The DOI matches its Crossref record, with a small difference in title or year.
High-throughput proteotyping of bacterial isolates by double barrel chromatography-tandem mass spectrometry based on microplate paramagnetic beads and phylopeptidomics
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Proteotyping of organisms based on tandem mass spectrometry data has been successfully used to identify bacteria [6, 7], and more complex medical microbiota [8, 9] or environmental microbiota [10].”
From Metaproteomic analysis of King Ghezo tomb wall (Abomey, Benin) confirms 19th century voodoo sacrifices (2024) · cites this paper as [6]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 40
- Grenga, 2019, Pathogen proteotyping: a rapidly developing application of mass spectrometry to address clinical concerns, Clin. Mass Spectro., 14, 9, 10.1016/j.clinms.2019.04.004 · DOI
- Lavigne, 2013, Mass spectrometry: a revolution in clinical microbiology?, Clin. Chem. Lab. Med., 51, 257, 10.1515/cclm-2012-0291 · DOI
- Karger, 2016, Current developments to use linear MALDI-TOF spectra for the identification and typing of bacteria and the characterization of other cells/organisms related to infectious diseases, Proteomics Clin. Appl., 10, 982, 10.1002/prca.201600038 · DOI
- Durighello, 2014, Proteogenomic biomarkers for identification of Francisella species and subspecies by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry, Anal. Chem., 86, 9394, 10.1021/ac501840g · DOI
- Emele, 2019, Proteotyping as alternate typing method to differentiate campylobacter coli clades, Sci. Rep., 9, 4244, 10.1038/s41598-019-40842-w · DOI
- Carvalhaes, 2018, Rapid detection of ceftazidime/avibactam resistance by MALDI-TOF MS, J. Antimicrob. Chemother., 73, 2579, 10.1093/jac/dky196 · DOI
- Patel, 2019, A moldy application of MALDI: MALDI-ToF mass spectrometry for fungal identification, J. Fungi. (Basel), 5
- Karlsson, 2015, Proteotyping: proteomic characterization, classification and identification of microorganisms--a prospectus, Syst. Appl. Microbiol., 38, 246, 10.1016/j.syapm.2015.03.006 · DOI
- Boulund, 2017, Typing and characterization of bacteria using bottom-up tandem mass spectrometry proteomics, Mol. Cell. Proteomics, 16, 1052, 10.1074/mcp.M116.061721 · DOI
- Karlsson, 2018, Proteotyping bacteria: characterization, differentiation and identification of pneumococcus and other species within the mitis group of the genus Streptococcus by tandem mass spectrometry proteomics, PLoS One, 13, 10.1371/journal.pone.0208804 · DOI
- Mappa, 2018, Assessing the ratio of Bacillus spores and vegetative cells by shotgun proteomics, Environ. Sci. Pollut. Res. Int.
- Berendsen, 2020, Untargeted accurate identification of highly pathogenic bacteria directly from blood culture flasks, Int. J. Med. Microbiol., 310, 151376, 10.1016/j.ijmm.2019.151376 · DOI
- Abbondio, 2019, Fecal metaproteomic analysis reveals unique changes of the gut microbiome functions after consumption of sourdough carasau bread, Front. Microbiol., 10, 1733, 10.3389/fmicb.2019.01733 · DOI
- Pible, 2020, Estimating relative biomasses of organisms in microbiota using “phylopeptidomics”, Microbiome, 8, 30, 10.1186/s40168-020-00797-x · DOI
- Chen, 2019, Detection of antimicrobial resistance using proteomics and the comprehensive antibiotic resistance database: a case study, Proteomics Clin. Appl.
- Armengaud, 2016, Next-generation proteomics faces new challenges in environmental biotechnology, Curr. Opin. Biotechnol., 38, 174, 10.1016/j.copbio.2016.02.025 · DOI
- Hartmann, 2014, Taking the shortcut for high-throughput shotgun proteomic analysis of bacteria, Methods Mol. Biol., 1197, 275, 10.1007/978-1-4939-1261-2_16 · DOI
- Ludwig, 2018, Comparison of In-Solution, FASP, and S-Trap based digestion methods for bottom-up proteomic studies, J. Proteome Res., 17, 2480, 10.1021/acs.jproteome.8b00235 · DOI
- Wisniewski, 2019, Filter aided sample preparation - a tutorial, Anal. Chim. Acta, 1090, 23, 10.1016/j.aca.2019.08.032 · DOI
- Zougman, 2014, Suspension trapping (STrap) sample preparation method for bottom-up proteomics analysis, Proteomics, 14, 10.1002/pmic.201300553 · DOI
- Hughes, 2014, Ultrasensitive proteome analysis using paramagnetic bead technology, Mol. Syst. Biol., 10, 757, 10.15252/msb.20145625 · DOI
- Hughes, 2019, Single-pot, solid-phase-enhanced sample preparation for proteomics experiments, Nat. Protoc., 14, 68, 10.1038/s41596-018-0082-x · DOI
- Hayoun, 2019, Evaluation of sample preparation methods for fast proteotyping of microorganisms by tandem mass spectrometry, Front. Microbiol., 10, 1985, 10.3389/fmicb.2019.01985 · DOI
- Dayon, 2014, Comprehensive and scalable highly automated MS-based proteomic workflow for clinical biomarker discovery in human plasma, J. Proteome Res., 13, 3837, 10.1021/pr500635f · DOI
- Humphrey, 2018, High-throughput and high-sensitivity phosphoproteomics with the EasyPhos platform, Nat. Protoc., 13, 1897, 10.1038/s41596-018-0014-9 · DOI
- Potriquet, 2017, A modified FASP protocol for high-throughput preparation of protein samples for mass spectrometry, PLoS One, 12, 10.1371/journal.pone.0175967 · DOI
- Yu, 2017, Quick 96FASP for high throughput quantitative proteome analysis, J. Proteome, 166, 1, 10.1016/j.jprot.2017.06.019 · DOI
- HaileMariam, 2018, S-trap, an ultrafast sample-preparation approach for shotgun proteomics, J. Proteome Res., 17, 2917, 10.1021/acs.jproteome.8b00505 · DOI
- Dagley, 2019, Universal Solid-Phase Protein Preparation (USP(3)) for Bottom-up and Top-down Proteomics, J. Proteome Res., 18, 2915, 10.1021/acs.jproteome.9b00217 · DOI
- Gonzalez-Lozano, 2019, A fast and economical sample preparation protocol for interaction proteomics analysis, Proteomics, 19, 10.1002/pmic.201900027 · DOI
- Müller, 2020, Automated sample preparation with SP3 for low-input clinical proteomics, Mol. Syst. Biol., 16, 10.15252/msb.20199111 · DOI
- Klein, 2016, RNA-binding proteins are a major target of silica nanoparticles in cell extracts, Nanotoxicology, 10, 1555, 10.1080/17435390.2016.1244299 · DOI
- Trapp, 2018, Digging deeper into the pyriproxyfen-response of the amphipod gammarus fossarum with a next-generation ultra-high-field orbitrap analyser: new perspectives for environmental toxicoproteomics, Front. Environ. Sci., 6
- Hosp, 2015, A double-barrel liquid chromatography-tandem mass spectrometry (LC-MS/MS) system to quantify 96 interactomes per day, Mol. Cell. Proteomics, 14, 2030, 10.1074/mcp.O115.049460 · DOI
- Rodriguez-Sanchez, 2019, Review of the impact of MALDI-TOF MS in public health and hospital hygiene, 2018, Euro. Surveill., 24, 10.2807/1560-7917.ES.2019.24.4.1800193 · DOI
- Singhal, 2015, MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis, Front. Microbiol., 6, 791, 10.3389/fmicb.2015.00791 · DOI
- Varghese, 2017, Current challenges in the accurate identification of Streptococcus pneumoniae and its serogroups/serotypes in the vaccine era, J. Microbiol. Methods, 141, 48, 10.1016/j.mimet.2017.07.015 · DOI
- Dumolin, 2019, Introducing SPeDE: high-Throughput dereplication and accurate determination of microbial diversity from matrix-assisted laser desorption-ionization time of flight mass spectrometry data, mSystems, 4, 10.1128/mSystems.00437-19 · DOI
- Sauget, 2017, Can MALDI-TOF mass spectrometry reasonably type Bacteria?, Trends Microbiol., 25, 447, 10.1016/j.tim.2016.12.006 · DOI · Paper page
- Kleiner, 2017, Assessing species biomass contributions in microbial communities via metaproteomics, Nat. Commun., 8, 1558, 10.1038/s41467-017-01544-x · DOI · Paper page
Cited by
Sorted by citations
Charlier, P., Bourdin, V., N'Dah, D., Kielbasa, M., Pible, O., & Armengaud, J. (2024) · PROTEOMICS · doi:10.1002/pmic.202400048 · Cited by 8
Self-citation
Metadata
- Authors
- Hayoun, K., Gaillard, J.-C., Pible, O., Alpha-Bazin, B., & Armengaud, J.
- Venue
- Journal of Proteomics
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 226
- Pages
- 103887
- ISSN
- 1874-3919
- Cited by
- 23
- References
- 0
- Language
- en
- Licence
- Funders
- Universitat de les Illes Balears
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review