This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via ¹³C/¹⁵N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled ¹³C and ¹⁵N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

Reptiles rely on hibernation to survive harsh winters, but climate change and pesticide use in agriculture jeopardize their survival, making the ecosystem vulnerable. S-metolachlor (SM), a commonly found herbicide in soil, and its metabolite metolachlor oxanilic acid (MO) induce oxidative stress and disrupt reproductive hormones. In this study, lizards were exposed to SM- and MO-contaminated soil for 45 days during hibernation. Weight loss and deaths occurred at the beginning of hibernation in all groups. Furthermore, the exposure group experienced severe oxidative stress and damage in the liver, kidney, heart, gonad, and brain. The testosterone levels significantly decreased in male lizards in both the SM and MO groups, whereas estradiol levels increased significantly in female lizards in the SM group. Gender-specific expression of steroidogenic-related genes in the brains and gonads of lizards was observed. Histological analysis revealed toxic effects induced by both SM and MO in vital organs during hibernation. Moreover, MO induced more severe reproductive toxicity in male lizards during hibernation. Therefore, this study suggests gender-specific toxic effects were observed in hibernating lizards exposed to SM and MO, underscoring the importance of vigilant monitoring of pesticide application in agriculture and assessing the potential harm of its metabolites.