Xia, L. | Search bioRxiv

bioRxiv2018

Identification of a Nocardia seriolae secreted protein targeting host cell mitochondria and inducing apoptosis in fathead minnow (FHM) cells

Nocardia seriolae, is a Gram-positive, partially acid-fast, aerobic, and filamentous bacterium. This bacterium is the main pathogen of fish nocardiosis. A bioinformatic analysis based on the genomic sequence of the N. seriolae strain ZJ0503 showed that ORF3141 encoded a secreted protein with a signal peptide at the N-terminate which may target the mitochondria in the host cell. However, the functions of this protein and its homologs remain unknown. In this study, we experimentally tested the bioinformatic prediction on this protein. Mass spectrometry analysis of the extracellular products from N. seriolae showed that ORF3141 was a secreted protein. Subcellular localization of the ORF3141-GFP fusion protein revealed that the green fluorescence protein co-localized with the mitochondria, while ORF3141{Delta}sig-GFP (with the signal peptide deleted) fusion protein was evenly distributed in the whole cell of fathead minnow (FHM) cells. Thus, the N-terminate signal peptide had a significant impact on mitochondrial targeting. Notably, the expression of ORF3141 protein changed the distribution of mitochondria from perinuclear halo into lumps in the transfected FHM cells. In addition, apoptotic features were found in the transfected FHM cells by overexpression of ORF3141 and ORF3141{Delta}sig proteins, respectively. Quantitative assays of mitochondrial membrane potential value, caspase-3 activity and apoptosis-related gene mRNA expression suggested that cell apoptosis was induced in the transfected FHM cells. In conclusion, the ORF3141 was a secreted protein of N. seriolae that targeted host cell mitochondria and induced apoptosis in FHM cells. This protein may participate in the cell apoptosis regulation and plays an important role in the pathogenesis of N. seriolae.\n\nAuthor summaryNocardia seriolae is the causative pathogen responsible for fish nocardiosis. This facultative intercellular bacterium, adapts to survive and colonize by evading intracellular killing after being engulfed with macrophages in the host. Despite considerable economic losses caused by N. seriolae in fish infection, the pathogenic mechanism and specific virulence factor of this bacterium remain ambiguous. In this study, the characteristic of ORF3141 protein function was investigated by subcellular localization and its possible contributions on the ability of N. seriolae to induce apoptosis in transfected fathead minnow (FHM) cells was investigated. Here, we confirmed that ORF3141 was a secreted protein that targeted host cell mitochondria and induced cell apoptosis in FHM cells. Interestingly, after deleting the signal peptide, ORF3141{Delta}sig protein was evenly distributed in the whole host cell and did not co-localize with the mitochondria which could also induce cell apoptosis. Thus, the N-terminate signal peptide played an important role in mitochondrial targeting, and the domain part without the signal peptide had a critical relationship with cell apoptosis. These results demonstrated that ORF3141 mays act as a potential virulence factor that induces apoptosis in fish cells. This protein is significant to elucidate the pathogenic mechanism of N. seriolae and this study mays provide beneficial insight to prevent and treat fish nocardiosis.

pathology↗

bioRxiv2018

Subset-Based Analysis using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes

ObjectivesClassical methods for combining summary data from genome-wide association studies (GWAS) only use marginal genetic effects and power can be compromised in the presence of heterogeneity. We aim to enhance the discovery of novel associated loci in the presence of heterogeneity of genetic effects in sub-groups defined by an environmental factor.\n\nMethodsWe present a p-value Assisted Subset Testing for Associations (pASTA) framework that generalizes the previously proposed association analysis based on subsets (ASSET) method by incorporating gene-environment (G-E) interactions into the testing procedure. We conduct simulation studies and provide two data examples.\n\nResultsSimulation studies show that our proposal is more powerful than methods based on marginal associations in the presence of G-E interactions and maintains comparable power even in their absence. Both data examples demonstrate that our method can increase power to detect overall genetic associations and identify novel studies/phenotypes that contribute to the association.\n\nConclusionsOur proposed method can be a useful screening tool to identify candidate single nucleotide polymorphisms (SNPs) that are potentially associated with the trait(s) of interest for further validation. It also allows researchers to determine the most probable subset of traits that exhibit genetic associations in addition to the enhancement of power.

genetics↗

bioRxiv2016

Baseline mutation profiling of 1134 samples of circulating cell-free DNA and blood cells from healthy individuals

The molecular alteration in circulating cell-free DNA (cfDNA) in plasma can reflect the status of the human body in a timely manner. Hence, cfDNA has emerged as important biomarkers in clinical diagnostics, particularly in cancer. However, somatic mutations are also commonly found in healthy individuals, which extensively interfere with the diagnostic results in cancer. This study was designed to examine the background somatic mutations in white blood cells (WBC) and cfDNA for healthy controls based on the sequencing data from 1134 samples, to understand the patterns and origin of mutations detected in cfDNA. We determined the mutation frequencies in both the WBC and cfDNA groups of the samples by a panel of 50 cancer-associated genes which covered 20K nucleotide regions using ultra-deep sequencing with average depth >40000 folds. Our results showed that most of mutations in cfDNA originated from WBC. We also observed that NPM1 gene was the most frequently mutant gene in both WBC and cfDNA. Our study highlighted the importance of sequencing both cfDNA and WBC, to improve the sensitivity and accuracy for calling cancer-related mutations from circulating tumor DNA, and shielded light on developing the early cancer diagnosis by cfDNA sequencing.

bioinformatics↗