Identifying important microbial and genomic biomarkers for differentiating right- versus left-sided colorectal cancer using random forest models.

BACKGROUND: Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence suggesting that right-sided colorectal cancer (RCC) and left-sided colorectal cancer (LCC) also differ in treatment success and patient outcomes. Biomarkers that differentiate between RCC and LCC are not well-established. Here, we apply random forest (RF) machine learning methods to identify genomic or microbial biomarkers that differentiate RCC and LCC. METHODS: RNA-seq expression data for 58,677 coding and non-coding human genes and count data for 28,557 human unmapped reads were obtained from 308 patient CRC tumour samples. We created three RF models for datasets of human genes-only, microbes-only, and genes-and-microbes combined. We used a permutation test to identify features of significant importance. Finally, we used differential expression (DE) and paired Wilcoxon-rank sum tests to associate features with a particular side. RESULTS: RF model accuracy scores were 90%, 70%, and 87% with area under curve (AUC) of 0.9, 0.76, and 0.89 for the human genomic, microbial, and combined feature sets, respectively. 15 features were identified as significant in the model of genes-only, 54 microbes in the model of microbes-only, and 28 genes and 18 microbes in the model with genes-and-microbes combined. PRAC1 expression was the most important feature for differentiating RCC and LCC in the genes-only model, with HOXB13, SPAG16, HOXC4, and RNLS also playing a role. Ruminococcus gnavus and Clostridium acetireducens were the most important in the microbial-only model. MYOM3, HOXC4, Coprococcus eutactus, PRAC1, lncRNA AC012531.25, Ruminococcus gnavus, RNLS, HOXC6, SPAG16 and Fusobacterium nucleatum were most important in the combined model. CONCLUSIONS: Many of the identified genes and microbes among all models have previously established associations with CRC. However, the ability of RF models to account for inter-feature relationships within the underlying decision trees may yield a more sensitive and biologically interconnected set of genomic and microbial biomarkers.

An epigenetic signature of advanced colorectal cancer metastasis.

Colorectal cancer (CRC) is a leading cause of morbidity and mortality worldwide. The majority of CRC deaths are caused by tumor metastasis, even following treatment. There is strong evidence for epigenetic changes, such as DNA methylation, accompanying CRC metastasis and poorer patient survival. Earlier detection and a better understanding of molecular drivers for CRC metastasis are of critical clinical importance. Here, we identify a signature of advanced CRC metastasis by performing whole genome-scale DNA methylation and full transcriptome analyses of paired primary cancers and liver metastases from CRC patients. We observed striking methylation differences between primary and metastatic pairs. A subset of loci showed coordinated methylation-expression changes, suggesting these are potentially epigenetic drivers that control the expression of critical genes in the metastatic cascade. The identification of CRC epigenomic markers of metastasis has the potential to enable better outcome prediction and lead to the discovery of new therapeutic targets.

Identifying Candidate Circulating RNA Markers for Coronary Artery Disease by Deep RNA-Sequencing in Human Plasma.

Advances in RNA sequencing (RNA-Seq) have facilitated transcriptomic analysis of plasma for the discovery of new diagnostic and prognostic markers for disease. We aimed to develop a short-read RNA-Seq protocol to detect mRNAs, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in plasma for the discovery of novel markers for coronary artery disease (CAD) and heart failure (HF). Circulating cell-free RNA from 59 patients with stable CAD (half of whom developed HF within 3 years) and 30 controls was sequenced to a median depth of 108 paired reads per sample. We identified fragments from 3986 messenger RNAs (mRNAs), 164 long non-coding RNAs (lncRNAs), 405 putative novel lncRNAs and 227 circular RNAs in plasma. Circulating levels of 160 mRNAs, 10 lncRNAs and 2 putative novel lncRNAs were altered in patients compared with controls (absolute fold change >1.2, p < 0.01 adjusted for multiple comparisons). The most differentially abundant transcripts were enriched in mRNAs encoded by the mitochondrial genome. We did not detect any differences in the plasma RNA profile between patients who developed HF compared with those who did not. In summary, we show that mRNAs, lncRNAs and circular RNAs can be reliably detected in plasma by deep RNA-Seq. Multiple coding and non-coding transcripts were altered in association with CAD, including several mitochondrial mRNAs, which may indicate underlying myocardial ischaemia and oxidative stress. If validated, circulating levels of these transcripts could potentially be used to help identify asymptomatic individuals with established CAD prior to an acute coronary event.

Host-Directed Targeting of LincRNA-MIR99AHG Suppresses Intracellular Growth of Mycobacterium tuberculosis.

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) kills 1.6 million people worldwide every year, and there is an urgent need for targeting host-pathogen interactions as a strategy to reduce mycobacterial resistance to current antimicrobials. Noncoding RNAs are emerging as important regulators of numerous biological processes and avenues for exploitation in host-directed therapeutics. Although long noncoding RNAs (lncRNAs) are abundantly expressed in immune cells, their functional role in gene regulation and bacterial infections remains understudied. In this study, we identify an immunoregulatory long intergenic noncoding RNA, lincRNA-MIR99AHG, which is upregulated in mouse and human macrophages upon IL-4/IL-13 stimulation and downregulated after clinical Mtb HN878 strain infection and in peripheral blood mononuclear cells from active TB patients. To evaluate the functional role of lincRNA-MIR99AHG, we used antisense locked nucleic acid (LNA) GapmeR-mediated antisense oligonucleotide (ASO) lncRNA knockdown experiments. Knockdown of lincRNA-MIR99AHG with ASOs significantly reduced intracellular Mtb growth in mouse and human macrophages and reduced pro-inflammatory cytokine production. In addition, in vivo treatment of mice with MIR99AHG ASOs reduced the mycobacterial burden in the lung and spleen. Furthermore, in macrophages, lincRNA-MIR99AHG is translocated to the nucleus and interacts with high affinity to hnRNPA2/B1 following IL-4/IL-13 stimulation and Mtb HN878 infection. Together, these findings identify lincRNA-MIR99AHG as a positive regulator of inflammation and macrophage polarization to promote Mtb growth and a possible target for adjunctive host-directed therapy against TB.

Novel and Annotated Long Noncoding RNAs Associated with Ischemia in the Human Heart.

BACKGROUND: Long noncoding RNAs (lncRNAs) have been implicated in the pathogenesis of cardiovascular diseases. We aimed to identify novel lncRNAs associated with the early response to ischemia in the heart. METHODS AND RESULTS: RNA sequencing data gathered from 81 paired left ventricle samples from patients undergoing cardiopulmonary bypass was collected before and after a period of ischemia. Novel lncRNAs were validated with Oxford Nanopore Technologies long-read sequencing. Gene modules associated with an early ischemic response were identified and the subcellular location of selected lncRNAs was determined with RNAscope. A total of 2446 mRNAs, 270 annotated lncRNAs and one novel lncRNA differed in response to ischemia (adjusted p < 0.001, absolute fold change >1.2). The novel lncRNA belonged to a gene module of highly correlated genes that also included 39 annotated lncRNAs. This module associated with ischemia (Pearson correlation coefficient = -0.69, p = 1 × 10-23) and activation of cell death pathways (p < 6 × 10-9). A further nine novel cardiac lncRNAs were identified, of which, one overlapped five cis-eQTL eSNPs for the gene RWD Domain-Containing Sumoylation Enhancer (RWDD3) and was itself correlated with RWDD3 expression (Pearson correlation coefficient -0.2, p = 0.002). CONCLUSION: We have identified 10 novel lncRNAs, one of which was associated with myocardial ischemia and may have potential as a novel therapeutic target or early marker for myocardial dysfunction.

Consensus molecular subtypes of primary colon tumors and their hepatic metastases.

AIM: This pilot study aimed to evaluate the congruency in consensus molecular subtypes (CMS) of primary colorectal cancer and corresponding hepatic metastasis (HM). MATERIALS & METHODS: RNA was extracted from both primary colorectal cancer and HM from ten patients, sequenced to establish gene-expression profiles and classified into CMS. Clinical data were collected retrospectively. RESULTS: Of the ten patients recruited, nine had primary tumors that were classifiable: seven were CMS2, one was CMS3 and one was CMS4. Five had incongruent classification in the corresponding HM. Three out of the five patients with incongruent classification had received adjuvant chemotherapy prior to hepatic resection. CONCLUSION: A change in CMS type between matched primary and metastatic colorectal tumors is common and may be attributable to chemotherapy.

Insights into circular RNAs: their biogenesis, detection, and emerging role in cardiovascular disease.

Circular RNAs (circRNAs) are an evolutionarily conserved form of noncoding RNA with covalently closed loop structures. Initial studies established a functional role for circRNAs as potent microRNA sponges and many other studies have focussed solely on this. However, the biological functions of most circRNAs are still undetermined and other functional roles are gaining traction. These include protein sponges and regulators, and coding for proteins with an alternative mechanism of translation, potentially opening up a whole new transcriptome. The first step to gaining insight into circRNA function is accurate identification and various software platforms have been developed. Specialized detection software has now evolved into whole bioinformatics pipelines that can be used for detection, de novo identification, functional prediction, and validation of circRNAs. However, few cardiovascular circRNA studies have utilized these tools. This review summarizes current knowledge of circRNA biogenesis, bioinformatic detection tools and the emerging role of circRNAs in cardiovascular disease.

Deep Learning in LncRNAome: Contribution, Challenges, and Perspectives.

Long non-coding RNAs (lncRNA), the pervasively transcribed part of the mammalian genome, have played a significant role in changing our protein-centric view of genomes. The abundance of lncRNAs and their diverse roles across cell types have opened numerous avenues for the research community regarding lncRNAome. To discover and understand lncRNAome, many sophisticated computational techniques have been leveraged. Recently, deep learning (DL)-based modeling techniques have been successfully used in genomics due to their capacity to handle large amounts of data and produce relatively better results than traditional machine learning (ML) models. DL-based modeling techniques have now become a choice for many modeling tasks in the field of lncRNAome as well. In this review article, we summarized the contribution of DL-based methods in nine different lncRNAome research areas. We also outlined DL-based techniques leveraged in lncRNAome, highlighting the challenges computational scientists face while developing DL-based models for lncRNAome. To the best of our knowledge, this is the first review article that summarizes the role of DL-based techniques in multiple areas of lncRNAome.

MinION Sequencing of colorectal cancer tumour microbiomes-A comparison with amplicon-based and RNA-Sequencing.

BACKGROUND: Recent evidence suggests a role for the gut microbiome in the development and progression of many diseases and many studies have been carried out to analyse the microbiome using a variety of methods. In this study, we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples. METHODS: DNA and RNA were extracted from 11 colorectal tumour samples. 16S rRNA amplicon sequencing and MinION sequencing was carried out using genomic DNA, and RNA-Sequencing for meta-transcriptomic analysis. Non-human MinION and RNA-Sequencing reads, and 16S rRNA amplicon sequencing reads were taxonomically classified using a database built from available RefSeq bacterial and archaeal genomes and a k-mer based algorithm in Kraken2. Concordance between the three platforms at different taxonomic levels was tested on a per-sample basis using Spearman's rank correlation. RESULTS: The average number of reads per sample using RNA-Sequencing was greater than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. Taxonomic assignment using 16S sequencing was less reliable beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect greater numbers of phyla and genera in the same samples, compared to 16S sequencing. Bacterial species associated with colorectal cancer, Fusobacterium nucleatum, Parvimonas micra, Bacteroides fragilis and Porphyromonas gingivalis, were detectable using MinION, RNA-Sequencing and 16S rRNA amplicon sequencing data. CONCLUSIONS: Long-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a cost-effective tool for rapid microbiome sequencing in a clinical setting.

Molecular subtyping improves prognostication of Stage 2 colorectal cancer.

BACKGROUND: Post-surgical staging is the mainstay of prognostic stratification for colorectal cancer (CRC). Here, we compare TNM staging to consensus molecular subtyping (CMS) and assess the value of subtyping in addition to stratification by TNM. METHODS: Three hundred and eight treatment-naïve colorectal tumours were accessed from our institutional tissue bank. CMS typing was carried out using tumour gene-expression data. Post-surgical TNM-staging and CMS were analysed with respect to clinicopathologic variables and patient outcome. RESULTS: CMS alone was not associated with survival, while TNM stage significantly explained mortality. Addition of CMS to TNM-stratified tumours showed a prognostic effect in stage 2 tumours; CMS3 tumours had a significantly lower overall survival (P = 0.006). Stage 2 patients with a good prognosis showed immune activation and up-regulation of tumour suppressor genes. CONCLUSIONS: Although stratification using CMS does not outperform TNM staging as a prognostic indicator, gene-expression based subtyping shows promise for improved prognostication in stage 2 CRC.

Metagenomics and transcriptomics data from human colorectal cancer.

Colorectal cancer is a heterogenous and mostly sporadic disease, the development of which is associated with microbial dysbiosis. Recent advances in subtype classification have successfully stratified the disease using molecular profiling. To understand potential relationships between molecular mechanisms differentiating the subtypes of colorectal cancer and composition of gut microbial community, we classified a set of 34 tumour samples into molecular subtypes using RNA-sequencing gene expression profiles and determined relative abundances of bacterial taxonomic groups. To identify bacterial community composition, 16S rRNA amplicon metabarcoding was used as well as whole genome metagenomics of the non-human part of RNA-sequencing data. The generated data expands the collection of the data sources related to the disease and connects molecular aspects of the cancer with environmental impact of microbial community.

Differential Targeting of c-Maf, Bach-1, and Elmo-1 by microRNA-143 and microRNA-365 Promotes the Intracellular Growth of Mycobacterium tuberculosis in Alternatively IL-4/IL-13 Activated Macrophages.

Mycobacterium tuberculosis (Mtb) can subvert the host defense by skewing macrophage activation toward a less microbicidal alternative activated state to avoid classical effector killing functions. Investigating the molecular basis of this evasion mechanism could uncover potential candidates for host directed therapy against tuberculosis (TB). A limited number of miRNAs have recently been shown to regulate host-mycobacterial interactions. Here, we performed time course kinetics experiments on bone marrow-derived macrophages (BMDMs) and human monocyte-derived macrophages (MDMs) alternatively activated with IL-4, IL-13, or a combination of IL-4/IL-13, followed by infection with Mtb clinical Beijing strain HN878. MiR-143 and miR-365 were highly induced in Mtb-infected M(IL-4/IL-13) BMDMs and MDMs. Knockdown of miR-143 and miR-365 using antagomiRs decreased the intracellular growth of Mtb HN878, reduced the production of IL-6 and CCL5 and promoted the apoptotic death of Mtb HN878-infected M(IL-4/IL-13) BMDMs. Computational target prediction identified c-Maf, Bach-1 and Elmo-1 as potential targets for both miR-143 and miR-365. Functional validation using luciferase assay, RNA-pulldown assay and Western blotting revealed that c-Maf and Bach-1 are directly targeted by miR-143 while c-Maf, Bach-1, and Elmo-1 are direct targets of miR-365. Knockdown of c-Maf using GapmeRs promoted intracellular Mtb growth when compared to control treated M(IL-4/IL-13) macrophages. Meanwhile, the blocking of Bach-1 had no effect and blocking Elmo-1 resulted in decreased Mtb growth. Combination treatment of M(IL-4/IL-13) macrophages with miR-143 mimics or miR-365 mimics and c-Maf, Bach-1, or Elmo-1 gene-specific GapmeRs restored Mtb growth in miR-143 mimic-treated groups and enhanced Mtb growth in miR-365 mimics-treated groups, thus suggesting the Mtb growth-promoting activities of miR-143 and miR-365 are mediated at least partially through interaction with c-Maf, Bach-1, and Elmo-1. We further show that knockdown of miR-143 and miR-365 in M(IL-4/IL-13) BMDMs decreased the expression of HO-1 and IL-10 which are known targets of Bach-1 and c-Maf, respectively, with Mtb growth-promoting activities in macrophages. Altogether, our work reports a host detrimental role of miR-143 and miR-365 during Mtb infection and highlights for the first time the role and miRNA-mediated regulation of c-Maf, Bach-1, and Elmo-1 in Mtb-infected M(IL-4/IL-13) macrophages.

Transcriptionally induced enhancers in the macrophage immune response to Mycobacterium tuberculosis infection.

BACKGROUND: Tuberculosis is a life-threatening infectious disease caused by Mycobacterium tuberculosis (M.tb). M.tb subverts host immune responses to build a favourable niche and survive inside of host macrophages. Macrophages can control or eliminate the infection, if acquire appropriate functional phenotypes. Transcriptional regulation is a key process that governs the activation and maintenance of these phenotypes. Among the factors orchestrating transcriptional regulation during M.tb infection, transcriptional enhancers still remain unexplored. RESULTS: We analysed transcribed enhancers in M.tb-infected mouse bone marrow-derived macrophages. We established a link between known M.tb-responsive transcription factors and transcriptional activation of enhancers and their target genes. Our data suggest that enhancers might drive macrophage response via transcriptional activation of key immune genes, such as Tnf, Tnfrsf1b, Irg1, Hilpda, Ccl3, and Ccl4. We report enhancers acquiring transcription de novo upon infection. Finally, we link highly transcriptionally induced enhancers to activation of genes with previously unappreciated roles in M.tb infection, such as Fbxl3, Tapt1, Edn1, and Hivep1. CONCLUSIONS: Our findings suggest the importance of macrophage host transcriptional enhancers during M.tb infection. Our study extends current knowledge of the regulation of macrophage responses to M.tb infection and provides a basis for future functional studies on enhancer-gene interactions in this process.

Contrasting patterns of coding and flanking region evolution in mammalian keratin associated protein-1 genes.

Mammalian genomes contain a number of duplicated genes, and sequence identity between these duplicates can be maintained by purifying selection. However, between-duplicate recombination can also maintain sequence identity between copies, resulting in a pattern known as concerted evolution where within-genome repeats are more similar to each other than to orthologous repeats in related species. Here we investigated the tandemly-repeated keratin-associated protein 1 (KAP1) gene family, KRTAP1, which encodes proteins that are important components of hair and wool in mammals. Comparison of eutherian mammal KRTAP1 gene repeats within and between species shows a strong pattern of concerted evolution. However, in striking contrast to the coding regions of these genes, we find that the flanking regions have a divergent pattern of evolution. This contrast in evolutionary pattern transitions abruptly near the start and stop codons of the KRTAP1 genes. We reveal that this difference in evolutionary patterns is not explained by conventional purifying selection, nor is it likely a consequence of codon adaptation or reverse transcription of KRTAP1-n mRNA. Instead, the evidence suggests that these contrasting patterns result from short-tract gene conversion events that are biased to the KRTAP1 coding region by selection and/or differential sequence divergence. This work demonstrates the power that gene conversion has to finely shape the evolution of repetitive genes, and provides another distinctive pattern of contrasting evolutionary outcomes that results from gene conversion. A greater emphasis on exploring the evolution of multi-gene eukaryotic families will reveal how common different contrasting evolutionary patterns are in gene duplicates.

Transcriptional landscape of Mycobacterium tuberculosis infection in macrophages.

Mycobacterium tuberculosis (Mtb) infection reveals complex and dynamic host-pathogen interactions, leading to host protection or pathogenesis. Using a unique transcriptome technology (CAGE), we investigated the promoter-based transcriptional landscape of IFNγ (M1) or IL-4/IL-13 (M2) stimulated macrophages during Mtb infection in a time-kinetic manner. Mtb infection widely and drastically altered macrophage-specific gene expression, which is far larger than that of M1 or M2 activations. Gene Ontology enrichment analysis for Mtb-induced differentially expressed genes revealed various terms, related to host-protection and inflammation, enriched in up-regulated genes. On the other hand, terms related to dis-regulation of cellular functions were enriched in down-regulated genes. Differential expression analysis revealed known as well as novel transcription factor genes in Mtb infection, many of them significantly down-regulated. IFNγ or IL-4/IL-13 pre-stimulation induce additional differentially expressed genes in Mtb-infected macrophages. Cluster analysis uncovered significant numbers, prolonging their expressional changes. Furthermore, Mtb infection augmented cytokine-mediated M1 and M2 pre-activations. In addition, we identified unique transcriptional features of Mtb-mediated differentially expressed lncRNAs. In summary we provide a comprehensive in depth gene expression/regulation profile in Mtb-infected macrophages, an important step forward for a better understanding of host-pathogen interaction dynamics in Mtb infection.

An Evaluation of Function of Multicopy Noncoding RNAs in Mammals Using ENCODE/FANTOM Data and Comparative Genomics.

Mammalian diversification has coincided with a rapid proliferation of various types of noncoding RNAs, including members of both snRNAs and snoRNAs. The significance of this expansion however remains obscure. While some ncRNA copy-number expansions have been linked to functionally tractable effects, such events may equally likely be neutral, perhaps as a result of random retrotransposition. Hindering progress in our understanding of such observations is the difficulty in establishing function for the diverse features that have been identified in our own genome. Projects such as ENCODE and FANTOM have revealed a hidden world of genomic expression patterns, as well as a host of other potential indicators of biological function. However, such projects have been criticized, particularly from practitioners in the field of molecular evolution, where many suspect these data provide limited insight into biological function. The molecular evolution community has largely taken a skeptical view, thus it is important to establish tests of function. We use a range of data, including data drawn from ENCODE and FANTOM, to examine the case for function for the recent copy number expansion in mammals of six evolutionarily ancient RNA families involved in splicing and rRNA maturation. We use several criteria to assess evidence for function: conservation of sequence and structure, genomic synteny, evidence for transposition, and evidence for species-specific expression. Applying these criteria, we find that only a minority of loci show strong evidence for function and that, for the majority, we cannot reject the null hypothesis of no function.

Genome-wide profiling of transcribed enhancers during macrophage activation.

BACKGROUND: Macrophages are sentinel cells essential for tissue homeostasis and host defence. Owing to their plasticity, macrophages acquire a range of functional phenotypes in response to microenvironmental stimuli, of which M(IFN-γ) and M(IL-4/IL-13) are well known for their opposing pro- and anti-inflammatory roles. Enhancers have emerged as regulatory DNA elements crucial for transcriptional activation of gene expression. RESULTS: Using cap analysis of gene expression and epigenetic data, we identify on large-scale transcribed enhancers in bone marrow-derived mouse macrophages, their time kinetics, and target protein-coding genes. We observe an increase in target gene expression, concomitant with increasing numbers of associated enhancers, and find that genes associated with many enhancers show a shift towards stronger enrichment for macrophage-specific biological processes. We infer enhancers that drive transcriptional responses of genes upon M(IFN-γ) and M(IL-4/IL-13) macrophage activation and demonstrate stimuli specificity of regulatory associations. Finally, we show that enhancer regions are enriched for binding sites of inflammation-related transcription factors, suggesting a link between stimuli response and enhancer transcriptional control. CONCLUSIONS: Our study provides new insights into genome-wide enhancer-mediated transcriptional control of macrophage genes, including those implicated in macrophage activation, and offers a detailed genome-wide catalogue of transcribed enhancers in bone marrow-derived mouse macrophages.

Distinct gut microbiome patterns associate with consensus molecular subtypes of colorectal cancer.

Colorectal cancer (CRC) is a heterogeneous disease and recent advances in subtype classification have successfully stratified the disease using molecular profiling. The contribution of bacterial species to CRC development is increasingly acknowledged, and here, we sought to analyse CRC microbiomes and relate them to tumour consensus molecular subtypes (CMS), in order to better understand the relationship between bacterial species and the molecular mechanisms associated with CRC subtypes. We classified 34 tumours into CRC subtypes using RNA-sequencing derived gene expression and determined relative abundances of bacterial taxonomic groups using 16S rRNA amplicon metabarcoding. 16S rRNA analysis showed enrichment of Fusobacteria and Bacteroidetes, and decreased levels of Firmicutes and Proteobacteria in CMS1. A more detailed analysis of bacterial taxa using non-human RNA-sequencing reads uncovered distinct bacterial communities associated with each molecular subtype. The most highly enriched species associated with CMS1 included Fusobacterium hwasookii and Porphyromonas gingivalis. CMS2 was enriched for Selenomas and Prevotella species, while CMS3 had few significant associations. Targeted quantitative PCR validated these findings and also showed an enrichment of Fusobacterium nucleatum, Parvimonas micra and Peptostreptococcus stomatis in CMS1. In this study, we have successfully associated individual bacterial species to CRC subtypes for the first time.

DES-ncRNA: A knowledgebase for exploring information about human micro and long noncoding RNAs based on literature-mining.

Noncoding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long ncRNAs (lncRNAs), are important players in diseases and emerge as novel drug targets. Thus, unraveling the relationships between ncRNAs and other biomedical entities in cells are critical for better understanding ncRNA roles that may eventually help develop their use in medicine. To support ncRNA research and facilitate retrieval of relevant information regarding miRNAs and lncRNAs from the plethora of published ncRNA-related research, we developed DES-ncRNA ( www.cbrc.kaust.edu.sa/des_ncrna ). DES-ncRNA is a knowledgebase containing text- and data-mined information from public scientific literature and other public resources. Exploration of mined information is enabled through terms and pairs of terms from 19 topic-specific dictionaries including, for example, antibiotics, toxins, drugs, enzymes, mutations, pathways, human genes and proteins, drug indications and side effects, mutations, diseases, etc. DES-ncRNA contains approximately 878,000 associations of terms from these dictionaries of which 36,222 (5,373) are with regards to miRNAs (lncRNAs). We provide several ways to explore information regarding ncRNAs to users including controlled generation of association networks as well as hypotheses generation. We show an example how DES-ncRNA can aid research on Alzheimer disease and suggest potential therapeutic role for Fasudil. DES-ncRNA is a powerful tool that can be used on its own or as a complement to the existing resources, to support research in human ncRNA. To our knowledge, this is the only knowledgebase dedicated to human miRNAs and lncRNAs derived primarily through literature-mining enabling exploration of a broad spectrum of associated biomedical entities, not paralleled by any other resource.