Deep Proteomic Deconvolution of Interferons and HBV Transfection Effects on a Hepatoblastoma Cell Line

Interferons are commonly utilized in the treatment of chronic hepatitis B virus (HBV) infection but are not effective for all patients. A deep understanding of the limitations of interferon treatment requires delineation of its activity at multiple "omic"levels. While myriad studies have characterized the transcriptomic effects of interferon treatment, surprisingly, few have examined interferon-induced effects at the proteomic level. To remedy this paucity, we stimulated HepG2 cells with both IFN-α and IFN-λ and performed proteomic analysis versus unstimulated cells. Alongside, we examined the effects of HBV transfection in the same cell line, reasoning that parallel IFN and HBV analysis might allow determination of cases where HBV transfection counters the effects of interferons. More than 6000 proteins were identified, with multiple replicates allowing for differential expression analysis at high confidence. Drawing on a compendium of transcriptomic data, as well as proteomic half-life data, we suggest means by which transcriptomic results diverge from our proteomic results. We also invoke a recent multiomic study of HBV-related hepatocarcinoma (HCC), showing that despite HBV\u27s role in initiating HCC, the regulated proteomic landscapes of HBV transfection and HCC do not strongly align. Special focus is applied to the proteasome, with numerous components divergently altered under IFN and HBV-transfection conditions. We also examine alterations of other protein groups relevant to HLA complex peptide display, unveiling intriguing alterations in a number of ubiquitin ligases. Finally, we invoke genome-scale metabolic modeling to predict relevant alterations to the metabolic landscape under experimental conditions. Our data should be useful as a resource for interferon and HBV researchers

Serum miRNA125a-5p, miR-125b-5p, and miR-433-5p as biomarkers to differentiate between posterior circulation stroke and peripheral vertigo

BACKGROUND: Acute vertigo is a common presentation of inner ear disease. However, it can also be caused by more serious conditions, especially posterior circulation stroke. Differentiating between these two conditions by clinical presentations and imaging studies during the acute phase can be challenging. This study aimed to identify serum microRNA (miRNA) candidates that could differentiate between posterior circulation stroke and peripheral vertigo, among patients presenting with acute vertigo. METHODS: Serum levels of six miRNAs including miR-125a-5p, miR-125b-5p, miR-143-3p, miR-342-3p, miR-376a-3p, and miR-433-5p were evaluated. Using quantitative reverse-transcription polymerase chain reaction (RT-qPCR), the serum miRNAs were assessed in the acute phase and at a 90 day follow-up visit. RESULTS: A total of 58 patients with posterior circulation stroke (n = 23) and peripheral vertigo (n = 35) were included in the study. Serum miR-125a-5p (P = 0.001), miR-125b-5p (P <  0.001), miR-143-3p (P = 0.014) and miR-433-5p (P = 0.0056) were present at significantly higher levels in the acute phase, in the patients with posterior circulation infarction. Based on the area under the receiver operating characteristic curve (AUROC) only miR-125a-5p (0.75), miR-125b-5p(0.77), and miR-433-5p (0.71) had an acceptable discriminative ability to differentiate between the central and peripheral vertigo. A combination of miRNAs revealed no significant improvement of AUROC when compared to single miRNAs. CONCLUSION: This study demonstrated the potential of serum miR-125a-5p, miR-125b-5p, and miR-433-5p as biomarkers to assist in the diagnosis of posterior circulation infarction among patients presenting with acute vertigo

An Attempt to Understand Kidney's Protein Handling Function by Comparing Plasma and Urine Proteomes

With the help of proteomics technology, the human plasma and urine proteomes, which closely represent the protein compositions of the input and output of the kidney, respectively, have been profiled in much greater detail by different research teams. Many datasets have been accumulated to form “reference profiles” of the plasma and urine proteomes. Comparing these two proteomes may help us understand the protein handling aspect of kidney function in a way, however, which has been unavailable until the recent advances in proteomics technology.After removing secreted proteins downstream of the kidney, 2611 proteins in plasma and 1522 in urine were identified with high confidence and compared based on available proteomic data to generate three subproteomes, the plasma-only subproteome, the plasma-and-urine subproteome, and the urine-only subproteome, and they correspond to three groups of proteins that are handled in three different ways by the kidney. The available experimental molecular weights of the proteins in the three subproteomes were collected and analyzed. Since the functions of the overrepresented proteins in the plasma-and-urine subproteome are probably the major functions that can be routinely regulated by excretion from the kidney in physiological conditions, Gene Ontology term enrichment in the plasma-and-urine subproteome versus the whole plasma proteome was analyzed. Protease activity, calcium and growth factor binding proteins, and coagulation and immune response-related proteins were found to be enriched.The comparison method described in this paper provides an illustration of a new approach for studying organ functions with a proteomics methodology. Because of its distinctive input (plasma) and output (urine), it is reasonable to predict that the kidney will be the first organ whose functions are further elucidated by proteomic methods in the near future. It can also be anticipated that there will be more applications for proteomics in organ function research

An integrative multi-platform analysis for discovering biomarkers of osteosarcoma

<p>Abstract</p> <p>Background</p> <p>SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry) has become an attractive approach for cancer biomarker discovery due to its ability to resolve low mass proteins and high-throughput capability. However, the analytes from mass spectrometry are described only by their mass-to-charge ratio (<it>m</it>/<it>z</it>) values without further identification and annotation. To discover potential biomarkers for early diagnosis of osteosarcoma, we designed an integrative workflow combining data sets from both SELDI-TOF-MS and gene microarray analysis.</p> <p>Methods</p> <p>After extracting the information for potential biomarkers from SELDI data and microarray analysis, their associations were further inferred by link-test to identify biomarkers that could likely be used for diagnosis. Immuno-blot analysis was then performed to examine whether the expression of the putative biomarkers were indeed altered in serum from patients with osteosarcoma.</p> <p>Results</p> <p>Six differentially expressed protein peaks with strong statistical significances were detected by SELDI-TOF-MS. Four of the proteins were up-regulated and two of them were down-regulated. Microarray analysis showed that, compared with an osteoblastic cell line, the expression of 653 genes was changed more than 2 folds in three osteosarcoma cell lines. While expression of 310 genes was increased, expression of the other 343 genes was decreased. The two sets of biomarkers candidates were combined by the link-test statistics, indicating that 13 genes were potential biomarkers for early diagnosis of osteosarcoma. Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.</p> <p>Conclusion</p> <p>Link-test on datasets from both SELDI-TOF-MS and microarray high-throughput analysis can accelerate the identification of tumor biomarkers. The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.</p

Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers

Computational prediction and experimental validation associating FABP-1 and pancreatic adenocarcinoma with diabetes

<p/> <p>Background</p> <p>Pancreatic cancer, composed principally of pancreatic adenocarcinoma (PaC), is the fourth leading cause of cancer death in the United States. PaC-associated diabetes may be a marker of early disease. We sought to identify molecules associated with PaC and PaC with diabetes (PaC-DM) using a novel translational bioinformatics approach. We identified fatty acid binding protein-1 (FABP-1) as one of several candidates. The primary aim of this pilot study was to experimentally validate the predicted association between FABP-1 with PaC and PaC with diabetes.</p> <p>Methods</p> <p>We searched public microarray measurements for genes that were specifically highly expressed in PaC. We then filtered for proteins with known involvement in diabetes. Validation of FABP-1 was performed via antibody immunohistochemistry on formalin-fixed paraffin embedded pancreatic tissue microarrays (FFPE TMA). FFPE TMA were constructed using148 cores of pancreatic tissue from 134 patients collected between 1995 and 2002 from patients who underwent pancreatic surgery. Primary analysis was performed on 21 normal and 60 pancreatic adenocarcinoma samples, stratified for diabetes. Clinical data on samples was obtained via retrospective chart review. Serial sections were cut per standard protocol. Antibody staining was graded by an experienced pathologist on a scale of 0-3. Bivariate and multivariate analyses were conducted to assess FABP-1 staining and clinical characteristics.</p> <p>Results</p> <p>Normal samples were significantly more likely to come from younger patients. PaC samples were significantly more likely to stain for FABP-1, when FABP-1 staining was considered a binary variable. Compared to normals, there was significantly increased staining in diabetic PaC samples (p = 0.004) and there was a trend towards increased staining in the non-diabetic PaC group (p = 0.07). In logistic regression modeling, FABP-1 staining was significantly associated with diagnosis of PaC (OR 8.6 95% CI 1.1-68, p = 0.04), though age was a confounder.</p> <p>Conclusions</p> <p>Compared to normal controls, there was a significant positive association between FABP-1 staining and PaC on FFPE-TMA, strengthened by the presence of diabetes. Further studies with closely phenotyped patient samples are required to understand the true relationship between FABP-1, PaC and PaC-associated diabetes. A translational bioinformatics approach has potential to identify novel disease associations and potential biomarkers in gastroenterology.</p

TLR7 single-nucleotide polymorphisms in the 3' untranslated region and intron 2 independently contribute to systemic lupus erythematosus in Japanese women: a case-control association study

IntroductionThe Toll-like receptor 7 (TLR7) gene, encoded on human chromosome Xp22.3, is crucial for type I interferon production. A recent multicenter study in East Asian populations, comprising Chinese, Korean and Japanese participants, identified an association of a TLR7 single-nucleotide polymorphism (SNP) located in the 3\u27 untranslated region (3\u27 UTR), rs3853839, with systemic lupus erythematosus (SLE), especially in males, although some difference was observed among the tested populations. To test whether additional polymorphisms contribute to SLE in Japanese, we systematically analyzed the association of TLR7 with SLE in a Japanese female population.MethodsA case-control association study was conducted on eight tag SNPs in the TLR7 region, including rs3853839, in 344 Japanese females with SLE and 274 healthy female controls.ResultsIn addition to rs3853839, two SNPs in intron 2, rs179019 and rs179010, which were in moderate linkage disequilibrium with each other (r2 = 0.53), showed an association with SLE (rs179019: P = 0.016, odds ratio (OR) 2.02, 95% confidence interval (95% CI) 1.15 to 3.54; rs179010: P = 0.018, OR 1.75, 95% CI 1.10 to 2.80 (both under the recessive model)). Conditional logistic regression analysis revealed that the association of the intronic SNPs and the 3\u27 UTR SNP remained significant after we adjusted them for each other. When only the patients and controls carrying the risk genotypes at the 3\u27 UTR SNPpositionwere analyzed, the risk of SLE was significantly increased when the individuals also carried the risk genotypes at both of the intronic SNPs (P = 0.0043, OR 2.45, 95% CI 1.31 to 4.60). Furthermore, the haplotype containing the intronic risk alleles in addition to the 3\u27 UTR risk allele was associated with SLE under the recessive model (P = 0.016, OR 2.37, 95% CI 1.17 to 4.80), but other haplotypes were not associated with SLE.ConclusionsThe TLR7 intronic SNPs rs179019 and rs179010 are associated with SLE independently of the 3\u27 UTR SNP rs3853839 in Japanese women. Our findings support a role of TLR7 in predisposition for SLE in Asian populations

Localization and trafficking of aquaporin 2 in the kidney

Aquaporins (AQPs) are membrane proteins serving in the transfer of water and small solutes across cellular membranes. AQPs play a variety of roles in the body such as urine formation, prevention from dehydration in covering epithelia, water handling in the blood–brain barrier, secretion, conditioning of the sensory system, cell motility and metastasis, formation of cell junctions, and fat metabolism. The kidney plays a central role in water homeostasis in the body. At least seven isoforms, namely AQP1, AQP2, AQP3, AQP4, AQP6, AQP7, and AQP11, are expressed. Among them, AQP2, the anti-diuretic hormone (ADH)-regulated water channel, plays a critical role in water reabsorption. AQP2 is expressed in principal cells of connecting tubules and collecting ducts, where it is stored in Rab11-positive storage vesicles in the basal state. Upon ADH stimulation, AQP2 is translocated to the apical plasma membrane, where it serves in the influx of water. The translocation process is regulated through the phosphorylation of AQP2 by protein kinase A. As soon as the stimulation is terminated, AQP2 is retrieved to early endosomes, and then transferred back to the Rab 11-positive storage compartment. Some AQP2 is secreted via multivesicular bodies into the urine as exosomes. Actin plays an important role in the intracellular trafficking of AQP2. Recent findings have shed light on the molecular basis that controls the trafficking of AQP2

Nanostructural and Transcriptomic Analyses of Human Saliva Derived Exosomes

Exosomes, derived from endocytic membrane vesicles are thought to participate in cell-cell communication and protein and RNA delivery. They are ubiquitous in most body fluids (breast milk, saliva, blood, urine, malignant ascites, amniotic, bronchoalveolar lavage, and synovial fluids). In particular, exosomes secreted in human saliva contain proteins and nucleic acids that could be exploited for diagnostic purposes. To investigate this potential use, we isolated exosomes from human saliva and characterized their structural and transcriptome contents.Exosomes were purified by differential ultracentrifugation and identified by immunoelectron microscopy (EM), flow cytometry, and Western blot with CD63 and Alix antibodies. We then described the morphology, shape, size distribution, and density using atomic force microscopy (AFM). Microarray analysis revealed that 509 mRNA core transcripts are relatively stable and present in the exosomes. Exosomal mRNA stability was determined by detergent lysis with RNase A treatment. In vitro, fluorescently labeled saliva exosomes could communicate with human keratinocytes, transferring their genetic information to human oral keratinocytes to alter gene expression at a new location.Our findings are consistent with the hypothesis that exosomes shuttle RNA between cells and that the RNAs present in the exosomes may be a possible resource for disease diagnostics