com-plexity of kallisto-bustools as closely as possible, alevin-fry processes data faster (~2.08 times as fast on average) and uses less peak memory (~ 0.34 times as much on average) compared to kallisto-bustools, while producing results that are similar when assessed in the manner done by Booeshaghi and Pachter (1). This is a notable inversion of the performance characteristics presented in the previous benchmark.

bioinformatics↗

bioRxiv2021

Accounting for fragments of unexpectedorigin improves transcript quantification inRNA-seq simulations focused on increased realism

Transcript and gene quantification is the first step in many RNA-seq analyses. While many factors and properties of experimental RNA-seq data likely contribute to differences in accuracy between various approaches to quantification, it has been demonstrated (1) that quantification accuracy generally benefits from considering, during alignment, potential genomic origins for sequenced fragments that reside outside of the annotated transcriptome. Recently, Varabyou et al. (2) demonstrated that the presence of transcriptional noise leads to systematic errors in the ability of tools -- particularly annotation-based ones -- to accurately estimate transcript expression. Here, we confirm the findings of Varabyou et al. (2) using the simulation framework they have provided. Using the same data, we also examine the methodology of Srivastava et al.(1) as implemented in recent versions of salmon (3), and show that it substantially enhances the accuracy of annotation-based transcript quantification in these data.

bioinformatics↗

bioRxiv2021

Hydrophobic residues advance the onset of simple coacervation in intrinsically disordered proteins at low densities: Insights from field theoretical simulations studies

Intrinsically disordered proteins (IDPs) have engendered a definitive change in the way we think about the classical "sequence-structure-function" dogma. Their conformational pliability and rich molecular recognition features endow them with the ability to bind to diverse partners and predispose them to an elaborate functional armory. And of late, with studies on IDP-based liquid-liquid phase separation (LLPS) leading to formation of functional subcellular coacervates - best described as "membrane-less organelles (MLOs)", IDPs are also bringing about paradigmatic changes in the way we think about biomolecular assemblies and subcellular organization. Though it is well recognized that the phase behavior of a given IDP is tightly coupled to its amino-acid sequences, there are only a few theories to model polyampholyte coacervation for IDPs. Recently, Joan-Emma Shea and co-workers used field theoretical simulations (FTS) to elucidate the complete phase diagram for LLPS of IDPs by considering different permutations of 50-residues chain representing 25 Lysine and 25 Glutamic acid [1]. Our work is an extension of that FTS framework where we develop and solve an augmented Hamiltonian that also accounts for hydrophobic interactions in the chain. We show that incorporation of hydrophobic interactions result in an advanced onset of coacervation at low densities. The patterning of hydrophobic, positive and negative residues plays important role in determining relative differences in the onset of phase separation. Though still very coarse-grained, once additional chemical specificities are incorporated, these high throughput analytical theory methods can be used as a starting point for designing sequences that drive LLPS.

biophysics↗

bioRxiv2020

Multimodal single-cell chromatin analysis with Signac

The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a framework for the analysis of single-cell chromatin data, as an extension of the Seurat R toolkit for single-cell multimodal analysis. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis, and interactive visualization. Furthermore, Signac facilitates the analysis of multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance, and mitochondrial genotype. We demonstrate scaling of the Signac framework to datasets containing over 700,000 cells. AvailabilityInstallation instructions, documentation, and tutorials are available at: https://satijalab.org/signac/

genomics↗

bioRxiv2020

Immunodominant T-cell epitopes from the SARS-CoV-2 spike antigen reveal robust pre-existing T-cell immunity in unexposed individuals

The COVID-19 pandemic has revealed a range of disease phenotypes in infected patients with asymptomatic, mild or severe clinical outcomes, but the mechanisms that determine such variable outcomes remain unresolved. In this study, we identified immunodominant CD8 T-cell epitopes in the RBD and the non-RBD domain of the spike antigen using a novel TCR-binding algorithm. A selected pool of 11 predicted epitopes induced robust T-cell activation in unexposed donors demonstrating pre-existing CD4 and CD8 T-cell immunity to SARS-CoV-2 antigen. The T-cell reactivity to the predicted epitopes was higher than the Spike-S1 and S2 peptide pools containing 157 and 158 peptides both in unexposed donors and in convalescent patients suggesting that strong T-cell epitopes are likely to be missed when larger peptide pools are used in assays. A key finding of our study is that pre-existing T-cell immunity to SARS-CoV-2 is contributed by TCRs that recognize common viral antigens such as Influenza and CMV, even though the viral epitopes lack sequence identity to the SARS-CoV-2 epitopes. This finding is in contrast to multiple published studies in which pre-existing T-cell immunity is suggested to arise from shared epitopes between SARS-CoV-2 and other common cold-causing coronaviruses. Whether the presence of pre-existing T-cell immunity provides protection against COVID-19 or contributes to severe disease phenotype remains to be determined in a larger cohort. However, our findings raise the expectation that a significant majority of the global population is likely to have SARS-CoV-2 reactive T-cells because of prior exposure to flu and CMV viruses, in addition to common cold-causing coronaviruses.

immunology↗

bioRxiv2020

PRAK-03202: A triple antigen VLP vaccine candidate against SARS CoV-2

The rapid development of safe and effective vaccines against SARS CoV-2 is the need of the hour for the coronavirus outbreak. Here, we have developed PRAK-03202, the worlds first triple antigen VLP vaccine candidate in a highly characterized S. cerevisiae-based D-CryptTM platform, which induced SARS CoV-2 specific neutralizing antibodies in BALB/c mice. Immunizations using three different doses of PRAK-03202 induces antigen specific (Spike, envelope and membrane proteins) humoral response and neutralizing potential. PBMCs from convalescent patients, when exposed to PRAK-03202, showed lymphocyte proliferation and elevated IFN-{gamma} levels suggestive of conservation of epitopes and induction of T helper 1 (Th1)-biased cellular immune responses. These data support the clinical development and testing of PRAK-03202 for use in humans.

immunology↗

bioRxiv2020

Systematic benchmarking of tools for CpG methylation detectionfrom Nanopore sequencing

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a new consensus approach, METEORE (https://github.com/comprna/METEORE), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.

bioinformatics↗

bioRxiv2020

Integrated analysis of multimodal single-cell data

The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce weighted-nearest neighbor analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. AvailabilityInstallation instructions, documentation, tutorials, and CITE-seq datasets are available at http://www.satijalab.org/seurat

genomics↗

bioRxiv2020

Emergence and expansion of highly infectious spike:D614G mutant SARS-CoV-2 in central India

COVID 19 has emerged as global pandemic with largest damage to the economy and human psyche. The genomic signature deciphered during the ongoing pandemic period is valuable to understand the virus evolutionary patterns and spread across the globe. Increased availability of genome information of circulating strain in our country will enable to generate selective details in virulent and non virulent markers to prophylaxis and therapeutic interventions. The first case of SARS CoV-2 was detected in Chambal region of Madhya Pradesh state in mid of March 2020 followed by multiple introduction events and expansion of COVID-19 cases within 3 months in this region. We analyzed around 5000 COVID -19 suspected samples referred to Defence Research and Development Establishment, Gwalior, Madhya Pradesh. A total of 136 cases were found positive over a span of three months period this includes virus introduction to region and further spread. Whole genome sequences employing Oxford nanopore technology were deciphered for 26 SARS-CoV-2 circulating in 10 different districts in Madhya Pradesh State of India. The region witnessed index cases with multiple travel history responsible for introduction of COVID-19 followed by remarkable expansion of virus. The genome wide substitutions including in important viral proteins were observed. The detailed phylogenetic analysis revealed the circulating SARS-CoV-2 clustered in multiple clades A2a, A4 and B. The cluster wise segregation was observed suggesting multiple introduction links and evolution of virus in the region. This is the first comprehensive details of whole genome sequence analysis from central India region, which will add genome wide knowledge towards diagnostic and therapeutic interventions.

molecular biology↗

bioRxiv2020

Towards A 3D Chromosome Shape Alphabet

The study of the 3-dimensional (3D) structure of chromosomes - the largest macromolecules in biology - is one of the most challenging to date in structural biology. Here, we develop a novel representation of chromosomes, as sequences of shape letters from a finite shape alphabet, which provides a compact and efficient way to analyze ensembles of chromosome shape data, akin to the analysis of texts in a language by using letters. We construct a Chromosome Shape Alphabet (CSA) from an ensemble of chromosome 3D structures inferred from Hi-C data - via SIMBA3D or other methods - by segmenting curves based on topologically associating domains (TADs) boundaries, and by clustering all TADs 3D structures into groups of similar shapes. The median shapes of these groups, with some pruning and processing, form the Chromosome Shape Letters (CSLs) of the alphabet. We provide a proof-of-concept for these CSLs by reconstructing independent test curves using only CSLs (and corresponding transformations) and comparing these reconstructions with the original curves. Finally, we demonstrate how CSLs can be used to summarize the variability of shapes in an ensemble of chromosome 3D structures using generalized sequence logos.

bioinformatics↗

bioRxiv2020

An equivalence of prokaryotic pore forming proteins of Plasmodium triggers cellular dysfunction responsible for malaria pathogenesis

Severe malaria caused by Plasmodium falciparum poses a major global health problem with high morbidity and mortality. The P. falciparum harbours a family of pore forming proteins (PFPs), known as perforin like proteins (PLPs), which are structurally equivalent to prokaryotic PFPs. These PLPs are secreted from the parasites and by interacting to host cells they contribute to disease pathogenesis. The severe malaria pathogenesis is associated with dysfunction of various barrier cells including endothelial cells. A number of factors, including PLPs, secreted by parasite contribute to the host cell dysfunction. Here in, we tested the hypothesis that the PLPs mediate dysfunction of barrier cells and might have a role in disease pathogenesis. We analysed various dysfunction in barrier cells following rPLP2 exposure and demonstrate that it causes an increase in intracellular Ca2+ levels. Additionally, rPLP2 exposed barrier cells displayed features of cell death including Annexin/PI positivity, depolarized mitochondrial membrane potential and ROS generation. We further performed the time lapse video microscopy of barrier cells and found the treatment of rPLP2 triggers their membrane blebbing. The cytoplasmic localization of HMGB1, a marker of necrosis, further confirmed the necrotic type of cell death. This study highlights the role of parasite factor PLP in endothelial dysfunction and provides a rational for the design of adjunct therapies against severe malaria.

cell biology↗