Differing lifestyles of Staphylococcus epidermidis as revealed through Bayesian clustering of multilocus sequence types

Staphylococcus epidermidis is part of the normal bacterial flora of human skin and a leading cause of infections associated with indwelling medical devices. Previous phylogenetic analyses of subgenomic data have been unable to distinguish between S. epidermidis strains with nosocomial or commensal lifestyles, despite the identification of specific phenotypes and accessory genes that may contribute to such lifestyles. To attempt to better define the population structure of this species, the international S. epidermidis multilocus sequence typing database was analyzed with the Bayesian clustering programs STRUCTURE and BAPS. A total of six genetic clusters (GCs) were identified. A local population of S. epidermidis from clinical specimens was classified according to these six GCs, and further characterized for antibiotic susceptibilities, biofilm, and various genetic markers. GC5 was abundant and significantly enriched for isolates that were resistant to four classes of antibiotics, high biofilm production, and positive for the virulence markers icaA, IS256, and sesD/bhp, indicating its potential clinical relevance. In contrast, GC2 was rare and contained the only isolates positive for the putative commensal marker, fdh. GC1 and GC6 were abundant but not significantly associated with any of the examined characteristics, except for sesF/aap and GC6. GC3 was rare and identified as a potential genetic sink that received, but did not donate, core genetic material from other GCs. In conclusion, population genetics analyses were essential for identifying clusters of strains that may differ in their adaptation to nosocomial or commensal lifestyles. These results provide a new, population genetics framework for studying S. epidermidis

Imaging tumour hypoxia with oxygen-enhanced MRI and BOLD MRI.

Hypoxia is known to be a poor prognostic indicator for nearly all solid tumours and also is predictive of treatment failure for radiotherapy, chemotherapy, surgery and targeted therapies. Imaging has potential to identify, spatially map and quantify tumour hypoxia prior to therapy, as well as track changes in hypoxia on treatment. At present no hypoxia imaging methods are available for routine clinical use. Research has largely focused on positron emission tomography (PET)-based techniques, but there is gathering evidence that MRI techniques may provide a practical and more readily translational alternative. In this review we focus on the potential for imaging hypoxia by measuring changes in longitudinal relaxation [R1; termed oxygen-enhanced MRI or tumour oxygenation level dependent (TOLD) MRI] and effective transverse relaxation [R2*; termed blood oxygenation level dependent (BOLD) MRI], induced by inhalation of either 100% oxygen or the radiosensitising hyperoxic gas carbogen. We explain the scientific principles behind oxygen-enhanced MRI and BOLD and discuss significant studies and their limitations. All imaging biomarkers require rigorous validation in order to translate into clinical use and the steps required to further develop oxygen-enhanced MRI and BOLD MRI into decision-making tools are discussed

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq

Do Staphylococcus epidermidis genetic clusters predict isolation sources?

Staphylococcus epidermidis is a ubiquitous colonizer of human skin and a common cause of medical device-associated infections. The extent to which the population genetic structure of S. epidermidis distinguishes commensal from pathogenic isolates is unclear. Previously, Bayesian clustering of 437 multilocus sequence types (STs) in the international database revealed a population structure of six genetic clusters (GCs) that may reflect the species' ecology. Here, we first verified the presence of six GCs, including two (GC3 and GC5) with significant admixture, in an updated database of 578 STs. Next, a single nucleotide polymorphism (SNP) assay was developed that accurately assigned 545 (94%) of 578 STs to GCs. Finally, the hypothesis that GCs could distinguish isolation sources was tested by SNP typing and GC assignment of 154 isolates from hospital patients with bacteremia and those with blood culture contaminants and from nonhospital carriage. GC5 was isolated almost exclusively from hospital sources. GC1 and GC6 were isolated from all sources but were overrepresented in isolates from nonhospital and infection sources, respectively. GC2, GC3, and GC4 were relatively rare in this collection. No association was detected between fdh-positive isolates (GC2 and GC4) and nonhospital sources. Using a machine learning algorithm, GCs predicted hospital and nonhospital sources with 80% accuracy and predicted infection and contaminant sources with 45% accuracy, which was comparable to the results seen with a combination of five genetic markers (icaA, IS256, sesD [bhp], mecA, and arginine catabolic mobile element [ACME]). Thus, analysis of population structure with subgenomic data shows the distinction of hospital and nonhospital sources and the near-inseparability of sources within a hospital

Coronaviridae—Old friends, new enemy!

Coronaviridae is a family of single‐stranded positive enveloped RNA viruses. This article aimed to review the history of these viruses in the last 60 years since their discovery to understand what lessons can be learned from the past. A review of the PubMed database was carried out, describing taxonomy, classification, virology, genetic recombination, host adaptation, and main symptoms related to each type of virus. SARS‐CoV‐2 is responsible for the ongoing global pandemic, and SARS‐CoV and MERS‐CoV were responsible for causing severe respiratory illness and regional epidemics in the past while the four other strains of CoVs (229‐E OC43, NL63, and HKU1) circulate worldwide and normally only cause mild upper respiratory tract infections. Given the enormous diversity of coronavirus viruses in wildlife and their continuous evolution and adaptation to humans, future outbreaks would undoubtedly occur. Restricting or banning all trade in wild animals in wet markets would be a necessary measure to reduce future zoonotic infections

Can people guess what happened to others from their reactions?

Are we able to infer what happened to a person from a brief sample of his/her behaviour? It has been proposed that mentalising skills can be used to retrodict as well as predict behaviour, that is, to determine what mental states of a target have already occurred. The current study aimed to develop a paradigm to explore these processes, which takes into account the intricacies of real-life situations in which reasoning about mental states, as embodied in behaviour, may be utilised. A novel task was devised which involved observing subtle and naturalistic reactions of others in order to determine the event that had previously taken place. Thirty-five participants viewed videos of real individuals reacting to the researcher behaving in one of four possible ways, and were asked to judge which of the four ‘scenarios’ they thought the individual was responding to. Their eye movements were recorded to establish the visual strategies used. Participants were able to deduce successfully from a small sample of behaviour which scenario had previously occurred. Surprisingly, looking at the eye region was associated with poorer identification of the scenarios, and eye movement strategy varied depending on the event experienced by the person in the video. This suggests people flexibly deploy their attention using a retrodictive mindreading process to infer events

The OPAL bugs count survey: exploring the effects of urbanisation and habitat characteristics using citizen science

Citizen science projects can gather datasets with observation counts and spatiotemporal coverage far in excess of what can easily be achieved using only professional scientists. However, there exists a potential trade-off between the number of participants and the quality of data gathered. The Bugs Count citizen science project had thousands of participants because of its few barriers to taking part, allowing participation by anyone in England with access to any area of outdoor space. It was designed to scope for both the effects of variation in local habitat and urbanisation on broad taxonomic groups of invertebrates, and the responses of six target ‘Species Quest’ species (Adalia bipunctata, Ocypus olens, Aglais urticae, Palomena prasina, Limax maximus, and Bombus hypnorum) to urbanisation. Participants were asked to search for invertebrates in three areas: ‘soft ground surfaces’, ‘human-made hard surfaces’, and ‘plants’ for 15 min per search. Participants recorded counts of taxa found and a range of environmental information about the survey area. Data samples were weighted according to identification experience and participant age and analysed using canonical correspondence analysis, and tests of observation homogeneity. Species Quest species showed species-specific relationships with urbanisation, but broad taxonomic groups did not show significant relationships with urbanisation. The latter were instead influenced by habitat type and microhabitat availability. The approach used demonstrates that citizen science projects with few barriers to entry can gather viable datasets for scoping broad trends, providing that the projects are carefully designed and analysed to ensure data quality