Skip to main content
SpringerLink
Log in

Omics Technology

  • Chapter
  • First Online:
Molecular Diagnostics: Promises and Possibilities

Abstract

Omics has become the new mantra in molecular research. “Omics” technologies include genomics, transcriptomics, proteomics and metabolomics. Genomics had revealed the static sequences of genes and proteins and focus has now been shifted to their dynamic functions and interactions. Transcriptomics, proteomics and metabolomics reveal the biological function of the gene product. The “-omic-” technologies are high-throughput technologies and they increase substantially the number of proteins/genes that can be detected simultaneously to relate complex mixtures to complex effects in the form of gene/protein expression profiles. The primary aim of omic technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. The powerful “omics” technologies have opened new avenues towards biomarker discovery, identification of signaling molecules associated with cell growth, cell death, cellular metabolism and early detection of cancer. Omics will not only have an impact on our understanding of biological processes, but the prospect of more accurately diagnosing and treating disease will soon become a reality.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Aardema, M.J., MacGregor, J.T., 2002, Toxicology and genetic toxicology in the new era of “toxicogenomics”: impact of “-omics” technologies. Mutat Res 499:13–25.

    CAS  PubMed  Google Scholar 

  • Abu-Issa, R., Kirby, M.L., 2004, Take heart in the age of “Omics”. Circ Res 95:335.

    Article  CAS  PubMed  Google Scholar 

  • Aebersold, R., Mann, M., 2003, Mass spectrometry-based proteomics. Nature 422:198–207.

    Article  CAS  PubMed  Google Scholar 

  • Arora, P.S., Yamagiwa, H., Srivastava, A., Bolander, M.E., Sarkar, G., 2005, Comparative evaluation of two two-dimensional gel electrophoresis image analysis software applications using synovial fluids from patients with joint disease. J Orthop Sci 10:160–166.

    Article  PubMed  Google Scholar 

  • Baggerly, K.A., Morris, J.S., Edmonson, S.R., Coombes, K.R., 2005, Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer. J Natl Cancer Inst 97:307–309.

    Article  CAS  PubMed  Google Scholar 

  • Bilello, J.A., 2005, The agony and ecstasy of “OMIC” technologies in drug development. Curr Mol 5:39–52.

    Article  CAS  Google Scholar 

  • Blagoev, B., Kratchmarova, I., Ong, S.E., Nielsen, M., Foster, L.J., Mann, M., 2003, A proteomics strategy to elucidate functional protein–protein interactions applied to EGF signaling. Nat Biotechnol 21:315–318.

    Article  CAS  PubMed  Google Scholar 

  • Brindle, J.T., Antti, H., Holmes, E., Tranter, G., Nicholson, J.K., Bethell, H.W.L., Clarke, S., Schofield, P.M., McKilligin, E., Mosedale, D.E., Grainger, D.J., 2002, Rapid and non-invasive diagnosis of the presence and severity of coronary heart disease using 1H NMR-based metabonomics. Nature Med 8:1439–1444.

    Article  CAS  PubMed  Google Scholar 

  • Coen, M., Ruepp, S.U., Lindon, J.C., Nicholson, J.K., Pognan, F., Lenz, E.M., Wilson, I.D., 2004, Integrated application of transcriptomics and metabonomics yields new insight into the toxicity due to paracetamol in the mouse. J Pharm Biomed Anal 35:93–105.

    Article  CAS  PubMed  Google Scholar 

  • Diamandis, E.P., 2004, Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. J Natl Cancer Inst 96:353–356.

    Article  PubMed  Google Scholar 

  • Ellis, D.I., Goodacre, R., 2006, Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy. Analyst 131:875–885.

    Article  CAS  PubMed  Google Scholar 

  • Fiehn, O., 2002, Metabolomics the link between genotypes and phenotypes. Plant Mol Biol 48:155–171.

    Article  CAS  PubMed  Google Scholar 

  • Fiers, W., Contreras, R., Duerinck, F., Haegeman, G., Iserentant, D., Merregaert, J., Min Jou, W., Molemans, F., Raeymaekers, A., Van den Berghe, A., Volckaert, G., Ysebaert, M., 1976, Complete nucleotide-sequence of bacteriophage MS2-RNA – primary and secondary structure of replicase gene. Nature 260:500–507.

    Article  CAS  PubMed  Google Scholar 

  • Fischer, H.P., 2005, Towards quantitative biology: integration of biological information to elucidate disease pathways and to guide drug discovery. Biotechnol Annu Rev 11:1–68.

    Article  CAS  PubMed  Google Scholar 

  • German, J.B., Hammock, B.D., Watkins, S.M., 2005, Metabolomics: building on a century of biochemistry to guide human health. Metabolomics 1:3–9.

    Article  CAS  PubMed  Google Scholar 

  • German, J.B., Roberts, M.A., Fay, L., Watkins, S.M., 2002, Metabolomics and individual metabolic assessment: the next great challenge for nutrition. J Nutr 132:2486–2487.

    CAS  PubMed  Google Scholar 

  • German, J.B., Roberts, M.A., Watkins, S.M., 2003, Genomics and metabolomics as markers for the interaction of diet and health: lessons from lipids. J Nutr 133:2078S–2083S.

    CAS  PubMed  Google Scholar 

  • Harrigan, G.G., Goodacre, R., 2003, Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function Analysis. Kluwer Academic Publishers, Boston, ISBN 1-4020-7370-4.

    Google Scholar 

  • Hye, A., Lynham, S., Thambisetty, M., Causevic, M., Campbell, J., Byers, H.L., Hooper, C., Rijsdijk, F., Tabrizi, S.J., Banner, S., Shaw, C.E., Foy, C., Poppe, M., Archer, N., Hamilton, G., Powell, J., Brown, R.G., Sham, P., Ward, M., Lovestone, S., 2006, Proteome-based plasma biomarkers for Alzheimer’s disease. Brain 129:3042–3050.

    Article  CAS  PubMed  Google Scholar 

  • Kaddurah-Daouk, R., 2006, Metabolic profiling of patients with schizophrenia. PLoS Med 3:363.

    Article  Google Scholar 

  • Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., Hirakawa, M., 2006, From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 34:D354–D357.

    Article  CAS  PubMed  Google Scholar 

  • Kaput, J., 2004, Diet-disease gene interactions. Nutrition 20:26–31.

    Article  CAS  PubMed  Google Scholar 

  • Katayama, S., Tomaru, Y., Kasukawa, T., Waki, K., Nakanishi, M., Nakamura, M., Nishida, H., Yap, C.C., Suzuki, M., Kawai, J., et al., 2005, “Antisense transcription in the mammalian transcriptome” by the RIKEN Genome Exploration Research Group and Genome Science Group (Genome Network Project Core Group) and the FANTOM Consortium. Science 309:1564–1566.

    Article  PubMed  Google Scholar 

  • Kristal, B.S., Shurubor, Y.I., 2005, Metabolomics: opening another window into aging. Sci Aging Knowl Environ, (26), pe 1.

    Google Scholar 

  • Kristiansen, T.Z., Bunkenborg, J., Gronborg, M., Molina, H., Thuluvath, P.J., Argani, P., Goggins, M.G., Maitra, A., Pandey, A., 2004, A proteomic analysis of human bile. Mol Cell Proteomics 3:715–728.

    Google Scholar 

  • Lein, E.S., Hawrylycz, M.J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A.F., Boguski, M.S., Brockway, K.S., Byrnes, E.J., et al., 2007, Genome-wide atlas of gene expression in the adult mouse brain. Nature 445:168–176.

    Article  CAS  PubMed  Google Scholar 

  • Lindon, J.C., Holmes, E., Nicholson, J.K., 2004, Metabonomics technologies and their applications in physiological monitoring, drug safety assessment and disease diagnosis. Biomarkers 9(1):1–31.

    Article  CAS  PubMed  Google Scholar 

  • Liotta, L.A., Lowenthal, M., Mehta, A., Conrads, T.P., Veenstra, T.D., Fishman, D.A., Petricoin, E.F., III, 2005, Importance of communication between producers and consumers of publicly available experimental data. J Natl Cancer Inst 97:315–319.

    Article  Google Scholar 

  • Loughlin, M.F., 2007, Using ‘omic’ technology to target Helicobacter pylori. Drug Discov 2:1041–1051.

    CAS  Google Scholar 

  • Macaulay, I.C., Carr, P., Gusnanto, A., Ouwehand, W.H., Fitzgerald, D., Watkins, N.A., 2005, Platelet genomics and proteomics in human health and disease. J Clin Invest 115:3370–3377.

    Article  CAS  PubMed  Google Scholar 

  • MacGregor, J.T., 2004, Biomarkers of cancer risk and therapeutic benefit: new technologies, new opportunities, and some challenges. Toxicol Pathol 1:99–105.

    Article  Google Scholar 

  • Min Jou, W., Haegeman, G., Ysebaert, M., Fiers, W., (1972) Nucleotide sequence of the gene coding for the bacteriophage MS2 coat protein. Nature 237:82–88.

    Article  CAS  PubMed  Google Scholar 

  • Mutch, D.M., Berger, A., Mansourian, R., Rytz, A., Roberts, M.A., 2002, The limit fold change model: a practical approach for selecting differentially expressed genes from microarray data. BMC Bioinformatics 3:17.

    Article  PubMed  Google Scholar 

  • Mutch, D.M., Wahli, W., Williamson, G., 2005, Nutrigenomics and nutrigenetics: the emerging faces of nutrition. FASEB J 19:1602–1616.

    Article  CAS  PubMed  Google Scholar 

  • Nishizuka, S., Charboneau, L., Young, L., Major, S., Reinhold, W.C., Waltham, M., Kouros-Mehr, H., Bussey, K.J., Lee, J.K., Espina, V., Munson, P.J., Petricoin, E., 3rd, Liotta, L.A., Weinstein, J.N., 2003, Proteomic profiling of the NCI-60 cancer cell lines using new high-density reverse-phase lysate microarrays. Proc Natl Acad Sci USA 100:14229–14234.

    Article  CAS  PubMed  Google Scholar 

  • Oliver, S.G., Winson, M.K., Kell, D.B., Baganz, F., 1998, Systematic functional analysis of the yeast genome. Trends Biotechnol 16:373–378.

    Article  CAS  PubMed  Google Scholar 

  • Ordovas, J.M., Mooser, V., 2004, Nutrigenomics and nutrigenetics. Curr Opin Lipidol 15:101–108.

    Article  CAS  PubMed  Google Scholar 

  • Pan, S., Zhang, H., Rush, J., Eng, J., Zhang, N., Patterson, D., Comb, M.J., Aebersold, R., 2005, High throughput proteome screening for biomarker detection. Mol Cell Proteom 4:182–190.

    Article  CAS  Google Scholar 

  • Pegram, M., Slamon, D., 2000, Biological rationale for HER2/neu (c-erbB2) as a target for monoclonal antibody therapy. Semin Oncol 27:13–19.

    CAS  PubMed  Google Scholar 

  • Perroud, B., Lee, J., Valkova, N., Dhirapong, A., Lin, P.Y., Fiehn, O., Kültz, D., Weiss, R.H., 2006, Pathway analysis of kidney cancer using proteomics and metabolic profiling. Mol Cancer 5:64–82.

    Google Scholar 

  • Petricoin, E.F., Ardekani, A.M., Hitt, B.A., Levine, P.J., Fusaro, V.A., Steinberg, S.M., Mills, G.B., Simone, C., Fishman, D.A., Kohn, E.C., Liotta, L.A., 2002, Use of proteomic patterns in serum to identify ovarian cancer. Lancet 359:572–577.

    Article  CAS  PubMed  Google Scholar 

  • Phizicky, E., Bastiaens, P.I., Zhu, H., Snyder, M., Fields, S., 2003, Protein analysis on a proteomic scale. Nature 422:208–215.

    Article  CAS  PubMed  Google Scholar 

  • Ransohoff, D.F., 2005, Lessons from controversy: ovarian cancer screening and serum proteomics. J Natl Cancer Inst 97:315–319.

    Article  CAS  PubMed  Google Scholar 

  • Rogers, M.A., Clarke, P., Noble, J., Munro, N.P., Paul, A., Selby, P.J., Banks, R.E., 2003, Proteomic profiling of urinary proteins in renal cancer by surface enhanced laser desorption ionization, and neural-network analysis: identification of key issues affecting clinical potential utility. Cancer Res 63:6971–6983.

    CAS  PubMed  Google Scholar 

  • Sanger, F., Air, G.M., Barrell, B.G., Brown, N.L., Coulson, A.R., Fiddes, C.A., Hutchison, C.A., Slocombe, P.M., Smith, M., 1977, Nucleotide sequence of bacteriophage phi X174 DNA. Nature 265:687–695.

    Article  CAS  PubMed  Google Scholar 

  • Schmidt, C., 2004, Metabolomics takes its place as latest up-and-coming “omic”science. J Natl Cancer Inst 96:732–734.

    Article  PubMed  Google Scholar 

  • Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S., Mesirov, J.P., 2005, Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102:15545–15550.

    Article  CAS  PubMed  Google Scholar 

  • Tirumalai, R.S., Chan, K.C., Prieto, D.A., Issaq, H.J., Conrads, T.P., Veenstra, T.D., 2003, Charaterization of the low molecular weight human serum proteome. Mol Cell Proteom 10:1096–1103.

    Article  Google Scholar 

  • Vasan, R.S., 2006, Biomarkers of cardiovascular disease: molecular basis and practical considerations. Circulation 113:2335–2362.

    Article  PubMed  Google Scholar 

  • Venkatesh, T.V., Harry, B., 2002, Harlow integromics: challenges in data integration. Genome Biol 3:reports 4027.1–reports 4027.3.

    Article  Google Scholar 

  • Wishart, D.S., Tzur, D., Knox, C., Eisner, R., Guo, A.C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., et al., 2007, HMDB: the human metabolome database. Nucleic Acids Res 35:521–526.

    Article  Google Scholar 

  • Wu, S.L., Kim, J., Hancock, W.S., Karger, B., 2005, Extended Range Proteomic Analysis (ERPA): a new and sensitive LC-MS platform for high sequence coverage of complex proteins with extensive post-translational modifications-comprehensive analysis of beta-casein and epidermal growth factor receptor (EGFR). J Proteome Res 4:1155–1170.

    Article  CAS  PubMed  Google Scholar 

  • Wulfkuhle, J.D., Liotta, L.A., Petricoin, E.F., 2003, Proteomic applications for the early detection of cancer. Nat Rev Cancer 3(4):267–275.

    Article  CAS  PubMed  Google Scholar 

  • Yanagisawa, K., Shyr, Y., Xu, B.J., Massion, P.P., Larsen, P.H., White, B.C., Roberts, J.R., Edgerton, M., Gonzalez, A., Nadaf, S., Moore, J.H., Caprioli, R.M., Carbone, D.P., 2003, Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet 362:433–439.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, Z., Bast, R.C., Jr., Yu, Y., Li, J., Sokoll, L.J., Rai, A.J., Rosenzweig, J.M., Cameron, B., Wang, Y.Y., Meng, XY., et al., 2004a, Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res 64:5882–5890.

    Article  CAS  PubMed  Google Scholar 

  • Zhu, W., Wang, X., Ma, Y., Rao, M., Glimm, J., Kovach, J.S., 2003, Detection of cancer-specific markers amid massive mass spectral data. Proc Nat Acad Sci USA 100:14666–14671.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. Biotechnology, Jaipur Engineering College & Research Centre, Jaipur, 302022, India

    Dr. Mousumi Debnath

  2. School of Studies in Biochemistry, Jiwaji University, Gwalior, 474011, India

    Dr. Godavarthi B.K.S. Prasad

  3. School of Studies in Biotechnology, Jiwaji University, Gwalior, 474011, India

    Dr. Prakash S. Bisen

Authors
  1. Dr. Mousumi Debnath
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dr. Godavarthi B.K.S. Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dr. Prakash S. Bisen
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Debnath, M., Prasad, G.B., Bisen, P.S. (2010). Omics Technology. In: Molecular Diagnostics: Promises and Possibilities. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3261-4_2

Download citation

Publish with us

Policies and ethics

Search

Navigation