Early detection of disease is essential for alleviating disease burden, increasing success rate and decreasing mortality rate especially for cancer. To improve disease diagnostics, many candidate biomarkers have been suggested using molecular biology or image analysis techniques over the past decade. The receiver operating characteristics (ROC) curve is a standard technique to evaluate a diagnostic accuracy of biomarkers, but it has some limitations especially for heterogeneous diseases. As an alternative of the ROC curve analysis, we suggest a jittered dot plot (JDP) and JDP-based evaluation measures, above mean difference (AMD) and averaged above mean difference (AAMD). We demonstrate how JDP and AMD or AAMD together better evaluate biomarkers than the standard ROC curve. We analyze real and heterogeneous basal-like breast cancer data.

Rationale: Cell-free protein microarrays display naturally-folded proteins based on just-in-time in situ synthesis, and have made important contributions to basic and translational research. However, the risk of spot-to-spot cross-talk from protein diffusion during expression has limited the feature density of these arrays.

Methods: In this work, we developed the Multiplexed Nucleic Acid Programmable Protein Array (M-NAPPA), which significantly increases the number of displayed proteins by multiplexing as many as five different gene plasmids within a printed spot.

Results: Even when proteins of different sizes were displayed within the same feature, they were readily detected using protein-specific antibodies. Protein-protein interactions and serological antibody assays using human viral proteome microarrays demonstrated that comparable hits were detected by M-NAPPA and non-multiplexed NAPPA arrays. An ultra-high density proteome microarray displaying > 16k proteins on a single microscope slide was produced by combining M-NAPPA with a photolithography-based silicon nano-well platform. Finally, four new tuberculosis-related antigens in guinea pigs vaccinated with Bacillus Calmette-Guerin (BCG) were identified with M-NAPPA and validated with ELISA.

Conclusion: All data demonstrate that multiplexing features on a protein microarray offer a cost-effective fabrication approach and have the potential to facilitate high throughput translational research.

The mission of the DNASU Plasmid Repository is to accelerate research by providing high-quality, annotated plasmid samples and online plasmid resources to the research community through the curated DNASU database, website and repository (http://dnasu.asu.edu or http://dnasu.org). The collection includes plasmids from grant-funded, high-throughput cloning projects performed in our laboratory, plasmids from external researchers, and large collections from consortia such as the ORFeome Collaboration and the NIGMS-funded Protein Structure Initiative: Biology (PSI:Biology). Through DNASU, researchers can search for and access detailed information about each plasmid such as the full length gene insert sequence, vector information, associated publications, and links to external resources that provide additional protein annotations and experimental protocols. Plasmids can be requested directly through the DNASU website. DNASU and the PSI:Biology-Materials Repositories were previously described in the 2010 NAR Database Issue (Cormier, C.Y., Mohr, S.E., Zuo, D., Hu, Y., Rolfs, A., Kramer, J., Taycher, E., Kelley, F., Fiacco, M., Turnbull, G. et al. (2010) Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community. Nucleic Acids Res., 38, D743–D749.). In this update we will describe the plasmid collection and highlight the new features in the website redesign, including new browse/search options, plasmid annotations and a dynamic vector mapping feature that was developed in collaboration with LabGenius. Overall, these plasmid resources continue to enable research with the goal of elucidating the role of proteins in both normal biological processes and disease.

To address the need to study frozen clinical specimens using next-generation RNA, DNA, chromatin immunoprecipitation (ChIP) sequencing and protein analyses, we developed a biobank work flow to prospectively collect biospecimens from patients with renal cell carcinoma (RCC). We describe our standard operating procedures and work flow to annotate pathologic results and clinical outcomes. We report quality control outcomes and nucleic acid yields of our RCC submissions (N=16) to The Cancer Genome Atlas (TCGA) project, as well as newer discovery platforms, by describing mass spectrometry analysis of albumin oxidation in plasma and 6 ChIP sequencing libraries generated from nephrectomy specimens after histone H3 lysine 36 trimethylation (H3K36me3) immunoprecipitation. From June 1, 2010, through January 1, 2013, we enrolled 328 patients with RCC. Our mean (SD) TCGA RNA integrity numbers (RINs) were 8.1 (0.8) for papillary RCC, with a 12.5% overall rate of sample disqualification for RIN <7. Banked plasma had significantly less albumin oxidation (by mass spectrometry analysis) than plasma kept at 25°C (P<.001). For ChIP sequencing, the FastQC score for average read quality was at least 30 for 91% to 95% of paired-end reads. In parallel, we analyzed frozen tissue by RNA sequencing; after genome alignment, only 0.2% to 0.4% of total reads failed the default quality check steps of Bowtie2, which was comparable to the disqualification ratio (0.1%) of the 786-O RCC cell line that was prepared under optimal RNA isolation conditions. The overall correlation coefficients for gene expression between Mayo Clinic vs TCGA tissues ranged from 0.75 to 0.82. These data support the generation of high-quality nucleic acids for genomic analyses from banked RCC. Importantly, the protocol does not interfere with routine clinical care. Collections over defined time points during disease treatment further enhance collaborative efforts to integrate genomic information with outcomes.

Background: Tissue-specific RNA plasticity broadly impacts the development, tissue identity and adaptability of all organisms, but changes in composition, expression levels and its impact on gene regulation in different somatic tissues are largely unknown. Here we developed a new method, polyA-tagging and sequencing (PAT-Seq) to isolate high-quality tissue-specific mRNA from Caenorhabditis elegans intestine, pharynx and body muscle tissues and study changes in their tissue-specific transcriptomes and 3’UTRomes.

Results: We have identified thousands of novel genes and isoforms differentially expressed between these three tissues. The intestine transcriptome is expansive, expressing over 30% of C. elegans mRNAs, while muscle transcriptomes are smaller but contain characteristic unique gene signatures. Active promoter regions in all three tissues reveal both known and novel enriched tissue-specific elements, along with putative transcription factors, suggesting novel tissue-specific modes of transcription initiation. We have precisely mapped approximately 20,000 tissue-specific polyadenylation sites and discovered that about 30% of transcripts in somatic cells use alternative polyadenylation in a tissue-specific manner, with their 3’UTR isoforms significantly enriched with microRNA targets.

Conclusions: For the first time, PAT-Seq allowed us to directly study tissue specific gene expression changes in an in vivo setting and compare these changes between three somatic tissues from the same organism at single-base resolution within the same experiment. We pinpoint precise tissue-specific transcriptome rearrangements and for the first time link tissue-specific alternative polyadenylation to miRNA regulation, suggesting novel and unexplored tissue-specific post-transcriptional regulatory networks in somatic cells.

Sera from patients with ovarian cancer contain autoantibodies (AAb) to tumor-derived proteins that are potential biomarkers for early detection. To detect AAb, we probed high-density programmable protein microarrays (NAPPA) expressing 5177 candidate tumor antigens with sera from patients with serous ovarian cancer (n = 34 cases/30 controls) and measured bound IgG. Of these, 741 antigens were selected and probed with an independent set of ovarian cancer sera (n = 60 cases/60 controls). Twelve potential autoantigens were identified with sensitivities ranging from 13 to 22% at >93% specificity. These were retested using a Luminex bead array using 60 cases and 60 controls, with sensitivities ranging from 0 to 31.7% at 95% specificity. Three AAb (p53, PTPRA, and PTGFR) had area under the curve (AUC) levels >60% (p < 0.01), with the partial AUC (SPAUC) over 5 times greater than for a nondiscriminating test (p < 0.01). Using a panel of the top three AAb (p53, PTPRA, and PTGFR), if at least two AAb were positive, then the sensitivity was 23.3% at 98.3% specificity. AAb to at least one of these top three antigens were also detected in 7/20 sera (35%) of patients with low CA 125 levels and 0/15 controls. AAb to p53, PTPRA, and PTGFR are potential biomarkers for the early detection of ovarian cancer.

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.

High proportions of autistic children suffer from gastrointestinal (GI) disorders, implying a link between autism and abnormalities in gut microbial functions. Increasing evidence from recent high-throughput sequencing analyses indicates that disturbances in composition and diversity of gut microbiome are associated with various disease conditions. However, microbiome-level studies on autism are limited and mostly focused on pathogenic bacteria. Therefore, here we aimed to define systemic changes in gut microbiome associated with autism and autism-related GI problems. We recruited 20 neurotypical and 20 autistic children accompanied by a survey of both autistic severity and GI symptoms. By pyrosequencing the V2/V3 regions in bacterial 16S rDNA from fecal DNA samples, we compared gut microbiomes of GI symptom-free neurotypical children with those of autistic children mostly presenting GI symptoms. Unexpectedly, the presence of autistic symptoms, rather than the severity of GI symptoms, was associated with less diverse gut microbiomes. Further, rigorous statistical tests with multiple testing corrections showed significantly lower abundances of the genera Prevotella, Coprococcus, and unclassified Veillonellaceae in autistic samples. These are intriguingly versatile carbohydrate-degrading and/or fermenting bacteria, suggesting a potential influence of unusual diet patterns observed in autistic children. However, multivariate analyses showed that autism-related changes in both overall diversity and individual genus abundances were correlated with the presence of autistic symptoms but not with their diet patterns. Taken together, autism and accompanying GI symptoms were characterized by distinct and less diverse gut microbial compositions with lower levels of Prevotella, Coprococcus, and unclassified Veillonellaceae.