Evidence map›Paper›PMID 27107714›Full record

ArticleBMC microbiology2016

Strain-level Staphylococcus differentiation by CeO2-metal oxide laser ionization mass spectrometry fatty acid profiling.

Nicholas R Saichek, Christopher R Cox, Seungki Kim, Peter B Harrington, Nicholas R Stambach, Kent J Voorhees

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.9field-weighted citation impact, top 17% of its field
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

10 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. "Omic" Approaches to Bacteria and Antibiotic Resistance Identification.International journal of molecular sciences · 2022
    Review
  6. Article
  7. Recent applications of mass spectrometry in bacterial lipidomics.Analytical and bioanalytical chemistry · 2020
    Review
  8. Review
  9. Article
  10. Molecular Docking and Screening Studies of New Natural Sortase A Inhibitors.International journal of molecular sciences · 2017
    Article
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

6 authors at 3 institutions in 2 countries.

Nicholas R SaichekDepartment of Chemistry, Colorado School of Mines, Golden, CO, 80401, USA.
Christopher R CoxDepartment of Chemistry, Colorado School of Mines, Golden, CO, 80401, USA.
Seungki KimKorea Institute of Science and Technology, Hwarangno 14-gil 5, Seongbuk-gu, Seoul, 136-791, Republic of Korea.
Peter B HarringtonCenter for Intelligent Chemical Instrumentation, Department of Chemistry, Clippinger Laboratories, Ohio University, Athens, OH, 45701, USA.
Nicholas R StambachDepartment of Chemistry, Colorado School of Mines, Golden, CO, 80401, USA.
Kent J VoorheesDepartment of Chemistry, Colorado School of Mines, Golden, CO, 80401, USA. kvoorhee@mines.edu.
Colorado School of Mines · USKorea Institute of Science and Technology · KROhio University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Staphylococcus genus is composed of 44 species, with S. aureus being the most pathogenic. Isolates of S. aureus are generally susceptible to β-lactam antibiotics, but extensive use of this class of drugs has led to increasing emergence of resistant strains. Increased occurrence of coagulase-negative staphylococci as well as S. aureus infections, some with resistance to multiple classes of antibiotics, has driven the necessity for innovative options for treatment and infection control. Despite these increasing needs, current methods still only possess species-level capabilities and require secondary testing to determine antibiotic resistance. This study describes the use of metal oxide laser ionization mass spectrometry fatty acid (FA) profiling as a rapid, simultaneous Staphylococcus identification and antibiotic resistance determination method.

resultsPrincipal component analysis was used to classify 50 Staphyloccocus isolates. Leave-one-spectrum-out cross-validation indicated 100 % correct assignment at the species and strain level. Fuzzy rule building expert system classification and self-optimizing partial least squares discriminant analysis, with more rigorous evaluations, also consistently achieved greater than 94 and 84 % accuracy, respectively. Preliminary analysis differentiating MRSA from MSSA demonstrated the feasibility of simultaneous determination of strain identification and antibiotic resistance.

conclusionThe utility of CeO2-MOLI MS FA profiling coupled with multivariate statistical analysis for performing strain-level differentiation of various Staphylococcus species proved to be a fast and reliable tool for identification. The simultaneous strain-level detection and antibiotic resistance determination achieved with this method should greatly improve outcomes and reduce clinical costs for therapeutic management and infection control.

Indexed as

CeriumFatty AcidsHumansMetabolomicsPhylogenyPrincipal Component AnalysisSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationStaphylococcal InfectionsStaphylococcusceric oxideCeriumFatty AcidsFatty acidsMALDI–MSMOLI MSMRSAStaphylococcus

Identifiers

PMID27107714
PMCPMC4842276
OpenAlexW2338520294

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.