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Reconstructing a metabolic model from the genome sequence of an organism is a useful but arduous approach for predicting phenotypes. Henry et al . describe a resource that automates most of this process and apply it to create >100 new metabolic models of microbes. Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Yet efforts to develop new models are failing to keep pace with genome sequencing. To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models. The Model SEED integrates existing methods and introduces techniques to automate nearly every step of this process, taking ∼48 h to reconstruct a metabolic model from an assembled genome sequence. We apply this resource to generate 130 genome-scale metabolic models representing a taxonomically diverse set of bacteria. Twenty-two of the models were validated against available gene essentiality and Biolog data, with the average model accuracy determined to be 66% before optimization and 87% after optimization.

Background To develop and evaluate a strategy for reducing the prevalence and impact of waterborne disease, a water quality intervention was developed for Fiji by Give Clean Water, Inc. in partnership with the Fiji Ministry of Health. Residents were provided and trained on how to use a Sawyer® PointONE™ filter, while also being taught proper handwashing techniques. At the time of the filter installation, all households were surveyed inquiring about the prior 2- to 4-week period. Households were measured a second time between 19 and 225 days later (mean = 66 days). Results To date, five economic and health outcomes have been tracked on 503 households to evaluate the efficacy of the intervention. When comparing baseline to follow-up among the 503 households, the 2-week diarrhea prevalence decreased in households from 17.5% at baseline to 1.8% at follow-up. Also, the 2-week prevalence of severe diarrhea decreased per household from 9.7% at baseline to 0.6% at follow-up. Finally, monthly diarrhea-related medical costs reduced by an average of Fijian (FJ) $3.54 per person, and monthly water expenses reduced by FJ $0.63 per person. All estimated values are obtained from general linear and logistic mixed-effect models, which adjusted for location, season, time to follow-up, household size, water source, and respondent changing. Changes in economic and health outcomes from installation to follow-up were statistically significant ( p  < 0.05) in all cases, in both unadjusted and adjusted models. Conclusions The installation of water filters shows promise for the reduction of diarrhea prevalence in Fiji, as well as the reduction of diarrhea-related medical costs and water expenses. Future work entails evaluation in other countries and contexts, long-term health monitoring, and comparison to alternative water quality interventions.

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs , and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%–90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943–0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including “hypothetical proteins” was accurately predicted (F1 = 0.902 [0.898–0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876–0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. Having the ability to predict the protein-encoding gene content of a genome is important for assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance and other virulence genes. In this study, we built a set of binary classifiers for predicting the presence or absence of variable genes occurring in 10%–90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer. This study offers a strategy for predicting gene content using limited input sequence data.

Bacteriophages isolated on Mycobacterium smegmatis mc(2)155 represent many distinct genomes sharing little or no DNA sequence similarity. The genomes are architecturally mosaic and are replete with genes of unknown function. A new group of genomes sharing substantial nucleotide sequences constitute Cluster J. The six mycobacteriophages forming Cluster J are morphologically members of the Siphoviridae, but have unusually long genomes ranging from 106.3 to 117 kbp. Reconstruction of the capsid by cryo-electron microscopy of mycobacteriophage BAKA reveals an icosahedral structure with a triangulation number of 13. All six phages are temperate and homoimmune, and prophage establishment involves integration into a tRNA-Leu gene not previously identified as a mycobacterial attB site for phage integration. The Cluster J genomes provide two examples of intron splicing within the virion structural genes, one in a major capsid subunit gene, and one in a tail gene. These genomes also contain numerous free-standing HNH homing endonuclease, and comparative analysis reveals how these could contribute to genome mosaicism. The unusual Cluster J genomes provide new insights into phage genome architecture, gene function, capsid structure, gene mobility, intron splicing, and evolution.

Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

The genome of the eukaryotic protist Giardia lamblia, an important human intestinal parasite, is compact in structure and content, contains few introns or mitochondrial relics, and has simplified machinery for DNA replication, transcription, RNA processing, and most metabolic pathways. Protein kinases comprise the single largest protein class and reflect Giardia's requirement for a complex signal transduction network for coordinating differentiation. Lateral gene transfer from bacterial and archaeal donors has shaped Giardia's genome, and previously unknown gene families, for example, cysteine-rich structural proteins, have been discovered. Unexpectedly, the genome shows little evidence of heterozygosity, supporting recent speculations that this organism is sexual. This genome sequence will not only be valuable for investigating the evolution of eukaryotes, but will also be applied to the search for new therapeutics for this parasite.

Background Genome scale annotation of regulatory interactions and reconstruction of regulatory networks are the crucial problems in bacterial genomics. The Lactobacillales order of bacteria collates various microorganisms having a large economic impact, including both human and animal pathogens and strains used in the food industry. Nonetheless, no systematic genome-wide analysis of transcriptional regulation has been previously made for this taxonomic group. Results A comparative genomics approach was used for reconstruction of transcriptional regulatory networks in 30 selected genomes of lactic acid bacteria. The inferred networks comprise regulons for 102 orthologous transcription factors (TFs), including 47 novel regulons for previously uncharacterized TFs. Numerous differences between regulatory networks of the Streptococcaceae and Lactobacillaceae groups were described on several levels. The two groups are characterized by substantially different sets of TFs encoded in their genomes. Content of the inferred regulons and structure of their cognate TF binding motifs differ for many orthologous TFs between the two groups. Multiple cases of non-orthologous displacements of TFs that control specific metabolic pathways were reported. Conclusions The reconstructed regulatory networks substantially expand the existing knowledge of transcriptional regulation in lactic acid bacteria. In each of 30 studied genomes the obtained regulatory network contains on average 36 TFs and 250 target genes that are mostly involved in carbohydrate metabolism, stress response, metal homeostasis and amino acids biosynthesis. The inferred networks can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. All reconstructed regulons are captured within the Streptococcaceae and Lactobacillaceae collections in the RegPrecise database ( http://regprecise.lbl.gov ).

Metal and metalloid contamination in drinking water sources is a global concern, particularly in developing countries. This study used hollow membrane water filters and metal-capturing polyurethane foams to sample 71 drinking water sources in 22 different countries. Field sampling was performed with sampling kits prepared in the lab at Hope College in Holland, MI, USA. Filters and foams were sent back to the lab after sampling, and subsequent analysis of flushates and rinsates allowed the estimation of suspended solids and metal and other analayte concentrations in source waters. Estimated particulate concentrations were 0–92 mg/L, and consisted of quartz, feldspar, and clay, with some samples containing metal oxides or sulfide phases. As and Cu were the only analytes which occurred above the World Health Organization (WHO) guidelines of 10 μg/L and 2000 μg/L, respectively, with As exceeding the guideline in 45% of the sources and Cu in 3%. Except for one value of ~ 285 μg/L, As concentrations were 45–200 μg/L (river), 65–179 μg/L (well), and 112–178 μg/L (tap). Other metals (Ce, Fe, Mg, Mn, Zn) with no WHO guideline were also detected, with Mn the most common. This study demonstrated that filters and foams can be used for reconnaissance characterization of untreated drinking water. However, estimated metal and other analyte concentrations could only be reported as minimum values due to potential incomplete retrieval of foam-bound analytes. A qualitative reporting methodology was used to report analytes as “present” if the concentration was below the WHO guideline, and “present-recommend retesting” if the concentration was quantifiable and above the WHO guideline.

ABSTRACT The Lilleengen type (LT) collection of Salmonella enterica serovar Typhimurium strains has served the scientific community as a group of model organisms for basic genetic and biochemical pathway research. Here, we report the whole-genome shotgun sequences of Salmonella enterica serovar Typhimurium strains LT1, LT18, LT19, LT20, LT21, and LT22.

Background Lack of sustainable access to clean drinking water continues to be an issue of paramount global importance, leading to millions of preventable deaths annually. Best practices for providing sustainable access to clean drinking water, however, remain unclear. Widespread installation of low-cost, in-home, point of use water filtration systems is a promising strategy. Methods We conducted a prospective, randomized, controlled trial whereby 16 villages were selected and randomly assigned to one of four treatment arms based on the installation location of Sawyer® PointONE™ filters (filter in both home and school; filter in home only; filter in school only; control group). Water samples and self-reported information on diarrhea were collected at multiple times throughout the study. Results Self-reported household prevalence of diarrhea decreased from 25.6 to 9.76% from installation to follow-up (at least 7 days, and up to 200 days post-filter installation). These declines were also observed in diarrhea with economic or educational consequences (diarrhea which led to medical treatment and/or missing school or work) with baseline prevalence of 9.64% declining to 1.57%. Decreases in diarrhea prevalence were observed across age groups. There was no evidence of a loss of efficacy of filters up to 200 days post-filter installation. Installation of filters in schools was not associated with decreases in diarrhea prevalence in school-aged children or family members. Unfiltered water samples both at schools and homes contained potential waterborne bacterial pathogens, dissolved heavy metals and metals associated with particulates. All dissolved metals were detected at levels below World Health Organization action guidelines. Conclusions This controlled trial provides strong evidence of the effectiveness of point-of-use, hollow fiber membrane filters at reducing diarrhea from bacterial sources up to 200 days post-installation when installed in homes. No statistically significant reduction in diarrhea was found when filters were installed in schools. Further research is needed in order to explore filter efficacy and utilization after 200 days post-installation. Trial registration ClinicalTrials.gov, NCT03972618 . Registered 3 June 2019—retrospectively registered.