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Results for “bioinformatics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Decoding the Epitranscriptional Landscape from Native RNA Sequences

Sequencing of native RNA and corresponding cDNA was performed using Oxford Nanopore Technology. The % Error of Specific Bases (%ESB) was higher for native RNA than for cDNA, which enabled detection of ribonucleotide modification sites. Based on %ESB differences of the two templates, a bioinformatic tool ELIGOS was developed and applied to rRNAs of E. coli, yeast and human cells. ELIGOS captured 91%, 95%, [~]75%, respectively, of the known variety of RNA methylation sites in these rRNAs. Yeast transcriptomes from different growth conditions were also compared, which identified an association between metabolic adaptation and inferred RNA modifications. ELIGOS was further applied to human transcriptome datasets, which identified the well-known DRACH motif containing N6-methyadenine being located close to 3-untranslated regions of mRNA. Moreover, the RNA G-quadruplex motif was uncovered by ELIGOS. In summary, we have developed an experimental method coupled with bioinformatic software to uncover native RNA modifications and secondary-structures within transcripts.

genetics↗

bioRxiv2019

A systems-based map of human brain cell-type enriched genes and malignancy-associated endothelial changes

Changes in the endothelium of the cerebral vasculature can contribute to inflammatory, thrombotic and malignant disorders. The importance of defining cell type-specific genes and how they are modified in disease is increasingly recognised. Here, we developed a bioinformatics-based approach to identify normal brain cell-enriched genes, using bulk RNAseq data from 238 normal human cortex samples from 2 independent cohorts. We compared endothelial cell-enriched gene profiles with astrocyte, oligodendrocyte and neuron profiles. Global modifications to the endothelium in malignant disease were characterised, using RNAseq data from 516 human lower grade gliomas and 401 human glioblastoma multiforme samples. Lower grade glioma appeared to be an endothelial intermediate between normal brain and glioblastoma multiforme. We identify the most highly glioblastoma multiforme-specific endothelial cell biomarkers, providing potential diagnostic or therapeutic targets. In summary, we provide a roadmap of endothelial cell identity in normal and malignant brain tissue, using a bioinformatics-based method developed to resolve bulk RNAseq datasets into constituent cell type-enriched profiles.

cell biology↗

bioRxiv2019

SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and abundances using DNA barcodes or mitogenomes

The accurate quantification of eukaryotic species abundances from bulk samples remains a key challenge for community description and environmental biomonitoring. We resolve this challenge by combining shotgun sequencing, mapping to reference DNA barcodes or to mitogenomes, and three correction factors: (1) a percent-coverage threshold to filter out false positives, (2) an internal-standard DNA spike-in to correct for stochasticity during sequencing, and (3) technical replicates to correct for stochasticity across sequencing runs. This pipeline achieves a strikingly high accuracy of intraspecific abundance estimates from samples of known composition (mapping to barcodes R2=0.93, mitogenomes R2=0.95) and a high repeatability across environmental-sample replicates (barcodes R2=0.94, mitogenomes R2=0.93). As proof of concept, we sequence arthropod samples from the High Arctic systematically collected over 17 years, detecting changes in species richness, abundance, and phenology using either barcodes or mitogenomes. SPIKEPIPE provides cost-efficient and reliable quantification of eukaryotic communities, with direct application to environmental biomonitoring. Statement of authorshipNMS has been involved in running the BioBasis sampling program for more than twenty years. TR, NMS, DWY, and OO conceived the study and its design. TH led the work in generating all the DNA samples and YJ led the work in assembling and annotating the mitogenomes for the mitochondrial genome reference database. TH led the work in generating the mock communities and bulk samples, with contributions from YJ and JW. YJ and DWY developed the molecular and bioinformatic methods. OO led the modelling of the data. TR and OO wrote the first draft of the manuscript, and all authors contributed substantially to its further improvement. Data accessibility statementShould the manuscript be accepted, the data supporting the results will be archived in an appropriate public repository (Dryad), and the data DOI will be included at the end of the article. The bioinformatic and R scripts and associated data tables will also be made available on github.com.

ecology↗

bioRxiv2019

High-throughput genotyping of a full voltage-gated sodium channel gene via genomic DNA using target capture sequencing and analytical pipeline MoNaS to discover novel insecticide resistance mutations

Insects voltage-gated sodium channel (VGSC) is the primary target site of pyrethroid insecticides. Various amino acid substitutions in the VGSC protein are known to confer insecticide resistance and are selected under insecticide pressure. In the genome, the VGSC gene consists of more than 30 exons sparsely distributed across a large genomic region, which often exceeds 100 kbp. Due to this complex genomic structure of gene VGSC, it is usually challenging to genotype full coding nucleotide sequences (CDSs) of VGSC from individual genomic DNA (gDNA). In this study, we designed biotinylated oligonucleotide probes via annotated CDSs of VGSC of Asian tiger mosquito, Aedes albopictus. The probe set effectively concentrated (>80,000-fold) all targeted regions of gene VGSC from pooled barcoded Illumina libraries each constructed from individual A. albopictus gDNAs. The probe set also captured all homologous VGSC CDSs except tiny exons from the gDNA of other Culicinae mosquitos, A. aegypti and Culex pipiens complex, with comparable efficiency by virtue of the high conservation of VGSC at the nucleotide level. Furthermore, we developed an automated bioinformatic analysis pipeline to genotype VGSC after capture sequencing--MoNaS (Mosquito Na+ channel mutation Search)--which conducts mapping of reads, variant calling, and variant annotation for nonsynonymous mutations. The proposed method and our bioinformatic tool should facilitate the discovery of novel amino acid variants conferring insecticide resistance on VGSC and population genetics studies on resistance alleles with respect to the origin, selection, and migration of both clinically and agriculturally important insect pests.

genetics↗

bioRxiv2019

Mechanistic characterization of RASGRP1 variants identifies an hnRNP K-regulated transcriptional enhancer contributing to SLE susceptibility

Systemic lupus erythematosus (SLE) is an autoimmune disease with a strong genetic component. We recently identified a novel SLE susceptibility locus near RASGRP1, which governs the ERK/MAPK kinase cascade and B-/T-cell differentiation and development. However, precise causal RASGRP1 functional variant(s) and their mechanisms of action in SLE pathogenesis remain undefined. Our goal was to fine-map this locus, prioritize genetic variants according to likely functionality, experimentally validate the contribution of three SNPs to SLE risk, and experimentally determine their biochemical mechanisms of action. We performed a meta-analysis across six Asian and European cohorts (9,529 cases; 22,462 controls), followed by in silico bioinformatic and epigenetic analyses to prioritize potentially functional SNPs. We experimentally validated the functional significance and mechanism of action of three SNPs in cultured T-cells. Meta-analysis identified 18 genome-wide significant (p<5x10-8) SNPs, mostly concentrated in two haplotype blocks, one intronic and the other intergenic. Epigenetic fine-mapping, allelic, eQTL and imbalance analyses predicted three transcriptional regulatory regions with four SNPs (rs7170151, rs11631591-rs7173565, and rs9920715) prioritized for functional validation. Luciferase reporter assays indicated significant allele-specific enhancer activity for intronic rs7170151 and rs11631591-rs7173565 in T-lymphoid (Jurkat) cells, but not in HEK293 cells. Following up with EMSA, mass spectrometry and ChIP-qPCR, we detected allele-dependent interactions between heterogeneous nuclear ribonucleoprotein K (hnRNP-K) and rs11631591. Furthermore, inhibition of hnRNP-K in Jurkat and primary T-cells downregulated RASGRP1 and ERK/MAPK signaling. Comprehensive association, bioinformatics, and epigenetic analyses yielded putative functional variants of RASGRP1, which were experimentally validated. Notably, intronic variant (rs11631591) is located in a cell type-specific enhancer sequence, where its risk allele binds to the hnRNP-K protein and modulates RASGRP1 expression in Jurkat and primary T-cells. As risk allele dosage of rs11631591 correlates with increased RASGRP1 expression and ERK activity, we suggest that this SNP may underlie SLE risk at this locus.

genetics↗

bioRxiv2019

Identifying drug combinations of individual cancer patients by personalized drug controller method

Treating cancer in precision medicine, it is important to identify the personalized combinational drugs under consideration of the individual heterogeneity. Many bioinformatics tools for the personalized driver genes identification have presented promising clues in determining candidate personalized drug targets for the personalized drugs discovery. However, it has not been studied how to fill the gap between personalized driver genes identification and personalized combinational drugs discovery. In this work, we developed a novel algorithm of structure network Controllability-based Personalized driver Genes and combinational Drug identification (CPGD), aiming to mine the personalized driver genes and identify the combinational drugs of an individual cancer patient. On two benchmark cancer datasets, the performance of CPGD for predicting the clinical efficacious combinational drugs is superior to that of other state-of-the-art driver gene-focus algorithms in terms of precision accuracy. In particular, by quantifying and referring the relationships between target genes of pairwise combinatorial drugs and disease module genes on breast cancer data set, CPGD can significantly divide patients into the discriminative high-risk and low-risk groups for risk asessment in combination therapy. In addition, CPGD can further enhance cancer subtyping by providing computationally personalized side effect signatures for individual patients. Collectively, CPGD provided a new and effecient bioinformatics tool from structure network controllability perspective for discovering personalized combinational drugs with personalized side effect consideration, so as to effectively support personalized risk assessement and disease subtyping. SignificanceIt is quite challenging to predict personalized combinational drugs rather than patient-cohort s drugs based on cancer omics data. In this work, a novel structure network Controllability-based algorithm (CPGD) from feedback vertex sets control perspective was developed, for discovering efficacious combinational drugs of an individual cancer patient by targeting the personalized driver genes. The CPGD contains three methodological advances by exploring more precise mathematical models on high-throughput personalized multi-omics data. The first is that a proper network structure is constructed to characterize the gene regulatory mechanism of an individual patient. The second is that considering the weight information of network edges/relations improves the performance for predicting clinical efficacious combinational drugs compared with other drivers-focus methods. And the third is that proper evaluation metrics for personalized combinational drugs prioritization, personalized risk assessment and disease subtyping are designed when evaluating the performance of CPGD.

systems biology↗

bioRxiv2019

Codon Optimality Confers GC-Rich-Induced Stability to mRNAs in Humans

Codon bias has been implicated as one of the major factors contributing to mRNA stability in yeast. However, the effects of codon-bias on mRNA stability remain unclear in humans. Here we show that human cells possess a mechanism to modulate RNA stability through a unique codon bias different from that of yeast. Bioinformatics analysis showed that codons could be clustered into two distinct groups - codons with G or C at the third base position (GC3) and codons with either A or T at the third base position (AT3); the former stabilizing while the latter destabilizing mRNA. Quantification of codon bias showed that increased GC3 content entails proportionately higher GC content. Through bioinformatics, ribosome profiling and in vitro analysis, we show that decoupling of the effects of codon bias reveals two modes of mRNA regulation, GC3- and GC-content dependent. Employing an immunoprecipitation-based strategy, we identified ILF2 as an RNA binding protein that differentially regulates global mRNA abundances based on codon bias. Our results demonstrate that codon bias is a two-pronged system that governs mRNA abundance.

molecular biology↗

bioRxiv2019

Validation of new tools to identify expanded repeats: an intronic pentamer expansion in RFC1 causes CANVAS

Genomic technologies such as Next Generation Sequencing (NGS) are revolutionizing molecular diagnostics and clinical medicine. However, these approaches have proven inefficient at identifying pathogenic repeat expansions. Here, we apply a collection of bioinformatics tools that can be utilized to identify either known or novel expanded repeat sequences in NGS data. We performed genetic studies of a cohort of 35 individuals from 22 families with a clinical diagnosis of cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS). Analysis of whole genome sequence (WGS) data with five independent algorithms identified a recessively inherited intronic repeat expansion [(AAGGG)exp] in the gene encoding Replication Factor C1 (RFC1). This motif, not reported in the reference sequence, localized to an Alu element and replaced the reference (AAAAG)11 short tandem repeat. Genetic analyses confirmed the pathogenic expansion in 18 of 22 CANVAS families and identified a core ancestral haplotype, estimated to have arisen in Europe over twenty-five thousand years ago. WGS of the four RFC1 negative CANVAS families identified plausible variants in three, with genomic re-diagnosis of SCA3, spastic ataxia of the Charlevoix-Saguenay type and SCA45. This study identified the genetic basis of CANVAS and demonstrated that these improved bioinformatics tools increase the diagnostic utility of WGS to determine the genetic basis of a heterogeneous group of clinically overlapping neurogenetic disorders.

genetics↗

bioRxiv2019

The fungal gene cluster for biosynthesis of the antibacterial agent viriditoxin

BackgroundViriditoxin is one of the classical secondary metabolites produced by fungi and that has antibacterial and other activities; however, the mechanism of its biosynthesis has remained unknown.\n\nResultsHere, a gene cluster responsible for its synthesis was identified, using bioinformatic approaches from two species that produce viriditoxin and then through gene disruption and metabolite profiling. All eight genes in the cluster in Paecilomyces variotii were mutated, revealing their roles in the synthesis of this molecule and establishing its biosynthetic pathway which includes an interesting Baeyer-Villiger monooxygenase catalyzed reaction. Additionally, a candidate catalytically-inactive hydrolase was identified as being required for the stereoselective biosynthesis of (M)-viriditoxin. The localization of two proteins were assessed by fusing these proteins to green fluorescent protein, revealing that at least two intracellular structures are involved in the compartmentalization of the synthesis steps of this metabolite.\n\nConclusionsThe full pathway for synthesis of viriditoxin was established by a combination of genomics, bioinformatics, gene disruption and chemical analysis processes. Hence, this work reveals the basis for the synthesis of an understudied class of fungal secondary metabolites and provides a new model species for understanding the synthesis of biaryl compounds with a chiral axis.

microbiology↗

bioRxiv2019

Translational control of Bcl-2 promotes apoptosis of gastric carcinoma cells

Aberrantly expressed microRNAs (miRNAs) are essential for the tumorigenesis of gastric carcinoma (GC). Nevertheless, an effect of miR-383 on GC cells apoptosis has not been acknowledged previously. Here, we investigated the miR-383 level and anti-apoptotic protein Bcl-2 level in specimens of GC. Bioinformatics analyses was performed, and assay of luciferase-reporter was used for analyzing the relationship between Bcl-2 and miR-383. We analyzed survival of GC cells upon Fluorouracil treatment in an assay of CCK, and measured apoptosis of cells using flow cytometric FITC Annexin V apoptosis detection assay. The level of miR-383 was found extremely lower while the level of Bcl-2 levels was found extremely higher in GC specimens, in comparison with tissue from the adjacent non-tumor region. Additionally, the miR-383 level and Bcl-2 level inversely correlated in specimens of GC. In comparison with miR-383-high subjects, MiR-383-low subjects showed overall lower survival. Bioinformatics analyses revealed that miR-383 targeted the 3-UTR of Bcl-2 mRNA to restrain its translation, demonstrated in a luciferase reporter assay. MiR-383 overexpression inhibited the Bcl-2-mediated survival of cell against apoptosis induced by Fluorouracil, while miR-383 depletion enhanced the cell survival. Together, these data indicate that suppression of miR-383 in GC improves the Bcl-2-mediated cell survival of GC against the chemotherapy-induced cell death. MiR-383 re-expression in cells of GC might augment apoptosis of GC cells during chemotherapy.

cancer biology↗

bioRxiv2019

Fecal microbiota as a non-invasive biomarker to predict the tissue iron accumulation in intestine epithelial cells and liver

Iron is an essential trace mineral for the growth, systemic metabolism, and immune response. Imbalance of tissue iron absorption and storage leads to various diseases. The excessive iron accumulation is associated with inflammation and cancer while iron deficiency leads to growth retardation. Studies investigated in Kenyan infants and school children suggests that both low and high iron intake result in dysbiosis of gut microbiota. This would lead to the disruption of microbial diversity, an increase of pathogen abundance and the induction of intestinal inflammation. Despite this progress, in-depth studies investigating the relationship between iron availability and gut microbiota is not completely explored. In the current study, we established a murine model to study the connection between iron and microbiota by feeding mice with either iron-deprived or -fortified diet. To identify key microbiota related to iron levels, we combined the 16S rRNA amplicon sequencing with the innovated bioinformatic algorithms, such as RDA, co-occurrence, and machine learning to identify key microbiota. Manipulation of iron levels in the diet leads to systemic iron dysregulation and dysbiosis of gut microbiota. The bioinformatic algorithms used here detect five key bacteria that correlate with systemic iron levels. Leveraging on these key microbiotas, we also established a prediction model which could precisely distinguish the individual under either iron-deprived or iron-fortified physiological condition to further prove the link between microbiota and systemic iron homeostasis. This innovated and non-invasive approach could be potentially used for the early diagnosis and therapy of iron-dysregulation related diseases, e.g. anemia, inflammatory disease, fibrosis, and cancers.

microbiology↗

bioRxiv2019

Towards best practice in cancer mutation detection with whole-genome and whole-exome sequencing

Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors introduced at each step of next generation sequencing (NGS). For NGS to successfully improve patient lives, discriminating between true mutations and artifacts is crucial.\n\nWe systematically interrogated somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy. Different types of samples with varying input amount and tumor purity were processed using multiple library construction protocols. Whole-genome and whole-exome sequencing were carried out at six sequencing centers followed by processing with nine bioinformatics pipelines to evaluate their reproducibility. We identified artifacts due to sample and library processing and evaluated the capabilities and limitations of bioinformatics tools for artifact detection and removal.\n\nBy examining the interaction and effect of various wet lab and computational parameters concomitantly, here we recommend actionable best practices for mutation detection in clinical applications using NGS technologies.

genomics↗

bioRxiv2019

De novo β-alanine synthesis in α-proteobacteria involves a β-alanine synthase from the uracil degradation pathway

{beta}-alanine synthesis in bacteria occurs by the decarboxylation of L-aspartate as part of the pantothenate synthesis pathway. In the other two domains of life we find different pathways for {beta}-alanine formation, such as sources from spermine in plants, uracil in yeast and by transamination reactions in insects and mammals. There are also promiscuous decarboxylases that can decarboxylate aspartate. Several bioinformatics studies about the conservation of pantothenate synthesis pathway performed on bacteria, archaea and eukaryotes, have shown a partial conservation of the pathway. As a part of our work, we performed an analysis of the prevalence of reported {beta}-alanine synthesis pathways in 204 genomes of alpha-proteobacteria, with a focus on the Rhizobiales order. The aim of this work was to determine the enzyme or pathway used to synthetize {beta}-alanine in Rhizobium etli CFN42. Our bioinformatics analysis showed that this strain encodes the pyrimidine degradation pathway in its genome. We obtained a {beta}-alanine synthase (amaB) mutant that was a {beta}-alanine auxotroph. Complementation with the cloned gene restored the wild type phenotype. Biochemical analysis confirmed that the recombinant AmaB catalyzed the formation of {beta}-alanine from 3-Ureidopropionic acid in vitro. Here we show a different way in bacteria to produce this essential metabolite.\n\nImportanceSince the pioneer studies of Cronan (1980) on {beta}-alanine synthesis in E. coli, it has been assumed that the decarboxilation of aspartate by the L-aspartate--decarboxylase its the main enzymatic reaction for {beta}-alanine synthesis in bacteria. Forty years later, while we were studying the pantothenic acid synthesis in rhizobia, we demonstrate that a numerous and diverse group of bacteria classified as -proteobacteria synthesize {beta}-alanine de novo using {beta}-alanine synthase, the last enzyme from the reductive pathway for uracil degradation.\n\nAdditionally, there is a growing interest in {beta}-amino acid due to its remarkable pharmaceuticals properties as hypoglycemic, antiketogenic and anti-fungal agents.

microbiology↗

bioRxiv2019

Integrated analysis of different non-coding features across the Sox2 locus implicates a diencephalic enhancer in adult brain expression.

SOX2 is a prominent member of the SOX family of transcription factors that has many different functional roles. This pleiotropy is made possible by multiple regulatory mechanisms that direct appropriate spatial and temporal patterns of expression, and therefore action. The current study concerns the mechanisms that determine Sox2 gene expression in the adult mammalian brain, where SOX2 protein is absent in general, but is selectively and abundantly expressed in a majority of neurons within a ventral diencephalic brain structure, the suprachiasmatic nucleus (SCN). In this study, a comparative bioinformatic and biochemical analysis of different adult rat brain regions was conducted in order to identify SCN-selective (immaturity-related) regulatory mechanisms. The approach incorporated an integrated analysis of Sox2 enhancers, CTCF binding sites, and also expression of the Sox2-overlapping, long non-coding (lnc)RNA, Sox2ot. Initial experiments revealed brain region-specific Sox2ot expression (including region-specific novel transcripts), indicating a significant diversity of Sox2ot expression across the adult brain. However, the pattern and abundance of Sox2ot expression in the SCN, relative to selected control areas of the brain, did not indicate an overt relationship to Sox2 gene expression. Furthermore, although multiple individual Sox2ot exon sequences were shown to overlap annotated Sox2 gene enhancers at different sites across the Sox2 locus, again there was no indication of a SCN-specific functional correlation. Further integration with an analysis of selectively-active CTCF sites within the Sox2 locus directed attention to one site with both a prominent peak of activity in immature brain, and proximity to a functionally-characterized, ventral diencephalic, Sox2 enhancer termed U6 (upstream enhancer 6). Ex vivo analysis of the U6-associated CTCF site revealed SCN-selective CTCF binding, and these sequences were both localized within a known (brain region-selective) super-enhancer. Bioinformatic analysis of the U6 enhancer sequence revealed an abundance of consensus sites for the SCN-selective transcription factor LHX1, and over-expression of this factor enhanced the activity of cloned U6 sequence in transfected cells. However, despite this compelling evidence for a molecular mechanism that underlies adult brain expression of SOX2, further analysis of LHX1-SOX2 co-expression in the SCN confounded this view, indicating the presence of other concurrent mechanisms in the different cell populations of the SCN.

neuroscience↗

bioRxiv2019

Restriction Enzyme Based Enriched L1Hs sequencing (REBELseq)

Long interspersed element-1 retrotransposons (LINE-1 or L1) are ~6 kb mobile DNA elements implicated in the origins of many Mendelian and complex diseases. The actively retrotransposing L1s are mostly limited to the L1 human specific Ta subfamily. In this manuscript, we present REBELseq as a method for the construction of differentially amplified next-generation sequencing libraries and bioinformatic identification of Ta subfamily long interspersed element-1 human specific elements. REBELseq was performed on DNA isolated from NeuN+ neuronal nuclei from postmortem brain samples of 177 individuals and empirically-driven bioinformatic and experimental cutoffs were established. REBELseq reliably identified both known and novel Ta subfamily L1 insertions distributed throughout the genome. Differences in the proportion of individuals possessing a given reference or non-reference retrotransposon insertion were identified. We conclude that REBELseq is an unbiased, whole genome approach to the amplification and detection of Ta subfamily L1 retrotransposons.

genetics↗

bioRxiv2019

Kcnn3 as a target for treating aberrant behaviors in stressed, ethanol-dependent mice

Anxiety and mood disorders are often comorbid with alcohol use disorder (AUD) and are considered critical in the development, maintenance, and reinstatement of alcohol dependence and harmful alcohol-seeking behaviors. Because of this high comorbidity, it is necessary to determine shared and unique genetic factors driving heavy ethanol drinking and anxiety-related behaviors. We used a model of stress-induced escalation of drinking in ethanol dependent C57BL/6J mice to measure anxiety-like behaviors on the marble burying and novelty-suppressed feeding task (NSFT) during abstinence. In order to identify novel pharmacogenetic targets that may lead to more effective treatment, a targeted bioinformatics analysis was used to quantify the expression of K+ channel genes in the amygdala that covary with anxiety-related phenotypes in the well phenotyped and fully sequenced family of BXD strains. A pharmacological approach was used to validate the key bioinformatics finding in ethanol-dependent, stressed C57BL/6J mice during the NSFT. Amygdalar expression of Kcnn3 correlated significantly with just over 40 anxiety-associated phenotypes. Further examination of Kcnn3 expression revealed a strong eigentrait for anxiety-like behaviors in this family. Kcnn3 expression in the amygdala correlated negatively with binge-like and voluntary ethanol drinking. C57BL/6J mice treated with chronic intermittent ethanol exposure and repeated swim stress consumed more ethanol in their home cages and showed hypophagia on the NSFT during prolonged abstinence. Pharmacologically targeting KCNN3 protein with the KCa2 channel positive modulator 1-EBIO decreased ethanol drinking and reduced latency to approach food during the NSFT in ethanol-dependent, stressed mice. Collectively these validation studies provide central nervous system mechanistic links into to the covariance of stress, anxiety, and AUD in the BXD strains. Further this analytical approach is effective in defining targets for treating alcohol dependence and comorbid mood and anxiety disorders.

neuroscience↗

bioRxiv2019

Differential gene expression and functional pathway enrichment in fetal colon cell line CCD 841 CoN (CRL-1790) transfected with miR-mimics miR-18b, miR-142-3p, miR-155, and miR-890.

This report is a bioinformatic analysis of samples from NCBI GEO database series GS132501. It includes previously un-reported data for miR-mimic over-expression of the miRNAs miR-18b, miR-155, miR-142-3p, and miR-890 in the ATCC CRL-1790 cell line. Data analysis was performed using Nanostring nSolver 4.0 and Advanced Analysis Module 2.0 plugin (Nanostring MAN-10030-03). Bioinformatic methods utilized include pathway scoring, differential expression (DE), and gene-set enrichment (GSE) analyses. Findings, with full supplementary data, provide a community resource for effects of dysregulation of these miRNAs in a colon epithelial-like cell line.

molecular biology↗

bioRxiv2019

Targeted Sequencing Workflows for Comprehensive Drug Resistance Profiling of Mycobacterium tuberculosis cultures using Illumina MiSeq and Nanopore MinION: Comparison of analytical and diagnostic performance, turnaround time and cost

The emergence of Mycobacterium tuberculosis strains with complex drug resistance profiles necessitates a rapid and extensive drug susceptibility test for comprehensive guidance of patient treatment. Here, we developed two targeted-sequencing workflows based on Illumina MiSeq and Nanopore MinION for the prediction of drug resistance in M. tuberculosis towards 12 anti-tuberculous agents.\n\nA total of 163 M. tuberculosis cultured isolates collected from Hong Kong and Ethiopia were subjected to a multiplex PCR for simultaneous amplification of 19 drug-resistance associated genetic regions. The amplicons were then barcoded and sequenced in parallel on MiSeq and MinION in respective batch sizes of 24 and 12 samples. Both platforms successfully sequenced all samples with average depths of coverage of 1,127x and 1,649x respectively. Utilizing a self-developed Web-based bioinformatics pipeline, Bacteriochek-TB, for variant analysis, we found that the MiSeq and MinION result could achieve 100% agreement if variants with an allele frequency of <40% reported by MinION were excluded. For drug resistance prediction, both workflows achieved an average sensitivity of 94.8% and specificity of 98.0% when compared with phenotypic drug susceptibility test. The turnaround times for the MiSeq and MinION workflows were 38 and 15 hours, facilitating the delivery of treatment guidance at least 17-18 days earlier than pDST respectively. The higher cost per sample on the MinION platform (US$71.56) versus the MiSeq platform (US$67.83) was attributed to differences in batching capabilities.\n\nOur study demonstrated the interchangeability of MiSeq and MinION sequencing workflows for generation of accurate and actionable results for the treatment of tuberculosis.\n\nImportanceTB therapy involving different combinations of antibiotics have been introduced to address the issue of drug resistance. However, this practice has led to increasing numbers of M. tuberculosis with complex drug resistance profiles. Molecular assays for rapid and comprehensive drug resistance profiling of M. tuberculosis are lacking.\n\nHere, we described targeted-sequencing workflows based on Illumina MiSeq and Nanopore MinION for the detection of drug resistance mutations scattered across 19 genetic regions in M. tuberculosis. A bioinformatics pipeline was also developed to translate raw datasets into clinician-friendly reports that provide comprehensive genetic information for the prediction of drug resistance towards 12 antibiotics.\n\nThis is the first study to evaluate and compare the uses of Illumina and Nanopore platforms for diagnosis of drug-resistant tuberculosis. Remarkably, our diagnostic strategy is compatible with different sequencing platforms that can be applied in diagnostic centres with different levels of throughput and financial support for TB diagnosis.

microbiology↗