Genomic diversity and versatility of Lactobacillus plantarum, a natural metabolic engineer

In the past decade it has become clear that the lactic acid bacterium Lactobacillus plantarum occupies a diverse range of environmental niches and has an enormous diversity in phenotypic properties, metabolic capacity and industrial applications. In this review, we describe how genome sequencing, comparative genome hybridization and comparative genomics has provided insight into the underlying genomic diversity and versatility of L. plantarum. One of the main features appears to be genomic life-style islands consisting of numerous functional gene cassettes, in particular for carbohydrates utilization, which can be acquired, shuffled, substituted or deleted in response to niche requirements. In this sense, L. plantarum can be considered a “natural metabolic engineer”

LocateP: Genome-scale subcellular-location predictor for bacterial proteins

Contains fulltext : 69477.pdf ( ) (Open Access)BACKGROUND: In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase) cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. RESULTS: LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms current tools especially where the N-terminally anchored and the SPIase-cleaved secreted proteins are concerned. Overall, the accuracy of LocateP was always higher than 90%. LocateP was then used to predict the SCLs of all proteins encoded by completed Gram-positive bacterial genomes. The results are stored in the database LocateP-DB http://www.cmbi.ru.nl/locatep-db1. CONCLUSION: LocateP is by far the most accurate and detailed protein SCL predictor for Gram-positive bacteria currently available

Maturation pathway of nisin and other lantibiotics:post-translationally modified antimicrobial peptides exported by Gram-positive bacteria

Lantibiotics form a family of highly modified peptides which are secreted by several Gram-positive bacteria. They exhibit antimicrobial activity, mainly against other Gram-positive bacteria, by forming pores in the cellular membrane. These antimicrobial peptides are ribosomally synthesized and contain leader peptides which do not show the characteristics of signal sequences. Several amino acid residues of the precursor lantibiotic are enzymatically modified, whereafter secretion and processing of the leader peptide takes place, yielding the active antimicrobial substance. For several lantibiotics the gene clusters encoding biosynthetic enzymes, translocator proteins, self-protection proteins, processing enzymes and regulatory proteins have been identified. This MicroReview describes the current knowledge about the biosynthetic, immunity and regulatory processes leading to lantibiotic production. Most of the attention is focused on the lantibiotic nisin, which is produced by the food-grade bacterium Lactococcus lactis and is widely used as a preservative in the food industry

Engineering Dehydrated Amino Acid Residues in the Antimicrobial Peptide Nisin

The small antimicrobial peptide nisin, produced by Lactococcus lactis, contains the uncommon amino acid residues dehydroalanine and dehydrobutyrine and five thio ether bridges. Since these structures are posttranslationally formed from Ser, Thr, and Cys residues, it is feasible to study their role in nisin function and biosynthesis by protein engineering. Here we report the development of an expression system for mutated nisin Z (nisZ) genes, using nisin A producing L. lactis as a host. Replacement by site-directed mutagenesis of the Ser-5 codon in nisZ by a Thr codon, led to a mutant with a dehydrobutyrine instead of a dehydroalanine residue at position 5, as shown by NMR. Its antimicrobial activity was 2-10-fold lower relative to wild-type nisin Z, depending on the indicator strain used. In another mutagenesis study a double mutation was introduced in the nisZ gene by replacing the codons for Met-17 and Gly-18 by codons for Gln and Thr, respectively, as in the third lanthionine ring of the related antimicrobial peptide subtilin from Bacillus subtilis. This resulted in the simultaneous production of two mutant species, one containing a Thr residue and the other containing a dehydrobutyrine residue at position 18, both having different bacteriocidal properties.

Predicting cis-acting elements of Lactobacillus plantarum by comparative genomics with different taxonomic subgroups

Cis-acting elements in Lactobacillus plantarum were predicted by comparative analysis of the upstream regions of conserved genes and predicted transcriptional units (TUs) in different bacterial genomes. TUs were predicted for two species sets, with different evolutionary distances to L.plantarum. TUs were designated ‘cluster of orthologous transcriptional units’ (COT) when >50% of the genes were orthologous in different species. Conserved DNA sequences were detected in the upstream regions of different COTs. Subsequently, conserved motifs were used to scan upstream regions of all TUs. This method revealed 18 regulatory motifs only present in lactic acid bacteria (LAB). The 18 LAB-specific candidate regulatory motifs included 13 that were not described previously. These LAB-specific different motifs were found in front of genes encoding functions varying from cold shock proteins to RNA and DNA polymerases, and many unknown functions. The best-described LAB-specific motif found was the CopR-binding site, regulating expression of copper transport ATPases. Finally, all detected motifs were used to predict co-regulated TUs (regulons) for L.plantarum, and transcriptome profiling data were analyzed to provide regulon prediction validation. It is demonstrated that phylogenetic footprinting using different species sets can identify and distinguish between general regulatory motifs and LAB-specific regulatory motifs

Co-Regulation of Metabolic Genes Is Better Explained by Flux Coupling Than by Network Distance

To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools

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

Correlation between sequence conservation and the genomic context after gene duplication

A key complication in comparative genomics for reliable gene function prediction is the existence of duplicated genes. To study the effect of gene duplication on function prediction, we analyze orthologs between pairs of genomes where in one genome the orthologous gene has duplicated after the speciation of the two genomes (i.e. inparalogs). For these duplicated genes we investigate whether the gene that is most similar on the sequence level is also the gene that has retained the ancestral gene-neighborhood. Although the majority of investigated cases show a consistent pattern between sequence similarity and gene-neighborhood conservation, a substantial fraction, 29–38%, is inconsistent. The observation of inconsistency is not the result of a chance outcome owing to a lack of divergence time between inparalogs, but rather it seems to be the result of a chance outcome caused by very similar rates of sequence evolution of both inparalogs relative to their ortholog. If one-to-one orthologous relationships are required, it is advisable to combine contextual information (i.e. gene-neighborhood in prokaryotes and co-expression in eukaryotes) with protein sequence information to predict the most probable functional equivalent ortholog in the presence of inparalogs

Comparative Genome Analysis of Lactococcus lactis Indicates Niche Adaptation and Resolves Genotype/Phenotype Disparity

Lactococcus lactis is one of the most important micro-organisms in the dairy industry for the fermentation of cheese and buttermilk. Besides the conversion of lactose to lactate it is responsible for product properties such as flavor and texture, which are determined by volatile metabolites, proteolytic activity and exopolysaccharide production. While the species Lactococcus lactis consists of the two subspecies lactis and cremoris their taxonomic position is confused by a group of strains that, despite of a cremoris genotype, display a lactis phenotype. Here we compared and analyzed the (draft) genomes of 43 L. lactis strains, of which 19 are of dairy and 24 are of non-dairy origin. Machine-learning algorithms facilitated the identification of orthologous groups of protein sequences (OGs) that are predictors for either the taxonomic position or the source of isolation. This allowed the unambiguous categorization of the genotype/phenotype disparity of ssp. lactis and ssp. cremoris strains. A detailed analysis of phenotypic properties including plasmid-encoded genes indicates evolutionary changes during niche adaptations. The results are consistent with the hypothesis that dairy isolates evolved from plant isolates. The analysis further suggests that genomes of cremoris phenotype strains are so eroded that they are restricted to a dairy environment. Overall the genome comparison of a diverse set of strains allowed the identification of niche and subspecies specific genes. This explains evolutionary relationships and will aid the identification and selection of industrial starter cultures