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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. 

Abstract Neuropeptides have tremendous potential for application in modern medicine, including utility as biomarkers and therapeutics. To overcome the inherent challenges associated with neuropeptide identification and characterization, data‐independent acquisition (DIA) is a fitting mass spectrometry (MS) method of choice to achieve sensitive and accurate analysis. It is advantageous for preliminary neuropeptidomic studies to occur in less complex organisms, with crustacean models serving as a popular choice due to their relatively simple nervous system. With spectral libraries serving as a means to interpret DIA‐MS output spectra, andCancer borealisas a model of choice for neuropeptide analysis, we performed the first spectral library mapping of crustacean neuropeptides. Leveraging pre‐existing data‐dependent acquisition (DDA) spectra, a spectral library was built using PEAKS Online. The library is comprised of 333 unique neuropeptides. The identification results obtained through the use of this spectral library were compared with those achieved through library‐free analysis of crustacean brain, pericardial organs (PO), and thoracic ganglia (TG) tissues. A statistically significant increase (Student'st‐test,Pvalue < 0.05) in the number of identifications achieved from the TG data was observed in the spectral library results. Furthermore, in each of the tissues, a distinctly different set of identifications was found in the library search compared to the library‐free search. This work highlights the necessity for the use of spectral libraries in neuropeptide analysis, illustrating the advantage of spectral libraries for interpreting DIA spectra in a reproducible manner with greater neuropeptidomic depth. 

Neuropeptides are important signaling molecules responsible for a wide range of functions within the nervous and neuroendocrine system. However, they are difficult to study due to numerous challenges, most notably their large degree of variability and low abundance in vivo . As a result, effective separation methods with sensitive detection capabilities are necessary for profiling neuropeptides in tissue samples, particularly those of simplified model organisms such as crustaceans. In order to address these challenges, this study utilized a capillary electrophoresis (CE)-matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) platform, building upon our previous design for improved neuropeptidomic coverage. The capillary was coated with polyethylenimine (PEI) to reduce peptide adsorption and reverse the electroosmotic flow, and large volume sample stacking (LVSS) was used to load and pre-concentrate 1 μL of sample. The method demonstrated good reproducibility, with lower than 5% relative standard deviation for standards, and a limit of detection of approximately 100 pM for an allatostatin III peptide standard. The method was tested on brain and sinus gland (SG) tissue extracts and enabled detection of over 200 neuropeptides per run. When comparing the number detected in brain extracts in a direct spot, 60-second fractions, and 30-second fractions, the continuous trace collection afforded by the CE-MALDI-MSI platform yielded the largest number of detected neuropeptides. The method was compared to conventional LC-ESI-MS, and though the number of neuropeptides detected by LC-ESI-MS was slightly larger, the two methods were highly complementary, indicating the potential for the CE-MALDI-MSI method to uncover previously undetected neuropeptides in the crustacean nervous system. These results indicate the potential of CE-MALDI-MSI for routine use in neuropeptide research.