A global metagenomic map of urban microbiomes and antimicrobial resistance.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

sRNAfrag: a pipeline and suite of tools to analyze fragmentation in small RNA sequencing data.

Fragments derived from small RNAs such as small nucleolar RNAs are biologically relevant but remain poorly understood. To address this gap, we developed sRNAfrag, a modular and interoperable tool designed to standardize the quantification and analysis of small RNA fragmentation across various biotypes. The tool outputs a set of tables forming a relational database, allowing for an in-depth exploration of biologically complex events such as multi-mapping and RNA fragment stability across different cell types. In a benchmark test, sRNAfrag was able to identify established loci of mature microRNAs solely based on sequencing data. Furthermore, the 5' seed sequence could be rediscovered by utilizing a visualization approach primarily applied in multi-sequence-alignments. Utilizing the relational database outputs, we detected 1411 snoRNA fragment conservation events between two out of four eukaryotic species, providing an opportunity to explore motifs through evolutionary time and conserved fragmentation patterns. Additionally, the tool's interoperability with other bioinformatics tools like ViennaRNA amplifies its utility for customized analyses. We also introduce a novel loci-level variance-score which provides insights into the noise around peaks and demonstrates biological relevance by distinctly separating breast cancer and neuroblastoma cell lines after dimension reduction when applied to small nucleolar RNAs. Overall, sRNAfrag serves as a versatile foundation for advancing our understanding of small RNA fragments and offers a functional foundation to further small RNA research. Availability: https://github.com/kenminsoo/sRNAfrag.

Regulome-wide association study identifies genetically driven accessible regions associated with pancreatic cancer risk.

Genome-wide association studies (GWAS) have identified two dozen genetic variants that are associated with the risk of pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy. However, a majority of these variants are located in noncoding regions of the genome, which limits the translation of GWAS findings into clinical applications. The regulome-wide association study (RWAS) is a recently developed method for identifying TF binding-induced accessibility regions for diseases. However, their potential connection to PDAC has yet to be fully explored. We evaluated the associations between genetically predicted levels of chromatin accessibility and risk of PDAC by using pan-cancer chromatin accessibility genetic prediction models. Our analysis included 8275 cases and 6723 controls from the PanScan (I, II, and III) and PanC4 consortia. To further refine our results, we also integrated genes associated to allele-specific accessibility quantitative trait loci (as-aQTL) and TF motifs located in the as-aQTL. We found that 50 chromatin accessibility features were associated with PDAC risk at a false discovery rate (FDR) of less than 0.05. A total of 28 RWAS peaks were identified as conditionally significant. By integrating the results from as-aQTL, motif analysis, and RWAS, we identified candidate causal regulatory elements for two potential chromatin accessibility regions (THCA_89956 and ESCA_89167) that are associated with PDAC risk. Our study identified chromatin accessibility features in noncoding genomic regions that are associated with PDAC risk. We also predicted the associated genes and disrupt motifs. Our findings provide new insights into the regulatory mechanisms of noncoding regions for pancreatic tumorigenesis.

Subverting the Canon: Novel Cancer-Promoting Functions and Mechanisms for snoRNAs.

Small nucleolar RNAs (snoRNAs) constitute a class of intron-derived non-coding RNAs ranging from 60 to 300 nucleotides. Canonically localized in the nucleolus, snoRNAs play a pivotal role in RNA modifications and pre-ribosomal RNA processing. Based on the types of modifications they involve, such as methylation and pseudouridylation, they are classified into two main families-box C/D and H/ACA snoRNAs. Recent investigations have revealed the unconventional synthesis and biogenesis strategies of snoRNAs, indicating their more profound roles in pathogenesis than previously envisioned. This review consolidates recent discoveries surrounding snoRNAs and provides insights into their mechanistic roles in cancer. It explores the intricate interactions of snoRNAs within signaling pathways and speculates on potential therapeutic solutions emerging from snoRNA research. In addition, it presents recent findings on the long non-coding small nucleolar RNA host gene (lncSNHG), a subset of long non-coding RNAs (lncRNAs), which are the transcripts of parental SNHGs that generate snoRNA. The nucleolus, the functional epicenter of snoRNAs, is also discussed. Through a deconstruction of the pathways driving snoRNA-induced oncogenesis, this review aims to serve as a roadmap to guide future research in the nuanced field of snoRNA-cancer interactions and inspire potential snoRNA-related cancer therapies.

Splicing transcriptome-wide association study to identify splicing events for pancreatic cancer risk.

A large proportion of the heritability of pancreatic cancer risk remains elusive, and the contribution of specific mRNA splicing events to pancreatic cancer susceptibility has not been systematically evaluated. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies (Enet, LASSO and MCP) to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for pancreatic cancer risk by assessing 8275 pancreatic cancer cases and 6723 controls of European ancestry. Data from 305 subjects of whom the majority are of European descent in the Genotype-Tissue Expression Project (GTEx) were used and both cis-acting and promoter-enhancer interaction regions were considered to build these models. We identified nine splicing events of seven genes (ABO, UQCRC1, STARD3, ETAA1, CELA3B, LGR4 and SFT2D1) that showed an association of genetically predicted expression with pancreatic cancer risk at a false discovery rate ≤0.05. Of these genes, UQCRC1 and LGR4 have not yet been reported to be associated with pancreatic cancer risk. Fine-mapping analyses supported likely causal associations corresponding to six splicing events of three genes (P4HTM, ABO and PGAP3). Our study identified novel genes and splicing events associated with pancreatic cancer risk, which can improve our understanding of the etiology of this deadly malignancy.

T-cell activation decreases miRNA-15a/16 levels to promote MEK1-ERK1/2-Elk1 signaling and proliferative capacity.

While miRs have been extensively studied in the context of malignancy and tumor progression, their functions in regulating T-cell activation are less clear. In initial studies, we found reduced levels of miR-15a/16 at 3 to 18 h post-T-cell receptor (TCR) stimulation, suggesting a role for decreased levels of this miR pair in shaping T-cell activation. To further explore this, we developed an inducible miR15a/16 transgenic mouse model to determine how elevating miR-15a/16 levels during early stages of activation would affect T-cell proliferation and to identify TCR signaling pathways regulated by this miR pair. Doxycycline (DOX)-induced expression of miR-15a/16 from 0 to 18 h post-TCR stimulation decreased ex vivo T-cell proliferation as well as in vivo antigen-specific T-cell proliferation. We also combined bioinformatics and proteomics approaches to identify the mitogen-activated protein kinase kinase 1 (MEK1) (Map2k1) as a target of miR-15a/16. MEK1 targeting by miR-15a/16 was confirmed using miR mimics that decreased Map2k1 mRNA containing the 3'-UTR target nucleotide sequence (UGCUGCUA) but did not decrease Map2k1 containing a mutated control sequence (AAAAAAAA). Phosphorylation of downstream signaling molecules, extracellular signal-regulated protein kinase 1/2 (ERK1/2) and Elk1, was also decreased by DOX-induced miR-15a/16 expression. In addition to MEK1, ERK1 was subsequently found to be targeted by miR-15a/16, with DOX-induced miR-15a/16 reducing total ERK1 levels in T cells. These findings show that TCR stimulation reduces miR-15a/16 levels at early stages of T-cell activation to facilitate increased MEK1 and ERK1, which promotes the sustained MEK1-ERK1/2-Elk1 signaling required for optimal proliferation.

Global landscape of SARS-CoV-2 mutations and conserved regions.

BACKGROUND: At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management. METHODS: 10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence. RESULTS: Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively. CONCLUSION: Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

Circulating microRNA Biomarker for Detecting Breast Cancer in High-Risk Benign Breast Tumors.

High-risk benign breast tumors are known to develop breast cancer at high rates. However, it is still controversial whether they should be removed during diagnosis or followed up until cancer development becomes evident. Therefore, this study sought to identify circulating microRNAs (miRNAs) that could serve as detection markers of cancers arising from high-risk benign tumors. Small RNA-seq was performed using plasma samples collected from patients with early-stage breast cancer (CA) and high-risk (HB), moderate-risk (MB), and no-risk (Be) benign breast tumors. Proteomic profiling of CA and HB plasma was performed to investigate the underlying functions of the identified miRNAs. Our findings revealed that four miRNAs, hsa-mir-128-3p, hsa-mir-421, hsa-mir-130b-5p, and hsa-mir-28-5p, were differentially expressed in CA vs. HB and had diagnostic power to discriminate CA from HB with AUC scores greater than 0.7. Enriched pathways based on the target genes of these miRNAs indicated their association with IGF-1. Furthermore, the Ingenuity Pathway Analysis performed on the proteomic data revealed that the IGF-1 signaling pathway was significantly enriched in CA vs. HB. In conclusion, these findings suggest that these miRNAs could potentially serve as biomarkers for detecting early-stage breast cancer from high-risk benign tumors by monitoring IGF signaling-induced malignant transformation.

Exploring Optimal Biomarker Sources: A Comparative Analysis of Exosomes and Whole Plasma in Fasting and Non-Fasting Conditions for Liquid Biopsy Applications.

The study of liquid biopsy with plasma samples is being conducted to identify biomarkers for clinical use. Exosomes, containing nucleic acids and metabolites, have emerged as possible sources for biomarkers. To evaluate the effectiveness of exosomes over plasma, we analyzed the small non-coding RNAs (sncRNAs) and metabolites extracted from exosomes in comparison to those directly extracted from whole plasma under both fasting and non-fasting conditions. We found that sncRNA profiles were not affected by fasting in either exosome or plasma samples. Our results showed that exosomal sncRNAs were found to have more consistent profiles. The plasma miRNA profiles contained high concentrations of cell-derived miRNAs that were likely due to hemolysis. We determined that certain metabolites in whole plasma exhibited noteworthy concentration shifts in relation to fasting status, while others did not. Here, we propose that (1) fasting is not required for a liquid biopsy study that involves both sncRNA and metabolomic profiling, as long as metabolites that are not influenced by fasting status are selected, and (2) the utilization of exosomal RNAs promotes robust and consistent findings in plasma samples, mitigating the impact of batch effects derived from hemolysis. These findings advance the optimization of liquid biopsy methodologies for clinical applications.

RNA-Sequencing based analysis of bovine endometrium during the maternal recognition of pregnancy.

BACKGROUND: Maternal recognition is the crucial step for establishing pregnancy in cattle. This study aims to identify endometrial genes and biological pathways involved in the maternal recognition of pregnancy. Caruncular endometrial tissues were collected from Day 15-17 of gestation (pregnant), non-pregnant (absence of conceptus), and cyclic (non-bred) heifers. RESULTS: Total RNAs were isolated from the caruncular endometrial tissues of pregnant, non-pregnant, and cyclic heifers, and were subjected to high-throughput RNA-sequencing. The genes with at least two-fold change and Benjamini and Hochberg p-value ≤ 0.05 were considered differentially expressed genes and further confirmed with quantitative real-time PCR. A total of 107 genes (pregnant vs cyclic) and 98 genes (pregnant vs non-pregnant) were differentially expressed in the pregnant endometrium. The most highly up-regulated genes in the pregnant endometrium were MRS2, CST6, FOS, VLDLR, ISG15, IFI6, MX2, C15H11ORF34, EIF3M, PRSS22, MS4A8, and TINAGL1. Interferon signaling, immune response, nutrient transporter, synthesis, and secretion of proteins are crucial pathways during the maternal recognition of pregnancy. CONCLUSIONS: The study demonstrated that the presence of conceptus at Day 15-17 of gestation affects the endometrial gene expression related to endometrial remodeling, immune response, nutrients and ion transporters, and relevant signaling pathways in the caruncular region of bovine endometrium during the maternal recognition of pregnancy.

Annotating unknown species of urban microorganisms on a global scale unveils novel functional diversity and local environment association.

In urban ecosystems, microbes play a key role in maintaining major ecological functions that directly support human health and city life. However, the knowledge about the species composition and functions involved in urban environments is still limited, which is largely due to the lack of reference genomes in metagenomic studies comprises more than half of unclassified reads. Here we uncovered 732 novel bacterial species from 4728 samples collected from various common surface with the matching materials in the mass transit system across 60 cities by the MetaSUB Consortium. The number of novel species is significantly and positively correlated with the city population, and more novel species can be identified in the skin-associated samples. The in-depth analysis of the new gene catalog showed that the functional terms have a significant geographical distinguishability. Moreover, we revealed that more biosynthetic gene clusters (BGCs) can be found in novel species. The co-occurrence relationship between BGCs and genera and the geographical specificity of BGCs can also provide us more information for the synthesis pathways of natural products. Expanded the known urban microbiome diversity and suggested additional mechanisms for taxonomic and functional characterization of the urban microbiome. Considering the great impact of urban microbiomes on human life, our study can also facilitate the microbial interaction analysis between human and urban environment.

Integrated Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unravels the Influences of SARS-CoV-2 Infections to Cancer Patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious and pathogenic coronavirus that emerged in late 2019 and caused a pandemic of respiratory illness termed as coronavirus disease 2019 (COVID-19). Cancer patients are more susceptible to SARS-CoV-2 infection. The treatment of cancer patients infected with SARS-CoV-2 is more complicated, and the patients are at risk of poor prognosis compared to other populations. Patients infected with SARS-CoV-2 are prone to rapid development of acute respiratory distress syndrome (ARDS) of which pulmonary fibrosis (PF) is considered a sequelae. Both ARDS and PF are factors that contribute to poor prognosis in COVID-19 patients. However, the molecular mechanisms among COVID-19, ARDS and PF in COVID-19 patients with cancer are not well-understood. In this study, the common differentially expressed genes (DEGs) between COVID-19 patients with and without cancer were identified. Based on the common DEGs, a series of analyses were performed, including Gene Ontology (GO) and pathway analysis, protein-protein interaction (PPI) network construction and hub gene extraction, transcription factor (TF)-DEG regulatory network construction, TF-DEG-miRNA coregulatory network construction and drug molecule identification. The candidate drug molecules (e.g., Tamibarotene CTD 00002527) obtained by this study might be helpful for effective therapeutic targets in COVID-19 patients with cancer. In addition, the common DEGs among ARDS, PF and COVID-19 patients with and without cancer are TNFSF10 and IFITM2. These two genes may serve as potential therapeutic targets in the treatment of COVID-19 patients with cancer. Changes in the expression levels of TNFSF10 and IFITM2 in CD14+/CD16+ monocytes may affect the immune response of COVID-19 patients. Specifically, changes in the expression level of TNFSF10 in monocytes can be considered as an immune signature in COVID-19 patients with hematologic cancer. Targeting N6-methyladenosine (m6A) pathways (e.g., METTL3/SERPINA1 axis) to restrict SARS-CoV-2 reproduction has therapeutic potential for COVID-19 patients.

RNA sequencing-based analysis of the magnum tissues revealed the novel genes and biological pathways involved in the egg-white formation in the laying hen.

BACKGROUND: The mechanism of egg formation in the oviduct of laying hens is tightly controlled; each segment of the oviduct contributes a unique component of the egg. Several genes/proteins are involved in the synthesis of a completely healthy egg. This implies a time- and tissue-specific expression of genes and proteins in the different oviductal segments. We used hens at different physiological stages and time points to understand the transcriptional regulation of egg-white (albumen) synthesis and secretion onto the eggs in the magnum of laying hens. This study used Next-Generation Sequencing and quantitative real-time PCR (qPCR) to detect the novel genes and the cognate biological pathways that regulate the major events during the albumen formation. RESULTS: Magnum tissues collected from laying (n = 5 each at 3 h post-ovulation, p.o. and 15-20 h p.o.), non-laying (n = 4), and molting (n = 5) hens were used for differential gene expression analyses. A total of 540 genes (152 upregulated and 388 down-regulated) were differentially expressed at 3 h p.o. in the magnum of laying hens. Kyoto Encyclopedia of Genes and Genomes pathways analysis of the 152 upregulated genes revealed that glycine, serine, and threonine metabolism was the most-enriched biological pathway. Furthermore, the top two most enriched keywords for the upregulated genes were amino-acid biosynthesis and proteases. Nine candidate genes associated with albumen formation were validated with qPCR to have differential expression in laying, non-laying, and molting hens. Proteases such as TMPRSS9, CAPN2, MMP1, and MMP9 (protein maturation, ECM degradation, and angiogenesis); enzymes such as PSPH, PHGDH, and PSAT1 (amino-acid biosynthesis); RLN3, ACE, and REN (albumen synthesis, secretion and egg transport); and AVD, AvBD11, and GPX3 (antimicrobial and antioxidants) were recognized as essential molecules linked to albumen deposition in the magnum. CONCLUSIONS: This study revealed some novel genes that participate in the signaling pathways for egg-white synthesis and secretion along with some well-known functional genes. These findings help to understand the mechanisms involved in albumen biosynthesis.

Regulation of endoplasmic reticulum stress and trophectoderm lineage specification by the mevalonate pathway in the mouse preimplantation embryo.

Early embryos are vulnerable to environmental insults, such as medications taken by the mother. Due to increasing prevalence of hypercholesterolemia, more women of childbearing potential are taking cholesterol-lowering medications called statins. Previously, we showed that inhibition of the mevalonate pathway by statins impaired mouse preimplantation development, by modulating HIPPO signaling, a key regulator for trophectoderm (TE) lineage specification. Here, we further evaluated molecular events that are altered by mevalonate pathway inhibition during the timeframe of morphogenesis and cell lineage specification. Whole transcriptome analysis revealed that statin treatment dysregulated gene expression underlying multiple processes, including cholesterol biosynthesis, HIPPO signaling, cell lineage specification and endoplasmic reticulum (ER) stress response. We explored mechanisms that link the mevalonate pathway to ER stress, because of its potential impact on embryonic health and development. Upregulation of ER stress-responsive genes was inhibited when statin-treated embryos were supplemented with the mevalonate pathway product, geranylgeranyl pyrophosphate (GGPP). Inhibition of geranylgeranylation was sufficient to upregulate ER stress-responsive genes. However, ER stress-responsive genes were not upregulated by inhibition of ras homolog family member A (RHOA), a geranylgeranylation target, although it interfered with TE specification and blastocyst cavity formation. In contrast, inhibition of Rac family small GTPase 1 (RAC1), another geranylgeranylation target, upregulated ER stress-responsive genes, while it did not impair TE specification or cavity formation. Thus, our study suggests that the mevalonate pathway regulates cellular homeostasis (ER stress repression) and differentiation (TE lineage specification) in preimplantation embryos through GGPP-dependent activation of two distinct small GTPases, RAC1 and RHOA, respectively. Translation of the findings to human embryos and clinical settings requires further investigations.

Focal Point of Fanconi Anemia Signaling.

Among human genetic diseases, Fanconi Anemia (FA) tops all with its largest number of health complications in nearly all human organ systems, suggesting the significant roles played by FA genes in the maintenance of human health. With the accumulated research on FA, the encoded protein products by FA genes have been building up to the biggest cell defense signaling network, composed of not only 22+ FA proteins but also ATM, ATR, and many other non-FA proteins. The FA D2 group protein (FANCD2) and its paralog form the focal point of FA signaling to converge the effects of its upstream players in response to a variety of cellular insults and simultaneously with downstream players to protect humans from contracting diseases, including aging and cancer. In this review, we update and discuss how the FA signaling crucially eases cellular stresses through understanding its focal point.

Bacterial Diversity Correlates with Overall Survival in Cancers of the Head and Neck, Liver, and Stomach.

One in five cancers is attributed to infectious agents, and the extent of the impact on the initiation, progression, and disease outcomes may be underestimated. Infection-associated cancers are commonly attributed to viral, and to a lesser extent, parasitic and bacterial etiologies. There is growing evidence that microbial community variation rather than a single agent can influence cancer development, progression, response to therapy, and outcome. We evaluated microbial sequences from a subset of infection-associated cancers-namely, head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and stomach adenocarcinoma (STAD) from The Cancer Genome Atlas (TCGA). A total of 470 paired tumor and adjacent normal samples were analyzed. In STAD, concurrent presence of EBV and Selemonas sputigena with a high diversity index were associated with poorer survival (HR: 2.23, 95% CI 1.26-3.94, p = 0.006 and HR: 2.31, 95% CI 1.1-4.9, p = 0.03, respectively). In LIHC, lower microbial diversity was associated with poorer overall survival (HR: 2.57, 95% CI: 1.2, 5.5, p = 0.14). Bacterial within-sample diversity correlates with overall survival in infection-associated cancers in a subset of TCGA cohorts.

Current trend and development in bioinformatics research.

This is an editorial report of the supplements to BMC Bioinformatics that includes 6 papers selected from the BIOCOMP'19-The 2019 International Conference on Bioinformatics and Computational Biology. These articles reflect current trend and development in bioinformatics research.

Development of predicitve models to distinguish metals from non-metal toxicants, and individual metal from one another.

BACKGROUND: Evaluating the toxicity of chemical mixture and their possible mechanism of action is still a challenge for humans and other organisms. Microarray classifier analysis has shown promise in the toxicogenomic area by identifying biomarkers to predict unknown samples. Our study focuses on identifying gene markers with better sensitivity and specificity, building predictive models to distinguish metals from non-metal toxicants, and individual metal from one another, and furthermore helping understand underlying toxic mechanisms. RESULTS: Based on an independent dataset test, using only 15 gene markers, we were able to distinguish metals from non-metal toxicants with 100% accuracy. Of these, 6 and 9 genes were commonly down- and up-regulated respectively by most of the metals. 8 out of 15 genes belong to membrane protein coding genes. Function well annotated genes in the list include ADORA2B, ARNT, S100G, and DIO3. Also, a 10-gene marker list was identified that can discriminate an individual metal from one another with 100% accuracy. We could find a specific gene marker for each metal in the 10-gene marker list. Function well annotated genes in this list include GSTM2, HSD11B, AREG, and C8B. CONCLUSIONS: Our findings suggest that using a microarray classifier analysis, not only can we create diagnostic classifiers for predicting an exact metal contaminant from a large scale of contaminant pool with high prediction accuracy, but we can also identify valuable biomarkers to help understand the common and underlying toxic mechanisms induced by metals.

Tissue-associated microbial detection in cancer using human sequencing data.

Cancer is one of the leading causes of morbidity and mortality in the globe. Microbiological infections account for up to 20% of the total global cancer burden. The human microbiota within each organ system is distinct, and their compositional variation and interactions with the human host have been known to attribute detrimental and beneficial effects on tumor progression. With the advent of next generation sequencing (NGS) technologies, data generated from NGS is being used for pathogen detection in cancer. Numerous bioinformatics computational frameworks have been developed to study viral information from host-sequencing data and can be adapted to bacterial studies. This review highlights existing popular computational frameworks that utilize NGS data as input to decipher microbial composition, which output can predict functional compositional differences with clinically relevant applicability in the development of treatment and prevention strategies.

miR-125 family regulates XIRP1 and FIH in response to myocardial infarction.

MicroRNAs (miRNAs) are powerful regulators of protein expression. Many play important roles in cardiac development and disease. While several miRNAs and targets have been well characterized, the abundance of miRNAs and the numerous potential targets for each suggest that the vast majority of these interactions have yet to be described. The goal of this study was to characterize miRNA expression in the mouse heart after coronary artery ligation (LIG) and identify novel mRNA targets altered during the initial response to ischemic stress. We performed small RNA sequencing (RNA-Seq) of ischemic heart tissue 1 day and 3 days after ligation and identified 182 differentially expressed miRNAs. We then selected relevant mRNA targets from all potential targets by correlating miRNA and mRNA expression from a corresponding RNA-Seq data set. From this analysis we chose to focus, as proof of principle, on two miRNAs from the miR-125 family, miR-125a and miR-351, and two of their potential mRNA targets, Xin actin-binding repeat-containing protein 1 (XIRP1) and factor inhibiting hypoxia-inducible factor (FIH). We found miR-125a to be less abundant and XIRP1 more abundant after ligation. In contrast, the related murine miRNA miR-351 was substantially upregulated in response to ischemic injury, and FIH expression correspondingly decreased. Luciferase reporter assays confirmed direct interactions between these miRNAs and targets. In summary, we utilized a correlative analysis strategy combining miRNA and mRNA expression data to identify functional miRNA-mRNA relationships in the heart after ligation. These findings provide insight into the response to ischemic injury and suggest future therapeutic targets.