A python-based pipeline for preprocessing lc–ms data for untargeted metabolomics workflows

Preprocessing data in a reproducible and robust way is one of the current challenges in untargeted metabolomics workflows. Data curation in liquid chromatography–mass spectrometry (LC–MS) involves the removal of biologically non-relevant features (retention time, m/z pairs) to retain only high-quality data for subsequent analysis and interpretation. The present work introduces TidyMS, a package for the Python programming language for preprocessing LC–MS data for quality control (QC) procedures in untargeted metabolomics workflows. It is a versatile strategy that can be customized or fit for purpose according to the specific metabolomics application. It allows performing quality control procedures to ensure accuracy and reliability in LC–MS measurements, and it allows preprocessing metabolomics data to obtain cleaned matrices for subsequent statistical analysis. The capabilities of the package are shown with pipelines for an LC–MS system suitability check, system conditioning, signal drift evaluation, and data curation. These applications were implemented to preprocess data corresponding to a new suite of candidate plasma reference materials developed by the National Institute of Standards and Technology (NIST; hypertriglyceridemic, diabetic, and African-American plasma pools) to be used in untargeted metabolomics studies in addition to NIST SRM 1950 Metabolites in Frozen Human Plasma. The package offers a rapid and reproducible workflow that can be used in an automated or semi-automated fashion, and it is an open and free tool available to all users.Fil: Riquelme, Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; ArgentinaFil: Zabalegui, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; ArgentinaFil: Marchi, Pablo Gabriel. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Jones, Christina M.. National Institute Of Standards And Technology; Estados UnidosFil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentin

Metabolic Footprinting of a Clear Cell Renal Cell Carcinoma in Vitro Model for Human Kidney Cancer Detection

A protocol for harvesting and extracting extracellular metabolites from an in vitro model of human renal cell lines was developed to profile the exometabolome by means of a discovery-based metabolomics approach using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry. Metabolic footprints provided by conditioned media (CM) samples (n = 66) of two clear cell Renal Cell Carcinoma (ccRCC) cell lines with different genetic backgrounds and a nontumor renal cell line, were compared with the human serum metabolic profile of a pilot cohort (n = 10) comprised of stage IV ccRCC patients and healthy individuals. Using a cross-validated orthogonal projection to latent structures-discriminant analysis model, a panel of 21 discriminant features selected by iterative multivariate classification, allowed differentiating control from tumor cell lines with 100% specificity, sensitivity, and accuracy. Isoleucine/leucine, phenylalanine, N-lactoyl-leucine, and N-acetyl-phenylalanine, and cysteinegluthatione disulfide (CYSSG) were identified by chemical standards, and hydroxyprolyl-valine was identified with MS and MS/MS experiments. A subset of 9 discriminant features, including the identified metabolites except for CYSSG, produced a fingerprint of classification value that enabled discerning ccRCC patients from healthy individuals. To our knowledge, this is the first time that N-lactoyl-leucine is associated with ccRCC. Results from this study provide a proof of concept that CM can be used as a serum proxy to obtain disease-related metabolic signatures.Fil: Knott, María Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Manzi, Malena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Zabalegui, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Salazar, Mario Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones para el Descubrimiento de Fármacos de Rosario. Universidad Nacional de Rosario. Instituto de Investigaciones para el Descubrimiento de Fármacos de Rosario; ArgentinaFil: Puricelli, Lydia Ines. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentin

Seawater analysis by ambient mass-spectrometry-based seaomics

An analytical method coupled to multivariate statistical analysis was developed based on transmissionmode direct analysis in real-time quadrupole time-of-flight mass spectrometry (TM-DART-QTOF-MS) to interrogate lipophilic compounds in seawater samples without the need for desalinization. An untargeted metabolomics approach is addressed here as seaomics and was successfully implemented to discriminate the sea surface microlayer (SML) from the underlying water (ULW) samples (n D 22, 10 paired samples) collected during a field campaign at the Cabo Verde islands during September-October 2017. A panel of 11 ionic species detected in all samples allowed sample class discrimination by means of supervised multivariate statistical models. Tentative identification of the species enriched in the SML samples suggests that fatty alcohols, halogenated compounds, and oxygenated boron-containing organic compounds are available at the surface for air-water transfer processes. A subset of SML samples (n D 5) were subjected to on-site experiments during the campaign by using a lab-tofield approach to test their secondary organic aerosol (SOA) formation potency. The results from these experiments and the analytical seaomics strategy provide a proof of a concept that can be used for an approach to identifying organic molecules involved in aerosol formation processes at the air- water interface.Fil: Zabalegui, Nicolás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Manzi, Malena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Depoorter, Antoine. Universite Lyon 2; FranciaFil: Hayeck, Nathalie. Universite Lyon 2; FranciaFil: Roveretto, Marie. Leibniz Institute for Tropospheric Research ; AlemaniaFil: Li, Chunlin. Leibniz Institute for Tropospheric Research ; AlemaniaFil: Van Pinxteren, Manuela. Leibniz Institute for Tropospheric Research ; AlemaniaFil: Herrmann, Hartmut. Leibniz Institute for Tropospheric Research ; AlemaniaFil: George, Christian. Universite Lyon 2; FranciaFil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentin

Marine organic matter in the remote environment of the Cape Verde islands-an introduction and overview to the MarParCloud campaign

The project MarParCloud (Marine biological production, organic aerosol Particles and marine Clouds: a process chain) aims to improve our understanding of the genesis, modification and impact of marine organic matter (OM) from its biological production, to its export to marine aerosol particles and, finally, to its ability to act as ice-nucleating particles (INPs) and cloud condensation nuclei (CCN). A field campaign at the Cape Verde Atmospheric Observatory (CVAO) in the tropics in September-October 2017 formed the core of this project that was jointly performed with the project MARSU (MARine atmospheric Science Unravelled). A suite of chemical, physical, biological and meteorological techniques was applied, and comprehensive measurements of bulk water, the sea surface microlayer (SML), cloud water and ambient aerosol particles collected at a ground-based and a mountain station took place. Key variables comprised the chemical characterization of the atmospherically relevant OM components in the ocean and the atmosphere as well as measurements of INPs and CCN. Moreover, bacterial cell counts, mercury species and trace gases were analyzed. To interpret the results, the measurements were accompanied by various auxiliary parameters such as air mass back-trajectory analysis, vertical atmospheric profile analysis, cloud observations and pigment measurements in seawater. Additional modeling studies supported the experimental analysis. During the campaign, the CVAO exhibited marine air masses with low and partly moderate dust influences. The marine boundary layer was well mixed as indicated by an almost uniform particle number size distribution within the boundary layer. Lipid biomarkers were present in the aerosol particles in typical concentrations of marine background conditions. Accumulation-and coarse-mode particles served as CCN and were efficiently transferred to the cloud water. The ascent of ocean-derived compounds, such as sea salt and sugar-like compounds, to the cloud level, as derived from chemical analysis and atmospheric transfer modeling results, denotes an influence of marine emissions on cloud formation. Organic nitrogen compounds (free amino acids) were enriched by several orders of magnitude in submicron aerosol particles and in cloud water compared to seawater. However, INP measurements also indicated a significant contribution of other non-marine sources to the local INP concentration, as (biologically active) INPs were mainly present in supermicron aerosol particles that are not suggested to undergo strong enrichment during ocean-atmosphere transfer. In addition, the number of CCN at the supersaturation of 0.30 % was about 2.5 times higher during dust periods compared to marine periods. Lipids, sugar-like compounds, UV-absorbing (UV: ultraviolet) humic-like substances and low-molecularweight neutral components were important organic compounds in the seawater, and highly surface-active lipids were enriched within the SML. The selective enrichment of specific organic compounds in the SML needs to be studied in further detail and implemented in an OM source function for emission modeling to better understand transfer patterns, the mechanisms of marine OM transformation in the atmosphere and the role of additional sources. In summary, when looking at particulate mass, we see oceanic compounds transferred to the atmospheric aerosol and to the cloud level, while from a perspective of particle number concentrations, sea spray aerosol (i.e., primary marine aerosol) contributions to both CCN and INPs are rather limited. © Author(s) 2020

Marine organic matter in the remote environment of the Cape Verde islands – an introduction and overview to the MarParCloud campaign

The project MarParCloud (Marine biological production, organic aerosol Particles and marine Clouds: a process chain) aims to improve our understanding of the genesis, modification and impact of marine organic matter (OM) from its biological production, to its export to marine aerosol particles and, finally, to its ability to act as ice-nucleating particles (INPs) and cloud condensation nuclei (CCN). A field campaign at the Cape Verde Atmospheric Observatory (CVAO) in the tropics in September–October 2017 formed the core of this project that was jointly performed with the project MARSU (MARine atmospheric Science Unravelled). A suite of chemical, physical, biological and meteorological techniques was applied, and comprehensive measurements of bulk water, the sea surface microlayer (SML), cloud water and ambient aerosol particles collected at a ground-based and a mountain station took place. Key variables comprised the chemical characterization of the atmospherically relevant OM components in the ocean and the atmosphere as well as measurements of INPs and CCN. Moreover, bacterial cell counts, mercury species and trace gases were analyzed. To interpret the results, the measurements were accompanied by various auxiliary parameters such as air mass back-trajectory analysis, vertical atmospheric profile analysis, cloud observations and pigment measurements in seawater. Additional modeling studies supported the experimental analysis. During the campaign, the CVAO exhibited marine air masses with low and partly moderate dust influences. The marine boundary layer was well mixed as indicated by an almost uniform particle number size distribution within the boundary layer. Lipid biomarkers were present in the aerosol particles in typical concentrations of marine background conditions. Accumulation- and coarse-mode particles served as CCN and were efficiently transferred to the cloud water. The ascent of ocean-derived compounds, such as sea salt and sugar-like compounds, to the cloud level, as derived from chemical analysis and atmospheric transfer modeling results, denotes an influence of marine emissions on cloud formation. Organic nitrogen compounds (free amino acids) were enriched by several orders of magnitude in submicron aerosol particles and in cloud water compared to seawater. However, INP measurements also indicated a significant contribution of other non-marine sources to the local INP concentration, as (biologically active) INPs were mainly present in supermicron aerosol particles that are not suggested to undergo strong enrichment during ocean–atmosphere transfer. In addition, the number of CCN at the supersaturation of 0.30 % was about 2.5 times higher during dust periods compared to marine periods. Lipids, sugar-like compounds, UV-absorbing (UV: ultraviolet) humic-like substances and low-molecular-weight neutral components were important organic compounds in the seawater, and highly surface-active lipids were enriched within the SML. The selective enrichment of specific organic compounds in the SML needs to be studied in further detail and implemented in an OM source function for emission modeling to better understand transfer patterns, the mechanisms of marine OM transformation in the atmosphere and the role of additional sources. In summary, when looking at particulate mass, we see oceanic compounds transferred to the atmospheric aerosol and to the cloud level, while from a perspective of particle number concentrations, sea spray aerosol (i.e., primary marine aerosol) contributions to both CCN and INPs are rather limited

Analytical strategies for mass spectrometry-based metabolomic studies : healthand atmospheric chemistry applications

La metabolómica es un campo en expansión a nivel mundial que estudia los cambios en los niveles de metabolitos en sistemas biológicos. La espectrometría de masas (MS) es una de las plataformas analíticas de preferencia para la caracterización del conjunto completo de moléculas pequeñas presentes en una muestra biológica (el metaboloma) debido a su sensibilidad y versatilidad, y ha sido aplicada a estudios metabolómicos en distintos campos, ya sea para analizar muestras de manera directa o bien acoplada a otras técnicas separativas. También se ha implementado con técnicas de desorción/ionización en condiciones ambientales. El propósito general de este trabajo de tesis es desarrollar estrategias analíticas por MS para analizar diferentes sistemas biológicos de manera de obtener paneles de metabolitos con potencial utilidad clínica en el estudio de cáncer renal o con relevancia en procesos atmosféricos. En el marco de las aplicaciones en química atmosférica, se desarrolló un método analítico utilizando la técnica de Análisis Directo en Tiempo Real (DART) acoplada a espectrometría de masas de alta resolución (HRMS) utilizando un espectrómetro con analizador de cuadrupolo tiempo de vuelo (QTOF), para el análisis de muestras de agua marina, y se evaluó su composición en relación a la capacidad de generación de aerosoles atmosféricos. Muestras de agua de mar recolectadas en la superficie del océano o a un metro de profundidad fueron discriminadas de acuerdo a los niveles de sus compuestos orgánicos disueltos usando una estrategia de metabolómica no dirigida e implementando procedimientos de control de calidad pioneros en el campo. En relación a las aplicaciones en salud humana, se realizó una exhaustiva revisión bibliográfica de estudios metabolómicos por MS para identificar las distintas estrategias adoptadas por la comunidad científica de metabolómica para mejorar el diagnóstico de cáncer renal. A partir del estudio de modelos in vitro, se realizó un análisis del exometaboloma de dos líneas celulares tumorales de carcinoma celular renal de células claras (CCRcc) y una línea celular no tumoral mediante un método de cromatografía líquida de ultra alta performance acoplada a HRMS (UPLC-HRMS) y se logró identificar un panel de metabolitos que permitió diferenciar los sistemas estudiados. Un subgrupo de metabolitos de dicho panel, identificado con el máximo nivel de confianza empleando estándares químicos comerciales y sintetizados en el laboratorio, permitió discriminar muestras séricas de pacientes con la enfermedad de controles sanos en una cohorte piloto (n=10). En un segundo estudio, se utilizó el mismo método analítico de UPLC-HRMS para obtener los perfiles metabólicos séricos en una cohorte (n=203) de controles sanos y pacientes con CCRcc en diferentes estadios y se aislaron variables metabólicas asociadas al diagnóstico y la progresión de la enfermedad. Además, tanto por UPLC-QTOF-MS como por DART-HRMS se identificaron huellas asociadas a los cambios post-quirúrgicos que ocurren en el fenotipo de los pacientes luego de haber sido sometidos a nefrectomía, a partir de la comparación de los perfiles obtenidos en muestras pareadas con los perfiles de controles sanos. Asimismo, se desarrolló un método de análisis rápido por DART-HRMS que permitió discriminar muestras de pacientes con CCRcc de controles sanos, detectando además un sub-grupo de lípidos discriminantes asociados al pronóstico de la enfermedad. Por último, se desarrolló una metodología para evaluar muestras candidatas a materiales de referencia en estudios metabolómicos no dirigidos por UPLC-HRMS en el marco de un estudio inter-laboratorio internacional.Metabolomics is a globally expanding field that studies changes in metabolite levels in various biological systems. Mass spectrometry is the analytical platform of preference for characterizing the small molecules present in a biological sample (the metabolome) due to its sensitivity and versatility. It has been applied to metabolomics studies in various fields, with direct sample analysis or coupled with other separation techniques, and it has also been implemented with ambient desorption/ionization techniques. The general aim of this doctoral thesis is to develop mass spectrometry-based analytical strategies to analyze different biological systems to obtain metabolite panels with potential clinical or atmospheric chemistry relevance. An analytical method was developed using Direct Analysis in Real Time (DART) coupled with high-resolution mass spectrometry (HRMS) using a quadrupole time-of-flight (QTOF) spectrometer as an approach to identifying organic molecules involved in aerosol formation processes at the air-water interface. Seawater samples, collected at the ocean surface or one-meter depth, were discriminated according to the levels of their dissolved organic compounds using an untargeted metabolomics strategy, and implementing pioneering quality control procedures in the field. Regarding applications in human health, an exhaustive literature review of mass spectrometry-based metabolomics studies was conducted to identify the different strategies adopted by the metabolomics scientific community to improve the diagnosis of renal cell carcinoma. Based on the study of in vitro models, metabolic footprints provided by conditioned media samples (n = 66) of two clear cell Renal Cell Carcinoma cell lines with different genetic backgrounds and a non-tumor renal cell line, were compared with the human serum metabolic profile of a pilot cohort (n=10), using an ultra-high performance liquid chromatography-HRMS (UPLC- HRMS)-based method. A metabolite panel allowed differentiating tumor from non-tumor cell lines and a subset of metabolites from this panel, identified with the highest level of confidence using commercial standards and standards synthesized in the laboratory, allowed discriminating serum samples from patients from healthy controls. In a second study, the same UPLC-HRMS-based analytical method was used to obtain serum metabolic profiles in a cohort (n=203) of healthy controls and ccRCC patients at different stages, and metabolic features associated with disease diagnosis and progression were isolated. In addition, signatures associated with the phenotype change after nephrectomy were identified in ccRCC patients by comparing the profiles obtained with UPLC-HRMS and DART-HRMS from paired samples. Furthermore, a fast DART-HRMS-based analysis method allowed discriminating ccRCC patients from healthy controls based on a subgroup of discriminating lipids associated with disease prognosis. Finally, a methodology was developed to evaluate reference materials in untargeted metabolomics studies by UPLC-HRMS in the context of an international inter-laboratory study.Fil: Zabalegui, Nicolás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Improving Diagnosis of Genitourinary Cancers: Biomarker Discovery Strategies through Mass Spectrometry-based Metabolomics

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.Fil: Manzi, Malena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Química Biológica; ArgentinaFil: Riquelme, Gabriel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Zabalegui, Nicolás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentin