ASU Scholarship Showcase

Many drugs are effective in the early stage of treatment, but patients develop drug resistance after a certain period of treatment, causing failure of the therapy. An important example is Herceptin, a popular monoclonal antibody drug for breast cancer by specifically targeting human epidermal growth factor receptor 2 (Her2). Here we demonstrate a quantitative binding kinetics analysis of drug-target interactions to investigate the molecular scale origin of drug resistance. Using a surface plasmon resonance imaging, we measured the in situ Herceptin-Her2 binding kinetics in single intact cancer cells for the first time, and observed significantly weakened Herceptin-Her2 interactions in Herceptin-resistant cells, compared to those in Herceptin-sensitive cells. We further showed that the steric hindrance of Mucin-4, a membrane protein, was responsible for the altered drug-receptor binding. This effect of a third molecule on drug-receptor interactions cannot be studied using traditional purified protein methods, demonstrating the importance of the present intact cell-based binding kinetics analysis.

Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM_2.5 index. The results demonstrate that the image analysis method provides good prediction of PM_2.5 indexes, and different features have different significance levels in the prediction.

Background: Obesity is a metabolic disease caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to investigate the role of skeletal muscle DNA methylation in combination with transcriptomic changes in obesity.

Results: Muscle biopsies were obtained basally from lean (n = 12; BMI = 23.4 ± 0.7 kg/m[superscript 2]) and obese (n = 10; BMI = 32.9 ± 0.7 kg/m[superscript 2]) participants in combination with euglycemic-hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing (RRBS) next-generation methylation and microarray analyses on DNA and RNA isolated from vastus lateralis muscle biopsies. There were 13,130 differentially methylated cytosines (DMC; uncorrected P < 0.05) that were altered in the promoter and untranslated (5' and 3'UTR) regions in the obese versus lean analysis. Microarray analysis revealed 99 probes that were significantly (corrected P < 0.05) altered. Of these, 12 genes (encompassing 22 methylation sites) demonstrated a negative relationship between gene expression and DNA methylation. Specifically, sorbin and SH3 domain containing 3 (SORBS3) which codes for the adapter protein vinexin was significantly decreased in gene expression (fold change −1.9) and had nine DMCs that were significantly increased in methylation in obesity (methylation differences ranged from 5.0 to 24.4 %). Moreover, differentially methylated region (DMR) analysis identified a region in the 5'UTR (Chr.8:22,423,530–22,423,569) of SORBS3 that was increased in methylation by 11.2 % in the obese group. The negative relationship observed between DNA methylation and gene expression for SORBS3 was validated by a site-specific sequencing approach, pyrosequencing, and qRT-PCR. Additionally, we performed transcription factor binding analysis and identified a number of transcription factors whose binding to the differentially methylated sites or region may contribute to obesity.

Conclusions: These results demonstrate that obesity alters the epigenome through DNA methylation and highlights novel transcriptomic changes in SORBS3 in skeletal muscle.

Background: Our publication of the BitTorious portal [1] demonstrated the ability to create a privatized distributed data warehouse of sufficient magnitude for real-world bioinformatics studies using minimal changes to the standard BitTorrent tracker protocol. In this second phase, we release a new server-side specification to accept anonymous philantropic storage donations by the general public, wherein a small portion of each user’s local disk may be used for archival of scientific data. We have implementated the server-side announcement and control portions of this BitTorrent extension into v3.0.0 of the BitTorious portal, upon which compatible clients may be built.

Results: Automated test cases for the BitTorious Volunteer extensions have been added to the portal’s v3.0.0 release, supporting validation of the “peer affinity” concept and announcement protocol introduced by this specification. Additionally, a separate reference implementation of affinity calculation has been provided in C++ for informaticians wishing to integrate into libtorrent-based projects.

Conclusions: The BitTorrent “affinity” extensions as provided in the BitTorious portal reference implementation allow data publishers to crowdsource the extreme storage prerequisites for research in “big data” fields. With sufficient awareness and adoption of BitTorious Volunteer-based clients by the general public, the BitTorious portal may be able to provide peta-scale storage resources to the scientific community at relatively insignificant financial cost.

Background: Centralized silos of genomic data are architecturally easier to initially design, develop and deploy than distributed models. However, as interoperability pains in EHR/EMR, HIE and other collaboration-centric life sciences domains have taught us, the core challenge of networking genomics systems is not in the construction of individual silos, but the interoperability of those deployments in a manner embracing the heterogeneous needs, terms and infrastructure of collaborating parties. This article demonstrates the adaptation of BitTorrent to private collaboration networks in an authenticated, authorized and encrypted manner while retaining the same characteristics of standard BitTorrent.

Results: The BitTorious portal was sucessfully used to manage many concurrent domestic Bittorrent clients across the United States: exchanging genomics data payloads in excess of 500GiB using the uTorrent client software on Linux, OSX and Windows platforms. Individual nodes were sporadically interrupted to verify the resilience of the system to outages of a single client node as well as recovery of nodes resuming operation on intermittent Internet connections.

Conclusions: The authorization-based extension of Bittorrent and accompanying BitTorious reference tracker and user management web portal provide a free, standards-based, general purpose and extensible data distribution system for large ‘omics collaborations.

Background: Immunosignaturing is a new peptide microarray based technology for profiling of humoral immune responses. Despite new challenges, immunosignaturing gives us the opportunity to explore new and fundamentally different research questions. In addition to classifying samples based on disease status, the complex patterns and latent factors underlying immunosignatures, which we attempt to model, may have a diverse range of applications.

Methods: We investigate the utility of a number of statistical methods to determine model performance and address challenges inherent in analyzing immunosignatures. Some of these methods include exploratory and confirmatory factor analyses, classical significance testing, structural equation and mixture modeling.

Results: We demonstrate an ability to classify samples based on disease status and show that immunosignaturing is a very promising technology for screening and presymptomatic screening of disease. In addition, we are able to model complex patterns and latent factors underlying immunosignatures. These latent factors may serve as biomarkers for disease and may play a key role in a bioinformatic method for antibody discovery.

Conclusion: Based on this research, we lay out an analytic framework illustrating how immunosignatures may be useful as a general method for screening and presymptomatic screening of disease as well as antibody discovery.

We have previously hypothesized a biological pathway of activity-dependent synaptic plasticity proteins that addresses the dual genetic and environmental contributions to schizophrenia. Accordingly, variations in the immediate early gene EGR3, and its target ARC, should influence schizophrenia susceptibility. We used a pooled Next-Generation Sequencing approach to identify variants across these genes in U.S. populations of European (EU) and African (AA) descent. Three EGR3 and one ARC SNP were selected and genotyped for validation, and three SNPs were tested for association in a replication cohort. In the EU group of 386 schizophrenia cases and 150 controls EGR3 SNP rs1877670 and ARC SNP rs35900184 showed significant associations (p = 0.0078 and p = 0.0275, respectively). In the AA group of 185 cases and 50 controls, only the ARC SNP revealed significant association (p = 0.0448). The ARC SNP did not show association in the Han Chinese (CH) population. However, combining the EU, AA, and CH groups revealed a highly significant association of ARC SNP rs35900184 (p = 2.353 x 10^-7; OR [95% CI] = 1.54 [1.310–1.820]). These findings support previously reported associations between EGR3 and schizophrenia. Moreover, this is the first report associating an ARC SNP with schizophrenia and supports recent large-scale GWAS findings implicating the ARC complex in schizophrenia risk. These results support the need for further investigation of the proposed pathway of environmentally responsive, synaptic plasticity-related, schizophrenia genes.

A novel portable wireless volatile organic compound (VOC) monitoring device with disposable sensors is presented. The device is miniaturized, light, easy-to-use, and cost-effective. Different field tests have been carried out to identify the operational, analytical, and functional performance of the device and its sensors. The device was compared to a commercial photo-ionization detector, gas chromatography-mass spectrometry, and carbon monoxide detector. In addition, environmental operational conditions, such as barometric change, temperature change and wind conditions were also tested to evaluate the device performance. The multiple comparisons and tests indicate that the proposed VOC device is adequate to characterize personal exposure in many real-world scenarios and is applicable for personal daily use.

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population.

Piezoresistivity is a fundamental property of materials that has found many device applications. Here we report piezoresistivity in double helical DNA molecules. By studying the dependence of molecular conductance and piezoresistivity of single DNA molecules with different sequences and lengths, and performing molecular orbital calculations, we show that the piezoresistivity of DNA is caused by force-induced changes in the π–π electronic coupling between neighbouring bases, and in the activation energy of hole hopping. We describe the results in terms of thermal activated hopping model together with the ladder-based mechanical model for DNA proposed by de Gennes.