Structure-function relationships of glucansucrase and fructansucrase enzymes from lactic acid bacteria

Lactic acid bacteria (LAB) employ sucrase-type enzymes to convert sucrose into homopolysaccharides consisting of either glucosyl units (glucans) or fructosyl units (fructans). The enzymes involved are labeled glucansucrases (GS) and fructansucrases (FS), respectively. The available molecular, biochemical, and structural information on sucrase genes and enzymes from various LAB and their fructan and α-glucan products is reviewed. The GS and FS enzymes are both glycoside hydrolase enzymes that act on the same substrate (sucrose) and catalyze (retaining) transglycosylation reactions that result in polysaccharide formation, but they possess completely different protein structures. GS enzymes (family GH70) are large multidomain proteins that occur exclusively in LAB. Their catalytic domain displays clear secondary-structure similarity with α-amylase enzymes (family GH13), with a predicted permuted (β/α)8 barrel structure for which detailed structural and mechanistic information is available. Emphasis now is on identification of residues and regions important for GS enzyme activity and product specificity (synthesis of α-glucans differing in glycosidic linkage type, degree and type of branching, glucan molecular mass, and solubility). FS enzymes (family GH68) occur in both gram-negative and gram-positive bacteria and synthesize β-fructan polymers with either β-(2→6) (inulin) or β-(2→1) (levan) glycosidic bonds. Recently, the first high-resolution three-dimensional structures have become available for FS (levansucrase) proteins, revealing a rare five-bladed β-propeller structure with a deep, negatively charged central pocket. Although these structures have provided detailed mechanistic insights, the structural features in FS enzymes dictating the synthesis of either β-(2→6) or β-(2→1) linkages, degree and type of branching, and fructan molecular mass remain to be identified

Draft Genome Sequence of Lactobacillus plantarum Lp90 Isolated from Wine

Contains fulltext : 155072.pdf (publisher's version ) (Open Access)Here, we describe the draft genome sequence and annotation of Lactobacillus plantarum strain Lp90, the first sequenced genome of a L. plantarum strain isolated from wine. This strain has a noticeable ropy phenotype and showed potential probiotic properties. The genome consists of 3,324,076 bp (33 contigs) and contains 3,155 protein coding genes, 34 pseudogenes, and 84 RNA genes

Diversity of acid stress resistant variants of Listeria monocytogenes and the potential role of ribosomal protein S21 encoded by rpsU

Contains fulltext : 155050.pdf (publisher's version ) (Open Access)The dynamic response of microorganisms to environmental conditions depends on the behavior of individual cells within the population. Adverse environments can select for stable stress resistant subpopulations. In this study, we aimed to get more insight in the diversity within Listeria monocytogenes LO28 populations, and the genetic basis for the increased resistance of stable resistant fractions isolated after acid exposure. Phenotypic cluster analysis of 23 variants resulted in three clusters and four individual variants and revealed multiple-stress resistance, with both unique and overlapping features related to stress resistance, growth, motility, biofilm formation, and virulence indicators. A higher glutamate decarboxylase activity correlated with increased acid resistance. Whole genome sequencing revealed mutations in rpsU, encoding ribosomal protein S21 in the largest phenotypic cluster, while mutations in ctsR, which were previously shown to be responsible for increased resistance of heat and high hydrostatic pressure resistant variants, were not found in the acid resistant variants. This underlined that large population diversity exists within one L. monocytogenes strain and that different adverse conditions drive selection for different variants. The finding that acid stress selects for rpsU variants provides potential insights in the mechanisms underlying population diversity of L. monocytogenes

CiVi: circular genome visualization with unique features to analyze sequence elements

Item does not contain fulltextWe have developed CiVi, a user-friendly web-based tool to create custom circular maps to aid the analysis of microbial genomes and sequence elements. Sequence related data such as gene-name, COG class, PFAM domain, GC%, and subcellular location can be comprehensively viewed. Quantitative gene-related data (e.g. expression ratios or read counts) as well as predicted sequence elements (e.g. regulatory sequences) can be uploaded and visualized. CiVi accommodates the analysis of genomic elements by allowing a visual interpretation in the context of: (i) their genome-wide distribution, (ii) provided experimental data and (iii) the local orientation and location with respect to neighboring genes. CiVi thus enables both experts and non-experts to conveniently integrate public genome data with the results of genome analyses in circular genome maps suitable for publication. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. AVAILABILITY AND IMPLEMENTATION: CiVi is freely available at http://civi.cmbi.ru.nl

Integration of omics data: how well does it work for bacteria?

In the current omics era, innovative high-throughput technologies allow measuring temporal and conditional changes at various cellular levels. Although individual analysis of each of these omics data undoubtedly results into interesting findings, it is only by integrating them that gaining a global insight into cellular behaviour can be aimed at. A systems approach thus is predicated on data integration. However, because of the complexity of biological systems and the specificities of the data-generating technologies (noisiness, heterogeneity, etc.), integrating omics data in an attempt to reconstruct signalling networks is not trivial. Developing its methodologies constitutes a major research challenge. Besides for their intrinsic value towards health care, environment and industry, prokaryotes are ideal model systems to further develop these methods because of their lower regulatory complexity compared with eukaryotes, and the ease with which they can be manipulated. Several successful examples outlined in this review already show the potential of the systems approach for both fundamental and industrial applications, which would be time-consuming or impossible to develop solely through traditional reductionist approaches