Bio- and Chemoinformatic Approaches for Metabolomics Data Analysis.

Metabolomics data analysis includes, next to the preprocessing, several additional repetitive tasks that can however be heavily dataset dependent or experiment setup specific due to the vast heterogeneity in instrumentation, protocols, or also compounds/samples that are being measured. To address this, various toolboxes and software packages in Python or R have been and are being developed providing researchers and analysts with bioinformatic/chemoinformatic tools to create their own workflows tailored toward their specific needs. This chapter presents tools and example workflows for common tasks focusing on the functionality provided by R packages developed as part of the RforMassSpectrometry initiative.

Differential Mobility Spectrometry-Based Cardiolipin Analysis.

Cardiolipins (CL) are special lipids in many respects. First of all, CL are composed of four fatty acids linked by two phosphatidic acids, which provide CL a unique molecular structure. Secondly, in eukaryotic cells they are specific to a single organelle, mitochondria, where they are also synthetized.

Navigating common pitfalls in metabolite identification and metabolomics bioinformatics.

Background: Metabolomics, the systematic analysis of small molecules in a given biological system, emerged as a powerful tool for different research questions. Newer, better, and faster methods have increased the coverage of metabolites that can be detected and identified in a shorter amount of time, generating highly dense datasets. While technology for metabolomics is still advancing, another rapidly growing field is metabolomics data analysis including metabolite identification.

Dipeptide metabolite, glutamyl-glutamate mediates microbe-host interaction to boost spermatogenesis.

The decrease in sperm count and infertility is a global issue that remains unresolved. By screening environmental bacterial isolates, we have found that a novel lactic acid bacterium, Lactiplantibacillus plantarum SNI3, increased testis size, testosterone levels, sperm count, sexual activity and fertility in mice that have consumed the bacteria for four weeks. The abundance of L.

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.

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 haploinsufficiency causes intellectual disability/autism syndromes and SIN3 plays a role in tumor biology.

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.

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

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.

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.

(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.

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.

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.

In-situ investigation of solid phase evolution during lyophilization of mannitol-based antibody formulations using an XRPD climate chamber.

Crystalline mannitol is commonly used as bulking agent in antibody formulations to provide structure to the lyophilized cake and prevent collapse. Depending on the lyophilization process conditions mannitol can either crystallize as α-, β-, δ-mannitol, mannitol-hemihydrate, or transition to its amorphous state. While crystalline mannitol helps to create a firmer cake structure this is not true for amorphous mannitol.

Lipidomic and Metallomic Alteration of 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.

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.

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.

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.

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.

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.

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.

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.