1
|
Tata A, Zacometti C, Massaro A, Bragolusi M, Ceroni S, Falappa S, Prataviera D, Merenda M, Piro R, Catania S. Empowering veterinary clinical diagnosis in industrial poultry production by ambient mass spectrometry and chemiometrics: a new approach for precise poultry farming. Poult Sci 2024; 103:103709. [PMID: 38598914 PMCID: PMC11017065 DOI: 10.1016/j.psj.2024.103709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/22/2024] [Accepted: 03/28/2024] [Indexed: 04/12/2024] Open
Abstract
Untargeted metabolomic profiling, by ambient mass spectrometry and chemometric tools, has made a dramatic impact on human disease detection. In a similar vein, this study attempted the translation of this clinical human disease experience to farmed poultry for precise veterinary diagnosis. As a proof of principle, in this diagnostic/prognostic study, direct analysis in real-time high resolution mass spectrometry (DART-HRMS) was used in an untargeted manner to analyze fresh tissues (abdominal fat, leg skin, liver, and leg muscle) of pigmented and non-pigmented broilers to investigate the causes of lack of pigmentation in an industrial poultry farm. Afterwards, statistical analysis was applied to the DART-HRMS data to retrieve the molecular features that codified for 2 broiler groups, that is, properly pigmented and non-pigmented broilers. Higher abundance of oxidized lipids, high abundance of oxidized bile derivatives, and lower levels of tocopherol isomers (Vitamin E) and retinol (Vitamin A) were captured in nonpigmented than in pigmented broilers. In addition, conventional rapid analyses were used: 1) color parameters of the tissues of pigmented and non-pigmented broilers were measured to rationalize the color differences in abdominal fat, leg skin and leg muscle, and 2) macronutrients were determined in broiler leg muscle, to capture a detailed picture of the pathology and exclude other possible causes. In this study, the DART-HRMS system performed well in retrieving valuable chemical information from broilers that explained the differences between the 2 groups of broilers in absorption of xanthophylls and the subsequent lack of proper broiler pigmentation in affected broilers. The results suggest this technology could be useful in providing near real-time feedback to aid in veterinary decision-making in poultry farming.
Collapse
Affiliation(s)
- Alessandra Tata
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy.
| | - Carmela Zacometti
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Andrea Massaro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Marco Bragolusi
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Simona Ceroni
- Fileni Alimentare SPA, Località Cerrete Collicelli N° 8, Cingoli, Macerata 62011, Italy
| | - Sonia Falappa
- Fileni Alimentare SPA, Località Cerrete Collicelli N° 8, Cingoli, Macerata 62011, Italy
| | - Davide Prataviera
- Avian Medicine Laboratory, Istituto Zooprofilattico Sperimentale delle Venezie, Buttapietra, Verona 37060, Italy
| | - Marianna Merenda
- Avian Medicine Laboratory, Istituto Zooprofilattico Sperimentale delle Venezie, Buttapietra, Verona 37060, Italy
| | - Roberto Piro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Salvatore Catania
- Avian Medicine Laboratory, Istituto Zooprofilattico Sperimentale delle Venezie, Buttapietra, Verona 37060, Italy
| |
Collapse
|
2
|
Katz L, Kiyota T, Woolman M, Wu M, Pires L, Fiorante A, Ye LA, Leong W, Berman HK, Ghazarian D, Ginsberg HJ, Das S, Aman A, Zarrine-Afsar A. Metabolic Lipids in Melanoma Enable Rapid Determination of Actionable BRAF-V600E Mutation with Picosecond Infrared Laser Mass Spectrometry in 10 s. Anal Chem 2023; 95:14430-14439. [PMID: 37695851 DOI: 10.1021/acs.analchem.3c02901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
Abstract
Rapid molecular profiling of biological tissues with picosecond infrared laser mass spectrometry (PIRL-MS) has enabled the detection of clinically important histologic types and molecular subtypes of human cancers in as little as 10 s of data collection and analysis time. Utilizing an engineered cell line model of actionable BRAF-V600E mutation, we observed statistically significant differences in 10 s PIRL-MS molecular profiles between BRAF-V600E and BRAF-wt cells. Multivariate statistical analyses revealed a list of mass-to-charge (m/z) values most significantly responsible for the identification of BRAF-V600E mutation status in this engineered cell line that provided a highly controlled testbed for this observation. These metabolites predicted BRAF-V600E expression in human melanoma cell lines with greater than 98% accuracy. Through chromatography and tandem mass spectrometry analysis of cell line extracts, a 30-member "metabolite array" was characterized for determination of BRAF-V600E expression levels in subcutaneous melanoma xenografts with an average sensitivity and specificity of 95.6% with 10 s PIRL-MS analysis. This proof-of-principle work warrants a future large-scale study to identify a metabolite array for 10 s determination of actionable BRAF-V600E mutation in human tissue to guide patient care.
Collapse
Affiliation(s)
- Lauren Katz
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Taira Kiyota
- Ontario Institute for Cancer Research (OICR), 661 University Avenue, Suite 510, Toronto, ON M5G 0A3, Canada
| | - Michael Woolman
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Megan Wu
- Peter Gilgan Centre for Research and Learning & Arthur and Sonia Labatt Brain Tumor Research Centre, Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 0A4, Canada
| | - Layla Pires
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Alexa Fiorante
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Lan Anna Ye
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Wey Leong
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON M5G 2C1, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, ON M5T 1P5, Canada
| | - Hal K Berman
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON M5G 2C1, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto and the Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
| | - Danny Ghazarian
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada
| | - Howard J Ginsberg
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, ON M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, 1 King's College Circle, Sixth Floor, Toronto, ON M5S 1A8, Canada
| | - Sunit Das
- Peter Gilgan Centre for Research and Learning & Arthur and Sonia Labatt Brain Tumor Research Centre, Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 0A4, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, ON M5T 1P5, Canada
| | - Ahmed Aman
- Ontario Institute for Cancer Research (OICR), 661 University Avenue, Suite 510, Toronto, ON M5G 0A3, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, ON M5S 3M2, Canada
| | - Arash Zarrine-Afsar
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, ON M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada
| |
Collapse
|
3
|
Tata A, Marzoli F, Cordovana M, Tiengo A, Zacometti C, Massaro A, Barco L, Belluco S, Piro R. A multi-center validation study on the discrimination of Legionella pneumophila sg.1, Legionella pneumophila sg. 2-15 and Legionella non- pneumophila isolates from water by FT-IR spectroscopy. Front Microbiol 2023; 14:1150942. [PMID: 37125166 PMCID: PMC10133462 DOI: 10.3389/fmicb.2023.1150942] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 03/20/2023] [Indexed: 05/02/2023] Open
Abstract
This study developed and validated a method, based on the coupling of Fourier-transform infrared spectroscopy (FT-IR) and machine learning, for the automated serotyping of Legionella pneumophila serogroup 1, Legionella pneumophila serogroups 2-15 as well as their successful discrimination from Legionella non-pneumophila. As Legionella presents significant intra- and inter-species heterogeneities, careful data validation strategies were applied to minimize late-stage performance variations of the method across a large microbial population. A total of 244 isolates were analyzed. In details, the method was validated with a multi-centric approach with isolates from Italian thermal and drinking water (n = 82) as well as with samples from German, Italian, French, and British collections (n = 162). Specifically, robustness of the method was verified over the time-span of 1 year with multiple operators and two different FT-IR instruments located in Italy and Germany. Moreover, different production procedures for the solid culture medium (in-house or commercial) and different culture conditions (with and without 2.5% CO2) were tested. The method achieved an overall accuracy of 100, 98.5, and 93.9% on the Italian test set of Legionella, an independent batch of Legionella from multiple European culture collections, and an extra set of rare Legionella non-pneumophila, respectively.
Collapse
Affiliation(s)
- Alessandra Tata
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
- *Correspondence: Alessandra Tata,
| | - Filippo Marzoli
- Department of Food Safety, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| | | | - Alessia Tiengo
- OIE Italian Reference Laboratory for Salmonella, Istituto Zooprofilattico Sperimentale delle Venezie, Padova, Italy
| | - Carmela Zacometti
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| | - Andrea Massaro
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| | - Lisa Barco
- OIE Italian Reference Laboratory for Salmonella, Istituto Zooprofilattico Sperimentale delle Venezie, Padova, Italy
| | - Simone Belluco
- Department of Food Safety, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| | - Roberto Piro
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| |
Collapse
|
4
|
Katz L, Woolman M, Kiyota T, Pires L, Zaidi M, Hofer SO, Leong W, Wouters BG, Ghazarian D, Chan AW, Ginsberg HJ, Aman A, Wilson BC, Berman HK, Zarrine-Afsar A. Picosecond Infrared Laser Mass Spectrometry Identifies a Metabolite Array for 10 s Diagnosis of Select Skin Cancer Types: A Proof-of-Concept Feasibility Study. Anal Chem 2022; 94:16821-16830. [DOI: 10.1021/acs.analchem.2c03918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Lauren Katz
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Michael Woolman
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Taira Kiyota
- Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, Ontario M5G 0A3, Canada
| | - Layla Pires
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
| | - Mark Zaidi
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Stefan O.P. Hofer
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Division of Plastic and Reconstructive Surgery, Department of Surgery and Surgical Oncology, University Health Network, University of Toronto. Toronto General Hospital, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - Wey Leong
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto Ontario M5G 2C1, Canada
| | - Brad G. Wouters
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
| | - Danny Ghazarian
- Department of Laboratory Medicine and Pathobiology, University of Toronto and University Health Network, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - An-Wen Chan
- Division of Dermatology, Department of Medicine, University of Toronto, Canada and Women’s College Research Institute, Women’s College Hospital, 76 Grenville St, Toronto, Ontario M5S 1B2, Canada
| | - Howard J. Ginsberg
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada
| | - Ahmed Aman
- Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, Ontario M5G 0A3, Canada
- Leslie Dan, Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, Ontario M5S 3M2, Canada
| | - Brian C. Wilson
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
| | - Hal K. Berman
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
- Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - Arash Zarrine-Afsar
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada
| |
Collapse
|
5
|
Liu Y, Su C, Zhang Y, Zhang D, Li Y, Gu J, Wang E, Sun D. High-throughput and trace analysis of diazepam in plasma using DART-MS/MS and its pharmacokinetic application. Anal Biochem 2021; 635:114435. [PMID: 34715069 DOI: 10.1016/j.ab.2021.114435] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 09/30/2021] [Accepted: 10/22/2021] [Indexed: 01/27/2023]
Abstract
A high-throughput quantitative analytical method based on Direct Analysis in Real Time tandem mass spectrometry (DART-MS/MS) has been developed and validated for the determination of diazepam in rat plasma, whereby analyzing of each sample needs merely 25 μL plasma, simple solid phase extraction sample preparation and 15 s acquisition time. The multiple reaction monitoring (MRM) transitions at m/z 285.2 → 193.1 and 316.0 → 270.0 were selected for the monitoring of diazepam and its internal standard clonazepam respectively. A good linearity within the range of 10-2000 ng/mL, an intra- and inter-day precisions within <7.78% as to an accuracy ranging from 1.04% to 7.92% have been achieved. The method has been successfully applied to the pharmacokinetic study of diazepam in rats' plasma after a single intragastric administration at a dose of 10 mg/kg. The results indicate that this method fulfills the requirements of the bioanalysis in sensitivity and accuracy. It shows considerable promise for application of DART-MS to the quantitative investigation of other drugs.
Collapse
Affiliation(s)
- Yingze Liu
- School of Pharmaceutical Sciences, Jilin University, Changchun, 130012, PR China; Beijing Institute of Drug Metabolism, Beijing, 102209, PR China
| | - Chong Su
- Zhuhai United Laboratories co.,LTD, PR China
| | - Yuyao Zhang
- Research Center for Drug Metabolism, School of Life Sciences, Jilin University, Changchun, 130012, PR China
| | - Di Zhang
- Research Center for Drug Metabolism, School of Life Sciences, Jilin University, Changchun, 130012, PR China
| | - Yaoshuang Li
- Research Center for Drug Metabolism, School of Life Sciences, Jilin University, Changchun, 130012, PR China
| | - Jingkai Gu
- Research Center for Drug Metabolism, School of Life Sciences, Jilin University, Changchun, 130012, PR China; Beijing Institute of Drug Metabolism, Beijing, 102209, PR China
| | - Ensi Wang
- School of Pharmaceutical Sciences, Jilin University, Changchun, 130012, PR China
| | - Dong Sun
- Research Center for Drug Metabolism, School of Life Sciences, Jilin University, Changchun, 130012, PR China; Beijing Institute of Drug Metabolism, Beijing, 102209, PR China.
| |
Collapse
|
6
|
Katz L, Tata A, Woolman M, Zarrine-Afsar A. Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns. Metabolites 2021; 11:metabo11100660. [PMID: 34677375 PMCID: PMC8537725 DOI: 10.3390/metabo11100660] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 09/18/2021] [Accepted: 09/22/2021] [Indexed: 02/06/2023] Open
Abstract
Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.
Collapse
Affiliation(s)
- Lauren Katz
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada; (L.K.); (M.W.)
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, ON M5G 1P5, Canada
| | - Alessandra Tata
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico delle Venezie, Viale Fiume 78, 36100 Vicenza, Italy;
| | - Michael Woolman
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada; (L.K.); (M.W.)
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, ON M5G 1P5, Canada
| | - Arash Zarrine-Afsar
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada; (L.K.); (M.W.)
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, ON M5G 1P5, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, ON M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada
- Correspondence: ; Tel.: +1-416-581-8473
| |
Collapse
|
7
|
Tata A, Marzoli F, Massaro A, Passabì E, Bragolusi M, Negro A, Cristaudo I, Piro R, Belluco S. Assessing direct analysis in real-time mass spectrometry for the identification and serotyping of Legionella pneumophila. J Appl Microbiol 2021; 132:1479-1488. [PMID: 34543502 DOI: 10.1111/jam.15301] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 09/01/2021] [Accepted: 09/05/2021] [Indexed: 12/11/2022]
Abstract
AIMS The efficacy of ambient mass spectrometry to identify and serotype Legionella pneumophila was assessed. To this aim, isolated waterborne colonies were submitted to a rapid extraction method and analysed by direct analysis in real-time mass spectrometry (DART-HRMS). METHODS AND RESULTS The DART-HRMS profiles, coupled with partial least squares discriminant analysis (PLS-DA), were first evaluated for their ability to differentiate Legionella spp. from other bacteria. The resultant classification model achieved an accuracy of 98.1% on validation. Capitalising on these encouraging results, DART-HRMS profiling was explored as an alternative approach for the identification of L. pneumophila sg. 1, L. pneumophila sg. 2-15 and L. non-pneumophila; therefore, a different PLS-DA classifier was built. When tested on a validation set, this second classifier reached an overall accuracy of 95.93%. It identified the harmful L. pneumophila sg. 1 with an impressive specificity (100%) and slightly lower sensitivity (91.7%), and similar performances were reached in the classification of L. pneumophila sg. 2-15 and L. non-pneumophila. CONCLUSIONS The results of this study show the DART-HMRS method has good accuracy, and it is an effective method for Legionella serogroup profiling. SIGNIFICANCE AND IMPACT OF THE STUDY These preliminary findings could open a new avenue for the rapid identification and quick epidemiologic tracing of L. pneumophila, with a consequent improvement to risk assessment.
Collapse
Affiliation(s)
- Alessandra Tata
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Filippo Marzoli
- Department of Food Safety, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| | - Andrea Massaro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Eleonora Passabì
- Department of Food Safety, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| | - Marco Bragolusi
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Alessandro Negro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Ilaria Cristaudo
- Department of Food Safety, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| | - Roberto Piro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Simone Belluco
- Department of Food Safety, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| |
Collapse
|