High-Resolution Mass Spectrometry Quantification: Impact of Differences in Data Processing of Centroid and Continuum Data

Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data

Liquid chromatography coupled with high-resolution mass spectrometry data-independent acquisition (LC-HRMS/DIA), including MSE, enable comprehensive metabolomics analyses though they pose challenges for data processing with automatic annotation and molecular networking (MN) implementation. This motivated the present proposal, in which we introduce DIA-IntOpenStream, a new integrated workflow combining open-source software to streamline MSE data handling. It provides 'in-house' custom database construction, allows the conversion of raw MSE data to a universal format (.mzML) and leverages open software (MZmine 3 and MS-DIAL) all advantages for confident annotation and effective MN data interpretation. This pipeline significantly enhances the accessibility, reliability and reproducibility of complex MSE/DIA studies, overcoming previous limitations of proprietary software and non-universal MS data formats that restricted integrative analysis. We demonstrate the utility of DIA-IntOpenStream with two independent datasets: dataset 1 consists of new data from 60 plant extracts from the Ocotea genus; dataset 2 is a publicly available actinobacterial extract spiked with authentic standard for detailed comparative analysis with existing methods. This user-friendly pipeline enables broader adoption of cutting-edge MS tools and provides value to the scientific community. Overall, it holds promise for speeding up metabolite discoveries toward a more collaborative and open environment for research.

Eight key rules for successful data-dependent acquisition in mass spectrometry-based metabolomics

In recent years, metabolomics has emerged as a pivotal approach for the holistic analysis of metabolites in biological systems. The rapid progress in analytical equipment, coupled to the rise of powerful data processing tools, now provides unprecedented opportunities to deepen our understanding of the relationships between biochemical processes and physiological or phenotypic conditions in living organisms. However, to obtain unbiased data coverage of hundreds or thousands of metabolites remains a challenging task. Among the panel of available analytical methods, targeted and untargeted mass spectrometry approaches are among the most commonly used. While targeted metabolomics usually relies on multiple-reaction monitoring acquisition, untargeted metabolomics use either data-independent acquisition (DIA) or data-dependent acquisition (DDA) methods. Unlike DIA, DDA offers the possibility to get real, selective MS/MS spectra and thus to improve metabolite assignment when performing untargeted metabolomics. Yet, DDA settings are more complex to establish than DIA settings, and as a result, DDA is more prone to errors in method development and application. Here, we present a tutorial which provides guidelines on how to optimize the technical parameters essential for proper DDA experiments in metabolomics applications. This tutorial is organized as a series of rules describing the impact of the different parameters on data acquisition and data quality. It is primarily intended to metabolomics users and mass spectrometrists that wish to acquire both theoretical background and practical tips for developing effective DDA methods.

A circular network of purine metabolism as coregulators of dilated cardiomyopathy

BACKGROUND

The crosstalk of purine biosynthesis and metabolism exists to balance the cell energy production, proliferation, survival and cytoplasmic environment stability, but disorganized mechanics of with respect to developing heart failure (HF) is currently unknown.

METHODS

We conducted a multi-omics wide analysis, including microarray-based transcriptomes, and full spectrum metabolomics with respect to chronic HF. Based on expression profiling by array, we applied a bioinformatics platform of quantifiable metabolic pathway changes based on gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), Shapley Additive Explanations (SHAP), and Xtreme Gradient Boosting (XGBoost) algorithms to comprehensively analyze the dynamic changes of metabolic pathways and circular network in the HF development. Additionally, left ventricular tissue from patients undergoing myocardial biopsy and transplantation were collected to perform the protein and full spectrum metabolic mass spectrometry.

RESULTS

Systematic bioinformatics analysis showed the purine metabolism reprogramming was significantly detected in dilated cardiomyopathy. In addition, this result was also demonstrated in metabolomic mass spectrometry. And the differentially expressed metabolites analysis showing the guanine, urea, and xanthine were significantly detected. Hub markers, includes IMPDH1, ENTPD2, AK7, AK2, and CANT1, also significantly identified based on XGBoost, SHAP model and PPI network.

CONCLUSION

The crosstalk in the reactions involved in purine metabolism may involving in DCM metabolism reprogramming, and as coregulators of development of HF, which may identify as potential therapeutic targets. And the markers of IMPDH1, ENTPD2, AK7, AK2, and CANT1, and metabolites involved in purine metabolism shown an important role.

Systematic Investigation of LC Miniaturization to Increase Sensitivity in Wide-Target LC-MS-Based Trace Bioanalysis of Small Molecules

Covering a wide spectrum of molecules is essential for global metabolome assessment. While metabolomics assays are most frequently carried out in microbore LC-MS analysis, reducing the size of the analytical platform has proven its ability to boost sensitivity for specific -omics applications. In this study, we elaborate the impact of LC miniaturization on exploratory small-molecule LC-MS analysis, focusing on chromatographic properties with critical impact on peak picking and statistical analysis. We have assessed a panel of small molecules comprising endogenous metabolites and environmental contaminants covering three flow regimes—analytical, micro-, and nano-flow. Miniaturization to the micro-flow regime yields moderately increased sensitivity as compared to the nano setup, where median sensitivity gains around 80-fold are observed in protein-precipitated blood plasma extract. This gain resulting in higher coverage at low µg/L concentrations is compound dependent. At the same time, the nano-LC-high-resolution mass spectrometry (HRMS) approach reduces the investigated chemical space as a consequence of the trap-and-elute nano-LC platform. Finally, while all three setups show excellent retention time stabilities, rapid gradients jeopardize the peak area repeatability of the nano-LC setup. Micro-LC offers the best compromise between improving signal intensity and metabolome coverage, despite the fact that only incremental gains can be achieved. Hence, we recommend using micro-LC for wide-target small-molecule trace bioanalysis and global metabolomics of abundant samples.

Targeted and untargeted characterization of underivatized policosanols in hemp inflorescence by liquid chromatography-high resolution mass spectrometry

The paper describes the development of a targeted quantitative method for the analysis of policosanols in hemp inflorescence. Policosanols are long chain aliphatic alcohols, with carbon chains typically in the range 20-36, with interesting biological activities. These compounds are typically separated by gas chromatography and only a few methods employ liquid chromatography for policosanols. In both cases, methods always include the derivatization of policosanols. In this study, policosanols were separated by ultra-high performance liquid chromatography without any derivatization and detected using high resolution mass spectrometry by formation of lithiated adducts. The procedure was optimized and a quantitative method was validated for the most abundant policosanols (with C24, C26, C27, C28, and C30 chain lengths) in industrial hemp inflorescence extracts. The method was used for the quantitative analysis of policosanols in five hemp types. Hemp wax was found rich in these compounds, especially C26 and C28 policosanols, which may prove useful for revalorization of wax by-products. Finally, the acquired data were also used to expand the search to the untargeted qualitative analysis of policosanols using Compound Discoverer. The untargeted method allowed the annotation of underivatized policosanols up to C33.

2020 White Paper on Recent Issues in Bioanalysis: BMV of Hybrid Assays, Acoustic MS, HRMS, Data Integrity, Endogenous Compounds, Microsampling and Microbiome (Part 1 - Recommendations on Industry/Regulators Consensus on BMV of Biotherapeutics by LCMS, Advanced Application in Hybrid Assays, Regulatory Challenges in Mass Spec, Innovation in Small Molecules, Peptides and Oligos)

The 14^th edition of the Workshop on Recent Issues in Bioanalysis (14^th WRIB) was held virtually on June 15-29, 2020 with an attendance of over 1000 representatives from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations, and regulatory agencies worldwide. The 14^th WRIB included three Main Workshops, seven Specialized Workshops that together spanned 11 days in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccine. Moreover, a comprehensive vaccine assays track; an enhanced cytometry track and updated Industry/Regulators consensus on BMV of biotherapeutics by Mass Spectrometry (hybrid assays, LCMS and HRMS) were special features in 2020. As in previous years, this year's WRIB continued to gather a wide diversity of international industry opinion leaders and regulatory authority experts working on both small and large molecules to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance and achieving scientific excellence on bioanalytical issues. This 2020 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the Global Bioanalytical Community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2020 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication covers the recommendations on (Part 1) Hybrid Assays, Innovation in Small Molecules, & Regulated Bioanalysis. Part 2A (BAV, PK LBA, Flow Cytometry Validation and Cytometry Innovation), Part 2B (Regulatory Input) and Part 3 (Vaccine, Gene/Cell Therapy, NAb Harmonization and Immunogenicity) are published in volume 13 of Bioanalysis, issues 5, and 6 (2021), respectively.

The use of UHPLC, IMS, and HRMS in multiresidue analytical methods: A critical review

Residue chemists who analyse pesticides in vegetables or veterinary drugs in animal-based food are currently facing a situation where there is a requirement to detect more and more compounds at lower and lower concentrations. Conventional tandem quadrupole instruments provide sufficient sensitivity, but speed and selectivity appear as future limitations. This will become an even larger issue when there is a need to not only detect active compounds but also their degradation products and metabolites. This will likely lead to a situation in which the conventional targeted approach must be expanded or augmented by a certain non-targeted strategy. High-resolution mass spectrometry provides such capabilities, but it frequently requires an additional degree of selectivity for the unequivocal confirmation of analytes present at trace levels in highly complex and variable food matrices. The hyphenation of ultrahigh performance liquid chromatography with ion mobility and high-resolution mass spectrometry provides analytical chemists with a new tool for performing such a demanding multiresidue analysis. The objective of this paper is to investigate the benefits of the added ion mobility dimension as well as to critically discuss the current limitations of this commercially available technology.

High-resolution mass spectrometry for bioanalytical applications: Is this the new gold standard?

Liquid chromatography coupled to quadrupole-based tandem mass spectrometry (QqQ) is termed the "gold standard" for bioanalytical applications because of its unpreceded selectivity, sensitivity, and the ruggedness of the technology. More recently, however, high-resolution mass spectrometry (HRMS) has become increasingly popular for bioanalytical applications. Nonetheless, this technique is still viewed, either as a screening technology or as a research tool. Although HRMS is actively discussed during scientific conferences, it is yet to be widely utilised in routine laboratory settings and there remains a reluctance to use HRMS for quantitative measurements in regulated environments. This paper does not aim to comprehensively describe the potential of the latest HRMS technology, but rather, it focuses on what results can be obtained and outlines the author's experiences over a period of many years of the routine application of various forms of HRMS instrumentation. Fifteen years ago, some nine different QqQ methods were used in the author's laboratory to analyse a variety of different veterinary drug resides. Today, many more analytes are quantified by seven HRMS methods and just three QqQ methods remain in use for the analysis of a small set of compounds yet to be upgraded to HRMS analysis. This continual upgrading and migration of analytical methods were accompanied by regularly participating in laboratory proficiency tests (PTs). The PT reports (covering a range of analytes and analytical methods) were used to compare the accuracy of HRMS- versus QqQ-based measurements. In the second part of this paper, the particular strengths and limitations of HRMS for both method development and routine measurements are critically discussed. This also includes some anecdotal experiences encountered when replacing QqQ assays with HRMS methods.

Current developments in LC-MS for pharmaceutical analysis

Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades.

Metabolomics Data Processing Using XCMS

XCMS is one of the most used software for liquid chromatography-mass spectrometry (LC-MS) data processing and it exists both as an R package and as a cloud-based platform known as XCMS Online. In this chapter, we first overview the nature of LC-MS data to contextualize the need for data processing software. Next, we describe the algorithms used by XCMS and the role that the different user-defined parameters play in the data processing. Finally, we describe the extended capabilities of XCMS Online.