A gene-centric approach to biomarker discovery identifies transglutaminase 1 as an epidermal autoantigen.
Ontology highlight
ABSTRACT:
SUBMITTER: Landegren N
PROVIDER: S-EPMC8713791 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Lasso peptides are a class of ribosomally synthesized posttranslationally modified natural products found in bacteria. Currently known lasso peptides have a diverse set of pharmacologically relevant activities, including inhibition of bacterial growth, receptor antagonism, and enzyme inhibition. The biosynthesis of lasso peptides is specified by a cluster of three genes encoding a precursor protein and two enzymes. Here we develop a unique genome-mining algorithm to identify lasso peptide gene clusters in prokaryotes. Our approach involves pattern matching to a small number of conserved amino acids in precursor proteins, and thus allows for a more global survey of lasso peptide gene clusters than does homology-based genome mining. Of more than 3,000 currently sequenced prokaryotic genomes, we found 76 organisms that are putative lasso peptide producers. These organisms span nine bacterial phyla and an archaeal phylum. To provide validation of the genome-mining method, we focused on a single lasso peptide predicted to be produced by the freshwater bacterium Asticcacaulis excentricus. Heterologous expression of an engineered, minimal gene cluster in Escherichia coli led to the production of a unique lasso peptide, astexin-1. At 23 aa, astexin-1 is the largest lasso peptide isolated to date. It is also highly polar, in contrast to many lasso peptides that are primarily hydrophobic. Astexin-1 has modest antimicrobial activity against its phylogenetic relative Caulobacter crescentus. The solution structure of astexin-1 was determined revealing a unique topology that is stabilized by hydrogen bonding between segments of the peptide.
| S-EPMC3458324 | biostudies-literature
Project description:Alzheimer's disease (AD) is a chronic neurodegenerative disorder. It is the most common type of dementia that has remained as an incurable disease in the world, which destroys the brain cells irreversibly. In this study, a systems biology approach was adopted to discover novel micro-RNA and gene-based biomarkers of the diagnosis of Alzheimer's disease. The gene expression data from three AD stages (Normal, Mild Cognitive Impairment, and Alzheimer) were used to reconstruct co-expression networks. After preprocessing and normalization, Weighted Gene Co-Expression Network Analysis (WGCNA) was used on a total of 329 samples, including 145 samples of Alzheimer stage, 80 samples of Mild Cognitive Impairment (MCI) stage, and 104 samples of the Normal stage. Next, three gene-miRNA bipartite networks were reconstructed by comparing the changes in module groups. Then, the functional enrichment analyses of extracted genes of three bipartite networks and miRNAs were done, respectively. Finally, a detailed analysis of the authentic studies was performed to discuss the obtained biomarkers. The outcomes addressed proposed novel genes, including MBOAT1, ARMC7, RABL2B, HNRNPUL1, LAMTOR1, PLAGL2, CREBRF, LCOR, and MRI1and novel miRNAs comprising miR-615-3p, miR-4722-5p, miR-4768-3p, miR-1827, miR-940 and miR-30b-3p which were related to AD. These biomarkers were proposed to be related to AD for the first time and should be examined in future clinical studies.
| S-EPMC7376049 | biostudies-literature
Project description:Neuroblastoma is a malignant neoplasm of the developing sympathetic nervous system that is notable for its phenotypic diversity. High-risk patients typically have widely disseminated disease at diagnosis and a poor survival probability, but low-risk patients frequently have localized tumors that are almost always cured with little or no chemotherapy. Our genome-wide association study (GWAS) has identified common variants within FLJ22536, BARD1, and LMO1 as significantly associated with neuroblastoma and more robustly associated with high-risk disease. Here we show that a GWAS focused on low-risk cases identified SNPs within DUSP12 at 1q23.3 (P = 2.07 × 10??), DDX4 and IL31RA both at 5q11.2 (P = 2.94 × 10?? and 6.54 × 10?? respectively), and HSD17B12 at 11p11.2 (P = 4.20 × 10??) as being associated with the less aggressive form of the disease. These data demonstrate the importance of robust phenotypic data in GWAS analyses and identify additional susceptibility variants for neuroblastoma.
| S-EPMC3060064 | biostudies-literature
Project description:The genetic susceptibility to preeclampsia, a pregnancy-specific complication with significant maternal and fetal morbidity, has been poorly characterized. To identify maternal genes associated with preeclampsia risk, we assembled 498 cases and 1864 controls of European ancestry from preeclampsia case-control collections in 5 different US sites (with additional matched population controls), genotyped samples on a cardiovascular gene-centric array composed of variants from ?2000 genes selected based on prior genetic studies of cardiovascular and metabolic diseases and performed case-control genetic association analysis on 27?429 variants passing quality control. In silico replication testing of 9 lead signals with P<10-4 was performed in independent European samples from the SOPHIA (Study of Pregnancy Hypertension in Iowa) and Inova cohorts (212 cases, 456 controls). Multiethnic assessment of lead signals was then performed in samples of black (26 cases, 136 controls), Hispanic (132 cases, 468 controls), and East Asian (9 cases, 80 controls) ancestry. Multiethnic meta-analysis (877 cases, 3004 controls) revealed a study-wide statistically significant association of the rs9478812 variant in the pleiotropic PLEKHG1 gene (odds ratio, 1.40 [1.23-1.60]; Pmeta=5.90×10-7). The rs9478812 effect was even stronger in the subset of European cases with known early-onset preeclampsia (236 cases diagnosed <37 weeks, 1864 controls; odds ratio, 1.59 [1.27-1.98]; P=4.01×10-5). PLEKHG1 variants have previously been implicated in genome-wide association studies of blood pressure, body weight, and neurological disorders. Although larger studies are required to further define maternal preeclampsia heritability, this study identifies a novel maternal risk locus for further investigation.
| S-EPMC6043396 | biostudies-literature
Project description:BackgroundResistant hypertension (RHTN), defined by lack of blood pressure (BP) control despite treatment with at least 3 antihypertensive drugs, increases cardiovascular risk compared with controlled hypertension. Yet, there are few data on genetic variants associated with RHTN.Methods and resultsWe used a gene-centric array containing ≈50 000 single-nucleotide polymorphisms (SNPs) to identify polymorphisms associated with RHTN in hypertensive participants with coronary artery disease (CAD) from INVEST-GENES (the INnternational VErapamil-SR Trandolapril STudy-GENEtic Substudy). RHTN was defined as BP≥140/90 on 3 drugs, or any BP on 4 or more drugs. Logistic regression analysis was performed in European Americans (n=904) and Hispanics (n=837), using an additive model adjusted for age, gender, randomized treatment assignment, body mass index, principal components for ancestry, and other significant predictors of RHTN. Replication of the top SNP was conducted in 241 European American women from WISE (Women's Ischemia Syndrome Evaluation), where RHTN was defined similarly. To investigate the functional effect of rs12817819, mRNA expression was measured in whole blood. We found ATP2B1 rs12817819 associated with RHTN in both INVEST European Americans (P-value=2.44×10(-3), odds ratio=1.57 [1.17 to 2.01]) and INVEST Hispanics (P=7.69×10(-4), odds ratio=1.76 [1.27 to 2.44]). A consistent trend was observed at rs12817819 in WISE, and the INVEST-WISE meta-analysis result reached chip-wide significance (P=1.60×10(-6), odds ratio=1.65 [1.36 to 1.95]). Expression analyses revealed significant differences in ATP2B1 expression by rs12817819 genotype.ConclusionsThe ATP2B1 rs12817819 A allele is associated with increased risk for RHTN in hypertensive participants with documented CAD or suspected ischemic heart disease.Clinical trial registration urlwww.clinicaltrials.gov; Unique identifiers: NCT00133692 (INVEST), NCT00000554 (WISE).
| S-EPMC4338734 | biostudies-literature
Project description:The advent of powerful genomics technologies has uncovered many fundamental aspects of biology, including the mechanisms of cancer; however, it has not been appropriately matched by the development of global approaches to discover new medicines against human diseases. Here we describe a unique high-throughput screening strategy by high-throughput sequencing, referred to as HTS(2), to meet this challenge. This technology enables large-scale and quantitative analysis of gene matrices associated with specific disease phenotypes, therefore allowing screening for small molecules that can specifically intervene with disease-linked gene-expression events. By initially applying this multitarget strategy to the pressing problem of hormone-refractory prostate cancer, which tends to be accelerated by the current antiandrogen therapy, we identify Peruvoside, a cardiac glycoside, which can potently inhibit both androgen-sensitive and -resistant prostate cancer cells without triggering severe cytotoxicity. We further show that, despite transcriptional reprogramming in prostate cancer cells at different disease stages, the compound can effectively block androgen receptor-dependent gene expression by inducing rapid androgen receptor degradation via the proteasome pathway. These findings establish a genomics-based phenotypic screening approach capable of quickly connecting pathways of phenotypic response to the molecular mechanism of drug action, thus offering a unique pathway-centric strategy for drug discovery.
| S-EPMC3311343 | biostudies-literature
Project description:Current cancer biomarkers present variability in their predictive power and demonstrate limited clinical efficacy, possibly due to the lack of functional relevance of biomarker genes to cancer progression. To address this challenge, a biomarker discovery pipeline was developed to integrate gene expression profiles from The Cancer Genome Atlas and essential survival gene datasets from The Cancer Dependency Map, the latter of which catalogs genes driving cancer progression. By applying this pipeline to lung adenocarcinoma, lung squamous cell carcinoma, and glioblastoma, genes highly associated with cancer progression were identified and designated as progression gene signatures (PGSs). Analysis of area under the receiver operating characteristics curve revealed that PGSs predicted patient survival more accurately than previously identified cancer biomarkers. Moreover, PGSs stratified patients with high risk for progressive disease indicated by worse prognostic outcomes, increased frequency of cancer progression, and poor responses to chemotherapy. The robust performance of these PGSs were recapitulated in four independent microarray datasets from Gene Expression Omnibus and were further verified in six freshly dissected tumors from glioblastoma patients. Our results demonstrate the power of an integrated approach to cancer biomarker discovery and the possibility of implementing PGSs into clinical biomarker tests.
| S-EPMC7718261 | biostudies-literature
Project description:Rapid advances in molecular microbial ecology have yielded an unprecedented amount of data about the evolutionary relationships and functional traits of microbial communities that regulate global geochemical cycles. Biogeochemical models, however, are trailing in the wake of the environmental genomics revolution, and such models rarely incorporate explicit representations of bacteria and archaea, nor are they compatible with nucleic acid or protein sequence data. Here, we present a functional gene-based framework for describing microbial communities in biogeochemical models by incorporating genomics data to provide predictions that are readily testable. To demonstrate the approach in practice, nitrogen cycling in the Arabian Sea oxygen minimum zone (OMZ) was modeled to examine key questions about cryptic sulfur cycling and dinitrogen production pathways in OMZs. Simulations support previous assertions that denitrification dominates over anammox in the central Arabian Sea, which has important implications for the loss of fixed nitrogen from the oceans. Furthermore, cryptic sulfur cycling was shown to attenuate the secondary nitrite maximum often observed in OMZs owing to changes in the composition of the chemolithoautotrophic community and dominant metabolic pathways. Results underscore the need to explicitly integrate microbes into biogeochemical models rather than just the metabolisms they mediate. By directly linking geochemical dynamics to the genetic composition of microbial communities, the method provides a framework for achieving mechanistic insights into patterns and biogeochemical consequences of marine microbes. Such an approach is critical for informing our understanding of the key role microbes play in modulating Earth's biogeochemistry.
| S-EPMC3918765 | biostudies-literature
Project description:Immune responses targeting self-proteins (autoantigens) can lead to a variety of autoimmune diseases. Identification of these antigens is important for both diagnostic and therapeutic reasons. However, current approaches to characterize autoantigens have, in most cases, met only with limited success. Here we present a synthetic representation of the complete human proteome, the T7 peptidome phage display library (T7-Pep), and demonstrate its application to autoantigen discovery. T7-Pep is composed of >413,000 36-residue, overlapping peptides that cover all open reading frames in the human genome, and can be analyzed using high-throughput DNA sequencing. We developed a phage immunoprecipitation sequencing (PhIP-Seq) methodology to identify known and previously unreported autoantibodies contained in the spinal fluid of three individuals with paraneoplastic neurological syndromes. We also show how T7-Pep can be used more generally to identify peptide-protein interactions, suggesting the broader utility of our approach for proteomic research.
| S-EPMC4169279 | biostudies-literature
Project description:Alcoholic liver disease (ALD) progresses from steatosis to alcoholic hepatitis to fibrosis and cirrhosis. Liver biopsy is considered as the gold standard method for diagnosis of liver cirrhosis and provides useful information about damaging process which is an invasive procedure with complications. Existing biomarkers in clinical practice have narrow applicability due to lack of specificity and lack of sensitivity. The objective of this article is to identify proteomic biomarker candidates for alcoholic liver cirrhosis by differential expression analysis between alcoholic liver cirrhotic and healthy subjects. Blood samples were collected from 20 subjects (10 alcoholic liver cirrhosis and 10 healthy) from R. L. Jalapa Hospital and Research Centre, Kolar, Karnataka, India. Differential protein analysis was carried out by two-dimensional electrophoresis after albumin depletion, followed by liquid chromatography-mass spectrometry. The image analysis found 46 spots in cirrhotic gel and 69 spots in healthy gel, of which 14 spots were identified with significant altered expression levels. Based on the protein score and clinical significance, among 14 spots, a total of 28 protein biomarker candidates were identified: 13 with increased expression and 15 with decreased expression were categorized in alcoholic liver cirrhosis compared to healthy subjects. Protein biomarker candidates identified by "-omics" approach based on differential expression between alcoholic liver cirrhotic subjects and healthy subjects may give better insights for diagnosis of ALD. Prioritization of candidates identified is a prerequisite for validation regimen. Biomarker candidates require verification that demonstrates the differential expression will remain detectable by assay to be used for validation.
| S-EPMC6050617 | biostudies-other