Biology subjects

Bharadwaj, V.

Publications and source records attributed to Bharadwaj, V..

5 recordsLinked to original sources

bioRxiv2026

Survival-associated cellular communication networks in human solid cancers

Single-cell atlases have enabled the prediction of human cell-cell communication (CCC) networks in cancer, but whether predicted communication networks have clinical significance is not well understood. Here, we integrated a pan-solid cancer scRNA-seq atlas comprising 78 cell types from 318,426 quality-controlled cells with bulk RNA-seq and clinical outcome data from The Cancer Genome Atlas (TCGA) to develop Single-cell-based Kaplan-Meier Analysis Network (SKyNet). SKyNet prioritizes ligand-receptor interactions associated with overall survival across 11 human solid cancers, predicting unique interactions not inferred by previous CCC algorithms. In pancreatic adenocarcinoma, SKyNet-predicted endothelial-pericyte interactions were associated with poor outcomes that were validated by independent spatial transcriptomics and survival cohorts. In lung adenocarcinoma, lymphatic endothelial cell interactions consisting of collagen-integrin pairs were associated with poorer survival outcomes. In kidney renal clear cell carcinoma and kidney renal papillary cell carcinoma, fibroblast communication networks displayed disparate survival associations, with the DSC2-DSG2 axis associated with better survival outcomes. Thus, SKyNet provides a hypothesis-generating framework for cell type-specific communication pathways associated with patient outcomes.

systems biology↗

bioRxiv2026

Comprehensive study on ferredoxin isoforms in the cyanobacterium Synechocystis sp. PCC 6803

Ferredoxins are central to cellular metabolism by mediating electron flow in energy conversion reactions. The focus of this study was to systematically examine twelve ferredoxin and ferredoxin-like proteins from Synechocystis sp. PCC 6803 to identify their properties, activities, and functions in electron transfer. Using electron paramagnetic resonance spectroscopy, we detected cluster types consistent with major ferredoxin families including plant-type [2Fe-2S], adrenodoxin, thioredoxin, and bacterial-type [4Fe- 4S] ferredoxins. In addition, we found that the ssr3184 ferredoxin-like protein exchanged between a [3Fe-4S] or a [4Fe-4S] cluster, pointing to a possible functional change in response to changes in oxygen or cellular redox poise. Electrochemical measurements demonstrated that these ferredoxins constitute a broad potential window, from -243 mV to -520 mV vs SHE. Investigations on their capacity to support electron-transfer focused on reactions with two major redox hubs: Photosystem I and pyruvate:ferredoxin oxidoreductase and included testing of binding interactions with nitrite reductase. Expression profiling under multiple environmental conditions was also used to predict function and revealed distinct regulatory patterns. Collectively, these findings identified a group of core ferredoxins that directly support photosynthetic electron transfer, and more specialized ones that may serve other functions. In summary, Synechocystis utilizes a suite of ferredoxins to maintain cellular redox homeostasis under dynamic environmental conditions.

biochemistry↗

bioRxiv2024

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes - Insights from machine learning models

Substrate specificity is an essential characteristic of any enzymes function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (eg: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naive-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

bioinformatics↗

bioRxiv2021

Real-Time Structure Search and Structure Classification for AlphaFold Protein Models

AlphaFold2 showed a substantial improvement in the accuracy of protein structure prediction. Following the release of the software, whole-proteome protein structure predictions by AlphaFold2 for 21 organisms were made publicly available. Here, we developed the infrastructure, 3D-AF-Surfer, to enable real-time structure-based search for the AlphaFold2 models by combining molecular surface representation with 3D Zernike descriptors and deep neural networks.

bioinformatics↗

bioRxiv2020

Structure of the Xylan O-Acetyltransferase AtXOAT1 Reveals Molecular Insight into Polysaccharide Acetylation in Plants

Acetylation of biomolecules is gaining increased attention due to both the abundance and importance of this modification across all kingdoms of life. Xylans are a major component of plant cell walls and are the third most abundant biopolymer in Nature. O-Acetyl moieties are the dominant backbone substituents of glucuronoxylan in dicots and play a major role in the polymer-polymer interactions that are crucial for proper wall architecture and normal plant development. Here, we describe the biochemical, structural, and mechanistic characterization of Arabidopsis thaliana xylan O-acetyltransferase 1 (AtXOAT1), a member of the plant-specific Trichome Birefrigence Like (TBL) family that catalyzes the 2-O-acetylation of xylan. A multipronged approach involving X-ray crystallography, biochemical analyses, mutagenesis, and molecular simulations show that XOAT1 catalyzes xylan acetylation through formation of an acyl-enzyme intermediate by a double displacement bi-bi mechanism involving a Ser-His-Asp catalytic triad and unconventionally employs an arginine residue in formation of an oxyanion hole.

biochemistry↗