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Record W2169204079 · doi:10.1074/mcp.m110.006387

Interpretation of Data Underlying the Link Between Colony Collapse Disorder (CCD) and an Invertebrate Iridescent Virus

2011· article· en· W2169204079 on OpenAlexaff
Leonard J. Foster

Bibliographic record

VenueMolecular & Cellular Proteomics · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIridescenceIridovirusBiologyVirusVirologyEcology

Abstract

fetched live from OpenAlex

In a recent publication, Bromenshenk et al. claim that an iridovirus, Invertebrate Iridescent Virus-6 (IIV-6) 1The abbreviations used are:IIV-6invertebrate iridescent virus-6CCDcolony collapse disorderFDRfalse discovery rateLTQlinear trap quadrupole.1The abbreviations used are:IIV-6invertebrate iridescent virus-6CCDcolony collapse disorderFDRfalse discovery rateLTQlinear trap quadrupole., is tightly linked to colony collapse disorder (CCD, the cause of many of the bee losses over the past four winters) based on proteomic analyses of bees from CCD-afflicted and unafflicted colonies (1.Bromenshenk J.J. Henderson C.B. Wick C.H. Stanford M.F. Zulich A.W. Jabbour R.E. Deshpande S.V. McCubbin P.E. Seccomb R.A. Welch P.M. Williams T. Firth D.R. Skowronski E. Lehmann M.M. Bilimoria S.L. Gress J. Wanner K.W. Cramer Jr., R.A. Iridovirus and microsporidian linked to honey bee colony decline.PLoS One. 2010; 5: e13181Crossref PubMed Scopus (185) Google Scholar). We believe that there are fundamental flaws in the interpretation of their data based on the following rationale. First, liquid chromatography-tandem MS (LC-MS/MS) tends to identify the most abundant proteins much more frequently and the major capsid protein of IIV-6 constitutes at least 17% of total virion protein (2.Ince I.A. Boeren S.A. van Oers M.M. Vervoort J.J. Vlak J.M. Proteomic analysis of chilo iridescent virus.Virology. 2010; 405: 253-258Crossref PubMed Scopus (32) Google Scholar) yet of the 792 IIV-6 peptides reported by the authors, only four (0.5%) are from protein 274L, the major capsid protein. This is especially troubling because the authors rely on spectral counting to correlate IIV-6 levels with CCD. Second, in the list of identified peptides provided by the authors there is a high frequency of missed cleavage sites. Trypsin is a very reliable protease (3.Olsen J.V. Ong S.E. Mann M. Trypsin cleaves exclusively C-terminal to arginine and lysine residues.Mol Cell Proteomics. 2004; 3: 608-614Abstract Full Text Full Text PDF PubMed Scopus (869) Google Scholar) and, indeed, if we examine some of our own recent large-scale bee proteomic data sets (available at http://www.ebi.ac.uk/pride/), we find that nearly 80% of all peptides are perfect tryptic peptides, with ∼18% containing one missed cleavage and a few percent containing two (Fig. 1, black bars). The peptides from Bromenshenk et al. are skewed dramatically toward greater numbers of missed cleavages (Fig. 1, light grey bars), which could be explained in one of two possible ways: (1) that the tryptic digest was inefficient, or (2) that many of the peptide identities are incorrect (i.e. a high false discovery rate (FDR)). Because there is no independent “gold standard” MS/MS data from IIV-6 proteins to compare against it is difficult to definitively evaluate the efficacy of trypsin from these data. However, other aspects of the described Methods suggest that the second possibility, a high FDR, is the more likely explanation: the authors state that they did not consider bee protein sequences when interpreting their MS/MS spectra, only pathogen protein sequences. Others have shown that when identifying proteins using a search engine such as SEQUEST or Mascot it is important to consider all the protein sequences that might be present in the sample or risk a high FDR (4.Cargile B.J. Bundy J.L. Stephenson Jr., J.L. Potential for false positive identifications from large databases through tandem mass spectrometry.J Proteome Res. 2004; 3: 1082-1085Crossref PubMed Scopus (173) Google Scholar). If we take the above-mentioned, large-scale LC-MS/MS dataset acquired on an linear trap quadrupole (LTQ)-OrbitrapXL, that should have similar fragmentation characteristics to the LTQ data reported by the authors, and search all 692,336 MS/MS against a database comprised only of proteins from IIV-6 and all other known bee viruses (i.e. no Apis mellifera sequences), we can also “identify” 103 IIV-6 peptides. However, if we include A. mellifera protein sequences in this search, as well as the virus sequences, then only a single IIV-6 peptide is found at an FDR of 1% based on reversed database searching: the other 102 spectra that matched IIV-6 peptides in the absence of bee sequences match considerably better to bee peptides than to IIV-6 peptides. In other words, at least 102 of the 103 matches were false discoveries when bee proteins were not considered. Interestingly, if one then plots the distribution of missed trypsin cleavages in the false IIV-6 peptides that we have “discovered,” the distribution is almost identical to that of the peptides from Bromenshenk et al. (Fig. 1, dark grey bars). We believe that there is currently insufficient evidence to conclude that bees are a natural host for IIV-6, let alone that the virus is linked to CCD. invertebrate iridescent virus-6 colony collapse disorder false discovery rate linear trap quadrupole. invertebrate iridescent virus-6 colony collapse disorder false discovery rate linear trap quadrupole.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.109
GPT teacher head0.298
Teacher spread0.189 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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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Citations27
Published2011
Admission routes1
Has abstractyes

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