Evidence map›Paper›PMID 32395630›Full record

ArticleBiology methods & protocols2019

MALDI-TOF MS protein fingerprinting of mixed samples.

Michael A Reeve, Denise Bachmann

Abstract read
In one paragraph

Article in Biology methods & protocols, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Diagnostic performance of MALDI-TOF MS for non-tuberculous mycobacteria: A systematic review and meta-analysis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Michael A ReeveDepartment of Bioscience, CABI Bioscience, Bakeham Lane, Egham, Surrey TW20 9TY, UK.
Denise BachmannDepartment of Bioscience, CABI Bioscience, Bakeham Lane, Egham, Surrey TW20 9TY, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analytical techniques currently available for the characterization of mixtures of microorganisms are generally based on next-generation sequencing. Motivated to develop practical and less-expensive methods for characterizing such mixtures, we propose, as an alternative or complement, the use of matrix-assisted laser-desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS), which is capable of high-resolution discrimination between species and even between biotypes within species. Potential approaches employing this technique for such characterization are discussed along with impediments to their successful employment. As a consequence, our rationale has been to capitalize on the powerful algorithms currently available for spectral comparison. Following this rationale, the first priority is to ensure the generation of MALDI-TOF MS spectra from mixtures of microorganisms that contain manageable peak complexities and that can be handled by the existing spectral comparison algorithms, preferably with the option to archive and re-run sample preparations and to pipette replicates of these onto MALDI-TOF MS sample plates. The second priority is to ensure that database entry is comparably facile to sample preparation so that large databases of known microorganism mixture MALDI-TOF MS spectra could be readily prepared for comparison with the spectra of unknown mixtures. In this article, we address the above priorities and generate illustrative MALDI-TOF MS spectra to demonstrate the utility of this approach. In addition, we investigate methods aimed at chemically modulating the peak complexity of the obtained MALDI-TOF MS spectra.

Indexed as

matrix-assisted laser-desorption and ionization time-of-flight mass spectrometrymixtures of microorganismsrice-associated bacteriaspectral comparison algorithmsspectral complexity

Identifiers

PMID32395630
PMCPMC7200911

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.