Biology subjects

Schnappinger, D.

Publications and source records attributed to Schnappinger, D..

25 records · Page 2Linked to original sources

bioRxiv2021

Multiple acyl-CoA dehydrogenase deficiency kills Mycobacterium tuberculosis in vitro and during infection

The human pathogen Mycobacterium tuberculosis (Mtb) devotes a significant fraction of its genome to fatty acid metabolism. Although Mtb depends on host fatty acids as a carbon source, fatty acid {beta}-oxidation is mediated by genetically redundant enzymes, which has hampered the development of antitubercular drugs targeting this metabolic pathway. Here, we identify rv0338c, referred to as etfDMtb, to encode a membrane dehydrogenase essential for fatty acid {beta}-oxidation in Mtb. An etfD deletion mutant ({Delta}etfD) was incapable of growing on fatty acids in vitro, with long-chain fatty acids being bactericidal, and failed to grow and survive in mice. The {Delta}etfD metabolome revealed a block in {beta}-oxidation at the step catalyzed by acyl-CoA dehydrogenases (ACADs). In many organisms, including humans, ACADs are functionally dependent on an electron transfer flavoprotein (ETF) and cognate dehydrogenase. Immunoprecipitation identified EtfD in complex with FixA (EtfBMtb). FixA (EtfBMtb) and FixB (EtfAMtb) are homologous to the human ETF subunits. Our results demonstrate that EtfBAMtb constitutes Mtbs ETF, while EtfDMtb, although not homologous to human EtfD, functions as the dehydrogenase. These findings identify Mtbs fatty acid {beta}-oxidation as a novel potential target for TB drug development.

microbiology↗

bioRxiv2021

Chemical-genetic interaction mapping links carbon metabolism and cell wall structure to tuberculosis drug efficacy

Current chemotherapy against Mycobacterium tuberculosis (Mtb), an important human pathogen, requires a multidrug regimen lasting several months. While efforts have been made to optimize therapy by exploiting drug-drug synergies, testing new drug combinations in relevant host environments remains arduous. In particular, host environments profoundly affect the bacterial metabolic state and drug efficacy, limiting the accuracy of predictions based on in vitro assays alone. In this study, we utilize conditional Mtb knockdown mutants of essential genes as an experimentally-tractable surrogate for drug treatment, and probe the relationship between Mtb carbon metabolism and chemical-genetic interactions (CGI). We examined the anti-tubercular drugs isoniazid, rifampicin and moxifloxacin, and found that CGI are differentially responsive to the metabolic state, defining both environment-independent and -dependent interactions. Specifically, growth on the in vivo-relevant carbon source, cholesterol, reduced rifampicin efficacy by altering mycobacterial cell surface lipid composition. We report that a variety of perturbations in cell wall synthesis pathways restore rifampicin efficacy during growth on cholesterol, and that both environment-independent and cholesterol-dependent in vitro CGI could be leveraged to enhance bacterial clearance in the mouse infection model. Our findings present an atlas of novel chemical-genetic-environmental interactions that can be used to optimize drug-drug interactions as well as provide a framework for understanding in vitro correlates of in vivo efficacy. SignificanceEfforts to improve tuberculosis therapy include optimizing multi-drug regimens to take advantage of drug-drug synergies. However, the complex host environment has a profound effect on bacterial metabolic state and drug activity, making predictions of optimal drug combinations difficult. In this study, we leverage a newly developed library of conditional knockdown Mycobacterium tuberculosis mutants in which genetic depletion of essential genes mimics the effect of drug therapy. This tractable system allowed us to assess the effect of growth condition on predicted drug-drug interactions. We found that these interactions can be differentially sensitive to the metabolic state and select in vitro-defined interactions can be leveraged to accelerate bacterial killing during infection. These findings suggest new strategies for optimizing tuberculosis therapy.

microbiology↗

bioRxiv2021

The Mycobacterium tuberculosis transposon sequencing database (MtbTnDB): a large-scale guide to genetic conditional essentiality

Characterizing genetic essentiality across various conditions is fundamental for understanding gene function. Transposon sequencing (TnSeq) is a powerful technique to generate genome-wide essentiality profiles in bacteria and has been extensively applied to Mycobacterium tuberculosis (Mtb). Dozens of TnSeq screens have yielded valuable insights into the biology of Mtb in vitro, inside macrophages, and in model host organisms. Despite their value, these Mtb TnSeq profiles have not been standardized or collated into a single, easily searchable database. This results in significant challenges when attempting to query and compare these resources, limiting our ability to obtain a comprehensive and consistent understanding of genetic conditional essentiality in Mtb. We address this problem by building a central repository of publicly available Mtb TnSeq screens, the Mtb transposon sequencing database (MtbTnDB). The MtbTnDB is a living resource that encompasses to date {approx}150 standardized TnSeq screens, enabling open access to data, visualizations, and functional predictions through an interactive web app (www.mtbtndb.app). We conduct several statistical analyses on the complete database, such as demonstrating that (i) genes in the same genomic neighborhood have similar TnSeq profiles, and (ii) clusters of genes with similar TnSeq profiles are enriched for genes from similar functional categories. We further analyze the performance of machine learning models trained on TnSeq profiles to predict functional annotation of orphan genes in Mtb. By facilitating the comparison of TnSeq screens across conditions, the MtbTnDB will accelerate the exploration of conditional genetic essentiality, provide insights into the functional organization of Mtb genes, and help predict gene function in this important human pathogen.

microbiology↗

bioRxiv2021

Genetic models of latent tuberculosis in mice reveal differential control by innate and adaptive immunity

Studying latent Mycobacterium tuberculosis (Mtb) infection has been limited by the lack of a suitable mouse model. We discovered that transient depletion of protein biotin ligase (BPL) and thioredoxin reductase (TrxB2) results in latent infections during which Mtb cannot be detected but that relapse in a subset of mice. The immune requirements for Mtb control during latency, and the frequency of relapse, were strikingly different depending on how latency was established. TrxB2 depletion resulted in a latent infection that required adaptive immunity for control and reactivated with high frequency, whereas latent infection after BPL depletion was independent of adaptive immunity and rarely reactivated. We identified immune signatures of T cells indicative of relapse and demonstrated that BCG vaccination failed to protect mice from TB relapse. These reproducible genetic latency models allow investigating the host immunological determinants that control the latent state and offer opportunities to evaluate therapeutic strategies in settings that mimic aspects of latency and TB relapse in humans.

microbiology↗

bioRxiv2020

Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice

The outcome of an encounter with Mycobacterium tuberculosis depends on the pathogens ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to associate bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb mutant fitness across the CC panel revealed that many virulence pathways are only in specific host microenvironments, identifying the large fraction of the pathogens genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits were associated with genetic variants distributed across the mouse genome, identifying the specific host-pathogen genetic interactions that influence pathogenesis.

genetics↗

bioRxiv2020

Re-discovery of PF-3845 as a new chemical scaffold inhibiting phenylalanyl-tRNA synthetase in Mycobacterium tuberculosis

Mycobacteria tuberculosis (Mtb) remains the deadliest pathogenic bacteria worldwide. The search for new antibiotics to treat drug-sensitive as well as drug-resistant tuberculosis has become a priority. The essential enzyme phenylalanyl-tRNA synthetase (PheRS) is an antibacterial drug target because of the large differences between bacterial and human PheRS counterparts. In a high-throughput screening of 2148 bioactive compounds, PF-3845, which is a known inhibitor of human fatty acid amide hydrolase (FAAH), was identified inhibiting Mtb PheRS at Ki [~]0.73 {+/-} 0.055 {micro}M. The inhibition mechanism was studied with enzyme kinetics, protein structural modelling and crystallography, in comparison to a PheRS inhibitor of the noted phenyl-thiazolylurea-sulfonamide class. The 2.3-[A] crystal structure of Mtb PheRS in complex with PF-3845 revealed its novel binding mode, in which a trifluoromethyl-pyridinylphenyl group occupies the Phe pocket while a piperidine-piperazine urea group binds into the ATP pocket through an interaction network enforced by a sulfate ion. It represents the first non-nucleoside bi-substrate competitive inhibitor of bacterial PheRS. PF-3845 inhibits the in vitro growth of Mtb H37Rv at [~]24 {micro}M, and the potency of PF-3845 increased against Mtb pheS-FDAS, suggesting on target activity in mycobacterial whole cells. PF-3845 does not inhibit human cytoplasmic or mitochondrial PheRSs in biochemical assay, which can be explained from the crystal structures. Further elaboration of the piperidine-piperazine urea moiety by medicinal chemistry effort will produce potential antibacterial lead with improved selectivity on the cellular level.

biochemistry↗

bioRxiv2019

Statistical Analysis of Variability in TnSeq Data Across Conditions Using Zero-Inflated Negative Binomial Regression

Deep sequencing of transposon mutant libraries (or TnSeq) is a powerful method for probing essentiality of genomic loci under different environmental conditions. Various analytical methods have been described for identifying conditionally essential genes whose tolerance for insertions varies between two conditions. However, for large-scale experiments involving many conditions, a method is needed for identifying genes that exhibit significant variability in insertions across multiple conditions. In this paper, we introduce a novel statistical method for identifying genes with significant variability of insertion counts across multiple conditions based on Zero-Inflated Negative Binomial (ZINB) regression. Using likelihood ratio tests, we show that the ZINB fits TnSeq data better than either ANOVA or a Negative Binomial (in a generalized linear model). We use ZINB regression to identify genes required for infection of M. tuberculosis H37Rv in C57BL/6 mice. We also use ZINB to perform a retrospective analysis of genes conditionally essential in H37Rv cultures exposed to multiple antibiotics. Our results show that, not only does ZINB generally identify most of the genes found by pairwise resampling (and vastly out-performs ANOVA), but it also identifies additional genes where variability is detectable only when the magnitudes of insertion counts are treated separately from local differences in saturation, as in the ZINB model.

bioinformatics↗