Comparative Analysis of Global Hepatic Gene Expression in Adolescents and Adults with Non-alcoholic Fatty Liver Disease.

Introduction: To gain insights into the mechanisms underlying distinct nonalcoholic fatty liver disease (NAFLD) histological phenotypes between children and adults, we compared hepatic gene expression profiles associated with NAFLD phenotypes between the two age groups. Methods: Histological characteristics of intra-operative liver biopsies from adolescents and adults undergoing bariatric surgery were assessed by the same pathologist using the non-alcoholic steatohepatitis (NASH) Clinical Research Network scoring system. Hepatic gene expression was measured by microarray analysis. Transcriptomic signatures of histological phenotypes between the two groups were compared, with significance defined as p-value <0.05 and a fold change >1.5. Results: In 67 adolescents and 76 adults, distribution of histological phenotypes was: not-NAFLD (controls) 51% vs 39%, NAFL 39% vs 37%, and NASH 10% vs 24%, respectively. There were 279 differentially expressed genes in adolescents and 213 in adults with NAFLD vs controls. In adolescents, transcriptomes for NAFL vs controls, and borderline vs definite NASH were undifferentiable, whereas in adults, NAFL and borderline NASH demonstrated a transcriptomic gradient between controls and definite NASH. When applied to adolescents, significant adult genes discriminated borderline and definite NASH from control and NAFL, but the majority of significant pediatric genes were not portable to adults. Genes associated with NASH in adolescents and adults showed some ontological consistency but notable differences. Conclusions: There is some similarity but major differences in the transcriptomic profiles associated with NAFLD between adolescents and adults with severe obesity. These data suggest different mechanisms contribute to the pathogenesis of NAFLD severity at different stages in life.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures.

ABSTRACT: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

Multi-Site Observational Study to Assess Biomarkers for Susceptibility or Resilience to Chronic Pain: The Acute to Chronic Pain Signatures (A2CPS) Study Protocol.

Chronic pain has become a global health problem contributing to years lived with disability and reduced quality of life. Advances in the clinical management of chronic pain have been limited due to incomplete understanding of the multiple risk factors and molecular mechanisms that contribute to the development of chronic pain. The Acute to Chronic Pain Signatures (A2CPS) Program aims to characterize the predictive nature of biomarkers (brain imaging, high-throughput molecular screening techniques, or "omics," quantitative sensory testing, patient-reported outcome assessments and functional assessments) to identify individuals who will develop chronic pain following surgical intervention. The A2CPS is a multisite observational study investigating biomarkers and collective biosignatures (a combination of several individual biomarkers) that predict susceptibility or resilience to the development of chronic pain following knee arthroplasty and thoracic surgery. This manuscript provides an overview of data collection methods and procedures designed to standardize data collection across multiple clinical sites and institutions. Pain-related biomarkers are evaluated before surgery and up to 3 months after surgery for use as predictors of patient reported outcomes 6 months after surgery. The dataset from this prospective observational study will be available for researchers internal and external to the A2CPS Consortium to advance understanding of the transition from acute to chronic postsurgical pain.

Optimization of Imputation Strategies for High-Resolution Gas Chromatography-Mass Spectrometry (HR GC-MS) Metabolomics Data.

Gas chromatography-coupled mass spectrometry (GC-MS) has been used in biomedical research to analyze volatile, non-polar, and polar metabolites in a wide array of sample types. Despite advances in technology, missing values are still common in metabolomics datasets and must be properly handled. We evaluated the performance of ten commonly used missing value imputation methods with metabolites analyzed on an HR GC-MS instrument. By introducing missing values into the complete (i.e., data without any missing values) National Institute of Standards and Technology (NIST) plasma dataset, we demonstrate that random forest (RF), glmnet ridge regression (GRR), and Bayesian principal component analysis (BPCA) shared the lowest root mean squared error (RMSE) in technical replicate data. Further examination of these three methods in data from baboon plasma and liver samples demonstrated they all maintained high accuracy. Overall, our analysis suggests that any of the three imputation methods can be applied effectively to untargeted metabolomics datasets with high accuracy. However, it is important to note that imputation will alter the correlation structure of the dataset and bias downstream regression coefficients and p-values.

High Resolution GC-Orbitrap-MS Metabolomics Using Both Electron Ionization and Chemical Ionization for Analysis of Human Plasma.

Gas chromatography-mass spectrometry (GC-MS) platforms are typically run in electron ionization (EI) mode for mass spectral matching and metabolite annotation. With the advent of high resolution mass spectrometry (HRMS), soft ionization techniques such as chemical ionization (CI) may provide additional coverage for compound identification. We evaluated NIST SRM 1950 pooled plasma reference sample using a HRGC-MS instrument [GC-Orbitrap-MS with electron ionization (EI), positive chemical ionization (PCI), and negative CI (NCI) capabilities] for metabolite annotation and quantification to assess the suitability of the platform for routine discovery metabolomics. Using both open source and vendor workflows, we validated the spectral matches with an in-house spectral library (Wake Forest CPM GC-MS spectral and retention time libraries) of EI-MS and CI-MS/MS spectra obtained from chemical standards. We confidently [metabolomics standards initiative (MSI) confidence level 2] identified 263, 93, and 65 metabolites using EI, PCI, and NCI modes, respectively, of which 270 metabolites (64%) were validated using our Wake Forest CPM GC-MS spectral libraries. When compared to published LC-MS-based efforts using the same NIST SRM 1950 plasma sample, there was only 17% overlap between the two platforms. In addition, the metabolomics analysis of community approved standard human plasma demonstrated the ability of EI- and CI-MS modes of analysis using a HRGC-MS platform to enable reproducible and interoperable spectral matching.

The Need for Multi-Omics Biomarker Signatures in Precision Medicine.

Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses-which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas-have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.

Tumour-specific amplitude-modulated radiofrequency electromagnetic fields induce differentiation of hepatocellular carcinoma via targeting Cav3.2 T-type voltage-gated calcium channels and Ca2+ influx.

BACKGROUND: Administration of amplitude modulated 27·12 MHz radiofrequency electromagnetic fields (AM RF EMF) by means of a spoon-shaped applicator placed on the patient's tongue is a newly approved treatment for advanced hepatocellular carcinoma (HCC). The mechanism of action of tumour-specific AM RF EMF is largely unknown. METHODS: Whole body and organ-specific human dosimetry analyses were performed. Mice carrying human HCC xenografts were exposed to AM RF EMF using a small animal AM RF EMF exposure system replicating human dosimetry and exposure time. We performed histological analysis of tumours following exposure to AM RF EMF. Using an agnostic genomic approach, we characterized the mechanism of action of AM RF EMF. FINDINGS: Intrabuccal administration results in systemic delivery of athermal AM RF EMF from head to toe at levels lower than those generated by cell phones held close to the body. Tumour shrinkage results from differentiation of HCC cells into quiescent cells with spindle morphology. AM RF EMF targeted antiproliferative effects and cancer stem cell inhibiting effects are mediated by Ca2+ influx through Cav3·2 T-type voltage-gated calcium channels (CACNA1H) resulting in increased intracellular calcium concentration within HCC cells only. INTERPRETATION: Intrabuccally-administered AM RF EMF is a systemic therapy that selectively block the growth of HCC cells. AM RF EMF pronounced inhibitory effects on cancer stem cells may explain the exceptionally long responses observed in several patients with advanced HCC. FUND: Research reported in this publication was supported by the National Cancer Institute's Cancer Centre Support Grant award number P30CA012197 issued to the Wake Forest Baptist Comprehensive Cancer Centre (BP) and by funds from the Charles L. Spurr Professorship Fund (BP). DWG is supported by R01 AA016852 and P50 AA026117.

High-resolution gas chromatography/mass spectrometry metabolomics of non-human primate serum.

RATIONALE: Metabolomics analyses using gas chromatography/mass spectrometry (GC/MS)-based metabolomics are heavily impeded by the lack of high-resolution mass spectrometers and limited spectral libraries to complement the excellent chromatography that GC platforms offer, a challenge that is being addressed with the implementation of high-resolution (HR) platforms such as 1D-GC/Orbitrap-MS. METHODS: We used serum samples from a non-human primate (NHP), a baboon (Papio hamadryas), with suitable quality controls to quantify the chemical space using an advanced HRMS platform for confident metabolite identification and robust quantification to assess the suitability of the platform for routine clinical metabolomics research. In a complementary approach, we also analyzed the same serum samples using two-dimensional gas chromatography/time-of-flight mass spectrometry (2D-GC/TOF-MS) for metabolite identification and quantification following established standard protocols. RESULTS: Overall, the 2D-GC/TOF-MS (~5000 peaks per sample) and 1D-GC/Orbitrap-MS (~500 peaks per sample) analyses enabled identification and quantification of a total of 555 annotated metabolites from the NHP serum with a spectral similarity score Rsim  ≥ 900 and signal-to-noise (S/N) ratio of >25. A common set of 30 metabolites with HMDB and KEGG IDs was quantified in the serum samples by both platforms where 2D-GC/TOF-MS enabled quantification of a total 384 metabolites (118 HMDB IDs) and 1D-GC/Orbitrap-MS analysis quantification of a total 200 metabolites (47 HMDB IDs). Thus, roughly 30-70% of the peaks remain unidentified or un-annotated across both platforms. CONCLUSIONS: Our study provides insights into the benefits and limitations of the use of a higher mass resolution and mass accuracy instrument for untargeted GC/MS-based metabolomics with multi-dimensional chromatography in future studies addressing clinical conditions or exposome studies.

Association of TMTC2 With Human Nonsyndromic Sensorineural Hearing Loss.

IMPORTANCE: Sensorineural hearing loss (SNHL) is commonly caused by conditions that affect cochlear structures or the auditory nerve, and the genes identified as causing SNHL to date only explain a fraction of the overall genetic risk for this debilitating disorder. It is likely that other genes and mutations also cause SNHL. OBJECTIVE: To identify a candidate gene that causes bilateral, symmetric, progressive SNHL in a large multigeneration family of Northern European descent. DESIGN, SETTING, AND PARTICIPANTS: In this prospective genotype and phenotype study performed from January 1, 2006, through April 1, 2016, a 6-generation family of Northern European descent with 19 individuals having reported early-onset hearing loss suggestive of an autosomal dominant inheritance were studied at a tertiary academic medical center. In addition, 179 unrelated adult individuals with SNHL and 186 adult individuals reporting nondeafness were examined. MAIN OUTCOMES AND MEASURES: Sensorineural hearing loss. RESULTS: Nine family members (5 women [55.6%]) provided clinical audiometric and medical records that documented hearing loss. The hearing loss is characterized as bilateral, symmetric, progressive SNHL that reached severe to profound loss in childhood. Audiometric configurations demonstrated a characteristic dip at 1000 to 2000 Hz. All affected family members wear hearing aids or have undergone cochlear implantation. Exome sequencing and linkage and association analyses identified a fully penetrant sequence variant (rs35725509) on chromosome 12q21 (logarithm of odds, 3.3) in the TMTC2 gene region that segregates with SNHL in this family. This gene explains the SNHL occurrence in this family. The variant is also associated with SNHL in a cohort of 363 unrelated individuals (179 patients with confirmed SNHL and 184 controls, P = 7 × 10-4). CONCLUSIONS AND RELEVANCE: A previously uncharacterized gene, TMTC2, has been identified as a candidate for causing progressive SNHL in humans. This finding identifies a novel locus that causes autosomal dominant SNHL and therefore a more detailed understanding of the genetic basis of SNHL. Because TMTC2 has not been previously reported to regulate auditory function, the discovery reveals a potentially new, uncharacterized mechanism of hearing loss.

Genome-wide association of polycystic ovary syndrome implicates alterations in gonadotropin secretion in European ancestry populations.

Polycystic ovary syndrome (PCOS) is a common, highly heritable complex disorder of unknown aetiology characterized by hyperandrogenism, chronic anovulation and defects in glucose homeostasis. Increased luteinizing hormone relative to follicle-stimulating hormone secretion, insulin resistance and developmental exposure to androgens are hypothesized to play a causal role in PCOS. Here we map common genetic susceptibility loci in European ancestry women for the National Institutes of Health PCOS phenotype, which confers the highest risk for metabolic morbidities, as well as reproductive hormone levels. Three loci reach genome-wide significance in the case-control meta-analysis, two novel loci mapping to chr 8p23.1 [Corrected] and chr 11p14.1, and a chr 9q22.32 locus previously found in Chinese PCOS. The same chr 11p14.1 SNP, rs11031006, in the region of the follicle-stimulating hormone B polypeptide (FSHB) gene strongly associates with PCOS diagnosis and luteinizing hormone levels. These findings implicate neuroendocrine changes in disease pathogenesis.

A comprehensive analysis of adiponectin QTLs using SNP association, SNP cis-effects on peripheral blood gene expression and gene expression correlation identified novel metabolic syndrome (MetS) genes with potential role in carcinogenesis and systemic inflammation.

BACKGROUND: Metabolic syndrome (MetS) is an aberration associated with increased risk for cancer and inflammation. Adiponectin, an adipocyte-produced abundant protein hormone, has countering effect on the diabetogenic and atherogenic components of MetS. Plasma levels of adiponectin are negatively correlated with onset of cancer and cancer patient mortality. We previously performed microsatellite linkage analyses using adiponectin as a surrogate marker and revealed two QTLs on chr5 (5p14) and chr14 (14q13). METHODS: Using individuals from 85 extended families that contributed to the linkage and who were measured for 42 clinical and biologic MetS phenotypes, we tested QTL-based SNP associations, peripheral white blood cell (PWBC) gene expression, and the effects of cis-acting SNPs on gene expression to discover genomic elements that could affect the pathophysiology and complications of MetS. RESULTS: Adiponectin levels were found to be highly intercorrelated phenotypically with the majority of MetS traits. QTL-specific haplotype-tagging SNPs associated with MetS phenotypes were annotated to 14 genes whose function could influence MetS biology as well as oncogenesis or inflammation. These were mechanistically categorized into four groups: cell-cell adhesion and mobility, signal transduction, transcription and protein sorting. Four genes were highly prioritized: cadherin 18 (CDH18), myosin X (MYO10), anchor protein 6 of AMPK (AKAP6), and neuronal PAS domain protein 3 (NPAS3). PWBC expression was detectable only for the following genes with multi-organ or with multi-function properties: NPAS3, MARCH6, MYO10 and FBXL7. Strong evidence of cis-effects on the expression of MYO10 in PWBC was found with SNPs clustered near the gene's transcription start site. MYO10 expression in PWBC was marginally correlated with body composition (p = 0.065) and adipokine levels in the periphery (p = 0.064). Variants of genes AKAP6, NPAS3, MARCH6 and FBXL7 have been previously reported to be associated with insulin resistance, inflammatory markers or adiposity studies using genome-wide approaches whereas associations of CDH18 and MYO10 with MetS traits have not been reported before. CONCLUSIONS: Adiponectin QTLs-based SNP association and mRNA expression identified genes that could mediate the association between MetS and cancer or inflammation.

Genetic variation in the peroxisome proliferator activated receptor-gamma gene is associated with histologically advanced NAFLD.

BACKGROUND: The peroxisome proliferator activated receptor-gamma (PPARG) is a nuclear receptor that regulates adipocyte differentiation, insulin sensitivity and lipid metabolism, thus, it represents a good candidate gene for non-alcoholic fatty liver disease (NAFLD). PURPOSE AND METHOD: We investigated the association of two PPARG variants (Pro12Ala and C1431T) with NAFLD and its histological features. DNA was extracted from 274 archived, formalin-fixed liver biopsy specimens from 212 patients with NAFLD and 62 controls with normal liver histology. RESULTS: Individual SNPs did not show significant association with NAFLD or its histological features. A haplotype comprised of both minor alleles (GT) was less enriched whereas a haplotype comprised of the two major alleles (CC) was more enriched in subjects with NAFLD compared to controls [9.3% vs. 28.1% for GT (P = 0.001, OR 0.26 (range 0.14-0.48) and 80.4% vs. 64.8% for CC (P = 0.037, OR 2.23 (range 1.30-3.81)]. Both haplotypes were significantly associated with steatosis and fibrosis. The GT haplotype was also associated with lobular inflammation. CONCLUSIONS: Genetic variation in PPARG is associated with NAFLD, and the GT haplotype is associated with inflammatory and fibrotic changes that denote histologically advanced NAFLD.

Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS) analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1) promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO) subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.

Hepatic gene networks in morbidly obese patients with nonalcoholic fatty liver disease.

BACKGROUND: Genetic factors alter the risk for nonalcoholic fatty liver disease (NAFLD). We sought to identify NAFLD-associated genes and elucidate gene networks and pathways involved in the pathogenesis of NAFLD. METHODS: Quantitative global hepatic gene expression analysis was performed on 53 morbidly obese Caucasian subjects undergoing bariatric surgery (27 with NAFLD and 26 controls). After standardization of data, gene expression profiles were compared between patients with NAFLD and controls. The set of genes that significantly correlated with NAFLD was further analyzed by hierarchical clustering and ingenuity pathways analyses. RESULTS: There were 25,643 quantitative transcripts, of which 108 were significantly associated with NAFLD (p < 0.001). Canonical pathway analysis in the NAFLD-associated gene clusters showed that the hepatic fibrosis signaling was the most significant pathway in the up-regulated NAFLD gene cluster containing three (COL1A1, IL10, IGFBP3) significantly altered genes, whereas the endoplasmic reticulum stress and protein ubiquitination pathways were the most significant pathways in the down-regulated NAFLD gene cluster, with the first pathway containing one (HSPA5) and the second containing two (HSPA5, USP25) significantly altered genes. The four primary gene networks associated with NAFLD were involved in cell death, immunological disease, cellular movement, and lipid metabolism with several significantly altered "hub" genes in these networks. CONCLUSIONS: This study reveals the canonical pathways and gene networks associated with NAFLD in morbidly obese Caucasians. The application of gene network analysis highlights the transcriptional relationships among NAFLD-associated genes and allows identification of hub genes that may represent high-priority candidates for NAFLD.

Relative quantification of peptide phosphorylation in a complex mixture using 18O labeling.

We have developed a method to determine the degree of phosphorylation of a peptide in a complex mixture without enrichment or operation of the mass spectrometer in negative ion mode. Yeast lysate containing known amounts of synthetic peptides (VPQLEIVPNSAEERLHSMK and VPQLEIVPN[pS]AEERLHSMK) was labeled with (16)O and (18)O during hydrolysis. After treatment of one sample with a cocktail of phosphatases, the two samples were pooled. The intensity of the dephosphorylated peptide peaks was used to infer the degree of phosphorylation present before treatment. The linear dynamic range of this method is >10-fold before either of the peptide envelopes becomes indistinguishable from the surrounding noise. Since both the site of posttranslational modification and the proportion of the protein population that is modified are vital in protein function, the employment of this technique will provide a valuable tool for the analysis of the functional implications of protein phosphorylation.

Characterization of vascular endothelial growth factor receptors on the endothelial cell surface during hypoxia using whole cell binding arrays.

Angiogenesis plays a central role in a variety of important biological processes such as reproduction, tissue development, and wound healing, as well as being critical to tumor formation in cancer. The development of chromosomal substitution (consomic) rat strains has permitted the chromosomal localization of genetic factors critical to angiogenesis, but many questions remain as to the mechanisms involved. Here we utilize a novel cell capture assay to assess changes in the functional expression of vascular endothelial growth factor (VEGF) receptors on the surface of vascular endothelial cells isolated from rat strains that are normal or impaired in angiogenesis. We show that functional VEGF receptor expression is increased under hypoxic conditions in rat strains that exhibit normal angiogenesis but not in a strain impaired in angiogenesis. This result implicates the dysregulation of VEGF receptor expression levels on the endothelial cell surface as a key factor in impaired angiogenesis.

Obesity and its therapy: from genes to community action.

Like many diseases, the causes of obesity are complex, and their investigation requires novel approaches. Given the many contributors to our weight status, as well as the dynamic nature, genomic tools must be applied in an ecological model. Evaluating disparate factors can be difficult, such as feeding behavior, nutritional genomics, and gene-environment interaction. Many of these behaviors are being evaluated in animal models and hold great promise for targeted interventions in the future.

Simultaneous quantification and identification using 18O labeling with an ion trap mass spectrometer and the analysis software application "ZoomQuant".

Stable isotope labeling with (18)O is a promising technique for obtaining both qualitative and quantitative information from a single differential protein expression experiment. The small 4 Da mass shift produced by incorporation of two molecules of (18)O, and the lack of available methods for automated quantification of large data sets has limited the use of this approach with electrospray ionization-ion trap (ESI-IT) mass spectrometers. In this paper, we describe a method of acquiring ESI-IT mass spectrometric data that provides accurate calculation of relative ratios of peptides that have been differentially labeled using(18)O. The method utilizes zoom scans to provide high resolution data. This allows for accurate calculation of (18)O/(16)O ratios for peptides even when as much as 50% of a (18)O labeled peptide is present as the singly labeled species. The use of zoom scan data also provides sufficient resolution for calculating accurate ratios for peptides of +3 and lower charge states. Sequence coverage is comparable to that obtained with data acquisition modes that use only MS and MS/MS scans. We have employed a newly developed analysis software tool, ZoomQuant, which allows for the automated analysis of large data sets. We show that the combination of zoom scan data acquisition and analysis using ZoomQuant provides calculation of isotopic ratios accurate to approximately 21%. This compares well with data produced from (18)O labeling experiments using time of flight (TOF) and Fourier transform-ion cyclotron resonance (FT-ICR) MS instruments.

Parallel single nucleotide polymorphism genotyping by surface invasive cleavage with universal detection.

Large-scale investigations of sequence variation within the human species will provide information about the basis of heritable variation in disease susceptibility and human migration. The surface invader assay (an adaptation of the invasive cleavage reaction to an array format) is capable of exquisitely sensitive and specific detection of genetic variation. It is shown here that this genotyping technology can be multiplexed in a DNA array format, permitting the parallel analysis of a panel of single nucleotide polymorphisms (SNPs) directly from an unamplified genomic DNA target. In addition, a "universal" mode of detection was developed that makes use of a mixture of degenerate templates for DNA ligation to the surface-bound cleaved oligonucleotides and thereby makes this strategy amenable to any desired SNP site or combination of SNP sites, without regard to their particular DNA sequences. This approach was demonstrated on a proof-of-principle scale using small DNA arrays to genotype 6 SNP markers in the PTPN1 gene and 10 mutations in the cystic fibrosis transmembrane conductance regulator gene. This ability to analyze many different genetic variations in parallel, directly from unamplified human genomic DNA samples, lays the groundwork for the development of high-density arrays able to analyze hundreds of thousands or even millions of SNPs.

ZoomQuant: an application for the quantitation of stable isotope labeled peptides.

The main goal of comparative proteomics is the quantitation of the differences in abundance of many proteins between two different biological samples in a single experiment. By differentially labeling the peptides from the two samples and combining them in a single analysis, relative ratios of protein abundance can be accurately determined. Protease catalyzed (18)O exchange is a simple method to differentially label peptides, but the lack of robust software tools to analyze the data from mass spectra of (18)O labeled peptides generated by common ion trap mass spectrometers has been a limitation. ZoomQuant is a stand-alone computational tool that analyzes the mass spectra of (18)O labeled peptides from ion trap instruments and determines relative abundance ratios between two samples. Starting with a filtered list of candidate peptides that have been successfully identified by Sequest, ZoomQuant analyzes the isotopic forms of the peptides using high-resolution zoom scan spectrum data. The theoretical isotope distribution is determined from the peptide sequence and is used to deconvolute the peak areas associated with the unlabeled, partially labeled, and fully labeled species. The ratio between the labeled and unlabeled peptides is then calculated using several different methods. ZoomQuant's graphical user interface allows the user to view and adjust the parameters for peak calling and quantitation and select which peptides should contribute to the overall abundance ratio calculation. Finally, ZoomQuant generates a summary report of the relative abundance of the peptides identified in the two samples.