Biology subjects

Verma, A.

Publications and source records attributed to Verma, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Depth-Resolved Macroscopic Fluorescence Lifetime Imaging via High-Spatial-Frequency Structured Illumination

SignificanceMacroscopic Fluorescence Lifetime Imaging (MFLI) is a powerful, non-invasive imaging modality that offers robust, physiologically relevant contrast largely independent of fluorophore concentration, excitation intensity, and tissue signal attenuation. However, accurately determining the depth of signal origin remains challenging, potentially leading to ambiguity in biological interpretation. Here, we present a novel optical correction method that effectively eliminates surface signal bias, such as that from skin in preclinical imaging, without the need for chemical clearance. This advancement supports the robust applicability of MFLI in translational research. AimEstablishment of a High Spatial Frequency-Fluorescence Lifetime Imaging (HSF-FLI) framework to selectively isolate subsurface fluorescence (deeper signals) from surface fluorescence, while preserving the accuracy of lifetime estimation. ApproachA modulation transfer function (MTF) that relates spatial frequency to penetration depth was derived using Monte Carlo eXtreme (MCX) simulations (for physics-based modeling) and validated with agar-based capillary phantoms on a time-gated ICCD-DMD system. Depth-independent fluorescence was decomposed into surface and subsurface components through structured three-phase sinusoidal illumination, and nonlinear least squares fitting was applied to recover lifetime or lifetime based parameters maps. HSF-FLI was demonstrated in vivo in mouse models bearing tumor xenogratfs and was cross validated with ex vivo measurements. ResultsWe extensively characterized the performance of High Spatial Frequency-Fluorescence Lifetime Imaging (HSF-FLI) through simulations and tissue-mimicking phantoms. The approach was further validated in vivo by assessing drug delivery in preclinical models using MFLI-FRET (Forster Resonance Energy Transfer). ConclusionBy coupling structured illumination with physics-based depth modeling, HSF-FLI delivers accurate, depth-selective lifetime readouts, setting the stage for robust and fast FLI implementation in translational studies.

bioengineering↗

bioRxiv2025

Live-cell analyses with unsegmented images to study cancer cell response to modified T cell therapy

Live-cell imaging (LCI) of modified T cells co-cultured with cancer cells is commonly used to quantify T cell anti-cancer function. Videos captured by LCI show complex multi-cell behavioral phenotypes that go beyond simple cancer cell fluorescence measurements. Here, we develop an unsupervised analysis workflow to characterize LCI data generated using the Incucyte imaging platform. Unlike most LCI analyses, we avoid cell segmentation due to the low spatiotemporal resolution of the LCI videos and high levels of cell-cell contact. Instead, we develop methods that identify global aggregation patterns and local cellular keypoints to characterize the multicellular interactions that determine cancer cell sensitivity to, or escape from, T cell surveillance. We demonstrate our segmentation-free live-cell behavioral analysis (SF-LCBA) methods on TCR T cells from four donors with varying proportions of cells with a beneficial RASA2 knockout and effector-to-target initial concentrations in a co-culture with A375 melanoma cells. We find that different T cell modifications affect the spatiotemporal dynamics of multicellular aggregate formation. In particular, we show that fewer and smaller cancer cell aggregates form at high ratios of effector T cells to target cancer cells and high titrations of T cells with RASA2 knockouts. Our SF-LCBA method identifies, characterizes, and tracks cellular aggregate formation in datasets that are unsuitable for cell segmentation and tracking, opening the door to more therapeutically-relevant measurements of modified T cell therapy cell behavioral phenotypes from LCI data.

cancer biology↗

bioRxiv2025

Peripheral blood cell-type and sex-specific signatures of alcohol misuse revealed by single-cell transcriptomics

Alcohol use disorder (AUD) is a complex condition with diverse molecular underpinnings. Chronic alcohol exposure is associated with alterations in both innate and adaptive immune cell populations that in turn contribute to AUD susceptibility and severity, suggesting a bidirectional gene-environment relationship. Yet, most clinical AUD studies of this system have relied on indirect measurement of immune function and/or assessment of only a small number of cell types or immune markers, approaches which cannot capture the immune systems inherent complexity and cellular heterogeneity. Therefore, in order to better characterize immune dysregulation in AUD, the goal of this study was to use single cell RNA sequencing (scRNA-seq) in peripheral blood mononuclear cells (PBMCs) to compare immune cell proportions and differential gene expression between individuals with AUD and healthy controls. Our findings highlight a distinct disproportionality of lymphocytes and monocytes in individuals with AUD and healthy controls as well as sex and dose-dependent alterations immune cell functional characteristics. These peripheral blood cell-type proportions and dose-dependent signatures of alcohol exposure may aid in developing more targeted and effective pharmacological interventions for AUD. Results also highlight the importance in including sex as a biological variable in AUD research, particularly when examining immune function.

genomics↗

bioRxiv2025

Evolutionary responses to historic drought across the range of scarlet monkeyflower

Adaptive evolution is a key means for populations to persist under environmental change, yet whether populations across a species range can adapt quickly enough to keep pace with climate change remains unknown. The breeders equation predicts the evolutionary change in a trait from one generation to the next as the product of the selection differential and the narrow-sense heritability in that trait. Incorporating these aspects of the breeders equation, we performed a resurrection study with the scarlet monkeyflower (Mimulus cardinalis) to evaluate whether traits associated with drought adaptation have evolved in populations across a species range in response to extreme drought. We compared trait and fitness differences of pre-drought ancestors and post-drought descendants from six populations transplanted into three latitudinally-arrayed common gardens and quantified phenotypic selection and trait heritabilities. The strength, direction, and mode of selection varied among traits and gardens. Trait heritabilities were relatively low, and did not differ dramatically among populations or gardens. Overall, instances of evolutionary responses between ancestors and descendants were few and small in magnitude, but the magnitude of these evolutionary differences varied among gardens. Together, these results suggest that the expression of genetic variation, and thus traits, depend on the environment, and that environmental variability in field settings may mask the genetic variation that is often detected in greenhouse environments.

evolutionary biology↗

bioRxiv2025

Affinity-matured CD72-targeting Nanobody CAR T-cells Enhance Elimination of Antigen-Low B-cell Malignancies

BackgroundChimeric antigen receptor (CAR) T-cell therapies are highly efficacious for several different hematologic cancers. However, for most CAR T targets it is observed that low surface antigen density on tumors can significantly reduce therapeutic efficacy. Here, we explore this dynamic in the context of CD72, a surface antigen we recently found as a promising target for refractory B-cell cancers, but for which CD72 low antigen density can lead to therapeutic resistance in preclinical models. MethodsPrimary samples were accessed via institutional review board-approved protocols. Affinity-matured and humanized nanobody clones were previously described in Temple et al.1 CAR T-cells were generated via lentiviral transduction. In vitro cytotoxicity assays were performed using luciferase-labeled cell lines. In vivo studies were performed using cell line- or patient-derived xenografts implanted in NOD scid gamma (NSG) mice. ResultsWe first confirmed ubiquitous CD72 expression across a range of primary B-cell non-Hodgkin lymphomas. We further found that after resistance to CD19-directed therapies, across both B-cell acute lymphoblastic leukemia (B-ALL) models and primary tumor samples, surface CD72 expression was largely preserved while CD22 expression was significantly diminished. Affinity maturation of a nanobody targeting CD72, when incorporated into chimeric antigen receptor (CAR) T-cells, led to more effective elimination in vitro of isogenic models of CD72 low-expressing tumors. These results suggested that nanobody-based CAR T-cells (nanoCARs) may exhibit a similar relationship between binder affinity, antigen expression, and efficacy as previously demonstrated only for scFv-based CAR T-cells. Surprisingly, however, this significantly improved in vitro efficacy only translated to modest in vivo survival benefit. As a parallel strategy to enhance CAR T function, we found that the small molecule bryostatin could also significantly increase CD72 surface antigen density on B-cell malignancy models. Structural modeling and biochemical analysis identified critical residues improving CD72 antigen recognition of our lead affinity-matured nanobody. ConclusionsTogether, these findings support affinity-matured CD72 nanoCARs as a potential immunotherapy product for CD19-refractory B-cell cancers. Our results also suggest that for B-ALL in particular, CD72 may be a preferable second-line immunotherapy target over CD22. What is already known on this topicPrevious work using single chain variable fragment (scFv) based CAR Ts has suggested that improving affinity for target antigen could potentially help mitigate tumor resistance mediated by antigen downregulation, or baseline low antigen density. However, it is unknown whether this same dynamic holds for CAR T-cells that utilize different antigen recognition elements, such as nanobodies. What this study addsHere we show that affinity maturation of nanobody-based CAR T-cells (nanoCARs) targeting CD72 can improve their in vitro efficacy versus CD72-low tumors; however, in vivo efficacy differences are more modest. Furthermore, we show that for refractory B-cell malignancies, surface CD72 appears preserved after CD19 resistance even in situations where CD22 is strongly downregulated. How this study might affect research, practice or policyCD72 warrants further investigation as a preferred immunotherapy target in the context of CD19-refractory B-cell cancers, though nanobody affinity maturation is not a universal solution to the challenge of low tumor surface antigen density.

immunology↗

bioRxiv2025

A cell-free bacterial signal orchestrates trans-kingdom fitness tradeoff to enhance sulfur deficiency tolerance in plants

Plant-associated microorganisms interact with each other and host plants via intricate chemical signals, offering multiple benefits, including plant nutrition. We report such a mechanism through which the rhizosphere microbiome improves plant growth under sulfur (S) deficiency. Disruption of plant S homeostasis resulted in a coordinated shift in composition and S-metabolism of the rhizosphere microbiome. Using this insight, we developed an 18-membered synthetic rhizosphere bacterial community (SynCom) that rescued growth of Arabidopsis and a leafy Brassicaceae vegetable under S-deficiency. This beneficial trait is taxonomically widespread among SynCom members, with bacterial pairs predominantly providing synergistic benefits to host plants. Notably, stronger competitive interactions among SynCom members conferred greater fitness benefits to the host, suggesting a trans-kingdom fitness tradeoff. Finally, guided chemical screening, deletion knockout mutant, and targeted metabolomics identified and validated microbially released glutathione (GSH) as the necessary bioactive signal that orchestrates plant-microbe (trans-kingdom) fitness tradeoff and improves plant growth under sulfur limitation. HighlightsO_LIAlteration in plant sulfur (S) homeostasis leads to coordinated shifts in the composition and S-metabolism of the rhizosphere microbiome. C_LIO_LITaxonomically divergent bacterial members within the rhizosphere microbiome improve plant growth under S-deficiency. C_LIO_LIStronger competitive interactions within rhizosphere bacterial members provide greater fitness benefit to the host plant under S-deficiency, suggesting a trans-kingdom fitness tradeoff. C_LIO_LIMicrobially released glutathione (GSH) is a necessary bioactive signal that improves plant growth under sulfur limitation and orchestrates plant-microbe (trans-kingdom) fitness tradeoff. C_LI

microbiology↗

bioRxiv2025

Identification of genetic and non-genetic modifiers of genomic imprinting through whole genome screening in humans

Genomic imprinting is required for normal development, and abnormal methylation of differentially methylated regions (iDMRs) controlling the parent of origin-dependent expression of the imprinted genes has been found in constitutional disorders affecting growth, metabolism, neurobehavior, and in cancer. In most of these cases the cause of the imprinting abnormalities is unknown. Also, these studies have generally been performed on a limited number of CpGs, and a systematic investigation of iDMR methylation in the general population is lacking. By analysing the iDMRs in a large number of peripheral blood DNA methylation array datasets of unaffected individuals and patients with rare disorders, we determined the most common iDMR methylation profiles and identified many genetic and non-genetic factors contributing to their variability. We found that methylation variability is not homogeneous within the iDMRs and that the CpGs closer to the ZFP57 binding sites are less susceptible to methylation changes. We demonstrated the methylation polymorphism of three iDMRs and the atypical behaviour of several others, and reported the association of 25 disease- and 47 non-disease-complex traits, including blood cell type composition, as well as 15 mendelian or chromosomal disorders, with iDMR methylation changes in blood DNA. These findings identify several genetic and non-genetic factors associated with genomic imprinting maintenance in humans, which may have a role in the aetiology of the diseases associated with imprinting abnormalities and have clear implications in molecular diagnostics.

genetics↗

bioRxiv2025

TGF-β inhibitor SB431542 suppresses coronavirus replication through multistep inhibition

The COVID-19 pandemic highlighted the critical need for broad-spectrum antivirals with high resistance barriers. Here, we demonstrate that SB431542, a selective TGF-{beta} receptor I (ALK5) inhibitor, exhibits potent antiviral activity against SARS-CoV-2 through unprecedented multitargeted mechanisms. Through comprehensive in vitro, and in silico analyses, we identified that SB431542 directly binds to SARS-CoV-2 ORF3a and disrupt its canonical function in inhibiting autophagosome-lysosome fusion. This interaction restored lysosomal acidification and normalized perinuclear LAMP-1 localization, significantly impairing virion assembly as evidenced by disrupted nucleocapsid-RNA association and reduced intracellular viral titers. Additionally, SB431542 downregulated the CLEAR network genes responsible for lysosomal biogenesis, further restricting viral egress pathways. Our temporal analyses revealed that at later infection stages (36-48 hpi), SARS-CoV-2 exploits TGF-{beta}-induced lysosomal membrane permeabilization (LMP) and apoptosis for viral release--processes effectively inhibited by SB431542 through suppression of GADD45b and BAX expression. These multiple mechanisms resulted in an exceptional EC50 of 515 nM against SARS-CoV-2. In vivo efficacy was demonstrated in embryonated chicken eggs, where SB431542 conferred dose-dependent protection against lethal infectious bronchitis virus (IBV) challenge, with a favourable therapeutic index of 34.54. Remarkably, sequential passaging of SARS-CoV-2 for 50 generations under SB431542 selection pressure failed to generate resistant variants, contrasting sharply with the rapid resistance emergence typical of direct-acting antivirals. These findings establish SB431542 as a promising broad-spectrum coronavirus inhibitor with a unique triple-mechanism approach that simultaneously targets viral entry via TGF-{beta}/Smad modulation, disrupts ORF3a-mediated lysosomal dysfunction affecting assembly, and attenuates TGF-{beta}-induced apoptosis during late-stage infection-- collectively imposing multiple selective constraints that impede escape mutation development. ImportanceThe COVID-19 pandemic highlighted the urgent need for antiviral drugs with high barriers to resistance. This study reveals that SB431542, a drug previously developed to inhibit TGF-{beta} signaling, exhibits remarkable effectiveness against SARS-CoV-2 through an unprecedented triple-mechanism approach. Unlike conventional antivirals that target a single viral component, SB431542 simultaneously disrupts viral entry, assembly, and release by binding to the viral ORF3a protein and modulating host cellular processes. Most importantly, SARS-CoV-2 failed to develop resistance against SB431542 even after 50 generations of exposure--a significant advantage over current therapeutics that quickly lose effectiveness due to viral mutations. Our findings also uncover that coronaviruses exploit both lysosomal dysfunction and programmed cell death to spread efficiently, providing new targets for therapeutic intervention. This research establishes SB431542 as a promising broad-spectrum coronavirus inhibitor and demonstrates the value of targeting host-virus interactions to overcome antiviral resistance.

microbiology↗

bioRxiv2025

Morphological Variation and DUS Characterization in Bitter Gourd (Momordica charantia L.) collections from Eastern India for Varietal Identification and Genetic Improvement

This study investigates the morphological variation and Distinctness, Uniformity, and Stability (DUS) characterization of Momordica charantia collections from Eastern India to facilitate varietal identification and genetic improvement. Twenty-two Bitter Gourd varieties were characterized based on morphological traits to assess genetic diversity and enhance breeding program efficiency. Significant variations were observed in fruit morphology (colour, length, surface tubercles, and ridges) and seed characteristics (Colour and margin indentation) enabling effective varietal differentiation. Notably, four accessions were classified as M. charantia var. muricata due to their distinctly small fruit size, highlighting the presence of diverse morphological forms within the studied population. Additionally, admixture was detected in seven varieties, which underscores the necessity for purification processes to ensure the commercial viability of these accessions. This research emphasizes the rich genetic diversity of Bitter Gourd in Eastern India and identifies key traits that are essential for distinguishing between varieties. The findings provide valuable insights for breeders to develop improved cultivars with enhanced productivity and consumer-preferred traits. Moreover, this study supports ongoing plant breeding efforts to enhance crop quality and yield by identifying reliable morphological traits for varietal differentiation. Furthermore, it recommends additional research to refine DUS criteria by incorporating more traits that effectively differentiate between smooth-type Bitter Gourd varieties.

genetics↗

bioRxiv2025

Avoidance of pyroptosis accounts for the relatively high metastatic potential observed in early hybrid EMT states

EMT converts epithelial (E) phenotypes to invasive mesenchymal (M) states. However, analyses of circulating tumor cells (CTCs) indicated that biphenotypic (E+M) CTCs better correlate with metastasis. Similarly, investigations of murine tumors undergoing EMT concluded that early E+M states posses the highest metastatic potential. To explore this, we selected in animals with breast cancer CTCs having progressively increasing intravasation abilities. This revealed that downregulation of arrestin Arrdc4 associates with CTC aggressiveness. In xenografts, depleting Arrdc4 accelerated tumor progression, whereas overexpression hindered progression in immunocompetent, but not in immunocompromised mice. Mechanistically, high Arrdc44 suppresses glucose uptake and enhances gasdermin E, triggering pyroptosis a type of pro-inflammatory cell death. Consistently, Arrdc4s lowest levels characterize the most metastatic biphenotypic states. In patients, both epigenetic and chromosomal aberrations downregulate ARRDC4 and predict poor prognosis. In summary, the uncovered mechanism portrays pyroptosis of biphenotypic EMT cells as a rheostat of CTCs, which may resolve the controversy on the role played by EMT in metastasis.

cancer biology↗

bioRxiv2025

AlphaCross-XL: a seamless tool for automated and proteome-scale map-ping of crosslinked peptides onto three-dimensional protein structures

Crosslinking mass spectrometry (XL-MS) is an exciting proteomics technology to capture native protein conformations in real time within biological systems. Historically, however, implementation of this technology has typically been limited to single purified recombinant proteins or in vitro assembled protein complexes. These limitations are associated with inherent challenges in XL-MS analysis, including extremely low abundance of crosslinked (XL) peptides and complex deconvolution of XL peptide-derived spectral data. However, impressive recent developments in computation and instrumentation have now made it feasible to address biological questions using proteome-wide XL-MS analysis. Although some XL mapping software tools exist, these require manual input of specific Protein Data Bank (PDB) structures at the single protein level, and do not function at the high throughput scale required to analyze datasets derived from thousands of proteins. To address this need, we therefore sought to develop a strategy enabling automated mapping of XL peptides onto the three-dimensional (3D) structures of proteins, at a proteome-wide scale. Herein we describe AlphaCross-XL, a first-in-class seamless computational tool for automated mapping of XL peptides onto the protein structures for intra-protein crosslinks and loop-links. The AlphaCross-XL software first retrieves protein structures from the AlphaFold Protein Structure Database and maps all the identified crosslinks onto the 3D structure. It also calculates the Euclidian distance between the crosslinked residues and reports the violated and satisfied crosslink distances based on a user-defined distance threshold, which is visually discriminated by color in PyMOL. Lastly, the tool also supports further validation of user-submitted protein structures, that can include any computer-predicted protein structure and experimentally derived protein structures (i.e., from PDB). AlphaCross-XL is available at https://github.com/sanjyotshenoy/alphacross-xl.

bioinformatics↗

bioRxiv2025

TMPRSS2-ERG confers resistance to antiandrogens: mechanism and therapeutic implications

Approximately 50% of prostate cancer (PCa) patients harbor fusions involving the TMPRSS2 and ERG genes. Despite this, tailored therapies targeting the fused gene, tERG, remain undeveloped. Our study analyzed biopsy samples from two clinical trials assessing the efficacies of androgen receptor (AR) signaling inhibitors (ARSIs). The results revealed that tERG promotes resistance to ARSIs and is associated with elevated levels of the glucocorticoid receptor (GR). Subsequent assays showed that GR directly interacts with tERG, alleviates allosteric autoinhibition and prevents chemotherapy-induced tERG degradation. In PCa models, either inhibiting GR or lowering cortisol levels suppressed tumor growth in tERG-positive models, but not in fusion-negative models. In addition, patient-derived fusion-positive xenografts displayed enhanced sensitivity to combined GR and AR inhibitors. Collectively, these findings highlight TMPRSS2-ERG as a new biomarker and propose that simultaneous inhibition of GR and AR may specifically benefit tERG-positine patients. However, GR stimulatory corticosteroid therapies may not be advisable for this patient subgroup.

cancer biology↗

bioRxiv2024

Cellular behavior analysis from live-cell imaging of TCR T cell-cancer cell interactions

T cell therapies, such as chimeric antigen receptor (CAR) T cells and T cell receptor (TCR) T cells, are a growing class of anti-cancer treatments. However, expansion to novel indications and beyond last-line treatment requires engineering cells dynamic population behaviors. Here we develop the tools for cellular behavior analysis of T cells from live-cell imaging, a common and inexpensive experimental setup used to evaluate engineered T cells. We first develop a state-of-the-art segmentation and tracking pipeline, Caliban, based on human-in-the-loop deep learning. We then build the Occident pipeline to collect a catalog of phenotypes that characterize cell populations, morphology, movement, and interactions in co-cultures of modified T cells and antigen-presenting tumor cells. We use Caliban and Occident to interrogate how interactions between T cells and cancer cells differ when beneficial knock-outs of RASA2 and CUL5 are introduced into TCR T cells. We apply spatiotemporal models to quantify T cell recruitment and proliferation after interactions with cancer cells. We discover that, compared to a safe harbor knockout control, RASA2 knockout T cells have longer interaction times with cancer cells leading to greater T cell activation and killing efficacy, while CUL5 knockout T cells have increased proliferation rates leading to greater numbers of T cells for hunting. Together, segmentation and tracking from Caliban and phenotype quantification from Occident enable cellular behavior analysis to better engineer T cell therapies for improved cancer treatment.

cell biology↗

bioRxiv2024

Temperature and dissolved organic matter shape marine prokaryotic activity and gene expression in a sub-arctic sea

Temperature and dissolved organic matter (DOM) are important drivers of microbial activity, but their effects, alone or in combination, on the physiological responses of sub-arctic prokaryotic assemblages remain poorly understood. In a northern Baltic Sea one-month mesocosm experiment, we therefore exposed a coastal microbial community to temperature and nutrient regimes representative of winter and early summer (i.e., 1{degrees}C and 10{degrees}C, with and without DOM additions) in a 2x2 factorial design. Midway through the experiment, specific growth rates were highest for the 10{degrees}C plus DOM treatment (TN; [~]2.5 day-1), comparable for the 1{degrees}C plus DOM (N) and the 10{degrees}C (T) treatments at [~]1.0 day-1; and low for the control (1{degrees}C, no DOM enrichment [C]; 0.2 day-1). Taxonomic analysis of metatranscriptomes uncovered broad treatment specific responses, and a PERMANOVA on the 182,618 transcribed genes revealed statistically significant effects of both temperature and DOM, and significant interaction effects between the two (altogether involving 18% of genes). Significant differences in transcription identified by EdgeR analysis included Nitrosopumilus genes for ammonium uptake and ammonia oxidation in the 1{degrees}C mesocosms (C, N), membrane transporters for small organic acids in the N-treatment, genes for nitrogen and phosphorus assimilation along with molecular chaperones in the T-treatment, and dominance of Oceanospirillales genes for energy and growth metabolism in the TN-treatment. These metatranscriptomic responses were associated with changes in e.g. prokaryotic growth rates and growth efficiency, providing clues to how successional changes in community composition and metabolism are directed by temperature and DOM as central factors underlying environmental change. ImportanceIt is recognized that increases in temperature and dissolved organic matter loading are key to understanding how climate change will influence polar ecosystems. Still, little is known of the effects of these factors on the physiological responses of Arctic prokaryotes. Since prokaryotes are principal drivers of biogeochemical cycles, we investigated how temperature and dissolved organic matter influence prokaryotic transcriptional responses in taxonomy and metabolic pathways. The metatranscriptomics analyses uncovered broad treatment specific responses linked with changes in prokaryotic community composition, growth rates, and growth efficiency. Yet, and importantly, the expression of most metabolic functions remained stable, suggesting a pronounced functional resilience of the prokaryotic community enabled by shifts in the dominance of different taxa. This emphasizes the large potential and importance of identifying the metabolic functions that underlie the divergence of prokaryotic communities in response to environmental changes projected to alter some of the most vulnerable marine environments.

ecology↗

bioRxiv2024

To nest or not to nest: environmental cues for olive ridley mass nesting events in Odisha, India

Sea turtles of the genus Lepidochelys take part in synchronised nesting events, known as arribadas, where a large number of females emerge simultaneously from the sea to nest on the beach. Despite some evidence for the role of environmental factors, there is considerable uncertainty about both the factors that influence mass-nesting at an annual scale as well as the onset of individual events. We used a multi-decadal dataset from two olive ridley mass nesting beaches in Odisha, India, to identify the environmental factors associated with inter-annual nesting variation, nesting seasonality and the onset of arribadas. Interestingly, the two sites showed different patterns in inter-annual patterns associated with the non-occurrence of arribadas, despite being only 250 km apart. The nesting season was consistently during the dry and cooler part of the year. Arribada start dates were non-uniformly distributed across the lunar phase in Gahirmatha with most arribadas occurring during the first and third quarters. Fast Southern Winds characterised the period before and during the arribada at both sites. Machine learning models (XGBoost) identified the most important parameters for the onset of mass nesting and accurately predicted more than 75% of the start dates. Lunar phase, mean sea level pressure and wind speed and direction were important parameters at both sites. Differences in parameter importance between sites suggest that mass nesting is influenced by the interaction of several environmental parameters, along with site-specific characteristics. Insights into the triggers of mass nesting can thus provide guidance for site-specific management efforts.

ecology↗

bioRxiv2024

Data-driven insights into the association between oxidative stress and calcium-regulating proteins in cardiovascular disease.

A growing body of biomedical literature suggests a bidirectional regulatory relationship between cardiac calcium (Ca2+)-regulating proteins and reactive oxygen species (ROS), which is integral to the pathogenesis of various cardiac disorders via oxidative stress signaling. To address the challenge of finding hidden connections within the growing volume of biomedical research, we developed a data science pipeline for efficient data extraction, transformation, and loading. Employing the CaseOLAP (Context-Aware Semantic Analytic Processing) algorithm, our pipeline quantifies interactions between 128 human cardiomyocyte Ca2+-regulating proteins and eight cardiovascular disease (CVD) categories. Our machine learning analysis of CaseOLAP scores reveals that the molecular interfaces of Ca2+-regulating proteins uniquely associate with cardiac arrhythmias and diseases of the cardiac conduction system, distinguishing them from other CVDs. Additionally, a knowledge graph analysis identified 59 of the 128 Ca2+-regulating proteins as involved in OS-related cardiac diseases, with cardiomyopathy emerging as the predominant category. By leveraging a link prediction algorithm, our research illuminates interactions between Ca2+-regulating proteins, OS, and CVDs. The insights gained from our study provide a deeper understanding of the molecular interplay between cardiac ROS and Ca2+-regulating proteins in the context of CVDs. Such understanding is essential for the innovation and development of targeted therapeutic strategies.

bioinformatics↗

bioRxiv2024

Understanding TCR T cell knockout behavior using interpretable machine learning

Genetic perturbation of T cell receptor (TCR) T cells is a promising method to un-lock better TCR T cell performance to create more powerful cancer immunotherapies, but understanding the changes to T cell behavior induced by genetic perturbations remains a challenge. Prior studies have evaluated the effect of different genetic modifications with cytokine production and metabolic activity assays. Live-cell imaging is an inexpensive and robust approach to capture TCR T cell responses to cancer. Most methods to quantify T cell responses in live-cell imaging data use simple approaches to count T cells and cancer cells across time, effectively quantifying how much space in the 2D well each cell type covers, leaving actionable information unexplored. In this study, we characterize changes in TCR T cells interactions with cancer cells from live-cell imaging data using explainable artificial intelligence (AI). We train convolutional neural networks to distinguish behaviors in TCR T cell with CRISPR knock outs of CUL5, RASA2, and a safe harbor control knockout. We use explainable AI to identify specific interaction types that define different knock-out conditions. We find that T cell and cancer cell coverage is a strong marker of TCR T cell modification when comparing similar experimental time points, but differences in cell aggregation characterize CUL5KO and RASA2KO behavior across all time points. Our pipeline for discovery in live-cell imaging data can be used for characterizing complex behaviors in arbitrary live-cell imaging datasets, and we describe best practices for this goal.

cell biology↗

bioRxiv2024

A STAT3 Degrader Demonstrates Pre-clinical Efficacy in Venetoclax resistant Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy that continues to have poor prognosis despite recent therapeutic advances. Venetoclax (Ven), a BCL2-inhibitor has shown a high response rate in AML; however, relapse is invariable due to mitochondrial dysregulation that includes upregulation of the antiapoptotic protein MCL1, a central mechanism of Ven resistance (Ven-res). We have previously demonstrated that the transcription factor STAT3 is upregulated in AML hematopoietic stem and progenitor cells (HSPCs) and can be effectively targeted to induce apoptosis of these aberrant cells. We now show that overexpression of STAT3 alone is sufficient to initiate a strong AML phenotype in a transgenic murine model. Phospho-proteomic data from Ven treated AML patients show a strong correlation of high total STAT3 and phospho-STAT3 [both p-STAT3(Y705) and p-STAT3(S727)] expression with worse survival and reduced remission duration. Additionally, significant upregulation of STAT3 was observed in Ven-res cell lines, in vivo models and primary patient samples. A novel and specific degrader of STAT3 demonstrated targeted reduction of total STAT3 and resulting inhibition of its active p-STAT3(Y705) and p-STAT3(S727) forms. Treatment with the STAT3 degrader induced apoptosis in parental and Ven-res AML cell lines and decreased mitochondrial depolarisation, and thereby dependency on MCL1 in Ven-res AML cell line, as observed by BH3 profiling assay. STAT3 degrader treatment also enhanced differentiation of myeloid and erythroid colonies in Ven-res peripheral blood mononuclear cells (PBMNCs). Upregulation of p-STAT3(S727) was also associated with pronounced mitochondrial structural and functional dysfunction in Ven-res cell lines, that were restored by STAT3 degradation. Treatment with a clinical-stage STAT3 degrader, KT-333 resulted in a significant reduction in STAT3 and MCL1 protein levels within two weeks of treatment in a cell derived xenograft model of Ven-res AML. Additionally, this treatment significant improvement in the survival of a Ven-res patient-derived xenograft in-vivo study. Degradation of STAT3 resulting in downregulation of MCL1 and improvements in global mitochondrial dysfunction suggests a novel mechanism of overcoming Ven-res in AML. Statement of PurposeFive-year survival from AML is dismal at 30%. Our prior research demonstrated STAT3 over-expression in AML HSPCs to be associated with inferior survival. We now explore STAT3 over-expression in Ven-res AML, explain STAT3 mediated mitochondrial perturbations and describe a novel therapeutic strategy, STAT3 degradation to overcome Ven-res.

cancer biology↗