Data-Dependent Acquisition Ladder for Capillary Electrophoresis Mass Spectrometry-Based Ultrasensitive (Neuro)Proteomics

Proteomics revealed composition- and size-related regulators for hepatic impairments induced by silica nanoparticles

Along with the growing production and application of silica nanoparticles (SiNPs), increased human exposure and ensuing safety evaluation have progressively attracted concern. Accumulative data evidenced the hepatic injuries upon SiNPs inhalation. Still, the understanding of the hepatic outcomes resulting from SiNPs exposure, and underlying mechanisms are incompletely elucidated. Here, SiNPs of two sizes (60 nm and 300 nm) were applied to investigate their composition- and size-related impacts on livers of ApoE-/- mice via intratracheal instillation. Histopathological and biochemical analysis indicated SiNPs promoted inflammation, lipid deposition and fibrosis in the hepatic tissue, accompanied by increased ALT, AST, TC and TG. Oxidative stress was activated upon SiNPs stimuli, as evidenced by the increased hepatic ROS, MDA and declined GSH/GSSG. Of note, these alterations were more dramatic in SiNPs with a smaller size (SiNPs-60) but the same dosage. LC-MS/MS-based quantitative proteomics unveiled changes in mice liver protein profiles, and filtered out particle composition- or size-related molecules. Interestingly, altered lipid metabolism and oxidative damage served as two critical biological processes. In accordance with correlation analysis and liver disease-targeting prediction, a final of 10 differentially expressed proteins (DEPs) were selected as key potential targets attributable to composition- (4 molecules) and size-related (6 molecules) liver impairments upon SiNPs stimuli. Overall, our study provided strong laboratory evidence for a comprehensive understanding of the harmful biological effects of SiNPs, which was crucial for toxicological evaluation to ensure nanosafety.

A critical evaluation of ultrasensitive single-cell proteomics strategies

Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.

The 15-min (Sub)Cellular Proteome

Single-cell mass spectrometry (MS) opens a proteomic window onto the inner workings of cells. Here, we report the discovery characterization of the subcellular proteome of single, identified embryonic cells in record speed and molecular coverage. We integrated subcellular capillary microsampling, fast capillary electrophoresis (CE), high-efficiency nano-flow electrospray ionization, and orbitrap tandem MS. In proof-of-principle tests, we found shorter separation times to hinder proteome detection using DDA, but not DIA. Within a 15-min effective separation window, CE data-independent acquisition (DIA) was able to identify 1,161 proteins from single HeLa-cell-equivalent (∼200 pg) proteome digests vs. 401 proteins by the reference data-dependent acquisition (DDA) on the same platform. The approach measured 1,242 proteins from subcellular niches in an identified cell in the live Xenopus laevis (frog) embryo, including many canonical components of organelles. CE-MS with DIA enables fast, sensitive, and deep profiling of the (sub)cellular proteome, expanding the bioanalytical toolbox of cell biology.

Authorship Contributions

P.N. and B.S. designed the study. L.R.P. collected the X. laevis cell aspirates. B.S. prepared and measured the samples. B.S. and P.N. analyzed the data and interpreted the results. P.N. and B.S. wrote the manuscript. All the authors commented on the manuscript.

Special Issue with Research Topics on "Recent Analysis and Applications of Mass Spectra on Biochemistry"

Analytical mass spectrometry applies irreplaceable mass spectrometric (MS) methods to analytical chemistry and chemical analysis, among other areas of analytical science [...].

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

Abundant proteins challenge deep mass spectrometry (MS) analysis of the proteome. Yolk, the source of food in many developing vertebrate embryos, complicates chemical separation and interferes with detection. We report here a strategy that enhances bottom-up proteomics in yolk-laden specimens by diluting the interferences using a yolk-depleted carrier (YODEC) proteome via isobaric multiplexing quantification. This method was tested on embryos of the South African Clawed Frog (Xenopus laevis), where a >90% yolk proteome content challenges deep proteomics. As a proof of concept, we isolated neural and epidermal fated cell clones from the embryo by dissection or fluorescence-activated cell sorting. Compared with the standard multiplexing carrier approach, YODEC more than doubled the detectable X. laevis proteome, identifying 5,218 proteins from D11 cell clones dissected from the embryo. Ca. ∼80% of the proteins were quantified without dropouts in any of the analytical channels. YODEC with high-pH fractionation quantified 3,133 proteins from ∼8,000 V11 cells that were sorted from ca. 2 embryos (1.5 μg total, or 150 ng yolk-free proteome), marking a 15-fold improvement in proteome coverage vs the standard proteomics approach. About 60% of these proteins were only quantifiable by YODEC, including molecular adaptors, transporters, translation, and transcription factors. While this study was tailored to limited populations of Xenopus cells, we anticipate the approach of "dilute to enrich" using a depleted carrier proteome to be adaptable to other biological models in which abundant proteins challenge deep MS proteomics.

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

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.

Exploring novel ANGICon-EIPs through ameliorated peptidomics techniques: Can deep learning strategies as a core breakthrough in peptide structure and function prediction?

Dairy-derived angiotensin-I-converting enzyme inhibitory peptides (ANGICon-EIPs) have been regarded as a relatively safe supplementary diet-therapy strategy for individuals with hypertension, and short-chain peptides may have more relevant antihypertensive benefits due to their direct intestinal absorption. Our previous explorations have confirmed that endogenous goat milk short-chain peptides are also an essential source of ANGICon-EIPs. Nonetheless, there are limited explorations on endogenous ANGICon-EIPs owing to the limitations of the extraction and enrichment of endogenous peptides, currently. This review outlined ameliorated pre-treatment strategies, data acquisition methods, and tools for the prediction of peptide structure and function, aiming to provide creative ideas for discovering novel ANGICon-EIPs. Currently, deep learning-based peptide structure and function prediction algorithms have achieved significant advancements. The convolutional neural network (CNN) and peptide sequence-based multi-label deep learning approach for determining the multi-functionalities of bioactive peptides (MLBP) can predict multiple peptide functions with absolute true value and accuracy of 0.699 and 0.708, respectively. Utilizing peptide sequence input, torsion angles, and inter-residue distance to train neural networks, APPTEST predicted the average backbone root mean square deviation (RMSD) value of peptide (5-40 aa) structures as low as 1.96 Å. Overall, with the exploration of more neural network architectures, deep learning could be considered a critical research tool to reduce the cost and improve the efficiency of identifying novel endogenous ANGICon-EIPs.

Microanalytical Mass Spectrometry with Super-Resolution Microscopy Reveals a Proteome Transition During Development of the Brain's Circadian Pacemaker

During brain development, neuronal proteomes are regulated in part by changes in spontaneous and sensory-driven activity in immature neural circuits. A longstanding model for studying activity-dependent circuit refinement is the developing mouse visual system where the formation of axonal projections from the eyes to the brain is influenced by spontaneous retinal activity prior to the onset of vision and by visual experience after eye-opening. The precise proteomic changes in retinorecipient targets that occur during this developmental transition are unknown. Here, we developed a microanalytical proteomics pipeline using capillary electrophoresis (CE) electrospray ionization (ESI) mass spectrometry (MS) in the discovery setting to quantify developmental changes in the chief circadian pacemaker, the suprachiasmatic nucleus (SCN), before and after the onset of photoreceptor-dependent visual function. Nesting CE-ESI with trapped ion mobility spectrometry time-of-flight (TOF) mass spectrometry (TimsTOF PRO) doubled the number of identified and quantified proteins compared to the TOF-only control on the same analytical platform. From 10 ng of peptide input, corresponding to <∼0.5% of the total local tissue proteome, technical triplicate analyses identified 1894 proteins and quantified 1066 proteins, including many with important canonical functions in axon guidance, synapse function, glial cell maturation, and extracellular matrix refinement. Label-free quantification revealed differential regulation for 166 proteins over development, with enrichment of axon guidance-associated proteins prior to eye-opening and synapse-associated protein enrichment after eye-opening. Super-resolution imaging of select proteins using STochastic Optical Reconstruction Microscopy (STORM) corroborated the MS results and showed that increased presynaptic protein abundance pre/post eye-opening in the SCN reflects a developmental increase in synapse number, but not presynaptic size or extrasynaptic protein expression. This work marks the first development and systematic application of TimsTOF PRO for CE-ESI-based microproteomics and the first integration of microanalytical CE-ESI TimsTOF PRO with volumetric super-resolution STORM imaging to expand the repertoire of technologies supporting analytical neuroscience.

Proteomic profiling reveals dysregulated mitochondrial complex subunits responsible for myocardial toxicity induced by SiNPs

The relationship between environmental exposure to silica nanoparticles (SiNPs) and adverse cardiac outcomes has received more attention. Our recent work has revealed a size-dependent impact of the intratracheal instilled SiNPs on cardiac health of ApoE^-/- mice using nanoscale SiNPs-60 and submicro-sized SiNPs-300, but the underlying mechanism of action still remains unclear. Hence, we identified proteins and protein networks perturbed by SiNPs in myocardial tissues of ApoE^-/- mice by using LC-MS/MS-based quantitative proteomics. A set of 435 differentially expressed proteins (DEPs) were screened in response to SiNPs, which mainly enriched in the mitochondria and functioned in cell metabolism, biosynthesis and signal transduction. KEGG analysis showed that DEPs were significantly associated with oxidative phosphorylation and cardiomyopathy. The protein-protein interaction (PPI) network revealed 9 DEPs (e.g., Ndufs1, Ndufv1, Cox4i1) as potential biomarkers of SiNPs-induced myocardial toxicity. Of note, all the 9 candidate proteins were subunits of mitochondria respiratory chain complex, and their expressions were dependent on particle size, which were remarkably down-regulated by SiNPs-60 but not by SiNPs-300. More importantly, the correlation analysis verified the 9 dysregulated mitochondria complex protein subunits strongly correlated to the biochemical and functional indexes of cardiac injury in response to SiNPs. In conclusion, our study firstly provided significant proteomic insights into the potential molecular mechanisms underlying SiNPs-elicited cardiotoxicity, with the dysregulated mitochondrial complex subunits as core regulatory molecules. Overall, our study would provide the scientific basis for the molecular actions and mechanisms of toxicity induced by SiNPs.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Microanalysis of Brain Angiotensin Peptides Using Ultrasensitive Capillary Electrophoresis Trapped Ion Mobility Mass Spectrometry

While the role of the renin-angiotensin system (RAS) in peripheral circulation is well characterized, we still lack an in-depth understanding of its role within the brain. This knowledge gap is sustained by lacking technologies for trace-level angiotensin detection throughout tissues, such as the brain. To provide a bridging solution, we enhanced capillary electrophoresis (CE) nanoflow electrospray ionization (ESI) with large-volume sample stacking and employed trapped ion mobility time-of-flight (timsTOF) tandem HRMS detection. A dynamic pH junction helped stack approximately 10 times more of the sample than optimal using the field-amplified reference. In conjunction, the efficiency of ion generation was maximized by a cone-jet nanospray on a low sheath-flow tapered-tip nano-electrospray emitter. The platform provided additional peptide-dependent information, the collision cross section, to filter chemical noise and improve sequence identification and detection limits. The lower limit of detection reached sub-picomolar or ∼30 zmol (∼18,000 copies) level. All nine targeted angiotensin peptides in mouse tissue samples were detectable and quantifiable from the paraventricular nucleus (PVN) of the hypothalamus even after removal of circulatory blood components (perfusion). We anticipate CE-ESI with timsTOF HRMS to be broadly applicable for the ultrasensitive detection of brain peptidomes in pursuit of a better understanding of the brain.

Capillary Electrophoresis Mass Spectrometry for Scalable Single-Cell Proteomics

Understanding the biochemistry of the cell requires measurement of all the molecules it produces. Single-cell proteomics recently became possible through advances in microanalytical sample preparation, separation by nano-flow liquid chromatography (nanoLC) and capillary electrophoresis (CE), and detection using electrospray ionization (ESI) high-resolution mass spectrometry (HRMS). Here, we demonstrate capillary microsampling CE-ESI-HRMS to be scalable to proteomics across broad cellular dimensions. This study established proof-of-principle using giant, ∼250-µm-diameter cells from embryos of the frog Xenopus laevis and small, ∼35-µm-diameter neurons in culture from the mouse hippocampus. From ∼18 ng, or ∼0.2% of the total cellular proteome, subcellular analysis of the ventral-animal midline (V11) and equatorial (V12) cells identified 1,133 different proteins in a 16-cell embryo. CE-HRMS achieved ∼20-times higher sensitivity and doubled the speed of instrumental measurements compared to nanoLC, the closest neighboring single-cell technology of choice. Microanalysis was scalable to 722 proteins groups from ∼5 ng of cellular protein digest from identified left dorsal-animal midline cell (D11), supporting sensitivity for smaller cells. Capillary microsampling enabled the isolation and transfer of individual neurons from the culture, identifying 37 proteins between three different cells. A total of 224 proteins were detected from 500 pg of neuronal protein digest, which estimates to a single neuron. Serial dilution returned 157 proteins from sample amounts estimating to about half a cell (250 pg protein) and 70 proteins from ca. a quarter of a neuron (125 pg protein), suggesting sufficient sensitivity for subcellular proteomics. CE-ESI-HRMS complements nanoLC proteomics with scalability, sensitivity, and speed across broad cellular dimensions.

Patch-Clamp Proteomics of Single Neurons in Tissue Using Electrophysiology and Subcellular Capillary Electrophoresis Mass Spectrometry

Understanding of the relationship between cellular function and molecular composition holds a key to next-generation therapeutics but requires measurement of all types of molecules in cells. Developments in sequencing enabled semiroutine measurement of single-cell genomes and transcriptomes, but analytical tools are scarce for detecting diverse proteins in tissue-embedded cells. To bridge this gap for neuroscience research, we report the integration of patch-clamp electrophysiology with subcellular shot-gun proteomics by high-resolution mass spectrometry (HRMS). Recording of electrical activity permitted identification of dopaminergic neurons in the substantia nigra pars compacta. Ca. 20-50% of the neuronal soma content, containing an estimated 100 pg of total protein, was aspirated into the patch pipette filled with ammonium bicarbonate. About 1 pg of somal protein, or ∼0.25% of the total cellular proteome, was analyzed on a custom-built capillary electrophoresis (CE) electrospray ionization platform using orbitrap HRMS for detection. A series of experiments were conducted to systematically enhance detection sensitivity through refinements in sample processing and detection, allowing us to quantify ∼275 different proteins from somal aspirate-equivalent protein digests from cultured neurons. From single neurons, patch-clamp proteomics of the soma quantified 91, 80, and 95 different proteins from three different dopaminergic neurons or 157 proteins in total. Quantification revealed detectable proteomic differences between the somal protein samples. Analysis of canonical knowledge predicted rich interaction networks between the observed proteins. The integration of patch-clamp electrophysiology with subcellular CE-HRMS proteomics expands the analytical toolbox of neuroscience.