Comparative genomics of <Emphasis Type="Italic">Lactobacillus sakei</Emphasis> with emphasis on strains from meat

Lactobacillus sakei is a lactic acid bacterium important in food microbiology mainly due to its ability to ferment and preserve meat. The genome sequence of L. sakei strain 23K has revealed specialized metabolic capacities that reflect the bacterium’s adaption to meat products, and that differentiate it from other LAB. An extensive genomic diversity analysis was conducted to elucidate the core features of the species, and to provide a better comprehension of niche adaptation of the organism. Here, we describe the genomic comparison of 18 strains of L. sakei originating mainly from processed meat against the 23K strain by comparative genome hybridization. Pulsed field gel electrophoresis was used to estimate the genome sizes of the strains, which varied from 1.880 to 2.175 Mb, and the 23K genome was among the smallest. Consequently, a large part of the genome of this strain belongs to a common gene pool invariant in this species. The majority of genes important in adaption to meat products, the ability to flexibly use meat components, and robustness during meat processing and storage were conserved, such as genes involved in nucleoside scavenging, catabolism of arginine, and the ability to cope with changing redox and oxygen levels, which is indicative of the role these genes play in niche specialization within the L. sakei species. Moreover, an additional set of sequenced L. sakei genes beyond the 23K genome was present on the microarray used, and it was demonstrated that all the strains carry remnants of or complete bacteriocin operons. The genomic divergence corresponded mainly to five regions in the 23K genome, which showed features consistent with horizontal gene transfer. Carbohydrate-fermentation profiles of the strains were evaluated in light of the CGH data, and for most substrates, the genotypes were consistent with the phenotypes. We have demonstrated a highly conserved organization of the L. sakei genomes investigated, and the 23K strain is a suitable model organism to study core features of the L. sakei species.     

The physiological link between metabolic rate depression and tau phosphorylation in mammalian hibernation

Abnormal phosphorylation and aggregation of tau protein are hallmarks of a variety of neurological disorders, including Alzheimer's disease (AD). Increased tau phosphorylation is assumed to represent an early event in pathogenesis and a pivotal aspect for aggregation and formation of neurofibrillary tangles. However, the regulation of tau phosphorylation in vivo and the causes for its increased stage of phosphorylation in AD are still not well understood, a fact that is primarily based on the lack of adequate animal models. Recently we described the reversible formation of highly phosphorylated tau protein in hibernating European ground squirrels. Hence, mammalian hibernation represents a model system very well suited to study molecular mechanisms of both tau phosphorylation and dephosphorylation under in vivo physiological conditions. Here, we analysed the extent and kinetics of hibernation-state dependent tau phosphorylation in various brain regions of three species of hibernating mammals: arctic ground squirrels, Syrian hamsters and black bears. Overall, tau protein was highly phosphorylated in torpor states and phosphorylation levels decreased after arousal in all species. Differences between brain regions, hibernation-states and phosphosites were observed with respect to degree and kinetics of tau phosphorylation. Furthermore, we tested the phosphate net turnover of tau protein to analyse potential alterations in kinase and/or phosphatase activities during hibernation. Our results demonstrate that the hibernation-state dependent phosphorylation of tau protein is specifically regulated but involves, in addition, passive, temperature driven regulatory mechanisms. By determining the activity-state profile for key enzymes of tau phosphorylation we could identify kinases potentially involved in the differentially regulated, reversible tau phosphorylation that occurs during hibernation. We show that in black bears hibernation is associated with conformational changes of highly phosphorylated tau protein that are typically related to neuropathological alterations. The particular hibernation characteristics of black bears with a continuous torpor period and an only slightly decreased body temperature, therefore, potentially reflects the limitations of this adaptive reaction pattern and, thus, might indicate a transitional state of a physiological process.     

Untangling the intracellular signalling network in cancer--a strategy for data integration in acute myeloid leukaemia

Protein and gene networks centred on the regulatory tumour suppressor proteins may be of crucial importance both in carcinogenesis and in the response to chemotherapy. Tumour suppressor protein p53 integrates intracellular data in stress responses, receiving signals and translating these into differential gene expression. Interpretation of the data integrated on p53 may therefore reveal the response to therapy in cancer. Proteomics offers more specific data - closer to "the real action" - than the hitherto more frequently used gene expression profiling. Integrated data analysis may reveal pathways disrupted at several regulatory levels. Ultimately, integrated data analysis may also contribute to finding key underlying cancer genes. We here proposes a Partial Least Squares Regression (PLSR)-based data integration strategy, which allows simultaneous analysis of proteomic data, gene expression data and classical clinical parameters. PLSR collapses multidimensional data into fewer relevant dimensions for data interpretation. PLSR can also aid identification of functionally important modules by also performing comparison to databases on known biological interactions. Further, PLSR allows meaningful visualization of complex datasets, aiding interpretation of the underlying biology. Extracting the true biological causal mechanisms from heterogeneous patient populations is the key to discovery of new therapeutic options in cancer.     

Microbial laboratory evolution in the era of genome‐scale science

Laboratory evolution studies provide fundamental biological insight through direct observation of the evolution process. They not only enable testing of evolutionary theory and principles, but also have applications to metabolic engineering and human health. Genome‐scale tools are revolutionizing studies of laboratory evolution by providing complete determination of the genetic basis of adaptation and the changes in the organism's gene expression state. Here, we review studies centered on four central themes of laboratory evolution studies: (1) the genetic basis of adaptation; (2) the importance of mutations to genes that encode regulatory hubs; (3) the view of adaptive evolution as an optimization process; and (4) the dynamics with which laboratory populations evolve.     

A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011

The initial genome‐scale reconstruction of the metabolic network of Escherichia coli K‐12 MG1655 was assembled in 2000. It has been updated and periodically released since then based on new and curated genomic and biochemical knowledge. An update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. iJO1366 was (1) updated in part using a new experimental screen of 1075 gene knockout strains, illuminating cases where alternative pathways and isozymes are yet to be discovered, (2) compared with its predecessor and to experimental data sets to confirm that it continues to make accurate phenotypic predictions of growth on different substrates and for gene knockout strains, and (3) mapped to the genomes of all available sequenced E. coli strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. Like its predecessors, the iJO1366 reconstruction is expected to be widely deployed for studying the systems biology of E. coli and for metabolic engineering applications.     

Phenotypes of non-attached Pseudomonas aeruginosa aggregates resemble surface attached biofilm

For a chronic infection to be established, bacteria must be able to cope with hostile conditions such as low iron levels, oxidative stress, and clearance by the host defense, as well as antibiotic treatment. It is generally accepted that biofilm formation facilitates tolerance to these adverse conditions. However, microscopic investigations of samples isolated from sites of chronic infections seem to suggest that some bacteria do not need to be attached to surfaces in order to establish chronic infections. In this study we employed scanning electron microscopy, confocal laser scanning microscopy, RT-PCR as well as traditional culturing techniques to study the properties of Pseudomonas aeruginosa aggregates. We found that non-attached aggregates from stationary-phase cultures have comparable growth rates to surface attached biofilms. The growth rate estimations indicated that, independently of age, both aggregates and flow-cell biofilm had the same slow growth rate as a stationary phase shaking cultures. Internal structures of the aggregates matrix components and their capacity to survive otherwise lethal treatments with antibiotics (referred to as tolerance) and resistance to phagocytes were also found to be strikingly similar to flow-cell biofilms. Our data indicate that the tolerance of both biofilms and non-attached aggregates towards antibiotics is reversible by physical disruption. We provide evidence that the antibiotic tolerance is likely to be dependent on both the physiological states of the aggregates and particular matrix components. Bacterial surface-attachment and subsequent biofilm formation are considered hallmarks of the capacity of microbes to cause persistent infections. We have observed non-attached aggregates in the lungs of cystic fibrosis patients; otitis media; soft tissue fillers and non-healing wounds, and we propose that aggregated cells exhibit enhanced survival in the hostile host environment, compared with non-aggregated bacterial populations.     

Measuring genome conservation across taxa: divided strains and united kingdoms

Species evolutionary relationships have traditionally been defined by sequence similarities of phylogenetic marker molecules, recently followed by whole-genome phylogenies based on gene order, average ortholog similarity or gene content. Here, we introduce genome conservation--a novel metric of evolutionary distances between species that simultaneously takes into account, both gene content and sequence similarity at the whole-genome level. Genome conservation represents a robust distance measure, as demonstrated by accurate phylogenetic reconstructions. The genome conservation matrix for all presently sequenced organisms exhibits a remarkable ability to define evolutionary relationships across all taxonomic ranges. An assessment of taxonomic ranks with genome conservation shows that certain ranks are inadequately described and raises the possibility for a more precise and quantitative taxonomy in the future. All phylogenetic reconstructions are available at the genome phylogeny server: .     

Expansion of the BioCyc collection of pathway/genome databases to 160 genomes

The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.