Biology subjects

Sarma, S.

Publications and source records attributed to Sarma, S..

15 recordsLinked to original sources

bioRxiv2025

Designed Peptides as Affinity Ligands for Extracellular-Vesicle-based Cancer Biomarker Detection

Assays for cancer diagnosis via the analysis of tumor biomarkers on circulating extracellular vesicles (EVs) have shown great potential. Single EV imaging that can measure the abundance of protein biomarkers in EVs can help in detecting the presence, stage, and progression of disease. Antibodies are typically used to detect EV proteins. Controlling the quality of antibody-based immunoassays can, however, be challenging, as they may exhibit unintended cross-reactivity with non-target proteins or variability in binding affinity across different batches, even for monoclonal antibodies. Here, we report short peptides that are a promising alternative to antibodies for detecting protein biomarkers in EVs. We describe an effort that combines a Peptide Binding Design (PepBD) algorithm and molecular-level simulations to identify peptides that can recognize (1) the extracellular domain of EpCAM (a known cancer biomarker) and (2) the extracellular domain of tetraspanin CD81(a protein commonly expressed on the surface of EVs). The peptides designed for EpCAM and CD81 were labeled with a fluorescent dye and their binding to the target protein was evaluated using fluorescence ELISA. The results demonstrated that one of the computationally designed peptides EP-2.1 exhibited an affinity for the target EpCAM protein comparable to that of an antibody. Further testing involved single EV imaging to gauge the peptides affinity towards EVs. Designed peptides for both the target proteins showed similar affinity as antibodies to EVs.

cancer biology↗

bioRxiv2024

Unified Sampling and Ranking for Protein Docking with DFMDock

Recent diffusion-based approaches to protein-protein docking typically decouple structure generation from decoy ranking. We introduce DFMDock (Denoising Force Matching for Docking), a unified diffusion model that integrates generative sampling and energy-based ranking through physically motivated supervision. DFMDock predicts both denoising forces and a scalar energy, trained using force matching and energy contrastive objectives. The predicted forces guide the reverse diffusion process, while the energy enables decoy ranking without relying on a separately trained confidence model. On the Docking Benchmark 5, DFMDock achieves a 32.8% Oracle success rate and 5.3% Top-1 success rate, outperforming DiffDock-PP (16.2% and 4.3%, respectively). Unlike co-folding models, DFM-Dock does not require MSAs and generalizes to unseen targets. In decoy ranking, its learned energy function outperforms Rosetta energy and model-derived confidence scores, producing funnel-shaped energy landscapes enriched for near-native structures. These results suggest DFMDock as an efficient and physically grounded approach to diffusion-based protein docking.

bioinformatics↗

bioRxiv2024

Development of MHC Class I Blocking Peptides to Target Metabolic Dysfunction-Associated Steatohepatitis CD8+ T Cell Activation

MHC class I molecules play a crucial role in the immune system by presenting peptides derived from intracellular proteins to cytotoxic T lymphocytes (CTLs). This process is essential for immune surveillance and eliminating infected or malignant cells. In some diseases, the immune system fails to recognize and eliminate abnormal cells, leading to disease progression. Under conditions of metabolic dysfunction-associated steatohepatitis (MASH), subsets of CD8+ T cells have been identified as pathogenic, leading to inflammation and fibrosis. Therefore, explicitly targeting factors responsible for T cell activation may be necessary to prevent the onset of MASH and future complications such as cirrhosis or hepatocellular carcinoma. We have identified a specific MHC class I antigen that activates hepatic and splenic CD8+ T cells isolated from MASH mice. To specifically target the antigen, we developed two MHC H2-Kb blocking peptides, MHCP3 and MHCP5, that competitively inhibit the Ncf2 peptide from binding to H2-Kb and reduce activation and proliferation of CD8+ T cells. By inhibiting the recognition of specific antigens, these blocking peptides may prevent the activation of CD8+ T cells and progression of MASH.

immunology↗

bioRxiv2023

Design of parallel ????-sheet nanofibrils using Monte-Carlo search, coarse-grained simulations, and experimental testing

Peptide self-assembly into amyloid fibrils provides numerous applications in drug delivery and biomedical engineering applications. We augment our previously-established computational screening technique along with experimental biophysical characterization to discover 7-mer peptides that self-assemble into "parallel {beta}-sheets", i.e., {beta}-sheets with N-terminus-to-C-terminus {beta}-strand vectors oriented in parallel. To accomplish the desired {beta}-strand organization, we applied the PepAD amino acid sequence design software to the Class-1 cross-{beta} spine defined by Sawaya et al. This molecular configuration includes two layers of parallel {beta}-sheets stacked such that N-terminus-to-C-terminus vectors are oriented antiparallel for molecules on adjacent {beta}-sheets. The first cohort of PepAD identified peptides were examined for their fibrillation behavior in DMD/PRIME20 simulations, and the top performing sequence was selected as a prototype for a subsequent round of sequence refinement. The two rounds of design resulted in a library of eight 7-mer peptides. In DMD/PRIME20 simulations, five of these peptides spontaneously formed fibril-like structures with a predominantly parallel {beta}-sheet arrangement, two formed fibril-like structure with <50% in parallel {beta}-sheet arrangement and one remained a random coil. Among the eight candidate peptides produced by PepAD and DMD/PRIME20, five were synthesized and purified. All five assembled into amyloid fibrils composed of parallel {beta}-sheets based on Fourier Transform Infrared Spectroscopy, Circular Dichroism, Electron Microscopy, and Thioflavin-T fluorescence spectroscopy measurements.

bioengineering↗

bioRxiv2023

Introgression of a dominant phototropin1 mutant superenhances carotenoids and boosts flavor-related volatiles in genome-edited tomato RIN mutants

The tomato (Solanum lycopersicum) ripening inhibitor (rin) mutation is known to completely repress fruit ripening. The heterozygous (RIN/rin) fruits have extended shelf life, ripen normally, but have poor taste and flavour. Even the CRISPR/Cas9-generated rin alleles have these undesirable attributes associated with the rin mutation. To address this, we used genome editing to generate newer alleles of RIN (rinCR) by targeting the K domain, which is essential for the oligomerization of MADS-box transcription factors. Unlike previously reported CRISPR alleles, the rinCRalleles displayed delayed onset of ripening, suggesting that the mutated K domain represses the onset of ripening. The rinCR fruits had extended shelf life and accumulated carotenoids at an intermediate level between rin and wild-type parent. Besides, the metabolites and hormonal levels in rinCR fruits were more akin to rin. To overcome the negative attributes of rin, we crossed the rinCR alleles with Nps1, which enhances carotenoid levels in tomato fruits. Nps1 harbours a dominant-negative mutation in the plant photoreceptor phototropin1. The resulting Nps1/rinCR hybrids had extended shelf life and 4.4-7.1-fold higher carotenoid levels than the wild-type parent. The Nps1/rinCR fruits had higher auxin and reduced ABA levels, which are reportedly linked with slower ripening. The metabolome of Nps1/rinCRfruits revealed higher sucrose, malate, and volatiles associated with tomato taste and flavour. Notably, the boosted volatile levels in Nps1/rinCR were only observed in fruits bearing the homozygous Nps1 (Nps1/Nps1) mutation. Our findings suggest that the Nps1 introgression into tomato ripening mutants provides a promising strategy for developing tomato cultivars with extended shelf life, improved taste, and flavour.

plant biology↗

bioRxiv2023

Design of 8-mer Peptides that Block Clostridioides difficile Toxin A in Intestinal Cells

Clostridioides difficile (C. diff.) is a bacterium that causes severe diarrhea and inflammation of the colon. The pathogenicity of C. diff. infection is derived from two major toxins, toxins A (TcdA) and B (TcdB). Peptide inhibitors that can be delivered to the gut to inactivate these toxins are an attractive therapeutic strategy. In this work, we present a new approach that combines a peptide binding design algorithm (PepBD), molecular-level simulations, rapid screening of candidate peptides for toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block the glucosyltransferase activity of TcdA by targeting its glucosyltransferase domain (GTD). Using PepBD and explicit-solvent molecular dynamics simulations, we identified seven candidate peptides, SA1-SA7. These peptides were selected for specific TcdA GTD binding through a custom solid-phase peptide screening system, which eliminated the weaker inhibitors SA5-SA7. The efficacies of SA1-SA4 were then tested using a trans-epithelial electrical resistance (TEER) assay on monolayers of the human gut epithelial culture model. One peptide, SA1, was found to block TcdA toxicity in primary-derived human jejunum (small intestinal) and colon (large intestinal) epithelial cells. SA1 bound TcdA with a KD of 56.1 {+/-} 29.8 nM as measured by surface plasmon resonance (SPR). Significance StatementInfections by Clostridioides difficile, a bacterium that targets the large intestine (colon), impact a significant number of people worldwide. Bacterial colonization is mediated by two exotoxins: toxins A and B. Short peptides that can inhibit the biocatalytic activity of these toxins represent a promising strategy to prevent and treat C. diff. infection. We describe an approach that combines a Peptide Binding Design (PepBD) algorithm, molecular-level simulations, a rapid screening assay to evaluate peptide:toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block Toxin A in small intestinal and colon epithelial cells. Importantly, our designed peptide, SA1, bound toxin A with nanomolar affinity and blocked toxicity in colon cells.

bioengineering↗

bioRxiv2022

Transcriptional fluctuations govern the serum dependent cell cycle duration heterogeneities in Mammalian cells

Mammalian cells exhibit a high degree of intercellular variability in cell cycle period and phase durations. However, the factors orchestrating the cell cycle duration heterogeneities remain unclear. Herein, by combining cell cycle network-based mathematical models with live single-cell imaging studies under varied serum conditions, we demonstrate that fluctuating transcription rates of cell cycle regulatory genes across cell lineages and during cell cycle progression in mammalian cells majorly govern the robust correlation patterns of cell cycle period and phase durations among sister, cousin, and mother-daughter lineage pairs. However, for the overall cellular population, alteration in serum level modulates the fluctuation and correlation patterns of cell cycle period and phase durations in a correlated manner. These heterogeneities at the population level can be finetuned under limited serum conditions by perturbing the cell cycle network using a p38-signaling inhibitor without affecting the robust lineage level correlations. Overall, our approach identifies transcriptional fluctuations as the key controlling factor for the cell cycle duration heterogeneities, and predicts ways to reduce cell-to-cell variabilities by perturbing the cell cycle network regulations. Significance statementIn malignant tumors, cells display a diverse pattern in cell division time. This cell-to-cell variability in cell cycle duration had been observed even under culture conditions for various mammalian cells. Here we used live-cell imaging studies to monitor FUCCI-HeLa cells and quantified the cell cycle period and time spent in different phases under varied serum conditions. We proposed a set of stochastic cell cycle network-based mathematical models to investigate the live-cell imaging data and unraveled that the transcription rate variation across cell lineages and during cell cycle phases explains every aspect of the cell cycle duration variabilities. Our models identified how different deterministic effects and stochastic fluctuations control these variabilities and predicted ways to alter these cell cycle duration variabilities.

systems biology↗

bioRxiv2022

Time series analysis of SARS-CoV-2 genomes and correlations among highly prevalent mutations

The efforts of the scientific community to tame the recent SARS-CoV-2 pandemic seems to have been diluted by the emergence of new viral strains. Therefore, it becomes imperative to study and understand the effect of mutations on viral evolution, fitness and pathogenesis. In this regard, we performed a time-series analysis on 59541 SARS-CoV-2 genomic sequences from around the world. These 59541 genomes were grouped according to the months (January 2020-March 2021) based on the collection date. Meta-analysis of this data led us to identify highly significant mutations in viral genomes. Correlation and Hierarchical Clustering of the highly significant mutations led us to the identification of sixteen mutation pairs that were correlated with each other and were present in >30% of the genomes under study. Among these mutation pairs, some of the mutations have been shown to contribute towards the viral replication and fitness suggesting the possible role of other unexplored mutations in viral evolution and pathogenesis. Additionally, we employed various computational tools to investigate the effects of T85I, P323L, and Q57H mutations in Non-structural protein 2 (Nsp2), RNA-dependent RNA polymerase (RdRp) and Open reading frame 3a (ORF3a) respectively. Results show that T85I in Nsp2 and Q57H in ORF3a mutations are deleterious and destabilize the parent protein whereas P323L in RdRp is neutral and has a stabilizing effect. The normalized linear mutual information (nLMI) calculations revealed the significant residue correlation in Nsp2 and ORF3a in contrast to reduce correlation in RdRp protein.

bioinformatics↗

bioRxiv2021

Seeing the unseen: A trifoliate (MYB117) mutant allele fortifies folate and carotenoids in tomato fruits

Micronutrient deficiency also termed hidden hunger affects a large segment of the human population, particularly in developing and underdeveloped nations. Tomato the second most consumed vegetable crop in the world after potato can serve as a sustainable source to alleviate micronutrient deficiency. In tomato, the mutations in the R2R3-MYB117 transcription factor elicit trifoliate leaves and initiate axillary meristems; however, its effect on fruit metabolome remains unexplored. The fruits of a new trifoliate (tf) allele (tf-5) were firmer, had higher {degrees}Brix, folate, and carotenoids. The transcriptome, proteome, and metabolome profiling of tf-5 reflected a broad-spectrum change in homeostasis. The tf-5 allele enhanced the fruit firmness by suppressing cell wall softening-related proteins. The tf-5 fruit displayed a substantial increase in aminome, particularly {gamma}-aminobutyric acid, with a parallel reduction in aminoacyl t-RNA synthases. The increased lipoxygenases proteins and transcripts seemingly elevated jasmonic acid. In addition, increased abscisic acid hydrolases transcripts coupled with reduced precursor supply lowered abscisic acid. The upregulation of carotenoids was mediated by modulation of methylerythreitol and plastoquinone pathways along with an increase in carotenoids isomerization proteins. The upregulation of folate in tf-5 was connoted by the increase in precursor p-aminobenzoic acid and transcripts of several folate biosynthesis pathway genes. The reduction in pterin-6-carboxylate and {gamma}-glutamyl hydrolase activity indicated that the diminished folate degradation also enriched folate levels. Our study delineates that introgression of the tf-5 can be used for the {gamma}-aminobutyric acid, carotenoids, and folate fortification of tomato. One-sentence summaryA tomato trifoliate allele encoding a truncated MYB117 transcription factor alters cellular homeostasis and fortifies {gamma}-aminobutyric acid, folate, and carotenoids in tomato fruits.

plant biology↗

bioRxiv2021

Dynamic Cognitive States Predict Individual Variability in Behavior and Modulate with EEG Functional Connectivity during Working Memory

Fluctuations in strategy, attention, or motivation can cause large variability in performance across task trials. Typically, this variability is treated as noise, and assumed to cancel out, leaving supposedly stable relationships among behavior, neural activity, and experimental task conditions. Those relationships, however, could change with a participants internal cognitive states, and variability in performance may carry important information regarding those states, which cannot be directly measured. Therefore, we used a mathematical, state-space modeling framework to estimate internal states from measured behavioral data, quantifying each participants sensitivity to factors such as past errors or distractions, to predict their reaction time fluctuations. We show how modeling these states greatly improves trial-by-trial prediction of behavior. Further, we identify EEG functional connectivity features that modulate with each state. These results illustrate the potential of this approach and how it could enable quantification of intra- and inter-individual differences and provide insight into their neural bases. Statement of RelevanceCognitive behavioral performance and its neural bases vary both across individuals and within individuals over time. Understanding this variability may be key to the success of clinical or educational interventions. Internal cognitive states reflecting differences in strategy, attention, and motivation may drive much of these inter- and intra-individual differences, but often cannot be reliably controlled or measured in cognitive neuroscience research. The mathematical modeling framework developed here uses measured data to estimate a participants dynamic, internal cognitive states, with each state derived from specific factors hypothesized to affect attention, motivation or strategy. The results highlight potential sources of behavioral variability and reveal EEG features that modulate with each state. Our method quantifies and characterizes individual behavioral differences and highlights their underlying neural mechanisms, which could be used for future targeted training or neuromodulation therapies to improve cognitive performance.

neuroscience↗

bioRxiv2020

Mutations in Tomato 1-Aminocyclopropane Carboxylic Acid Synthase2 Uncover Its Role in Development beside System II Responses

The role of ethylene in plant development is mostly inferred from its exogenous application. The usage of the mutants affecting ethylene biosynthesis proffers a better alternative to decipher its role. In tomato, 1-aminocyclopropane carboxylic acid synthase2 (ACS2) is a key enzyme regulating ripening-specific ethylene biosynthesis. We characterized two contrasting acs2 mutants; acs2-1 overproduces ethylene, has higher ACS activity, and increased protein levels, while acs2-2 is an ethylene under-producer, displays lower ACS activity, and protein levels than wild type. Consistent with high/low ethylene emission, the mutants show opposite phenotypes, physiological responses, and metabolomic profiles than the wild type. The acs2-1 showed early seed germination, faster leaf senescence, and accelerated fruit ripening. Conversely, acs2-2 had delayed seed germination, slower leaf senescence, and prolonged fruit ripening. The phytohormone profiles of mutants were mostly opposite in the leaves and fruits. The faster/slower senescence of acs2-1/acs2-2 leaves correlated with the endogenous ethylene/zeatin ratio. The genetic analysis showed that the metabolite profiles of respective mutants co-segregated with the homozygous mutant progeny. Our results uncover that besides ripening, ACS2 participates in vegetative and reproductive development of tomato. The distinct influence of ethylene on phytohormone profiles indicates intertwining of ethylene action with other phytohormones in regulating plant development.

plant biology↗

bioRxiv2020

In-silico analysis of SARS-CoV-2 genomes: Insights from SARS encoded non-coding RNAs

Recently a novel coronavirus (SARS-CoV-2) emerged from Wuhan, China and has infected more than 571000 people leading to more than 26000 deaths. Since SARS-CoV-2 genome sequences show similarity with those of SARS, we sought to analyze all the available SARS-CoV-2 genomes based on the insights obtained from SARS genome specifically focusing on non-coding RNAs. Here, results are presented from the dual approach i.e identifying host encoded miRNAs that might regulate viral pathogenesis as well as identifying viral encoded miRNAs that might regulate host cell signaling pathways and aid in viral pathogenesis. Analysis utilizing first approach resulted in the identification of 10 host encoded miRNAs that could target the genome of both the viruses (SARS-CoV-2 and SARS reference genome). Interestingly our analysis revealed that there is significantly higher number of host miRNAs that could target SARS-CoV-2 genome as compared to the SARS reference genome. Results from second approach involving SARS-CoV-2 and SARS reference genome identified a set of virus encoded miRNAs which might regulate host signaling pathways. Our analysis further identified a similar "GA" rich motif in SARS-CoV-2 genome that was shown to play a vital role in lung pathogenesis during severe SARS infections. Hence, we successfully identified human and virus encoded miRNAs that might regulate pathogenesis of both these coronaviruses and the fact that more number of host miRNAs could target SARS-CoV-2 genomes possibly reveal as to why this virus follows mild pathogenesis in healthy individuals. We identified non-coding sequences in SARS-CoV-2 genomes that were earlier reported to contribute towards SARS pathology. The study provides insights into the overlapping sequences among these viruses for their effective inhibition as well as identifying new drug targets that could be used for development of new antivirals.

microbiology↗

bioRxiv2019

Nodal Fragility of Intracranial EEG Networks: Towards an EEG Fingerprint for the Epileptogenic Zone

Over 15 million epilepsy patients worldwide do not respond to drugs. Successful surgical treatment requires complete removal, or disconnection of the seizure onset zone (SOZ), brain region(s) where seizures originate. Unfortunately, surgical success rates vary between 30%-70% because no clinically validated biological marker of the SOZ exists. We develop and retrospectively validate a new EEG marker - neural fragility - in a retrospective analysis of 91 patients by using neural fragility of the annotated SOZ as a metric to predict surgical outcomes. Fragility predicts 43/47 surgical failures with an overall prediction accuracy of 76%, compared to the accuracy of clinicians being 48% (successful outcomes). In failed outcomes, we identify fragile regions that were untreated. When compared to 20 EEG features proposed as SOZ markers, fragility outperformed in predictive power and interpretability suggesting neural fragility as an EEG biomarker of the SOZ.

neuroscience↗

bioRxiv2019

Evaluating Invasive EEG Implantations in Medically Refractory Epilepsy with Functional Scalp EEG Recordings and Structural Imaging Data

Seizures in patients with medically refractory epilepsy (MRE) epilepsy cannot be controlled with drugs. For focal MRE, seizures originate in the epileptogenic zone (EZ), which is the minimum amount of cortex that must be treated to be seizure free. Localizing the EZ is often a laborious process wherein clinicians first inspect scalp EEG recordings during several seizure events, and then formulate an implantation plan for subsequent invasive monitoring. The goal of implantation is to place electrodes into the brain region covering the EZ. Then, during invasive monitoring, clinicians visually inspect intracranial EEG recordings to more precisely localize the EZ. The EZ is then surgically removed. Unfortunately surgical success rates average at 50%. Such grim outcomes call for analytical assistance in creating more accurate implantation plans from scalp EEG. In this paper, we introduce a method that combines imaging data (CT and MRI scans) with scalp EEG to derive an implantation distribution. Specifically, scalp EEG data recorded over a seizure event is converted into a time-gamma frequency map, which is then processed to derive a spectrally annotated implantation distribution (SAID). The SAID represents a distribution of gamma power in each of the eight cortical lobe/hemisphere partitions. We applied this method to 4 MRE patients who underwent treatment, and found that the SAID distribution overlapped more with clinical implantations in success cases than in failed cases. These preliminary findings suggest that the SAID may help in improving EZ localization accuracy and surgical outcomes.

neuroscience↗

bioRxiv2017

MutS-Homolog2 Silencing Generates Tetraploid Meiocytes In Tomato (Solanum lycopersicum)

MSH2 is the core protein of MutS-homolog family involved in recognition and repair of the errors in the DNA. While other members of MutS-homolog family reportedly regulate mitochondrial stability, meiosis, and fertility, MSH2 is believed to participate mainly in mismatch repair. The search for polymorphism in MSH2 sequence in tomato accessions revealed both synonymous and nonsynonymous SNPs; however, SIFT algorithm predicted that none of the SNPs influenced MSH2 protein function. The silencing of MSH2 gene expression by RNAi led to phenotypic abnormalities in highly-silenced lines, particularly in the stamens with highly reduced pollen formation. MSH2 silencing exacerbated formation of UV-B induced thymine dimers and blocked light-induced repair of the dimers. The MSH2 silencing also affected the progression of male meiosis to a varying degree with either halt of meiosis at zygotene stage or formation of diploid tetrads. The immunostaining of male meiocytes with centromere localized CENPC (Centromere protein C) protein antibody showed the presence of 48 univalent along with 24 bivalent chromosomes suggesting abnormal tetraploid meiosis. The mitotic cells of root tips of silenced lines showed diploid nuclei but lacked intervening cell plates leading to cells with syncytial nuclei. Thus we speculate that tetraploid pollen mother cells may have arisen due to the fusion of syncytial nuclei before the onset of meiosis. It is likely that in addition to Mismatch repair (MMR), MSH2 may have an additional role in regulating ploidy stability.

plant biology↗