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>
Project description:Compilation of the targeted metabolomics data present in the associated paper: Metabolic mutations induce antibiotic resistance by pathway-specific bottlenecks.
See "File names association" table in "supplementary files" to link file names with paper figures.
Project description:Using Nanopore sequencing, our study has revealed a close correlation between genomic methylation levels and antibiotic resistance rates in Acinetobacter Baumannii. Specifically, the combined genome-wide DNA methylome and transcriptome analysis revealed the first epigenetic-based antibiotic-resistance mechanism in A. baumannii. Our findings suggest that the precise location of methylation sites along the chromosome could provide new diagnostic markers and drug targets to improve the management of multidrug-resistant A. baumannii infections.
Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humans’ age. Metagenomic DNA from fecal samples of 123 healthy volunteers of four different age groups, i.e. pre-school Children (CH), School Children (SC), High School Students (HSS) and Adults (AD) were used for hybridization. The results showed that 80 different gene types were recovered from the 123 individuals gut microbiota, among which 25 were present in CH, 37 in SC, 58 in HSS and 72 in AD. Further analysis indicated that antibiotic resistance genes in groups of CH, SC and AD can be independently clustered, and those ones in group HSS are more divergent. The detailed analysis of antibiotic resistance genes in human gut is further described in the paper DNA microarray analysis reveals the antibiotic resistance gene diversity in human gut microbiota is age-related submitted to Sentific Reports
Project description:In a given bacterial population, antibiotic treatment kills a large portion of the population, while a small, tolerant subpopulation survives. Tolerant cells disrupt the efficacy of antibiotic treatment and increase the likelihood that a population gains antibiotic resistance. Antibiotic tolerance is different from resistance because tolerant cells cannot grow and replicate in the presence of the antibiotic, but when the antibiotic is removed, they begin to propagate. When a population becomes resistant, the antibiotic becomes ineffective, which is a major health concern. Since antibiotic tolerance often leads to antibiotic resistance, we have taken a systems biology approach to examine how regulatory networks respond to antibiotic stress so that cells can survive and recover after antibiotic treatment. We have compared gene expression with and without ampicillin in E. coli.
Project description:S. aureus is a deadly pathogen due to its abilities to readily develop antibiotic resistance and evade our immune system. Antibiotic resistance in S. aureus is associated with reduced levels of neutrophil recruitment, which is a vital step in triggering an immune response to resolve infection. In this work, we report enhanced antibiotic agents that act as potential dual-function antibiotic-chemoattractants, enabling augmented neutrophil recruitment to S. aureus along with direct killing. Our agents exploit formylated peptides as chemoattractants for neutrophil recruitment, which is combined with the targeted binding of vancomycin to bacteria that generates a chemoattractant gradient for neutrophil recruitment. The combination of in vitro assays, cellular assays, infection-on-a-chip and in vivo mouse models, determined that these antibiotic-chemoattractants improve the recruitment, engulfment and killing of S. aureus by neutrophils. Furthermore, optimizing the fPep sequence can play an important role in the enhancement of neutrophil activity through differential activation of formyl peptide receptors. This offers an alternate approach in antibiotic development to overcome the threat of antibiotic resistance in the clinic.
Project description:Antimicrobial resistance (AMR) is an increasing challenge for therapy and management of bacterial infections. Currently, antimicrobial resistance detection relies on phenotypic assays, which are performed independently of species identification. On the contrary, phenotypic prediction from molecular data using genomics is gaining interest in clinical microbiology and might become a serious alternative in the future. Although, in general protein analysis should be superior to genomics for phenotypic prediction, no untargeted proteomics workflow specifically related to AMR detection has been proposed so far. In this study, we present a universal proteomics workflow to detect the bacterial species and antimicrobial resistance related proteins in the absence of secondary antibiotic cultivation in less than 4 h from a primary culture. The method was validated using a sample cohort of 7 bacterial species and 11 AMR determinants represented by 13 protein isoforms which resulted in a sensitivity of 92 % (100 % with vancomycin inference) and a specificity of 100 % with respect to AMR determinants. This proof-of concept study demonstrates the high potential of untargeted proteomics for clinical microbiology.
Project description:Characterization of the putative genetic determinants of the VBNC state in a known spore-forming Gram-positive organism Bacillus subtilis 168. The VBNC state was induced under osmotic stress and aminoglycoside treatment. The transcriptome landscape of VBNC cells was compared to the viable, antibiotic sensitive B. subtilis cells and to the viable cells with no antibiotic treatment.