Project description:Cationic antimicrobial peptides (CAPs) are promising novel alternatives to conventional antibacterial agents, but the overlap in resistance mechanisms between small-molecule antibiotics and CAPs is unknown. Does evolution of antibiotic resistance decrease (cross-resistance) or increase (collateral sensitivity) susceptibility to CAPs? We systematically addressed this issue by studying the susceptibilities of a comprehensive set of antibiotic resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic resistant bacteria frequently showed collateral sensitivity to CAPs, while cross-resistance was relatively rare. We identified clinically relevant multidrug resistance mutations that simultaneously elevate susceptibility to certain CAPs. Transcriptome and chemogenomic analysis revealed that such mutations frequently alter the lipopolysaccharide composition of the outer cell membrane and thereby increase the killing efficiency of membrane-interacting antimicrobial peptides. Furthermore, we identified CAP-antibiotic combinations that rescue the activity of existing antibiotics and slow down the evolution of resistance to antibiotics. Our work provides a proof of principle for the development of peptide based antibiotic adjuvants that enhance antibiotic action and block evolution of resistance.
Project description:The increased urban pressures are often associated with specialization of microbial communities. Microbial communities being a critical player in the geochemical processes, makes it important to identify key environmental parameters that influence the community structure and its function.In this proect we study the influence of land use type and environmental parameters on the structure and function of microbial communities. The present study was conducted in an urban catchment, where the metal and pollutants levels are under allowable limits. The overall goal of this study is to understand the role of engineered physicochemical environment on the structure and function of microbial communities in urban storm-water canals. Water and sediment samples were collected after a rain event from Sungei Ulu Pandan watershed of >25km2, which has two major land use types: Residential and industrial. Samples were analyzed for physicochemical variables and microbial community structure and composition. Functional gene abundance was determined using GeoChip.
Project description:The increased urban pressures are often associated with specialization of microbial communities. Microbial communities being a critical player in the geochemical processes, makes it important to identify key environmental parameters that influence the community structure and its function.In this proect we study the influence of land use type and environmental parameters on the structure and function of microbial communities. The present study was conducted in an urban catchment, where the metal and pollutants levels are under allowable limits. The overall goal of this study is to understand the role of engineered physicochemical environment on the structure and function of microbial communities in urban storm-water canals. Microbial community structure was determined using PhyoChio (G3) Water and sediment samples were collected after a rain event from Sungei Ulu Pandan watershed of >25km2, which has two major land use types: Residential and industrial. Samples were analyzed for physicochemical variables and microbial community structure and composition. Microbial community structure was determined using PhyoChio (G3)
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>
| phs001260 | dbGaP
Project description:Antimicrobial resistance genes of Enterobacteriaceae
Project description:The increased urban pressures are often associated with specialization of microbial communities. Microbial communities being a critical player in the geochemical processes, makes it important to identify key environmental parameters that influence the community structure and its function.In this proect we study the influence of land use type and environmental parameters on the structure and function of microbial communities. The present study was conducted in an urban catchment, where the metal and pollutants levels are under allowable limits. The overall goal of this study is to understand the role of engineered physicochemical environment on the structure and function of microbial communities in urban storm-water canals.
Project description:Methods for rapid and reliable microbial identification are essential in modern healthcare. The ability to detect and correctly identify pathogenic species and their resistance phenotype is necessary for accurate diagnosis and efficient treatment of infectious diseases. Bottom-up tandem mass spectrometry (MS) proteomics enables rapid characterization of large parts of the expressed genes of microorganisms. The generated data is however highly fragmented, making down-stream analyses complex. Here we present TCUP, a new computational method for typing and characterizing bacteria using proteomics data from bottom-up tandem MS. TCUP compares the generated protein sequence data to reference databases and automatically finds peptides suitable for characterization of taxonomic composition and identification of expressed antimicrobial resistance genes. TCUP was evaluated using four clinically relevant bacterial species (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Streptococcus pneumoniae), using both simulated data generated by in silico peptide digestion and experimental proteomics data generated by liquid chromatography-tandem mass spectrometry (MS/MS). The results showed that TCUP performs correct peptide classifications at rates between 90.3% and 98.5% at the species level. The method was also able to accurately estimate the relative abundances of individual species in mixed cultures. Furthermore, TCUP could identify expressed beta-lactamases in an ESBL-producing E. coli strain, even when the strain was cultivated in the absence of antibiotics on non-selective media. Finally, TCUP is computationally efficient, easy to integrate in existing bioinformatics workflows and freely available under an open source license for both Windows and Linux environments.