Biology subjects

Sherman, D. R.

Publications and source records attributed to Sherman, D. R..

11 recordsLinked to original sources

bioRxiv2025

Transcript-Capture sequencing enriches mRNA of Mycobacterium tuberculosis from host samples

Bacterial gene expression from sites of infection are poorly studied due to low levels of bacterial mRNA present in clinical samples. Here, we develop Transcript-Capture Seq, which uses customizable biotinylated probes generated in-house to enrich bacteria-specific RNA from host samples before Next Generation Sequencing (NGS). This method results in a >200-fold increase in bacterial mRNA reads from mixed samples and allows analysis of the complete bacterial transcriptome from clinical samples. We apply Transcript-Capture to models of tuberculosis (TB) infection as well as sputum samples from TB patients. TB patients exhibit unexplained heterogeneity in disease progression, and the activity of Mycobacterium tuberculosis (Mtb) has been proposed to affect treatment response. By applying Transcript-Capture to sputum samples collected from TB patients we generate the first complete in vivo bacterial transcriptome of Mtb via NGS. Mtb from patient sputa shows upregulation of genes involved in host lipid utilization and zinc limitation, as well as a similar gene expression profile to Mtb log phase growth in vitro. Applying Transcript-Capture to clinical sputa provides a snapshot of bacterial activity directly from human patients and can be used to investigate the physiological state of bacteria surviving in vivo. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/685133v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@406294org.highwire.dtl.DTLVardef@1080173org.highwire.dtl.DTLVardef@973909org.highwire.dtl.DTLVardef@21becc_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

ESX-5 Deletions in Mycobacterium tuberculosis Alter Macrophage Cytokine Signaling and Bacterial Heavy Metal Response

The ESX-5 secretion system is critical for Mycobacterium tuberculosis (Mtb) viability and putatively linked to pathogenesis, but a functional understanding of how it interacts with the host is unknown. ESX-5 is encoded at a single genomic locus with small, paralogous, secreted targets (ESX-5a, 5b, 5c) spaced throughout the genome. To examine host-pathogen interactions of these putative virulence clusters, we made mutant strains lacking these loci and infected primary human macrophages. Surprisingly, all deletion mutants independently reduced cytokine secretion during infection, specific to certain analytes. This defect depended on viable bacteria and was mediated by a post-transcriptional mechanism. In bacterial transcriptomic analyses, each mutant downregulated heavy metal response genes compared to wild type bacteria. Treatment of Mtb with Cu or Cd led to increased ESX-5a and ESX-5c expression, concurrent with increased TNF and IL-6 secretion in macrophages compared to untreated bacilli, indicating a link between ESX-5 expression and cellular cytokine levels.

immunology↗

bioRxiv2025

The pH gradient contributes to persistence in Mycobacterium tuberculosis

Tuberculosis (TB) remains difficult to cure due in part to poorly defined drug-tolerant persister cells formed by Mycobacterium tuberculosis (Mtb), which survive antibiotic treatment without evidence of genetic resistance. To better define this phenotype, we screened 2,336 FDA-approved drugs for compounds that target persistence. Unexpectedly, we identified a strong inducer of drug tolerance -- the antiparasitic niclosamide (NCA), which is known to disrupt proton motive force. In contrast to earlier reports that it harbors promising anti-TB activity, we found that NCA protected Mtb from bactericidal doses of isoniazid, rifampicin, and other standard TB drugs. Investigating further, we showed that disruption of the pH gradient and consequent intracellular acidification is needed to induce tolerance, while disruption of membrane potential is not, and also that protection is tunable by external pH. Transcriptomic analysis of these chemically-induced persister (CIP) cells implicated specific genes in this phenotype, and targeted knockdowns confirmed roles for three genes in either promoting or mitigating the tolerance state. These findings highlight that chemical disruption of the pH gradient is a facile and rapid means to induce drug tolerance, offering a potentially useful tool to probe persister biology in TB and other infectious diseases.

microbiology↗

bioRxiv2024

Netupitant Exhibits Potent Activity on Mycobacterium tuberculosis Persisters

In Mycobacterium tuberculosis (Mtb), persisters are genotypically drug-sensitive bacteria that nonetheless survive antibiotic treatment. Persisters represent a significant challenge to shortening TB treatment and preventing relapse, underscoring the need for new therapeutic strategies. In this study, we screened 2,336 FDA-approved compounds to identify agents that enhance the sterilizing activity of standard anti-TB drugs and prevent the regrowth of persisters. Netupitant (NTP), an FDA-approved antiemetic, emerged as a promising candidate with bacteriostatic activity on its own. However, in combination with isoniazid (INH) and rifampicin (RIF), NTP eliminated viable Mtb cells within 7 days, achieving a >6-log reduction in colony-forming units (CFUs) compared to the 2.5-log reduction observed with INH-RIF alone. NTP also demonstrated broad-spectrum efficacy, enhancing the activity of multiple TB drugs, including ethambutol, moxifloxacin, amikacin, and bedaquiline. Notably, NTP retained its potency under hypoxic and caseum-mimicking conditions, both of which are known to enrich for non-replicating, drug-tolerant cells. Interestingly, under hypoxic conditions, NTP demonstrated strong tuberculocidal activity, achieving an approximate 4-log CFU reduction, whereas high-dose INH-RIF was ineffective. Transcriptomic analysis revealed that NTP primarily disrupts cellular bioenergetics, with significant downregulation observed in activities associated with the electron transport chain, oxidative phosphorylation, NADH-ubiquinone oxidoreductase, succinate dehydrogenase, and ATP synthesis. While further studies are required to decipher the mechanism of action and resistance profile of NTP, and to assess its in vivo efficacy, these findings underscore its potential as a promising adjunct to existing TB therapies.

microbiology↗

bioRxiv2024

Predicting bacterial fitness in Mycobacterium tuberculosis with transcriptional regulatory network-informed interpretable machine learning

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis disease, the greatest source of global mortality by a bacterial pathogen. Mtb adapts and responds to diverse stresses such as antibiotics by inducing transcriptional stress-response regulatory programs. Understanding how and when these mycobacterial regulatory programs are activated could enable novel treatment strategies for potentiating the efficacy of new and existing drugs. Here we sought to define and analyze Mtb regulatory programs that modulate bacterial fitness. We assembled a large Mtb RNA expression compendium and applied these to infer a comprehensive Mtb transcriptional regulatory network and compute condition-specific transcription factor activity profiles. We utilized transcriptomic and functional genomics data to train an interpretable machine learning model that can predict Mtb fitness from transcription factor activity profiles. We demonstrated that this transcription factor activity-based model can successfully predict Mtb growth arrest and growth resumption under hypoxia and reaeration using only RNA-seq expression data as a starting point. These integrative network modeling and machine learning analyses thus enable the prediction of mycobacterial fitness under different environmental and genetic contexts. We envision these models can potentially inform the future design of prognostic assays and therapeutic intervention that can cripple Mtb growth and survival to cure tuberculosis disease.

systems biology↗

bioRxiv2022

The Mycobacterium tuberculosis protein O-phosphorylation landscape

Bacterial phosphosignaling has long been synonymous with the histidine kinases of the two component systems, but many bacteria, including Mycobacterium tuberculosis (Mtb), also code for Ser/Thr protein kinases (STPKs). STPKs are the main phosphosignaling enzymes in eukaryotes, but the full extent of phosphorylation on protein Ser/Thr and Tyr (O-phosphorylation) in bacteria remains unclear. Here, we explored the global signaling capacity of the STPKs in Mtb. We generated STPK loss-and gain-of-function strains and measured the resulting O-phosphorylation and transcriptional changes. This deep phosphoproteome shows that O-phosphorylation in Mtb is an underexplored protein modification that affects >70% of the proteome. The substrate-STPK interactions show an extensive interface with the transcriptional machinery, resulting in regulation of gene expression of [~]30% of Mtb genes. Mtb O-phosphorylation gives rise to an expansive, distributed, and cooperative network of a complexity that has previously only been associated with eukaryotic phosphosignaling networks.

microbiology↗

bioRxiv2020

Rapid, direct detection of bacterial Topoisomerase 1 - DNA adducts by RADAR/ELISA

Topoisomerases are proven drug targets, but antibiotics that poison bacterial Topoisomerase 1 (Top1) have yet to be discovered. We have developed a rapid and direct assay for quantification of Top1-DNA adducts that is suitable for high throughput assays. Adducts are recovered by "RADAR fractionation", a quick, convenient approach in which cells are lysed in chaotropic salts and detergent and nucleic acids and covalently bound adducts then precipitated with alcohol. Here we show that RADAR fractionation followed by ELISA immunodetection can quantify adducts formed by wild-type and mutant Top1 derivatives encoded by two different bacterial pathogens, Y. pestis and M. tuberculosis, expressed in E. coli or M. smegmatis, respectively. For both enzymes, quantification of adducts by RADAR/ELISA produces results comparable to the more cumbersome classical approach of CsCl density gradient fractionation. The experiments reported here establish that RADAR/ELISA assay offers a simple way to characterize Top1 mutants and analyze kinetics of adduct formation and repair. They also provide a foundation for discovery and optimization of drugs that poison bacterial Top1 using standard high-throughput approaches.

microbiology↗

bioRxiv2020

Network analysis identifies regulators of lineage-specific phenotypes in Mycobacterium tuberculosis

The Mycobacterium tuberculosis (Mtb) complex includes ten phylogenetically distinct human-adapted lineages with varying geographical distributions and pathogenicity. Lineage 1 (L1) is associated with low virulence, while Lineage 2 (L2) is linked to hyper-virulence, increased transmission, and drug resistance. We performed multi-layer comparative analyses integrating whole-genome sequencing with quantitative transcriptomic and proteomic profiling of a panel of L1 and L2 clinical strains, each grown under two in vitro conditions. Our data revealed variable correlations between transcript and protein levels across strains and gene categories, indicating lineage-specific post-translational regulation. Transcriptional and translational differences scaled with phylogenetic distance, with one in three SNPs on average leading to gene expression changes. A newly developed genome-scale transcriptional regulatory model identified master transcription factors--closely linked to the sigma factor network--whose targets were differentially expressed between L1 and L2. Notably, DosR proteins showed higher basal levels and a stronger nitric oxide (NO) response in L2. Time-course validation using an Rv1985c induction and wild-type H37Rv under hypoxia and reaeration confirmed the role of Rv1985c in the differentially expressed genes between L1 and L2. These findings suggest that limited genetic variation can translate into significant phenotypic differences via differential regulation of key transcriptional networks. HighlightsO_LIProteomic and transcriptomic characterization of fully sequenced diverse L1 and L2 clinical strains of Mtb. C_LIO_LIPost translational control mechanisms for regulatory and virulence genes are mitigated in Mtb L2. C_LIO_LIA genome-scale transcriptional framework identifies DosR, Rv1985c, Lsr2 and Rv0691c as master transcription factors responsible for differential target gene expression in L2 compared to L1 strains. C_LIO_LIL1 and L2 DosR proteins respond differently to nitric oxide stress, thus determining a relevant phenotype. C_LIO_LITime-course phenotypic and transcriptomic data under hypoxia and reaeration validate Rv1985c as a key transcription factor differentiating L2 and L1 strains. C_LI

systems biology↗

bioRxiv2019

Transcriptomic signatures predict regulators of drug synergy and clinical regimen efficacy against Tuberculosis

The rapid spread of multi-drug resistant strains has created a pressing need for new drug regimens to treat tuberculosis (TB), which kills 1.8 million people each year. Identifying new regimens has been challenging due to the slow growth of the pathogen M. tuberculosis (MTB), coupled with large number of possible drug combinations. Here we present a computational model (INDIGO-MTB) that identified synergistic regimens featuring existing and emerging anti-TB drugs after screening in silico over 1 million potential drug combinations using MTB drug transcriptomic profiles. INDIGO-MTB further predicted the gene Rv1353c as a key transcriptional regulator of multiple drug interactions, and we confirmed experimentally that Rv1353c up-regulation reduces the antagonism of the bedaquiline-streptomycin combination. Retrospective analysis of 57 clinical trials of TB regimens using INDIGO-MTB revealed that synergistic combinations were significantly more efficacious than antagonistic combinations (p-value = 1 x 10-4) based on the percentage of patients with negative sputum cultures after 8 weeks of treatment. Our study establishes a framework for rapid assessment of TB drug combinations and is also applicable to other bacterial pathogens.\n\nIMPORTANCEMulti-drug combination therapy is an important strategy for treating tuberculosis, the worlds deadliest bacterial infection. Long treatment durations and growing rates of drug resistance have created an urgent need for new approaches to prioritize effective drug regimens. Hence, we developed a computational model called INDIGO-MTB, which identifies synergistic drug regimens from an immense set of possible drug combinations using pathogen response transcriptome elicited by individual drugs. Although the underlying input data for INDIGO-MTB was generated under in vitro broth culture conditions, the predictions from INDIGO-MTB correlated significantly with in vivo drug regimen efficacy from clinical trials. INDIGO-MTB also identified the transcription factor Rv1353c as a regulator of multiple drug interaction outcomes, which could be targeted for rationally enhancing drug synergy.

systems biology↗

bioRxiv2018

Network stress test reveals novel drug potentiators in Mycobacterium tuberculosis

Deciphering molecular stress response is highly relevant to studies of microbes such as Mycobacterium tuberculosis (MTB), the causative pathogen of tuberculosis (TB) which sickens 10 million people and kills 1.8 million each year1. Prolonged therapy and unfavorable outcomes arise partially because MTB has evolved stress responses to achieve tolerance, wherein MTB persists in otherwise inhibitory drug concentrations by means independent of heritable resistance mutations2-4. Understanding these adaptations and how they are regulated can reveal new biology, including unexplored drug targets and treatment-enhancing strategies. Here, we present a novel network-based genetic screening approach: the Transcriptional Regulator Induced Phenotype (TRIP) screen, which we used to identify previously uncharacterized MTB network adaptations to the first-line drug isoniazid (INH). We found regulators that alter IN ...

systems biology↗

bioRxiv2018

Macrophage-induced rifampin tolerance across Mycobacterium tuberculosis lineages is Rv1258c-dependent

The Mycobacterium tuberculosis (Mtb) Lineage 4 strains CDC1551 and H37Rv develop tolerance to multiple antibiotics upon macrophage residence. Genetic mutation of the efflux pump Rv1258c in CDC1551 abolishes rifampin tolerance but not isoniazid tolerance. Here we show that clinical isolates from the other predominant Mtb lineages developed macrophage-induced isoniazid tolerance. Furthermore, all lineages developed rifampin tolerance except Lineage 2 Beijing strains, which are natural Rv1258c mutants. Thus macrophage-induced antibiotic tolerance is featured across the majority of Mtb lineages. Our findings further link Rv1258c to rifampin tolerance among clinical isolates.

microbiology↗