Biology subjects

Baliga, N. S.

Publications and source records attributed to Baliga, N. S..

At least 19 recordsLinked to original sources

bioRxiv2026

An adenylyl cyclase switch reroutes carbon from growth to virulence lipids in Mycobacterium tuberculosis

Anti-TB drugs act non-uniformly on Mycobacterium tuberculosis (Mtb) because of its distinct physiological states across diverse infection niches shaped by host-derived nutrients and stresses. Agonists of the adenylyl cyclase Rv1625c are a novel drug class that selectively inhibits Mtb growth in macrophages and cholesterol-rich conditions by an unknown mechanism. Combining condition-resolved transcriptomics, genome-scale metabolic modeling, and genetic perturbation, we show these agonists cause a blockade in the electron transport chain, which likely activates Rv1625c. The elevated cAMP in turn drives global transcriptional and post-translational remodeling of central carbon and lipid metabolism. The resulting methylcitrate cycle reversal chokes cholesterol breakdown products from entering central metabolism, diverting carbon toward cell wall and virulence-lipid (phthiocerol dimycocerosate) synthesis and inhibiting growth. These drugs thus hijack an endogenous switch that reroutes carbon from biomass to virulence-lipid production. Hence, nutrients that restore carbon flux and relieve ETC blockade reduce activity, whereas Rv1625c overexpression and ETC inhibitors potentiate drug action even in refractory conditions.

systems biology↗

bioRxiv2026

Monocyte-amplified transcriptional signatures of human diseases

Blood-based biomarkers discovered by machine learning often lack disease specificity and cross-population robustness for clinical applications. We describe a biomarker discovery strategy that exploits monocytes as circulating sentinels to amplify disease-perturbed signals in blood. This strategy leverages monocyteMINER, a mechanistic transcriptional regulatory network inferred from monocyte transcriptomes of 1,202 healthy individuals. As proof-of-concept, we uncovered a 31-gene atherosclerosis-perturbed network that underpins disease etiology, identifying diagnostic signatures for coronary artery disease (ARAP2, P2RY14, FKBP15) and acute myocardial infarction (SERPINA1, ASGR2). For tuberculosis (TB), monocyteMINER uncovered a 5-gene signature (MAS_TB_META5: ANKRD22, AIM2, VAMP5, GBP5, TGM2) from just 438 samples. MAS_TB_META5 outperformed 77 existing signatures across 18 cohorts (>4,400 patients, 12 countries), achieving WHO target product profile for high-sensitivity screening (including in advanced HIV patients), and predicting TB progression up to 5 years before diagnosis. Thus, our findings show that monocyteMINER offers a generalizable platform for discovering clinically actionable biomarkers for diverse diseases.

systems biology↗

bioRxiv2026

Enrichments along gradients resolve eco-evolutionary forces on subsurface microbiomes

How a single gram of soil harbors billions of microorganisms, each with distinct genomic variants that collectively maintain coherent ecological function(s), is one of microbiologys grand unsolved problems. A key obstacle is determining which variants contribute to individual- and community-level fitness, in which contexts, and how co-occurring ecotypes interact to divide niche space. Here, using nitrate (NO3-)-contaminated subsurface sediment as inoculum, we have performed high throughput enrichments in laboratory media of defined carbon source compositions across ecologically relevant gradients of pH and NO3-. Long-read metagenomics and link-community decomposition of co-occurrence networks of taxa across these enrichments has revealed context-specific functional interactions among dominant generalist and lower-abundance specialist denitrifier ecotypes that comprise 53 distinct enriched communities (EnComs) across 288 enrichments derived from a single sediment sample. We identified a single enzymatic difference of alternative NO3- reductases (NapAB vs. NarGHI) with differing substrate affinities that provided a mechanistic explanation for competitive niche partitioning between the two dominant taxa, Neorhizobium spp. and Allorhizobium spp., along the NO3- gradient. Genome-wide polymorphism ratios (pN/pS) revealed that selective pressures vary systematically with carbon source availability and gradients of pH and NO3-, which helps explain the natural biodiversity and functional interactions of ecotypes within denitrifying communities in the subsurface sediment. Our findings show that controlled enrichments along ecological gradients can thus uncover eco-evolutionary forces of selection, drift, and diversification that sculpt the biodiversity of microbial populations in the natural environment.

microbiology↗

bioRxiv2025

Host oxidative stress primes mycobacteria for rapid antibiotic resistance evolution

The rapid emergence of multidrug-resistant Mycobacterium tuberculosis (Mtb) threatens global TB control, yet the mechanisms enabling rapid evolution of drug resistance in Mtb remain poorly understood. Here we reveal that pre-existing mutations in oxidative stress response genes create permissive genomic backgrounds that accelerate high-level isoniazid resistance (INHR) without fitness costs, challenging the paradigm that resistance mutations always precede their fitness compensatory adaptations. Using M. smegmatis mc2155 (Msm) as a model, we show that brief exposure to sublethal INH (2x IC50) enriches for "low-level resistance and tolerance" (LLRT) mutants in a single step. These LLRT mutants, particularly those with ohrR loss-of-function mutations, acquire high-level resistance (> 500x IC50) at 6-fold higher rates than wildtype, primarily through otherwise-deleterious mycothiol biosynthesis mutations that become tolerable in the oxidative stress-buffered background. Crucially, we demonstrate that sublethal oxidative stress alone, mimicking host immune pressure, nearly tripled the rate of INH resistance evolution in Msm. Bayesian analysis of 1,578 clinical Mtb isolates from Vietnam confirmed that mutations in oxidative stress response genes were significantly associated with the emergence of INHR strains (p-value = 1.09x10-7). Independently, reanalysis of genome-wide CRISPRi screens revealed that the OSR network and high Bayes probability genes are functionally associated with treatment escape and survival with multiple antibiotics, including isoniazid, rifampicin, ethambutol, bedaquiline, vancomycin, clarithromycin, linezolid, and streptomycin. Our findings that host-imposed oxidative stress and inadequate drug penetration may synergistically prime Mtb populations for rapid resistance evolution suggest that targeting pre-resistance mechanisms, such as oxidative stress defenses, could help slow the emergence of antibiotic resistance in tuberculosis.

microbiology↗

bioRxiv2025

Heat-responsive dynamic shifts in alternative splicing of the coral Acropora cervicornis

Climate change has caused drastic declines in corals. As sessile organisms, response to shifting environmental conditions may include changes in gene expression, epigenetic modifications, or the microbiome, but as of yet, a common mechanism of stress response, alternative splicing (AS), has been underexplored in corals. Using short-term acute thermal stress assays, we investigated patterns of AS in the scleractinian coral Acropora cervicornis during response to and a subsequent overnight recovery phase from low (33), medium (35), and high (37) levels of heat stress. We find that 40% of the genomic gene set is subject to AS. Our findings demonstrate conserved and dynamic shifts in splicing profiles during the heat treatment and subsequent recovery phase. AS increased in response to heat stress and was primarily dominated by intron retention in specific classes of transcripts, including those related to splicing regulation itself. While AS returned to baseline levels post-exposure to low heat, AS persisted even after reprieve from higher levels of heat stress. Partial overlap of AS transcripts with differentially expressed genes suggests that AS may represent a distinct and previously underappreciated regulatory mechanism for thermal stress response in corals.

genomics↗

bioRxiv2024

Emergence and disruption of cooperativity in a denitrifying microbial community

Anthropogenic perturbations to the nitrogen cycle, primarily through use of synthetic fertilizers, is driving an unprecedented increase in the emission of nitrous oxide (N2O), a potent greenhouse gas and an ozone depleting substance, causing urgency in identifying the sources and sinks of N2O. Microbial denitrification is a primary contributor to biotic production of N2O in anoxic regions of soil, marine systems, and wastewater treatment facilities. Here, through comprehensive genome analysis, we show that pathway partitioning is a ubiquitous mechanism of complete denitrification within microbial communities. We have investigated mechanisms and consequences of process partitioning of denitrification through detailed physiological characterization and kinetic modeling of a synthetic community of Rhodanobacter R12 and Acidovorax 3H11. We have discovered that these two bacterial isolates, from a heavily nitrate (NO3-) contaminated superfund site, complete denitrification through the exchange of nitrite (NO2-) and nitric oxide (NO). The process partitioning of denitrification and other processes, including amino acid metabolism, contribute to increased cooperativity within this denitrifying community. We demonstrate that certain contexts, such as high NO3-, cause unbalanced growth of community members, due to differences in their substrate utilization kinetics. The altered growth characteristics of community members drives accumulation of toxic NO2-, which disrupts denitrification causing N2O off gassing.

microbiology↗

bioRxiv2024

Gene Regulatory Network topology governs resistance and treatment escape in glioma stem-like cells

Poor prognosis and drug resistance in glioblastoma (GBM) manifests from heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation to glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation is inherently resistant to temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and thereby drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how topology of transcription factor interactions drives distinct trajectories of cell state transitions of susceptible and resistant PD-GSCs in response to cytotoxic drug treatment. By experimentally testing TRN simulation-based predictions, we show that drug treatment drives surviving cells of a PD-GSC along a trajectory of intermediate states, akin to a bottleneck in gene expression space, exposing vulnerability to potentiated killing by sequential addition of siRNA or a second drug targeting transcriptional programs governing non-genetic plasticity of a PD-GSC. Thus, our findings demonstrate an approach to uncover and use TRN topology of a PD-GSC to rationally predict combinatorial and sequential treatments that block treatment escape and acquired resistance in GBM.

systems biology↗

bioRxiv2023

Origin of biogeographically distinct ecotypes during laboratory evolution

Resource partitioning within microbial communities is central to their incredible productivity, including over 1 gigaton of annual methane emissions through syntrophic interactions1. Here, we show how isogenic strains of a sulfate reducing bacterium (Desulfovibrio vulgaris, Dv) and a methanogen (Methanococcus maripaludis, Mm) underwent evolutionary diversification over 300-1,000 generations in a purely planktonic environmental2-4 context giving rise to coexisting ecotypes that could partition resources and improve overall stability, cooperativity, and productivity in a simulated subsurface environment. We discovered that mutations in just 15 Dv and 7 Mm genes gave rise to ecotypes within each species that were spatially enriched between sediment and planktonic phases over the course of only a few generations after transferring the evolved populations to a fluidized bed reactor (FBR). While lactate utilization by Dv in the attached community was significantly greater, the resulting H2 was partially consumed by low affinity hydrogenases in Mm within the same attached phase. The unutilized H2 was scavenged by high affinity hydrogenases in the planktonic phase Mm, generating copious amounts of methane and higher ratio of Mm to Dv. Our findings show how a handful of mutations that arise in one environmental context can drive resource partitioning by ecologically differentiated variants in another environmental context, whose interplay synergistically improves productivity of the entire mutualistic community.

microbiology↗

bioRxiv2023

Genetic manipulation of candidate phyla radiation bacteria provides functional insights into microbial dark matter

The study of bacteria has yielded fundamental insights into cellular biology and physiology, biotechnological advances and many therapeutics. Yet due to a lack of suitable tools, the significant portion of bacterial diversity held within the candidate phyla radiation (CPR) remains inaccessible to such pursuits. Here we show that CPR bacteria belonging to the phylum Saccharibacteria exhibit natural competence. We exploit this property to develop methods for their genetic manipulation, including the insertion of heterologous sequences and the construction of targeted gene deletions. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth and a transposon insertion sequencing genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their Actinobacteria hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii, as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.

microbiology↗

bioRxiv2023

Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut.

Clostridioides difficile colonizes up to 30-40% of community-dwelling adults without causing disease. C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S. and typically develop in individuals following disruption of the gut microbiota due to antibiotic or chemotherapy treatments. Further treatment of CDI with antibiotics is not always effective and can lead to antibiotic resistance and recurrent infections (rCDI). The most effective treatment for rCDI is the reestablishment of an intact microbiota via fecal microbiota transplants (FMTs). However, the success of FMTs has been difficult to generalize because the microbial interactions that prevent engraftment and facilitate the successful clearance of C. difficile are still only partially understood. Here we show how microbial community-scale metabolic models (MCMMs) accurately predicted known instances of C. difficile colonization susceptibility or resistance in vitro and in vivo. MCMMs provide detailed mechanistic insights into the ecological interactions that govern C. difficile engraftment, like cross-feeding or competition involving metabolites like succinate, trehalose, and ornithine, which differ from person to person. Indeed, three distinct C. difficile metabolic niches emerge from our MCMMs, two associated with positive growth rates and one that represents non-growth, which are consistently observed across 15,204 individuals from five independent cohorts. Finally, we show how MCMMs can predict personalized engraftment and C. difficile growth suppression for a probiotic cocktail (VE303) designed to replace FMTs for the treatment rCDI. Overall, this powerful modeling approach predicts personalized C. difficile engraftment risk and can be leveraged to assess probiotic treatment efficacy. MCMMs could be extended to understand the mechanistic underpinnings of personalized engraftment of other opportunistic bacterial pathogens, beneficial probiotic organisms, or more complex microbial consortia.

systems biology↗

bioRxiv2023

Discovery of a unique pathway for glutathione utilization in Francisella

Glutathione (GSH) is an abundant metabolite that can act as a signal, a nutrient source, or serve in a redox capacity for intracellular pathogens. For Francisella, GSH is thought to be a critical in vivo source of cysteine; however, the cellular pathways permitting GSH utilization by Francisella differ between strains and have remained poorly understood. Using genetic screening, we discovered a unique pathway for GSH utilization in Francisella spp. Whereas prior work suggested GSH catabolism initiates in the periplasm, the pathway we define consists of a major facilitator superfamily member that transports intact GSH and a previously unrecognized bacterial cytoplasmic enzyme that catalyzes the first step of GSH degradation. Interestingly, we find that the transporter gene for this pathway is pseudogenized in pathogenic Francisella, explaining phenotypic discrepancies in GSH utilization among Francisella spp. and revealing a critical role for GSH in the environmental niche of these bacteria.

microbiology↗

bioRxiv2022

A genome-scale atlas reveals complex interplay of transcription and translation in an archaeon

The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation on environmental acclimation is underexplored for organisms of the domain Archaea. Here, we have investigated the scale of post-transcriptional regulation in the extremely halophilic archaeon Halobacterium salinarum NRC-1 by integrating transcriptome-wide locations of transcript processing sites (TPS) and SmAP1 binding, genome-wide locations of antisense RNAs (asRNAs), and consequences of RNase_2099C knockout on differential expression of all genes. This integrated analysis has discovered that 54% of all protein-coding genes in the genome of this haloarchaeon are likely targeted by multiple mechanisms for putative post-transcriptional processing and regulation, with about 20% of genes likely regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (RNA-Seq) and protein levels (SWATH-MS) for 2,579 genes over four phases of batch culture growth in complex medium has generated additional evidence for conditional post-transcriptional regulation of 7% of all protein-coding genes. We demonstrate that post-transcriptional regulation may act to fine-tune specialized and rapid acclimation to stressful environments, e.g., as a switch to turn on gas vesicle biogenesis to promote vertical relocation in anoxic conditions and to modulate frequency of transposition by IS elements of the IS200/IS605, IS4, and ISH3 families. Findings from this study are provided as an atlas in a public web resource (https://halodata.systemsbiology.net). IMPORTANCEWhile the transcriptional regulation landscape of archaea has been extensively investigated, we currently have limited knowledge about post-transcriptional regulation and its driving mechanisms in this domain of life. In this study, we collected and integrated omics data from multiple sources and technologies to infer post-transcriptionally regulated genes and the putative mechanisms modulating their expression at the protein level in Halobacterium salinarum NRC-1. The results suggest that post-transcriptional regulation may drive environmental acclimation by regulating hallmark biological processes. To foster discoveries by other research groups interested in the topic, we extended our integrated data to the public in the form of an interactive atlas (https://halodata.systemsbiology.net).

systems biology↗

bioRxiv2021

MtrA regulation of essential peptidoglycan cleavage in Mycobacterium tuberculosis during infection

The success of Mycobacterium tuberculosis (Mtb) is largely due to its ability to withstand multiple stresses encountered in the host. Here, we present a data-driven model that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. The model captures the genome-wide distribution of cis-acting gene regulatory elements and the conditional influences of transcription factors at those elements to elicit environment-specific responses. Analysis of transcriptional responses that may be essential for Mtb to survive acidic stress within the maturing macrophage, identified regulatory control by the MtrAB two-component signal system. Using genome-wide transcriptomics as well as imaging studies, we have characterized the MtrAB circuit by tunable CRISPRi knockdown in both Mtb and the non-pathogenic organism, M. smegmatis (Msm). These experiments validated the essentiality of MtrA in Mtb, but not Msm. We identified that MtrA regulates multiple enzymes that cleave cell wall peptidoglycan and is required for efficient cell division. Moreover, our results suggest that peptidoglycan cleavage, regulated by MtrA, is necessary for Mtb to survive intracellular stress. Further, we present MtrA as an attractive drug target, as even weak repression of mtrA results in loss of Mtb viability and completely clears the bacteria with low-dose isoniazid or rifampicin treatment.

systems biology↗

bioRxiv2021

Transcriptome signature of cell viability predicts drug response and drug interaction for Tuberculosis

The treatment of tuberculosis (TB), which kills 1.8 million each year, remains difficult, especially with the emergence of multidrug resistant strains of Mycobacterium tuberculosis (Mtb). While there is an urgent need for new drug regimens to treat TB, the process of drug evaluation is slow and inefficient owing to the slow growth rate of the pathogen, the complexity of performing bacteriologic assays in a high-containment facility, and the context-dependent variability in drug sensitivity of the pathogen. Here, we report the development of "DRonA" and "MLSynergy", algorithms to perform rapid drug response assays and predict response of Mtb to novel drug combinations. Using a novel transcriptome signature for cell viability, DRonA accurately detects bacterial killing by diverse mechanisms in broth culture, macrophage infection and patient sputum, providing an efficient, and more sensitive alternative to time- and resource-intensive bacteriologic assays. Further, MLSynergy builds on DRonA to predict novel synergistic and antagonistic multi-drug combinations using transcriptomes of Mtb treated with single drugs. Together DRonA and MLSynergy represent a generalizable framework for rapid monitoring of drug effects in host-relevant contexts and accelerate the discovery of efficacious high-order drug combinations.

microbiology↗

bioRxiv2021

Autophagy as a mechanism for adaptive prediction-mediated emergence of drug resistance

Drug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-FOA). Here, we demonstrate that mutations selected across multiple laboratory evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. We propose a model to explain how extensive genome-wide genetic interactions of autophagy facilitates emergence of AP over short evolutionary timescales to potentiate selection of resistance-conferring mutations.

evolutionary biology↗

bioRxiv2021

Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks of Mycobacterium tuberculosis

The ability of Mycobacterium tuberculosis (Mtb) to adopt heterogeneous physiological states, underlies its success in evading the immune system and tolerating antibiotic killing. Drug tolerant phenotypes are a major reason why the tuberculosis (TB) mortality rate is so high, with over 1.8 million deaths annually. To develop new TB therapeutics that better treat the infection (faster and more completely), a systems-level approach is needed to reveal the complexity of network-based adaptations of Mtb. Here, we report a new predictive model called PRIME (Phenotype of Regulatory influences Integrated with Metabolism and Environment) to uncover environment-specific vulnerabilities within the regulatory and metabolic networks of Mtb. Through extensive performance evaluations using genome-wide fitness screens, we demonstrate that PRIME makes mechanistically accurate predictions of context-specific vulnerabilities within the integrated regulatory and metabolic networks of Mtb, accurately rank-ordering targets for potentiating treatment with frontline drugs.

systems biology↗

bioRxiv2020

A plastid antiporter as a bioindicator of Thalassiosira pseudonana resilience

Acidification of the ocean due to high atmospheric CO2 levels may increase the resilience of diatoms causing dramatic shifts in abiotic and biotic cycles with lasting implications on marine ecosystems. Here, we report a potential bioindicator of a shift in the resilience of a coastal and centric model diatom Thalassiosira pseudonana under elevated CO2. Specifically, we have discovered, through EGFP-tagging, a plastid membrane localized putative Na+(K+)/H+ antiporter that is significantly upregulated at > 800 ppm CO2, with a potentially important role in maintaining pH homeostasis. Notably, transcript abundance of this antiporter gene was relatively low and constant over the diel cycle under contemporary CO2 conditions. In future acidified oceanic conditions, dramatic oscillations of >10-fold change between nighttime (high) and daytime (low) in transcript abundances of the antiporter gene were associated with increased resilience of T. pseudonana. By analyzing metatranscriptomic data from the Tara Oceans project, we demonstrate that phylogenetically diverse diatoms express homologs of this antiporter across the globe. We propose that the differential between night- and daytime transcript levels of the antiporter could serve as a bioindicator of a shift in the resilience of diatoms in response to high CO2 conditions in marine environments.

systems biology↗

bioRxiv2020

Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile

Though Clostridioides difficile is among the most studied anaerobes, the interplay of metabolism and regulation that underlies its ability to colonize the human gut is unknown. We have compiled public resources into three models and a portal to support comprehensive systems analysis of C. difficile. First, by leveraging 151 transcriptomes from 11 studies we generated a regulatory model (EGRIN) that organizes 90% of C. difficile genes into 297 high quality conditional co-regulation modules. EGRIN predictions, validated with independent datasets, recapitulated and extended regulons of key transcription factors, implicating new genes for sporulation, carbohydrate transport and metabolism. Second, by advancing a metabolic model, we discovered that 15 amino acids, diverse carbohydrates, and 10 metabolic genes are essential for C. difficile growth within an intestinal environment. Finally, by integrating EGRIN with the metabolic model, we developed a PRIME model that revealed unprecedented insights into combinatorial control of essential processes for in vivo colonization of C. difficile and its interactions with commensals. We have developed an interactive web portal (http://networks.systemsbiology.net/cdiff-portal/) to disseminate all data, algorithms, and models to support collaborative systems analyses of C. difficile.

systems biology↗