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PubMed2002

A full-coverage, high-resolution human chromosome 22 genomic microarray for clinical and research applications.

We have constructed the first comprehensive microarray representing a human chromosome for analysis of DNA copy number variation. This chromosome 22 array covers 34.7 Mb, representing 1.1% of the genome, with an average resolution of 75 kb. To demonstrate the utility of the array, we have applied it to profile acral melanoma, dermatofibrosarcoma, DiGeorge syndrome and neurofibromatosis 2. We accurately diagnosed homozygous/heterozygous deletions, amplifications/gains, IGLV/IGLC locus instability, and breakpoints of an imbalanced translocation. We further identified the 14-3-3 eta isoform as a candidate tumor suppressor in glioblastoma. Two significant methodological advances in array construction were also developed and validated. These include a strictly sequence defined, repeat-free, and non-redundant strategy for array preparation. This approach allows an increase in array resolution and analysis of any locus; disregarding common repeats, genomic clone availability and sequence redundancy. In addition, we report that the application of phi29 DNA polymerase is advantageous in microarray preparation. A broad spectrum of issues in medical research and diagnostics can be approached using the array. This well annotated and gene-rich autosome contains numerous uncharacterized disease genes. It is therefore crucial to associate these genes to specific 22q-related conditions and this array will be instrumental towards this goal. Furthermore, comprehensive epigenetic profiling of 22q-located genes and high-resolution analysis of replication timing across the entire chromosome can be studied using our array.

Chromosome Mapping↗
PubMed2005

Transcriptome analysis of zebrafish embryogenesis using microarrays.

Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html).

Journal Article↗
PubMed2005

What it takes to get a herbicide's mode of action. Physionomics, a classical approach in a new complexion.

Discovering new herbicides with novel modes of action is a priority assignment in plant protection research. However, for active compounds identified in greenhouse screens, the crucial point is to tread the most efficient path in determining a herbicide's target site, regarding chance of success, time and research costs. Today, in the literature, molecular (functional genomics, transcriptomics), biochemical (proteomics) and analytical (metabolomics) approaches are particularly discussed. So far, less attention has been focused on the comprehensive physiological profiling of the complex plant system as a procedure which enables new herbicides, with an unknown target site for their mode of action, to be screened rapidly. Here, the concept of an array of 'functional' bioassays is presented which has ultimately been developed from the classical tool of mode of action diagnosis by symptoms. These bioassays are designed to differentiate between the distinct responses of the multiple organization units (plant, tissue, meristematic cell, organelle), developmental stages, types of metabolism (phototrophic, heterotrophic) and physiological processes in the plant organism. The response pattern to a herbicide can be viewed as the end result of changes induced in the molecular and biochemical process chain and should be diagnostic of its physiological mode of action. The results can be interpreted directly or a fingerprint database for all known modes of action to be screened for analogy. The term 'physionomics' is proposed for this comprehensive physiological profiling of the plant system, following the parallel terminology of the molecular and biochemical 'omics' technologies. Physionomics procedures provide a first clue to the mode of action of a new herbicide that can direct more time-consuming and costly molecular, biochemical, histochemical or analytical studies to identify a target site more efficiently.

Biological Assay↗
PubMed2025

Transcriptomic landscape of NK cell-related genes in hepatocellular carcinoma: associations with prognosis and therapeutic response.

Hepatocellular carcinoma (HCC) is a highly aggressive and heterogeneous malignancy, in which natural killer (NK) cells play a crucial role in tumor progression and immune surveillance. This study aimed to characterize the transcriptomic landscape of NK cell-associated genes (NAGs) and explore their associations with clinical outcomes and therapeutic responses in HCC. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we identified key NAGs through comprehensive statistical analyses. Patients were stratified into distinct risk groups based on NAG expression profiles. Low-risk patients demonstrated better survival, higher immune infiltration, and greater predicted sensitivity to immunotherapy, whereas high-risk patients were associated with reduced chemotherapy responsiveness. These findings contribute to a deeper understanding of the immunogenomic features of HCC and provide a basis for developing personalized therapeutic approaches centered on NK cell-related mechanisms.

Hepatocellular carcinoma↗
PubMed2026

Comprehensive Somatic Profiling of Gastroenteropancreatic Neuroendocrine Neoplasms.

BACKGROUND: The incidence of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) is rising, yet their biological heterogeneity and variable response to treatments remain poorly understood. Comprehensive genomic characterization may uncover somatic drivers and inform biomarker-driven therapeutic strategies. METHODS: We retrospectively analyzed clinically ordered next-generation sequencing (NGS) results from tumor samples of 111 patients with confirmed GEP-NENs treated at Johns Hopkins Hospital between 2020 and 2022. Pathogenic and likely pathogenic mutations were identified using OncoKB, CHASMplus, and COSMIC databases. Mutational patterns were correlated with clinical characteristics and overall survival using univariate and multivariate analyses. RESULTS: In this retrospective study of 111 patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs), somatic pathogenic or likely pathogenic mutations were identified in 79% of cases. The most frequent alterations involved TP53 (19%), MEN1 (17%), and chromatin remodeling genes such as DAXX (9%) and ATRX (6%). Notably, we also identified a subset of patients (9%) patients with mutations typically associated with hematologic malignancies. Distinct co-mutation and mutual exclusivity patterns were observed between pancreatic and non-pancreatic NENs. Poorly differentiated or high-grade tumors correlated with mutations in TP53, KRAS, and CDKN2A. Mutations in KRAS, DAXX/ATRX, and hematologic malignancy-associated genes were independently associated with worse overall survival. CONCLUSIONS: This study reveals distinct somatic mutation patterns in GEP-NENs associated with tumor differentiation, grade, primary site, and survival. The identification of hematologic malignancy-associated mutations in a subset of GEP-NENs suggests possible shared molecular phenotypes with poor prognostic implications. The presence of KRAS mutations supports exploring pan-RAS inhibitors as potential therapies in select patients. These findings highlight the clinical utility of genomic profiling in GEP-NENs.

Neuroendocrine neoplasms↗
PubMed2001

yMGV: a database for visualization and data mining of published genome-wide yeast expression data.

The yeast Microarray Global Viewer (yMGV) is an on-line database providing a synthetic view of the transcriptional expression profiles of Saccharomyces cerevisiae genes in most of the published expression datasets. yMGV displays a one-screen graphical representation of gene expression variations for each published genome-wide experiment, allowing quick retrieval of experimental conditions affecting expression of this gene. yMGV also provides tools to isolate groups of genes sharing similar transcription profiles in a defined subset of experiments. Additionally, yMGV furnishes a set of statistical tools for critical assessment of published data. We therefore believe that yMGV is an efficient tool that affords a quick and comprehensive overview of microarray data and generates new gene classifications. As of 20 March 2001 the yMGV database contains 6 000 000 measurements, representing genome-wide expression comparisons of 932 experiments from 39 microarray publications. The yMGV interface is available at http://transcriptome.ens.fr/ymgv/.

Computational Biology↗
PubMed2025

Comprehensive profiling of activity and specificity of RNA-guided transposons reveals opportunities to engineer improved variants.

Recently discovered CRISPR-associated transposons (CASTs) are natural RNA-guided DNA transposition systems capable of single-step genomic integration of large DNA cargo. Wild-type CASTs exhibit low integration activity in heterologous systems; therefore, engineering efforts are required to develop therapeutically relevant tools. Here we developed a high-throughput dual genetic screen capable of accurately quantifying the relative activity and specificity of a large pool of CAST variants. Under the conditions of our screen, we discovered that the wild-type V-K CAST system can consistently achieve between 88% and 95% on-site targeting specificity. We used site-saturation mutagenesis of the conserved core transposition machinery (TnsB, TnsC, and TniQ) to reveal novel mechanistic insights into the function of these transposon proteins. Furthermore, we found that different components have varying trade-offs between activity and specificity, a critical aspect overlooked in conventional screening pipelines. These findings provide clear engineering principles for further optimization of CASTs. Finally, we identified several mutations that, together, enhance CAST activity up to four-fold while minimally impacting targeting specificity. These methods are a powerful tool to characterize the sequence-function landscape across multiple functional parameters while also providing a robust platform for developing enhanced genome-editing tools.

DNA Transposable Elements↗
PubMed2026

Genome-Wide Characterization of the ZIP Transporter Family in Sea Island Cotton (Gossypium barbadense L.) and Expression Profiling Under Heavy Metal and Pathogen Stresses.

G. barbadense represents an indispensable germplasm resource for high-quality textile fiber and disease resistance; nevertheless, systematic information regarding its ZRT/IRT-like protein (ZIP) gene family remains limited. Here, a total of 46 GbZIP genes were identified across the G. barbadense genome. Comprehensive bioinformatic investigations revealed uneven chromosomal distribution and confirmed that segmental/whole-genome duplications, supplemented by localized tandem duplications, drove family expansion. Members clustered within the same phylogenetic clades shared conserved motif organization and gene architecture, while promoter regions harbored abundant cis-acting elements associated with phytohormone and stress signaling. Transcriptome profiling indicated distinct expression patterns across vegetative/reproductive tissues, fiber and ovule developmental stages, and diverse abiotic stress conditions (cold, hot, drought, and salt). Quantitative Real-Time PCR (qRT-PCR) further validated that several GbZIP candidates exhibited temporal expression variations upon exposure to cadmium toxicity, V. dahliae infection, and combined Cd-V. dahliae stress. Specifically, GbZIP13, GbZIP18, GbZIP27, and GbZIP36 displayed prominent broad-spectrum responses to all three stress conditions, whereas GbZIP16, GbZIP29, and GbZIP30 showed stress-specific regulatory divergence. Overall, this study aims to systematically analyze the evolutionary characteristics and expression patterns of the GbZIP family, and to specifically evaluate the response differences under Cd stress, V. dahliae stress, and combined stress, in order to identify potential key candidate genes.

Gossypium barbadense↗
PubMed2006

Genomic and functional profiling of duplicated chromosome 15 cell lines reveal regulatory alterations in UBE3A-associated ubiquitin-proteasome pathway processes.

Autism is a complex neurodevelopmental disorder having both genetic and epigenetic etiological elements. Isodicentric chromosome 15 (Idic15), characterized by duplications of the multi-disorder critical region of 15q11-q14, is a relatively common cytogenetic event. When the duplication involves maternally derived content, this abnormality is strongly correlated with autism disorder. However, the mechanistic links between Idic15 and autism are ill-defined. To gain insight into the potential role of these duplications, we performed a comprehensive, genomics-based characterization of an in vitro model system consisting of lymphoblast cell lines derived from individuals with both autism and Idic15. Array-based comparative genomic hybridization using commercial single nucleotide polymorphism arrays was conducted and found to be capable of sub-classifying Idic15 samples by virtue of the lengths of the duplicated chromosomal region. In further analysis, whole-genome expression profiling revealed that 112 transcripts were significantly dysregulated in samples harboring duplications. Paramount among changing genes was ubiquitin protein ligase E3A (UBE3A; 15q11-q13), which was found to be nearly 1.5-2.0-fold up-regulated in duplicated samples at both the RNA and protein levels. Other key findings from gene expression analysis included two down-regulated genes, APP and SUMO1, with well-characterized roles in the process of apoptosis. We further demonstrate in this lymphoblast model that the gene-dosage directed increases in UBE3A levels can lead to dysregulation of the process of ubiquitination in response to genotoxic insult. This study provides insight into the direct and indirect effects of copy number gains in chromosome 15 and provides a framework for the study of these effects in neuronal systems.

Cell Line, Transformed↗
PubMed2002

Comparative genomics and evolution of proteins involved in RNA metabolism.

RNA metabolism, broadly defined as the compendium of all processes that involve RNA, including transcription, processing and modification of transcripts, translation, RNA degradation and its regulation, is the central and most evolutionarily conserved part of cell physiology. A comprehensive, genome-wide census of all enzymatic and non-enzymatic protein domains involved in RNA metabolism was conducted by using sequence profile analysis and structural comparisons. Proteins related to RNA metabolism comprise from 3 to 11% of the complete protein repertoire in bacteria, archaea and eukaryotes, with the greatest fraction seen in parasitic bacteria with small genomes. Approximately one-half of protein domains involved in RNA metabolism are present in most, if not all, species from all three primary kingdoms and are traceable to the last universal common ancestor (LUCA). The principal features of LUCA's RNA metabolism system were reconstructed by parsimony-based evolutionary analysis of all relevant groups of orthologous proteins. This reconstruction shows that LUCA possessed not only the basal translation system, but also the principal forms of RNA modification, such as methylation, pseudouridylation and thiouridylation, as well as simple mechanisms for polyadenylation and RNA degradation. Some of these ancient domains form paralogous groups whose evolution can be traced back in time beyond LUCA, towards low-specificity proteins, which probably functioned as cofactors for ribozymes within the RNA world framework. The main lineage-specific innovations of RNA metabolism systems were identified. The most notable phase of innovation in RNA metabolism coincides with the advent of eukaryotes and was brought about by the merge of the archaeal and bacterial systems via mitochondrial endosymbiosis, but also involved emergence of several new, eukaryote-specific RNA-binding domains. Subsequent, vast expansions of these domains mark the origin of alternative splicing in animals and probably in plants. In addition to the reconstruction of the evolutionary history of RNA metabolism, this analysis produced numerous functional predictions, e.g. of previously undetected enzymes of RNA modification.

Animals↗
PubMed2026

Epigenetic alterations of AKT1 orchestrate a metabolic reprogramming in advanced lipedema: translational insights from an integrated multi-omics study.

BACKGROUND: lipedema is a chronic, progressive adipose disorder predominantly affecting women, characterized by painful, symmetrical subcutaneous fat accumulation, and typically resistant to lifestyle interventions. The pathophysiology of advanced-stage lipedema remains poorly defined, and no validated biomarkers or targeted therapies are currently available. METHODS: in this observational study, we applied a comprehensive multi-omics approach to dissect the molecular and metabolic alterations underlying late-stage lipedema. RESULTS: Genome-wide DNA methylation profiling identified over 5,000 differentially methylated CpG sites affecting genes involved in receptor tyrosine kinase signaling, phospho-metabolism, and immune pathways. Transcriptomic analysis revealed profound downregulation of mitochondrial functions, including oxidative phosphorylation, the TCA cycle, and fatty acid β-oxidation, alongside disruption of the sirtuin pathway and extracellular matrix remodeling. Integrative analysis pinpointed AKT1 as a central regulatory node: its promoter region was hypomethylated, correlating with increased gene expression and protein phosphorylation. Metabolomic profiling confirmed AKT1-linked metabolic dysregulation, including altered levels of L-arginine, NADP+, ATP, guanosine, glycerol, and glutamate, indicating impaired redox balance and energy metabolism. Trans-omic network analysis positioned AKT1 at the intersection of multiple dysregulated pathways, suggesting its key role in advanced-stage lipedema. CONCLUSIONS: the consistent enhancing of AKT pathway signaling across omic layers highlights its potential not only as a biomarker for disease stratification but also as a putative druggable target for therapeutic intervention. These findings offer new mechanistic insights into lipedema pathophysiology and provide a rationale for future personalized treatment strategies guided by AKT1-centric molecular profiling.

Proto-Oncogene Proteins c-akt↗
PubMed1997

From gene to screen with yeast.

With the complete sequence now available, the yeast genome project enters a post-sequencing phase that will concentrate on a comprehensive determination of gene function. Novel techniques have been developed to undertake genome-wide functional analysis at the levels of phenotype, transcript and protein. These include techniques for the efficient deletion of individual genes while tagging the deletants with specific oligonucleotide signatures, as well as strategies to quantify the physiological effects of such deletions by comparing growth rates and metabolite profiles under a range of conditions. Comprehensive approaches to the study of gene expression include hybridization array technology to identify and quantify transcripts, and the exploitation of mass spectometry to identify proteins resolved by two-dimensional gel electrophoresis. Yeast presents opportunities for the discovery of new human medicines both via the recognition of functional homologies between human and yeast genes and by the use of yeast to express human coding sequences specifying potential drug targets.

Fungal Proteins↗
PubMed2025

Epstein-Barr Virus-Associated Gastric Cancer: A Histopathologic Study With Comprehensive Molecular Profiling.

A subset of gastric cancers (GCs) is linked to Epstein-Barr virus (EBV) infection. This study aims to characterize the histopathological and molecular features of EBV-associated GCs (EBVaGCs), focusing on predictive biomarkers and genomic and transcriptomic analysis. A total of 35 primary EBVaGCs were considered. The presence of EBV was confirmed with in situ hybridization. Immunohistochemical analyses for HER2, PD-L1, claudin 18.2, and mismatch repair proteins were performed. Genomic and transcriptomic profiles were assessed using AmoyDx Master Panel, which can identify single-nucleotide variants, InDels, and copy number variations on 571 hot genes, as well as microsatellite status, tumor molecular burden, and homologous recombination deficiency at the DNA level; however, at the RNA level, it identifies rearrangements/fusions in 45 genes and also quantifies the expression of 2396 cancer-related transcripts. The following histotypes were identified: carcinoma with lymphoid stroma (CLS; 69%), tubular (20%), and mixed (11%). Most cases were associated with atrophic gastritis (71%), and only 11% with dysplasia. The vast majority (94%) of EBVaGCs expressed EBV-encoded RNA in all tumor cells. Mismatch repair deficiency and HER2 overexpression were each observed in 6% of cases, whereas all tumors had a PD-L1-combined positive score ≥10. Sixty-six percent of cases showed moderate/strong claudin 18.2 expression in ≥75% of cancer cells. The most frequently altered genes were PIK3CA (41%) and ARID1A (17%). Transcriptomic analysis revealed substantial differential gene expression between EBVaGCs and EBV-negative controls, with upregulation of genes involved in antigen presentation, natural killer cell-mediated cytotoxicity, and cytokine-cytokine receptor interaction in EBVaGCs. Within EBVaGC, CLS showed higher expression of immune-related transcripts and higher PD-L1 expression than other histotypes. This study establishes EBVaGC as a distinct molecular class, with a distinctive profile of genomic alterations and expression of predictive biomarkers, and also with a unique immune microenvironment with enhanced cytotoxic activity. The findings highlight EBV's role in early tumor development and EBVaG-CLS as a distinct subgroup within EBVaGC, characterized by unique morphologic features and a pronounced immune activation profile.

Humans↗
PubMed2001

Degenerate oligonucleotide primed-polymerase chain reaction-based array comparative genomic hybridization for extensive amplicon profiling of breast cancers : a new approach for the molecular analysis of paraffin-embedded cancer tissue.

We have developed a protocol for degenerate oligonucleotide-primed-polymerase chain reaction-based array comparative genomic hybridization (array CGH) that, when combined with a laser microdissection technique, allows the analysis of cancer cell populations isolated from routine, formalin-fixed, paraffin-embedded tissue samples. Comparison of copy number changes detected by degenerate oligonucleotide-primed-polymerase chain reaction-based array CGH to those detected by conventional array CGH or fluorescence in situ hybridization, demonstrated that amplifications can be reliably detected. Using a genomic microarray containing 57 oncogenes, we screened a total of 28 breast cancer samples and obtained a detailed amplicon profile that is the most comprehensive to date in human breast cancer. The array CGH method described here will allow the genetic analysis of paraffin-embedded human cancer materials for example in the context of clinical trials.

Breast Neoplasms↗
PubMed2005

Metabolome analysis: the potential of in vivo labeling with stable isotopes for metabolite profiling.

Metabolome analysis technologies are still in early development because, unlike genome, transcriptome and proteome analyses, metabolome analysis has to deal with a highly diverse range of biomolecules. Combinations of different analytical platforms are therefore required for comprehensive metabolomic studies. Each of these platforms covers only part of the metabolome. To establish multiparallel technologies, thorough standardization of each measured metabolite is required. Standardization is best achieved by addition of a specific stable isotope-labeled compound, a mass isotopomer, for each metabolite. This suggestion, at first glance, seems unrealistic because of cost and time constraints. A possible solution to this problem is discussed in this article. Saturation in vivo labeling with stable isotopes enables the biosynthesis of differentially mass-labeled metabolite mixtures, which can be exploited for highly standardized metabolite profiling by mass isotopomer ratios.

Biochemistry↗
PubMed2006

Quantitative proteomic and genomic profiling reveals metastasis-related protein expression patterns in gastric cancer cells.

Gastric cancer is a leading cause of death worldwide, and patients have an overall 5-year survival rate of less than 10%. Using quantitative proteomic techniques together with microarray chips, we have established comprehensive proteome and transcriptome profiles of the metastatic gastric cancer TMC-1 cells and the noninvasive gastric cancer SC-M1 cell. Our qualitative protein profiling strategy offers the first comprehensive analysis of the gastric cancer cell proteome, identifying 926 and 909 proteins from SC-M1 and TMC-1 cells, respectively. Cleavable isotope-coded affinity tagging analysis allows quantitation of a total of 559 proteins (with a protein false-positive rate of <0.005), and 240 proteins were differentially expressed (>1.3-fold) between the SC-M1 and TMC-1 cells. We identified numerous proteins not previously associated with gastric cancer. Notably, a large subset of differentially expressed proteins was associated with tumor metastasis, including proteins functioning in cell-cell and cell-extracellular matrix (cell-ECM) adhesion, cell motility, proliferation, and tumor immunity. Gene expression profiling by DNA microarray revealed differential expression (of >2-fold) of about 1000 genes. The weak correlation observed between protein and mRNA profiles highlights the important complementarities of DNA microarray and proteomics approaches. These comparative data enabled us to map the disease-perturbed cell-cell and cell-ECM adhesion and Rho GTPase-mediated cytoskeletal pathways. Further validation of a subset of genes suggests the potential use of vimentin and galectin 1 as markers for metastasis. We demonstrate that combining proteomic and genomic approaches not only provides a rapid, robust, and sensitive platform to elucidate the molecular mechanisms underlying gastric cancer metastasis but also may identify candidate diagnostic markers and therapeutic targets.

Biomarkers, Tumor↗
PubMed2004

Gene expression profiles of transcription factors and signaling molecules in the ascidian embryo: towards a comprehensive understanding of gene networks.

Achieving a real understanding of animal development obviously requires a comprehensive rather than partial identification of the genes working in each developmental process. Recent decoding of genome sequences will enable us to perform such studies. An ascidian, Ciona intestinalis, one of the animals whose genome has been sequenced, is a chordate sharing a basic body plan with vertebrates, although its genome contains less paralogs than are usually seen in vertebrates. In the present study, we discuss the genomewide approach to networks of developmental genes in Ciona embryos. We focus on transcription factor genes and some major groups of signal transduction genes. These genes are comprehensively listed and examined with regard to their embryonic expression by in situ hybridization (http://ghost.zool.kyoto-u.ac.jp/tfst.html). The results revealed that 74% of the transcription factor genes are expressed maternally and that 56% of the genes are zygotically expressed during embryogenesis. Of these, 34% of the transcription factor genes are expressed both maternally and zygotically. The number of zygotically expressed transcription factor genes increases gradually during embryogenesis. As an example, and taking advantage of this comprehensive description of gene expression profiles, we identified transcription factor genes and signal transduction genes that are expressed at the early gastrula stage and that work downstream of beta-catenin, FoxD and/or Fgf9/16/20. Because these three genes are essential for ascidian endomesoderm specification, transcription factor genes and signal transduction genes involved in each of the downstream processes can be deduced comprehensively using the present approach.

Animals↗
PubMed2001

Individual metabolism should guide agriculture toward foods for improved health and nutrition.

Genomics and bioinformatics have the vast potential to identify genes that cause disease by investigating whole-genome databases. Comparison of an individual's geno-type with a genomic database will allow the prescription of drugs to be tailored to an individual's genotype. This same bioinformatic approach, applied to the study of human metabolites, has the potential to identify and validate targets to improve personalized nutritional health and thus serve to define the added value for the next generation of foods and crops. Advances in high-throughput analytic chemistry and computing technologies make the creation of a vast database of metabolites possible for several subsets of metabolites, including lipids and organic acids. In creating integrative databases of metabolites for bioinformatic investigation, the current concept of measuring single biomarkers must be expanded to 3 dimensions to 1) include a highly comprehensive set of metabolite measurements (a profile) by multiparallel analyses, 2) measure the metabolic profile of individuals over time rather than simply in the fasted state, and 3) integrate these metabolic profiles with genomic, expression, and proteomic databases. Application of the knowledge of individual metabolism will revolutionize the ability of nutrition to deliver health benefits through food in the same way that knowledge of genomics will revolutionize individual treatment of dis-ease with pharmaceuticals.

Biomarkers↗