Joshua LaBaer

Reduced Incidence of Prevotella and Other Fermenters in Intestinal Microflora of Autistic Children

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.

Proteome-scale purification of human proteins from bacteria

The completion of the human genome project and the development of high-throughput approaches herald a dramatic acceleration in the pace of biological research. One of the most compelling next steps will be learning the functional roles of all proteins. Achievement of this goal depends in part on the rapid expression and isolation of proteins at large scale. We exploited recombinational cloning to facilitate the development of methods for the high-throughput purification of human proteins. cDNAs were introduced into a master vector from which they could be rapidly transferred into a variety of protein expression vectors for further analysis. A test set of 32 sequence-verified human cDNAs of various sizes and activities was moved into four different expression vectors encoding different affinity-purification tags. By means of an automatable 2-hr protein purification procedure, all 128 proteins were purified and subsequently characterized for yield, purity, and steps at which losses occurred. Under denaturing conditions when the His6 tag was used, 84% of samples were purified. Under nondenaturing conditions, both the glutathione S-transferase and maltose-binding protein tags were successful in 81% of samples. The developed methods were applied to a larger set of 336 randomly selected cDNAs. Sixty percent of these proteins were successfully purified under denaturing conditions and 82% of these under nondenaturing conditions. A relational database, FLEXProt, was built to compare properties of proteins that were successfully purified and proteins that were not. We observed that some domains in the Pfam database were found almost exclusively in proteins that were successfully purified and thus may have predictive character.

Next-generation high-density self-assembling functional protein arrays

We developed a high-density self-assembling protein microarray, based on the nucleic acid programmable protein array (NAPPA) concept, to display thousands of proteins that are produced and captured in situ from immobilized cDNA templates. We arrayed up to 1,000 unique human cDNAs and obtained high yields of protein expression and capture with minimal variation and good reproducibility. This method will enable various experimental approaches to study protein function in high throughput.

Protein Microarray Signature of Autoantibody Biomarkers for the Early Detection of Breast Cancer

Cancer patients spontaneously generate autoantibodies (AAb) to tumor-derived proteins. To detect AAb, we have probed novel high-density custom protein microarrays (NAPPA) expressing 4988 candidate tumor antigens with sera from patients with early stage breast cancer (IBC), and bound IgG was measured. We used a three-phase serial screening approach. First, a prescreen was performed to eliminate uninformative antigens. Sera from stage I-III IBC (n = 53) and healthy women (n = 53) were screened for AAb to all 4988 protein antigens. Antigens were selected if the 95th percentile of signal of cases and controls were significantly different (p < 0.05) and if the number of cases with signals above the 95th percentile of controls was significant (p < 0.05). These 761 antigens were screened using an independent set of IBC sera (n = 51) and sera from women with benign breast disease (BBD) (n = 39). From these, 119 antigens had a partial area under the ROC curve (p < 0.05), with sensitivities ranging from 9-40% at >91% specificity. Twenty-eight of these antigens were confirmed using an independent serum cohort (n = 51 cases/38 controls, p < 0.05). Using all 28 AAb, a classifier was identified with a sensitivity of 80.8% and a specificity of 61.6% (AUC = 0.756). These are potential biomarkers for the early detection of breast cancer.

Application of Protein Microarrays for Multiplexed Detection of Antibodies to Tumor Antigens in Breast Cancer

There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum; may exist in greater concentrations than their cognate antigens; and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies.

Emerging tools for real-time label-free detection of interactions on functional protein microarrays.

The availability of extensive genomic information and content has spawned an era of high‐throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions – yeast two‐hybrid and immunoprecipitation with mass spectrometric detection – have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high‐throughput technologies for displaying proteins on functional protein microarrays and the real‐time label‐free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large‐scale study of protein interactions with proteins as well as with other biomolecules.

DNASU plasmid and PSI:Biology-Materials repositories: resources to accelerate biological 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.

G1/S Cell Cycle Arrest Provides Anoikis Resistance through Erk-Mediated Bim Suppression

ABSTRACT Proper attachment to the extracellular matrix is essential for cell survival. Detachment from the extracellular matrix results in an apoptotic process termed anoikis. Anoikis induction in MCF-10A mammary epithelial cells is due not only to loss of survival signals following integrin disengagement, but also to consequent downregulation of epidermal growth factor (EGFR) and loss of EGFR-induced survival signals. Here we demonstrate that G1/S arrest by overexpression of the cyclin-dependent kinase inhibitors p16INK4a, p21Cip1, or p27Kip1 or by treatment with mimosine or aphidicolin confers anoikis resistance in MCF-10A cells. G1/S arrest-mediated anoikis resistance involves suppression of the BH3-only protein Bim. Furthermore, in G1/S-arrested cells, Erk phosphorylation is maintained in suspension and is necessary for Bim suppression. Following G1/S arrest, known proteins upstream of Erk, including Raf and Mek, are not activated. However, retained Erk activation under conditions in which Raf and Mek activation is lost is observed, suggesting that G1/S arrest acts at the level of Erk dephosphorylation. Thus, anoikis resistance by G1/S arrest is mediated by a mechanism involving Bim suppression through maintenance of Erk activation. These results provide a novel link between cell cycle arrest and survival, and this mechanism could contribute to the survival of nonreplicating, dormant tumor cells that avert apoptosis during early stages of metastasis.

Regulated ectopic expression of cyclin D1 induces transcriptional activation of the cdk inhibitor p21 gene without altering cell cycle progression.

Cyclin D1 plays a key regulatory role during the G1 phase of the cell cycle and its gene is amplified and overexpressed in many cancers. To address the relationship between cyclin D1 and other cell cycle regulatory proteins, we established human glioma and rodent fibroblast cell lines in which cyclin D1 expression could be regulated ectopically with tetracycline. In both of these cell lines, we found that ectopic expression of cyclin D1 in asynchronously growing cells was accompanied by increased levels of the p53 tumor suppressor protein and the cyclin/cdk inhibitor p21. Despite the induction of these cell cycle inhibitory proteins, cyclin D1-associated cdk kinase remained activated and the cells grew essentially like that of the parent cells. Although growth parameters were unchanged in these cells, morphological changes were clearly identifiable and anchorage independent growth was observed in NIH3T3 cells. In a first step toward elaborating the mechanism for cyclin D1-mediated induction of p21 gene expression we show that co-expression of E2F-1 and DP-1 can specifically transactivate the p21 promoter. In support of these findings and a direct effect of E2F on induction of p21 gene expression a putative E2F binding site was identified within the p21 promoter. In summary, our results demonstrate that ectopic expression of cyclin D1 can induce gene expression of the cdk inhibitor p21 through an E2F mechanism the consequences of which are not to growth arrest cells but possibly to stabilize cyclin D1/cdk function.

Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large‐scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.