Bo Burla, Makoto Arita, Masanori Arita, Anne K. Bendt, Amaury Cazenave-Gassiot, Edward A. Dennis, Kim Ekroos, Xianlin Han, Kazutaka Ikeda, Gerhard Liebisch, Michelle K. Lin, Tze Ping Loh, Peter J. Meikle, Matej Orešič, Oswald Quehenberger, Andrej Shevchenko, Federico Torta, Michael J. O. Wakelam, Craig E. Wheelock, Markus R. Wenk

• Overview of current state of mass spectrometry based lipidomics. • Highlighting ongoing efforts towards harmonization. • Invitation to join international community.

Background: Tuberculosis (TB) is the ninth leading cause of death worldwide and the leading cause from a single infectious agent, based on the WHO Global Tuberculosis Report in 2017. TB causes massive health care burdens in many parts of the world, specifically in the resource constrained developing world. Most deaths from TB could be prevented with cost effective early diagnosis and appropriate treatment. Purpose: Conventional TB detection methods are either too slow as it takes a few weeks for diagnosis or they lack the specificity and accuracy. Thus the objective of this study was to develop a fast and efficient detection for TB using surface enhanced Raman scattering (SERS) technique. Methods: SERS spectra for different forms of mycolic acids (MAs) that are both synthetic origin and actual extracts from the mycobacteria species were obtained by label-free direct detection mode. Similarly, we collected SERS spectra for γ-irradiated whole bacteria (WB). Measurements were done using silver (Ag) coated silicon nanopillar (Ag SNP) as SERS substrate. Results: We report the SERS based detection of MA, which is a biomarker for mycobacteria species including Mycobacterium tuberculosis. For the first time, we also establish the SERS spectral characterization of the three major forms of MA – αMA, methoxy-MA, and keto-MA, in bacterial extracts and also in γ-irradiated WB. We validated our findings by mass spectrometry. SERS detection of these three forms of MA could be useful in differentiating pathogenic and nonpathogenic Mycobacterium spp. Conclusions: We have demonstrated the direct detection of three major forms of MA – αMA, methoxy-MA, and keto-MA, in two different types of MA extracts from MTB bacteria, namely delipidated MA and undelipidated MA and finally in γ-irradiated WB. In the near future, this study could pave the way for a fast and efficient detection method for TB, which is of high clinical significance.

Human pathologies are complex and might benefit from a more holistic diagnostic approach than currently practiced. Omics is a concept in biological research that aims to comprehensively characterize and quantify large numbers of biological molecules in complex samples, e.g., proteins (proteomics), low molecular weight molecules (metabolomics), glycans (glycomics) or amphiphilic molecules (lipidomics). Over the past decades, respective unbiased discovery approaches have been intensively applied to investigate functional physiological and pathophysiological relationships in various research study cohorts. In the context of clinical diagnostics, omics approaches seem to have potential in two main areas: (i) biomarker discovery i.e. identification of individual marker analytes for subsequent translation into diagnostics (as classical target analyses with conventional laboratory techniques), and (ii) the readout of complex, higher-dimensional signatures of diagnostic samples, in particular by means of spectrometric techniques in combination with biomathematical approaches of pattern recognition and artificial intelligence for diagnostic classification. Resulting diagnostic methods could potentially represent a disruptive paradigm shift away from current one-dimensional (i.e., single analyte marker based) laboratory diagnostics. The underlying hypothesis of omics approaches for diagnostics is that complex, multigenic pathologies can be more accurately diagnosed via the readout of “omics-type signatures” than with the current one-dimensional single marker diagnostic procedures. While this is indeed promising, one must realize that the clinical translation of high-dimensional analytical procedures into routine diagnostics brings completely new challenges with respect to long-term reproducibility and analytical standardization, data management, and quality assurance. In this article, the conceivable opportunities and challenges of omics-based laboratory diagnostics are discussed.

Lipids in breastmilk play a critical role in infant growth and development. However, few studies have investigated sources of variability of both high- and low-abundant milk lipids. The objective of our study was to investigate individual and morning–evening differences in the human milk lipidome. In this study, a modified two-phase method (MTBE: Methanol 7:2) was validated for the extraction of lipids from human breastmilk. This method was then applied to samples from a group of 20 healthy women to measure inter- and intra-individual (morning versus evening) variability of the breastmilk lipidome. We report here the levels of 237 lipid species from 13 sub-classes using reversed-phase liquid chromatography mass spectrometry (RP-LCMS) and direct-infusion mass spectrometry (DI-MS). About 85% of lipid species showed stable inter-individual differences across time points. Half of lipid species showed higher concentrations in the evening compared with the morning, with phosphatidylethanolamines (PEs) and triacylglycerols (TAGs) exhibiting the largest changes. In morning and evening samples, the biological variation was greater for diacylglycerols (DAGs) and TAGs compared with phospholipids and sphingolipids, and the variation in DAGs and TAGs was greater in evening samples compared with morning samples. These results demonstrate that variation in the milk lipidome is strongly influenced by individual differences and time of day.

Objectives: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. Methods: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. Results: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. Conclusions: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.