Rhizobium etli CFN42 and Sinorhizobium meliloti 1021 bioinformatic transcriptional regulatory networks from culture and symbiosis.

Rhizobium etli CFN42 proteome-transcriptome mixed data of exponential growth and nitrogen-fixing bacteroids, as well as Sinorhizobium meliloti 1021 transcriptome data of growth and nitrogen-fixing bacteroids, were integrated into transcriptional regulatory networks (TRNs). The one-step construction network consisted of a matrix-clustering analysis of matrices of the gene profile and all matrices of the transcription factors (TFs) of their genome. The networks were constructed with the prediction of regulatory network application of the RhizoBindingSites database (http://rhizobindingsites.ccg.unam.mx/). The deduced free-living Rhizobium etli network contained 1,146 genes, including 380 TFs and 12 sigma factors. In addition, the bacteroid R. etli CFN42 network contained 884 genes, where 364 were TFs, and 12 were sigma factors, whereas the deduced free-living Sinorhizobium meliloti 1021 network contained 643 genes, where 259 were TFs and seven were sigma factors, and the bacteroid Sinorhizobium meliloti 1021 network contained 357 genes, where 210 were TFs and six were sigma factors. The similarity of these deduced condition-dependent networks and the biological E. coli and B. subtilis independent condition networks segregates from the random Erdös-Rényi networks. Deduced networks showed a low average clustering coefficient. They were not scale-free, showing a gradually diminishing hierarchy of TFs in contrast to the hierarchy role of the sigma factor rpoD in the E. coli K12 network. For rhizobia networks, partitioning the genome in the chromosome, chromids, and plasmids, where essential genes are distributed, and the symbiotic ability that is mostly coded in plasmids, may alter the structure of these deduced condition-dependent networks. It provides potential TF gen-target relationship data for constructing regulons, which are the basic units of a TRN.

Rhizobium etli CFN42 proteomes showed isoenzymes in free-living and symbiosis with a different transcriptional regulation inferred from a transcriptional regulatory network.

A comparative proteomic study at 6 h of growth in minimal medium (MM) and bacteroids at 18 days of symbiosis of Rhizobium etli CFN42 with the Phaseolus vulgaris leguminous plant was performed. A gene ontology classification of proteins in MM and bacteroid, showed 31 and 10 pathways with higher or equal than 30 and 20% of proteins with respect to genome content per pathway, respectively. These pathways were for energy and environmental compound metabolism, contributing to understand how Rhizobium is adapted to the different conditions. Metabolic maps based on orthology of the protein profiles, showed 101 and 74 functional homologous proteins in the MM and bacteroid profiles, respectively, which were grouped in 34 different isoenzymes showing a great impact in metabolism by covering 60 metabolic pathways in MM and symbiosis. Taking advantage of co-expression of transcriptional regulators (TF's) in the profiles, by selection of genes whose matrices were clustered with matrices of TF's, Transcriptional Regulatory networks (TRN´s) were deduced by the first time for these metabolic stages. In these clustered TF-MM and clustered TF-bacteroid networks, containing 654 and 246 proteins, including 93 and 46 TFs, respectively, showing valuable information of the TF's and their regulated genes with high stringency. Isoenzymes were specific for adaptation to the different conditions and a different transcriptional regulation for MM and bacteroid was deduced. The parameters of the TRNs of these expected biological networks and biological networks of E. coli and B. subtilis segregate from the random theoretical networks. These are useful data to design experiments on TF gene-target relationships for bases to construct a TRN.

Garvicins AG1 and AG2: Two Novel Class IId Bacteriocins of Lactococcus garvieae Lg-Granada.

Lactococcus garvieae causes infectious diseases in animals and is considered an emerging zoonotic pathogen involved in human clinical conditions. In silico analysis of plasmid pLG50 of L. garvieae Lg-Granada, an isolate from a patient with endocarditis, revealed the presence of two gene clusters (orf46-47 and orf48-49), each one encoding a novel putative bacteriocin, i.e., garvicin AG1 (GarAG1; orf46) and garvicin AG2 (GarAG2; orf48), and their corresponding immunity proteins (orf47 and orf49). The chemically synthesised bacteriocins GarAG1 and GarAG2 presented inhibitory activity against pathogenic L. garvieae strains, with AG2 also being active against Listeria monocytogenes, Listeria ivanovii and Enterococcus faecalis. Genetic organisation, amino acid sequences and antimicrobial activities of GarAG1 and GarAG2 indicate that they belong to linear non-pediocin-like one-peptide class IId bacteriocins. Gram-positive bacteria that were sensitive to GarAG2 were also able to ferment mannose, suggesting that this bacteriocin could use the mannose phosphotransferase transport system (Man-PTS) involved in mannose uptake as a receptor in sensitive strains. Intriguingly, GarAG1 and GarAG2 were highly active against their own host, L. garvieae Lg-Granada, which could be envisaged as a new strategy to combat pathogens via their own weapons.

Effect of Sample Collection (Manual Expression vs. Pumping) and Skimming on the Microbial Profile of Human Milk Using Culture Techniques and Metataxonomic Analysis.

Human milk microbiota is a unique bacterial community playing a relevant role in infant health, but its composition depends on different factors (woman health, lactation stage, and geographical lactation). However, information is lacking regarding some other factors that may affect the bacterial community of human milk. In this study we aimed to study the impact of the sample collection method and the skimming procedure using culture-dependent and culture-independent techniques to study the human milk microbial profile. One set of milk samples was provided by women (n = 10) in two consecutive days; half of the samples were collected the first day by manual expression and the other half on the second day by pumping. The rest of the participants (n = 17) provided milk samples that were fractionated by centrifugation; the bacterial profiles of whole milk and skimmed milk were compared by culture techniques in 10 milk samples, while those of whole milk, fat and skimmed milk were subjected to metataxonomic analysis in seven samples. Globally, the results obtained revealed high interindividual variability but that neither the use of single-use sterile devices to collect the sample nor the skimming procedure have a significant impact of the microbial profile of human samples.