Machine Learning Leveraging Genomes from Metagenomes Identifies Influential Antibiotic Resistance Genes in the Infant Gut Microbiome.

Antibiotic resistance in pathogens is extensively studied, and yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leveraged genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We found that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly, Clostridium difficile strains harboring this gene are at higher abundance in formula-fed infants than C. difficile strains lacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have higher replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism's direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data to five principal components classified by boosted decision trees. Among the genes involved in predicting whether an organism increased in relative abundance after treatment are those that encode subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics treatment and predict how organisms in the gut microbiome will respond to antibiotic administration. IMPORTANCE The process of reconstructing genomes from environmental sequence data (genome-resolved metagenomics) allows unique insight into microbial systems. We apply this technique to investigate how the antibiotic resistance genes of bacteria affect their ability to flourish in the gut under various conditions. Our analysis reveals that strain-level selection in formula-fed infants drives enrichment of beta-lactamase genes in the gut resistome. Using genomes from metagenomes, we built a machine learning model to predict how organisms in the gut microbial community respond to perturbation by antibiotics. This may eventually have clinical applications.

Genome-resolved metagenomics of a bioremediation system for degradation of thiocyanate in mine water containing suspended solid tailings.

Thiocyanate (SCN- ) is a toxic compound that forms when cyanide (CN- ), used to recover gold, reacts with sulfur species. SCN- -degrading microbial communities have been studied, using bioreactors fed synthetic wastewater. The inclusion of suspended solids in the form of mineral tailings, during the development of the acclimatized microbial consortium, led to the selection of an active planktonic microbial community. Preliminary analysis of the community composition revealed reduced microbial diversity relative to the laboratory-based reactors operated without suspended solids. Despite minor upsets during the acclimation period, the SCN- degradation performance was largely unchanged under stable operating conditions. Here, we characterized the microbial community in the SCN- degrading bioreactor that included solid particulate tailings and determined how it differed from the biofilm-based communities in solids-free reactor systems inoculated from the same source. Genome-based analysis revealed that the presence of solids decreased microbial diversity, selected for different strains, suppressed growth of thiobacilli inferred to be primarily responsible for SCN- degradation, and promoted growth of Trupera, an organism not detected in the reactors without solids. In the solids reactor community, heterotrophy and aerobic respiration represent the dominant metabolisms. Many organisms have genes for denitrification and sulfur oxidation, but only one Thiobacillus sp. in the solids reactor has SCN- degradation genes. The presence of the solids prevented floc and biofilm formation, leading to the observed reduced microbial diversity. Collectively the presence of the solids and lack of biofilm community may result in a process with reduced resilience to process perturbations, including fluctuations in the influent composition and pH. The results from this investigation have provided novel insights into the community composition of this industrially relevant community, giving potential for improved process control and operation through ongoing process monitoring.

Influence of Bioaerosol Source Location and Ceiling Fan Direction on Eggcrate Upper-room Ultraviolet Germicidal Irradiation.

BACKGROUND: Eggcrate upper-room ultraviolet germicidal irradiation (UVGI), an engineering control method for reducing the airborne transmission of infectious diseases, was recently developed as an alternative to conventional upper-room UVGI using conventional louvered fixtures. A UV screen, which is composed of open-cell eggcrate panels supported in a frame designed for a conventional suspended ceiling, was used to minimize UV radiation in the lower room. A ceiling fan, which was blowing upward directly above the microbiological source, provided vertical air exchange between the upper and lower room. This system has been shown to be significantly more effective than conventional upper-room UVGI. STUDY DESIGN: In the present study, the microbiological source location and the airflow direction due to the ceiling fan were varied in order to evaluate their impact on germicidal efficacy. RESULTS: The test results clearly showed that placing an aerosol source directly underneath an upward blowing ceiling fan produces the maximum efficacy. CONCLUSIONS: The likely explanation for this outcome is that the fan sucks the microorganisms emitted by the source into the UV beam before being mixed with the air in the room. This is somewhat analogous to local exhaust ventilation in which the contaminant is removed prior to being mixed with the air in the room. Thus, when possible, the ceiling fan should be blowing upward and directly above the source. However, for experimental testing, the source location should be varied in order to access the range of germicidal efficacies that can be expected.