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Record W2168447402 · doi:10.1016/s1535-9476(20)31954-x

What Has Proteomics Accomplished?

2007· article· en· W2168447402 on OpenAlexaffabout
John Bergeron, Ralph Bradshaw

Bibliographic record

VenueMolecular & Cellular Proteomics · 2007
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsProteomicsComputational biologyComputer scienceChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

The Barbados Principles, which emanated from the Barbados Conference in January 2007 and were reported in HUPO News (1Bergeron J.J.M. Beretta L. Barbados Conference 2007.Mol. Cell. Proteomics. 2007; 6: 1287-1288Abstract Full Text Full Text PDF Google Scholar), assigned to Ralph Bradshaw and John Bergeron the task of formulating a statement on “What has proteomics accomplished?” as a way of providing a progress report for the discipline and a guideline for future emphases. The amazing expansion in proteomics in the last five years is underscored by the number of international meetings, symposia, and workshops and on the growth in the scientific literature focused on this field. This is due in part to a major influx of physicists, chemists, and bioinformaticians who have helped catalyze the development and application of the principal supporting technologies utilized in proteomics research. At the same time, the biological community has made enormous strides in utilizing these tools to execute global analyses of protein expression with concomitant insight into the mechanisms of proteins of unknown function emanating from these analyses. Biologists are becoming comfortable with MS, which is the current backbone of the field, as well as other useful methods for protein separation and identification. Because a significant percentage of the genes in any genome are of unknown function, this remains a major challenge for proteomics, and it will, in turn, have a key role to play in filling these gaps in our knowledge. Budding yeast have been a surrogate model for the eukaryotic kingdom, and it is not surprising that the first comprehensive proteomics analyses have come from studies with yeast. The expression products of genes readily detected by a Western blot approach, as well as tagged versions of proteins made from corresponding open reading frames, have given a global analysis of protein expression (2Ghaemmaghami S. Huh W.K. Bower K. Howson R.W. Belle A. Dephoure N. O'Shea E.K. Weissman J.S. Global analysis of protein expression in yeast.Nature. 2003; 425: 737-741Crossref PubMed Scopus (2993) Google Scholar). MS initially lagged behind the Western blot approach but is now able to match and even exceed it utilizing new quantitation technologies, as reported by Matthias Mann at a recent meeting in San Francisco (3!!8th International Symposium on Mass Spectrometry in the Health and Life Sciences. San Francisco, California. August 19-23, 2007Google Scholar) and in an article (4Cox J. Mann M. Is Proteomics the New Genomics?.Cell. 2007; 130: 395-398Abstract Full Text Full Text PDF PubMed Scopus (342) Google Scholar). That this is accomplished in a single MS experiment, as opposed to the 6,000 separate experiments for the Western blot data, is an amazing testimonial to the tremendous progress in current mass spec-based technology and data analysis. Just as Magellan was the first to circumnavigate the globe with all the uncertainty of the resulting maps to document the voyage, navigation of the global protein-protein interaction networks in yeast has been one of the unassailable accomplishments of proteomics. As reported in these pages previously, from the HUPO congress highlights in Long Beach (5Yates J. Peipei P. Bergeron J.J.M. The HUPO World Congress at Long Beach.Mol. Cell. Proteomics. 2006; 6: 1110-1111Abstract Full Text Full Text PDF Scopus (1) Google Scholar), there is only a small proportion (about 25%) of overlap between the two major efforts to accomplish this monumental journey through the yeast interactome (6Gavin A.C. Aloy P. Grandi P. Krause R. Boesche M. Marzioch M. Rau C. Jensen L.J. Bastuck S. Dümpelfeld B. Edelmann A. Heurtier M.A. Hoffman V. Hoefert C. Klein K. Hudak M. Michon A.M. Schelder M. Schirle M. Remor M. Rudi T. Hooper S. Bauer A. Bouwmeester T. Casari G. Drewes G. Neubauer G. Rick J.M. Kuster B. Bork P. Russell R.B. Superti-Furga G. Proteome survey reveals modularity of the yeast cell machinery.Nature. 2006; 440: 631-636Crossref PubMed Scopus (2116) Google Scholar, 7Krogan N.J. Cagney G. Yu H. Zhong G. Guo X. Ignatchenko A. Li J. Pu S. Datta N. Tikuisis A.P. Punna T. Peregrín-Alvarez J.M. Shales M. Zhang X. Davey M. Robinson M.D. Paccanaro A. Bray J.E. Sheung A. Beattie B. Richards D.P. Canadien V. Lalev A. Mena F. Wong P. Starostine A. Canete M.M. Vlasblom J. Wu S. Orsi C. Collins S.R. Chandran S. Haw R. Rilstone J.J. Gandi K. Thompson N.J. Musso G. St Onge P. Ghanny S. Lam M.H. Butland G. Altaf-Ul A.M. Kanaya S. Shilatifard A. O'Shea E. Weissman J.S. Ingles C.J. Hughes T.R. Parkinson J. Gerstein M. Wodak S.J. Emili A. Greenblatt J.F. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae.Nature. 2006; 440: 637-643Crossref PubMed Scopus (2333) Google Scholar). However, considerable new insight into the biology emanating from these networks has been realized. This has especially been due to the superimposition of these interaction networks on global approaches to identify pathways by synthetic lethal screens. Here, the characterization of genes whose knock-out may be subtle or nonessential when coupled with the knock-out of another nonessential gene enables further insight into protein function (8Collins S.R. Miller K.M. Maas N.L. Roguev A. Fillingham J. Chu C.S. Schuldiner M. Gebbia M. Recht J. Shales M. Ding H. Xu H. Han J. Ingvarsdottir K. Cheng B. Andrews B. Boone C. Berger S.L. Hieter P. Zhang Z. Brown G.W. Ingles C.J. Emili A. Allis C.D. Toczyski D.P. Weissman J.S. Greenblatt J.F. Krogan N.J. Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map.Nature. 2007; 446: 806-810Crossref PubMed Scopus (718) Google Scholar). Striking biological discoveries are stemming from these approaches (e.g. Refs. 9Sanchatjate S. Schekman R. Chs5/6 Complex: A multiprotein complex that interacts with and conveys chitin synthase III from the trans-Golgi network to the cell surface.Mol. Biol. Cell. 2006; 17: 4157-4166Crossref PubMed Scopus (60) Google Scholar, 10Wang C.-W. Hamamoto S. Orci L. Schekman R. Exomer: a coat complex for transport of select membrane proteins from the trans-Golgi network to the plasma membrane in yeast.J. Cell Biol. 2006; 174: 973-983Crossref PubMed Scopus (95) Google Scholar, 11Schuldiner M. Collins S.R. Thompson N.J. Denic V. Bhamidipati A. Punna T. Ihmels J. Andrews B. Boone C. Greenblatt J.F. Weissman J.S. Krogan N.J. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile.Cell. 2005; 123: 507-519Abstract Full Text Full Text PDF PubMed Scopus (686) Google Scholar). As the value and credibility (12Collins S.R. Kemmeren P. Zhao X.C. Greenblatt J.F. Spencer F. Holstege F.C. Weissman J.S. Krogan N.J. Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae.Mol. Cell. Proteomics. 2007; 6: 439-450Abstract Full Text Full Text PDF PubMed Scopus (638) Google Scholar) of this resource grows, these “gold” mines of data bases will undoubtedly lead to further discoveries. This is a particularly notable achievement of proteomics because the magnitude of protein-protein interactions in cells was simply grossly underestimated, if appreciated at all. As opposed to these large scale efforts, the generation of individual protein complexes by specific and careful sample preparation has also led to biological insight wherein MS is again the preferred technology to characterize these individual protein complexes. Two such efforts may be indicated as a sample of such discoveries. Using ICAT technology, the lab of Aebersold reported a new subunit of the RNA polymerase II complex (13Ranish J.A. Hahn S. Lu Y. Yi E.C. Li X.J. Eng J. Aebersold R. Identification of TFB5, a new component of general transcription and DNA repair factor IIH.Nat. Genet. 2004; 36: 707-713Crossref PubMed Scopus (125) Google Scholar). The detection of this subunit was at the limit of the technology of the time. Its importance has grown since the demonstration also by Aebersold and collaborators that this new subunit (TFB5) was mutated in a subset of patients suffering from trichothiodystrophy (14Giglia-Mari G. Coin F. Ranish J.A. Hoogstraten D. Theil A. Wijgers N. Jaspers N.G. Raams A. Argentini M. van der Spek P.J. Botta E. Stefanini M. Egly J.M. Aebersold R. Hoeijmakers J.H. Vermeulen W. A new, tenth subunit of TFIIH is responsible for the DNA repair syndrome trichothiodystrophy group A.Nat. Genet. 2004; 36: 714-719Crossref PubMed Scopus (268) Google Scholar). A further noteworthy advance has been in the elucidation of proteins in association with mutant CFTR protein that leads to cystic fibrosis. Using a label-free quantitative approach, the Yates group with collaborators could elucidate a comprehensive characterization of all the molecular chaperones retaining CFTR in the endoplasmic reticulum (15Wang X. Venable J. LaPointe P. Hutt D.M. Koulov A.V. Coppinger J. Gurkan C. Kellner W. Matteson J. Plutner H. Riordan J.R. Kelly J.W. Yates III, J.R. Balch W.E. Hsp90 cochaperone Aha1 downregulation rescues misfolding of CFTR in cystic fibrosis.Cell. 2006; 127: 803-815Abstract Full Text Full Text PDF PubMed Scopus (504) Google Scholar). Since this leads to degradation of the CFTR protein, the patients suffer and die because of this over stringent quality control machinery in the endoplasmic reticulum. By using RNA interference technology the Yates collaborators, i.e. Balch and Kelly, could selectively remove each of the chaperones uncovered by MS methodology. The removal of one (Aha1) led to the astonishing observation that the mutant CFTR protein would now leave the endoplasmic reticulum and be successfully transported to the cell surface acting as a functional chloride channel and effectively “curing” the disease at the level of cells in culture. Of course, the deleterious effects of chaperone removal in the patient would outweigh the benefit of successfully transporting the mutant CFTR protein to the cell surface. Regardless, the principle of “curing” cystic fibrosis by rescuing the mislocalized protein represents a proof of principle for a strategy in which drugs may be used to elicit greater specificity in effecting mutant CFTR “rescue.” The enormous advances in sensitivity and quantitation at the MS level as demonstrated at a mini-symposium on Protein Quantitation and Dynamics in San Francisco (3!!8th International Symposium on Mass Spectrometry in the Health and Life Sciences. San Francisco, California. August 19-23, 2007Google Scholar), coupled with efforts to effect global protein-protein interaction pulldowns in mice at each stage of development from the embryo to the adult, will be a projected accomplishment in the near future. The application of antibody-based methods indicated in journal (16Mathias U. HUPO Views, Mapping the human proteome using antibodies.Mol. Cell. Proteomics. 2007; 6: 1455-1456Abstract Full Text Full Text PDF PubMed Google Scholar) as an alternative to gene tagging will also be a method to check on the expected aberrations in protein expression from high throughput tagging technologies. As high quality antibodies become available to the representative protein of each human gene then the application of this resource to the magnetic bead isolation method from the Chait laboratory may be a further expected outcome of proteomics (17Cristea I.M. Williams R. Chait B.T. Rout M.P. Fluorescent proteins as proteomic probes.Mol. Cell. Proteomics. 2005; 4: 1933-1941Abstract Full Text Full Text PDF PubMed Scopus (201) Google Scholar). Clinical proteomics is focused on disease-linked proteins and especially proteins that maybe used as marker molecules indicative of disease stages. For the latter, a number of community efforts organized by HUPO are exploring clinical proteomics in a variety of disease phenotypes in organs including liver, brain, and the cardiovascular systems (Human Liver Proteome Project, Human Brain Proteome Project, and Human Cardiovascular Initiative) through either proteomic profiling (Human Plasma Proteome Project) or post-translational modified proteins (including glycosylation, e.g. Human Disease Glycomics Proteomic Initiative). In particular, efforts to map comprehensively the proteins in plasma have undergone a dramatic increase in credibility. From the pioneering efforts of the HUPO Human Plasma Proteome Project (18States D.J. Omenn G.S. Blackwell T.W. Fermin D. Eng J. Speicher D.W. Hanash S.M. Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study.Nat. Biotechnol. 2006; 24: 333-338Crossref PubMed Scopus (286) Google Scholar), the accession of nearly two million identified spectra from over 17,000 peptides mapping to proteins of the human plasma proteome via the PeptideAtlas resource was reported by Eric Deutsch at the recent San Francisco meeting (3!!8th International Symposium on Mass Spectrometry in the Health and Life Sciences. San Francisco, California. August 19-23, 2007Google Scholar). The enormous resource and the quantitation of protein abundance in plasma by application of the Absolute Protein Expression Profiling method of quantitation (19Lu P. Vogel C. Wang R. Yao X. Marcotte E.M. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation.Nat. Biotechnol. 2007; 1: 117-124Crossref Scopus (911) Google Scholar) has now extended to 7 orders of magnitude the dynamic range of protein characterization in human plasma. Thus, proteomics has already provided important new information on basic cell function and organization and expanded our understanding of the nature (and complexity) of post-translational modified proteins and other manipulations. It has provided significant new foundations for translational applications and, to a very real degree, helped to define what the challenges will be for the next five years. In this regard, technological innovations in sensitivity and quantitation of peptides and proteins as well as their post-translational modification, characterized by MS, are expanding at a breathless pace. This will inevitably lead to an even larger influx of biologists and clinicians as the ready pickings from this new technology are realized. The complete mapping of functional annotations and disease links to each of the genes of the human genome has become a realistic target, if still several years off. Efforts are underway to position and map proteins deduced by proteomics to each location in the cell and to resolve function by the elucidation of complexes. A single global project perhaps organized by HUPO could very well coordinate this bold challenge especially because order and standardization in the reporting of proteomics experiments is well under way (20Taylor C.F. Paton N.W. Lilley K.S. Binz P.A. Julian R.K.J. Jones A.R. Zhu W. Apweiler R. Aebersold R. Deutsch E.W. Dunn M.J. Heck A.J. Leitner A. Macht M. Mann M. Martens L. Neubert T.A. Patterson S.D. Ping P. Seymour S.L. Souda P. Tsugita A. Vandekerckhove J. Vondriska T.M. Whitelegge J.P. Wilkins M.R. Xenarios I. Yates J.R. Hermjakob H. The minimum information about a proteomics experiment (MIAPE).Nat. Biotechnol. 2007; 8: 887-893Crossref Scopus (580) Google Scholar).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.259
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2007
Admission routes2
Has abstractyes

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