The proteolytic system of lactic acid bacteria revisited: a genomic comparison

Contains fulltext : 87750.pdf (publisher's version ) (Open Access)BACKGROUND: Lactic acid bacteria (LAB) are a group of gram-positive, lactic acid producing Firmicutes. They have been extensively used in food fermentations, including the production of various dairy products. The proteolytic system of LAB converts proteins to peptides and then to amino acids, which is essential for bacterial growth and also contributes significantly to flavor compounds as end-products. Recent developments in high-throughput genome sequencing and comparative genomics hybridization arrays provide us with opportunities to explore the diversity of the proteolytic system in various LAB strains. RESULTS: We performed a genome-wide comparative genomics analysis of proteolytic system components, including cell-wall bound proteinase, peptide transporters and peptidases, in 22 sequenced LAB strains. The peptidase families PepP/PepQ/PepM, PepD and PepI/PepR/PepL are described as examples of our in silico approach to refine the distinction of subfamilies with different enzymatic activities. Comparison of protein 3D structures of proline peptidases PepI/PepR/PepL and esterase A allowed identification of a conserved core structure, which was then used to improve phylogenetic analysis and functional annotation within this protein superfamily.The diversity of proteolytic system components in 39 Lactococcus lactis strains was explored using pangenome comparative genome hybridization analysis. Variations were observed in the proteinase PrtP and its maturation protein PrtM, in one of the Opp transport systems and in several peptidases between strains from different Lactococcus subspecies or from different origin. CONCLUSIONS: The improved functional annotation of the proteolytic system components provides an excellent framework for future experimental validations of predicted enzymatic activities. The genome sequence data can be coupled to other "omics" data e.g. transcriptomics and metabolomics for prediction of proteolytic and flavor-forming potential of LAB strains. Such an integrated approach can be used to tune the strain selection process in food fermentations

PhenoLink - a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains

Contains fulltext : 109042.pdf (publisher's version ) (Open Access)BACKGROUND: Linking phenotypes to high-throughput molecular biology information generated by ~omics technologies allows revealing cellular mechanisms underlying an organism's phenotype. ~Omics datasets are often very large and noisy with many features (e.g., genes, metabolite abundances). Thus, associating phenotypes to ~omics data requires an approach that is robust to noise and can handle large and diverse data sets. RESULTS: We developed a web-tool PhenoLink (http://bamics2.cmbi.ru.nl/websoftware/phenolink/) that links phenotype to ~omics data sets using well-established as well new techniques. PhenoLink imputes missing values and preprocesses input data (i) to decrease inherent noise in the data and (ii) to counterbalance pitfalls of the Random Forest algorithm, on which feature (e.g., gene) selection is based. Preprocessed data is used in feature (e.g., gene) selection to identify relations to phenotypes. We applied PhenoLink to identify gene-phenotype relations based on the presence/absence of 2847 genes in 42 Lactobacillus plantarum strains and phenotypic measurements of these strains in several experimental conditions, including growth on sugars and nitrogen-dioxide production. Genes were ranked based on their importance (predictive value) to correctly predict the phenotype of a given strain. In addition to known gene to phenotype relations we also found novel relations. CONCLUSIONS: PhenoLink is an easily accessible web-tool to facilitate identifying relations from large and often noisy phenotype and ~omics datasets. Visualization of links to phenotypes offered in PhenoLink allows prioritizing links, finding relations between features, finding relations between phenotypes, and identifying outliers in phenotype data. PhenoLink can be used to uncover phenotype links to a multitude of ~omics data, e.g., gene presence/absence (determined by e.g.: CGH or next-generation sequencing), gene expression (determined by e.g.: microarrays or RNA-seq), or metabolite abundance (determined by e.g.: GC-MS)

Enterococcus faecium genome dynamics during long-term asymptomatic patient gut colonization

Enterococcus faecium is a gut commensal of humans and animals. In addition, it has recently emerged as an important nosocomial pathogen through the acquisition of genetic elements that confer resistance to antibiotics and virulence. We performed a whole-genome sequencing-based study on 96 multidrug-resistant E. faecium strains that asymptomatically colonized five patients with the aim of describing the genome dynamics of this species. The patients were hospitalized on multiple occasions and isolates were collected over periods ranging from 15 months to 6.5 years. Ninety-five of the sequenced isolates belonged to E. faecium clade A1, which was previously determined to be responsible for the vast majority of clinical infections. The clade A1 strains clustered into six clonal groups of highly similar isolates, three of which consisted entirely of isolates from a single patient. We also found evidence of concurrent colonization of patients by multiple distinct lineages and transfer of strains between patients during hospitalization. We estimated the evolutionary rate of two clonal groups that each colonized single patients at 12.6 and 25.2 single-nucleotide polymorphisms (SNPs)/genome/year. A detailed analysis of the accessory genome of one of the clonal groups revealed considerable variation due to gene gain and loss events, including the chromosomal acquisition of a 37 kbp prophage and the loss of an element containing carbohydrate metabolism-related genes. We determined the presence and location of 12 different insertion sequence (IS) elements, with ISEfa5 showing a unique pattern of location in 24 of the 25 isolates, suggesting widespread ISEfa5 excision and insertion into the genome during gut colonization. Our findings show that the E. faecium genome is highly dynamic during asymptomatic colonization of the human gut. We observed considerable genomic flexibility due to frequent horizontal gene transfer and recombination, which can contribute to the generation of genetic diversity within the species and, ultimately, can contribute to its success as a nosocomial pathogen

REVISITING ANNA MOSCOWITZ\u27S KROSS\u27S CRITIQUE OF NEW YORK CITY\u27S WOMEN\u27S COURT: THE CONTINUED PROBLEM OF SOLVING THE PROBLEM OF PROSTITUTION WITH SPECIALIZED CRIMINAL COURTS

This article explores New York City\u27s non-traditional, judicially based response to prostitution. This article first recounts the history of New York City’s Women’s Court. It then examines the work of the Midtown Community Court, the “problem-solving court” established in 1993 to address criminal issues, like prostitution, in Midtown Manhattan. It also discusses the renewed concerns about sex work in New York and describe the movement, propelled by modern reformers, to address prostitution through specialty courts. It then contrasts the shared features and attributes of the Women’s Court and Midtown Court models. Finally, the article urges modern reformers to step back from the problem-solving court movement and their call for the creation of more such specialized criminal courts

Computational approaches for network-based integrative multi-omics analysis

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell. Here we review network-based multi-omics/multi-modal integrative analytical approaches. We classify these approaches according to the type of omics data supported, the methods and/or algorithms implemented, their node and/or edge weighting components, and their ability to identify key nodes and subnetworks. We show how these approaches can be used to identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers of physiological and pathological mechanisms. We provide insight into the most appropriate methods and tools for research questions as showcased around the aetiology and treatment of COVID-19 that can be informed by multi-omics data integration. We conclude with an overview of challenges associated with multi-omics network-based analysis, such as reproducibility, heterogeneity, (biological) interpretability of the results, and we highlight some future directions for network-based integration

Enterococcus faecium genome dynamics during long-term asymptomatic patient gut colonization

Enterococcus faecium is a gut commensal of humans and animals. In addition, it has recently emerged as an important nosocomial pathogen through the acquisition of genetic elements that confer resistance to antibiotics and virulence. We performed a whole-genome sequencing-based study on 96 multidrug-resistant E. faecium strains that asymptomatically colonized five patients with the aim of describing the genome dynamics of this species. The patients were hospitalized on multiple occasions and isolates were collected over periods ranging from 15 months to 6.5 years. Ninety-five of the sequenced isolates belonged to E. faecium clade A1, which was previously determined to be responsible for the vast majority of clinical infections. The clade A1 strains clustered into six clonal groups of highly similar isolates, three of which consisted entirely of isolates from a single patient. We also found evidence of concurrent colonization of patients by multiple distinct lineages and transfer of strains between patients during hospitalization. We estimated the evolutionary rate of two clonal groups that each colonized single patients at 12.6 and 25.2 single-nucleotide polymorphisms (SNPs)/genome/year. A detailed analysis of the accessory genome of one of the clonal groups revealed considerable variation due to gene gain and loss events, including the chromosomal acquisition of a 37 kbp prophage and the loss of an element containing carbohydrate metabolism-related genes. We determined the presence and location of 12 different insertion sequence (IS) elements, with ISEfa5 showing a unique pattern of location in 24 of the 25 isolates, suggesting widespread ISEfa5 excision and insertion into the genome during gut colonization. Our findings show that the E. faecium genome is highly dynamic during asymptomatic colonization of the human gut. We observed considerable genomic flexibility due to frequent horizontal gene transfer and recombination, which can contribute to the generation of genetic diversity within the species and, ultimately, can contribute to its success as a nosocomial pathogen

Limited influence of hospital wastewater on the microbiome and resistome of wastewater in a community sewerage system

Effluents from wastewater treatment plants (WWTPs) have been proposed to act as point sources of antibiotic-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs) in the environment. Hospital sewage may contribute to the spread of ARB and ARGs as it contains the feces and urine of hospitalized patients, who are more frequently colonized with multi-drug resistant bacteria than the general population. However, whether hospital sewage noticeably contributes to the quantity and diversity of ARGs in the general sewerage system has not yet been determined. Here, we employed culture-independent techniques, namely 16S rRNA gene sequencing and nanolitre-scale quantitative PCRs, to assess the role of hospital effluent as a point source of ARGs in the sewerage system, through comparing microbiota composition and levels of ARGs in hospital sewage with WWTP influent with and without hospital sewage. Compared to other sites, hospital sewage was richest in human-associated bacteria and contained the highest relative levels of ARGs. Yet, the relative abundance of ARGs was comparable in the influent of WWTPs with and without hospital sewage, suggesting that hospitals do not contribute importantly to the quantity and diversity of ARGs in the investigated sewerage system