Biology subjects

Chaudhari, A.

Publications and source records attributed to Chaudhari, A..

11 recordsLinked to original sources

bioRxiv2026

Synthesis cost is a hidden driver of convergent amino acid composition in plastid ribosomal proteins

Protein evolution is a walk in the evolutionary space directed by mutation and selection. While functional and structural constraints serve as the main determinant of amino acid substitution in most proteins, synthesis cost and mutational bias can also alter the direction and rate of amino acid evolution, especially in systems experiencing relaxed selection. Here, we focused on the highly expressed plastid ribosomal proteins (PRP), which comprise 58 conserved proteins encoded by both plastid and nuclear genomes. Relaxed selection has been repeatedly identified in three distantly related plant lineages, providing a valuable comparative framework to investigate the significance of synthesis cost and mutation. We first demonstrated that the hemiparasitic tribe Cymbarieae (Orobanchaceae) represented a new case where concerted cyto-nuclear rate elevation occurs in their PRP. Further investigation revealed convergent shifts in amino acid composition in all four plant lineages attributable to arginine-to-lysine and methionine-to-isoleucine/valine/leucine substitutions. The replacement residues were biophysically similar but had lower molecular weight and shorter side chains, which significantly destabilized protein folding as demonstrated by protein structure modeling. We found that the composition shifts ran counter to the expectation of mutational bias but were consistent with the expectation of synthesis cost minimization, which is potentially adaptive for highly expressed PRP. Further, cost minimization significantly influenced all conservative substitutions between biophysically similar amino acids but was absent in non-conservative substitutions. We thus propose cost minimization as a secondary selective drive for protein evolution in PRP, unmasked in lineages and sites with relaxed selection on their function.

evolutionary biology↗

bioRxiv2025

Imagined Speech Reconstruction with 3D Neural Metabolism and Large Language Model Integration

Cognitive linguistics posits that language underpins human thought, and this principle has influenced the study and development of large language models (LLMs). In particular, several studies have investigated the metabolic costs of sentence formation using neuroimaging techniques such as positron emission tomography, functional magnetic resonance imaging, electroencephalography (EEG), and imagined speech reconstruction (ISR). In this study, EEG data corresponding to imagined English-language speech phonemes were used for ISR, in combination with an LLM trained on an abridged autobiography. The LLM-generated text responses guided the synthesis of EEG data from relevant phonemes, which were then used to estimate corresponding metabolic activity, and the changes in simulated neurometabolic and electrical parameters were visually represented. Notably, introducing pseudorandom variance significantly (p < 0.001) enhanced the models ability to reflect biological variability. Future directions include expanding the ISR system with lightweight or locally run LLMs, incorporating training data from larger and more diverse populations, and utilizing truly random variability sources. Further optimization for broader hardware compatibility and implementation--such as neural phantoms, emotional context integration, or human-computer interaction platforms--offer promising pathways for advancement. Overall, this work establishes a foundation for the next generation of biologically inspired, modular, and adaptable ISR systems for both research and practical applications.

neuroscience↗

bioRxiv2025

Changes in free-roaming dog population demographics and health associated with a catch-neuter-vaccinate-release program in Jamshedpur, India

Indias large free-roaming dog populations contribute to significant human health, environmental, and social challenges. Population management strategies, such as capture-neuter-vaccinate-return (CNVR), aim to reduce dog numbers, improve their welfare, and reduce human-animal conflict. The Humane Society International, in partnership with the Animal Health Foundation, implemented a CNVR program in Jamshedpur, neutering and vaccinating over 20,000 dogs. This study evaluates the impact of this program on dog health, population structure and size. The study areas encompassed 10 sites within the Jamshedpur Metropolitan Region, including both intervention sites where CNVR was directly applied and sites without direct intervention. Data was collected from May 2014 until December 2018, including bi-annual street surveys, as well as clinical data from the dogs captured and treated. We fit logistic regression, negative binomial, and binomial mixed effects models to assess changes in dog population characteristics, health, and reproductive conditions over time in relation to the CNVR intervention. We found that, over time, the CNVR program significantly reduced the probability of dogs entering the clinic with mange, transmissible venereal tumours, and pregnant. Street surveys showed an increase in sterilised dogs, with higher proportions observed in CNVR-treated sites, although the counts of dogs observed increased overall. The age-structure of free-roaming dogs remained stable over time. In CNVR-treated areas, the probability of observing lactating female dogs decreased, whereas it increased in untreated sites. This work contributes to the growing body of knowledge investigating the impact of dog population management interventions. Continued monitoring and evaluation of CNVR programs are required to identify optimal coverage required to reduce population size effectively.

ecology↗

bioRxiv2024

Marker Data Enhancement For Markerless Motion Capture

ObjectiveHuman pose estimation models can measure movement from videos at a large scale and low cost; however, open-source pose estimation models typically detect only sparse keypoints, which leads to inaccurate joint kinematics. OpenCap, a freely available service for researchers to measure movement from videos, addresses this issue using a deep learning model-- the marker enhancer--that transforms sparse keypoints into dense anatomical markers. However, OpenCap performs poorly on movements not included in the training data. Here, we create a much larger and more diverse training dataset and develop a more accurate and generalizable marker enhancer. MethodsWe compiled marker-based motion capture data from 1176 subjects and synthesized 1433 hours of keypoints and anatomical markers to train the marker enhancer. We evaluated its accuracy in computing kinematics using both benchmark movement videos and synthetic data representing unseen, diverse movements. ResultsThe marker enhancer improved kinematic accuracy on benchmark movements (mean error: 4.1{degrees}, max: 8.7{degrees}) compared to using video keypoints (mean: 9.6{degrees}, max: 43.1{degrees}) and OpenCaps original enhancer (mean: 5.3{degrees}, max: 11.5{degrees}). It also better generalized to unseen, diverse movements (mean: 4.1{degrees}, max: 6.7{degrees}) than OpenCaps original enhancer (mean: 40.4{degrees}, max: 252.0{degrees}). ConclusionOur marker enhancer demonstrates both accuracy and generalizability across diverse movements. SignificanceWe integrated the marker enhancer into OpenCap, thereby offering its thousands of users more accurate measurements across a broader range of movements.

bioengineering↗

bioRxiv2024

In Situ-Crosslinked Zippersomes Enhance Cardiac Repair by Increasing Accumulation and Retention

Mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs) are a promising treatment for myocardial infarction, but their therapeutic efficacy is limited by inefficient accumulation at the target site. A non-invasive MSC EV therapy that enhances EV accumulation at the disease site and extends EV retention could significantly improve post-infarct cardiac regeneration. Here we show that EVs decorated with the next-generation of high-affinity heterodimerizing leucine zippers, termed high-affinity (HiA) Zippersomes, amplify targetable surface areas through in situ crosslinking and exhibited [~]7-fold enhanced accumulation within the infarcted myocardium in mice after three days and continued to be retained up to day 21, surpassing the performance of unmodified EVs. After myocardial infarction in mice, high-affinity Zippersomes increase the ejection fraction by 53% and 100% compared with unmodified EVs and PBS, respectively. This notable improvement in cardiac function played a crucial role in restoring healthy heart performance. High-affinity Zippersomes also robustly decrease infarct size by 52% and 60% compared with unmodified EVs and PBS, respectively, thus representing a promising platform for non-invasive vesicle delivery to the infarcted heart. Translational Impact StatementTherapeutic delivery to the heart remains inefficient and poses a bottleneck in modern drug delivery. Surgical application and intramyocardial injection of therapeutics carry high risks for most heart attack patients. To address these limitations, we have developed a non-invasive strategy for efficient cardiac accumulation of therapeutics using in situ crosslinking. Our approach achieves high cardiac deposition of therapeutics without invasive intramyocardial injections. Patients admitted with myocardial infarction typically receive intravenous access, which would allow painless administration of Zippersomes alongside standard of care.

bioengineering↗

bioRxiv2023

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation

ObjectiveRecent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing self-supervised learning (SSL) techniques to leverage large IMU datasets to pre-train deep learning models, which can improve the accuracy and data efficiency of IMU-based GRF estimation. MethodsWe performed SSL by masking a random portion of the input IMU data and training a transformer model to reconstruct the masked portion. We systematically compared a series of masking ratios across three pre-training datasets that included real IMU data, synthetic IMU data, or a combination of the two. Finally, we built models that used pre-training and labeled data to estimate GRF during three prediction tasks: overground walking, treadmill walking, and drop landing. ResultsWhen using the same amount of labeled data, SSL pre-training significantly improved the accuracy of 3-axis GRF estimation during walking compared to baseline models trained by conventional supervised learning. Fine-tuning SSL model with 1-10% of walking data yielded comparable accuracy to training baseline model with 100% of walking data. The optimal masking ratio for SSL is 6.25-12.5%. ConclusionSSL leveraged large real and synthetic IMU datasets to increase the accuracy and data efficiency of deep-learning-based GRF estimation, reducing the need for labeled data. SignificanceThis work, with its open-source code and models, may unlock broader use cases of IMU-driven kinetic assessment by mitigating the scarcity of GRF measurements in practical applications.

bioengineering↗

bioRxiv2021

CRISPR-Cas9 mediated knockout of SagD gene for overexpression of streptokinase in Streptococcus equisimilis

Streptokinase is an enzyme that can break down the blood clots in some cases of myocardial infarction (Heart attack), pulmonary embolism, and arterial thromboembolism. Demand for streptokinase is high globally than the production due to increased incidences of various heart conditions. The main source of streptokinase is from various strains of Streptococcus. Expression of streptokinase in native strain Streptococcus equisimilis is limited due to the SagD inhibitor gene for production of streptokinase that needs to be knocked out in order to increase it expression. However, FasX is a small RNA (sRNA) present in group A Streptococcus species which is responsible for post-transcriptional regulation of streptokinase (ska) gene by binding at the 5 end of ska mRNA. S. equisimilis is a {beta}-hemolysin producing streptococcus bacterium (group C) containing the orthologue of FasX and natively expresses a clinically important thrombolytic streptokinase. In order to improve the stability of mRNA and increasing the expression of streptokinase which is inhibited by SagD. We used CRISPR-Cas9 to successfully knock-out of SagD gene and observed a 13.58-fold relative quantification of streptokinase expression in the mutant strain as compared to wild type. We have also demonstrated the successful target gene knockout using CRISPR-Cas9 in S. equisimilis that engineered strain can be used further for overexpression of streptokinase for therapeutic applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/465095v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@8e3ebeorg.highwire.dtl.DTLVardef@b92f4eorg.highwire.dtl.DTLVardef@1d0dd8borg.highwire.dtl.DTLVardef@180ee54_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2021

Defective ORF8 dimerization in delta variant of SARS CoV2 leads to abrogation of ORF8 MHC-I interaction and overcome suppression of adaptive immune response

In India, the breakthrough infections during second wave of COVID-19 pandemic was due to SARS-COV-2 delta variant (B.1.617.2). It was reported that majority of the infections were caused by the delta variant and only 9.8% percent cases required hospitalization whereas, only 0.4% fatality was observed. Sudden dropdown in COVID-19 infections was observed within a short timeframe, suggesting better host adaptation with evolved delta variant. Down regulation of host immune response against SARS-CoV-2 by ORF8 induced MHC-I degradation has been reported earlier. The Delta variant carried mutations (deletion) at Asp119 and Phe120 amino acids which are critical for ORF8 dimerization. The deletions of amino acids Asp119 and Phe120 in ORF8 of delta variant results in structural instability of ORF8 dimer caused by disruption of hydrogen bonding and salt bridges as revealed by structural analysis and MD simulation studies of ORF8 dimer. Further, flexible docking of wild type and mutant ORF8 dimer revealed reduced interaction of mutant ORF8 dimer with MHC-I as compared to wild type ORF8 dimer with MHC-1, thus implicating its possible role in MHC-I expression and host immune response against SARS-CoV-2. We thus propose that mutant ORF8 may not hindering the MHC-I expression thereby resulting in better immune response against SARS-CoV-2 delta variant, which partly explains the sudden drop of SARS-CoV-2 infection rate in the second wave of SARS-CoV-2 predominated by delta variant in India Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/457457v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@751eeaorg.highwire.dtl.DTLVardef@140b5b5org.highwire.dtl.DTLVardef@159a3a5org.highwire.dtl.DTLVardef@6c206_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

E156/G and Arg158, Phe-157/del mutation in NTD of spike protein in B.1.167.2 lineage of SARS-CoV-2 leads to immune evasion through antibody escape

Emerging variants of SARS-CoV-2 with better immune escape mechanisms and higher transmissibility remains a persistent threat across the globe. B.1.617.2 (Delta) variant was first emerged from Maharashtra, India in December, 2020. This variant is classified to be a major cause and concern of the second wave of COVID-19 in India. In the present study, we explored the genomic and structural basis of this variant through computational analysis, protein modelling and molecular dynamics (MD) simulations approach. B.1.617.2 variant carried E156G and Arg158, Phe-157/del mutations in NTD of spike protein. These mutations in N-terminal domain (NTD) of spike protein of B.1.617.2 variant revealed more rigidity and reduced flexibility compared to spike protein of Wuhan isolate. Further, docking and MD simulation study with 4A8 monoclonal antibody which was reported to bind NTD of spike protein suggested reduced binding of B.1.617.2 spike protein compared to that of spike protein of Wuhan isolate. The results of the present study demonstrate the possible case of immune escape and thereby fitness advantage of the new variant and further warrants demonstration through experimental evidence. Our study identified the probable mechanism through which B.1.617.2 variant is more pathogenically evolved with higher transmissibility as compared to the wild-type. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/447321v3_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@b92cborg.highwire.dtl.DTLVardef@1d261f7org.highwire.dtl.DTLVardef@11da73eorg.highwire.dtl.DTLVardef@1cef6ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2020

In-Silico analysis reveals lower transcription efficiency of C241T variant of SARS-CoV-2 with host replication factors MADP1 and hnRNP-1

Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more than 1.5 million lives worldwide and counting. As per the GISAID database, the genomics of SARS-CoV2 is extensively studied with more than 500 genome submissions per day. Out of several hotspot mutations within the SARS-CoV-2 genome, researchers have focused a lot on missense variants but the least work is done on the UTRs. One of the most frequent 5 UTR variants in the SARS-CoV-2 genome is the C241T with a global frequency of more than 0.9. In the present study, the effect of the C241T mutation has been studied with respect to change in RNA structure and its interaction with the host replication factors MADP1 Zinc finger CCHC-type and RNA-binding motif 1 (hnRNP1). The results obtained from molecular docking and molecular dynamics simulation indicated weaker interaction of C241T mutant stem loops with host transcription factor MADP1 indicating reduced replication efficiency. The results are also correlated with increased recovery rates and decreased death rates of global SARS-CoV-2 cases.

bioinformatics↗

bioRxiv2018

Real-time three-dimensional MRI for the assessment of dynamic carpal instability

Carpal instability is defined as a condition where wrist motion or loading creates mechanical dysfunction, resulting in weakness, pain and decreased function. Often the diagnosis is made late when malalignment is visualized on static radiography, CT, or MRI. When conventional imaging methods do not identify the instability patterns, yet clinical signs associated with instability exist, the diagnosis of dynamic instability is often suggested to describe carpal derangement manifested only during the wrists active motion or stress. We addressed the question: can advanced MRI techniques provide quantitative measures for evaluating dynamic carpal instability and supplement standard static MRI acquisition? Our objectives were to [1] develop a real-time, three-dimensional MRI method to image the carpal joints during their active, uninterrupted motion; and [2] demonstrate feasibility of the method for assessing metrics relevant to dynamic carpal instability, thus overcoming limitations of conventional MRI. Twenty wrists (bilateral wrists of ten healthy participants) were scanned during radial-ulnar deviation and clenched-fist maneuvers. Images resulting from two real-time MRI pulse sequences, four sparse data acquisition schemes, and three constrained image reconstruction priors were compared. Image quality was assessed via blinded scoring by two radiologists and quantitative imaging metrics. Data acquisition employing sparse radial sampling with a gradient-recalled-echo acquisition and constrained iterative reconstruction (temporal resolution up to 135 ms per slice) appeared to provide a reasonable tradeoff between imaging speed and quality. This real-time MRI method effectively reduced streaking artifacts arising from data undersampling and enabled the derivation of quantitative measures pertinent to evaluating dynamic carpal instability.

bioengineering↗