Targeted and untargeted metabolomics and lipidomics in dried blood microsampling: Recent applications and perspectives.

Blood microsampling (BµS) offers an alternative to conventional methods that use plasma or serum for profiling human health, being minimally invasive and cost effective, especially beneficial for vulnerable populations. We present a non-systematic review that offers a synopsis of the analytical methods, applications and perspectives related to dry blood microsampling in targeted and untargeted metabolomics and lipidomics research in the years 2022 and 2023. BµS shows potential in neonatal and paediatric studies, therapeutic drug monitoring, metabolite screening, biomarker research, sports supervision, clinical disorders studies and forensic toxicology. Notably, dried blood spots and volumetric absorptive microsampling options have been more extensively studied than other volumetric technologies. Therefore, we suggest that a further investigation and application of the volumetric technologies will contribute to the use of BµS as an alternative to conventional methods. Conversely, we support the idea that harmonisation of the analytical methods when using BµS would have a positive impact on its implementation.

SIN-3 transcriptional coregulator maintains mitochondrial homeostasis and polyamine flux.

Mitochondrial function relies on the coordinated transcription of mitochondrial and nuclear genomes to assemble respiratory chain complexes. Across species, the SIN3 coregulator influences mitochondrial functions, but how its loss impacts mitochondrial homeostasis and metabolism in the context of a whole organism is unknown. Exploring this link is important because SIN3 haploinsufficiency causes intellectual disability/autism syndromes and SIN3 plays a role in tumor biology. Here we show that loss of C. elegans SIN-3 results in transcriptional deregulation of mitochondrial- and nuclear-encoded mitochondrial genes, potentially leading to mito-nuclear imbalance. Consistent with impaired mitochondrial function, sin-3 mutants show extensive mitochondrial fragmentation by transmission electron microscopy (TEM) and in vivo imaging, and altered oxygen consumption. Metabolomic analysis of sin-3 mutant animals revealed a mitochondria stress signature and deregulation of methionine flux, resulting in decreased S-adenosyl methionine (SAM) and increased polyamine levels. Our results identify SIN3 as a key regulator of mitochondrial dynamics and metabolic flux, with important implications for human pathologies.

Challenges and perspectives for naming lipids in the context of lipidomics.

INTRODUCTION: Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied. OBJECTIVES: In addition, their structures are varied and complex, which complicates their analysis. Indeed, the structural resolution does not always allow a complete level of annotation so the actual compound analysed will vary from study to study and should be clearly stated. For all these reasons the identification and naming of lipids is complicated and very variable from one study to another, it needs to be harmonized. METHODS & RESULTS: In this position paper we will present and discuss the different way to name lipids (with chemoinformatic and semantic identifiers) and their importance to share lipidomic results. CONCLUSION: Homogenising this identification and adopting the same rules is essential to be able to share data within the community and to map data on functional networks.

APEX: an Annotation Propagation Workflow through Multiple Experimental Networks to Improve the Annotation of New Metabolite Classes in Caenorhabditis elegans.

Spectral similarity networks, also known as molecular networks, are crucial in non-targeted metabolomics to aid identification of unknowns aiming to establish a potential structural relation between different metabolite features. However, too extensive differences in compound structures can lead to separate clusters, complicating annotation. To address this challenge, we developed an automated Annotation Propagation through multiple EXperimental Networks (APEX) workflow, which integrates spectral similarity networks with mass difference networks and homologous series. The incorporation of multiple network tools improved annotation quality, as evidenced by high matching rates of the molecular formula derived by SIRIUS. The selection of manual annotations as the Seed Nodes Set (SNS) significantly influenced APEX annotations, with a higher number of seed nodes enhancing the annotation process. We applied APEX to different Caenorhabditis elegans metabolomics data sets as a proof-of-principle for the effective and comprehensive annotation of glycerophospho N-acyl ethanolamides (GPNAEs) and their glyco-variants. Furthermore, we demonstrated the workflow's applicability to two other, well-described metabolite classes in C. elegans, specifically ascarosides and modular glycosides (MOGLs), using an additional publicly available data set. In summary, the APEX workflow presents a powerful approach for metabolite annotation and identification by leveraging multiple experimental networks. By refining the SNS selection and integrating diverse networks, APEX holds promise for comprehensive annotation in metabolomics research, enabling a deeper understanding of the metabolome.

Volumetric Absorptive Microsampling in the Analysis of Endogenous Metabolites.

Volumetric absorptive microsampling (VAMS) has arisen as a relevant tool in biological analysis, offering simplified sampling procedures and enhanced stability. Most of the attention VAMS has received in the past decade has been from pharmaceutical research, with most of the published work employing VAMS targeting drugs or other exogenous compounds, such as toxins and pollutants. However, biomarker analysis by employing blood microsampling has high promise. Herein, a comprehensive review on the applicability of VAMS devices for the analysis of endogenous metabolites/biomarkers was performed. The study presents a full overview of the analysis process, incorporating all the steps in sample treatment and validation parameters. Overall, VAMS devices have proven to be reliable tools for the analysis of endogenous analytes with biological importance, often offering improved analyte stability in comparison with blood under ambient conditions as well as a convenient and straightforward sample acquisition model.

(Re-)use and (re-)analysis of publicly available metabolomics data.

Metabolomics, the systematic measurement of small molecules (<1000 Da) in a given biological sample, is a fast-growing field with many different applications. In contrast to transcriptomics and proteomics, sharing of data is not as widespread in metabolomics, though more scientists are sharing their data nowadays. However, to improve data analysis tools and develop new data analytical approaches and to improve metabolite annotation and identification, sharing of reference data is crucial. Here, different possibilities to share (metabolomics) data are reviewed and some recent approaches and applications regarding the (re-)use and (re-)analysis are highlighted.

Capillary electrophoresis-mass spectrometry as a tool for Caenorhabditis elegans metabolomics research.

INTRODUCTION: Polar metabolites in Caenorhabditis elegans (C. elegans) have predominantly been analyzed using hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC-MS). Capillary electrophoresis coupled to mass spectrometry (CE-MS) represents another complementary analytical platform suitable for polar and charged analytes. OBJECTIVE: We compared CE-MS and HILIC-MS for the analysis of a set of 60 reference standards relevant for C. elegans and specifically investigated the strengths of CE separation. Furthermore, we employed CE-MS as a complementary analytical approach to study polar metabolites in C. elegans samples, particularly in the context of longevity, in order to address a different part of its metabolome. METHOD: We analyzed 60 reference standards as well as metabolite extracts from C. elegans daf-2 loss-of-function mutants and wild-type (WT) samples using HILIC-MS and CE-MS employing a Q-ToF-MS instrument. RESULTS: CE separations showed narrower peak widths and a better linearity of the estimated response function across different concentrations which is linked to less saturation of the MS signals. Additionally, CE exhibited a distinct selectivity in the separation of compounds compared to HILIC-MS, providing complementary information for the analysis of the target compounds. Analysis of C. elegans metabolites of daf-2 mutants and WT samples revealed significant alterations in shared metabolites identified through HILIC-MS, as well as the presence of distinct metabolites. CONCLUSION: CE-MS was successfully applied in C. elegans metabolomics, being able to recover known as well as identify novel putative biomarkers of longevity.

Venoarterial Extracorporeal Membrane Oxygenation With or Without Advanced Intervention for Massive Pulmonary Embolism.

INTRODUCTION: Massive pulmonary embolism (MPE) is a rare but highly fatal condition. Our study's objective was to evaluate the association between advanced interventions and survival among patients with MPE treated with venoarterial extracorporeal membrane oxygenation (VA-ECMO). METHODS: This is a retrospective review of the Extracorporeal Life Support Organization (ELSO) registry data. We included adult patients with MPE who were treated with VA-ECMO during 2010-2020. Our Primary outcome was survival to hospital discharge; secondary outcomes were ECMO duration among survivors and rates of ECMO-related complications. Clinical variables were compared using the Pearson chi-square and Kruskal-Wallis H tests. RESULTS: We included 802 patients; 80 (10%) received SPE and 18 (2%) received CDT. Overall, 426 (53%) survived to discharge; survival was not significantly different among those treated with SPE or CDT on VA-ECMO (70%) versus VA-ECMO alone (52%) or SPE or CDT before VA-ECMO (52%). Multivariable regression found a trend towards increased survival among those treated with SPE or CDT while on ECMO (AOR 1.8, 95% CI 0.9-3.6), but no significant correlation. There was no association between advanced interventions and ECMO duration among survivors, or rates of ECMO-related complications. CONCLUSION: Our study found no difference in survival in patients with MPE who received advanced interventions prior to ECMO, and a slight non-significant benefit in those who received advanced interventions while on ECMO.

Lipidomic and Metallomic Alteration of Caenorhabditis elegans after Acute and Chronic Manganese, Iron, and Zinc Exposure with a Link to Neurodegenerative Disorders.

Parkinson's disease (PD) progresses with the loss of dopaminergic neurons in the substantia nigra pars compacta region of the brain. The superior mechanisms and the cause of this specific localized neurodegeneration is currently unknown. However, experimental evidence indicates a link between PD progression and reactive oxygen species with imbalanced metal homeostasis. Wild-type Caenorhabditis elegans exposed to redox-active metals was used as the model organism to study cellular response to imbalanced metal homeostasis linked to neurodegenerative diseases. Using modern hyphenated techniques such as capillary electrophoresis coupled to inductively coupled plasma mass spectrometry and ultrahigh-performance liquid chromatography mass spectrometry, alterations in the lipidome and metallome were determined in vivo. In contrast to iron, most of the absorbed zinc and manganese were loosely bound. We observed changes in the phospholipid composition for acute iron and manganese exposures, as well as chronic zinc exposure. Furthermore, we focused on the mitochondrial membrane alteration due to its importance in neuronal function. However, significant changes in the inner mitochondrial membrane by determination of cardiolipin species could only be observed for acute iron exposure. These results indicate different intracellular sites of local ROS generation, depending on the redox active metal. Our study combines metallomic and lipidomic alterations as the cause and consequence to enlighten intracellular mechanisms in vivo, associated with PD progression. The mass spectrometry raw data have been deposited to the MassIVE database (https://massive.ucsd.edu) with the identifier MSV000090796 and 10.25345/C51J97C8F.

Providing metabolomics education and training: pedagogy and considerations.

BACKGROUND: Metabolomics is a highly multidisciplinary and non-standardised research field. Metabolomics researchers must possess and apply extensive cross-disciplinary content knowledge, subjective experience-based judgement, and the associated diverse skill sets. Accordingly, appropriate educational and training initiatives are important in developing this knowledge and skills base in the metabolomics community. For these initiatives to be successful, they must consider both pedagogical best practice and metabolomics-specific contextual challenges. AIM OF REVIEW: The aim of this review is to provide consolidated pedagogical guidance for educators and trainers in metabolomics educational and training programmes. KEY SCIENTIFIC CONCEPTS OF REVIEW: In this review, we discuss the principles of pedagogical best practice as they relate to metabolomics. We then discuss the challenges and considerations in developing and delivering education and training in metabolomics. Finally, we present examples from our own teaching practice to illustrate how pedagogical best practice can be integrated into metabolomics education and training programmes.

Critical assessment of chromatographic metadata in publicly available metabolomics data repositories.

INTRODUCTION: The structural identification of metabolites represents one of the current bottlenecks in non-targeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics. The Metabolomics Standard Initiative has developed a multilevel system to report confidence in metabolite identification, which involves the use of MS, MS/MS and orthogonal data. Limitations due to similar or same fragmentation pattern (e.g. isomeric compounds) can be overcome by the additional orthogonal information of the retention time (RT), since it is a system property that is different for each chromatographic setup. OBJECTIVES: In contrast to MS data, sharing of RT data is not as widespread. The quality of data and its (re-)useability depend very much on the quality of the metadata. We aimed to evaluate the coverage and quality of this metadata from public metabolomics repositories. METHODS: We acquired an overview on the current reporting of chromatographic separation conditions. For this purpose, we defined the following information as important details that have to be provided: column name and dimension, flow rate, temperature, composition of eluents and gradient. RESULTS: We found that 70% of descriptions of the chromatographic setups are incomplete (according to our definition) and an additional 10% of the descriptions contained ambiguous and/or incorrect information. Accordingly, only about 20% of the descriptions allow further (re-)use of the data, e.g. for RT prediction. Therefore, we have started to develop a unified and standardized notation for chromatographic metadata with detailed and specific description of eluents, columns and gradients. CONCLUSION: Reporting of chromatographic metadata is currently not unified. Our recommended suggestions for metadata reporting will enable more standardization and automatization in future reporting.

Anteroposterior pacer pad position is better than anterolateral for transcutaneous cardiac pacing.

INTRODUCTION: Transcutaneous cardiac pacing (TCP) is a lifesaving procedure for patients with certain types of unstable bradycardia. We aimed to assess the difference in the pacing thresholds between the anteroposterior (AP) and anterolateral (AL) pacer pad positions. The second aim was to characterize the severity of chest wall muscle contractions during TCP. METHODS: In this prospective crossover trial, we enrolled patients presenting to the electrophysiology laboratory for elective cardioversion. After successful cardioversion, sedated participants were sequentially paced in both positions. The study procedure concluded after successful capture or inability to achieve capture by 140 mA (the pacer's maximum output) in both positions. Pacing thresholds were compared between positions, using a student's paired t-test, assigning a value of 141 mA to any trials with non-capture. RESULTS: Forty-one patients were screened; 20 were enrolled in the study. Seven participants were excluded from the paired analysis (three were prevented from pacing in the second position at the anesthesiologist's discretion, and 4 did not capture in either position). The study population consisted of 14 men and 6 women with a median age of 65 years. The mean pacing threshold was 33 mA lower (P = 0.001, 95% CI 20-45) in the AP (93 mA) versus the AL (126 mA) position. The median contraction severity score was 3 in the AL position versus 4 in the AP position (P = 0.005). CONCLUSIONS: Placing pacer pads in the AP position requires less energy to capture. Major resuscitation guidelines may favor the AP position for TCP. CLINICALTRIALS: gov Identifier: NCT03898050 https://clinicaltrials.gov/ct2/show/NCT03898050.

WHEN AND HOW TO USE ORTHOSTATIC VITAL SIGNS.

BACKGROUND: Much controversy surrounds the use of orthostatic vital signs (OVS), including their indications, performance, and interpretation. This can lead to conflict between nurses, physicians, and consultants. This article summarizes the evidence for OVS in selected emergency department (ED) indications and the basis for a rapid measurement protocol. OBJECTIVE: This narrative review is intended to clarify indications for OVS measurement, their performance, and interpretation. DISCUSSION: Phlebotomy studies indicate that OVS are more discriminating than supine vital signs in hypovolemia, but many findings, even some considered "positive," do not provide compelling evidence in favor of or against disease. Evaluated as a diagnostic test, they have a low yield and controversial criteria for a positive test, but as vital signs, they are useful for selected patients with frequent ED presentations-blood loss, dehydration, dizziness, weakness, and falls. Available evidence supports a rapid measurement protocol, including a 1-min interval after standing. CONCLUSION: OVS are useful in selected patients, in a variety of frequent presentations, but their indications and implications for a patient's care are subject to physician interpretation. Given their ease of measurement and effect on decision-making, physicians may consider measuring them early in the evaluation of selected patients.

Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management.

BACKGROUND: Demonstrating that the data produced in metabolic phenotyping investigations (metabolomics/metabonomics) is of good quality is increasingly seen as a key factor in gaining acceptance for the results of such studies. The use of established quality control (QC) protocols, including appropriate QC samples, is an important and evolving aspect of this process. However, inadequate or incorrect reporting of the QA/QC procedures followed in the study may lead to misinterpretation or overemphasis of the findings and prevent future metanalysis of the body of work. OBJECTIVE: The aim of this guidance is to provide researchers with a framework that encourages them to describe quality assessment and quality control procedures and outcomes in mass spectrometry and nuclear magnetic resonance spectroscopy-based methods in untargeted metabolomics, with a focus on reporting on QC samples in sufficient detail for them to be understood, trusted and replicated. There is no intent to be proscriptive with regard to analytical best practices; rather, guidance for reporting QA/QC procedures is suggested. A template that can be completed as studies progress to ensure that relevant data is collected, and further documents, are provided as on-line resources. KEY REPORTING PRACTICES: Multiple topics should be considered when reporting QA/QC protocols and outcomes for metabolic phenotyping data. Coverage should include the role(s), sources, types, preparation and uses of the QC materials and samples generally employed in the generation of metabolomic data. Details such as sample matrices and sample preparation, the use of test mixtures and system suitability tests, blanks and technique-specific factors are considered and methods for reporting are discussed, including the importance of reporting the acceptance criteria for the QCs. To this end, the reporting of the QC samples and results are considered at two levels of detail: "minimal" and "best reporting practice" levels.

MobilityTransformR: an R package for effective mobility transformation of CE-MS data.

SUMMARY: We present MobilityTransformR, an R/Bioconductor package for the effective mobility scaling of capillary zone electrophoresis-mass spectrometry (CE-MS) data. It uses functionality from different R packages that are frequently used for data processing and analysis in MS-based metabolomics workflows, allowing the subsequent use of reproducible transformed CE-MS data in existing workflows. AVAILABILITY AND IMPLEMENTATION: MobilityTransformR is implemented in R (Version >= 4.2) and can be downloaded directly from the Bioconductor database (https://bioconductor.org/packages/MobilityTransformR) or GitHub (https://github.com/LiesaSalzer/MobilityTransformR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics.

The extraction of meaningful biological knowledge from high-throughput mass spectrometry data relies on limiting false discoveries to a manageable amount. For targeted approaches in metabolomics a main challenge is the detection of false positive metabolic features in the low signal-to-noise ranges of data-independent acquisition results and their filtering. Another factor is that the creation of assay libraries for data-independent acquisition analysis and the processing of extracted ion chromatograms have not been automated in metabolomics. Here we present a fully automated open-source workflow for high-throughput metabolomics that combines data-dependent and data-independent acquisition for library generation, analysis, and statistical validation, with rigorous control of the false-discovery rate while matching manual analysis regarding quantification accuracy. Using an experimentally specific data-dependent acquisition library based on reference substances allows for accurate identification of compounds and markers from data-independent acquisition data in low concentrations, facilitating biomarker quantification.

Networks and Graphs Discovery in Metabolomics Data Analysis and Interpretation.

Both targeted and untargeted mass spectrometry-based metabolomics approaches are used to understand the metabolic processes taking place in various organisms, from prokaryotes, plants, fungi to animals and humans. Untargeted approaches allow to detect as many metabolites as possible at once, identify unexpected metabolic changes, and characterize novel metabolites in biological samples. However, the identification of metabolites and the biological interpretation of such large and complex datasets remain challenging. One approach to address these challenges is considering that metabolites are connected through informative relationships. Such relationships can be formalized as networks, where the nodes correspond to the metabolites or features (when there is no or only partial identification), and edges connect nodes if the corresponding metabolites are related. Several networks can be built from a single dataset (or a list of metabolites), where each network represents different relationships, such as statistical (correlated metabolites), biochemical (known or putative substrates and products of reactions), or chemical (structural similarities, ontological relations). Once these networks are built, they can subsequently be mined using algorithms from network (or graph) theory to gain insights into metabolism. For instance, we can connect metabolites based on prior knowledge on enzymatic reactions, then provide suggestions for potential metabolite identifications, or detect clusters of co-regulated metabolites. In this review, we first aim at settling a nomenclature and formalism to avoid confusion when referring to different networks used in the field of metabolomics. Then, we present the state of the art of network-based methods for mass spectrometry-based metabolomics data analysis, as well as future developments expected in this area. We cover the use of networks applications using biochemical reactions, mass spectrometry features, chemical structural similarities, and correlations between metabolites. We also describe the application of knowledge networks such as metabolic reaction networks. Finally, we discuss the possibility of combining different networks to analyze and interpret them simultaneously.