Genomic analysis of four strains of Corynebacterium pseudotuberculosis bv. Equi isolated from horses showing distinct signs of infection.

The genomes of four strains (MB11, MB14, MB30, and MB66) of the species Corynebacterium pseudotuberculosis biovar equi were sequenced on the Ion Torrent PGM platform, completely assembled, and their gene content and structure were analyzed. The strains were isolated from horses with distinct signs of infection, including ulcerative lymphangitis, external abscesses on the chest, or internal abscesses on the liver, kidneys, and lungs. The average size of the genomes was 2.3 Mbp, with 2169 (Strain MB11) to 2235 (Strain MB14) predicted coding sequences (CDSs). An optical map of the MB11 strain generated using the KpnI restriction enzyme showed that the approach used to assemble the genome was satisfactory, producing good alignment between the sequence observed in vitro and that obtained in silico. In the resulting Neighbor-Joining dendrogram, the C. pseudotuberculosis strains sequenced in this study were clustered into a single clade supported by a high bootstrap value. The structural analysis showed that the genomes of the MB11 and MB14 strains were very similar, while the MB30 and MB66 strains had several inverted regions. The observed genomic characteristics were similar to those described for other strains of the same species, despite the number of inversions found. These genomes will serve as a basis for determining the relationship between the genotype of the pathogen and the type of infection that it causes

Genome Sequence of Corynebacterium pseudotuberculosis MB20 bv. equi Isolated from a Pectoral Abscess of an Oldenburg Horse in California.

The genome of Corynebacterium pseudotuberculosis MB20 bv. equi was sequenced using the Ion Personal Genome Machine (PGM) platform, and showed a size of 2,363,089 bp, with 2,365 coding sequences and a GC content of 52.1%. These results will serve as a basis for further studies on the pathogenicity of C. pseudotuberculosis bv. equi

Analysis of quality raw data of second generation sequencers with Quality Assessment Software

<p>Abstract</p> <p>Background</p> <p>Second generation technologies have advantages over Sanger; however, they have resulted in new challenges for the genome construction process, especially because of the small size of the reads, despite the high degree of coverage. Independent of the program chosen for the construction process, DNA sequences are superimposed, based on identity, to extend the reads, generating contigs; mismatches indicate a lack of homology and are not included. This process improves our confidence in the sequences that are generated.</p> <p>Findings</p> <p>We developed Quality Assessment Software, with which one can review graphs showing the distribution of quality values from the sequencing reads. This software allow us to adopt more stringent quality standards for sequence data, based on quality-graph analysis and estimated coverage after applying the quality filter, providing acceptable sequence coverage for genome construction from short reads.</p> <p>Conclusions</p> <p>Quality filtering is a fundamental step in the process of constructing genomes, as it reduces the frequency of incorrect alignments that are caused by measuring errors, which can occur during the construction process due to the size of the reads, provoking misassemblies. Application of quality filters to sequence data, using the software Quality Assessment, along with graphing analyses, provided greater precision in the definition of cutoff parameters, which increased the accuracy of genome construction.</p

Hydrogen peroxide production regulates the mitochondrial function in insulin resistant muscle cells: Effect of catalase overexpression

AbstractThe mitochondrial redox state plays a central role in the link between mitochondrial overloading and insulin resistance. However, the mechanism by which the ROS induce insulin resistance in skeletal muscle cells is not completely understood. We examined the association between mitochondrial function and H2O2 production in insulin resistant cells. Our hypothesis is that the low mitochondrial oxygen consumption leads to elevated ROS production by a mechanism associated with reduced PGC1α transcription and low content of phosphorylated CREB. The cells were transfected with either the encoded sequence for catalase overexpression or the specific siRNA for catalase inhibition. After transfection, myotubes were incubated with palmitic acid (500μM) and the insulin response, as well as mitochondrial function and fatty acid metabolism, was determined. The low mitochondrial oxygen consumption led to elevated ROS production by a mechanism associated with β-oxidation of fatty acids. Rotenone was observed to reduce the ratio of ROS production. The elevated H2O2 production markedly decreased the PGC1α transcription, an effect that was accompanied by a reduced phosphorylation of Akt and CREB. The catalase transfection prevented the reduction in the phosphorylated level of Akt and upregulated the levels of phosphorylated CREB. The mitochondrial function was elevated and H2O2 production reduced, thus increasing the insulin sensitivity. The catalase overexpression improved mitochondrial respiration protecting the cells from fatty acid-induced, insulin resistance. This effect indicates that control of hydrogen peroxide production regulates the mitochondrial respiration preventing the insulin resistance in skeletal muscle cells by a mechanism associated with CREB phosphorylation and β-oxidation of fatty acids

Emotional, hyperactivity and inattention problems in adolescents with immunocompromising chronic diseases during the COVID-19 pandemic

Objective: To assess factors associated with emotional changes and Hyperactivity/Inattention (HI) motivated by COVID-19 quarantine in adolescents with immunocompromising diseases. Methods: A cross-sectional study included&nbsp;343&nbsp;adolescents with immunocompromising diseases and 108&nbsp;healthy adolescents. Online questionnaires were answered including socio-demographic data and self-rated healthcare routine during COVID-19 quarantine and validated surveys: Strengths and Difficulties Questionnaire (SDQ), Pittsburgh Sleep Quality Index (PSQI), Pediatric Quality of Life Inventory 4.0 (PedsQL4.0). Results: The frequencies of abnormal emotional SDQ scores from adolescents with chronic diseases were similar to those of healthy subjects (110/343&nbsp;[32%] vs.&nbsp;38/108 [35%], p&nbsp;=&nbsp;0.548), as well as abnormal hyperactivity/inattention SDQ scores (79/343 [23%] vs.&nbsp;29/108 [27%], p&nbsp;=&nbsp;0.417). Logistic regression analysis of independent variables associated with abnormal emotional scores from adolescents with chronic diseases showed: female sex (Odds Ratio [OR&nbsp;=&nbsp;3.76]; 95%&nbsp;Confidence Interval (95%&nbsp;CI) 2.00‒7.05; p &lt; 0.001), poor sleep quality (OR&nbsp;=&nbsp;2.05; 95%&nbsp;CI&nbsp;1.08‒3.88; p&nbsp;=&nbsp;0.028) and intrafamilial violence during pandemic (OR&nbsp;=&nbsp;2.17; 95%&nbsp;CI&nbsp;1.12‒4.19; p&nbsp;=&nbsp;0.021) as independently associated with abnormal emotional scores, whereas total PedsQL score was inversely associated with abnormal emotional scores (OR&nbsp;=&nbsp;0.95; 95%&nbsp;CI&nbsp;0.93‒0.96; p &lt; 0.0001). Logistic regression analysis associated with abnormal HI scores from patients evidenced that total PedsQL score (OR&nbsp;=&nbsp;0.97; 95%&nbsp;CI&nbsp;0.95‒0.99; p&nbsp;=&nbsp;0.010], changes in medical appointments during the pandemic (OR&nbsp;=&nbsp;0.39; 95%&nbsp;CI&nbsp;0.19-0.79; p&nbsp;=&nbsp;0.021), and reliable COVID-19 information (OR&nbsp;=&nbsp;0.35; 95%&nbsp;CI&nbsp;0.16‒0.77; p&nbsp;=&nbsp;0.026) remained inversely associated with abnormal HI scores. Conclusion: The present study showed emotional and HI disturbances in adolescents with chronic immunosuppressive diseases during the COVID-19 pandemic. It reinforces the need to promptly implement a longitudinal program to protect the mental health of adolescents with and without chronic illnesses during future pandemics

Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars

Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype–genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite–metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background