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Hintzen KFH, Blanchet L, Smolinska A, Boumans ML, Stobberingh EE, Dallinga JW, Lubbers T, van Schooten FJ, Boots AW. Volatile organic compounds in headspace characterize isolated bacterial strains independent of growth medium or antibiotic sensitivity. PLoS One 2024; 19:e0297086. [PMID: 38277384 PMCID: PMC10817157 DOI: 10.1371/journal.pone.0297086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 12/23/2023] [Indexed: 01/28/2024] Open
Abstract
INTRODUCTION Early and reliable determination of bacterial strain specificity and antibiotic resistance is critical to improve sepsis treatment. Previous research demonstrated the potential of headspace analysis of volatile organic compounds (VOCs) to differentiate between various microorganisms associated with pulmonary infections in vitro. This study evaluates whether VOC analysis can also discriminate antibiotic sensitive from resistant bacterial strains when cultured on varying growth media. METHODS Both antibiotic-sensitive and -resistant strains of Pseudomonas aeruginosa, Staphylococcus aureus and Klebsiella pneumonia were cultured on 4 different growth media, i.e. Brain Heart Infusion, Marine Broth, Müller-Hinton and Trypticase Soy Agar. After overnight incubation at 37°C, the headspace air of the cultures was collected on stainless steel desorption tubes and analyzed by gas chromatography time-of-flight mass spectrometry (GC-tof-MS). Statistical analysis was performed using regularized multivariate analysis of variance and cross validation. RESULTS The three bacterial species could be correctly recognized based on the differential presence of 14 VOCs (p<0.001). This discrimination was not influenced by the different growth media. Interestingly, a clear discrimination could be made between the antibiotic-resistant and -sensitive variant of Pseudomonas aeruginosa (p<0.001) based on their species-specific VOC signature. CONCLUSION This study demonstrates that isolated microorganisms, including antibiotic-sensitive and -resistant strains of Pseudomonas aeruginosa, could be identified based on their excreted VOCs independent of the applied growth media. These findings suggest that the discriminating volatiles are associated with the microorganisms themselves rather than with their growth medium. This study exemplifies the potential of VOC analysis as diagnostic tool in medical microbiology. However, validation of our results in appropriate in vivo models is critical to improve translation of breath analysis to clinical applications.
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Affiliation(s)
- Kim F. H. Hintzen
- Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands
- Department of Surgery, Maastricht University Medical Centre, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Lionel Blanchet
- Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Agnieszka Smolinska
- Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Marie-Louise Boumans
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
- Department of Medical Microbiology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Ellen E. Stobberingh
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
- Department of Medical Microbiology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jan W. Dallinga
- Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Tim Lubbers
- Department of Surgery, Maastricht University Medical Centre, Maastricht, The Netherlands
- GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Frederik-Jan van Schooten
- Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Agnes W. Boots
- Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
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van Vorstenbosch R, van Munster K, Pachen D, Mommers A, Stavropoulos G, van Schooten FJ, Ponsioen C, Smolinska A. The Detection of Primary Sclerosing Cholangitis Using Volatile Metabolites in Fecal Headspace and Exhaled Breath. Metabolites 2023; 14:23. [PMID: 38248826 PMCID: PMC10819709 DOI: 10.3390/metabo14010023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 12/20/2023] [Accepted: 12/26/2023] [Indexed: 01/23/2024] Open
Abstract
Up to 5% of inflammatory bowel disease patients may at some point develop primary sclerosing cholangitis (PSC). PSC is a rare liver disease that ultimately results in liver damage, cirrhosis and liver failure. It typically remains subclinical until irreversible damage has been inflicted. Hence, it is crucial to screen IBD patients for PSC, but its early detection is challenging, and the disease's etiology is not well understood. This current study aimed at the early detection of PSC in an IBD population using Volatile Organic Compounds in fecal headspace and exhaled breath. To this aim, fecal material and exhaled breath were collected from 73 patients (n = 16 PSC/IBD; n = 8 PSC; n = 49 IBD), and their volatile profile were analyzed using Gas Chromatography-Mass Spectrometry. Using the most discriminatory features, PSC detection resulted in areas under the ROC curve (AUCs) of 0.83 and 0.84 based on fecal headspace and exhaled breath, respectively. Upon data fusion, the predictive performance increased to AUC 0.92. The observed features in the fecal headspace relate to detrimental microbial dysbiosis and exogenous exposure. Future research should aim for the early detection of PSC in a prospective study design.
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Affiliation(s)
- Robert van Vorstenbosch
- Department of Toxicology, Nutrition and Toxicology Research Institute, Maastricht University, 6229 ER Maastricht, The Netherlands; (D.P.); (A.M.); (F.-J.v.S.)
| | - Kim van Munster
- Department of Gastroenterology and Hepathology, Amsterdam University Medical Center, 1105 AZ Amsterdam, The Netherlands; (K.v.M.); (C.P.)
| | - Danielle Pachen
- Department of Toxicology, Nutrition and Toxicology Research Institute, Maastricht University, 6229 ER Maastricht, The Netherlands; (D.P.); (A.M.); (F.-J.v.S.)
| | - Alex Mommers
- Department of Toxicology, Nutrition and Toxicology Research Institute, Maastricht University, 6229 ER Maastricht, The Netherlands; (D.P.); (A.M.); (F.-J.v.S.)
| | - Georgios Stavropoulos
- Department of Toxicology, Nutrition and Toxicology Research Institute, Maastricht University, 6229 ER Maastricht, The Netherlands; (D.P.); (A.M.); (F.-J.v.S.)
| | - Frederik-Jan van Schooten
- Department of Toxicology, Nutrition and Toxicology Research Institute, Maastricht University, 6229 ER Maastricht, The Netherlands; (D.P.); (A.M.); (F.-J.v.S.)
| | - Cyriel Ponsioen
- Department of Gastroenterology and Hepathology, Amsterdam University Medical Center, 1105 AZ Amsterdam, The Netherlands; (K.v.M.); (C.P.)
| | - Agnieszka Smolinska
- Department of Toxicology, Nutrition and Toxicology Research Institute, Maastricht University, 6229 ER Maastricht, The Netherlands; (D.P.); (A.M.); (F.-J.v.S.)
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Menżyk A, Martyna A, Damin A, Vincenti M, Zadora G. Breaking with trends in forensic dating: A likelihood ratio-based comparison approach. Forensic Sci Int 2023; 349:111763. [PMID: 37356322 DOI: 10.1016/j.forsciint.2023.111763] [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: 02/20/2023] [Revised: 06/04/2023] [Accepted: 06/08/2023] [Indexed: 06/27/2023]
Abstract
Further steps toward understanding the time-related information contained within bloodstains found at the crime scene are rightly considered a top priority in forensic science. Contrary to widely held assumptions, the reason for the delayed exploitation of bloodstains dating methods in practice is not the lack of suitable analytical techniques for monitoring degradation processes. The problem lies in the variability of the environmental and circumstantial conditions, playing a vital role in the degradation kinetics of blood deposits. The present article demonstrates the possibility of breaking with current approaches based on absolute age estimations to finally answer time-centered questions in real forensic scenarios. The proposed novel framework for situating forensic traces in time is based on the likelihood ratio assessment of the (dis)similarity between the evidence decomposition and sets of reference materials obtained through supervised aging. In such a strategy, every dating procedure is constructed on a case-by-case basis to fit examined blood traces, thereby limiting the adverse influence of external factors on the validity of age estimations and providing a way for future crime scene implementation.
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Affiliation(s)
- Alicja Menżyk
- Forensic Chemistry Research Group, Institute of Chemistry, University of Silesia in Katowice, Szkolna 9, 40-006 Katowice, Poland; Institute of Forensic Research in Krakow, Westerplatte 9, 31-003, Krakow, Poland.
| | - Agnieszka Martyna
- Forensic Chemistry Research Group, Institute of Chemistry, University of Silesia in Katowice, Szkolna 9, 40-006 Katowice, Poland
| | - Alessandro Damin
- Dipartimento di Chimica, Universita degli Studi di Torino, Via P. Giuria 7, 10125 Torino, Italy
| | - Marco Vincenti
- Dipartimento di Chimica, Universita degli Studi di Torino, Via P. Giuria 7, 10125 Torino, Italy; Centro Regionale Antidoping e di Tossicologia "A. Bertinaria", Regione Gonzole 10/1, Orbassano, 10043 Torino, Italy
| | - Grzegorz Zadora
- Forensic Chemistry Research Group, Institute of Chemistry, University of Silesia in Katowice, Szkolna 9, 40-006 Katowice, Poland; Institute of Forensic Research in Krakow, Westerplatte 9, 31-003, Krakow, Poland
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Parastar H, Tauler R. Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.201801134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Hadi Parastar
- Department of Chemistry Sharif University of Technology Tehran Iran
| | - Roma Tauler
- Department of Environmental Chemistry IDAEA-CSIC 08034 Barcelona Spain
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Exhaled Breath Analysis for Investigating the Use of Inhaled Corticosteroids and Corticosteroid Responsiveness in Wheezing Preschool Children. J Clin Med 2022; 11:jcm11175160. [PMID: 36079088 PMCID: PMC9456576 DOI: 10.3390/jcm11175160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/26/2022] [Accepted: 08/29/2022] [Indexed: 11/28/2022] Open
Abstract
Exhaled breath analysis has great potential in diagnosing various respiratory and non-respiratory diseases. In this study, we investigated the influence of inhaled corticosteroids (ICS) on exhaled volatile organic compounds (VOCs) of wheezing preschool children. Furthermore, we assessed whether exhaled VOCs could predict a clinical steroid response in wheezing preschool children. We performed a crossover 8-week ICS trial, in which 147 children were included. Complete data were available for 89 children, of which 46 children were defined as steroid-responsive. Exhaled VOCs were measured by GC-tof-MS. Statistical analysis by means of Random Forest was used to investigate the effect of ICS on exhaled VOCs. A set of 20 VOCs could best discriminate between measurements before and after ICS treatment, with a sensitivity of 73% and specificity of 67% (area under ROC curve = 0.72). Most discriminative VOCs were branched C11H24, butanal, octanal, acetic acid and methylated pentane. Other VOCs predominantly included alkanes. Regularised multivariate analysis of variance (rMANOVA) was used to determine treatment response, which showed a significant effect between responders and non-responders (p < 0.01). These results show that ICS significantly altered the exhaled breath profiles of wheezing preschool children, irrespective of clinical treatment response. Furthermore, exhaled VOCs were capable of determining corticosteroid responsiveness in wheezing preschool children.
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Bliziotis NG, Kluijtmans LAJ, Tinnevelt GH, Reel P, Reel S, Langton K, Robledo M, Pamporaki C, Pecori A, Van Kralingen J, Tetti M, Engelke UFH, Erlic Z, Engel J, Deutschbein T, Nölting S, Prejbisz A, Richter S, Adamski J, Januszewicz A, Ceccato F, Scaroni C, Dennedy MC, Williams TA, Lenzini L, Gimenez-Roqueplo AP, Davies E, Fassnacht M, Remde H, Eisenhofer G, Beuschlein F, Kroiss M, Jefferson E, Zennaro MC, Wevers RA, Jansen JJ, Deinum J, Timmers HJLM. Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension. Metabolites 2022; 12:metabo12080679. [PMID: 35893246 PMCID: PMC9394285 DOI: 10.3390/metabo12080679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 06/17/2022] [Accepted: 07/11/2022] [Indexed: 11/24/2022] Open
Abstract
Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing’s syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies.
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Affiliation(s)
- Nikolaos G. Bliziotis
- Department of Laboratory Medicine, Translational Metabolic Laboratory, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
- Correspondence: (N.G.B.); (L.A.J.K.); (R.A.W.); (H.J.L.M.T.)
| | - Leo A. J. Kluijtmans
- Department of Laboratory Medicine, Translational Metabolic Laboratory, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
- Correspondence: (N.G.B.); (L.A.J.K.); (R.A.W.); (H.J.L.M.T.)
| | - Gerjen H. Tinnevelt
- Department of Analytical Chemistry, Institute for Molecules and Materials, Radboud University, 6500 HB Nijmegen, The Netherlands; (G.H.T.); (J.J.J.)
| | - Parminder Reel
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee DD2 4BF, UK; (P.R.); (S.R.); (E.J.)
| | - Smarti Reel
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee DD2 4BF, UK; (P.R.); (S.R.); (E.J.)
| | - Katharina Langton
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany; (K.L.); (C.P.); (G.E.)
| | - Mercedes Robledo
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), 28029 Madrid, Spain;
| | - Christina Pamporaki
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany; (K.L.); (C.P.); (G.E.)
| | - Alessio Pecori
- Division of Internal Medicine and Hypertension Unit, Department of Medical Sciences, University of Torino, 10124 Torino, Italy; (A.P.); (M.T.); (T.A.W.)
| | - Josie Van Kralingen
- British Heart Foundation Glasgow Cardiovascular Research Centre (BHF GCRC), Institute of Cardiovascular & Medical Sciences (ICAMS), University of Glasgow, Glasgow G12 8TA, UK; (J.V.K.); (E.D.)
| | - Martina Tetti
- Division of Internal Medicine and Hypertension Unit, Department of Medical Sciences, University of Torino, 10124 Torino, Italy; (A.P.); (M.T.); (T.A.W.)
| | - Udo F. H. Engelke
- Department of Laboratory Medicine, Translational Metabolic Laboratory, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Zoran Erlic
- Department of Endocrinology, Diabetology and Clinical Nutrition, University Hospital Zurich (USZ), University of Zurich (UZH), 8006 Zurich, Switzerland; (Z.E.); (F.B.)
| | - Jasper Engel
- Biometris, Wageningen University & Research, 6708 PB Wageningen, The Netherlands;
| | - Timo Deutschbein
- Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, 97080 Würzburg, Germany; (T.D.); (M.F.); (H.R.); (M.K.)
- Medicover Oldenburg MVZ, 26122 Oldenburg, Germany
| | - Svenja Nölting
- Department of Medicine IV, University Hospital, LMU Munich, 80336 Munich, Germany;
| | - Aleksander Prejbisz
- Department of Hypertension, Institute of Cardiology, 04-628 Warsaw, Poland; (A.P.); (A.J.)
| | - Susan Richter
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, 01307 Dresden, Germany;
| | - Jerzy Adamski
- Research Unit Molecular Endocrinology and Metabolism, Genome Analysis Center, Helmholtz Center München, German Research Center for Environmental Health, 85764 Neuherberg, Germany;
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
- Institute of Experimental Genetics, Technical University München, 85350 Freising-Weihenstephan, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 119077 Singapore, Singapore
| | - Andrzej Januszewicz
- Department of Hypertension, Institute of Cardiology, 04-628 Warsaw, Poland; (A.P.); (A.J.)
| | - Filippo Ceccato
- Endocrinology Unit, Department of Medicine DIMED, University-Hospital of Padova, 35128 Padova, Italy; (F.C.); (C.S.)
| | - Carla Scaroni
- Endocrinology Unit, Department of Medicine DIMED, University-Hospital of Padova, 35128 Padova, Italy; (F.C.); (C.S.)
| | - Michael C. Dennedy
- The Discipline of Pharmacology and Therapeutics, School of Medicine, National University of Ireland, H91 CF50 Galway, Ireland;
| | - Tracy A. Williams
- Division of Internal Medicine and Hypertension Unit, Department of Medical Sciences, University of Torino, 10124 Torino, Italy; (A.P.); (M.T.); (T.A.W.)
| | - Livia Lenzini
- Department of Medicine-DIMED, Emergency and Hypertension Unit, University of Padova, University Hospital, 35126 Padova, Italy;
| | - Anne-Paule Gimenez-Roqueplo
- INSERM, PARCC, Université de Paris, 75015 Paris, France; (A.-P.G.-R.); (M.-C.Z.)
- Service de Genétique, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, 75015 Paris, France
| | - Eleanor Davies
- British Heart Foundation Glasgow Cardiovascular Research Centre (BHF GCRC), Institute of Cardiovascular & Medical Sciences (ICAMS), University of Glasgow, Glasgow G12 8TA, UK; (J.V.K.); (E.D.)
| | - Martin Fassnacht
- Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, 97080 Würzburg, Germany; (T.D.); (M.F.); (H.R.); (M.K.)
- Core Unit Clinical Mass Spectrometry, University Hospital Würzburg, 97080 Würzburg, Germany
- Comprehensive Cancer Center Mainfranken, Würzburg University, 97070 Würzburg, Germany
| | - Hanna Remde
- Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, 97080 Würzburg, Germany; (T.D.); (M.F.); (H.R.); (M.K.)
| | - Graeme Eisenhofer
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany; (K.L.); (C.P.); (G.E.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, 01307 Dresden, Germany;
| | - Felix Beuschlein
- Department of Endocrinology, Diabetology and Clinical Nutrition, University Hospital Zurich (USZ), University of Zurich (UZH), 8006 Zurich, Switzerland; (Z.E.); (F.B.)
- Department of Medicine IV, University Hospital, LMU Munich, 80336 Munich, Germany;
| | - Matthias Kroiss
- Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, 97080 Würzburg, Germany; (T.D.); (M.F.); (H.R.); (M.K.)
- Department of Medicine IV, University Hospital, LMU Munich, 80336 Munich, Germany;
- Core Unit Clinical Mass Spectrometry, University Hospital Würzburg, 97080 Würzburg, Germany
- Comprehensive Cancer Center Mainfranken, Würzburg University, 97070 Würzburg, Germany
| | - Emily Jefferson
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee DD2 4BF, UK; (P.R.); (S.R.); (E.J.)
- Institute of Health & Wellbeing, Glasgow University, Glasgow G12 8RZ, UK
| | - Maria-Christina Zennaro
- INSERM, PARCC, Université de Paris, 75015 Paris, France; (A.-P.G.-R.); (M.-C.Z.)
- Service de Genétique, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, 75015 Paris, France
| | - Ron A. Wevers
- Department of Laboratory Medicine, Translational Metabolic Laboratory, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
- Correspondence: (N.G.B.); (L.A.J.K.); (R.A.W.); (H.J.L.M.T.)
| | - Jeroen J. Jansen
- Department of Analytical Chemistry, Institute for Molecules and Materials, Radboud University, 6500 HB Nijmegen, The Netherlands; (G.H.T.); (J.J.J.)
| | - Jaap Deinum
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Henri J. L. M. Timmers
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
- Correspondence: (N.G.B.); (L.A.J.K.); (R.A.W.); (H.J.L.M.T.)
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Comparison of Multivariate ANOVA-Based Approaches for the Determination of Relevant Variables in Experimentally Designed Metabolomic Studies. Molecules 2022; 27:molecules27103304. [PMID: 35630781 PMCID: PMC9147242 DOI: 10.3390/molecules27103304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/08/2022] [Accepted: 05/19/2022] [Indexed: 02/01/2023] Open
Abstract
The use of chemometric methods based on the analysis of variances (ANOVA) allows evaluation of the statistical significance of the experimental factors used in a study. However, classical multivariate ANOVA (MANOVA) has a number of requirements that make it impractical for dealing with metabolomics data. For this reason, in recent years, different options have appeared that overcome these limitations. In this work, we evaluate the performance of three of these multivariate ANOVA-based methods (ANOVA simultaneous component analysis—ASCA, regularized MANOVA–rMANOVA, and Group-wise ANOVA-simultaneous component analysis—GASCA) in the framework of metabolomics studies. Our main goals are to compare these various ANOVA-based approaches and evaluate their performance on experimentally designed metabolomic studies to find the significant factors and identify the most relevant variables (potential markers) from the obtained results. Two experimental data sets were generated employing liquid chromatography coupled to mass spectrometry (LC-MS) with different complexity in the design to evaluate the performance of the statistical approaches. Results show that the three considered ANOVA-based methods have a similar performance in detecting statistically significant factors. However, relevant variables pointed by GASCA seem to be more reliable as there is a strong similarity with those variables detected by the widely used partial least squares discriminant analysis (PLS-DA) method.
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Holz O, van Vorstenbosch R, Günther F, Schuchardt S, Trinkmann F, van Schooten FJ, Smolinska A, Hohlfeld J. Changes of breath volatile organic compounds in healthy volunteers following segmental and inhalation endotoxin challenge. J Breath Res 2022; 16. [PMID: 35366648 DOI: 10.1088/1752-7163/ac6359] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/01/2022] [Indexed: 11/11/2022]
Abstract
Background It is still unclear how airway inflammation affects the breath volatile organic compounds (VOC) profile in exhaled air. We therefore analyzed breath following well-defined pulmonary endotoxin (lipopolysaccharide, LPS) challenges. Methods Breath was collected from 10 healthy non-smoking subjects at eight time points before and after segmental and whole lung LPS inhalation challenge. Four Tenax-TA® adsorption tubes were simultaneously loaded from an aluminum reservoir cylinder and independently analyzed by two research groups using gas chromatography - mass spectrometry. Airway inflammation was assessed in bronchoalveolar lavage (BAL) and in sputum after segmental and inhaled LPS challenge, respectively. Results Segmental LPS challenge significantly increased the median (interquartile range, IQR) percentage of neutrophils in BAL from 3.0 (4.2) % to 64.0 (7.3) %. The inhalation challenge increased sputum neutrophils from 33.9 (26.8) % to 78.3 (13.5) %. We observed increases in breath aldehydes at both time points after segmental and inhaled LPS challenge. These results were confirmed by an independent laboratory. The longitudinal breath analysis also revealed distinct VOC patterns related to environmental exposures, clinical procedures, and to metabolic changes after food intake. Conclusions Changes in breath aldehydes suggest a relationship to LPS induced inflammation compatible with lipid peroxidation processes within the lung. Findings from our longitudinal data highlight the need for future studies to better consider the potential impact of the multiple VOCs from detergents, hygiene or lifestyle products a subject is continuously exposed to. We suspect that this very individual "owncloud" exposure is contributing to an increased variability of breath aldehydes, which might limit a use as inflammatory markers in daily clinical practice.
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Affiliation(s)
- Olaf Holz
- Clinical Airway Research, Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Feodor-Lynen-Str. 15, Hannover, 30625, GERMANY
| | | | - Frank Günther
- Bio- and Environmental Analytics, Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Feodor-Lynen-Str. 15, Hannover, 30625, GERMANY
| | - Sven Schuchardt
- Bio- and Environmental Analytics, Fraunhofer-Institut fur Toxikologie und Experimentelle Medizin, Feodor-Lynen-Str. 15, Hannover, Niedersachsen, 30625, GERMANY
| | - Frederik Trinkmann
- Pneumology and Critical Care Medicine, Thoraxklinik at University Hospital Heidelberg, Röntgenstraße 1, Heidelberg, 69126, GERMANY
| | - Frederik Jan van Schooten
- Department of Toxicology, University of Maastricht, Universiteitssingel 50, THE NETHERLANDS, Maastricht, 6229 ER, NETHERLANDS
| | - Agnieszka Smolinska
- Toxicology Department, Maastricht University, Universiteitssingel 50, Maastricht, 6229 ER, NETHERLANDS
| | - Jens Hohlfeld
- ITEM, Fraunhofer Institute for Toxicology and Experimental Medicine, Nikolai-Fuchs-Str. 1, Hannover, 30625, GERMANY
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Plantier L, Smolinska A, Fijten R, Flamant M, Dallinga J, Mercadier JJ, Pachen D, d'Ortho MP, van Schooten FJ, Crestani B, Boots AW. The use of exhaled air analysis in discriminating interstitial lung diseases: a pilot study. Respir Res 2022; 23:12. [PMID: 35057817 PMCID: PMC8772159 DOI: 10.1186/s12931-021-01923-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 12/29/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Fibrotic Interstitial lung diseases (ILD) are a heterogeneous group of chronic lung diseases characterized by diverse degrees of lung inflammation and remodeling. They include idiopathic ILD such as idiopathic pulmonary fibrosis (IPF), and ILD secondary to chronic inflammatory diseases such as connective tissue disease (CTD). Precise differential diagnosis of ILD is critical since anti-inflammatory and immunosuppressive drugs, which are beneficial in inflammatory ILD, are detrimental in IPF. However, differential diagnosis of ILD is still difficult and often requires an invasive lung biopsy. The primary aim of this study is to identify volatile organic compounds (VOCs) patterns in exhaled air to non-invasively discriminate IPF and CTD-ILD. As secondary aim, the association between the IPF and CTD-ILD discriminating VOC patterns and functional impairment is investigated. METHODS Fifty-three IPF patients, 53 CTD-ILD patients and 51 controls donated exhaled air, which was analyzed for its VOC content using gas chromatograph- time of flight- mass spectrometry. RESULTS By applying multivariate analysis, a discriminative profile of 34 VOCs was observed to discriminate between IPF patients and healthy controls whereas 11 VOCs were able to distinguish between CTD-ILD patients and healthy controls. The separation between IPF and CTD-ILD could be made using 16 discriminating VOCs, that also displayed a significant correlation with total lung capacity and the 6 min' walk distance. CONCLUSIONS This study reports for the first time that specific VOC profiles can be found to differentiate IPF and CTD-ILD from both healthy controls and each other. Moreover, an ILD-specific VOC profile was strongly correlated with functional parameters. Future research applying larger cohorts of patients suffering from a larger variety of ILDs should confirm the potential use of breathomics to facilitate fast, non-invasive and proper differential diagnosis of specific ILDs in the future as first step towards personalized medicine for these complex diseases.
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Affiliation(s)
- L Plantier
- Department of Pulmonology and Lung Function Testing, CHRU, Tours, France
- Université de Tours, Tours, France
- Centre d'Etude des Pathologies Respiratoires, INSERM UMR1100, Tours, France
| | - A Smolinska
- Department of Pharmacology and Toxicology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - R Fijten
- Department of Pharmacology and Toxicology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
- Department of Radiation Oncology (Maastro) GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, 6229 ET, Maastricht, The Netherlands
| | - M Flamant
- Service de Physiologie - Explorations Fonctionnelle, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Paris, France
| | - J Dallinga
- Department of Pharmacology and Toxicology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - J J Mercadier
- Service de Physiologie - Explorations Fonctionnelle, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Paris, France
| | - D Pachen
- Department of Pharmacology and Toxicology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - M P d'Ortho
- Service de Physiologie - Explorations Fonctionnelle, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Paris, France
- Université de Paris, INSERM UMR 1141, NeuroDiderot, France
| | - F J van Schooten
- Department of Pharmacology and Toxicology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - B Crestani
- Service de Pneumologie A, DHU FIRE, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Paris, France
- Université Paris Diderot, PRES Sorbonne Paris Cité, Paris, France
- INSERM UMR1152, Labex Inflamex, Paris, France
| | - A W Boots
- Department of Pharmacology and Toxicology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.
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González-López NM, Huertas-Ortiz KA, Leguizamon-Guerrero JE, Arias-Cortés MM, Tere-Peña CP, García-Castañeda JE, Rivera-Monroy ZJ. Omics in the detection and identification of biosynthetic pathways related to mycotoxin synthesis. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:4038-4054. [PMID: 34486583 DOI: 10.1039/d1ay01017d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Mycotoxins are secondary metabolites that are known to be toxic to humans and animals. On the other hand, some mycotoxins and their analogues possess antioxidant as well as antitumor properties, which could be relevant in the fields of pharmaceutical analysis and food research. Omics techniques are a group of analytical tools applied in the biological sciences in order to study genes (genomics), mRNA (transcriptomics), proteins (proteomics), and metabolites (metabolomics). Omics have become a vital tool in the field of mycotoxins, especially contributing to the identification of biomarkers with potential use for the detection of mycotoxigenic species and the gathering of information about the biosynthetic pathways of mycotoxins in different environments. This approach has provided tools for the development of prevention strategies and control measures for different mycotoxins. Additionally, research has revealed important information about the impact of global warming and climate change on the prevalence of mycotoxin issues in society. In the context of foodomics, the aim is to apply omics techniques in order to ensure food safety. The objective of the present review is to determine the state of the art regarding the development of analytical techniques based on omics in the identification of biosynthetic pathways related to mycotoxin synthesis.
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Affiliation(s)
| | - Kevin Andrey Huertas-Ortiz
- Facultad de Ciencias, Universidad Nacional de Colombia, Carrera 45 No 26-85, Building 450, Bogotá, Colombia.
| | | | | | | | | | - Zuly Jenny Rivera-Monroy
- Facultad de Ciencias, Universidad Nacional de Colombia, Carrera 45 No 26-85, Building 450, Bogotá, Colombia.
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11
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Pérez-Cova M, Jaumot J, Tauler R. Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116207] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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12
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Garrido A, Engel J, Mumm R, Conde A, Cunha A, De Vos RCH. Metabolomics of Photosynthetically Active Tissues in White Grapes: Effects of Light Microclimate and Stress Mitigation Strategies. Metabolites 2021; 11:metabo11040205. [PMID: 33808188 PMCID: PMC8067353 DOI: 10.3390/metabo11040205] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 03/19/2021] [Accepted: 03/26/2021] [Indexed: 12/17/2022] Open
Abstract
The effects of climate change are becoming a real concern for the viticulture sector, with impacts on both grapevine physiology and the quality of the fresh berries and wine. Short-term mitigation strategies, like foliar kaolin application and smart irrigation regimes, have been implemented to overcome these problems. We previously showed that these strategies also influence the photosynthetic activity of the berries themselves, specifically in the exocarp and seed. In the present work, we assessed the modulating effects of both canopy-light microclimate, kaolin and irrigation treatments on the metabolic profiles of the exocarp and seed, as well as the potential role of berry photosynthesis herein. Berries from the white variety Alvarinho were collected at two contrasting light microclimate positions within the vine canopy (HL—high light and LL—low light) from both irrigated and kaolin-treated plants, and their respective controls, at three fruit developmental stages (green, véraison and mature). Untargeted liquid chromatography mass spectrometry (LCMS) profiling of semi-polar extracts followed by multivariate statistical analysis indicate that both the light microclimate and irrigation influenced the level of a series of phenolic compounds, depending on the ripening stage of the berries. Moreover, untargeted gas chromatography mass spectrometry (GCMS) profiling of polar extracts show that amino acid and sugar levels were influenced mainly by the interaction of irrigation and kaolin treatments. The results reveal that both photosynthetically active berry tissues had a distinct metabolic profile in response to the local light microclimate, which suggests a specific role of photosynthesis in these tissues. A higher light intensity within the canopy mainly increased the supply of carbon precursors to the phenylpropanoid/flavonoid pathway, resulting in increased levels of phenolic compounds in the exocarp, while in seeds, light mostly influenced compounds related to carbon storage and seed development. In addition, our work provides new insights into the influence of abiotic stress mitigation strategies on the composition of exocarps and seeds, which are both important tissues for the quality of grape-derived products.
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Affiliation(s)
- Andreia Garrido
- Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal;
- Correspondence: (A.G.); (A.C.)
| | - Jasper Engel
- Business Unit Bioscience, Wageningen Plant Research, Wageningen University and Research (Wageningen-UR), P.O. Box 16, 6700 AA Wageningen, The Netherlands; (J.E.); (R.M.); (R.C.H.D.V.)
- Business Unit Biometris, Wageningen Plant Research, Wageningen University and Research (Wageningen-UR), P.O. Box 16, 6700 AA Wageningen, The Netherlands
| | - Roland Mumm
- Business Unit Bioscience, Wageningen Plant Research, Wageningen University and Research (Wageningen-UR), P.O. Box 16, 6700 AA Wageningen, The Netherlands; (J.E.); (R.M.); (R.C.H.D.V.)
| | - Artur Conde
- Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal;
- Centre of Molecular and Environmental Biology (CBMA), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal
| | - Ana Cunha
- Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal;
- Centre of Molecular and Environmental Biology (CBMA), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal
- Centre of Biological Engineering (CEB), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal
- Correspondence: (A.G.); (A.C.)
| | - Ric C. H. De Vos
- Business Unit Bioscience, Wageningen Plant Research, Wageningen University and Research (Wageningen-UR), P.O. Box 16, 6700 AA Wageningen, The Netherlands; (J.E.); (R.M.); (R.C.H.D.V.)
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13
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O'Leary J, Journeaux KL, Houthuijs K, Engel J, Sommer U, Viant MR, Eastwood DC, Müller C, Boddy L. Space and patchiness affects diversity-function relationships in fungal decay communities. THE ISME JOURNAL 2021; 15:720-731. [PMID: 33067587 PMCID: PMC8027639 DOI: 10.1038/s41396-020-00808-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 10/01/2020] [Accepted: 10/05/2020] [Indexed: 01/30/2023]
Abstract
The space in which organisms live determines health and physicality, shaping the way in which they interact with their peers. Space, therefore, is critically important for species diversity and the function performed by individuals within mixed communities. The biotic and abiotic factors defined by the space that organisms occupy are ecologically significant and the difficulty in quantifying space-defined parameters within complex systems limits the study of ecological processes. Here, we overcome this problem using a tractable system whereby spatial heterogeneity in interacting fungal wood decay communities demonstrates that scale and patchiness of territory directly influence coexistence dynamics. Spatial arrangement in 2- and 3-dimensions resulted in measurable metabolic differences that provide evidence of a clear biological response to changing landscape architecture. This is of vital importance to microbial systems in all ecosystems globally, as our results demonstrate that community function is driven by the effects of spatial dynamics.
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Affiliation(s)
- Jade O'Leary
- Cardiff School of Biosciences, Cardiff University, Cardiff, CF10 3AX, UK
| | - Katie L Journeaux
- Cardiff School of Biosciences, Cardiff University, Cardiff, CF10 3AX, UK
| | - Kas Houthuijs
- Institute for Molecules and Materials, Radboud University, 6525 AJ, Nijmegen, The Netherlands
| | - Jasper Engel
- NERC Biomolecular Analysis Facility-Metabolomics Node (NBAF-B), School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Ulf Sommer
- NERC Biomolecular Analysis Facility-Metabolomics Node (NBAF-B), School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Mark R Viant
- NERC Biomolecular Analysis Facility-Metabolomics Node (NBAF-B), School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | | | - Carsten Müller
- Cardiff School of Biosciences, Cardiff University, Cardiff, CF10 3AX, UK
| | - Lynne Boddy
- Cardiff School of Biosciences, Cardiff University, Cardiff, CF10 3AX, UK.
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14
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van Horck M, Smolinska A, Wesseling G, de Winter-de Groot K, de Vreede I, Winkens B, Jöbsis Q, Dallinga J, Dompeling E, van Schooten FJ. Exhaled volatile organic compounds detect pulmonary exacerbations early in children with cystic fibrosis: results of a 1 year observational pilot study. J Breath Res 2021; 15:026012. [PMID: 33630756 DOI: 10.1088/1752-7163/abda55] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
In patients with cystic fibrosis (CF), pulmonary exacerbations (PEx) have an important influence on well-being, quality of life, and lung function decline. Early detection combined with early treatment may prevent severe PEx. To determine whether early detection of PEx is possible by non-invasive markers (volatile organic compounds) in exhaled breath. In a 1 year prospective observational pilot study, 49 children with CF were studied. At clinical visits with an interval of 2 months, lung function, volatile organic compounds (VOCs) in exhaled breath by means of gas chromatography-time-of-flight-mass spectrometry, and medication use were assessed. PEx were recorded. Random forest (RF) classification modelling was used to select discriminatory VOCs, followed by building of receiver operating characteristic curves. An inverse relation between the predictive power of a set of VOCs and time between exhaled breath sampling and the onset of PEx was found. When this time period was within 7 d, the RF model with the nine most discriminatory VOCs was able to correctly predict 79% of the children with an upcoming PEx or remaining stable (sensitivity 79% and specificity 78%). This result was validated by means of bootstrapping within the RF classification model. PEx in children with CF can be detected at an early stage by means of exhaled VOCs. The highest predictive value was reached if time between sampling and the onset of an exacerbation was no longer than 7 d.
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Affiliation(s)
- Marieke van Horck
- Department of Paediatric Pulmonology, School for Public Health and Primary Health Care (CAPHRI), Maastricht University Medical Centre (MUMC+), Maastricht, The Netherlands
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15
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Bertinetto C, Engel J, Jansen J. ANOVA simultaneous component analysis: A tutorial review. Anal Chim Acta X 2020; 6:100061. [PMID: 33392497 PMCID: PMC7772684 DOI: 10.1016/j.acax.2020.100061] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 09/29/2020] [Accepted: 10/02/2020] [Indexed: 12/27/2022] Open
Abstract
When analyzing experimental chemical data, it is often necessary to incorporate the structure of the study design into the chemometric/statistical models to effectively address the research questions of interest. ANOVA-Simultaneous Component Analysis (ASCA) is one of the most prominent methods to include such information in the quantitative analysis of multivariate data, especially when the number of variables is large. This tutorial review intends to explain in a simple way how ASCA works, how it is operated and how to correctly interpret ASCA results, with approachable mathematical and visual descriptions. Two examples are given: the first, a simulated chemical reaction, serves to illustrate the ASCA steps and the second, from a real chemical ecology data set, the interpretation of results. An overview of methods closely related to ASCA is also provided, pointing out their differences and scope, to give a wide-ranging picture of the available options to build multivariate models that take experimental design into account. ASCA is a multivariate method for analysis of multi-factor data. An overview of the (mathematical) principles of ASCA is presented. Key aspects for practical application of ASCA are discussed. Detailed explanation of ASCA output in terms of score and loading plots is given. Literature review of other multivariate techniques for analysis of multi-factor data.
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Affiliation(s)
- Carlo Bertinetto
- Department of Analytical Chemistry, Institute of Molecular Materials, Radboud University, the Netherlands
| | - Jasper Engel
- Biometris, Wageningen UR, Droevendaalsesteeg 1, 6708 PB, Wageningen, the Netherlands
| | - Jeroen Jansen
- Department of Analytical Chemistry, Institute of Molecular Materials, Radboud University, the Netherlands
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16
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Chemometric Strategies for Spectroscopy-Based Food Authentication. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10186544] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
In the last decades, spectroscopic techniques have played an increasingly crucial role in analytical chemistry, due to the numerous advantages they offer. Several of these techniques (e.g., Near-InfraRed—NIR—or Fourier Transform InfraRed—FT-IR—spectroscopy) are considered particularly valuable because, by means of suitable equipment, they enable a fast and non-destructive sample characterization. This aspect, together with the possibility of easily developing devices for on- and in-line applications, has recently favored the diffusion of such approaches especially in the context of foodstuff quality control. Nevertheless, the complex nature of the signal yielded by spectroscopy instrumentation (regardless of the spectral range investigated) inevitably calls for the use of multivariate chemometric strategies for its accurate assessment and interpretation. This review aims at providing a comprehensive overview of some of the chemometric tools most commonly exploited for spectroscopy-based foodstuff analysis and authentication. More in detail, three different scenarios will be surveyed here: data exploration, calibration and classification. The main methodologies suited to addressing each one of these different tasks will be outlined and examples illustrating their use will be provided alongside their description.
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17
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Menżyk A, Damin A, Martyna A, Alladio E, Vincenti M, Martra G, Zadora G. Toward a novel framework for bloodstains dating by Raman spectroscopy: How to avoid sample photodamage and subsampling errors. Talanta 2020; 209:120565. [DOI: 10.1016/j.talanta.2019.120565] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 11/07/2019] [Accepted: 11/12/2019] [Indexed: 01/22/2023]
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18
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Clavel J, Morlon H. Reliable Phylogenetic Regressions for Multivariate Comparative Data: Illustration with the MANOVA and Application to the Effect of Diet on Mandible Morphology in Phyllostomid Bats. Syst Biol 2020; 69:927-943. [DOI: 10.1093/sysbio/syaa010] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 02/02/2020] [Accepted: 02/07/2020] [Indexed: 11/12/2022] Open
Abstract
Abstract
Understanding what shapes species phenotypes over macroevolutionary timescales from comparative data often requires studying the relationship between phenotypes and putative explanatory factors or testing for differences in phenotypes across species groups. In phyllostomid bats for example, is mandible morphology associated to diet preferences? Performing such analyses depends upon reliable phylogenetic regression techniques and associated tests (e.g., phylogenetic Generalized Least Squares, pGLS, and phylogenetic analyses of variance and covariance, pANOVA, pANCOVA). While these tools are well established for univariate data, their multivariate counterparts are lagging behind. This is particularly true for high-dimensional phenotypic data, such as morphometric data. Here, we implement much-needed likelihood-based multivariate pGLS, pMANOVA, and pMANCOVA, and use a recently developed penalized-likelihood framework to extend their application to the difficult case when the number of traits $p$ approaches or exceeds the number of species $n$. We then focus on the pMANOVA and use intensive simulations to assess the performance of the approach as $p$ increases, under various levels of phylogenetic signal and correlations between the traits, phylogenetic structure in the predictors, and under various types of phenotypic differences across species groups. We show that our approach outperforms available alternatives under all circumstances, with greater power to detect phenotypic differences across species group when they exist, and a lower risk of improperly detecting nonexistent differences. Finally, we provide an empirical illustration of our pMANOVA on a geometric-morphometric data set describing mandible morphology in phyllostomid bats along with data on their diet preferences. Overall our results show significant differences between ecological groups. Our approach, implemented in the R package mvMORPH and illustrated in a tutorial for end-users, provides efficient multivariate phylogenetic regression tools for understanding what shapes phenotypic differences across species. [Generalized least squares; high-dimensional data sets; multivariate phylogenetic comparative methods; penalized likelihood; phenomics; phyllostomid bats; phylogenetic MANOVA; phylogenetic regression.]
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Affiliation(s)
- Julien Clavel
- Institut de Biologie de l’École Normale Supérieure (IBENS), École Normale Supérieure, Paris Sciences et Lettres (PSL) Research University, CNRS UMR 8197, INSERM U1024, 46 rue d’Ulm, F-75005 Paris, France
- Life Sciences Department, The Natural History Museum, Cromwell Road, London SW7 5BD, UK
- Univ Lyon, Laboratoire d’Ecologie des Hydrosystémes Naturels et Anthropisés, UMR CNRS 5023, Université Claude Bernard Lyon 1, ENTPE, Boulevard du 11 Novembre 1918 F-69622, Villeurbanne Cedex, France
| | - Hélène Morlon
- Institut de Biologie de l’École Normale Supérieure (IBENS), École Normale Supérieure, Paris Sciences et Lettres (PSL) Research University, CNRS UMR 8197, INSERM U1024, 46 rue d’Ulm, F-75005 Paris, France
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MacAllister S, Mencuccini M, Sommer U, Engel J, Hudson A, Salmon Y, Dexter KG. Drought-induced mortality in Scots pine: opening the metabolic black box. TREE PHYSIOLOGY 2019; 39:1358-1370. [PMID: 31038161 DOI: 10.1093/treephys/tpz049] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 04/11/2019] [Accepted: 04/15/2019] [Indexed: 06/09/2023]
Abstract
Forests are sensitive to droughts, which increase the mortality rate of tree species. Various processes have been proposed to underlie drought-induced tree mortality, including hydraulic failure, carbon starvation and increased susceptibility to natural enemies. To give insights into these processes, we assessed the metabolic effects of a mortality-inducing drought on seedlings of Pinus sylvestris L. (Scots Pine), a widespread and important Eurasian species. We found divergence over time in the foliar metabolic composition of droughted vs well-watered seedlings, with the former showing increased abundance of aromatic amino acids and decreases in secondary metabolism associated with defence. We observed no significant differences amongst provenances in these effects: seedlings from drought-prone areas showed the same foliar metabolic changes under drought as seedlings from moist environments, although morphological effects of drought varied by provenance. Overall, our results demonstrate how severe drought prior to death may target particular primary and secondary metabolic pathways, weakening defences against natural enemies and contributing to the risk of drought-induced mortality in P. sylvestris.
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Affiliation(s)
| | | | - Ulf Sommer
- NBAF-Birmingham, School of Biosciences, University of Birmingham, UK
| | - Jasper Engel
- NBAF-Birmingham, School of Biosciences, University of Birmingham, UK
| | - Andrew Hudson
- School of Biological Sciences, University of Edinburgh, UK
| | | | - Kyle G Dexter
- School of GeoSciences, University of Edinburgh, UK
- Royal Botanic Garden Edinburgh, UK
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Gorrochategui E, Jaumot J, Tauler R. ROIMCR: a powerful analysis strategy for LC-MS metabolomic datasets. BMC Bioinformatics 2019; 20:256. [PMID: 31101001 PMCID: PMC6525397 DOI: 10.1186/s12859-019-2848-8] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 04/25/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND The analysis of LC-MS metabolomic datasets appears to be a challenging task in a wide range of disciplines since it demands the highly extensive processing of a vast amount of data. Different LC-MS data analysis packages have been developed in the last few years to facilitate this analysis. However, most of these strategies involve chromatographic alignment and peak shaping and often associate each "feature" (i.e., chromatographic peak) with a unique m/z measurement. Thus, the development of an alternative data analysis strategy that is applicable to most types of MS datasets and properly addresses these issues is still a challenge in the metabolomics field. RESULTS Here, we present an alternative approach called ROIMCR to: i) filter and compress massive LC-MS datasets while transforming their original structure into a data matrix of features without losing relevant information through the search of regions of interest (ROIs) in the m/z domain and ii) resolve compressed data to identify their contributing pure components without previous alignment or peak shaping by applying a Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) analysis. In this study, the basics of the ROIMCR method are presented in detail and a detailed description of its implementation is also provided. Data were analyzed using the MATLAB (The MathWorks, Inc., www.mathworks.com ) programming and computing environment. The application of the ROIMCR methodology is described in detail, with an example of LC-MS data generated in a lipidomic study and with other examples of recent applications. CONCLUSIONS The methodology presented here combines the benefits of data filtering and compression based on the searching of ROI features, without the loss of spectral accuracy. The method has the benefits of the application of the powerful MCR-ALS data resolution method without the necessity of performing chromatographic peak alignment or modelling. The presented method is a powerful alternative to other existing data analysis approaches that do not use the MCR-ALS method to resolve LC-MS data. The ROIMCR method also represents an improved strategy compared to the direct applications of the MCR-ALS method that use less-powerful data compression strategies such as binning and windowing. Overall, the strategy presented here confirms the usefulness of the ROIMCR chemometrics method for analyzing LC-MS untargeted metabolomics data.
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Affiliation(s)
- Eva Gorrochategui
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas (CSIC), Jorsi Girona 18-25, Barcelona, 08034, Catalonia, Spain
| | - Joaquim Jaumot
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas (CSIC), Jorsi Girona 18-25, Barcelona, 08034, Catalonia, Spain
| | - Romà Tauler
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas (CSIC), Jorsi Girona 18-25, Barcelona, 08034, Catalonia, Spain.
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Strani L, Grassi S, Casiraghi E, Alamprese C, Marini F. Milk Renneting: Study of Process Factor Influences by FT-NIR Spectroscopy and Chemometrics. FOOD BIOPROCESS TECH 2019. [DOI: 10.1007/s11947-019-02266-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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Comparing patterns of volatile organic compounds exhaled in breath after consumption of two infant formulae with a different lipid structure: a randomized trial. Sci Rep 2019; 9:554. [PMID: 30679671 PMCID: PMC6346115 DOI: 10.1038/s41598-018-37210-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 11/25/2018] [Indexed: 01/29/2023] Open
Abstract
Infant formulae have been used since decades as an alternative to or a complement to human milk. Human milk, the "gold standard" of infant nutrition, has been studied for its properties in order to create infant formulae that bring similar benefits to the infant. One of the characteristics of milk is the size of the lipid droplets which is known to affect the digestion, gastric emptying and triglyceride metabolism. In the current study a concept infant milk formula with large, phospholipid coating of lipid droplets (mode diameter 3-5 μm; NUTURIS, further described as "active"), was compared to a commercially available formula milk characterised by smaller lipid droplets, further described as "control" (both products derived from Nutricia). We investigated whether we could find an effect of lipid droplet size on volatile compounds in exhaled air upon ingestion of either product. For that purpose, exhaled breath was collected from a group of 29 healthy, non-smoking adult males before ingestion of a study product (baseline measurements, T0) and at the following time points after the test meal: 30, 60, 120, 180 and 240 min. Volatile organic compounds (VOCs) in breath were detected by gas chromatography-time-of-flight-mass spectrometry. Any differences in the time course of VOCs patterns upon intake of active and control products were investigated by regularised multivariate analysis of variance (rMANOVA). The rMANOVA analysis revealed statistically significant differences in the exhaled breath composition 240 min after ingestion of the active formula compared to control product (p-value < 0.0001), but did not show significant changes between active and control product at any earlier time points. A set of eight VOCs in exhaled breath had the highest contribution to the difference found at 240 minutes between the two formulas. A set of ten VOCs was different between baseline and the two formulae at T240 with p-value < 0.0001. To our knowledge this is the first study that shows the ability of VOCs in exhaled breath to monitor metabolic effects after ingestion of infant formulae with different lipid structure. The statistically significant differences in compound abundance found between active and control formula milk may be related to: (i) specific differences in the digestion, (ii) absorption of lipids and proteins and (iii) assimilation of the products in the gut.
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Smolinska A, Engel J, Szymanska E, Buydens L, Blanchet L. General Framing of Low-, Mid-, and High-Level Data Fusion With Examples in the Life Sciences. DATA HANDLING IN SCIENCE AND TECHNOLOGY 2019. [DOI: 10.1016/b978-0-444-63984-4.00003-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Clavel J, Aristide L, Morlon H. A Penalized Likelihood Framework for High-Dimensional Phylogenetic Comparative Methods and an Application to New-World Monkeys Brain Evolution. Syst Biol 2018; 68:93-116. [PMID: 29931145 DOI: 10.1093/sysbio/syy045] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 06/13/2018] [Indexed: 01/03/2023] Open
Abstract
Working with high-dimensional phylogenetic comparative data sets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits $p $ approaches the number of species $n $ and because some computational complications occur when $p $ exceeds $n$. Alternative phylogenetic comparative methods have recently been proposed to deal with the large $p $ small $n $ scenario but their use and performances are limited. Herein, we develop a penalized likelihood (PL) framework to deal with high-dimensional comparative data sets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian motion (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU), and Pagel's lambda models. We show using simulations that our PL approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when $p$ approaches $n$, and allows for their accurate estimation when $p$ equals or exceeds $n$. In addition, we show that PL models can be efficiently compared using generalized information criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic principal component analysis in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3D data set of brain shape in the New World monkeys. We find a clear support for an EB model suggesting an early diversification of brain morphology during the ecological radiation of the clade. PL offers an efficient way to deal with high-dimensional multivariate comparative data.
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Affiliation(s)
- Julien Clavel
- École Normale Supérieure, Paris Sciences et Lettres (PSL) Research University, Institut de Biologie de l'École Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, 46 rue d'Ulm, F-75005 Paris, France
| | - Leandro Aristide
- École Normale Supérieure, Paris Sciences et Lettres (PSL) Research University, Institut de Biologie de l'École Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, 46 rue d'Ulm, F-75005 Paris, France
| | - Hélène Morlon
- École Normale Supérieure, Paris Sciences et Lettres (PSL) Research University, Institut de Biologie de l'École Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, 46 rue d'Ulm, F-75005 Paris, France
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Ortiz-Villanueva E, Jaumot J, Martínez R, Navarro-Martín L, Piña B, Tauler R. Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 635:156-166. [PMID: 29660719 DOI: 10.1016/j.scitotenv.2018.03.369] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 03/29/2018] [Accepted: 03/30/2018] [Indexed: 05/15/2023]
Abstract
Bisphenol A (BPA), perfluorooctane sulfonate (PFOS), and tributyltin (TBT) are emerging endocrine disruptors (EDCs) with still poorly defined mechanisms of toxicity and metabolic effects in aquatic organisms. We used an untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) metabolomic approach to study the effects of sub-lethal doses of these three EDCs on the metabolic profiles of zebrafish embryos exposed from 48 to 120hpf (hours post fertilization). Advanced chemometric data analysis methods were used to reveal effects on the subjacent regulatory pathways. EDC treatments induced changes in concentrations of about 50 metabolites for TBT and BPA, and of 25 metabolites for PFOS. The analysis of the corresponding metabolic changes suggested the presence of similar underlying zebrafish responses to BPA, TBT and PFOS affecting the metabolism of glycerophospholipids, amino acids, purines and 2-oxocarboxylic acids. We related the changes in glycerophospholipid metabolism to alterations in absorption of the yolk sack, the main source of nutrients (including lipids) for the developing embryo, linking the molecular markers with adverse phenotypic effects. We propose a general mode of action for all three chemical compounds, probably related to their already described interaction with the PPAR/RXR complex, combined with specific effects on different signaling pathways resulting in particular alterations in the zebrafish embryos metabolism.
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Affiliation(s)
- Elena Ortiz-Villanueva
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Joaquim Jaumot
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Rubén Martínez
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Laia Navarro-Martín
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Benjamin Piña
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Romà Tauler
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain.
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Tauler R, Parastar H. Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists. Angew Chem Int Ed Engl 2018; 61:e201801134. [DOI: 10.1002/anie.201801134] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Indexed: 11/08/2022]
Affiliation(s)
- Roma Tauler
- IDAEA-CSIC Environmental Chemistry Jordi Girona 18-26 08034 Barcelona SPAIN
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Multivariate Analysis of Multiple Datasets: a Practical Guide for Chemical Ecology. J Chem Ecol 2018; 44:215-234. [PMID: 29479643 DOI: 10.1007/s10886-018-0932-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 02/03/2018] [Accepted: 02/04/2018] [Indexed: 10/17/2022]
Abstract
Chemical ecology has strong links with metabolomics, the large-scale study of all metabolites detectable in a biological sample. Consequently, chemical ecologists are often challenged by the statistical analyses of such large datasets. This holds especially true when the purpose is to integrate multiple datasets to obtain a holistic view and a better understanding of a biological system under study. The present article provides a comprehensive resource to analyze such complex datasets using multivariate methods. It starts from the necessary pre-treatment of data including data transformations and distance calculations, to the application of both gold standard and novel multivariate methods for the integration of different omics data. We illustrate the process of analysis along with detailed results interpretations for six issues representative of the different types of biological questions encountered by chemical ecologists. We provide the necessary knowledge and tools with reproducible R codes and chemical-ecological datasets to practice and teach multivariate methods.
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Piña B, Raldúa D, Barata C, Portugal J, Navarro-Martín L, Martínez R, Fuertes I, Casado M. Functional Data Analysis: Omics for Environmental Risk Assessment. COMPREHENSIVE ANALYTICAL CHEMISTRY 2018. [DOI: 10.1016/bs.coac.2018.07.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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Saccenti E, Smilde AK, Camacho J. Group-wise ANOVA simultaneous component analysis for designed omics experiments. Metabolomics 2018; 14:73. [PMID: 29861703 PMCID: PMC5962647 DOI: 10.1007/s11306-018-1369-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 05/05/2018] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis (ASCA) which allows interpretation of the variation induced by the different factors in a principal component analysis fashion. However, while in general only a subset of the measured variables may be related to the problem studied, all variables contribute to the final model and this may hamper interpretation. OBJECTIVES We introduce here a sparse implementation of ASCA termed group-wise ANOVA-simultaneous component analysis (GASCA) with the aim of obtaining models that are easier to interpret. METHODS GASCA is based on the concept of group-wise sparsity introduced in group-wise principal components analysis where structure to impose sparsity is defined in terms of groups of correlated variables found in the correlation matrices calculated from the effect matrices. RESULTS The GASCA model, containing only selected subsets of the original variables, is easier to interpret and describes relevant biological processes. CONCLUSIONS GASCA is applicable to any kind of omics data obtained through designed experiments such as, but not limited to, metabolomic, proteomic and gene expression data.
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Metabolomics in gestational diabetes. Clin Chim Acta 2017; 475:116-127. [DOI: 10.1016/j.cca.2017.10.019] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 10/19/2017] [Accepted: 10/20/2017] [Indexed: 12/21/2022]
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Simultaneous optimisation of extraction of xanthone and benzophenone α-glucosidase inhibitors from Cyclopia genistoides and identification of superior genotypes for propagation. J Funct Foods 2017. [DOI: 10.1016/j.jff.2017.03.011] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Smolinska A, Bodelier AGL, Dallinga JW, Masclee AAM, Jonkers DM, van Schooten FJ, Pierik MJ. The potential of volatile organic compounds for the detection of active disease in patients with ulcerative colitis. Aliment Pharmacol Ther 2017; 45:1244-1254. [PMID: 28239876 DOI: 10.1111/apt.14004] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Revised: 07/26/2016] [Accepted: 02/01/2017] [Indexed: 12/22/2022]
Abstract
BACKGROUND To optimise treatment of ulcerative colitis (UC), patients need repeated assessment of mucosal inflammation. Current non-invasive biomarkers and clinical activity indices do not accurately reflect disease activity in all patients and cannot discriminate UC from non-UC colitis. Volatile organic compounds (VOCs) in exhaled air could be predictive of active disease or remission in Crohn's disease. AIM To investigate whether VOCs are able to differentiate between active UC, UC in remission and non-UC colitis. METHODS UC patients participated in a 1-year study. Clinical activity index, blood, faecal and breath samples were collected at each out-patient visit. Patients with clear defined active faecal calprotectin >250 μg/g and inactive disease (Simple Clinical Colitis Activity Index <3, C-reactive protein <5 mg/L and faecal calprotectin <100 μg/g) were included for cross-sectional analysis. Non-UC colitis was confirmed by stool culture or radiological evaluation. Breath samples were analysed by gas chromatography time-of-flight mass spectrometry and kernel-based method to identify discriminating VOCs. RESULTS In total, 72 UC (132 breath samples; 62 active; 70 remission) and 22 non-UC-colitis patients (22 samples) were included. Eleven VOCs predicted active vs. inactive UC in an independent internal validation set with 92% sensitivity and 77% specificity (AUC 0.94). Non-UC colitis patients could be clearly separated from active and inactive UC patients with principal component analysis. CONCLUSIONS Volatile organic compounds can accurately distinguish active disease from remission in UC and profiles in UC are clearly different from profiles in non-UC colitis patients. VOCs have demonstrated potential as new non-invasive biomarker to monitor inflammation in UC.
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Affiliation(s)
- A Smolinska
- Department of Pharmacology and Toxicology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - A G L Bodelier
- Department of Gastroenterology and Hepatology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, The Netherlands.,Department of Gastroenterology, Amphia Hospital, Breda, The Netherlands
| | - J W Dallinga
- Department of Pharmacology and Toxicology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - A A M Masclee
- Department of Gastroenterology and Hepatology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - D M Jonkers
- Department of Gastroenterology and Hepatology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - F-J van Schooten
- Department of Pharmacology and Toxicology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - M J Pierik
- Department of Gastroenterology and Hepatology, NUTRIM School for Nutrition, and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, The Netherlands
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Combining ANOVA-PCA with POCHEMON to analyse micro-organism development in a polymicrobial environment. Anal Chim Acta 2017; 963:1-16. [DOI: 10.1016/j.aca.2017.01.064] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Revised: 01/26/2017] [Accepted: 01/31/2017] [Indexed: 11/23/2022]
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Blanchet L, Smolinska A, Baranska A, Tigchelaar E, Swertz M, Zhernakova A, Dallinga JW, Wijmenga C, van Schooten FJ. Factors that influence the volatile organic compound content in human breath. J Breath Res 2017; 11:016013. [PMID: 28140379 DOI: 10.1088/1752-7163/aa5cc5] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Thousands of endogenous and exogenous volatile organic compounds (VOCs) are excreted in each breath. Inflammatory and deviant metabolic processes affect the level of endogeneous VOCs, which can serve as specific biomarkers for clinical diagnosis and disease monitoring. Important issues that still need to be tackled are related to potential confounding factors like gender and age and endogenous and exogenous factors, like f.i. smoking. METHODS The aim of this study was to systematically access the effect of endogenous and exogenous factors on VOC composition of exhaled breath. In the current study breath samples from 1417 adult participants from the LifeLines cohort, a general population cohort in the Netherlands, were collected and the total content of VOCs was measured using gas chromatography-time-of-flight-mass spectrometry. Breath samples were collected in Groningen and transferred to carbon tubes immediately. These samples were then shipped to Maastricht and measured in batches. VOCs profiles were correlated to 14 relevant characteristics of all participants including age, BMI, smoking and blood cell counts and metabolic parameters as well as to 16 classes of medications. RESULTS VOCs profiles were shown to be significantly influenced by smoking behavior and to a lesser extent by age, BMI and gender. These factors need to be controlled for in breath analysis studies. We found no evidence whatsoever in this 1417 subjects' cohort that white blood cell counts, cholesterol or triglycerides levels have an influence on the VOC profile. Thus they may not have to be controlled for in exhaled breath studies. CONCLUSION The large cohort of volunteers used here represents a unique opportunity to gauge the factors influencing VOCs profiles in a general population i.e. the most clinically relevant population. Classical clinical parameters and smoking habits clearly influence breath content and should therefore be accounted for in future clinical studies involving breath analysis.
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Affiliation(s)
- L Blanchet
- Top Institute Food and Nutrition (TIFN), Wageningen, The Netherlands. Department of Pharmacology and Toxicology, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University Medical Centre, Maastricht, The Netherlands. Thayer school of engineering, Dartmouth College, Hanover, NH, United States of America
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Tedjo DI, Smolinska A, Savelkoul PH, Masclee AA, van Schooten FJ, Pierik MJ, Penders J, Jonkers DMAE. The fecal microbiota as a biomarker for disease activity in Crohn's disease. Sci Rep 2016; 6:35216. [PMID: 27734914 PMCID: PMC5062155 DOI: 10.1038/srep35216] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 09/26/2016] [Indexed: 12/17/2022] Open
Abstract
Monitoring mucosal inflammation is crucial to prevent complications and disease progression in Crohn's disease (CD). Endoscopy is the current standard, but is invasive. Clinical activity scores and non-invasive biochemical markers do not correlate well with mucosal inflammation. Microbial perturbations have been associated with disease activity in CD. Therefore, we aimed to investigate its potential use to differentiate CD patients in remission from those with an exacerbation. From 71 CD patients repeated fecal samples were collected, resulting in 97 active disease and 97 remission samples based on a combination of biochemical and clinical parameters. The microbiota composition was assessed by pyrosequencing of the 16S rRNA V1-V3 region. Random Forest analysis was used to find the most discriminatory panel of operational taxonomic units (OTUs) between active and remission samples. An independent internal validation set was used to validate the model. A combination of 50 OTUs was able to correctly predict 73% of remission and 79% of active samples with an AUC of 0.82 (sensitivity: 0.79, specificity: 0.73). This study demonstrates that fecal microbial profiles can be used to differentiate between active and remission CD and underline the potential of the fecal microbiota as a non-invasive tool to monitor disease activity in CD.
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Affiliation(s)
- Danyta I Tedjo
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Division Gastroenterology-Hepatology, Maastricht University Medical Center+, Maastricht, The Netherlands.,School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Agnieszka Smolinska
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Pharmacology &Toxicology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Paul H Savelkoul
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Ad A Masclee
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Division Gastroenterology-Hepatology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Frederik J van Schooten
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Pharmacology &Toxicology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Marieke J Pierik
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Division Gastroenterology-Hepatology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - John Penders
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Daisy M A E Jonkers
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Division Gastroenterology-Hepatology, Maastricht University Medical Center+, Maastricht, The Netherlands
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A profile of volatile organic compounds in exhaled air as a potential non-invasive biomarker for liver cirrhosis. Sci Rep 2016; 6:19903. [PMID: 26822454 PMCID: PMC4731784 DOI: 10.1038/srep19903] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Accepted: 12/16/2015] [Indexed: 12/16/2022] Open
Abstract
Early diagnosis of liver cirrhosis may prevent progression and development of complications. Liver biopsy is the current standard, but is invasive and associated with morbidity. We aimed to identify exhaled volatiles within a heterogeneous group of chronic liver disease (CLD) patients that discriminates those with compensated cirrhosis (CIR) from those without cirrhosis, and compare this with serological markers. Breath samples were collected from 87 CLD and 34 CIR patients. Volatiles in exhaled air were measured by gas chromatography mass spectrometry. Discriminant Analysis was performed to identify the optimal panel of serological markers and VOCs for classifying our patients using a random training set of 27 CIR and 27 CLD patients. Two randomly selected independent internal validation sets and permutation test were used to validate the model. 5 serological markers were found to distinguish CIR and CLD patients with a sensitivity of 0.71 and specificity of 0.84. A set of 11 volatiles discriminated CIR from CLD patients with sensitivity of 0.83 and specificity of 0.87. Combining both did not further improve accuracy. A specific exhaled volatile profile can predict the presence of compensated cirrhosis among CLD patients with a higher accuracy than serological markers and can aid in reducing liver biopsies.
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Analysis of volatile organic compounds in exhaled breath to diagnose ventilator-associated pneumonia. Sci Rep 2015; 5:17179. [PMID: 26608483 PMCID: PMC4660425 DOI: 10.1038/srep17179] [Citation(s) in RCA: 99] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Accepted: 10/27/2015] [Indexed: 01/19/2023] Open
Abstract
Ventilator-associated pneumonia (VAP) is a nosocomial infection occurring in the
intensive care unit (ICU). The diagnostic standard is based on clinical criteria and
bronchoalveolar lavage (BAL). Exhaled breath analysis is a promising non-invasive
method for rapid diagnosis of diseases and contains volatile organic compounds
(VOCs) that can differentiate diseased from healthy individuals. The aim of this
study was to determine whether analysis of VOCs in exhaled breath can be used as a
non-invasive monitoring tool for VAP. One hundred critically ill patients with
clinical suspicion of VAP underwent BAL. Before BAL, exhaled air samples were
collected and analysed by gas chromatography time-of-flight mass spectrometry
(GC-tof-MS). The clinical suspicion of VAP was confirmed by BAL
diagnostic criteria in 32 patients [VAP(+)] and rejected in 68 patients
[VAP(−)]. Multivariate statistical comparison of VOC profiles between
VAP(+) and VAP(−) revealed a subset of 12 VOCs that correctly
discriminated between those two patient groups with a sensitivity and specificity of
75.8% ± 13.5% and 73.0% ± 11.8%, respectively. These results
suggest that detection of VAP in ICU patients is possible by examining exhaled
breath, enabling a simple, safe and non-invasive approach that could diminish
diagnostic burden of VAP.
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