Project description:Crohn’s disease, which can affect any part of the gastrointestinal tract, is characterised by the formation of strictures and frequently requires surgery to manage symptoms, which increases morbidity and mortality. A better understanding of the strictured state is therefore needed to identify new targets for therapy. The aim of this study was to identify molecular signals of the strictured state. Sections from proximal, strictured and distal regions of resected colonoic tissue from Crohn’s disease patients undergoing surgery for stricturing disease, were collected in RNAlater. RNA was extracted using RNeasy columns (Qiagen) and quantified by Qubit (Life Technologies). 0.5ng RNA was used to prepare uniquely indexed cDNA QIAseq UPX 3’ Transcriptome libraries according to manufacturer’s instructions (Qiagen). Libraries were quantified and quality-controlled using the QIAseq Library Quant Assay Kit and tapestation analysis and sequenced on the Nextseq Illumina platform using the illumina sequencing primer and PhiX 15% to a depth of 1-3milion reads/sample. Read numbers were set as 101 bp (R1) x 51 bp (R2). Fastq files were obtained through BaseSpace and reads de-multiplexed, aligned to the human genome version GRCh38, quantified and normalised by the TPM method using the CLC Genomics Workbench (Qiagen). The following differential expression procedure was performed across the three sites. TPM normalised values were log-transformed with a pseudocount of 1 added. Transcripts with < 1 transformed count in any sample were excluded from further analysis, as were transcripts with low variance (defined as less than 10% unique counts across both conditions and greater than a 19:1 ratio of the most frequent count to the second most frequent across both conditions). Differential expression analysis between tissues was conducted with the limma package. Library size was estimated using reduced maximum likelihood estimator with 500 iterations. Initial fitting was performed using a robust M-estimation, and moderated test statistics computed by empirical Bayes. A FDR corrected p value <0.05 was considered and filtered for further downstream data analysis. Partial least squares discriminant analysis (PLS-DA) modelling was also performed on the genes, giving a Variable Importance in Projection (VIP) score was used to further rank the genes. VIP is a measure of a variable's importance in the PLS-DA model. To understand the biological significance and pathways, we also performed enrichment analysis using EnrichR with Gene ontology biological pathways, Wiki pathways and Kyoto Encyclopaedia of Genes and Genomes (KEGG). For those genes that showed strong statistical and biological relevance we assessed their combined ability to predict stricture vs non stricture using the Random Foreset Method of Area under the curve analysis.

Project description:The objective of the study was to understand gene expression patterns and pathways that relate to Endoscopic Remission and Histologic remission in IBD as defined by different endoscopic and histological disease activity scores. Colonic Endoscopic biopsies were collected in RNAlater from 21 UC patients undergoingcolonoscopies withthe endocytoscope CF- Y-0058-1 prototype Olympus, Japan). RNA was extracted using RNeasy columns (Qiagen) and quantified by Qubit (Life Technologies). 0.5ng RNA was used to prepare uniquely indexed cDNA QIAseq UPX 3’ Transcriptome libraries according to manufacturer’s instructions (Qiagen). Libraries were quantified and quality-controlled using the QIAseq Library Quant Assay Kit and tapestation analysis and sequenced on the Miseq and Nextseq Illumina platforms using the illumina sequencing primer and PhiX 15% to a depth of 1-3milion reads/sample. Read numbers were set as 101 bp (R1) x 51 bp (R2). Fastq files were obtained through BaseSpace and reads de-multiplexed, aligned to human genome GRCh38, quantified and normalised by the TPM method using the CLC Genomics Workbench (Qiagen). The following differential expression procedure was performed for participants classified as healed versus non-healed according different histologic and endoscpic scores which included the histological scores: Nancy and Robarts Histological Index (RHI) as well as the mayo endoscopic score (MES) and the endocytoscopy score system (ECSS). Normalised values were log-transformed with a pseudocount of 1 added. Transcripts with < 1 transformed count in any sample were excluded from further analysis, as were transcripts with low variance (defined as less than 10% unique counts across both conditions and greater than a 19:1 ratio of the most frequent count to the second most frequent across both conditions). Differential expression analysis between conditions was conducted with the limma package. Library size was estimated using reduced maximum likelihood estimator with 500 iterations. Initial fitting was performed using a robust M-estimation, and moderated test statistics computed by empirical Bayes. A FDR corrected p value <0.05 was considered and filtered for further downstream data analysis. Partial least squares discriminant analysis (PLS-DA) modelling was performed on these genes and a variable Importance in Projection (VIP) score of >1 was used to further filter the genes. To understand the biological significance and pathways, we also performed enrichment analysis using EnrichR involving three databases: Gene ontology, Wiki pathways and Kyoto Encyclopaedia of Genes and Genomes (KEGG).

Project description:The objective of the study was to understand gene expression patterns and pathways that relate to Endoscopic Remission and Histologic remission in IBD as defined by different endoscopic and histological disease activity scores. Colonic Endoscopic biopsies were collected in RNAlater from 9 Crohn's disease patients undergoing colonoscopies with the endocytoscope CF- Y-0058-1 prototype Olympus, Japan). RNA was extracted using RNeasy columns (Qiagen) and quantified by Qubit (Life Technologies). 0.5ng RNA was used to prepare uniquely indexed cDNA QIAseq UPX 3’ Transcriptome libraries according to manufacturer’s instructions (Qiagen). Libraries were quantified and quality-controlled using the QIAseq Library Quant Assay Kit and tapestation analysis and sequenced on the Miseq and Nextseq Illumina platforms using the illumina sequencing primer and PhiX 15% to a depth of 1-3milion reads/sample. Read numbers were set as 101 bp (R1) x 51 bp (R2). Fastq files were obtained through BaseSpace and reads de-multiplexed, aligned to human genome GRCh38, quantified and normalised by the TPM method using the CLC Genomics Workbench (Qiagen). The following differential expression procedure was performed for participants classified as healed versus non-healed according different histologic and endoscpic scores which included the histological scores: Nancy and Robarts Histological Index (RHI) as well as SES-CD, Modified Riley and and the endocytoscopy score system (ECSS). Normalised values were log-transformed with a pseudocount of 1 added. Transcripts with < 1 transformed count in any sample were excluded from further analysis, as were transcripts with low variance (defined as less than 10% unique counts across both conditions and greater than a 19:1 ratio of the most frequent count to the second most frequent across both conditions). Differential expression analysis between conditions was conducted with the limma package. Library size was estimated using reduced maximum likelihood estimator with 500 iterations. Initial fitting was performed using a robust M-estimation, and moderated test statistics computed by empirical Bayes. A FDR corrected p value <0.05 was considered and filtered for further downstream data analysis. Partial least squares discriminant analysis (PLS-DA) modelling was performed on these genes and a variable Importance in Projection (VIP) score of >1 was used to further filter the genes. To understand the biological significance and pathways, we also performed enrichment analysis using EnrichR involving three databases: Gene ontology, Wiki pathways and Kyoto Encyclopaedia of Genes and Genomes (KEGG).

Project description:The objective of this study was to identify pre-treatment colonic gene expression patterns in patients with inflammatory bowel disease (Ulcerative Colitis and colonic Crohn’s disease) that are predictive of a good versus poor response to treatment with the bioloic anti-TNFa. By identifying key pathways that are altered in responders versus non-responders we also aimed to propose novel targets for therapy. Pre-treatment colonic endoscopic biopsies were collected in RNAlater from 22 patients (14 CD and 8 UC) who were starting anti-TNFa therapy. RNA was extracted using RNeasy columns (Qiagen) and quantified by Qubit (Life Technologies). 0.5ng RNA was used to prepare uniquely indexed cDNA QIAseq UPX 3’ Transcriptome libraries according to manufacturer’s instructions (Qiagen). Libraries were quantified and quality-controlled using the QIAseq Library Quant Assay Kit and tapestation analysis and sequenced on the Miseq and Nextseq Illumina platforms using the illumina sequencing primer and PhiX 15% to a depth of 1-3milion reads/sample. Read numbers were set as 101 bp (R1) x 51 bp (R2). Fastq files were obtained through BaseSpace and reads de-multiplexed, aligned to human genome GRCh38, quantified and normalised by the TPM method using the CLC Genomics Workbench (Qiagen). The following differential expression procedure was performed for participants classified as responders, partial responders or non-responders according to their endoscopic presentation 12 weeks after therapy. For UC patients the Mayo score was used: Responders Mayo= 0, Partial responders 1<= Mayo <3 and Non Responders Mayo >=3. For CD patients % reduction in the SES-CD score was used: Responders >=50% of SES-CD, Partial responders 50%<SES-CD<75%, Non responders SES-CD > 75%. Normalised values were log-transformed with a pseudocount of 1 added. Transcripts with < 1 transformed count in any sample were excluded from further analysis, as were transcripts with low variance (defined as less than 10% unique counts across both conditions and greater than a 19:1 ratio of the most frequent count to the second most frequent across both conditions). Differential expression analysis between conditions was conducted with the limma package. Library size was estimated using reduced maximum likelihood estimator with 500 iterations. Initial fitting was performed using a robust M-estimation, and moderated test statistics computed by empirical Bayes. A FDR corrected p value <0.05 was considered and filtered for further downstream data analysis. Partial least squares discriminant analysis (PLS-DA) modelling was performed on these genes to calculate their variable Importance in Projection (VIP) score. To understand the biological significance and pathways represented in the DEGS, we also performed enrichment analysis using the DAVID Gene Functional Classification Tool (REF I,II). Finally, strongest indicators of response were predicted by Random Forest Area Under the Curve (AUC) analysis.

Project description:We investigated the relationships of the two immune-regulatory plant metabolites salicylic acid (SA) and pipecolic acid (Pip) in the establishment of plant systemic acquired resistance (SAR) in Arabidopsis thaliana induced by the bacterial pathogen Pseudomonas syringae. To characterize the transcriptional SAR response, we used wild-type Col-0 plants, SA-deficient sid2 plants and Pip-deficient ald1 plants and performed RNA-sequencing analyses (Bernsdorff et al., Plant Cell, 2016). SAR establishment in the wild-type is characterized by a strong transcriptional response systemically induced in the foliage that prepares plants for future pathogen attack by pre-activating multiple stages of defense signaling. Whereas systemic Pip elevations are indispensable for SAR and necessary for virtually the whole transcriptional SAR response, a moderate but significant SA-independent component of SAR activation and SAR gene expression is revealed. Arabidopsis thaliana plants were grown individually in pots containing a mixture of soil, vermiculite and sand (8:1:1) in a controlled cultivation chamber with a 10-h day (9 AM to 7 PM; photon flux density 100 mol m-2 s-1) / 14-h night cycle and a relative humidity of 70 %. Day and night temperatures were set to 21C and 18C, respectively. Experiments were performed with 5- to 6-week-old, naive plants exhibiting a uniform appearance. To activate SAR, plants were infiltrated between 10 AM and 12 AM into three lower (1) leaves with suspensions of the bacterial pathogen Pseudomonas syringae pv. maculicola (OD600 = 0.005). Infiltration with 10 mM MgCl2 served as the mock-control treatment. Upper (2) leaves were harvested 48 h after the primary treatment for the determination of systemic gene expression by RNA-seq analyses. Three biologically independent, replicate SAR induction experiments were performed with Col-0 and sid2 plants (experimental set 1), and three other biologically independent experiments with Col-0 and ald1 plants (experimental set 2). In each SAR experiment, at least 6 upper (2) leaves from 6 different plants pre-treated in 1 leaves with Psm (MgCl2) were pooled for one biological Psm- (mock-control) replicate. In this way, 3 biologically independent, replicate samples per treatment and plant genotype were obtained within each SAR set.

Project description:Background. Coral reef communities are undergoing marked declines due to a variety of stressors including climate change, eutrophication, sedimentation, and disease. The sea fan coral, Gorgonia ventalina, is a tractable study system to investigate the hypothesis that stressors compromise immunity and lead to onset of disease. Functional studies in Gorgonia ventalina immunity indicate that several key pathways and cellular responses are involved in response to natural microbial invaders, although to date the functional and regulatory pathways remain largely un-neffectors, the primary line of defense in invertebrates. This study used short-read sequencing (Illumina GAIIx) to identify genes involved in the response of G. ventalina to a naturally occurring Aplanochytrium spp. parasite. Results. De novo assembly of the G. ventalina transcriptome yielded 90,230 contigs of which 40, 142 were annotated. RNA-Seq analysis revealed 210 differentially expressed genes in sea fans exposed to the Aplanochytrium parasite. Differentially expressed genes involved in immunity include pattern recognition molecules, anti-microbial peptides, wound repair, and reactive oxygen species. Gene enrichment analysis indicated eight biological processes were enriched representing 36 genes, largely involved with protein translation and energy production. Conclusions. This is the first report using high-throughput sequencing to characterize the host response of a coral to a natural pathogen. Furthermore, we have generated the first transcriptome for a soft coral species. G. ventalina is a non-model species for which few sequences had been previously described, and we were able to annotate a large number of genes and describe their potential roles in immune function. Expression analysis revealed genes important in invertebrate innate immune pathways, as well as those whose role is previously un-described in cnidarians. This resource will be valuable in characterizing G. ventalina immune response to infection and co-infection of pathogens in the context of environmental change. RNA seq experiment using Illumina GAIIx to compare sea fans exposed to an Aplanochytrium species compared to controls

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RNA-seq comparison of Clostridium acetobutylicum wild-type and pks mutant under batch fermentation conditions.

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