Biology subjects

Srivastava, S.

Publications and source records attributed to Srivastava, S..

9 recordsLinked to original sources

bioRxiv2018

A human embryonic stem cell model of Aβ-dependent chronic progressive neurodegeneration

We describe construction and phenotypic analysis of a human embryonic stem cell model of progressive A{beta}-dependent neurodegeneration (ND) with potential relevance to Alzheimers disease (AD). We modified one allele of the normal APP locus to directly express a secretory form of A{beta}40 or A{beta}42, eliminating the need for amyloidogenic APP proteolysis. Following neuronal differentiation edited cell lines specifically accumulate aggregated/oligomeric A{beta}, exhibit a synaptic deficit and have an abnormal accumulation of endolysosomal vesicles. Edited cultures progress to a stage of overt ND. All phenotypes appear at earlier culture times for A{beta}42 relative to A{beta}40. Whole transcriptome RNA-Seq analysis identified 23 up and 70 down regulated genes (DEGs) with similar directional fold change but larger absolute values in the A{beta}42 samples suggesting common underlying pathogenic mechanisms. Pathway/annotation analysis suggested that down regulation of extracellular matrix and cilia functions are significantly overrepresented. This cellular model could be useful for uncovering mechanisms directly linking A{beta} to neuronal death and as a tool to screen for new therapeutic agents that slow or prevent human ND.

neuroscience↗

bioRxiv2018

Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotroph Methylococcus capsulatus str. Bath

The increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model of an obligate methanotroph, Methylococcus capsulatus str. Bath was reconstructed. The model contains 535 genes, 898 reactions and 784 unique metabolites and is named iMC535. The predictive potential of the model was validated using previously-reported experimental data. The model predicted the Entner-Duodoroff (ED) pathway to be essential for the growth of this bacterium, whereas the Embden-Meyerhof-Parnas (EMP) pathway was found non-essential. The performance of the model was simulated on various carbon and nitrogen sources and found that M. capsulatus can grow on amino acids. The analysis of network topology of the model identified that six amino acids were in the top-ranked metabolic hubs. Using flux balance analysis (FBA), 29% of the metabolic genes were predicted to be essential, and 76 double knockout combinations involving 92 unique genes were predicted to be lethal. In conclusion, we have reconstructed a genome-scale metabolic model of a unique methanotroph Methylococcus capsulatus str. Bath. The model will serve as a knowledge-base for deeper understanding, as a platform for exploring the metabolic potential, and as a tool to engineer this bacterium for methane mitigation and industrial applications.

bioengineering↗

bioRxiv2018

Cdc23/Mcm10 Primase Generates the Lagging Strand-Specific Ribonucleotide Imprint in Fission Yeast

The developmental asymmetry of fission yeast daughter cells derives from inheriting \"older Watson\" versus \"older Crick\" DNA strand from the parental cell, strands that are complementary but not identical with each other. A novel DNA strand-specific \"imprint\", installed during DNA replication at the mating-type locus (mat1), imparts competence for cell type inter-conversion to one of the two chromosome replicas. The biochemical nature of the imprint and the mechanism of its installation are still not understood. The catalytic subunit of DNA Polymerase (Pol) has been implicated in the imprinting process. Based on its known biochemical function, Pol might install the mat1 imprint during lagging strand synthesis. The nature of the imprint is not clear: it is either a nick or a ribonucleotide insertion. Our investigations do not support a role of Pol in nicking through putative endonuclease domains but confirm its role in installing an alkali-labile moiety as the imprint. A detailed genetic and molecular analysis reveals a direct role of the Cdc23/Mcm10 primase activity in installing the imprint in cooperation with Pol and Swi1.

genetics↗

bioRxiv2017

Pre-mature senescence in the oldest leaves of low nitrate-grown Atxdh1 mutant uncovers a role for purine catabolism in plant nitrogen metabolism

The nitrogen rich ureides allantoin and allantoate, are known to play a role in nitrogen delivery in Leguminosae, in addition to their role as reactive oxygen species scavengers. However, their role as a nitrogen source in non-legume plants has not been shown. Xanthine dehydrogenase1 (AtXDH1) activity is a catalytic bottleneck step in purine catabolism. Atxdh1 mutant exhibited early leaf senescence, lower soluble protein and organic-N levels as compared to wild-type (WT) older leaves when grown with 1 mM nitrate, whereas under 5mM, mutant plants were comparable to WT. Similar nitrate-dependent senescence phenotypes were evident in the older leaves of allantoinase (Ataln) and allantoate amidohydrolase (Ataah) mutants, impaired in further downstream steps of purine catabolism. Importantly, under low nitrate conditions, xanthine was accumulated in older leaves of Atxdh1, whereas allantoin in both older and younger leaves of Ataln but not in WT leaves, indicating remobilization of xanthine degraded products from older to younger leaves. Supporting this notion, ureide transporters UPS1, UPS2 and UPS5 were enhanced in older leaves of 1 mM nitrate-fed WT as compared to 5 mM. Enhanced AtXDH, AtAAH and purine catabolic transcripts, were detected in WT grown in low nitrate, indicating regulation at protein and transcript levels. Higher nitrate reductase activity in Atxdh1 than WT leaves, indicates their need for nitrate assimilation products. It is further demonstrated that the absence of remobilized purine-degraded N from older leaves is the cause for senescence symptoms, a result of higher chloroplastic protein degradation in older leaves of nitrate starved Atxdh1 plants.\n\nSummaryThe absence of remobilized purine-degraded N from older to the young growing leaves is the cause for senescence symptoms, a result of higher chloroplastic protein degradation in older leaves of nitrate starved Atxdh1 plants.

biochemistry↗

bioRxiv2017

PDGFRα signaling in cardiac stem and stromal cells modulates quiescence, metabolism and self-renewal, and promotes anatomical and functional repair

The interstitial and perivascular spaces of the mammalian heart contain a highly interactive tissue community essential for cardiac homeostasis, repair and regeneration. Mesenchymal cells (fibroblasts) are one of the most abundant cell types, playing key roles as sentinels, tissue architects, paracrine signaling hubs and lineage precursors, and are linked to heart disease through their roles in inflammation and fibrosis. Platelet-derived growth factors (PDGFs) are secreted by several cell types involved in cardiac injury and repair, and are recognized mitogens for cardiac fibroblasts and mesenchymal stem cells. However, their roles are complex and investigations of their impact on heart repair have produced contrasting outcomes, leaving therapeutic potential uncertain. Here, we use new approaches and tools, including single cell RNA sequencing, to explore cardiac fibroblast heterogeneity and how PDGF receptor (PDGFR) signaling impacts fibroblasts during heart repair. Short-term systemic delivery of PDGF-AB to mice from the time of myocardial infarction (MI) led to enhanced anatomical and functional recovery. Underpinning these benefits was a priming effect, in which PDGF-AB accelerated exit of fibroblasts from quiescence and induced a higher translational biosynthetic capacity in both fibroblasts and macrophages without triggering fibrosis. Our study highlights the significant biosynthetic heterogeneity and plasticity in cardiac fibroblast populations, and suggests a rationale for a novel therapeutic approach to cardiac injury involving controlled stimulation of fibroblast activation.

cell biology↗

bioRxiv2017

Summarizing Performance for Genome Scale Measurement of miRNA: Reference Samples and Metrics

BackgroundThe potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls.\n\nResultsThree pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes.\n\nConclusionsThe set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

genomics↗

bioRxiv2017

Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

Advances in proteomics reveal that pathway databases fail to capture the majority of cellular signaling activity. Our mass spectrometry study of the dynamic epidermal growth factor (EGF) response demonstrates that over 89% of significantly (de)phosphorylated proteins are excluded from individual EGF signaling maps, and 63% are absent from all annotated pathways. We present a computational method, the Temporal Pathway Synthesizer (TPS), to discover missing pathway elements by modeling temporal phosphoproteomic data. TPS uses constraint solving to exhaustively explore all possible structures for a signaling pathway, eliminating structures that are inconsistent with protein-protein interactions or the observed phosphorylation event timing. Applied to our EGF response data, TPS connects 83% of the responding proteins to receptors and signaling proteins in EGF pathway maps. Inhibiting predicted active kinases supports the TPS pathway model. The TPS algorithm is broadly applicable and also recovers an accurate model of the yeast osmotic stress response.

bioinformatics↗

bioRxiv2017

C-State: An interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search

BackgroundComparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge.\n\nResultsWe developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript- based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge.\n\nConclusionsC-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.

bioinformatics↗

bioRxiv2017

Partitioning and Enhanced Self-Assembly of Actin in Polypeptide Coacervates

Biomolecules exist and function in cellular micro-environments that control their spatial organization, local concentration and biochemical reactivity. Due to the complexity of native cytoplasm, the development of artificial bioreactors and cellular mimics to compartmentalize, concentrate and control the local physicochemical properties is of great interest. Here, we employ self-assembling polypeptide coacervates to explore the partitioning of the ubiquitous cytoskeletal protein actin into liquid polymer-rich droplets. We find that actin spontaneously partitions into coacervate droplets and is enriched by up to {approx}30-fold. Actin polymerizes into micrometer-long filaments and, in contrast to the globular protein BSA, these filaments localize predominately to the droplet periphery. We observe up to a 50-fold enhancement in the actin filament assembly rate inside coacervate droplets, consistent with the enrichment of actin within the coacervate phase. Together these results suggest that coacervates can serve as a versatile platform in which to localize and enrich biomolecules to study their reactivity in physiological environments.\n\nSIGNIFICANCE STATEMENTLiving cells harbor many protein-rich membrane-less organelles, the biological functions of which are defined by compartment composition and properties. Significant differences between the physico-chemical properties of these crowded compartments and the dilute solutions in which biochemical reactions are traditionally studied pose a major challenge for understanding regulation of organelle composition and component activity. Here, we report the spontaneous partitioning and accelerated polymerization of the cytoskeletal protein actin inside model polypeptide coacervates as a proof-of-concept demonstration of coacervates as bioreactors for studying biomolecular reactions in cell-like environments. Our work introduces exciting avenues for the use of synthetic polymers to control the physical and biological properties of bioreactors in vitro, enabling studies of biochemical reactions in cell-like micro-environments.

biophysics↗