Investigations on microbiome of the used clinical device revealed many uncultivable newer bacterial species associated with persistent chronic infections

Introduction. Chronic persistent device-related infections (DRIs) often give culture-negative results in a microbiological investigation. In such cases, investigations on the device metagenome might have a diagnostic value. Materials and Methods. The 16SrRNA gene sequence analysis and next-generation sequencing (NGS) of clinical metagenome were performed to detect bacterial diversity on invasive medical devices possibly involved in culture-negative DRIs. Device samples were first subjected to microbiological investigation followed by metagenome analysis. Environmental DNA (e-DNA) isolated from device samples was subjected to 16SrRNA gene amplification followed by Sanger sequencing (n=14). In addition, NGS of the device metagenome was also performed (n=12). Five samples were only common in both methods. Results. Microbial growth was observed in only nine cases; among these, five cases were considered significant growth, and in the remaining four cases, growth was considered either insignificant or contaminated. Culture and sequencing analysis yielded identical results only in six cases. In culture-negative cases, Sanger sequencing of 16SrRNA gene and NGS of 16SrDNA microbiome was able to identify the presence of rarely described human pathogens, namely Streptococcus infantis, Gemella haemolysans, Meiothermus silvanus, Schlegelella aquatica, Rothia mucilaginosa, Serratia nematodiphila, and Enterobacter asburiae, along with some known common nosocomial pathogens. Bacterial species such as M. silvanus and S. nematodiphila that are never reported in human infection were also identified. Conclusions. Results of a small number of diverse samples of this pilot study might lead to a path to study a large number of device samples that may validate the diversity witnessed. The study shows that a culture free, a holistic metagenomic approach using NGS could help identify the pathogens in culture-negative chronic DRIs

A transcriptomic study on cold stress in two Indian rice varieties using RNA-Seq analysis

Cold weather negatively affects the growth of seedling, which ultimately decrees the production of crops. Studies were done in the context of cold stress related to rice (Oryza Sativa) production, which is an important staple crop taken as food by half of the human population worldwide. It's always been a challenge to tackle out the problems related to such stress conditions. Rice is a model organism for monocots, finding out the molecular markers can help improve different crop varieties against cold stress. Advancement in High throughput techniques such as RNA-Seq, gives us an opportunity to revisit all the aspects of previous studies and improve them in more depth. Here we chose rice at seedling stage of both cold tolerant and susceptible genotype for our transcriptome level study under normal temperature, cold stress, and recovery condition. In our experiment, Genome wide expression profile of both the genotypes at all three different conditions was studied. We detected a total of 3217 and 485 common regulated differentially expressed genes (DEGs) during cold stress and recovery condition respectively. Followed by their gene ontology (GO) enrichment analysis for different functions they involved. By combining co-expression study and cluster analysis, we suggested few of the genes which may be highly responsible for cold stress and not reported before. These results expand the opportunities to explore cold stress and their recovery for crop plants with more detail in future

Insights on the Functional Impact of MicroRNAs Present in Autism-Associated Copy Number Variants

<div><p>Autism spectrum disorder is a complex neurodevelopmental disorder that appears during the first three years of infancy and lasts throughout a person’s life. Recently a large category of genomic structural variants, denoted as copy number variants (CNVs), were established to be a major contributor of the pathophysiology of autism. To date almost all studies have focussed only on the genes present in the CNV loci, but the impact of non-coding regulatory microRNAs (miRNAs) present in these regions remain largely unexplored. Hence we attempted to elucidate the biological and functional significance of miRNAs present in autism-associated CNV loci and their target genes by using a series of computational tools. We demonstrate that nearly 11% of the CNV loci harbor miRNAs and a few of these miRNAs were previously reported to be associated with autism. A systematic analysis of the CNV-miRNAs based on their interactions with the target genes enabled the identification of top 10 miRNAs namely hsa-miR-590-3p, hsa-miR-944, hsa-miR-570, hsa-miR-34a, hsa-miR-124, hsa-miR-548f, hsa-miR-429, hsa-miR-200b, hsa-miR-195 and hsa-miR-497 as hub molecules. Further, the CNV-miRNAs formed a regulatory loop with transcription factors and their downstream target genes, and annotation of these target genes indicated their functional involvement in neurodevelopment and synapse. Moreover, miRNAs present in deleted and duplicated CNV loci may explain the difference in dosage of the crucial genes controlled by them. These CNV-miRNAs can also impair the global processing and biogenesis of all miRNAs by targeting key molecules in the miRNA pathway. To our knowledge, this is the first report to highlight the significance of CNV-microRNAs and their target genes to contribute towards the genetic heterogeneity and phenotypic variability of autism.</p> </div

CNV-miRNAs and their target genes involved in the microRNA processing and biogenesis pathways.

<p>Saffron ellipses represent the key components involved in miRNA processing and biogenesis, while miRNAs are denoted by the blue coloured squares. Dashed lines represent the validated interactions between the genes and CNV-miRNAs.</p

The top 10 hub molecules in the autism CNV-microRNA-target gene network.

*<p>Only selected targets are shown. For the complete list of target genes, see supporting information <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056781#pone.0056781.s005" target="_blank">Table S5</a>.</p

Intersection analysis of the 326 genes targeted by miRNAs present in CNVs.

<p>The Venn diagram represents the distribution of genes targeted by microRNAs belonging to three CNV categories (deletion, duplication and deletion-duplication). The effect on the dosage/expression status of these genes is described along the sides of the figure with arrow mark indications.</p

Functional annotation of the 326 genes targeted by miRNAs present in autism-associated CNV loci.

<p>The results for each enriched GO categories of the 326 genes targeted by the autism associated CNV-miRNAs are listed in this table. Each GO category belongs to one of the three sub-roots (<i>biological process, molecular function, or cellular component</i>). R is the ratio of enrichment. Adj P – P-value adjusted by multiple testing.</p

The genomic location of autism-associated CNV-microRNAs.

<p>The genomic locations of miRNAs present in the 41 CNV loci consistently associated with autism are indicated with arrow heads. The miRNAs labelled in red, green and black indicate the deleted, duplicated and deleted-duplicated categories, respectively.</p

Normalized density distribution of autism-associated CNVs across human chromosomes.

<p>The normalized CNV density is plotted in y-axis against the chromosomes in x-axis. For any given chromosome, a value above 1 indicates that it has accumulated more number of autism-associated CNVs compared to the mean of all chromosomal CNV densities. The error bars indicate the standard deviation.</p