Small molecules play critical roles in life science, yet their facile detection and imaging in physiological or pathological settings remain a challenge. Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) is a powerful tool for molecular analysis. However, conventional organic matrices (CHCA, DHB, etc.) used in assisting analyte ionization suffer from intensive background noise in the mass region below m/z 700, which hinders MALDI MS applications for small-molecule detection. Here, we report that a hydroxyl-group-dominated graphite dot (GD) matrix overcomes limitations of conventional matrices and allows MALDI MS to be used in fast and high-throughput analysis of small biomolecules. GDs exhibit extremely low background noise and ultrahigh sensitivity (with limit of detection <1 fmol) in MALDI MS. This approach allows identification of complex oligosaccharides, detection of low-molecular-weight components in traditional Chinese herbs, and facile analysis of puerarin and its metabolites in serum without purification. Moreover, we show that the GDs provide an effective matrix for the direct imaging or spatiotemporal mapping of small molecules and their metabolites (m/z < 700) simultaneously at the suborgan tissue level. Density functional theory calculations further provide the mechanistic basis of GDs as an effective MALDI matrix in both the positive-ion and negative-ion modes. Collectively, our work uncovered a useful matrix which reshapes MALDI MS technology for a wide range of applications in biology and medicine.

Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.

There is a great need to develop sensitive and specific methods for quantitative analysis of caspase-3 activities in cell apoptosis.