Biology subjects

Tiwari, K.

Publications and source records attributed to Tiwari, K..

9 recordsLinked to original sources

bioRxiv2026

Genetic Perturbation Prediction Models Fail Out-of-Distribution: A Rigorous Benchmark and Systematic Evaluation

Perturbation prediction models - which forecast transcriptional responses to gene inactivation - are increasingly proposed as in silico surrogates for genome-scale drug discovery screens. Yet, rigorous evaluation of whether these models genuinely generalize beyond their training distribution has been lacking. Existing benchmarks rely predominantly on random train-test splits, obscuring systematic failure modes that only emerge under realistic out-of-distribution (OOD) conditions. Here we introduce EL-PERTURB (Extrapolative Learning for PERTURBation Prediction), a benchmarking framework that stress-tests 20 perturbation prediction models spanning six architecture classes on both essential gene and genome-wide Perturb-seq screens, using a novel stratified OOD splitting strategy that partitions train and test sets into functionally distinct regions of transcriptional space. We find that model performance degrades substantially under OOD conditions, and that architectural complexity - including single-cell foundation model embeddings - confers no reliable advantage over well-tuned simpler baselines. EL-PERTURB establishes a rigorous benchmark for perturbation effect prediction across a gradient of generalization difficulty, providing a guide for building models that can genuinely serve as surrogates for wet-lab screening.

systems biology↗

bioRxiv2024

The metabolic benefits of thermogenic stimulation are preserved in aging

Adipose thermogenesis has been actively investigated as a therapeutic target for improving metabolic dysfunction in obesity. However, its applicability to middle-aged and older populations, which bear the highest obesity prevalence in the US (approximately 40%), remains uncertain due to age-related decline in thermogenic responses. In this study, we investigated the effects of chronic thermogenic stimulation using the {beta}3-adrenergic (AR) agonist CL316,243 (CL) on systemic metabolism and adipose function in aged (18-month-old) C57BL/6JN mice. Sustained {beta}3-AR treatment resulted in reduced fat mass, increased energy expenditure, increased fatty acid oxidation and mitochondrial activity in adipose depots, improved glucose homeostasis, and a favorable adipokine profile. At the cellular level, CL treatment increased uncoupling protein 1 (UCP1)-dependent thermogenesis in brown adipose tissue (BAT). However, in white adipose tissue (WAT) depots, CL treatment increased glycerol and lipid de novo lipogenesis (DNL) and turnover suggesting the activation of the futile substrate cycle of lipolysis and reesterification in a UCP1-independent manner. Increased lipid turnover was also associated with the simultaneous upregulation of proteins involved in glycerol metabolism, fatty acid oxidation, and reesterification in WAT. Further, a dose-dependent impact of CL treatment on inflammation was observed, particularly in subcutaneous WAT, suggesting a potential mismatch between fatty acid supply and oxidation. These findings indicate that chronic {beta}3-AR stimulation activates distinct cellular mechanisms that increase energy expenditure in BAT and WAT to improve systemic metabolism in aged mice. Our study provides foundational evidence for targeting adipose thermogenesis to improve age-related metabolic dysfunction.

pharmacology and toxicology↗

bioRxiv2023

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of [~]800 disease reactions constituting [~]400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactomes pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

systems biology↗

bioRxiv2023

ASTA-P: a pipeline for the detection, quantification and statistical analysis of complex alternative splicing events

Alternative splicing dramatically increases the repertoire of the human transcriptome and plays a critical role in cellular differentiation. Long read sequencing has dramatically improved our ability to explore isoform diversity directly. However, short read sequencing still provides advantages in terms of sequencing depth at low cost, which is important in comparative quantitative studies. Here, we present a pipeline called ASTA-P for profiling, quantification, and differential splicing analysis of tissue-specific, arbitrarily complex alternative splicing patterns. We discover novel events by supplementing existing annotation with reconstructed transcripts and use spliced RNA-seq reads to quantify splicing changes accurately based on their unique assignments. We used simulated RNA-seq data to demonstrate that ASTA-P provides a good trade-off between discovery and accuracy compared with several popular methods. Further, we applied ASTA-P to analyse AS patterns in real data from hiPSC derived cranial neural crest cells capturing the transition from primary neural cells into migratory cranial neural crest cells, differentiated by their expression of the transcription factor, SOX10. Our analysis revealed a significant splicing complexity, i.e., numerous AS events that cannot be described using the conventionally analysed 2D splicing event patterns. Such events are misclassified when analysed using current differential splicing analysis methods. Thus, ASTA-P provides a new approach for studying both conventional and complex splicing across different cellular conditions and the dynamic regulation of AS. The pipeline is available at https://github.com/uqktiwar/ASTAP/tree/main

bioinformatics↗

bioRxiv2023

Novel Function of Transcription Factor TTF1 in UV Mediated DNA Damage Repair in Mammalian Cells

Various DNA repair machineries have evolved in the cell to maintain the integrity of the genome for proper functioning of the same. Repair of ultraviolet (UV) irradiation mediated DNA damage occurs by nucleotide excision repair pathway through transcription coupled repair (TCR), a process in which the damage is repaired on transcriptionally active genic regions. This process requires various protein complexes including heterodimer DNA Damage Binding 1 (DDB1) protein. Defects in TCR have been found in patients with mutations in the Cockayne syndrome (CS) group A and group B genes and in the Xeroderma pigmentosum (XP) group G gene. Transcription factors (TFs) play a very important role in regulation of TCR system, especially those TFs which binds to DNA at specific loci. Several TFs have been shown to modulate the repair of photolesions either by inducing or inhibiting the TCR. However, the mechanism behind their action is not very clear. Mammalian TTF1 is an essential multifunctional transcription factor involved in transcription initiation, termination, DNA fork blockage, chromatin remodelling etc., and has been shown to interact with CSB protein. Hence, to discover its role in TCR and to identify its interaction partners, we purified this protein and did a pull-down assay with HEK293T cell lysate followed by LC-MS and discovered DDB1 as one of its major interactors. This established our confidence that TTF1 protein might be playing a critical role in TCR. Further, we discovered that, upon UV mediated DNA damage in HEK293T cells the expression of TTF1 is significantly induced and is co-localized with {gamma}H2AX protein. To our surprise, we found that after knockdown of TTF1, DDB1 level decreases in HEK293T cells while knockdown of DDB1, increases TTF1 level in the cells. Hence, our study opens up a new avenue towards exploring a noble function of the transcription factor TTF1, which in turn could establish the potential to develop therapeutics towards cancers and other diseases.

biochemistry↗

bioRxiv2022

Biophysical Characterization of an Essential Mammalian Protein; Transcription Termination Factor I (TTF1)

Mammalian Transcription Terminator Factor 1 (TTF1) is an essential protein which plays diverse cellular physiological functions like transcription regulation (both initiation and termination), replication fork blockage, chromatin remodelling, DNA damage repair etc. Hence, understanding the structure and mechanism conferred by its variable confirmations becomes significantly important. But so far, almost nothing is known about the structure of either the full-length protein or any of its domain in isolation. Moving towards achieving the above goals, our lab has codon optimised, expressed and purified N-terminal 190 amino acid deleted TTF1 ({Delta}N190TTF1) protein, since full length protein even after multiple trials could not be purified in soluble form. In this article, we have characterized this essential protein by studying its homogeneity, molecular size and secondary structure using tools like dynamic light scattering (DLS), circular dichroism (CD) spectroscopy, Raman spectroscopy and atomic force microscopy (AFM). By CD and DLS we have shown that the purified protein is homogenous and soluble. CD spectroscopy also revealed that {Delta}N190TTF1 is a helical protein which was further confirmed by analysis of Raman spectra and Amide I region deconvolution studies. AFM imaging data discovered the size of single protein molecule to be 94 nm which is in agreement with the size determined by the DLS study as well. Our structural and biophysical characterization of this essential protein will open avenues towards solving the structure to atomic resolution and also will encourage the research to investigate the mechanism behind its diverse functions attributed to its various domains.

biochemistry↗

bioRxiv2021

Ab initio modelling of an essential mammalian protein: Transcription Termination Factor 1 (TTF1)

Transcription Termination Factor 1 (TTF1) is an essential mammalian protein that regulates cellular transcription, replication fork arrest, DNA damage repair, chromatin remodelling etc. TTF1 interacts with numerous cellular proteins to regulate various cellular phenomena, and plays a crucial role in maintaining normal cellular physiology, dysregulation of which has been reported towards cancerous transformation of the cells. However, despite its key role in cellular physiology, the complete structure of human TTF1 has not been elucidated to date, either experimentally or computationally. Hence, understanding the structure of human TTF1 becomes highly important for studying its functions and interactions with other cellular factors. Therefore, the aim of this study was to construct the complete structure of human TTF1 protein, using molecular modelling approaches. Owing to the lack of suitable homologues in the PDB, the complete structure of human TTF1 was constructed using ab initio modelling. The structural stability was determined using molecular dynamics (MD) simulations in explicit solvent, and trajectory analyses. The representative structure of human TTF1 was obtained by trajectory clustering, and the central residues were determined by centrality analyses of the residue interaction network of TTF1. Two residue clusters, in the oligomerisation domain and C-terminal domain, were determined to be central to the structural stability of human TTF1. To the best of our knowledge, this study is the first to report the complete structure of human TTF1, and the results obtained herein will provide structural insights for future research in cancer biology and related studies. Author SummaryThe transcription termination factor 1 (TTF1) is an essential multifunctional mammalian protein which plays important role in regulating important cellular process like transcription, replication, DNA damage repair, chromatin remodelling etc. and its dysregulation leads to various cancers. Despite its being such an important factor, the complete structure of human TTF1 has not been determined to date, either using experimental techniques or computationally. Therefore, the aim of this study was to construct the complete structure of human TTF1 using computational modelling. In this study the complete structure of human TTF1 was constructed by ab initio modelling using iTasser. The stability of this model was determined by 200 ns molecular dynamics (MD) simulations. The representative conformation of human TTF1 was further determined by clustering the simulation trajectory and the residues that are central to the stability of this structure were identified. The results demonstrate the presence of two residue clusters in human TTF1, one in the oligomerisation domain and other in the C-terminal domain, which were found to be crucial for the structural stability of this protein. Hence, the results of this study will aid future studies in this field towards engineering this important protein for further biochemistry and cell biology research.

bioinformatics↗

bioRxiv2021

High efficiency excitation energy transfer in biohybrid quantum dot-bacterial reaction center nanoconjugates

Reaction centers (RCs) are the pivotal component of natural photosystems, converting solar energy into the potential difference between separated electrons and holes that is used to power much of biology. RCs from anoxygenic purple photosynthetic bacteria such as Rhodobacter sphaeroides only weakly absorb much of the visible region of the solar spectrum which limits their overall light-harvesting capacity. For in vitro applications such as bio-hybrid photodevices this deficiency can be addressed by effectively coupling RCs with synthetic lightharvesting materials. Here, we studied the time scale and efficiency of Forster resonance energy transfer (FRET) in a nanoconjugate assembled from a synthetic quantum dot (QD) antenna and a tailored RC engineered to be fluorescent. Time-correlated single photon counting spectroscopy of biohybrid conjugates enabled the direct determination of FRET from QDs to attached RCs on a time scale of 26.6 {+/-} 0.1 ns and with a high efficiency of 0.75 {+/-} 0.01.

biophysics↗

bioRxiv2020

Reproducibility in systems biology modelling

The reproducibility crisis has emerged as an important concern across many fields of science including life science, since many published results failed to reproduce. Systems biology modelling, which involves mathematical representation of biological processes to study complex system behaviour, was expected to be least affected by this crisis. While lack of reproducibility of experimental results and computational analysis could be a repercussion of several compounded factors, it was not fully understood why systems biology models with well-defined mathematical expressions fail to reproduce and how prevalent it is. Hence, we systematically attempted to reproduce 455 kinetic models of biological processes published in peer-reviewed research articles from 152 journals; which is collectively a work of about 1400 scientists from 49 countries. Our investigation revealed that about half (49%) of the models could not be reproduced using the information provided in the published manuscripts. With further effort, an additional 12% of the models could be reproduced either by empirical correction or support from authors. The other 37% remained non-reproducible models due to missing parameter values, missing initial concentration, inconsistent model structure, or a combination of these factors. Among the corresponding authors of the non-reproducible model we contacted, less than 30% responded. Our analysis revealed that models published in journals across several fields of life science failed to reproduce, revealing a common problem in the peer-review process. Hence, we propose an 8-point reproducibility scorecard that can be used by authors, reviewers and journal editors to assess each model and address the reproducibility crisis.

systems biology↗