The evolution of drug resistance is a major health threat. In chronic infections with rapidly mutating pathogens—including HIV, tuberculosis, and hepatitis B and C viruses—multidrug resistance can cause even aggressive combination drug treatment to fail. Oftentimes, individual drugs within a combination do not penetrate equally to all infected regions of the body.

Arctic permafrost soils store large amounts of soil organic carbon (SOC) that could be released into the atmosphere as methane (CH4) in a future warmer climate. How warming affects the complex microbial network decomposing SOC is not understood. The researchers studied CH4 production of Arctic peat soil microbiota in anoxic microcosms over a temperature gradient from 1 to 30 °C, combining metatranscriptomic, metagenomic, and targeted metabolic profiling.

Original Source

Northeast Microbial Database (NEMiD) is a first of its kind digital database on microbial diversity from North East (NE) India, which provides information on culturable microbes (bacteria, fungi and actinomycetes) isolated from soils of the region (Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura, Sikkim and parts of North Bengal) distributed across landscape elements (LSE) spread in various ecosystems. The database is based on the primary data through survey, isolation and
characterization of the microbes during 2008–2012.

Antimicrobials are used in livestock production to maintain health and productivity. These practices contribute to the spread of drug-resistant pathogens in both livestock and humans, posing a significant public health threat. We present the first global map (228 countries) of antibiotic consumption in livestock and conservatively estimate the total consumption in 2010 at 63,151 tons. We project that antimicrobial consumption will rise by 67% by 2030, and nearly double in Brazil, Russia, India, China, and South Africa.

Antibiotic resistance genes (ARGs) in livestock feedlots deserve attention because they are prone to transfer to human pathogens and thus pose threats to human health. In this study, the occurrence of 21 ARGs, including tetracycline (tet)-, sulfonamide (sul)-, plasmid-mediated quinolone (PMQR)- and macrolide-resistance (erm) genes were investigated in feces and adjacent soils from chicken, swine, and cattle feedlots in Northern China.

Antimicrobial resistance threatens the very core of modern medicine and the sustainability of an effective, global public health response to the enduring threat from infectious diseases.

Over a 2-year period, from 2013 to 2014, WHO undertook an initial “country situation analysis” in order to determine the extent to which effective practices and structures to address antimicrobial resistance have been put in place and where gaps remain.

Antibiotic resistance is a growing international problem. This has led to increasing numbers of serious infections that are very difficult, or sometimes impossible to treat. Increasing resistance involves nearly all bacteria that infect people, including very common ones such as Escherichia coli and Staphylococcus aureus. People with infections caused by resistant isolates have much higher death rates as well as increased complications and suffering.

Several mechanisms are developed by the microorganisms to tolerate few high concentrations of heavy metals. One of these mechanisms dependent upon anabolic and catabolic energy of microorganisms is the bioaccumulation of heavy metals. In present work, approximately four varieties of bacteria have been isolated from the ash dyke sample of four thermal power plants of Chhattisgarh, i.e., Bharat Aluminium Company (BALCO), Chhattisgarh State Electricity Board (CSEB), Korba, Thermal Power Cooperation (NTPC), Bilaspur and KSK Akaltara, Chattisgarh.

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012.

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