<i>Propionibacterium acnes: </i>disease-causing agent or common contaminant? Detection in diverse patient samples by next generation sequencing

Propionibacterium acnes is the most abundant bacterium on human skin, particularly in sebaceous areas. P. acnes is suggested to be an opportunistic pathogen involved in the development of diverse medical conditions but is also a proven contaminant of human clinical samples and surgical wounds. Its significance as a pathogen is consequently a matter of debate. In the present study, we investigated the presence of P. acnes DNA in 250 next-generation sequencing data sets generated from 180 samples of 20 different sample types, mostly of cancerous origin. The samples were subjected to either microbial enrichment, involving nuclease treatment to reduce the amount of host nucleic acids, or shotgun sequencing. We detected high proportions of P. acnes DNA in enriched samples, particularly skin tissue-derived and other tissue samples, with the levels being higher in enriched samples than in shotgun-sequenced samples. P. acnes reads were detected in most samples analyzed, though the proportions in most shotgun-sequenced samples were low. Our results show that P. acnes can be detected in practically all sample types when molecular methods, such as next-generation sequencing, are employed. The possibility of contamination from the patient or other sources, including laboratory reagents or environment, should therefore always be considered carefully when P. acnes is detected in clinical samples. We advocate that detection of P. acnes always be accompanied by experiments validating the association between this bacterium and any clinical condition

“The people who are out of ‘right’ English”: Japanese university students' social evaluations of English language diversity and the internationalisation of Japanese higher education

Previous research indicates that evaluations of speech forms reflect stereotypes of, and attitudes towards, the perceived group(s) of speakers of the language/variety under consideration. This study, employing both implicit and explicit attitude measures, investigates 158 Japanese university students' perceptions of forms of UK, US, Japanese, Chinese, Thai and Indian English speech. The results show a general convergence between students' explicit and implicit attitudes, for instance, regarding US and UK English as the most correct, and solidarity with Japanese speakers of English. The findings are discussed in relation to intergroup relations between the traditional Japanese cohort and specific groups of overseas students, particularly in light of recent internationalisation policies adopted by many Japanese universities, and the resultant increase in international students from South and East Asia

Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers

Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified

Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022

Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control