Biological mass spectrometry enables spatiotemporal ‘omics: From tissues to cells to organelles

Abstract

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space‐time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever‐deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community‐wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space‐time.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

“…It proficiently demonstrates TEMPOmap’s capability to trace the subcellular distribution and cytoplasmic translocation of transcripts over time, thereby providing a comprehensive insight into RNA subcellular dynamics at the single-cell level. Moreover, the observed strong correlation between the dynamic patterns of RNA and the molecular function of genes suggests that a functionally driven regulation of the RNA lifecycle has likely evolved to manage spatiotemporal gene expression with both precision and efficiency [ 82 ]. The validation of TEMPOmap was conducted across various cell types, including human induced pluripotent stem cell-derived cell cultures and primary cell cultures.…”

“…Traditional proteomic analyses of bulk tissues often fail to the spatial distribution and cellular specificity due to tissue homogenization, resulting in merely an average representation of protein expression levels in the mass spectrometry signal [ 82 ]. Conversely, advanced spatial proteomics provides a precise delineation of protein expression profiles across varied cells and tissue regions [ 83 ].…”

Dilute to Enrich for Deeper Proteomics: A Yolk-Depleted Carrier for Limited Populations of Embryonic (Frog) Cells

“…14 As discussed earlier, these abundant yolk contaminants hamper proteome coverage. Another difficulty with the approach of physical depletion is due to the manual finesse that is necessary to scale to limited proteomes, such as developing single cells and cell lineages in X. laevis (partially reviewed in the literature 53 ). For a tissue equivalent to ∼5% of the embryo, which estimates to the D11 and V11 lineage we target in this study, the yolk platelet was barely visible after sucrose centrifugation (Figure S1), a step necessary for yolk depletion in high fidelity.…”

“…Further, in developing organisms, like the (X. laevis) embryos studied here, active proteome reorganization presents an opportunity to specifically tailor the depleted carrier proteome to the specimen with spatiotemporal resolution. 53 Pooling of tissues over multiple developmental stages to prepare the depleted carrier provides a simple solution to help adjust the YODEC carrier proteome. It also holds the potential to advance the study of posttranslational modifications from limited samples by permitting enrichment for targeted modifications in the carrier proteome.…”

Editorial: Methods in Metabolomics 2022

“…This can reduce differences in matrix effects across samples and aid in compound annotation. In recent years, the spatial distribution of metabolites has gained importance as an alternative dimension of separation (Pade et al, 2023). Two articles in this issue demonstrate such potential and show ways to reduce the impact of matrix effects (Molenaar et al) and to improve the annotation of detected compounds (Lukowski et al).Generally, metabolomics experiments include three main steps: Sample preparation, data acquisition, and data analysis.…”