Highlights
This study with MALDI-TOF comprises, as far as we know, the first report describing the performance of this technology with COVID-19 diagnosis.
This work would encourage researchers to explore the potential of MALDI-TOF MS to assess the feasibility of this technology, as a rapid and reproducible screening tool for diagnosis of SARS-CoV-2.
According to our preliminary results, mass spectrometry-based methods combined with multivariate analysis showed potential as a complementary diagnostic tool.
Coronavirus disease 2019 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid, sensitive and specific diagnosis of SARS-CoV-2 by fast and unambiguous testing is widely recognized to be critical in responding to the ongoing outbreak. Since the current testing capacity of RT-PCR-based methods is being challenged due to the extraordinary demand of supplies, such as RNA extraction kits and PCR reagents worldwide, alternative and/or complementary testing assays should be developed. Here, we exploit the potential of mass spectrometry technology combined with machine learning algorithms as an alternative fast tool for SARS-CoV-2 detection from nasopharyngeal swabs samples. According to our preliminary results, mass spectrometry-based methods combined with multivariate analysis showed an interesting potential as a complementary diagnostic tool and further steps should be focused on sample preparation protocols and the improvement of the technology applied.was not certified by peer review)
drug. However, pathogenic E.coli exhibited highest resistance to Trimethoprim/Sulphurmethoxazole) drug at (94%, 95% CI 70 to 99%). Conclusion: Prevalence of STEC was 5.4%, Stx 1 /Stx 2 /hlyA virulence genes combination was the most common and high resistance observed to commonly prescribed antibiotics and needed further research investigation.
Mass spectrometry has revolutionized the clinical microbiology field in America’s and Europe’s industrialized countries, for being a fast, reliable and inexpensive technique. Our study is based on the comparison of the performance of two commercial platforms, Microflex LT (Bruker Daltonics, Bremen, Germany) and Vitek MS (bioMérieux, Marcy l´Etoile, France) for the identification of unusual and hard-to-diagnose microorganisms in a Reference Laboratory in Argentina. During a four-month period (February–May 2018) the diagnostic efficiency and the concordance between both systems were assessed, and the results were compared with the polyphasic taxonomic identification of all isolates. The study
included 265 isolates: 77 Gram-Negative Bacilli, 33 Gram-Positive Cocci, 40 Anaerobes, 35 Actinomycetales, 19 Fastidious Microorganisms and 61 Gram-Positive Bacilli.
All procedures were practiced according to the manufacturer’s recommendations in each case by duplicate, and strictly in parallel. Other relevant factors, such as the utility of the recommended extraction protocols, reagent stability and connectivity were also evaluated. Both systems correctly identified the majority of the isolates to species and complex level
(82%, 217/265)
. Vitex MS achieved a higher number of correct species-level identifications between the gram-positive microorganisms; however, it presented greater difficulty in the identification of non-fermenting bacilli and a higher number of incorrect identifications when the profile of the microorganism was not represented in the commercial database. Both platforms showed an excellent performance on the identification of anaerobic bacteria and fastidious species. Both systems enabled the fast and reliable identification of most of the tested isolates and were shown to be very practical for the user.
Introduction. The different pathotypes of
Escherichia coli
can produce a large number of human diseases. Surveillance is complex since their differentiation is not easy. In particular, the detection of Shiga toxin-producing
Escherichia coli
(STEC) serotype O157 : H7 consists of stool culture of a diarrhoeal sample on enriched and/or selective media and identification of presumptive colonies and confirmation, which require a certain level of training and are time-consuming and expensive.
Hypothesis. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a quick and easy way to obtain the protein spectrum of a microorganism, identify the genus and species, and detect potential biomarker peaks of certain characteristics.
Aim. To verify the usefulness of MALDI-TOF MS to rapidly identify and differentiate STEC O157 : H7 from other
E. coli
pathotypes.
Methodology. The direct method was employed, and the information obtained using Microflex LT platform-based analysis from 60 clinical isolates (training set) was used to detect differences between the peptide fingerprints of STEC O157 : H7 and other
E. coli
strains. The protein profiles detected laid the foundations for the development and evaluation of machine learning predictive models in this study.
Results. The detection of potential biomarkers in combination with machine learning predictive models in a new set of 142 samples, called ‘test set‘, achieved 99.3 % (141/142) correct classification, allowing us to distinguish between the isolates of STEC O157 : H7 and the other
E. coli
group. Great similarity was also observed with respect to this last group and the
Shigella
species when applying the potential biomarkers algorithm, allowing differentiation from STEC O157 : H7
Conclusion. Given that STEC O157 : H7 is the main causal agent of haemolytic uremic syndrome, and based on the performance values obtained in the present study (sensitivity=98.5 % and specificity=100.0 %), the implementation of this technique provides a proof of principle for MALDI-TOF MS and machine learning to identify biomarkers to rapidly screen or confirm STEC O157 : H7 versus other diarrhoeagenic
E. coli
in the future.
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