Exploring the functional composition of the human microbiome using a hand-curated microbial trait database.

BACKGROUND: Even when microbial communities vary wildly in their taxonomic composition, their functional composition is often surprisingly stable. This suggests that a functional perspective could provide much deeper insight into the principles governing microbiome assembly. Much work to date analyzing the functional composition of microbial communities, however, relies heavily on inference from genomic features. Unfortunately, output from these methods can be hard to interpret and often suffers from relatively high error rates. RESULTS: We built and analyzed a domain-specific microbial trait database from known microbe-trait pairs recorded in the literature to better understand the functional composition of the human microbiome. Using a combination of phylogentically conscious machine learning tools and a network science approach, we were able to link particular traits to areas of the human body, discover traits that determine the range of body areas a microbe can inhabit, and uncover drivers of metabolic breadth. CONCLUSIONS: Domain-specific trait databases are an effective compromise between noisy methods to infer complex traits from genomic data and exhaustive, expensive attempts at database curation from the literature that do not focus on any one subset of taxa. They provide an accurate account of microbial traits and, by limiting the number of taxa considered, are feasible to build within a reasonable time-frame. We present a database specific for the human microbiome, in the hopes that this will prove useful for research into the functional composition of human-associated microbial communities.

Injection of oral medication into the skin confirmed by infrared spectroscopy.

"Skin popping" refers to the practice of injecting drugs, most commonly heroin, subcutaneously or into granulation tissue. Pharmaceutical tablets meant for oral consumption are modified into solutions for injection. Excipients-inactive substances that serve as vehicles for medication-are often not filtered out before injection and result in abscess formation, granulomatous inflammation, and scarring. Common excipients used in the production of pharmaceutical tablets include starch, microcrystalline cellulose, magnesium stearate, silica, and polyvinylpyrrolidone (PVP). Identification of these exogenous materials is valuable in confirming the diagnosis of skin popping, especially when patients may not be forthcoming about their drug use. We present a case of subcutaneous oral medication injection in which PVP and cellulose were identified by Fourier transform infrared spectroscopy. Considering the variable cutaneous manifestations of injection drug abuse, recognition of histopathologic and chemical characteristics of exogenous material from oral medications is helpful for diagnosis and intervention.

Trait-based analysis of the human skin microbiome.

BACKGROUND: The past decade of microbiome research has concentrated on cataloging the diversity of taxa in different environments. The next decade is poised to focus on microbial traits and function. Most existing methods for doing this perform pathway analysis using reference databases. This has both benefits and drawbacks. Function can go undetected if reference databases are coarse-grained or incomplete. Likewise, detection of a pathway does not guarantee expression of the associated function. Finally, function cannot be connected to specific microbial constituents, making it difficult to ascertain the types of organisms exhibiting particular traits-something that is important for understanding microbial success in specific environments. A complementary approach to pathway analysis is to use the wealth of microbial trait information collected over years of lab-based, culture experiments. METHODS: Here, we use journal articles and Bergey's Manual of Systematic Bacteriology to develop a trait-based database for 971 human skin bacterial taxa. We then use this database to examine functional traits that are over/underrepresented among skin taxa. Specifically, we focus on three trait classes-binary, categorical, and quantitative-and compare trait values among skin taxa and microbial taxa more broadly. We compare binary traits using a Chi-square test, categorical traits using randomization trials, and quantitative traits using a nonparametric relative effects test based on global rankings using Tukey contrasts. RESULTS: We find a number of traits that are over/underrepresented within the human skin microbiome. For example, spore formation, acid phosphatase, alkaline phosphatase, pigment production, catalase, and oxidase are all less common among skin taxa. As well, skin bacteria are less likely to be aerobic, favoring, instead, a facultative strategy. They are also less likely to exhibit gliding motility, less likely to be spirillum or rod-shaped, and less likely to grow in chains. Finally, skin bacteria have more difficulty at high pH, prefer warmer temperatures, and are much less resilient to hypotonic conditions. CONCLUSIONS: Our analysis shows how an approach that relies on information from culture experiments can both support findings from pathway analysis, and also generate new insights into the structuring principles of microbial communities.

Gaining awareness: Cultivating clinical reflection in nursing students.

Earlier this year, in an article published in Nurse Education in Practice, a nurse educator in our school of nursing described an activity designed to refresh and inspire undergraduate nursing students who feel fatigued at the end of the day, and/or anxious, pressured, or overwhelmed during their clinical practice experiences (Andersen, 2016). We are some of those students who participated in this activity during some of our therapeutic debriefing and reflective discussions and we would like to respond by describing our experiences.