Molecular Responses During Bacterial Filamentation Induced by Antibiotics
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ABSTRACT:
ORGANISM(S): Escherichia Coli
SUBMITTER: 
Liang Qiao
PROVIDER: PXD039235 | iProX | Wed Jan 04 00:00:00 GMT 2023
REPOSITORIES: iProX
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Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>
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Project description:Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild-type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.
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Project description:Coordinated protein-coding sequence transcriptional responses of Staphylococcus aureus to antimicrobial exposure are well described but little is known of the role of bacterial non-coding, small RNAs (sRNAs) in these responses. Here we used RNAseq to investigate the sRNA response of the epidemic multiresistant hospital ST239 S. Aureus strain JKD6009 and its vancomycin-intermediate clinical derivative, JKD6008, after exposure to four antibiotics representing the major classes of antimicrobials used to treat methicillin-resistant S. Aureus infections. These agents included vancomycin, linezolid, ceftobiprole, and tigecycline. We identified 410 potential sRNAs (sRNAs) and then compared global sRNA and mRNA expression profiles at 2 and 6 hours, without antibiotic exposure, and after exposure to 0.5 x MIC for each antibiotic, for both JKD6009 (VSSA), and JKD6008 (VISA). Two strains were used (JKD6009, vancomycin-susceptible S. Aureus; JKD6008, in vivo derived vancomycin-intermediate S. Aureus). The complete JKD6008 genome seqeuce was used as the reference. Two time points, 2 hours and 6 hours after culture in Mueller Hinton broth. Strains were exposed to no antibiotic, or 0.5 x MIC for 10 mins for the following antibiotics; vancomycin, linezolid, ceftobiprole, tigecycline. RNA isolation procedures enriched for mRNA or sRNA. The 40 cDNA libraries were sequenced using a whole flowcell (8 lanes) in an Illumina genome analyzer GAII for 36 cycles. Data was analyzed using the BioConductor package limma, and by applying non-negative matrix factorization to determine the impact of antibiotic exposure on the sRNA and mRNA transcriptional profiles.
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