Polyphenol- and Glucuronoxylan-Rich Fiber Extract from Birch (Betula sp.) Wood Regulates Colonic Barrier Function and Cell Proliferation in Healthy Rats.

Birch wood-derived fiber extracts containing glucuronoxylans (GX) and polyphenols show potential for various food technological applications. This study investigated the effect of two extracts, GXpoly and pureGX, differing in lignin content on colonic barrier function. Healthy rats were fed diets containing 10% GXpoly, pureGX, or cellulose for 4 weeks. Colon crypt depth was lower in the GX groups than in the control group, but in the proximal colon, the result was significant only in GXpoly. An artificial intelligence approach was established to measure the mucus content and goblet cells. In the distal colon, their amounts were higher in the control group than in the GX groups. All diets had a similar effect on the expression of the tight junction proteins occludin, claudin-1, and claudin-7. GXpoly enhanced the fecal IgA production. Our results suggest that GX-rich extracts could support the colonic barrier and work as functional food ingredients in the future.

The in vitro immunomodulatory effect of multi-walled carbon nanotubes by multilayer analysis.

The study of multi-walled carbon nanotube (MWCNT) induced immunotoxicity is crucial for determining hazards posed to human health. MWCNT exposure most commonly occurs via the airways, where macrophages are first line responders. Here we exploit an in vitro assay, measuring dose-dependent secretion of a wide panel of cytokines, as a measure of immunotoxicity following the non-lethal, multi-dose exposure (IC5, IC10 and IC20) to 7 MWCNTs with different intrinsic properties. We find that a tangled structure, and small aspect ratio are key properties predicting MWCNT induced immunotoxicity, mediated predominantly by IL1B cytokine secretion. To assess the mechanism of action giving rise to MWCNT immunotoxicity, transcriptomics analysis was linked to cytokine secretion in a multilayer model established through correlation analysis across exposure concentrations. This reinforced the finding that tangled MWCNTs have greater immunomodulatory potency, displaying enrichment of immune system, signal transduction and pattern recognition associated pathways. Together our results further elucidate how structure, length and aspect ratio, critical intrinsic properties of MWCNTs, are tied to immunotoxicity.

OxLDL sensitizes platelets for increased formation of extracellular vesicles capable of finetuning macrophage gene expression.

Platelet extracellular vesicles (PEVs) generated upon platelet activation may play a role in inflammatory pathologies such as atherosclerosis. Oxidized low-density lipoprotein (oxLDL), a well-known contributor to atherogenesis, activates platelets and presensitizes them for activation by other agonists. We studied the effect of oxLDL on the secretion, composition, and inflammatory functions of PEVs using contemporary EV analytics. Platelets were activated by co-stimulation with thrombin (T) and collagen (C) ± oxLDL and characterized by high-resolution flow cytometry, nanoparticle tracking analysis, proximity extension assay, western blot, and electron microscopy. The effect of PEVs on macrophage differentiation and functionality was examined by analyzing macrophage surface markers, cytokine secretion, and transcriptome. OxLDL upregulated TC-induced formation of CD61+, P-selectin+ and phosphatidylserine+ PEVs. Blocking the scavenger receptor CD36 significantly suppressed the oxLDL+TC-induced PEV formation, and HDL caused a slight but detectable suppression. The inflammatory protein cargo differed between the PEVs from stimulated and unstimulated platelets. Both oxLDL+TC- and TC-induced PEVs enhanced macrophage HLA-DR and CD86 expression and decreased CD11c expression as well as secretion of several cytokines. Pathways related to cell cycle and regulation of gene expression, and immune system signaling were overrepresented in the differentially expressed genes between TC PEV -treated vs. control macrophages and oxLDL+TC PEV -treated vs. control macrophages, respectively. In conclusion, we speculate that oxLDL and activated platelets contribute to proatherogenic processes by increasing the number of PEVs that provide an adhesive and procoagulant surface, contain inflammatory mediators, and subtly finetune the macrophage gene expression.

Integrated Network Pharmacology Approach for Drug Combination Discovery: A Multi-Cancer Case Study.

Despite remarkable efforts of computational and predictive pharmacology to improve therapeutic strategies for complex diseases, only in a few cases have the predictions been eventually employed in the clinics. One of the reasons behind this drawback is that current predictive approaches are based only on the integration of molecular perturbation of a certain disease with drug sensitivity signatures, neglecting intrinsic properties of the drugs. Here we integrate mechanistic and chemocentric approaches to drug repositioning by developing an innovative network pharmacology strategy. We developed a multilayer network-based computational framework integrating perturbational signatures of the disease as well as intrinsic characteristics of the drugs, such as their mechanism of action and chemical structure. We present five case studies carried out on public data from The Cancer Genome Atlas, including invasive breast cancer, colon adenocarcinoma, lung squamous cell carcinoma, hepatocellular carcinoma and prostate adenocarcinoma. Our results highlight paclitaxel as a suitable drug for combination therapy for many of the considered cancer types. In addition, several non-cancer-related genes representing unusual drug targets were identified as potential candidates for pharmacological treatment of cancer.

PeptiCHIP: A Microfluidic Platform for Tumor Antigen Landscape Identification.

Identification of HLA class I ligands from the tumor surface (ligandome or immunopeptidome) is essential for designing T-cell mediated cancer therapeutic approaches. However, the sensitivity of the process for isolating MHC-I restricted tumor-specific peptides has been the major limiting factor for reliable tumor antigen characterization, making clear the need for technical improvement. Here, we describe our work from the fabrication and development of a microfluidic-based chip (PeptiCHIP) and its use to identify and characterize tumor-specific ligands on clinically relevant human samples. Specifically, we assessed the potential of immobilizing a pan-HLA antibody on solid surfaces via well-characterized streptavidin-biotin chemistry, overcoming the limitations of the cross-linking chemistry used to prepare the affinity matrix with the desired antibodies in the immunopeptidomics workflow. Furthermore, to address the restrictions related to the handling and the limited availability of tumor samples, we further developed the concept toward the implementation of a microfluidic through-flow system. Thus, the biotinylated pan-HLA antibody was immobilized on streptavidin-functionalized surfaces, and immune-affinity purification (IP) was carried out on customized microfluidic pillar arrays made of thiol-ene polymer. Compared to the standard methods reported in the field, our methodology reduces the amount of antibody and the time required for peptide isolation. In this work, we carefully examined the specificity and robustness of our customized technology for immunopeptidomics workflows. We tested this platform by immunopurifying HLA-I complexes from 1 × 106 cells both in a widely studied B-cell line and in patients-derived ex vivo cell cultures, instead of 5 × 108 cells as required in the current technology. After the final elution in mild acid, HLA-I-presented peptides were identified by tandem mass spectrometry and further investigated by in vitro methods. These results highlight the potential to exploit microfluidics-based strategies in immunopeptidomics platforms and in personalized immunopeptidome analysis from cells isolated from individual tumor biopsies to design tailored cancer therapeutic vaccines. Moreover, the possibility to integrate multiple identical units on a single chip further improves the throughput and multiplexing of these assays with a view to clinical needs.

A systematic comparison of data- and knowledge-driven approaches to disease subtype discovery.

Typical clustering analysis for large-scale genomics data combines two unsupervised learning techniques: dimensionality reduction and clustering (DR-CL) methods. It has been demonstrated that transforming gene expression to pathway-level information can improve the robustness and interpretability of disease grouping results. This approach, referred to as biological knowledge-driven clustering (BK-CL) approach, is often neglected, due to a lack of tools enabling systematic comparisons with more established DR-based methods. Moreover, classic clustering metrics based on group separability tend to favor the DR-CL paradigm, which may increase the risk of identifying less actionable disease subtypes that have ambiguous biological and clinical explanations. Hence, there is a need for developing metrics that assess biological and clinical relevance. To facilitate the systematic analysis of BK-CL methods, we propose a computational protocol for quantitative analysis of clustering results derived from both DR-CL and BK-CL methods. Moreover, we propose a new BK-CL method that combines prior knowledge of disease relevant genes, network diffusion algorithms and gene set enrichment analysis to generate robust pathway-level information. Benchmarking studies were conducted to compare the grouping results from different DR-CL and BK-CL approaches with respect to standard clustering evaluation metrics, concordance with known subtypes, association with clinical outcomes and disease modules in co-expression networks of genes. No single approach dominated every metric, showing the importance multi-objective evaluation in clustering analysis. However, we demonstrated that, on gene expression data sets derived from TCGA samples, the BK-CL approach can find groupings that provide significant prognostic value in both breast and prostate cancers.

Viral Molecular Mimicry Influences the Antitumor Immune Response in Murine and Human Melanoma.

Molecular mimicry is one of the leading mechanisms by which infectious agents can induce autoimmunity. Whether a similar mechanism triggers an antitumor immune response is unexplored, and the role of antiviral T cells infiltrating the tumor has remained anecdotal. To address these questions, we first developed a bioinformatic tool to identify tumor peptides with high similarity to viral epitopes. Using peptides identified by this tool, we demonstrated that, in mice, preexisting immunity toward specific viral epitopes enhanced the efficacy of cancer immunotherapy via molecular mimicry in different settings. To understand whether this mechanism could partly explain immunotherapy responsiveness in humans, we analyzed a cohort of patients with melanoma undergoing anti-PD1 treatment who had a high IgG titer for cytomegalovirus (CMV). In this cohort of patients, we showed that high levels of CMV-specific antibodies were associated with prolonged progression-free survival and found that, in some cases, peripheral blood mononuclear cells (PBMC) could cross-react with both melanoma and CMV homologous peptides. Finally, T-cell receptor sequencing revealed expansion of the same CD8+ T-cell clones when PBMCs were expanded with tumor or homologous viral peptides. In conclusion, we have demonstrated that preexisting immunity and molecular mimicry could influence the response to immunotherapies. In addition, we have developed a free online tool that can identify tumor antigens and neoantigens highly similar to pathogen antigens to exploit molecular mimicry and cross-reactive T cells in cancer vaccine development.

Signals of pseudo-starvation unveil the amino acid transporter SLC7A11 as key determinant in the control of Treg cell proliferative potential.

Human CD4+CD25hiFOXP3+ regulatory T (Treg) cells are key players in the control of immunological self-tolerance and homeostasis. Here, we report that signals of pseudo-starvation reversed human Treg cell in vitro anergy through an integrated transcriptional response, pertaining to proliferation, metabolism, and transmembrane solute carrier transport. At the molecular level, the Treg cell proliferative response was dependent on the induction of the cystine/glutamate antiporter solute carrier (SLC)7A11, whose expression was controlled by the nuclear factor erythroid 2-related factor 2 (NRF2). SLC7A11 induction in Treg cells was impaired in subjects with relapsing-remitting multiple sclerosis (RRMS), an autoimmune disorder associated with reduced Treg cell proliferative capacity. Treatment of RRMS subjects with dimethyl fumarate (DMF) rescued SLC7A11 induction and fully recovered Treg cell expansion. These results suggest a previously unrecognized mechanism that may account for the progressive loss of Treg cells in autoimmunity and unveil SLC7A11 as major target for the rescue of Treg cell proliferation.

Effects of In Vivo Gluten Challenge on PBMC Gene Expression Profiles in Diet Treated Celiac Disease.

The pathological mechanisms that lead to the onset and reactivation of celiac disease (CD) remain largely unknown. While gluten free diet (GFD) improves the intestinal damage and associated clinical symptoms in majority of cases, it falls short of providing full recovery. Additionally, late or misdiagnosis is also common as CD presents with a wide range of symptoms. Clear understanding of CD pathogenesis is thus critical to address both diagnostic and treatment concerns. We aimed to study the molecular impact of short gluten exposure in GFD treated CD patients, as well as identify biological pathways that remain altered constitutively in CD regardless of treatment. Using RNAseq profiling of PBMC samples collected from treated CD patients and gluten challenged patient and healthy controls, we explored the peripheral transcriptome in CD patients following a short gluten exposure. Short gluten exposure of just three days was enough to alter the genome-wide PBMC transcriptome of patients. Pathway analysis revealed gluten-induced upregulation of mainly immune response related pathways, both innate and adaptive, in CD patients. We evaluated the perturbation of biological pathways in sample-specific manner. Compared to gluten exposed healthy controls, pathways related to tight junction, olfactory transduction, metabolism of unsaturated fatty acids (such as arachidonic acid), metabolism of amino acids (such as cysteine and glutamate), and microbial infection were constitutively altered in CD patients regardless of treatment, while GFD treatment appears to mostly normalize immune response pathways to "healthy" state. Upstream regulator prediction analysis using differentially expressed genes identified constitutively activated regulators relatively proximal to previously reported CD associated loci, particularly SMARCA4 on 19p13.2 and CSF2 on 5q31. We also found constitutively upregulated genes in CD that are in CD associated genetic loci such as MEF2BNB-MEF2B (BORCS8-MEF2B) on 19p13.11 and CSTB on 21q22.3. RNAseq revealed strong effects of short oral gluten challenge on whole PBMC fraction and constitutively altered pathways in CD PBMC suggesting important factors other than gluten in CD pathogenesis.

Epigenetic alterations in skin homing CD4+CLA+ T cells of atopic dermatitis patients.

T cells expressing the cutaneous lymphocyte antigen (CLA) mediate pathogenic inflammation in atopic dermatitis (AD). The molecular alterations contributing to their dysregulation remain unclear. With the aim to elucidate putative altered pathways in AD we profiled DNA methylation levels and miRNA expression in sorted T cell populations (CD4+, CD4+CD45RA+ naïve, CD4+CLA+, and CD8+) from adult AD patients and healthy controls (HC). Skin homing CD4+CLA+ T cells from AD patients showed significant differences in DNA methylation in 40 genes compared to HC (p < 0.05). Reduced DNA methylation levels in the upstream region of the interleukin-13 gene (IL13) in CD4+CLA+ T cells from AD patients correlated with increased IL13 mRNA expression in these cells. Sixteen miRNAs showed differential expression in CD4+CLA+ T cells from AD patients targeting genes in 202 biological processes (p < 0.05). An integrated network analysis of miRNAs and CpG sites identified two communities of strongly interconnected regulatory elements with strong antagonistic behaviours that recapitulated the differences between AD patients and HC. Functional analysis of the genes linked to these communities revealed their association with key cytokine signaling pathways, MAP kinase signaling and protein ubiquitination. Our findings support that epigenetic mechanisms play a role in the pathogenesis of AD by affecting inflammatory signaling molecules in skin homing CD4+CLA+ T cells and uncover putative molecules participating in AD pathways.

Mechanistic Similarities between 3D Human Bronchial Epithelium and Mice Lung, Exposed to Copper Oxide Nanoparticles, Support Non-Animal Methods for Hazard Assessment.

The diversity and increasing prevalence of products derived from engineered nanomaterials (ENM), warrants implementation of non-animal approaches to health hazard assessment for ethical and practical reasons. Although non-animal approaches are becoming increasingly popular, there are almost no studies of side-by-side comparisons with traditional in vivo assays. Here, transcriptomics is used to investigate mechanistic similarities between healthy/asthmatic models of 3D air-liquid interface (ALI) cultures of donor-derived human bronchial epithelia cells, and mouse lung tissue, following exposure to copper oxide ENM. Only 19% of mouse lung genes with human orthologues are not expressed in the human 3D ALI model. Despite differences in taxonomy and cellular complexity between the systems, a core subset of matching genes cluster mouse and human samples strictly based on ENM dose (exposure severity). Overlapping gene orthologue pairs are highly enriched for innate immune functions, suggesting an important and maybe underestimated role of epithelial cells. In conclusion, 3D ALI models based on epithelial cells, are primed to bridge the gap between traditional 2D in vitro assays and animal models of airway exposure, and transcriptomics appears to be a unifying dose metric that links in vivo and in vitro test systems.

Carbon Nanomaterials Promote M1/M2 Macrophage Activation.

Toxic effects of certain carbon nanomaterials (CNM) have been observed in several exposure scenarios both in vivo and in vitro. However, most of the data currently available has been generated in a high-dose/acute exposure setup, limiting the understanding of their immunomodulatory mechanisms. Here, macrophage-like THP-1 cells, exposed to ten different CNM for 48 h in low-cytotoxic concentration of 10 µg mL-1 , are characterized by secretion of different cytokines and global transcriptional changes. Subsequently, the relationships between cytokine secretion and transcriptional patterns are modeled, highlighting specific pathways related to alternative macrophage activation. Finally, time- and dose-dependent activation of transcription and secretion of M1 marker genes IL-1ß and tumor necrosis factor, and M2 marker genes IL-10 and CSF1 is confirmed among the three most responsive CNM, with concentrations of 5, 10, and 20 µg mL-1 at 24, 48, and 72 h of exposure. These results underline CNM effects on the formation of cell microenvironment and gene expression leading to specific patterns of macrophage polarization. Taken together, these findings imply that, instead of a high and toxic CNM dose, a sub-lethal dose in controlled exposure setup can be utilized to alter the cell microenvironment and program antigen presenting cells, with fascinating implications for novel therapeutic strategies.

Cobalt nanoparticles trigger ferroptosis-like cell death (oxytosis) in neuronal cells: Potential implications for neurodegenerative disease.

The neurotoxicity of hard metal-based nanoparticles (NPs) remains poorly understood. Here, we deployed the human neuroblastoma cell line SH-SY5Y differentiated or not into dopaminergic- and cholinergic-like neurons to study the impact of tungsten carbide (WC) NPs, WC NPs sintered with cobalt (Co), or Co NPs versus soluble CoCl2 . Co NPs and Co salt triggered a dose-dependent cytotoxicity with an increase in cytosolic calcium, lipid peroxidation, and depletion of glutathione (GSH). Co NPs and Co salt also suppressed glutathione peroxidase 4 (GPX4) mRNA and protein expression. Co-exposed cells were rescued by N-acetylcysteine (NAC), a precursor of GSH, and partially by liproxstatin-1, an inhibitor of lipid peroxidation. Furthermore, in silico analyses predicted a significant correlation, based on similarities in gene expression profiles, between Co-containing NPs and Parkinson's disease, and changes in the expression of selected genes were validated by RT-PCR. Finally, experiments using primary human dopaminergic neurons demonstrated cytotoxicity and GSH depletion in response to Co NPs and CoCl2 with loss of axonal integrity. Overall, these data point to a marked neurotoxic potential of Co-based but not WC NPs and show that neuronal cell death may occur through a ferroptosis-like mechanism.

DNA sequence context as a marker of CpG methylation instability in normal and cancer tissues.

DNA methylation alterations are related to multiple molecular mechanisms. The DNA context of CpG sites plays a crucial role in the maintenance and stability of methylation patterns. The quantitative relationship between DNA composition and DNA methylation has been studied in normal as well as pathological conditions, showing that DNA methylation status is highly dependent on the local sequence context. In this work, we describe this relationship by analyzing the DNA sequence context associated to methylation profiles in both physiological and pathological conditions. In particular, we used DNA motifs to describe methylation stability patterns in normal tissues and aberrant methylation events in cancer lesions. In this manuscript, we show how different groups of DNA sequences can be related to specific epigenetic events, across normal and cancer tissues, and provide a thorough structural and functional characterization of these sequences.

Knowledge Generation with Rule Induction in Cancer Omics.

The explosion of omics data availability in cancer research has boosted the knowledge of the molecular basis of cancer, although the strategies for its definitive resolution are still not well established. The complexity of cancer biology, given by the high heterogeneity of cancer cells, leads to the development of pharmacoresistance for many patients, hampering the efficacy of therapeutic approaches. Machine learning techniques have been implemented to extract knowledge from cancer omics data in order to address fundamental issues in cancer research, as well as the classification of clinically relevant sub-groups of patients and for the identification of biomarkers for disease risk and prognosis. Rule induction algorithms are a group of pattern discovery approaches that represents discovered relationships in the form of human readable associative rules. The application of such techniques to the modern plethora of collected cancer omics data can effectively boost our understanding of cancer-related mechanisms. In fact, the capability of these methods to extract a huge amount of human readable knowledge will eventually help to uncover unknown relationships between molecular attributes and the malignant phenotype. In this review, we describe applications and strategies for the usage of rule induction approaches in cancer omics data analysis. In particular, we explore the canonical applications and the future challenges and opportunities posed by multi-omics integration problems.

Phosphorylation of NFATC1 at PIM1 target sites is essential for its ability to promote prostate cancer cell migration and invasion.

BACKGROUND: Progression of prostate cancer from benign local tumors to metastatic carcinomas is a multistep process. Here we have investigated the signaling pathways that support migration and invasion of prostate cancer cells, focusing on the role of the NFATC1 transcription factor and its post-translational modifications. We have previously identified NFATC1 as a substrate for the PIM1 kinase and shown that PIM1-dependent phosphorylation increases NFATC1 activity without affecting its subcellular localization. Both PIM kinases and NFATC1 have been reported to promote cancer cell migration, invasion and angiogenesis, but it has remained unclear whether the effects of NFATC1 are phosphorylation-dependent and which downstream targets are involved. METHODS: We used mass spectrometry to identify PIM1 phosphorylation target sites in NFATC1, and analysed their functional roles in three prostate cancer cell lines by comparing phosphodeficient mutants to wild-type NFATC1. We used luciferase assays to determine effects of phosphorylation on NFAT-dependent transcriptional activity, and migration and invasion assays to evaluate effects on cell motility. We also performed a microarray analysis to identify novel PIM1/NFATC1 targets, and validated one of them with both cellular expression analyses and in silico in clinical prostate cancer data sets. RESULTS: Here we have identified ten PIM1 target sites in NFATC1 and found that prevention of their phosphorylation significantly decreases the transcriptional activity as well as the pro-migratory and pro-invasive effects of NFATC1 in prostate cancer cells. We observed that also PIM2 and PIM3 can phosphorylate NFATC1, and identified several novel putative PIM1/NFATC1 target genes. These include the ITGA5 integrin, which is differentially expressed in the presence of wild-type versus phosphorylation-deficient NFATC1, and which is coexpressed with PIM1 and NFATC1 in clinical prostate cancer specimens. CONCLUSIONS: Based on our data, phosphorylation of PIM1 target sites stimulates NFATC1 activity and enhances its ability to promote prostate cancer cell migration and invasion. Therefore, inhibition of the interplay between PIM kinases and NFATC1 may have therapeutic implications for patients with metastatic forms of cancer.

Gain-of-function CEBPE mutation causes noncanonical autoinflammatory inflammasomopathy.

BACKGROUND: CCAAT enhancer-binding protein epsilon (C/EBPε) is a transcription factor involved in late myeloid lineage differentiation and cellular function. The only previously known disorder linked to C/EBPε is autosomal recessive neutrophil-specific granule deficiency leading to severely impaired neutrophil function and early mortality. OBJECTIVE: The aim of this study was to molecularly characterize the effects of C/EBPε transcription factor Arg219His mutation identified in a Finnish family with previously genetically uncharacterized autoinflammatory and immunodeficiency syndrome. METHODS: Genetic analysis, proteomics, genome-wide transcriptional profiling by means of RNA-sequencing, chromatin immunoprecipitation (ChIP) sequencing, and assessment of the inflammasome function of primary macrophages were performed. RESULTS: Studies revealed a novel mechanism of genome-wide gain-of-function that dysregulated transcription of 464 genes. Mechanisms involved dysregulated noncanonical inflammasome activation caused by decreased association with transcriptional repressors, leading to increased chromatin occupancy and considerable changes in transcriptional activity, including increased expression of NLR family, pyrin domain-containing 3 protein (NLRP3) and constitutively expressed caspase-5 in macrophages. CONCLUSION: We describe a novel autoinflammatory disease with defective neutrophil function caused by a homozygous Arg219His mutation in the transcription factor C/EBPε. Mutated C/EBPε acts as a regulator of both the inflammasome and interferome, and the Arg219His mutation causes the first human monogenic neomorphic and noncanonical inflammasomopathy/immunodeficiency. The mechanism, including widely dysregulated transcription, is likely not unique for C/EBPε. Similar multiomics approaches should also be used in studying other transcription factor-associated diseases.

Targeted Analysis of Serum Proteins Encoded at Known Inflammatory Bowel Disease Risk Loci.

Background: Few studies have investigated the blood proteome of inflammatory bowel disease (IBD). We characterized the serum abundance of proteins encoded at 163 known IBD risk loci and tested these proteins for their biomarker discovery potential. Methods: Based on the Human Protein Atlas (HPA) antibody availability, 218 proteins from genes mapping at 163 IBD risk loci were selected. Targeted serum protein profiles from 49 Crohn's disease (CD) patients, 51 ulcerative colitis (UC) patients, and 50 sex- and age-matched healthy individuals were obtained using multiplexed antibody suspension bead array assays. Differences in relative serum abundance levels between disease groups and controls were examined. Replication was attempted for CD-UC comparisons (including disease subtypes) by including 64 additional patients (33 CD and 31 UC). Antibodies targeting a potentially novel risk protein were validated by paired antibodies, Western blot, immuno-capture mass spectrometry, and epitope mapping. Results: By univariate analysis, 13 proteins mostly related to neutrophil, T-cell, and B-cell activation and function were differentially expressed in IBD patients vs healthy controls, 3 in CD patients vs healthy controls and 2 in UC patients vs healthy controls (q < 0.01). Multivariate analyses further differentiated disease groups from healthy controls and CD subtypes from UC (P < 0.05). Extended characterization of an antibody targeting a novel, discriminative serum marker, the laccase (multicopper oxidoreductase) domain containing 1 (LACC1) protein, provided evidence for antibody on-target specificity. Conclusions: Using affinity proteomics, we identified a set of IBD-associated serum proteins encoded at IBD risk loci. These candidate proteins hold the potential to be exploited as diagnostic biomarkers of IBD.

IntEREst: intron-exon retention estimator.

BACKGROUND: In-depth study of the intron retention levels of transcripts provide insights on the mechanisms regulating pre-mRNA splicing efficiency. Additionally, detailed analysis of retained introns can link these introns to post-transcriptional regulation or identify aberrant splicing events in human diseases. RESULTS: We present IntEREst, Intron-Exon Retention Estimator, an R package that supports rigorous analysis of non-annotated intron retention events (in addition to the ones annotated by RefSeq or similar databases), and support intra-sample in addition to inter-sample comparisons. It accepts binary sequence alignment/map (.bam) files as input and determines genome-wide estimates of intron retention or exon-exon junction levels. Moreover, it includes functions for comparing subsets of user-defined introns (e.g. U12-type vs U2-type) and its plotting functions allow visualization of the distribution of the retention levels of the introns. Statistical methods are adapted from the DESeq2, edgeR and DEXSeq R packages to extract the significantly more or less retained introns. Analyses can be performed either sequentially (on single core) or in parallel (on multiple cores). We used IntEREst to investigate the U12- and U2-type intron retention in human and plant RNAseq dataset with defects in the U12-dependent spliceosome due to mutations in the ZRSR2 component of this spliceosome. Additionally, we compared the retained introns discovered by IntEREst with that of other methods and studies. CONCLUSION: IntEREst is an R package for Intron retention and exon-exon junction levels analysis of RNA-seq data. Both the human and plant analyses show that the U12-type introns are retained at higher level compared to the U2-type introns already in the control samples, but the retention is exacerbated in patient or plant samples carrying a mutated ZRSR2 gene. Intron retention events caused by ZRSR2 mutation that we discovered using IntEREst (DESeq2 based function) show considerable overlap with the retained introns discovered by other methods (e.g. IRFinder and edgeR based function of IntEREst). Our results indicate that increase in both the number of biological replicates and the depth of sequencing library promote the discovery of retained introns, but the effect of library size gradually decreases with more than 35 million reads mapped to the introns.

miR-34b/c Regulates Wnt1 and Enhances Mesencephalic Dopaminergic Neuron Differentiation.

The differentiation of dopaminergic neurons requires concerted action of morphogens and transcription factors acting in a precise and well-defined time window. Very little is known about the potential role of microRNA in these events. By performing a microRNA-mRNA paired microarray screening, we identified miR-34b/c among the most upregulated microRNAs during dopaminergic differentiation. Interestingly, miR-34b/c modulates Wnt1 expression, promotes cell cycle exit, and induces dopaminergic differentiation. When combined with transcription factors ASCL1 and NURR1, miR-34b/c doubled the yield of transdifferentiated fibroblasts into dopaminergic neurons. Induced dopaminergic (iDA) cells synthesize dopamine and show spontaneous electrical activity, reversibly blocked by tetrodotoxin, consistent with the electrophysiological properties featured by brain dopaminergic neurons. Our findings point to a role for miR-34b/c in neuronal commitment and highlight the potential of exploiting its synergy with key transcription factors in enhancing in vitro generation of dopaminergic neurons.