Carbon And Lipid Metabolism In Mycobacterium Tuberculosis

Mycobacterium tuberculosis is an air borne, facultative intracellular bacterial pathogen that resides in the phagosome of host cells. Virulence of M. tuberculosis is related to its abilities to respond to environmental cues encountered during infection and reprogram its metabolism to adapt to them. Nutrients derived from the host are key factors contributing to shape the carbon metabolism of M. tuberculosis during infection. This metabolic shift involves activation of fatty acid and cell wall lipids metabolism of the bacterium; however, the mechanistic interplay between them is undefined. In this study, to understand the metabolic adaptation on propionyl-CoA 3carbon product of cholesterol in M. tuberculosis, the propionate detoxification and methyl-branched (MB) lipid synthesis pathways were investigated. The data presented here shows that excess propionyl-CoA was toxic to M. tuberculosis, as the propionylCoA inhibited pyruvate dehydrogenase (PDH) and acetate or fatty acid rescued the toxicity through providing acetyl-CoA the product of PDH. A mechanistic insight was revealed by metabolic labeling with radioactive propionate and fatty acids: the given fatty acids facilitate propionyl-CoA incorporation into a key MB lipid PDIM by serving as acyl-primers required for its biosynthesis. Additionally, to further define genes required for propionate and fatty acid metabolism an approach exploiting propionate toxicity and TraSH analysis was employed. The data from the genetic profiling by TraSH confirms our model for the fatty acids rescue from the propionate toxicity and suggests putative roles for uncharacterized genes in MB lipids synthesis and fatty acid metabolism. This model was also validated by using lipid droplet loaded macrophage where M. tuberculosis exploited fatty acids from the host lipid droplet to synthesis PDIM resulting in reduction of the propionate stress. Data presented in this work demonstrates that the propionyl-CoA processing is a significant problem for survival in the host cell, and that the routing of propionyl-CoA into MB cell wall lipids plays an important role for limiting the metabolic stress derived from propionate. And, the data also demonstrates that the fatty acids from lipid droplets in the host macrophage may provide a well-balanced diet that retains appropriate level of acetyl-CoA and propionyl-CoA

Efficient production of d-lactate from methane in a lactate-tolerant strain of Methylomonas sp. DH-1 generated by adaptive laboratory evolution

Background Methane, a main component of natural gas and biogas, has gained much attention as an abundant and low-cost carbon source. Methanotrophs, which can use methane as a sole carbon and energy source, are promising hosts to produce value-added chemicals from methane, but their metabolic engineering is still challenging. In previous attempts to produce lactic acid (LA) from methane, LA production levels were limited in part due to LA toxicity. We solved this problem by generating an LA-tolerant strain, which also contributes to understanding novel LA tolerance mechanisms. Results In this study, we engineered a methanotroph strain Methylomonas sp. DH-1 to produce d-lactic acid (d-LA) from methane. LA toxicity is one of the limiting factors for high-level production of LA. Therefore, we first performed adaptive laboratory evolution of Methylomonas sp. DH-1, generating an LA-tolerant strain JHM80. Genome sequencing of JHM80 revealed the causal gene watR, encoding a LysR-type transcription factor, whose overexpression due to a 2-bp (TT) deletion in the promoter region is partly responsible for the LA tolerance of JHM80. Overexpression of the watR gene in wild-type strain also led to an increase in LA tolerance. When d form-specific lactate dehydrogenase gene from Leuconostoc mesenteroides subsp. mesenteroides ATCC 8293 was introduced into the genome while deleting the glgA gene encoding glycogen synthase, JHM80 produced about 7.5-fold higher level of d-LA from methane than wild type, suggesting that LA tolerance is a critical limiting factor for LA production in this host. d-LA production was further enhanced by optimization of the medium, resulting in a titer of 1.19 g/L and a yield of 0.245 g/g CH4. Conclusions JHM80, an LA-tolerant strain of Methylomonas sp. DH-1, generated by adaptive laboratory evolution was effective in LA production from methane. Characterization of the mutated genes in JHM80 revealed that overexpression of the watR gene, encoding a LysR-type transcription factor, is responsible for LA tolerance. By introducing a heterologous lactate dehydrogenase gene into the genome of JHM80 strain while deleting the glgA gene, high d-LA production titer and yield were achieved from methane.This work was supported by C1 Gas Refnery Program through the National Research Foundation of Korean (NRF) funded by the Ministry of Science and ICT (2016M3D3A01913245)

Multidrug Intrinsic Resistance Factors inStaphylococcus aureusIdentified by Profiling Fitness within High-Diversity Transposon Libraries

Staphylococcus aureus is a leading cause of life-threatening infections worldwide. The MIC of an antibiotic against S. aureus, as well as other microbes, is determined by the affinity of the antibiotic for its target in addition to a complex interplay of many other cellular factors. Identifying nontarget factors impacting resistance to multiple antibiotics could inform the design of new compounds and lead to more-effective antimicrobial strategies. We examined large collections of transposon insertion mutants in S. aureus using transposon sequencing (Tn-Seq) to detect transposon mutants with reduced fitness in the presence of six clinically important antibiotics-ciprofloxacin, daptomycin, gentamicin, linezolid, oxacillin, and vancomycin. This approach allowed us to assess the relative fitness of many mutants simultaneously within these libraries. We identified pathways/genes previously known to be involved in resistance to individual antibiotics, including graRS and vraFG (graRS/vraFG), mprF, and fmtA, validating the approach, and found several to be important across multiple classes of antibiotics. We also identified two new, previously uncharacterized genes, SAOUHSC_01025 and SAOUHSC_01050, encoding polytopic membrane proteins, as important in limiting the effectiveness of multiple antibiotics. Machine learning identified similarities in the fitness profiles of graXRS/vraFG, SAOUHSC_01025, and SAOUHSC_01050 mutants upon antibiotic treatment, connecting these genes of unknown function to modulation of crucial cell envelope properties. Therapeutic strategies that combine a known antibiotic with a compound that targets these or other intrinsic resistance factors may be of value for enhancing the activity of existing antibiotics for treating otherwise-resistant S. aureus strains