Development of Escherichia coli-based gene expression profiling of sewage sludge leachatesShow others and affiliations
2018 (English)In: Journal of Applied Microbiology, ISSN 1364-5072, E-ISSN 1365-2672, Vol. 125, no 5, p. 1502-1517Article in journal (Refereed) Published
Abstract [en]
AIMS: The impact of municipal waste on pathogenic microorganisms released into the environment is a public health concern. The present study aims to evaluate the effects of sewage sludge and antibiotic contaminants on stress response, virulence and antibiotic resistance in a pathogenic Escherichia coli.
METHODS AND RESULTS: The effects of sewage sludge leachates on uropathogenic E. coli CFT073 were determined by monitoring the expression of 45 genes associated with antibiotic/metal resistance, stress response and virulence using RT-qPCR. The E. coli gene expression was validated using sub-inhibitory concentrations of tetracycline and ciprofloxacin. E. coli exposed to sewage sludge or sewage sludge-fly ash leachates altered the expression of 5 antibiotic and metal resistance, 3 stress response and 2 virulence associated genes. When antibiotics were combined with sludge or sludge-fly ash the antibiotic-associated gene expression was altered.
CONCLUSIONS: E. coli treated with two sludge leachates had distinct gene expression patterns that were altered when the sludge leachates were combined with tetracycline, although to a lesser extent with ciprofloxacin.
SIGNIFICANCE AND IMPACT OF STUDY: The E. coli multigene expression analysis is a potential new tool for assessing the effects of pollutants on pathogenic microbes in environmental waters for improved risk assessment.
Place, publisher, year, edition, pages
Blackwell Publishing, 2018. Vol. 125, no 5, p. 1502-1517
Keywords [en]
Ecotoxicity, Gene expression, Resistance, Sludge, Stress response, Virulence
National Category
Microbiology
Identifiers
URN: urn:nbn:se:oru:diva-67511DOI: 10.1111/jam.14028ISI: 000447408400024PubMedID: 29928772Scopus ID: 2-s2.0-85050482911OAI: oai:DiVA.org:oru-67511DiVA, id: diva2:1224051
Funder
Knowledge Foundation, Dnr 201101772018-06-262018-06-262018-11-01Bibliographically approved