Biology subjects

Shinde, P.

Publications and source records attributed to Shinde, P..

12 recordsLinked to original sources

bioRxiv2026

An Open Benchmark for Systems Vaccinology: Insights from the CMI-PB Challenges

Systems vaccinology approaches have identified factors affecting vaccine responses in multiple studies, but the ability of computational models to generalize these findings to unseen data remains unclear. We established a community resource to create and compare models predicting B. pertussis booster vaccination responses and put such modeling approaches to the test. We compiled multi-modal experimental training data from three independent cohorts (n=117 individuals), and asked investigators to predict vaccine responses in a cohort of 54 newly recruited individuals using only their pre-booster vaccination data. We benchmarked a total of 107 computational models. Top-performing models were characterized by workflows that prioritized rigorous data preprocessing, robust imputation of missing data, and the use of multi-omics integration or non-linear machine learning. We identified pre-existing antigen-specific antibody titers and baseline monocyte frequencies as the most consistent predictors of post-vaccination immunity, highlighting the dominant role of individual immune setpoints. We established the resulting datasets and evaluation framework as a community resource to advance predictive immunology and facilitate personalized vaccination strategies.

immunology↗

bioRxiv2025

Influenza virus infection in the lungs leads to pancytopenia and defective immune cell differentiation program in the thymus and bone marrow

Exaggerated inflammation and cytokine storm are hallmark features of influenza A virus (IAV)-induced respiratory diseases. While previous studies unequivocally demonstrated the pathophysiological consequences (multiorgan failure) of IAV-associated cytokine storm, it remains unknown if IAV-induced systemic inflammation impacts the "fitness" and differentiation of immune cells from hematopoietic stem cells (HSCs). Our data on lethal IAV-infected C57BL/6 wildtype mice after 10 days of infection indicated reduced monocyte- and lymphocyte-counts in the peripheral blood, and overall cellularity of spleen, thymus and lymph nodes. IAV-infection resulted in increased numbers of myeloid cells, CD8+ T cells, alveolar macrophages (AVMs), CD11b+ dendritic cells (DCs) & plasmacytoid DCs (pDCs), whereas decreased frequencies of CD103+ DCs, in the lungs of IAV-infected mice. Analysis of spleen and draining lymph nodes indicated reduced absolute numbers of B cells, T cells, monocytes and DCs after 10 days of lethal IAV infection. Thymic analysis indicated perturbed T cell differentiation and bone marrow (BM) data revealed impaired DC differentiation following IAV infection. Hematopoietic stem and progenitor cells (HSPCs) studies demonstrated an imbalanced distribution of HSCs, multipotent progenitors (MPPs), myeloid progenitors and DC progenitors within the BM niche. Mechanistic studies exhibited elevated levels of systemic inflammation and altered local pro-inflammatory milieu. Molecular analyses documented elevated levels of intracellular reactive oxygen species (ROS) at all stages of HSPC differentiation and increased mass of active mitochondria in HSPC subsets. In essence, our studies provide novel insights into mechanisms through which lethal IAV-infection induces deficiencies of the innate and adaptive immune system.

immunology↗

bioRxiv2024

Putting computational models of immunity to the test - an invited challenge to predict B. pertussis vaccination outcomes

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting B. pertussis booster responses and generate experimental data for the explicit purpose of model evaluation. We here describe our second computational prediction challenge using this resource, where we benchmarked 49 algorithms from 53 scientists. We found that the most successful models stood out in their handling of nonlinearities, reducing large feature sets to representative subsets, and advanced data preprocessing. In contrast, we found that models adopted from literature that were developed to predict vaccine antibody responses in other settings performed poorly, reinforcing the need for purpose-built models. Overall, this demonstrates the value of purpose-generated datasets for rigorous and open model evaluations to identify features that improve the reliability and applicability of computational models in vaccine response prediction.

immunology↗

bioRxiv2024

Th1 polarization in Bordetella pertussis vaccine responses is maintained through a positive feedback loop

Outbreaks of Bordetella pertussis (BP), the causative agent of whooping cough, continue despite broad vaccination coverage and have been increasing since vaccination switched from whole-BP (wP) to acellular BP (aP) vaccines. wP vaccination has been associated with more durable protective immunity and an induced Th1 polarized memory T cell response. Here, a multi-omics approach was applied to profile the immune response of 30 wP and 31 aP-primed individuals and identify correlates of T cell polarization before and after Tdap booster vaccination. We found that transcriptional changes indicating an interferon response on day 1 post-booster along with elevated plasma concentrations of IFN-{gamma} and interferon-induced chemokines that peaked at day 1-3 post-booster correlated best with the Th1 polarization of the vaccine-induced memory T cell response on day 28. Our studies suggest that wP-primed individuals maintain their Th1 polarization through this early memory interferon response. This suggests that stimulating the interferon pathway during vaccination could be an effective strategy to elicit a predominant Th1 response in aP-primed individuals that protects better against infection.

immunology↗

bioRxiv2024

Brain rewiring during developmental transitions: A Comparative Analysis of Larva and Adult Drosophila melanogaster

The brains ability to adapt through structural rewiring during developmental transitions is a fundamental aspect of neuroscience. Our study conducts a detailed comparison of Drosophila melanogaster s brain networks during larval and adult stages, revealing significant changes in neuronal wiring during developmental phases. The degree distribution of the larval brain deviates significantly from power-law behavior and fits well with the Weibull distribution. In contrast, the adult brain exhibits power-law behavior in its degree distribution, with the exponent for the out-degree distribution lying in the scale-free regime and the exponent for the in-degree distribution being close to this regime. This difference reflects a change in the robustness of brain development from larval to adult phases. The core of these networks also changes during development in terms of their cell composition and topological influence. The larval core comprises Mushroom Body neurons, while the adult core mainly has Antennal Lobe neurons. Moreover, all the core neurons in the larval brain are also part of the rich-club neurons, a group of neurons with high in/out degrees that are well connected, whereas the same is not true for the adult brain network. Additionally, the core of the larval brain displays a more heterogeneous connectivity profile in its second-order neighbors compared to adult brain neurons, indicating greater diversity in larval brain connectivity. Our work stands as a step forward in understanding the rewiring of brain networks across the life stages of Drosophila melanogaster.

neuroscience↗

bioRxiv2023

Integrated longitudinal multi-omics study identifies immune programs associated with COVID-19 severity and mortality in 1152 hospitalized participants

Hospitalized COVID-19 patients exhibit diverse clinical outcomes, with some individuals diverging over time even though their initial disease severity appears similar. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity. In this study, we carried out deep immunophenotyping and conducted longitudinal multi-omics modeling integrating ten distinct assays on a total of 1,152 IMPACC participants and identified several immune cascades that were significant drivers of differential clinical outcomes. Increasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, NETosis, and T-cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma immunoglobulins and B cells, as well as dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to the failure of viral clearance in patients with fatal illness. Our longitudinal multi-omics profiling study revealed novel temporal coordination across diverse omics that potentially explain disease progression, providing insights that inform the targeted development of therapies for hospitalized COVID-19 patients, especially those critically ill.

immunology↗

bioRxiv2023

A systems vaccinology resource to develop and test computational models of immunity

Computational models that predict an individuals response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such dry run for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.

systems biology↗

bioRxiv2023

Differential modulation of miR-122 transcription by TGFbeta1/BMP6: implications for nonresolving inflammation and hepatocarcinogenesis

Chronic inflammation is widely recognized as a significant factor that promotes and worsens the development of malignancies, including hepatocellular carcinoma. This study aimed to explore the potential role of microRNAs in inflammation-associated nonresolving hepatocarcinogenesis. By conducting a comprehensive analysis of altered microRNAs in animal models with liver cancer of various etiologies, we identified miR-122 as the most significantly downregulated microRNA in the liver of animals with inflammation-associated liver cancer. Although previous research has indicated the importance of miR-122 in maintaining hepatocyte function, its specific role as either the trigger or the consequence of underlying diseases remains unclear. Through extensive analysis of animals and in vitro models, we have successfully demonstrated that MIR122 transcription is differentially regulated by the immunoregulatory cytokines by the transforming growth factor-beta 1 (TGF{beta}1) and the bone morphogenetic protein- 6 (BMP6). Furthermore, we presented convincing evidence directly linking reduced MIR122 transcription to inflammation and in chronic liver diseases. The results of this study strongly suggest that prolonged activation of signaling pathways, leading to disruption of cytokine-mediated regulation of MIR122, may significantly contribute to the onset and exacerbation of chronic liver disease.

cancer biology↗

bioRxiv2023

Higher-order co-mutation interactions in mitochondrial genomes

Pair-wise co-mutation networks of the mitochondrial genome have already provided ample evidences about the roles of genetic interactions in the manifestation of phenotype under altered environmental conditions. Here, we present a method to construct and analyze higher-order interactions, namely, 3-uniform hypergraphs of the mitochondrial genome for different altitude populations to decipher the role of co-mutating variable sites beyond pair-wise interactions. While the weights distribution of such gene hyperedges manifested power-law for all the altitudes, we identified altitude-specific genes based on gene hyperedge weight. This framework of hypergraphs serves a promising avenue for future investigation of nuclear genomes in context of phenotypic association and genetic disorders.

systems biology↗

bioRxiv2022

Discovery of oncogenic ROS1 missense mutations with sensitivity to tyrosine kinase inhibitors

Chromosomal rearrangements of ROS1 generate ROS1 tyrosine kinase fusion proteins that are established oncogenes predicting effectiveness of tyrosine kinase inhibitors (TKI) treatment. The cancer genome reveals nonsynonymous missense mutations in ROS1, however, their oncogenic potential remains unknown. We nominated thirty-four tumor-associated missense mutations in ROS1 kinase domain for functional interrogation. Immunoblotting revealed diverse impact of the mutations on the kinase, ranging from loss of function to significant increase in catalytic activity. Notably, Asn and Gly substitutions at the Asp-2113 position in ROS1 kinase domain were TKI- sensitive hyper-activating mutations, and transformative oncogenes in independent cell models. Molecular modeling revealed drastic alterations in the activation loop of ROS1D2113N compared to wildtype kinase. Proteomics studies showed that ROS1D2113N increases phosphorylation of known effectors akin to ROS1 fusions, and upregulates pathways not previously linked to ROS1, including mTORC2, JNK1/2, AP-1, TGFB1 and CCN1/2. In vivo, ROS1D2113N drove tumor formation that was sensitive to inhibition by crizotinib and lorlatinib. Taken together, these data show that select point mutations within ROS1 RTK are oncogenic, and maybe therapeutically targetable with FDA-approved TKI.

cancer biology↗

bioRxiv2018

Impact of mitochondrial epistatic interactions on evolution of different human subpopulations

Investigation of human mitochondrial (mt) genome variation has been shown to provide insights to the human history and natural selection. By analyzing 24,167 human mt-genome samples, collected for five continents, we have developed a co-mutation network model to investigate characteristic human evolutionary patterns. The analysis highlighted richer co-mutating regions of the mt-genome, suggesting the presence of epistasis. Specifically, a large portion of COX genes was found to co-mutate in Asian and American populations, whereas, in African, European, and Oceanic populations, there was greater co-mutation bias in hypervariable regions. Interestingly, this study demonstrated hierarchical modularity as a crucial agent for these co-mutation networks. More profoundly, our ancestry-based co-mutation module analyses showed that mutations cluster preferentially in known mitochondrial haplogroups. Contemporary human mt-genome nucleotides most closely resembled the ancestral state, and very few of them were found to be ancestral-variants. Overall, these results demonstrated that subpopulation-based biases may favor mitochondrial gene specific epistasis.

synthetic biology↗

bioRxiv2016

Codon based co-occurrence network motifs in human mitochondria

Human mitochondrial DNA (mtDNA) generates a highly divergent pool of alleles even within species that have dispersed and expanded in size. On top of that codon position bias plays a relative role in prompting population wide sequence based variations. Codon positions are immensely studied as independent evolutionary genetic markers, however co-evolution of codon positions are still largely unexplored. Using 18,411 genome samples, we analyze nucleotide co-occurrences over mitochondrial DNA of human sub-populations covering most of the mtDNA diversity on the earth. Our codon based network motif investigation reveals that codon position is one of the critical factor to form higher order motifs. It is interesting to report a different evolution of Asian genomes than those of the rest which is divulged by motifs in non-coding regions. Most notably, we demonstrate that there are preferences of codon position co-evolution with respect to codon position sensitivity implying the selective role of evolutionary processes on fundamental formation of genetic code in terms of codon bias evolution. These network based findings not only recapitulates the established facts regarding the importance of each codon position in providing codon bias but also highlight their preferential role in resulting correlated mutations. Moreover, codon based nucleotide co-occurrence provides framework to investigate important evolutionary insights into human mitochondrial evolutionary genomics.

evolutionary biology↗