Paul S. Kayne

A high-resolution association mapping panel for the dissection of complex traits in mice.

Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.

Network for Activation of Human Endothelial Cells by Oxidized Phospholipids: A Critical Role of Heme Oxygenase 1

Rationale: Oxidized palmitoyl arachidonyl phosphatidylcholine (Ox-PAPC) accumulates in atherosclerotic lesions, is proatherogenic, and influences the expression of more than 1000 genes in endothelial cells. Objective: To elucidate the major pathways involved in Ox-PAPC action, we conducted a systems analysis of endothelial cell gene expression after exposure to Ox-PAPC. Methods and Results: We used the variable responses of primary endothelial cells from 149 individuals exposed to Ox-PAPC to construct a network that consisted of 11 groups of genes, or modules. Modules were enriched for a broad range of Gene Ontology pathways, some of which have not been identified previously as major Ox-PAPC targets. Further validating our method of network construction, modules were consistent with relationships established by cell biology studies of Ox-PAPC effects on endothelial cells. This network provides novel hypotheses about molecular interactions, as well as candidate molecular regulators of inflammation and atherosclerosis. We validated several hypotheses based on network connections and genomic association. Our network analysis predicted that the hub gene CHAC1 (cation transport regulator homolog 1) was regulated by the ATF4 (activating transcription factor 4) arm of the unfolded protein response pathway, and here we showed that ATF4 directly activates an element in the CHAC1 promoter. We showed that variation in basal levels of heme oxygenase 1 (HMOX1) contribute to the response to Ox-PAPC, consistent with its position as a hub in our network. We also identified G-protein–coupled receptor 39 (GPR39) as a regulator of HMOX1 levels and showed that it modulates the promoter activity of HMOX1. We further showed that OKL38/OSGN1 (oxidative stress–induced growth inhibitor), the hub gene in the blue module, is a key regulator of both inflammatory and antiinflammatory molecules. Conclusions: Our systems genetics approach has provided a broad view of the pathways involved in the response of endothelial cells to Ox-PAPC and also identified novel regulatory mechanisms.

Genetic regulation of human adipose microRNA expression and its consequences for metabolic traits

The genetics of messenger RNA (mRNA) expression has been extensively studied in humans and other organisms, but little is known about genetic factors contributing to microRNA (miRNA) expression. We examined natural variation of miRNA expression in adipose tissue in a population of 200 men who have been carefully characterized for metabolic syndrome (MetSyn) phenotypes as part of the Metabolic Syndrome in Men (METSIM) study. We genotyped the subjects using high-density single-nucleotide polymorphism microarrays and quantified the mRNA abundance using genome-wide expression arrays and miRNA abundance using next-generation sequencing. We reliably quantified 356 miRNA species that were expressed in human adipose tissue, a limited number of which made up most of the expressed miRNAs. We mapped the miRNA abundance as an expression quantitative trait and determined cis regulation of expression for nine of the miRNAs and of the processing of one miRNA (miR-28). The degree of genetic variation of miRNA expression was substantially less than that of mRNAs. For the majority of the miRNAs, genetic regulation of expression was independent of the expression of mRNA from which the miRNA is transcribed. We also showed that for 108 miRNAs, mapped reads displayed widespread variation from the canonical sequence. We found a total of 24 miRNAs to be significantly associated with MetSyn traits. We suggest a regulatory role for miR-204-5p which was predicted to inhibit acetyl coenzyme A carboxylase β, a key fatty acid oxidation enzyme that has been shown to play a role in regulating body fat and insulin resistance in adipose tissue.

Transcriptomic Responses to Sodium Chloride-Induced Osmotic Stress: A Study of Industrial Fed-Batch CHO Cell Cultures

The rapidly expanding market for monoclonal antibody and Fc‐fusion‐protein therapeutics has increased interest in improving the productivity of mammalian cell lines, both to alleviate capacity limitations and control the cost of goods. In this study, we evaluated the responses of an industrial CHO cell line producing an Fc‐fusion‐protein to hyperosmotic stress, a well‐known productivity enhancer, and compared them with our previous studies of murine hybridomas (Shen and Sharfstein, Biotechnol Bioeng. 2006;93:132–145). In batch culture studies, cells showed substantially increased specific productivity in response to increased osmolarity as well as significant metabolic changes. However, the final titer showed no substantial increase due to the decrease in viable cell density. In fed batch cultures, hyperosmolarity slightly repressed the cellular growth rate, but no significant change in productivity or final titer was detected. To understand the transcriptional responses to increased osmolarity and relate changes in gene expression to increased productivity and repressed growth, proprietary CHO microarrays were used to monitor the transcription profile changes in response to osmotic stress. A set of osmotically regulated genes was generated and classified by extracting their annotations and functionalities from online databases. The gene list was compared with results previously obtained from similar studies of murine‐hybridoma cells. The overall transcriptomic responses of the two cell lines were rather different, although many functional groups were commonly perturbed between them. Building on this study, we anticipate that further analysis will establish connections between productivity and the expression of specific gene(s), thus allowing rational engineering of mammalian cells for higher recombinant‐protein productivity.

Cell culture and gene transcription effects of copper sulfate on Chinese hamster ovary cells

This study reports the effects of varying concentrations of copper sulfate on the metabolic and gene transcriptional profile of a recombinant Chinese hamster ovary (CHO) cell line producing an immunoglobulin G (IgG)‐fusion protein (B0). Addition of 50 μM copper sulfate significantly decreased lactate accumulation in the cultures while increasing viable cell density and protein titer. These changes could be seen from day 6 and became increasingly evident with culture duration. Reducing the copper sulfate concentration to 5 μM retained all the above beneficial effects, but with the added benefit of reduced levels of the aggregated form of the B0 protein. To profile the cellular changes due to copper sulfate addition at the transcriptional level, Affymetrix® CHO microarrays were used to identify differentially expressed genes related to reduced cellular stresses and facilitated cell cycling. Based on the microarray results, down‐regulation of the transferrin receptor and lactate dehydrogenase, and up‐regulation of a cytochrome P450 family‐2 polypeptide were then confirmed by Western blotting. These results showed that copper played a critical role in cell metabolism and productivity on recombinant CHO cells and highlighted the usefulness of microarray data for better understanding biological responses on medium modification.

Genetic regulation of mouse liver metabolite levels

We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites exhibit a wide range of variation, as has been previously observed with metabolites in blood serum. Using genome‐wide association analysis, we mapped 40% of the quantified metabolites to at least one locus in the genome and for 75% of the loci mapped we identified at least one candidate gene by local expression QTL analysis of the transcripts. Moreover, we validated 2 of 3 of the significant loci examined by adenoviral overexpression of the genes in mice. In our GWAS results, we find that at significant loci the peak markers explained on average between 20 and 40% of variation in the metabolites. Moreover, 39% of loci found to be regulating liver metabolites in mice were also found in human GWAS results for serum metabolites, providing support for similarity in genetic regulation of metabolites between mice and human. We also integrated the metabolomic data with transcriptomic and clinical phenotypic data to evaluate the extent of co‐variation across various biological scales.

Exome Sequencing Reveals Comprehensive Genomic Alterations across Eight Cancer Cell Lines

It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the “exome”) can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome-sequencing technology (Roche Nimblegen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ∼95% concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read-depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anti-cancer therapies.

Gene Expression Analyses of Mouse Aortic Endothelium in Response to Atherogenic Stimuli

Objective—Endothelial cells are central to the initiation of atherosclerosis, yet there has been limited success in studying their gene expression in the mouse aorta. To address this, we developed a method for determining the global transcriptional changes that occur in the mouse endothelium in response to atherogenic conditions and applied it to investigate inflammatory stimuli. Approach and Results—We characterized a method for the isolation of endothelial cell RNA with high purity directly from mouse aortas and adapted this method to allow for the treatment of aortas ex vivo before RNA collection. Expression array analysis was performed on endothelial cell RNA isolated from control and hyperlipidemic prelesion mouse aortas, and 797 differentially expressed genes were identified. We also examined the effect of additional atherogenic conditions on endothelial gene expression, including ex vivo treatment with inflammatory stimuli, acute hyperlipidemia, and age. Of the 14 most highly differentially expressed genes in endothelium from prelesion aortas, 8 were also perturbed significantly by ≥1 atherogenic conditions: 2610019E17Rik, Abca1, H2-Ab1, H2-D1, Pf4, Ppbp, Pvrl2, and Tnnt2. Conclusions—We demonstrated that RNA can be isolated from mouse aortic endothelial cells after in vivo and ex vivo treatments of the murine vessel wall. We applied these methods to identify a group of genes, many of which have not been described previously as having a direct role in atherosclerosis, that were highly regulated by atherogenic stimuli and may play a role in early atherogenesis.

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data.

Semi-Automated Sample Preparation for Plasma Proteomics

The discovery of new biomarkers will be an essential step to enhance our ability to better diagnose and treat human disease. The proteomics research community has recently increased its use of human blood (plasma/serum) as a sample source for these discoveries. However, while blood is fairly non-invasive and readily available as a specimen, it is not easily analyzed by liquid chromatography (LC)/mass spectrometry (MS), because of its complexity. Therefore, sample preparation is a crucial step prior to the analysis of blood. This sample preparation must also be standardized in order to gain the most information from these valuable samples and to ensure reproducibility. We have designed a semi-automated and highly parallel procedure for the preparation of human plasma samples. Our process takes the samples through eight successive steps before analysis by LC/MS: (1) receipt, (2) reformatting, (3) filtration, (4) depletion, (5) concentration determination and normalization, (6) digestion, (7) extraction, and (8) randomization, triplication, and lyophilization. These steps utilize a number of different liquid handlers and liquid chromatography (LC) systems. This process enhances our ability to discover new biomarkers from human plasma.