Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics Experiments.

Direct-to-Mass Spectrometry and ambient ionization techniques can be used for biochemical fingerprinting in a fast way. Data processing is typically accomplished with vendor-provided software tools. Here, a novel, open-source functionality, entitled Tidy-Direct-to-MS, was developed for data processing of direct-to-MS data sets. It allows for fast and user-friendly processing using different modules for optional sample position detection and separation, mass-to-charge ratio drift detection and correction, consensus spectra calculation, and bracketing across sample positions as well as feature abundance calculation. The tool also provides functionality for the automated comparison of different sets of parameters, thereby assisting the user in the complex task of finding an optimal combination to maximize the total number of detected features while also checking for the detection of user-provided reference features. In addition, Tidy-Direct-to-MS has the capability for data quality review and subsequent data analysis, thereby simplifying the workflow of untargeted ambient MS-based metabolomics studies. Tidy-Direct-to-MS is implemented in the Python programming language as part of the TidyMS library and can thus be easily extended. Capabilities of Tidy-Direct-to-MS are showcased in a data set acquired in a marine metabolomics study reported in MetaboLights (MTBLS1198) using a transmission mode Direct Analysis in Real Time-Mass Spectrometry (TM-DART-MS)-based method.

Metabolomics 2023 workshop report: moving toward consensus on best QA/QC practices in LC-MS-based untargeted metabolomics.

INTRODUCTION: During the Metabolomics 2023 conference, the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) presented a QA/QC workshop for LC-MS-based untargeted metabolomics. OBJECTIVES: The Best Practices Working Group disseminated recent findings from community forums and discussed aspects to include in a living guidance document. METHODS: Presentations focused on reference materials, data quality review, metabolite identification/annotation and quality assurance. RESULTS: Live polling results and follow-up discussions offered a broad international perspective on QA/QC practices. CONCLUSIONS: Community input gathered from this workshop series is being used to shape the living guidance document, a continually evolving QA/QC best practices resource for metabolomics researchers.

Calcium, Phosphorus, and Vitamin D Levels in a Series of Cystic Fibrosis Patients: A Cross-Sectional Study.

Cystic fibrosis (CF) is a monogenic disease with different types of mutations that mainly affect the respiratory-digestive system. Calcium (Ca), phosphorus (P), and vitamin D (Vit-D) are essential nutrients for maintaining adequate growth and development, as well as key components in crucial metabolic pathways. Proper diagnosis, treatment, and response are decisive components of precision medicine. Therefore, we conducted a cross-sectional study to evaluate Ca, P, and Vit-D levels along with health and nutritional indicators, regarding their non-skeletal functions, in a series of CF patients. Anthropometric and clinical evaluation, biochemical analysis, dietary survey, and respiratory and pancreatic status were performed. Even though the results showed that all patients had normal dietary and serum Ca levels, 47% of patients had deficient Vit-D intake, 53% of patients had hypovitaminosis D, 35% had insufficient Vit-D levels, 18% had hypophosphatemia, 76% had elevated alkaline phosphate levels, 29% had hypercalciuria, and 65% had hyperphosphaturia. There were no significant differences between homozygous and compound heterozygous patients. Ca, P, and Vit-D levels were associated with body mass index; body composition; physical activity; diet; growth hormones; and the immune, liver, and kidney systems. We suggest a periodically evaluation of Ca and P losses.

Impact of Kluyveromyces marxianus VM004 culture conditions on the cell wall structure and its influence on aflatoxin B1 binding.

The aim of this study was to determine the impact of Kluyveromyces marxianus VM004 culture conditions on the cell wall (CW) structure and its influence on aflatoxin B1 binding. The yeast was inoculated into two types of culture media: yeast extract-peptone-dextrose (YPD) broth and dried distiller's grains with solubles (DDG). The CW was extracted from the biomass produced in these media. AFB1 (150ng/ml) adsorption tests using the biomass (1×107cells/ml) and the CW (0.001g) were performed at pH 2 and pH 8. Transmission electron microscopy (TEM) evaluated the CW thickness, and infrared spectroscopy (IR) determined the CW composition. Biomass production in YPD was higher than that in DDG. Cell diameter (µm) and CW thickness (µm) increased in the DDG medium. The CW percentage obtained in DDG was higher than that in YPD. The absorbance of carbohydrates by IR was higher in YPD. pH influenced AFB1 adsorption, which was lower at pH 8. The proportion of ß-glucan and chitin present in CW was higher in the YPD medium. The IR method allowed to study the CW carbohydrate variation under the influence of these carbon sources. In conclusion, the culture media composition influenced the ß-glucan and chitin composition and consequently, AFB1 adsorption.

Postoperative Metabolic Phenoreversion in Clear Cell Renal Cell Carcinoma.

The ultimate goal of surgical treatment in cancer is to remove the tumor mass for restoring a healthy state. A 16-lipid panel that discriminated healthy controls from clear cell renal cell carcinoma (ccRCC) patients in a prior study was evaluated in the present work in paired-serum samples collected from patients (n = 41) before and after nephrectomy. Changes in the lipid and metabolite fingerprints from ccRCC patients were investigated and compared with fingerprints from healthy individuals obtained by means of ultra-performance liquid chromatography-high-resolution mass spectrometry. The lipid panel differentiated phenotypes associated with metabolic restoration after surgery, representing a serum signature of phenoreversion to a healthy metabolic state. In particular, PC 16:0/0:0, PC 18:2/18:2, and linoleic acid allowed discriminating serum samples from ccRCC patients with poor prognosis from those with an improved outcome during the follow-up period. Ratios of PC 16:0/0:0 and PC 18:2/18:2 with linoleic acid levels may contribute as prognostic tools to support decision-making during the patient follow-up care. The preliminary character of these results should be validated with larger cohorts, including subjects with different ethnicities, life style, and diets. MetaboLights study references: MTBLS1839, MTBLS3838, and MTBLS4629.

Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples.

Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics.

Model-driven data curation pipeline for LC-MS-based untargeted metabolomics.

INTRODUCTION: There is still no community consensus regarding strategies for data quality review in liquid chromatography mass spectrometry (LC-MS)-based untargeted metabolomics. Assessing the analytical robustness of data, which is relevant for inter-laboratory comparisons and reproducibility, remains a challenge despite the wide variety of tools available for data processing. OBJECTIVES: The aim of this study was to provide a model to describe the sources of variation in LC-MS-based untargeted metabolomics measurements, to use it to build a comprehensive curation pipeline, and to provide quality assessment tools for data quality review. METHODS: Human serum samples (n=392) were analyzed by ultraperformance liquid chromatography coupled to high-resolution mass spectrometry (UPLC-HRMS) using an untargeted metabolomics approach. The pipeline and tools used to process this dataset were implemented as part of the open source, publicly available TidyMS Python-based package. RESULTS: The model was applied to understand data curation practices used by the metabolomics community. Sources of variation, which are often overlooked in untargeted metabolomic studies, were identified in the analysis. New tools were used to characterize certain types of variations. CONCLUSION: The developed pipeline allowed confirming data robustness by comparing the experimental results with expected values predicted by the model. New quality control practices were introduced to assess the analytical quality of data.

Response: "The Signal and the Noise"-a response to Clayton et al. (2021).

The purpose of this response is to clarify points about the steps we took in a systematic review of the literature and to reaffirm our findings.

Coupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma.

A discovery-based lipid profiling study of serum samples from a cohort that included patients with clear cell renal cell carcinoma (ccRCC) stages I, II, III, and IV (n = 112) and controls (n = 52) was performed using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry and machine learning techniques. Multivariate models based on support vector machines and the LASSO variable selection method yielded two discriminant lipid panels for ccRCC detection and early diagnosis. A 16-lipid panel allowed discriminating ccRCC patients from controls with 95.7% accuracy in a training set under cross-validation and 77.1% accuracy in an independent test set. A second model trained to discriminate early (I and II) from late (III and IV) stage ccRCC yielded a panel of 26 compounds that classified stage I patients from an independent test set with 82.1% accuracy. Thirteen species, including cholic acid, undecylenic acid, lauric acid, LPC(16:0/0:0), and PC(18:2/18:2), identified with level 1 exhibited significantly lower levels in samples from ccRCC patients compared to controls. Moreover, 3α-hydroxy-5α-androstan-17-one 3-sulfate, cis-5-dodecenoic acid, arachidonic acid, cis-13-docosenoic acid, PI(16:0/18:1), PC(16:0/18:2), and PC(O-16:0/20:4) contributed to discriminate early from late ccRCC stage patients. The results are auspicious for early ccRCC diagnosis after validation of the panels in larger and different cohorts.

Mass Spectrometry-Based Metabolic Fingerprinting Contributes to Unveil the Role of RSUME in Renal Cell Carcinoma Cell Metabolism.

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous disease with 50-80% patients exhibiting mutations in the von Hippel-Lindau (VHL) gene. RSUME (RWD domain (termed after three major RWD-containing proteins: RING finger-containing proteins, WD-repeat-containing proteins, and yeast DEAD (DEXD)-like helicases)-containing protein small ubiquitin-related modifier (SUMO) enhancer) acts as a negative regulator of VHL function in normoxia. A discovery-based metabolomics approach was developed by means of ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (MS) for fingerprinting the endometabolome of a human ccRCC cell line 786-O and three other transformed cell systems (n = 102) with different expressions of RSUME and VHL. Cross-validated orthogonal projection to latent structures discriminant analysis models were built on positive, negative, and a combination of positive- and negative-ion mode MS data sets. Discriminant feature panels selected by an iterative multivariate classification allowed differentiating cells with different expressions of RSUME and VHL. Fifteen identified discriminant metabolites with level 1, including glutathione, butyrylcarnitine, and acetylcarnitine, contributed to understand the role of RSUME in ccRCC. Altered pathways associated with the RSUME expression were validated by biological and bioinformatics analyses. Combined results showed that in the absence of VHL, RSUME is involved in the downregulation of the antioxidant defense system, whereas in the presence of VHL, it acts in rerouting energy-related pathways, negatively modulating the lipid utilization, and positively modulating the fatty acid synthesis, which may promote deposition in droplets.

Multifocal pyoderma gangrenosum secondary to subclinical diverticulitis: case report and brief literature review.

Pyoderma gangrenosum is characteristically associated with inflammatory bowel disease. However, the association between this neutrophilic dermatosis and diverticular disease is scarcely mentioned in the literature. Diverticulitis should be included in the differential diagnosis in patients with pyoderma gangrenosum and gastrointestinal complaints, or even in asymptomatic patients, particularly in the elderly. Misdiagnosis can lead to inadequate treatments and serious complications.

Review: Puberty blockers for transgender and gender diverse youth-a critical review of the literature.

BACKGROUND: Increasingly, early adolescents who are transgender or gender diverse (TGD) are seeking gender-affirming healthcare services. Pediatric healthcare providers supported by professional guidelines are treating many of these children with gonadotropin-releasing hormone agonists (GnRHa), which reversibly block pubertal development, giving the child and their family more time in which to explore the possibility of medical transition. METHODS: We conducted a critical review of the literature to answer a series of questions about criteria for using puberty-blocking medications, the specific drugs used, the risks and adverse consequences and/or the positive outcomes associated with their use. We searched four databases: LGBT Life, PsycINFO, PubMed, and Web of Science. From an initial sample of 211 articles, we systematically reviewed 9 research studies that met inclusion/exclusion criteria. RESULTS: Studies reviewed had samples ranging from 1 to 192 (N = 543). The majority (71%) of participants in these studies required a diagnosis of gender dysphoria to qualify for puberty suppression and were administered medication during Tanner stages 2 through 4. Positive outcomes were decreased suicidality in adulthood, improved affect and psychological functioning, and improved social life. Adverse factors associated with use were changes in body composition, slow growth, decreased height velocity, decreased bone turnover, cost of drugs, and lack of insurance coverage. One study met all quality criteria and was judged 'excellent', five studies met the majority of quality criteria resulting in 'good' ratings, whereas three studies were judged fair and had serious risks of bias. CONCLUSION: Given the potentially life-saving benefits of these medications for TGD youth, it is critical that rigorous longitudinal and mixed methods research be conducted that includes stakeholders and members of the gender diverse community with representative samples.

Effect of fungicides commonly used for Fusarium head blight management on growth and fumonisin production by Fusarium proliferatum.

Fumonisin occurrence was reported in wheat grains and F. proliferatum has been suggested to be the main contributor to its presence in wheat. Thus, a survey was performed in order to study the impact of four commercial fungicides used in Argentina for controlling Fusarium head blight disease (epoxiconazole+metconazole, tebuconazole, pyraclostrobin+epoxiconazole, and prothioconazole) on growth and fumonisin production of two F. proliferatum strains in relation to water activity (aW; 0.99, 0.97, 0.95) and temperature (15°C and 25°C). Most fungicides reduced growth rates when compared to the control (reduction increased as fungicide concentration increased), and reduced fumonisin production when they were used at high doses; however, most fungicides enhanced fumonisin production at sublethal doses, with the exception of prothioconazole. Thus, fungicides used for FHB management could enhance fumonisin production by F. proliferatum strains present in wheat grains.

Early Detection of Cystic Fibrosis Acute Pulmonary Exacerbations by Exhaled Breath Condensate Metabolomics.

The most common cause of death in cystic fibrosis (CF) patients is progressive lung function decline, which is punctuated by acute pulmonary exacerbations (APEs). A major challenge is to discover biomarkers for detecting an oncoming APE and allow for pre-emptive clinical interventions. Metabolic profiling of exhaled breath condensate (EBC) samples collected from CF patients before, during, and after APEs and under stable conditions (n = 210) was performed using ultraperformance liquid chromatography (UPLC) coupled to Orbitrap mass spectrometry (MS). Negative ion mode MS data showed that classification between metabolic profiles from "pre-APE" (pending APE before the CF patient had any signs of illness) and stable CF samples was possible with good sensitivities (85.7 and 89.5%), specificities (88.4 and 84.1%), and accuracies (87.7 and 85.7%) for pediatric and adult patients, respectively. Improved classification performance was achieved by combining positive with negative ion mode data. Discriminant metabolites included two potential biomarkers identified in a previous pilot study: lactic acid and 4-hydroxycyclohexylcarboxylic acid. Some of the discriminant metabolites had microbial origins, indicating a possible role of bacterial metabolism in APE progression. The results show promise for detecting an oncoming APE using EBC metabolites, thus permitting early intervention to abort such an event.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners.

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics. OBJECTIVES: In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics. METHODS: All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach. RESULTS: For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%). CONCLUSIONS: Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Preoperative Metabolic Signatures of Prostate Cancer Recurrence Following Radical Prostatectomy.

Technological advances in mass spectrometry (MS), liquid chromatography (LC) separations, nuclear magnetic resonance (NMR) spectroscopy, and big data analytics have made possible studying metabolism at an "omics" or systems level. Here, we applied a multiplatform (NMR + LC-MS) metabolomics approach to the study of preoperative metabolic alterations associated with prostate cancer recurrence. Thus far, predicting which patients will recur even after radical prostatectomy has not been possible. Correlation analysis on metabolite abundances detected on serum samples collected prior to surgery from prostate cancer patients ( n = 40 remission vs n = 40 recurrence) showed significant alterations in a number of pathways, including amino acid metabolism, purine and pyrimidine synthesis, tricarboxylic acid cycle, tryptophan catabolism, glucose, and lactate. Lipidomics experiments indicated higher lipid abundances on recurrent patients for a number of classes that included triglycerides, lysophosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, diglycerides, acyl carnitines, and ceramides. Machine learning approaches led to the selection of a 20-metabolite panel from a single preoperative blood sample that enabled prediction of recurrence with 92.6% accuracy, 94.4% sensitivity, and 91.9% specificity under cross-validation conditions.

Mass Spectrometry-Based Non-targeted Metabolic Profiling for Disease Detection: Recent Developments.

Mass spectrometry (MS) plays an important role in seeking biomarkers for disease detection. High-quality quantitative data is needed for accurate analysis of metabolic perturbations in patients. This article describes recent developments in MS-based non-targeted metabolomics research with applications to the detection of several major common human diseases, focusing on study cohorts, MS platforms utilized, statistical analyses and discriminant metabolite identification. Potential disease biomarkers recently discovered for type 2 diabetes, cardiovascular disease, hepatocellular carcinoma, breast cancer and prostate cancer through metabolomics are summarized, and limitations are discussed.

Transition to Self-Management among Adolescents with Polycystic Ovary Syndrome: Parent and Adolescent Perspectives.

PURPOSE: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among females. The foundation of PCOS self-management is engaging in healthy lifestyle habits, however, there is limited literature regarding adolescents' transition to PCOS self-management. The purpose of this study, therefore, is to explore parental and adolescent views of the transition to PCOS self-management. DESIGN AND METHODS: A qualitative descriptive approach was used through focus groups (N = 4) with adolescents diagnosed with PCOS and their parents. RESULTS: A total of seven adolescents and eight parents participated in two focus groups each. The primary theme from the parent groups was Concerns for Transition to Self-Care with the subthemes of facilitation versus direction and recognition of personal habits. The primary theme identified from the adolescent groups was Taking Control with subthemes of managing symptoms, cognitive dissonance, support, and balance. CONCLUSIONS: Study findings provide insight into the experiences of adolescents with PCOS and their parents as they navigate both a family-level transition in health habits and anticipate the adolescent transition to self-management as an emerging adult. PRACTICE IMPLICATIONS: Nurses and other health care providers can help facilitate transition to self-management among adolescents with PCOS by encouraging increased independence in health behavior decisions while they are still living at home. Middle and older adolescents who begin to take ownership of their physical activity, nutritional choices, and sleep hygiene will have a firm foundation on which to build as they transition into life beyond high school.

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.

Flow Injection-Traveling-Wave Ion Mobility-Mass Spectrometry for Prostate-Cancer Metabolomics.

Flow injection-traveling-wave ion mobility-mass spectrometry (FI-TWIM-MS) was applied to the nontargeted metabolic profiling of serum extracts from 61 prostate-cancer (PCa) patients and 42 controls with an analysis speed of 6 min per sample, including a 3 min wash run. Comprehensive data mining of the mobility-mass domain was used to discriminate species with various charge states and filter matrix salt-cluster ions. Specific criteria were developed to ensure correct grouping of adducts, in-source fragments, and impurities in the data set. Endogenous metabolites were identified with high confidence using FI-TWIM-MS/MS and collision-cross-section (CCS) matching with chemical standards or CCS databases. PCa patient samples were distinguished from control samples with good accuracies (88.3-89.3%), sensitivities (88.5-90.2%), and specificity (88.1%) using supervised multivariate classification methods. Although largely underutilized in metabolomics studies, FI-TWIM-MS proved advantageous in terms of analysis speed, separation of ions in complex mixtures, improved signal-to-noise ratio, and reduction of spectral congestion. Results from this study showcase the potential of FI-TWIM-MS as a high-throughput metabolic-profiling tool for large-scale metabolomics studies.