LENS: web-based lens for enrichment and network studies of human proteins

Flow blockage disrupts cilia-driven fluid transport in the epileptic brain

A carpet of ependymal motile cilia lines the brain ventricular system, forming a network of flow channels and barriers that pattern cerebrospinal fluid (CSF) flow at the surface. This CSF transport system is evolutionary conserved, but its physiological function remains unknown. Here we investigated its potential role in epilepsy with studies focused on CDKL5 deficiency disorder (CDD), a neurodevelopmental disorder with early-onset epilepsy refractory to seizure medications and the most common cause of infant epilepsy. CDKL5 is a highly conserved X-linked gene suggesting its function in regulating cilia length and motion in the green alga Chlamydomonas might have implication in the etiology of CDD. Examination of the structure and function of airway motile cilia revealed both the CDD patients and the Cdkl5 knockout mice exhibit cilia lengthening and abnormal cilia motion. Similar defects were observed for brain ventricular cilia in the Cdkl5 knockout mice. Mapping ependymal cilia generated flow in the ventral third ventricle (v3V), a brain region with important physiological functions showed altered patterning of flow. Tracing of cilia-mediated inflow into v3V with fluorescent dye revealed the appearance of a flow barrier at the inlet of v3V in Cdkl5 knockout mice. Analysis of mice with a mutation in another epilepsy-associated kinase, Yes1, showed the same disturbance of cilia motion and flow patterning. The flow barrier was also observed in the Foxj1^± and FOXJ1Cre^ERT:Cdkl5^y/fl mice, confirming the contribution of ventricular cilia to the flow disturbances. Importantly, mice exhibiting altered cilia-driven flow also showed increased susceptibility to anesthesia-induced seizure-like activity. The cilia-driven flow disturbance arises from altered cilia beating orientation with the disrupted polarity of the cilia anchoring rootlet meshwork. Together these findings indicate motile cilia disturbances have an essential role in CDD-associated seizures and beyond, suggesting cilia regulating kinases may be a therapeutic target for medication-resistant epilepsy.

A new strategy to uncover fragile X proteomic biomarkers using the nascent proteome of peripheral blood mononuclear cells (PBMCs)

Fragile X syndrome (FXS) is the most prevalent inherited cause of intellectual disabilities and autism spectrum disorders. FXS result from the loss of expression of the FMRP protein, an RNA-binding protein that regulates the expression of key synaptic effectors. FXS is also characterized by a wide array of behavioural, cognitive and metabolic impairments. The severity and penetrance of those comorbidities are extremely variable, meaning that a considerable phenotypic heterogeneity is found among fragile X individuals. Unfortunately, clinicians currently have no tools at their disposal to assay a patient prognosis upon diagnosis. Since the absence of FMRP was repeatedly associated with an aberrant protein synthesis, we decided to study the nascent proteome in order to screen for potential proteomic biomarkers of FXS. We used a BONCAT (Biorthogonal Non-canonical Amino Acids Tagging) method coupled to label-free mass spectrometry to purify and quantify nascent proteins of peripheral blood mononuclear cells (PBMCs) from 7 fragile X male patients and 7 age-matched controls. The proteomic analysis identified several proteins which were either up or downregulated in PBMCs from FXS individuals. Eleven of those proteins were considered as potential biomarkers, of which 5 were further validated by Western blot. The gene ontology enrichment analysis highlighted molecular pathways that may contribute to FXS physiopathology. Our results suggest that the nascent proteome of PBMCs is well suited for the discovery of FXS biomarkers.

The Role of Fibroblast Growth Factor 19 in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the third leading cause of cancer-related deaths worldwide. Liver resection or liver transplantation is the most effective therapy for HCC because drugs approved by the US Food and Drug Administration to treat patients with unresectable HCC have an unfavorable overall survival rate. Therefore, the development of biomarkers for early diagnosis and effective therapy strategies are still necessary to improve patient outcomes. Fibroblast growth factor (FGF) 19 was amplified in patients with HCC from various studies, including patients from The Cancer Genome Atlas. FGF19 plays a syngeneic function with other signaling pathways in primary liver cancer development, such as epidermal growth factor receptor, Wnt/β-catenin, the endoplasmic reticulum-related signaling pathway, STAT3/IL-6, RAS, and extracellular signal-regulated protein kinase, among others. The current review presents a comprehensive description of the FGF19 signaling pathway involved in liver cancer development. The use of big data and bioinformatic analysis can provide useful clues for further studies of the FGF19 pathway in HCC, including its application as a biomarker, targeted therapy, and combination therapy strategies.

Localized EMT reprograms glial progenitors to promote spinal cord repair

Anti-regenerative scarring obstructs spinal cord repair in mammals and presents a major hurdle for regenerative medicine. In contrast, adult zebrafish possess specialized glial cells that spontaneously repair spinal cord injuries by forming a pro-regenerative bridge across the severed tissue. To identify the mechanisms that regulate differential regenerative capacity between mammals and zebrafish, we first defined the molecular identity of zebrafish bridging glia and then performed cross-species comparisons with mammalian glia. Our transcriptomics show that pro-regenerative zebrafish glia activate an epithelial-to-mesenchymal transition (EMT) gene program and that EMT gene expression is a major factor distinguishing mammalian and zebrafish glia. Functionally, we found that localized niches of glial progenitors undergo EMT after spinal cord injury in zebrafish and, using large-scale CRISPR-Cas9 mutagenesis, we identified the gene regulatory network that activates EMT and drives functional regeneration. Thus, non-regenerative mammalian glia lack an essential EMT-driving gene regulatory network that reprograms pro-regenerative zebrafish glia after injury.

Protein Biomarkers of Autism Spectrum Disorder Identified by Computational and Experimental Methods

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects millions of people worldwide. However, there are currently no reliable biomarkers for ASD diagnosis. Materials and Methods: The strategy of computational prediction combined with experimental verification was used to identify blood protein biomarkers for ASD. First, brain tissue-based transcriptome data of ASD were collected from Gene Expression Omnibus database and analyzed to find ASD-related genes by bioinformatics method of significance analysis of microarrays. Then, a prediction program of blood-secretory proteins was applied on these genes to predict ASD-related proteins in blood. Furthermore, ELISA was used to verify these proteins in plasma samples of ASD patients. Results: A total of 364 genes were identified differentially expressed in brain tissue of ASD, among which 59 genes were predicted to encode ASD-related blood-secretory proteins. After functional analysis and literature survey, six proteins were chosen for experimental verification and five were successfully validated. Receiver operating characteristic curve analyses showed that the area under the curve of SLC25A12, LIMK1, and RARS was larger than 0.85, indicating that they are more powerful in discriminating ASD cases from controls. Conclusion: SLC25A12, LIMK1, and RARS might serve as new potential blood protein biomarkers for ASD. Our findings provide new insights into the pathogenesis and diagnosis of ASD.

Genome-wide meta-analysis associates GPSM1 with type 2 diabetes, a plausible gene involved in skeletal muscle function

Genome-wide association studies (GWASs) have identified many genetic variations associated with type 2 diabetes mellitus (T2DM) in Asians, but understanding the functional genetic variants that influence traits is often a complex process. In this study, fine mapping and other analytical strategies were performed to investigate the effects of G protein signaling modulator 1 (GPSM1) on insulin resistance in skeletal muscle. A total of 128 single-nucleotide polymorphisms (SNPs) within GPSM1 were analysed in 21,897 T2DM cases and 32,710 healthy controls from seven GWASs. The SNP rs28539249 in intron 9 of GPSM1 showed a nominally significant association with T2DM in Asians (OR = 1.07, 95% CI = 1.04-1.10, P < 10^-4). The GPSM1 mRNA was increased in skeletal muscle and correlated with T2DM traits across obese mice model. An eQTL for the cis-acting regulation of GPSM1 expression in human skeletal muscle was identified for rs28539249, and the increased GPSM1 expression related with T2DM traits within GEO datasets. Another independent Asian cohort showed that rs28539249 is associated with the skeletal muscle expression of CACFD1, GTF3C5, SARDH, and FAM163B genes, which are functionally enriched for endoplasmic reticulum stress (ERS) and unfolded protein response (UPR) pathways. Moreover, rs28539249 locus was predicted to disrupt regulatory regions in human skeletal muscle with enriched epigenetic marks and binding affinity for CTCF. Supershift EMSA assays followed luciferase assays demonstrated the CTCF specifically binding to rs28539249-C allele leading to decreased transcriptional activity. Thus, the post-GWAS annotation confirmed the Asian-specific association of genetic variant in GPSM1 with T2DM, suggesting a role for the variant in the regulation in skeletal muscle.

Potentially repurposable drugs for schizophrenia identified from its interactome

We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.

Mining cancer biology through bioinformatic analysis of proteomic data

Introduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research. Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes. Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output.

Identification of Blood Biomarkers for Alzheimer's Disease Through Computational Prediction and Experimental Validation

Background: Alzheimer's disease (AD) is the major cause of dementia in population aged over 65 years, accounting up to 70% dementia cases. However, validated peripheral biomarkers for AD diagnosis are not available up to present. In this study, we adopted a new strategy of combination of computational prediction and experimental validation to identify blood protein biomarkers for AD.

Methods: First, we collected tissue-based gene expression data of AD patients and healthy controls from GEO database. Second, we analyzed these data and identified differentially expressed genes for AD. Third, we applied a blood-secretory protein prediction program on these genes and predicted AD-related proteins in blood. Finally, we collected blood samples of AD patients and healthy controls to validate the potential AD biomarkers by using ELISA experiments and Western blot analyses.

Results: A total of 2754 genes were identified to express differentially in brain tissues of AD, among which 296 genes were predicted to encode AD-related blood-secretory proteins. After careful analysis and literature survey on these predicted blood-secretory proteins, ten proteins were considered as potential AD biomarkers, five of which were experimentally verified with significant change in blood samples of AD vs. controls by ELISA, including GSN, BDNF, TIMP1, VLDLR, and APLP2. ROC analyses showed that VLDLR and TIMP1 had excellent performance in distinguishing AD patients from controls (area under the curve, AUC = 0.932 and 0.903, respectively). Further validation of VLDLR and TIMP1 by Western blot analyses has confirmed the results obtained in ELISA experiments.

Conclusion: VLDLR and TIMP1 had better discriminative abilities between ADs and controls, and might serve as potential blood biomarkers for AD. To our knowledge, this is the first time to identify blood protein biomarkers for AD through combination of computational prediction and experimental validation. In addition, VLDLR was first reported here as potential blood protein biomarker for AD. Thus, our findings might provide important information for AD diagnosis and therapies.

Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity

Non-alcoholic fatty liver disease (NAFLD) represents a wide spectrum of disease, ranging from simple fatty liver through steatosis with inflammation and necrosis to cirrhosis. One of the most challenging problems in biomedical research and within the chemical industry is to understand the underlying mechanisms of complex disease, and complex adverse outcome pathways (AOPs). Based on a set of 28 steatotic chemicals with gene expression data measured on primary hepatocytes at three times (2, 8, and 24 h) and three doses (low, medium, and high), we identified genes and pathways, defined as molecular initiating events (MIEs) and key events (KEs) of steatosis using a combination of a time series and pathway analyses. Among the genes deregulated by these compounds, the study highlighted OSBPL9, ALDH7A1, MYADM, SLC51B, PRDX6, GPAT3, TMEM135, DLGDA5, BCO2, APO10LA, TSPAN6, NEURL1B, and DUSP1. Furthermore, pathway analysis indicated deregulation of pathways related to lipid accumulation, such as fat digestion and absorption, linoleic and linolenic acid metabolism, calcium signaling pathway, fatty acid metabolism, peroxisome, retinol metabolism, and steroid metabolic pathways in a time dependent manner. Such transcription profile analysis can help in the understanding of the steatosis evolution over time generated by chemical exposure.

iTRAQ-Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism

PURPOSE

Autism is a childhood neurological disorder with poorly understood etiology and pathology. This study is designed to identify differentially expressed proteins that might serve as potential biomarkers for autism.

EXPERIMENTAL DESIGN

We perform iTRAQ (isobaric tags for relative and absolute quantitation) analysis for normal and autistic children's plasma of the same age group.

RESULTS

The results show that 24 differentially expressed proteins were identified between autistic subjects and controls. For the first time, differential expression of complement C5 (C5) and fermitin family homolog 3 (FERMT3) are related to autism. Five proteins, that is, complement C3 (C3), C5, integrin alpha-IIb (ITGA2B), talin-1 (TLN1), and vitamin D-binding protein (GC) were validated via enzyme-linked immunosorbent assay (ELISA). By ROC (receiver operating characteristic) analysis, combinations of these five proteins C3, C5, GC, ITGA2B, and TLN1 distinguished autistic children from healthy controls with a high AUC (area under the ROC curve) value (0.982, 95% CI, 0.957-1.000, p < 0.000).

CONCLUSION

These above described proteins are found involved in different pathways that have previously been linked to the pathophysiology of autism spectrum disorders (ASDs). The results strongly support that focal adhesions, acting cytoskeleton, cell adhesion, motility and migration, synaptogenesis, and complement system are involved in the pathogenesis of autism, and highlight the important role of platelet function in the pathophysiology of autism.

Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia

Several chronic lymphocytic leukaemia (CLL) susceptibility loci have been reported; however, much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1,000 Genomes and UK10K data, totalling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P=5.04 × 10-13), 1q42.13 (rs41271473, P=1.06 × 10-10), 4q24 (rs71597109, P=1.37 × 10-10), 4q35.1 (rs57214277, P=3.69 × 10-8), 6p21.31 (rs3800461, P=1.97 × 10-8), 11q23.2 (rs61904987, P=2.64 × 10-11), 18q21.1 (rs1036935, P=3.27 × 10-8), 19p13.3 (rs7254272, P=4.67 × 10-8) and 22q13.33 (rs140522, P=2.70 × 10-9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for the key determinants of B-cell development and immune response.

Pilot study of small bowel mucosal gene expression in patients with irritable bowel syndrome with diarrhea

Prior studies in with irritable bowel syndrome with diarrhea (IBS-D) patients showed immune activation, secretion, and barrier dysfunction in jejunal or colorectal mucosa. We measured mRNA expression by RT-PCR of 91 genes reflecting tight junction proteins, chemokines, innate immunity, ion channels, transmitters, housekeeping genes, and controls for DNA contamination and PCR efficiency in small intestinal mucosa from 15 IBS-D and 7 controls (biopsies negative for celiac disease). Fold change was calculated using 2((-ΔΔCT)) formula. Nominal P values (P < 0.05) were interpreted with false detection rate (FDR) correction (q value). Cluster analysis with Lens for Enrichment and Network Studies (LENS) explored connectivity of mechanisms. Upregulated genes (uncorrected P < 0.05) were related to ion transport (INADL, MAGI1, and SONS1), barrier (TJP1, 2, and 3 and CLDN) or immune functions (TLR3, IL15, and MAPKAPK5), or histamine metabolism (HNMT); downregulated genes were related to immune function (IL-1β, TGF-β1, and CCL20) or antigen detection (TLR1 and 8). The following genes were significantly upregulated (q < 0.05) in IBS-D: INADL, MAGI1, PPP2R5C, MAPKAPK5, TLR3, and IL-15. Among the 14 nominally upregulated genes, there was clustering of barrier and PDZ domains (TJP1, TJP2, TJP3, CLDN4, INADL, and MAGI1) and clustering of downregulated genes (CCL20, TLR1, IL1B, and TLR8). Protein expression of PPP2R5C in nuclear lysates was greater in patients with IBS-D and controls. There was increase in INADL protein (median 9.4 ng/ml) in patients with IBS-D relative to controls (median 5.8 ng/ml, P > 0.05). In conclusion, altered transcriptome (and to lesser extent protein) expression of ion transport, barrier, immune, and mast cell mechanisms in small bowel may reflect different alterations in function and deserves further study in IBS-D.

Predicted protein interactions of IFITMs may shed light on mechanisms of Zika virus-induced microcephaly and host invasion

After the first reported case of Zika virus (ZIKV) in Brazil, in 2015, a significant increase in the reported cases of microcephaly was observed. Microcephaly is a neurological condition in which the infant's head is significantly smaller with complications in brain development. Recently, two small membrane-associated interferon-inducible transmembrane proteins (IFITM1 and IFITM3) have been shown to repress members of the flaviviridae family which includes ZIKV. However, the exact mechanisms leading to the inhibition of the virus are yet unknown. Here, we assembled an interactome of IFITM1 and IFITM3 with known protein-protein interactions (PPIs) collected from publicly available databases and novel PPIs predicted using the High-confidence Protein-Protein Interaction Prediction (HiPPIP) model. We analyzed the functional and pathway associations of the interacting proteins, and found that there are several immunity pathways (toll-like receptor signaling, cd28 signaling in T-helper cells, crosstalk between dendritic cells and natural killer cells), neuronal pathways (axonal guidance signaling, neural tube closure and actin cytoskeleton signaling) and developmental pathways (neural tube closure, embryonic skeletal system development) that are associated with these interactors. Our novel PPIs associate cilia dysfunction in ependymal cells to microcephaly, and may also shed light on potential targets of ZIKV for host invasion by immunosuppression and cytoskeletal rearrangements. These results could help direct future research in elucidating the mechanisms underlying host defense to ZIKV and other flaviviruses.

Variation at 2q35 (PNKD and TMBIM1) influences colorectal cancer risk and identifies a pleiotropic effect with inflammatory bowel disease

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 × 10-8, odds ratio = 1.10, 95% confidence interval = 1.06-1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r2 = 0.90, D' = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR]) < 0.05). Our findings provide further insight into the biological basis of inherited genetic susceptibility to CRC, and identify risk factors that may influence the development of both CRC and IBD.

GIW and InCoB, two premier bioinformatics conferences in Asia with a combined 40 years of history

Knowledge discovery in bioinformatics thrives on joint and inclusive efforts of stakeholders. Similarly, knowledge dissemination is expected to be more effective and scalable through joint efforts. Therefore, the International Conference on Bioinformatics (InCoB) and the International Conference on Genome Informatics (GIW) were organized as a joint conference for the first time in 13 years of coexistence. The Asia-Pacific Bioinformatics Network (APBioNet) and the Japanese Society for Bioinformatics (JSBi) collaborated to host GIW/InCoB2015 in Tokyo, September 9-11, 2015. The joint endeavour yielded 51 research articles published in seven journals, 78 poster and 89 oral presentations, showcasing bioinformatics research in the Asia-Pacific region. Encouraged by the results and reduced organizational overheads, APBioNet will collaborate with other bioinformatics societies in organizing co-located bioinformatics research and training meetings in the future. InCoB2016 will be hosted in Singapore, September 21-23, 2016.