Human Microbiota Network: Unveiling Potential Crosstalk between the Different Microbiota Ecosystems and Their Role in Health and Disease.

The human body is host to a large number of microorganisms which conform the human microbiota, that is known to play an important role in health and disease. Although most of the microorganisms that coexist with us are located in the gut, microbial cells present in other locations (like skin, respiratory tract, genitourinary tract, and the vaginal zone in women) also play a significant role regulating host health. The fact that there are different kinds of microbiota in different body areas does not mean they are independent. It is plausible that connection exist, and different studies have shown that the microbiota present in different zones of the human body has the capability of communicating through secondary metabolites. In this sense, dysbiosis in one body compartment may negatively affect distal areas and contribute to the development of diseases. Accordingly, it could be hypothesized that the whole set of microbial cells that inhabit the human body form a system, and the dialogue between the different host microbiotas may be a contributing factor for the susceptibility to developing diseased states. For this reason, the present review aims to integrate the available literature on the relationship between the different human microbiotas and understand how changes in the microbiota in one body region can influence other microbiota communities in a bidirectional process. The findings suggest that the different microbiotas may act in a coordinated way to decisively influence human well-being. This new integrative paradigm opens new insights in the microbiota field of research and its relationship with human health that should be taken into account in future studies.

Changes in intestinal microbiota and disease resistance following dietary postbiotic supplementation in rainbow trout (Oncorhynchus mykiss).

This experimental study was aimed to investigate whether the dietary supplementation of a postbiotic obtained as a food product fermented with two lactic acid bacteria could induce changes in the intestinal microbiota and prevent the development of Lactococcus garvieae infection in rainbow trout (Oncorhynchus mykiss). After 30 days of dietary postbiotic supplementation, bacterial community composition and structure was significantly different between the treated and control groups. A higher bacterial diversity and richness in the intestinal samples was found in treated fish, as compared to those samples from untreated fish. Dietary postbiotic supplementation also conferred increased protection against L. garvieae infection. These findings suggest that the establishment of a beneficial microbiota is essential to prevent diseases or protect the host from foreign agents.

First identification of Francisella noatunensis subsp. orientalis causing mortality in Mexican tilapia Oreochromis spp.

Francisellosis, an emerging disease in tilapia Oreochromis spp., is caused by the facultative, intracellular bacterium Francisella noatunensis subsp. orientalis, which is present in various countries where tilapia farming is commercially important. We confirmed the presence of francisellosis in Mexican tilapia cultures in association with an outbreak during the second semester of 2012. Broodstock fish presented a mortality rate of approximately 40%, and disease was characterized by histologically classified granulomas, or whitish nodules, in different organs, mainly the spleen and kidney. Through DNA obtained from infected tissue and pure cultures in a cysteine heart medium supplemented with hemoglobin, F. noatunensis subsp. orientalis was initially confirmed through the amplification and analysis of the 16S rRNA gene and the internal transcribed spacer region. Phylogenetic analysis of these genes demonstrated close similarity with previously reported F. noatunensis subsp. orientalis sequences obtained from infected tilapia from various countries. The identification of this subspecies as the causative agent of the outbreak was confirmed using the iglC gene as a target sequence, which showed 99.5% identity to 2 F. noatunensis subsp. orientalis strains (Ethime-1 and Toba04). These findings represent the first documented occurrence of francisellosis in Mexican tilapia cultures, which highlights the importance of establishing preventative measures to minimize the spread of this disease within the Mexican aquaculture industry.

Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases.

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers-Logistic Regression, Naïve Bayes and Random Forest-with a range of social network measures and the necessary databases to model the verdicts in two real-world cases: the U.S. Watergate Conspiracy of the 1970's and the now-defunct Canada-based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures.

Identification and genetic characterization of Piscirickettsia salmonis in native fish from southern Chile.

Piscirickettsia salmonis is the etiological agent of piscirickettsiosis, a severe disease causing high mortalities in salmonids. This bacterium has been previously identified and isolated in all cultivated salmonids in Chile and worldwide, including Salmo salar, Oncorhynchus kisutch, and O. mykiss, in addition to being found in non-salmonid species such as Dicentrarchus labrax and Atractoscion nobilis. In this study, the 16S rRNA gene and intergenic spacer ITS-1 of P. salmonis were amplified by PCR from DNA samples extracted from the native Chilean fish species Eleginops maclovinus, Odontesthes regia, Sebastes capensis, and Salilota australis. Analysis of the 16S rRNA sequences from O. regia demonstrated a close phylogenetic relationship with the 16S rRNA gene in the Chilean EM-90 strain. The 16S rRNA sequences from E. maclovinus, S. capensis, and S. australis were related to the Chilean LF-89 sequence and Scottish strains. To confirm these findings, analysis of P. salmonis ITS-1 sequences obtained from the 4 sampled native species demonstrated a high degree of identity and a close phylogenetic relationship with Chilean P. salmonis sequences, including LF-89 and EM-90. These results suggest a strong relationship between the nucleotide sequences from the 16S rRNA and ITS-1 genes amplified from native fish with those sequences described in the first P. salmonis strains to be identified and isolated in Chile.