Evaluation of culture conditions for sewage-based surveillance of antibiotic resistance in Klebsiella pneumoniae.

BACKGROUND: Recent studies have shown promise in predicting clinical antibiotic resistance rates from sewage data. Few have focused on Klebsiella pneumoniae, despite its virulence and importance as carrier of antibiotic resistance. Several media have been suggested for the isolation of K. pneumoniae from complex samples. However, comprehensive evaluations of culture protocols for isolation of K. pneumoniae from sewage are lacking. METHODS: Here, influent samples from a major Swedish sewage treatment plant were used to evaluate ten culture conditions in parallel: cultivation on Brilliant green containing Inositol-Nitrate-Deoxycholate agar (BIND), Bruce agar, Klebsiella ChromoSelect Selective agar®, MacConkey-Inositol-Carbenicillin, or Simmons Citrate Agar with Inositol (SCAI) incubated at either 37°C or 42°C for 44 h. The culture conditions were compared based on colony counts of presumed K. pneumoniae and identification precision assessed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. RESULTS: The sensitivity was lowest for BIND, whereas it was similar for the other media irrespective of incubation temperature. For four media, a better precision was observed after incubation at 42°C compared to 37°C, to a large extent explained by a lower frequency of captured Klebsiella oxytoca. SCAI incubated at 42°C showed the highest precision (84.4%). By combining this protocol with subsequent antibiotic resistance screening of collected isolates, low resistance rates in sewage K. pneumoniae were revealed, potentially reflecting the local resistance landscape. CONCLUSION: When combined with downstream analyses, SCAI incubated at 42°C could be a valuable culture protocol for sewage-based studies on various aspects of K. pneumoniae epidemiology including antibiotic resistance prevalence.

Population-level surveillance of antibiotic resistance in Escherichia coli through sewage analysis.

IntroductionThe occurrence of antibiotic resistance in faecal bacteria in sewage is likely to reflect the current local clinical resistance situation.AimThis observational study investigated the relationship between Escherichia coli resistance rates in sewage and clinical samples representing the same human populations.MethodsE. coli were isolated from eight hospital (n = 721 isolates) and six municipal (n = 531 isolates) sewage samples, over 1 year in Gothenburg, Sweden. An inexpensive broth screening method was validated against disk diffusion and applied to determine resistance against 11 antibiotics in sewage isolates. Resistance data on E. coli isolated from clinical samples from corresponding local hospital and primary care patients were collected during the same year and compared with those of the sewage isolates by linear regression.ResultsE. coli resistance rates derived from hospital sewage and hospital patients strongly correlated (r2 = 0.95 for urine and 0.89 for blood samples), as did resistance rates in E. coli from municipal sewage and primary care urine samples (r2 = 0.82). Resistance rates in hospital sewage isolates were close to those in hospital clinical isolates while resistance rates in municipal sewage isolates were about half of those measured in primary care isolates. Resistance rates in municipal sewage isolates were more stable between sampling occasions than those from hospital sewage.ConclusionOur findings provide support for development of a low-cost, sewage-based surveillance system for antibiotic resistance in E. coli, which could complement current monitoring systems and provide clinically relevant antibiotic resistance data for countries and regions where surveillance is lacking.

METAXA2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data.

The ribosomal rRNA genes are widely used as genetic markers for taxonomic identification of microbes. Particularly the small subunit (SSU; 16S/18S) rRNA gene is frequently used for species- or genus-level identification, but also the large subunit (LSU; 23S/28S) rRNA gene is employed in taxonomic assignment. The METAXA software tool is a popular utility for extracting partial rRNA sequences from large sequencing data sets and assigning them to an archaeal, bacterial, nuclear eukaryote, mitochondrial or chloroplast origin. This study describes a comprehensive update to METAXA - METAXA2 - that extends the capabilities of the tool, introducing support for the LSU rRNA gene, a greatly improved classifier allowing classification down to genus or species level, as well as enhanced support for short-read (100 bp) and paired-end sequences, among other changes. The performance of METAXA2 was compared to other commonly used taxonomic classifiers, showing that METAXA2 often outperforms previous methods in terms of making correct predictions while maintaining a low misclassification rate. METAXA2 is freely available from http://microbiology.se/software/metaxa2/.