Taxonomic distribution of the species in the metagenome of Indian currency notes using MEGAN & relative microbial load for all the three samples.

<p><b>(A)</b> The overall proportion of each Kingdom found in all the three samples. <b>(B)</b> Heatmap representation of the relative microbial load in the range shown in sale bars on the three currency samples C1, C2, C3. The red, green and yellow color represents bacteria, eukaryota and archaea phyla respectively.</p

Sequencing reads and contigs statistics for each of the three datasets.

<p>Sequencing reads and contigs statistics for each of the three datasets.</p

(A): The venn diagram depicts the number of unique and common antibiotic resistance genes between the three samples.

<p>(B): Average contig coverage for 18 common antibiotic resistance genes between the three samples is represented as a bar chart. X-axis: The antibiotic resistance genes types and Y-axis: The average contig coverage. C1, C2 and C3 are represented by red, blue and green color bars, respectively. Error bars represent the standard error. [<b>aac6ie</b>, Aminoglycoside N-acetyltransferase, (Resistance profile: amikacin, dibekacin, isepamicin, netilmicin, sisomicin, tobramycin); <b>acrb</b>, Resistance-nodulation-cell division transporter system- Multidrug resistance efflux pump, (Resistance profile: acriflavin, aminoglycoside, beta_lactam, glycylcycline, macrolide); <b>adeb</b>: Resistance-nodulation-cell division transporter system. Multidrug resistance efflux pump, (Resistance profile: aminoglycoside; chloramphenicol); <b>aph3ia</b>: Aminoglycoside O-phosphotransferase, (Resistance profile: gentamincin b, kanamycin, lividomycin, neomycin, paromomycin, ribostamycin); <b>baca</b>: Undecaprenyl pyrophosphate phosphatase, (Resistance profile: bacitracin); <b>bl2a_pc</b>: Class A beta-lactamase, (Resistance profile: penicillin); <b>cata7</b>: Group A chloramphenicol acetyltransferase, (Resistance profile: chloramphenicol); <b>cata8</b>: Group A chloramphenicol acetyltransferase, (Resistance profile: chloramphenicol); <b>ermb</b>: rRNA adenine N-6-methyltransferase, (Resistance profile: lincosamide, macrolide, streptogramin) b; <b>ermc</b>: rRNA adenine N-6-methyltransferase, (Resistance profile: lincosamide; macrolide; streptogramin b); <b>lnua</b>: Lincosamide nucleotidyltransferase, (Resistance profile: lincomycin; <b>mphc</b>: Macrolide phosphotransferase, Resistance profile: macrolide); <b>msra</b>: ABC transporter system, Macrolide-Lincosamide-Streptogramin B efflux pump, (Resistance profile: lincosamide; macrolide; streptogramin_b); <b>nora</b>: multidrug efflux protein NorA, (Resistance profile: quinolone); <b>pbp2x</b>: penicillin-binding protein 2, (Resistance profile: penicillin); <b>str</b>: streptomycin 3'-phosphotransferase, (Resistance profile: streptomycin); <b>tetk</b>: tetracycline efflux pump, (Resistance profile: tetracycline); <b>tolc</b>: Resistance-nodulation-cell division transporter system, (Resistance profile: acriflavin, aminoglycoside, beta_lactam, glycylcycline, macrolide)].</p

Screening Currency Notes for Microbial Pathogens and Antibiotic Resistance Genes Using a Shotgun Metagenomic Approach

<div><p>Fomites are a well-known source of microbial infections and previous studies have provided insights into the sojourning microbiome of fomites from various sources. Paper currency notes are one of the most commonly exchanged objects and its potential to transmit pathogenic organisms has been well recognized. Approaches to identify the microbiome associated with paper currency notes have been largely limited to culture dependent approaches. Subsequent studies portrayed the use of 16S ribosomal RNA based approaches which provided insights into the taxonomical distribution of the microbiome. However, recent techniques including shotgun sequencing provides resolution at gene level and enable estimation of their copy numbers in the metagenome. We investigated the microbiome of Indian paper currency notes using a shotgun metagenome sequencing approach. Metagenomic DNA isolated from samples of frequently circulated denominations of Indian currency notes were sequenced using Illumina Hiseq sequencer. Analysis of the data revealed presence of species belonging to both eukaryotic and prokaryotic genera. The taxonomic distribution at kingdom level revealed contigs mapping to eukaryota (70%), bacteria (9%), viruses and archae (~1%). We identified 78 pathogens including <i>Staphylococcus aureus</i>, <i>Corynebacterium glutamicum</i>, <i>Enterococcus faecalis</i>, and 75 cellulose degrading organisms including <i>Acidothermus cellulolyticus</i>, <i>Cellulomonas flavigena</i> and <i>Ruminococcus albus</i>. Additionally, 78 antibiotic resistance genes were identified and 18 of these were found in all the samples. Furthermore, six out of 78 pathogens harbored at least one of the 18 common antibiotic resistance genes. To the best of our knowledge, this is the first report of shotgun metagenome sequence dataset of paper currency notes, which can be useful for future applications including as bio-surveillance of exchangeable fomites for infectious agents.</p></div

Comparative GC distribution among all the three samples i.e., C1 vs. C2, C1 vs. C3 and C3 vs. C2 is represented as scatter plots.

<p>The size of the spot denotes the contig length while the color denotes its GC coverage.</p

Chamber Specific Gene Expression Landscape of the Zebrafish Heart

<div><p>The organization of structure and function of cardiac chambers in vertebrates is defined by chamber-specific distinct gene expression. This peculiarity and uniqueness of the genetic signatures demonstrates functional resolution attributed to the different chambers of the heart. Altered expression of the cardiac chamber genes can lead to individual chamber related dysfunctions and disease patho-physiologies. Information on transcriptional repertoire of cardiac compartments is important to understand the spectrum of chamber specific anomalies. We have carried out a genome wide transcriptome profiling study of the three cardiac chambers in the zebrafish heart using RNA sequencing. We have captured the gene expression patterns of 13,396 protein coding genes in the three cardiac chambers—atrium, ventricle and bulbus arteriosus. Of these, 7,260 known protein coding genes are highly expressed (≥10 FPKM) in the zebrafish heart. Thus, this study represents nearly an all-inclusive information on the zebrafish cardiac transcriptome. In this study, a total of 96 differentially expressed genes across the three cardiac chambers in zebrafish were identified. The atrium, ventricle and bulbus arteriosus displayed 20, 32 and 44 uniquely expressing genes respectively. We validated the expression of predicted chamber-restricted genes using independent semi-quantitative and qualitative experimental techniques. In addition, we identified 23 putative novel protein coding genes that are specifically restricted to the ventricle and not in the atrium or bulbus arteriosus. In our knowledge, these 23 novel genes have either not been investigated in detail or are sparsely studied. The transcriptome identified in this study includes 68 differentially expressing zebrafish cardiac chamber genes that have a human ortholog. We also carried out spatiotemporal gene expression profiling of the 96 differentially expressed genes throughout the three cardiac chambers in 11 developmental stages and 6 tissue types of zebrafish. We hypothesize that clustering the differentially expressed genes with both known and unknown functions will deliver detailed insights on fundamental gene networks that are important for the development and specification of the cardiac chambers. It is also postulated that this transcriptome atlas will help utilize zebrafish in a better way as a model for studying cardiac development and to explore functional role of gene networks in cardiac disease pathogenesis.</p></div

Quantitative Real time PCR based validation of chamber-restricted candidate genes.

<p>Atrium-restricted genes (a), (b) and (c). Ventricle-restricted genes (d), (e), (f) and (g). Bulbus arteriosus-restricted genes (h) and (i). See text for detailed information.</p

Developmental and adult tissue expression profile of the putative novel protein coding genes identified in the ventricular chamber.

<p>The heat maps represent spatiotemporal expression profile of 23 ventricle-restricted putative novel protein coding genes across 11 zebrafish developmental stages and 6 adult tissue types. The gene expression data for the embryonic and larval developmental stages were obtained from previous published studies (Ulitsky et al, 2011; Pauli et al, 2012) that utilized whole embryos or larvae. In contrast our dataset was obtained exclusively from the adult heart tissue. Thus, the expression profiles of the novel ventricular-restricted genes may not reflect in parallel to the early ventricular developmental hallmarks. The colour key represents transcripts in the range of 0 for genes with least expression to 5 for transcripts with maximum expression.</p

Data workflow and analysis summary.

<p>An overview of experimental and data analysis workflow adopted in the study for identification of known and putative novel cardiac chamber-restricted protein coding genes. (B) Venn diagram representing the total number of known protein coding genes (7,260) identified with expression level > = 10 FPKM across the three cardiac chambers. (C) A heat map representing expression pattern of 7,260 RefSeq protein coding genes with expression level > = 10 FPKM in the three cardiac chambers. The colour key represents transcripts in the range of 0 for transcripts with least expression to 15 for transcripts with maximum expression.</p

Summary of the RNA sequencing data generation and alignment.

<p>Total number of sequence reads obtained from the three cardiac chambers using RNA sequencing is described. Mapped reads refer to and include all transcripts that aligned back to the zebrafish reference genome (Zv9). The total number of uniquely expressing known protein coding genes as well as <i>de novo</i> transcripts are mentioned.</p