Biology subjects

Subramanian, N.

Publications and source records attributed to Subramanian, N..

13 recordsLinked to original sources

bioRxiv2026

Modeling and dissecting bidirectional feedback in gene-metabolite systems using the CausalFlux method

Predicting cellular behaviors, a central task in systems biology and metabolic engineering, can be enhanced through integrative modeling of processes such as gene regulation and metabolism. Information flow from gene regulation (modeled via a gene regulatory network) to metabolism (modeled via a genome-scale metabolic model) is well-studied, but the reciprocal regulation of genes by metabolites is less explored. We introduce CausalFlux, a method that models bidirectional feedback between genes and metabolites, in order to predict steady-state reaction fluxes under wild-type (WT) or perturbed (e.g., gene knockout/KO) conditions. CausalFlux does so by iteratively performing causal surgery on a Bayesian gene regulatory network and constraint-based analysis of a coupled metabolic model. CausalFlux enabled us to assess the impact of two-way feedback in several testbed models and real-world biological systems by comparing its predictions to those of TRIMER, a state-of-the-art model of gene-to-metabolite one-way feedback. Incorporating bidirectional feedback, as in CausalFlux, improved the Spearman correlation between actual and predicted fluxes in 92% of the 39 distinct simulation conditions relative to TRIMER. For predicting growth/no-growth phenotype following single-gene KOs in E. coli, CausalFlux achieved a balanced accuracy of 0.79 in identifying essential genes, and TRIMER achieved 0.71 for the same task, again highlighting the importance of modeling two-way feedback. In ablation studies that further dissect the role of specific metabolite[->]gene feedback edges in E. coli, the F1 scores of gene essentiality predictions decreased by 7.5% and 13% upon ablation of feedback edges from any metabolite to the crp gene and the 10 metabolic feedback genes with the highest influence on the KO genes, respectively. Finally, we highlight the application of CausalFlux to predict the essentiality of several hundred genes under different media conditions. Overall, our findings show that CausalFlux can crucially utilize information on feedback metabolites to predict trends in reaction fluxes and qualitative (growth/no-growth) outcomes; thereby encouraging future systems modeling efforts to carefully incorporate not only gene-to-metabolite but also metabolite-to-gene interactions. AvailabilityCode pertaining to the CausalFlux method, and its benchmarking and application is publicly available at: https://github.com/BIRDSgroup/CausalFlux. Author summaryThe myriad processes within a living cell, such as gene regulation or metabolism, are tightly interconnected. Modeling these interconnected processes can offer a deeper mechanistic understanding of cellular behaviors, as well as guide efforts that engineer the metabolic output of a cell. In this work, we develop a novel integrated model of gene regulation and metabolism that incorporates bidirectional feedback between these two processes, via the concept of metabolite-induced causal surgery on a gene regulatory network and gene-induced constraints on the fluxes of metabolic reactions. Our model, which we call CausalFlux, represents an advance over most existing models that capture just the one-way gene-to-metabolism feedback (i.e., genes coding for enzymes that control metabolic reactions). Our CausalFlux methodology opens up an unique opportunity to quantify the impact of two-way feedback in gene-metabolite systems, via comparison of CausalFluxs predictions to those of TRIMER, a published model incorporating one-way feedback alone. For predicting reaction fluxes in testbed models and essential genes in E. coli, quantitative comparison of the performance of CausalFlux vs. TRIMER showed that accounting for two-way feedback leads to more accurate and biologically meaningful predictions. CausalFlux also enabled us to quantify the effect of two-way feedback by comparing prediction performance before and after ablation of certain feedback edges from metabolites to genes. Overall, our findings highlight the importance of modeling gene regulation and metabolism as two-way interconnected systems within a living cell, and encourage future works to incorporate gene{leftrightarrow}metabolite feedback into their analyses.

systems biology↗

bioRxiv2026

Immediate transcriptional changes initiated by direct cell-cell contact between cytotoxic T cells and cancer cells

Many biological processes are regulated by the direct interaction between two or more cell types. However, our understanding of the immediate dynamic changes in gene transcription upon physical interaction between two cells has remained limited due to technical limitations. Here we address these limitations in a model system of cancer-specific T cell receptor (TCR)-modified CD8 T cells where single and cancer-interacting T cells were isolated by image-enabled cell sorting and transcripts from heterotypic cancer cell and T cell pairs were in silico assigned. This approach uncovers immediate, dynamic changes in gene expression following the specific interaction between TCR-modified CD8 T cells and cancer cells. In addition to dissecting transcriptional cascades dependent on the peptide sensitivity of the TCR, we for the first time directly compare these gene expression changes between single T cells and T cells in direct physical contact with cancer cells. Modeling of the observed transcriptomic activation signature identifies phenotypically distinct tumor infiltrating CD8 T cell subsets associated with reduced TCR diversity in in vivo datasets. Taken together, the paradigm developed here allows for future clonal identification of T cell receptors mediating ongoing effective cytotoxic responses in vivo.

immunology↗

bioRxiv2025

Multiomics Reveals Compartmentalized Immune Responses and Tissue-Vascular Signatures in Lyme Disease

Lyme disease (LD) is growing in incidence, with nearly 500,000 cases diagnosed annually in the United States. Despite treatment, some patients experience persistent symptoms. The immune mechanisms underlying LD remain poorly understood. We conducted a multiomic longitudinal analysis of 49 LD patients and matched controls, integrating plasma proteomics, metabolomics, PBMC immunophenotyping, and a meta-analysis of skin lesions. We identified compartmentalized immune responses in acute LD, with coordinated alterations in circulating plasma proteins and metabolites linked to endothelial barrier stability, metabolic reprogramming, and symptom severity, predominantly traced to tissue and vascular immune processes at the site of infection. In contrast, PBMCs remained largely quiescent, revealing a disconnect between localized tissue responses and systemic immunity. These findings provide novel insights into LD pathophysiology and highlight the potential for diagnostics leveraging tissue and vascular immune markers detectable in blood. They also provide a resource for biomarker discovery and predictive modeling to improve LD management.

immunology↗

bioRxiv2025

Meta plasticity and Continual Learning: Mechanisms sub serving Brain Computer Interface Proficiency

ObjectiveBrain Computer Interfaces (BCIs) require substantial cognitive flexibility to optimize control performance across diverse settings. Remarkably, learning this control is rapid, suggesting it might be mediated by neuroplasticity mechanisms operating on very short time scales. However, these mechanisms remain far from understood. Here, we propose a meta plasticity model of BCI learning and skill consolidation at the single cell and population levels comprised of three elements: a) behavioral time scale synaptic plasticity (BTSP), b) intrinsic plasticity (IP) and c) synaptic scaling (SS) operating at time scales from seconds to minutes to hours and days. Notably, the model is able to explain representational drift - a frequent and widespread phenomenon observed in multiple brain areas that adversely affects BCI control and continued use. ApproachWe developed a closed loop, all optical approach to characterize IP, BTSP and SS with single cell resolution in cortical L2/3 of awake mice using fluorescent two photon (2P) GCaMP7s imaging and optogenetic stimulation of the soma targeted ChRmineKv2.1. We further trained mice on a one-dimensional (1D) BCI control task and systematically characterized within session (seconds to minutes) learning as well as across sessions (days and weeks) with different neural ensembles. Main resultsWe found that on the time scale of seconds, substantial BTSP could be induced and was associated with significant IP over minutes. Over the time scale of days and weeks, these changes could predict BCI control proficiency, suggesting that BTSP and IP might be complemented by SS to stabilize and consolidate BCI control. SignificanceOur results provide theoretical and early experimental support for an integrated meta plasticity model of continual BCI learning and skill consolidation. The model predictions may be used to design and calibrate neural decoders with complete autonomy while considering the temporal and spatial scales of plasticity mechanisms and their anticipated order of occurrence. With the power of modern-day machine learning (ML) and artificial Intelligence (AI), fully autonomous neural decoding and adaptation in BCIs might be achieved with minimal to no human intervention.

neuroscience↗

bioRxiv2025

Heterogeneous monotonic and non-monotonic responses to odor in mitral/tufted glomeruli of the mouse olfactory bulb

Animals can recognize and discriminate between different odors and the same odor over a range of concentrations. Processing within the mouse olfactory bulb (OB) may be involved, yet the underlying mechanisms remain unclear. Each olfactory receptor neuron (ORN) type maps to the OB in olfactory receptor specific channels called glomeruli where they connect with the dendrites of mitral/tufted cells (MTCs), which project their axons to the rest of the brain. Differences between input and output define the functions carried out by a brain region. Using in vivo dual-color 2-photon Ca2+ imaging from the ORNs and MTCs innervating the same glomeruli in the mouse OB, we identified a novel MTC response type with a non-monotonic concentration-response relationship. We used mathematical modeling to demonstrate that non-monotonic response types are consistent with a form of interglomerular processing, which we propose is a mechanism to facilitate odor discrimination and the ability to achieve concentration-invariant odor perception. Graphical AbstractThe olfactory bulb input-output transformation was imaged using dual-color 2-photon imaging. (Top) Cartoon and histological examples of labeling the olfactory bulb input and output using spectrally distinct optical sensors. (Middle) Modeling and experimental work reveal that input neurons that respond with primarily monotonic concentration-response relationships are transformed into a mix of monotonic and non-monotonic responses. (Bottom) Olfactory bulb output state space for a population of 3 glomeruli with exclusively monotonic responses (black), and with both monotonic and non-monotonic responses (red). Each trajectory represents a cloud of points that reflects variations in the fluctuations of molecular components present in natural odor stimuli. Monotonic responses alone cluster together, while multiple response types broaden coverage of MTC state space. Greater coverage of state space makes it easier to discriminate one odor from another, even though the dimension of olfactory bulb state space is larger than 3. Key PointsO_LIAlthough the olfactory bulb is the first stage of olfactory sensory processing, its role in transforming sensory information remains poorly understood. C_LIO_LIDifferent olfactory receptor neuron types map to the olfactory bulb in olfactory receptor specific channels called glomeruli, where they interact with the dendrites of mitral/tufted cells, which project to the rest of the brain. C_LIO_LIWe used dual-color 2-photon Ca2+ imaging to image the input-output transformation olfactory receptor neuron (ORN) and mitral/tufted (MTC) glomeruli across a wide concentration range. C_LIO_LIThe ORN input to all tested glomeruli responded to increasing concentration changes with monotonic increases, while the corresponding MTCs outputs of each glomerulus responded with monotonic and non-monotonic changes. C_LIO_LIThe results were consistent with a mathematical model of the olfactory bulb incorporating feed-forward and lateral inhibition. C_LI

neuroscience↗

bioRxiv2024

Recent odor experience selectively modulates olfactory sensitivity across the glomerular output in the mouse olfactory bulb

Although animals can reliably locate and recognize odorants embedded in complex environments, the neural circuits for accomplishing these tasks remain incompletely understood. Adaptation is likely to be important as it could allow neurons in a brain area to adjust to the broader sensory environment. Adaptive processes must be flexible enough to allow the brain to make dynamic adjustments, while maintaining sufficient stability so that organisms do not forget important olfactory associations. Processing within the mouse olfactory bulb is likely involved in generating adaptation, although there are conflicting models of how it transforms the glomerular output of the mouse olfactory bulb. Here we performed 2-photon Ca2+ imaging from mitral/tufted glomeruli in awake mice to determine the time course of recovery from adaptation, and whether it acts broadly or selectively across the glomerular population. Individual glomerular responses, as well as the overall population odor representation was similar across imaging sessions. However, odor-concentration pairings presented with interstimulus intervals upwards of 30-s evoked heterogeneous adaptation that was concentration-dependent. We demonstrate that this form of adaptation is unrelated to variations in respiration, and olfactory receptor neuron glomerular measurements indicate that it is unlikely to be inherited from the periphery. Our results indicate that the olfactory bulb output can reliably transmit stable odor representations, but recent odor experiences can selectively shape neural responsiveness for upwards of 30 seconds. We propose that neural circuits that allow for non-uniform adaptation across mitral/tufted glomerular could be important for making dynamic adjustments in complex odor environments.

neuroscience↗

bioRxiv2022

Dual blockade of misfolded alpha-sarcoglycan degradation by bortezomib and givinostat combination

Limb-girdle muscular dystrophy type R3 (LGMD R3) is a rare genetic disorder characterized by a progressive proximal muscle weakness and caused by mutations in the SGCA gene encoding alpha-sarcoglycan (-SG). Here, we report the results of a mechanistic screening ascertaining the molecular mechanisms involved in the degradation of the most prevalent misfolded R77C--SG protein. We performed a combinatorial study to identify drugs potentializing the effect of a low dose of the proteasome inhibitor bortezomib on the R77C--SG degradation inhibition. Analysis of the screening associated to artificial intelligence-based predictive ADMET characterization of the hits led to identification of the HDAC inhibitor givinostat as potential therapeutical candidate. Functional characterization revealed that givinostat effect was related to autophagic pathway inhibition, unveiling new theories concerning degradation pathways of misfolded SG proteins. Beyond the identification of a new therapeutic option for LGMD R3 patients, our results shed light on the potential repurposing of givinostat for the treatment of other genetic diseases sharing similar protein degradation defects such as LGMD R5 and cystic fibrosis.

pharmacology and toxicology↗

bioRxiv2020

In Vivo two-photon imaging and parasympathetic neuromodulation of pancreatic microvascular dynamics in rats

The pancreas has long been known to be densely innervated with parasympathetic, sympathetic, and visceral afferent fibers that are believed to exert significant influence on local endocrine activity and vascular function. Yet the extent to which these interactions depend on neurovascular dynamics in the normal and pathological states remain largely unknown. Herein we describe a new method for high resolution functional imaging of the rat pancreas in vivo. The method comprises a number of elements: a stability-optimized preparation in dorsal recumbency immobilizing several square centimeters of intact pancreas for upright fluorescent imaging while leaving access for concurrent manipulation of abdominal nerves, a full-frame two-photon imaging protocol and analysis pipeline supporting high-throughput (100+) monitoring of islet and acinar microvessel diameter dynamics simultaneously, and a first adaptation of random-access linescan imaging to the pancreas capable of tracking internal blood flow speeds up to 5 mm/s at 20 Hz across multiple microvessels. These methods were then deployed in concert to characterize the capacity of parasympathetic fibers to modulate pancreatic microvascular dynamics with compartment specificity. Electrical stimulation was repeatedly applied to the abdominal vagal trunks at various current magnitudes while imaging islet and acinar microvascular populations in the pancreas. Vagal stimulation consistently elicited increases in both islet and acinar capillary population motility in a current-dependent manner, with only acinar responsive vessels trending toward dilation. Further, we found vagal stimulation to profoundly and reversibly disrupt all traces of fast-wave vasomotor oscillation across a lobular arteriole-venule pair, and this was associated with a significant increase in average flow speed. Together, these findings add to mounting evidence that vagal projections exert tangible reversible influence on pancreatic microvascular activity and underscore the potential for new neuromodulation-based strategies to address diabetes, pancreatitis, or other diseases of the pancreas under autonomic nervous influence.

neuroscience↗

bioRxiv2020

Validation of Functional Polymorphisms Affecting Maize Plant Height by Unoccupied Aerial Systems (UAS) allows Novel Temporal Phenotypes

Plant height (PHT) in maize (Zea mays L.) has been scrutinized genetically and phenotypically due to relationship with other agronomically valuable traits (e.g. yield). Heritable variation of PHT is determined by many discovered quantitative trait loci (QTLs); however, phenotypic effects of such loci often lack validation across environments and genetic backgrounds, especially in the hybrid state grown by farmers rather than the inbred state preferred by geneticists. A previous genome wide association study using a hybrid diversity panel identified two novel quantitative trait variants (QTVs) controlling both PHT and grain yield. Here, heterogeneous inbred families demonstrated that these two loci, characterized by two single nucleotide polymorphisms (SNPs), cause phenotypic variation in inbred lines, but that size of these effects were variable across four different genetic backgrounds, ranging from 1 to 10 cm. Weekly unoccupied aerial system flights demonstrated both SNPs had larger effects, varying from 10 to 25 cm, in early growth while SNPs effects decreased towards the end of the season. These results show that allelic effect sizes of economically valuable loci are both dynamic in temporal growth and dynamic across genetic backgrounds resulting in informative phenotypic variability overlooked following traditional phenotyping methods. Public genotyping data shows recent favorably selection in elite temperate germplasm with little change across tropical backgrounds. As these loci remain rare in tropical germplasm, with effects most visible early in growth, they are useful for breeding and selection to expand the genetic basis of maize.

plant biology↗

bioRxiv2020

Multiomic Immunophenotyping of COVID-19 Patients Reveals Early Infection Trajectories

Host immune responses play central roles in controlling SARS-CoV2 infection, yet remain incompletely characterized and understood. Here, we present a comprehensive immune response map spanning 454 proteins and 847 metabolites in plasma integrated with single-cell multi-omic assays of PBMCs in which whole transcriptome, 192 surface proteins, and T and B cell receptor sequence were co-analyzed within the context of clinical measures from 50 COVID19 patient samples. Our study reveals novel cellular subpopulations, such as proliferative exhausted CD8+ and CD4+ T cells, and cytotoxic CD4+ T cells, that may be features of severe COVID-19 infection. We condensed over 1 million immune features into a single immune response axis that independently aligns with many clinical features and is also strongly associated with disease severity. Our study represents an important resource towards understanding the heterogeneous immune responses of COVID-19 patients and may provide key information for informing therapeutic development.

immunology↗

bioRxiv2019

Antibody-Recruiting Protein-Catalyzed Capture Agents to Combat Antibiotic-Resistant Bacteria

Antibiotic resistant infections are projected to cause over 10 million deaths by 2050, yet the development of new antibiotics has slowed. This points to an urgent need for methodologies for the rapid development of antibiotics against emerging drug resistant pathogens. We report on a generalizable combined computational and synthetic approach, called antibody-recruiting protein-catalyzed capture agents (AR-PCCs), to address this challenge. We applied the combinatorial PCC technology to identify macrocyclic peptide ligands against highly conserved surface protein epitopes of carbapenem-resistant Klebsiella pneumoniae, an opportunistic gram-negative pathogen with drug resistant strains. Multi-omic data combined with bioinformatic analyses identified epitopes of the highly expressed MrkA surface protein of K. pneumoniae for targeting in PCC screens. The top-performing ligand exhibited high-affinity (EC50[~]50 nM) to full-length MrkA, and selectively bound to MrkA-expressing K. pneumoniae, but not to other pathogenic bacterial species. AR-PCCs conjugated with immunogens promoted antibody recruitment to K. pneumoniae, leading to phagocytosis and phagocytic killing by macrophages. The rapid development of this highly targeted antibiotic implies that the integrated computational and synthetic toolkit described here can be used for the accelerated production of antibiotics against drug resistant bacteria.

bioengineering↗

bioRxiv2019

Arfgef1 haploinsufficiency in mice alters neuronal endosome composition and decreases membrane surface postsynaptic GABAA receptors

ARFGEF1 encodes a guanine exchange factor involved in intracellular vesicle trafficking, and is a candidate gene for childhood genetic epilepsies. To model ARFGEF1 haploinsufficiency observed in a recent Lennox Gastaut Syndrome patient, we studied a frameshift mutation (Arfgef1fs) in mice. Arfgef1fs/+ pups exhibit signs of developmental delay, and Arfgef1fs/+ adults have a significantly decreased threshold to induced seizures but do not experience spontaneous seizures. Histologically, the Arfgef1fs/+ brain exhibits a disruption in the apical lining of the dentate gyrus and altered spine morphology of deep layer neurons. In primary hippocampal neuron culture, dendritic surface and synaptic but not total GABAA receptors (GABAAR) are reduced in Arfgef1fs/+ neurons with an accompanying decrease in GABAAR-containing recycling endosomes in cell body. Arfgef1fs/+ neurons also display differences in the relative ratio of Arf6+:Rab11+:TrfR+ recycling endosomes. Although the GABAAR-containing early endosomes in Arfgef1fs/+ neurons are comparable to wildtype, Arfgef1fs/+ neurons show an increase in GABAAR-containing lysosomes in dendrite and cell body. Together, the altered endosome composition and decreased neuronal surface GABAAR results suggests a mechanism whereby impaired neuronal inhibition leads to seizure susceptibility.\n\nHighlightsO_LIArfgef1fs/+ mice have lower seizure threshold but no spontaneous seizure.\nC_LIO_LIArfgef1fs/+ neurons show reduced dendritic surface GABAAR.\nC_LIO_LIArfgef1fs/+ neurons have decreased GABAAR-containing recycling endosome accompanied with an increase in GABAAR-containing lysosomes.\nC_LI

genetics↗

bioRxiv2019

A sustained small increase in NOD1 expression promotes ligand-independent oncogenic activity

Small genetically-determined differences in transcription (eQTLs) are implicated in complex disease but the mechanisms by which small changes in gene expression impact complex disease are unknown. Here we show that a persistent small increase in expression of the innate sensor NOD1 precipitates large cancer-promoting changes in cell state. A ~1.2-1.4 fold increase in NOD1 protein concentration by loss of miR-15b/16 regulation sensitizes cells to ligand-induced inflammation, with an additional slight increase leading to ligand-independent NOD1 activation that is linked to poor prognosis in gastric cancer. Our data show that tight expression regulation of NOD1 prevents this sensor from exceeding a physiological switching checkpoint that promotes persistent inflammation and oncogene expression and reveal the impact of a single small quantitative change in cell state on cancer.\n\nOne Sentence SummaryA small change in NOD1 expression has a large cancer-promoting impact on cell state.

systems biology↗