Project description:Tuberculosis (TB) is one of the deadliest infectious disorders in the world. To effectively TB manage, an essential step is to gain insight into the lineage of Mycobacterium tuberculosis (MTB) strains and the distribution of drug resistance. Although the Campania region is declared a cluster area for the infection, to contribute to the effort to understand TB evolution and transmission, still poorly known, we have generated a dataset of 159 genomes of MTB strains, from Campania region collected during 2018-2021, obtained from the analysis of whole genome sequence data. The results show that the most frequent MTB lineage is the 4 according for 129 strains (81.11%). Regarding drug resistance, 139 strains (87.4%) were classified as multi susceptible, while the remaining 20 (12.58%) showed drug resistance. Among the drug-resistance strains, 8 were isoniazid-resistant MTB (HR-MTB), 7 were resistant only to one antibiotic (3 were resistant only to ethambutol and 3 isolate to streptomycin while one isolate showed resistance to fluoroquinolones), 4 multidrug-resistant MTB, while only one was classified as pre-extensively drug-resistant MTB (pre-XDR). This dataset expands the existing available knowledge on drug resistance and evolution of MTB, contributing to further TB-related genomics studies to improve the management of TB infection.
Project description:We sought to determine how a cystic fibrosis isolate of Stenotrophomonas maltophilia responds to relevant pH gradients (pH 5, 7, and 9) by growing the bacterium in phosphate buffered media and conducting RNAseq experiments. Our data suggests acidic conditions are stressful for strain FLR19, as it responded by increasing expression of stress-response and antibiotic-resistance genes.
Project description:CyuR (b0447, also known as DecR or YbaO) is a recently characterized transcription regulator responsible for the generation of hydrogen sulfide (H2S) from L-cysteine (Cys), which decreases oxidative stress. Given that mitigation of oxidative stress is an important survival mechanism to achieve antibiotic resistance (AR) in many pathogenic bacteria such as Escherichia coli and Salmonella enterica, detailed studies about its effect and the regulatory network of CyuR are imperative. In this study, we investigated the roles of CyuR and its regulon genes in a Cys-dependent AR mechanism in E. coli in a microaerobic condition. We show that (1) CyuR negatively controls the expression of mdlAB encoding a transporter that may export antibiotics. (2) Cys metabolism has a significant role in AR and its effect is conserved in many E. coli strains including clinical isolates. (3) CyuR binds ‘GAAwAAATTGTxGxxATTTsyCC’ in the absence of Cys found by performing an in vitro binding assay. (4) CyuR may regulate 14 genes, in addition to previously reported 2 genes, as we suggested by in silico motif scanning and transcriptome sequencing. Collectively, our findings confirm the significant roles of CyuR and its relevance to antibiotic resistance associated with Cys.
Project description:The pathogen Clostridioides difficile causes toxin-mediated diarrhea and is the leading cause of hospital-acquired infection in the United States. Due to growing antibiotic resistance and recurrent infection, targeting C. difficile metabolism presents a new approach to combat this infection. Genome-scale metabolic network reconstructions (GENREs) have been used to identify therapeutic targets and uncover properties that determine cellular behaviors. Thus, we constructed C. difficile GENREs for a hypervirulent isolate (strain [str.] R20291) and a historic strain (str. 630), validating both with in vitro and in vivo data sets. Growth simulations revealed significant correlations with measured carbon source usage (positive predictive value [PPV] ≥ 92.7%), and single-gene deletion analysis showed >89.0% accuracy. Next, we utilized each GENRE to identify metabolic drivers of both sporulation and biofilm formation. Through contextualization of each model using transcriptomes generated from in vitro and infection conditions, we discovered reliance on the pentose phosphate pathway as well as increased usage of cytidine and N-acetylneuraminate when virulence expression is reduced, which was subsequently supported experimentally. Our results highlight the ability of GENREs to identify novel metabolite signals in higher-order phenotypes like bacterial pathogenesis.