Skin and Gill Microbiome during Infection.

Maintaining the high overall health of farmed animals is a central tenant of their well-being and care. Intense animal crowding in aquaculture promotes animal morbidity especially in the absence of straightforward methods for monitoring their health. Here, we used bacterial 16S ribosomal RNA gene sequencing to measure bacterial population dynamics during infection.

Bacterial networks in Atlantic salmon with Piscirickettsiosis.

An unbalanced composition of gut microbiota in fish is hypothesized to play a role in promoting bacterial infections, but the synergistic or antagonistic interactions between bacterial groups in relation to fish health are not well understood. We report that pathogenic species in the Piscirickettsia, Aeromonas, Renibacterium and Tenacibaculum genera were all detected in the digesta and gut mucosa of healthy Atlantic salmon without clinical signs of disease. Although Piscirickettsia salmonis (and other pathogens) occurred in greater frequencies of fish with clinical Salmonid Rickettsial Septicemia (SRS), the relative abundance was about the same as that observed in healthy fish.

Differences in Bacterial Small RNAs in Stool Samples from Hypercholesterolemic and Normocholesterolemic Subjects.

Cholesterol metabolism is important at the physiological level as well as in several diseases, with small RNA being an element to consider in terms of its epigenetic control. Thus, the aim of this study was to identify differences between bacterial small RNAs present at the gut level in hypercholesterolemic and normocholesterolemic individuals. Twenty stool samples were collected from hypercholesterolemic and normocholesterolemic subjects.

Characterization of microbial communities from gut microbiota of hypercholesterolemic and control subjects.

Introduction: In recent years, several studies have evidenced the importance of the microbiome to host physiology as metabolism regulator, along with its potential role in triggering various diseases. In this study, we analyzed the gut microbiota in hypercholesterolemic (cases) and normocholesterolemic (controls) individuals to identify characteristic microbial signature for each condition.

Methods: Stool samples were obtained from 57 adult volunteers (27 hypercholesterolemic and 30 controls).

OUTBREAK: a user-friendly georeferencing online tool for disease surveillance.

The current COVID-19 pandemic has already claimed more than 3.7 million victims and it will cause more deaths in the coming months. Tools that track the number and locations of cases are critical for surveillance and help in making policy decisions for controlling the outbreak.

RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.

Non-coding RNAs (ncRNAs) are important players in the cellular regulation of organisms from different kingdoms. One of the key steps in ncRNAs research is the ability to distinguish coding/non-coding sequences. We applied seven machine learning algorithms (Naive Bayes, Support Vector Machine, K-Nearest Neighbors, Random Forest, Extreme Gradient Boosting, Neural Networks and Deep Learning) through model organisms from different evolutionary branches to create a stand-alone and web server tool (RNAmining) to distinguish coding and non-coding sequences.

Novel molecular insights and public omics data in pulmonary hypertension.

Pulmonary hypertension is a rare disease with high morbidity and mortality which mainly affects women of reproductive age. Despite recent advances in understanding the pathogenesis of pulmonary hypertension, the high heterogeneity in the presentation of the disease among different patients makes it difficult to make an accurate diagnosis and to apply this knowledge to effective treatments. Therefore, new studies are required to focus on translational and personalized medicine to overcome the lack of specificity and efficacy of current management.

Predicting RNA Families in Nucleotide Sequences Using StructRNAfinder.

Noncoding RNA (ncRNA) research is already a routine in every genomics or transcriptomics initiatives. According to their functions, ncRNAs can be grouped into several different RNA families, which can be represented by conserved primary sequences, secondary structures, or covariance models (CMs). CMs are very sensitive in predicting RNA families in nucleotide sequences and have been widely used in characterizing the repertoire of ncRNAs in organisms from all domains of life.

Core non-coding RNAs of Piscirickettsia salmonis.

Piscirickettsia salmonis, a fastidious Gram-negative intracellular facultative bacterium, is the causative agent o Piscirickettsiosis. P. salmonis has broad host range with a nearly worldwide distribution, causing significant mortality.

Long Non-Coding RNAs Responsive to Salt and Boron Stress in the Hyper-Arid Lluteño Maize from Atacama Desert.

Long non-coding RNAs (lncRNAs) have been defined as transcripts longer than 200 nucleotides, which lack significant protein coding potential and possess critical roles in diverse cellular processes. Long non-coding RNAs have recently been functionally characterized in plant stress-response mechanisms. In the present study, we perform a comprehensive identification of lncRNAs in response to combined stress induced by salinity and excess of boron in the Lluteño maize, a tolerant maize landrace from Atacama Desert, Chile.

Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci.

Background: The mammalian genome is transcribed into large numbers of long noncoding RNAs (lncRNAs), but the definition of functional lncRNA groups has proven difficult, partly due to their low sequence conservation and lack of identified shared properties. Here we consider promoter conservation and positional conservation as indicators of functional commonality.

Results: We identify 665 conserved lncRNA promoters in mouse and human that are preserved in genomic position relative to orthologous coding genes.

Genome-wide circulating microRNA expression profiling reveals potential biomarkers for amyotrophic lateral sclerosis.

The occurrence of mutations of TDP-43, FUS, and C9ORF72 in amyotrophic lateral sclerosis (ALS) suggests pathogenic alterations to RNA metabolism and specifically to microRNA (miRNA) biology. Moreover, several ALS-related proteins impact stress granule dynamics affecting miRNA biogenesis and cellular miRNA levels. miRNAs are present in different biological fluids and have been proposed as potential biomarkers.

CEMiTool: a Bioconductor package for performing comprehensive modular co-expression analyses.

Background: The analysis of modular gene co-expression networks is a well-established method commonly used for discovering the systems-level functionality of genes. In addition, these studies provide a basis for the discovery of clinically relevant molecular pathways underlying different diseases and conditions.

Results: In this paper, we present a fast and easy-to-use Bioconductor package named CEMiTool that unifies the discovery and the analysis of co-expression modules.

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

Background: The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files.

LeishDB: a database of coding gene annotation and non-coding RNAs in Leishmania braziliensis.

www.leishdb.com.