What's new in single-cell proteomics.

In recent years, single-cell proteomics (SCP) has advanced significantly, enabling the analysis of thousands of proteins within single mammalian cells. This progress is driven by advances in experimental design, with maturing label-free and multiplexed methods, optimized sample preparation, and innovations in separation techniques, including ultra-low-flow nanoLC. These factors collectively contribute to improved sensitivity, throughput, and reproducibility. Cutting-edge mass spectrometry platforms and data acquisition approaches continue to play a critical role in enhancing data quality. Furthermore, the exploration of spatial proteomics with single-cell resolution offers significant promise for understanding cellular interactions, giving rise to various phenotypes. SCP has far-reaching applications in cancer research, biomarker discovery, and developmental biology. Here, we provide a critical review of recent advances in the field of SCP.

Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics.

Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.

TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis.

A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.

Easy and Accessible Workflow for Label-Free Single-Cell Proteomics.

Single-cell proteomics (SCP) can provide information that is unattainable through either bulk-scale protein measurements or single-cell profiling of other omes. Maximizing proteome coverage often requires custom instrumentation, consumables, and reagents for sample processing and separations, which has limited the accessibility of SCP to a small number of specialized laboratories. Commercial platforms have become available for SCP cell isolation and sample preparation, but the high cost of these platforms and the technical expertise required for their operation place them out of reach of many interested laboratories. Here, we assessed the new HP D100 Single Cell Dispenser for label-free SCP. The low-cost instrument proved highly accurate and reproducible for dispensing reagents in the range from 200 nL to 2 µL. We used the HP D100 to isolate and prepare single cells for SCP within 384-well PCR plates. When the well plates were immediately centrifuged following cell dispensing and again after reagent dispensing, we found that ∼97% of wells that were identified in the instrument software as containing a single cell indeed provided the proteome coverage expected of a single cell. This commercial dispenser combined with one-step sample processing provides a very rapid and easy-to-use workflow for SCP with no reduction in proteome coverage relative to a nanowell-based workflow, and the commercial well plates also facilitate autosampling with unmodified instrumentation. Single-cell samples were analyzed using home-packed 30 µm i.d. nanoLC columns as well as commercially available 50 µm i.d. columns. The commercial columns resulted in ∼35% fewer identified proteins. However, combined with the well plate-based preparation platform, the presented workflow provides a fully commercial and relatively low-cost alternative for SCP sample preparation and separation, which should greatly broaden the accessibility of SCP to other laboratories.

Rapid, One-Step Sample Processing for Label-Free Single-Cell Proteomics.

Sample preparation for single-cell proteomics is generally performed in a one-pot workflow with multiple dispensing and incubation steps. These hours-long processes can be labor intensive and lead to long sample-to-answer times. Here we report a sample preparation method that achieves cell lysis, protein denaturation, and digestion in 1 h using commercially available high-temperature-stabilized proteases with a single reagent dispensing step. Four different one-step reagent compositions were evaluated, and the mixture providing the highest proteome coverage was compared to the previously employed multistep workflow. The one-step preparation increases proteome coverage relative to the previous multistep workflow while minimizing labor input and the possibility of human error. We also compared sample recovery between previously used microfabricated glass nanowell chips and injection-molded polypropylene chips and found the polypropylene provided improved proteome coverage. Combined, the one-step sample preparation and the polypropylene substrates enabled the identification of an average of nearly 2400 proteins per cell using a standard data-dependent workflow with Orbitrap mass spectrometers. These advances greatly simplify sample preparation for single-cell proteomics and broaden accessibility with no compromise in terms of proteome coverage.

TDP-43-stratified single-cell proteomic profiling of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis.

Unbiased proteomics has been employed to interrogate central nervous system (CNS) tissues (brain, spinal cord) and fluid matrices (CSF, plasma) from amyotrophic lateral sclerosis (ALS) patients; yet, a limitation of conventional bulk tissue studies is that motor neuron (MN) proteome signals may be confounded by admixed non-MN proteins. Recent advances in trace sample proteomics have enabled quantitative protein abundance datasets from single human MNs (Cong et al., 2020b). In this study, we leveraged laser capture microdissection (LCM) and nanoPOTS (Zhu et al., 2018c) single-cell mass spectrometry (MS)-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control donor spinal cord tissues, leading to the identification of 2515 proteins across MNs samples (>900 per single MN) and quantitative comparison of 1870 proteins between disease groups. Furthermore, we studied the impact of enriching/stratifying MN proteome samples based on the presence and extent of immunoreactive, cytoplasmic TDP-43 inclusions, allowing identification of 3368 proteins across MNs samples and profiling of 2238 proteins across TDP-43 strata. We found extensive overlap in differential protein abundance profiles between MNs with or without obvious TDP-43 cytoplasmic inclusions that together point to early and sustained dysregulation of oxidative phosphorylation, mRNA splicing and translation, and retromer-mediated vesicular transport in ALS. Our data are the first unbiased quantification of single MN protein abundance changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein abundance changes in human neurologic diseases.

Data-Dependent Acquisition with Precursor Coisolation Improves Proteome Coverage and Measurement Throughput for Label-Free Single-Cell Proteomics.

We combined efficient sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to quantify >3,000 proteins from single cells in rapid label-free analyses. WWA employs large isolation windows to intentionally co-isolate and co-fragment adjacent precursors along with the selected precursor. Optimized WWA increased the number of MS2-identified proteins by ≈40 % relative to standard data-dependent acquisition. For a 40-min LC gradient operated at ≈15 nL/min, we identified an average of 3,524 proteins per single-cell-sized aliquot of protein digest. Reducing the active gradient to 20 min resulted in a modest 10 % decrease in proteome coverage. Using this platform, we compared protein expression between single HeLa cells having an essential autophagy gene, atg9a, knocked out, with their isogenic WT parental line. Similar proteome coverage was observed, and 268 proteins were significantly up- or downregulated. Protein upregulation primarily related to innate immunity, vesicle trafficking and protein degradation.

HyperSCP: Combining Isotopic and Isobaric Labeling for Higher Throughput Single-Cell Proteomics.

Recent developments in mass spectrometry-based single-cell proteomics (SCP) have resulted in dramatically improved sensitivity, yet the relatively low measurement throughput remains a limitation. Isobaric and isotopic labeling methods have been separately applied to SCP to increase throughput through multiplexing. Here we combined both forms of labeling to achieve multiplicative scaling for higher throughput. Two-plex stable isotope labeling of amino acids in cell culture (SILAC) and isobaric tandem mass tag (TMT) labeling enabled up to 28 single cells to be analyzed in a single liquid chromatography-mass spectrometry (LC-MS) analysis, in addition to carrier, reference, and negative control channels. A custom nested nanowell chip was used for nanoliter sample processing to minimize sample losses. Using a 145-min total LC-MS cycle time, ∼280 single cells were analyzed per day. This measurement throughput could be increased to ∼700 samples per day with a high-duty-cycle multicolumn LC system producing the same active gradient. The labeling efficiency and achievable proteome coverage were characterized for multiple analysis conditions.

Metabolomic Analysis of Extracellular Vesicles from the Cereal Fungal Pathogen Fusarium graminearum.

Fusarium graminearum (F. graminearum) is a filamentous fungus that infects cereals such as corn, wheat, and barley, with serious impact on yield as well as quality when the grain is contaminated with mycotoxins. Despite the huge impact of F. graminearum on food security and mammalian health, the mechanisms used by F. graminearum to export virulence factors during infection are not fully understood and may involve non-classical secretory pathways. Extracellular vesicles (EVs) are lipid-bound compartments produced by cells of all kingdoms that transport several classes of macromolecules and are implicated in cell-cell communication. EVs produced by human fungal pathogens carry cargo that facilitate infection, leading us to ask whether plant fungal pathogens also deliver molecules that increase virulence via EVs. We examined the metabolome of the EVs produced by F. graminearum to determine whether they carry small molecules that could modulate plant-pathogen interactions. We discovered that EVs from F. graminearum were produced in liquid medium-containing inducers of trichothecene production, but in lower quantities compared to other media. Nanoparticle tracking analysis and cryo-electron microscopy revealed that the EVs were morphologically similar to EVs from other organisms; hence, the EVs were metabolically profiled using LC-ESI-MS/MS. This analysis revealed that EVs carry 2,4-dihydroxybenzophenone (BP-1) and metabolites that have been suggested by others to have a role in host-pathogen interactions. BP-1 reduced the growth of F. graminearum in an in vitro assay, suggesting that F. graminearum might use EVs to limit metabolite self-toxicity.

The Effect of Scale Insects on Growth Parameters of cv. Chardonnay and cv. Sauvignon Blanc Grapevines Grown in a Greenhouse.

Plants can respond to insects that feed with stylet mouthparts using various processes that are initiated via the salicylic acid metabolic pathway. In Australia, scale insects of the genus Parthenolecanium can cause economic damage to grapevines as they feed on the vines and produce honeydew as a waste by-product, which supports the growth of black sooty mould on fruit and leaves, potentially affecting the plant growth and yield. Using rootlings of Sauvignon Blanc (SB, resistant) and Chardonnay (Char, susceptible), the growth and production of volatile organic compounds (VOCs) following exposure to scale insect infestations were measured under controlled greenhouse conditions. At harvest, the numbers of scale insects per five leaves were higher on plants infested at the start of the study compared with the control plants. Infested SB had increased dry root and shoot mass compared with the SB control, which was also the case with Char (control and infested). Leaf volatiles differed between cultivars in response to scale infestation. Benzyl alcohol decreased among infested SB plants compared with the other treatments. A change in the salicylic acid pathway as indicated by the change in benzyl alcohol may cause the increased growth in SB associated with the increased scale insect infestation.

In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 µm.

Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories to cost-effectively preserve valuable specimens for later study. With the rapid growth of spatial proteomics, FFPE tissues can serve as a more accessible alternative to more commonly used frozen tissues. However, extracting proteins from FFPE tissues is challenging due to cross-links formed between proteins and formaldehyde. Here, we have adapted the nanoPOTS sample processing workflow, which was previously applied to single cells and fresh-frozen tissues, to profile protein expression from FFPE tissues. Following the optimization of extraction solvents, times, and temperatures, we identified an average of 1312 and 3184 high-confidence master proteins from 10 µm thick FFPE-preserved mouse liver tissue squares having lateral dimensions of 50 and 200 µm, respectively. The observed proteome coverage for FFPE tissues was on average 88% of that achieved for similar fresh-frozen tissues. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. This modified nanodroplet processing in one pot for trace samples (nanoPOTS) and fully automated processing in one pot for trace sample (autoPOTS) workflows provides the greatest coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues. Data are available via ProteomeXchange with identifier PXD029729.

Radiation exposure for the population living around the coal-fired power plant complexes in Vietnam.

A coal-fired power plant's operation can release radioactive nuclides and radon gas into the environment, affecting the surrounding ecosystem. In this work, the collective effective dose due to the inhalation and the consumption of food containing the deposited radionuclides from the atmospheric release of the plants were evaluated. The results show that the radioactivity concentration in coal and fly ash samples depends on the origin of feed coal. The distribution of Th and U radionuclides in the 6a1 dust coal and bituminous coal is different. In general, the collective effective dose for different organs due to radiation exposure from the atmospheric release of two surveyed CFPP complexes are lower than the corresponding value published by UNSCEAR.

Detection and analysis of novel and known plant volatile apocarotenoids.

As the climate becomes increasingly unpredictable due to global warming, plants will encounter a greater challenge to adapt to their hostile environment (e.g., drought, heat, pollution). Volatile apocarotenoids (VAs) are an integral part of this necessary adaptation. VAs are involved in diverse plant life processes such as defense against biotic or abiotic stresses and regulate various aspects of plant development. The discovery of new VAs will help enhance abiotic and biotic stress tolerance, optimize biomass and crop yield, improve root development to better search for nutrients and promote symbiotic associations. This chapter describes an optimized method, HeadSpace Solid-Phase MicroExtraction (HS-SPME) coupled to Gas Chromatography-Mass Spectrometry (GC/MS), for the sensitive, reproducible, accurate, and high-throughput detection and quantification of novel and known VAs. Further optimization of this method can be performed by (1) adapting optimal growth conditions for your plants, (2) identifying the correct SPME fiber coating chemistry for the VAs of interest, (3) adapting optimal sample HS-SPME extraction temperature and time, and the desorption time in the GC inlet, (4) identifying the correct GC column and applying the optimal GC/MS parameters for good chromatographic baseline separation of the VAs, mass spectral matching and retention index (RI) validation, and (5) performing suitable quantification and statistical analyses. With this optimized and validated analytical technique, we detected and quantified 28 VAs; 20 of these were identified for the first time in Arabidopsis.

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform.

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

Features of Peptide Fragmentation Spectra in Single-Cell Proteomics.

The goal of proteomics is to identify and quantify the complete set of proteins in a biological sample. Single-cell proteomics specializes in the identification and quantitation of proteins for individual cells, often used to elucidate cellular heterogeneity. The significant reduction in ions introduced into the mass spectrometer for single-cell samples could impact the features of MS2 fragmentation spectra. As all peptide identification software tools have been developed on spectra from bulk samples and the associated ion-rich spectra, the potential for spectral features to change is of great interest. We characterize the differences between single-cell spectra and bulk spectra by examining three fundamental spectral features that are likely to affect peptide identification performance. All features show significant changes in single-cell spectra, including the loss of annotated fragment ions, blurring signal and background peaks due to diminishing ion intensity, and distinct fragmentation pattern, compared to bulk spectra. As each of these features is a foundational part of peptide identification algorithms, it is critical to adjust algorithms to compensate for these losses.

Retail fresh vegetables as a potential source of Salmonella infection in the Mekong Delta, Vietnam.

From July 2017 to Jan 2019, a total of 572 retail fresh vegetables were collected to clarify the contamination of Salmonella in the Mekong Delta, Vietnam. Salmonella was isolated from 74 (12.9%) of 572 samples. The isolation rate of Salmonella from retail fresh vegetables in the rainy season (15.3%) was significantly higher than that in the dry season (7.6%) (P < 0.05). Of 74 Salmonella isolates, Salmonella Weltevreden was the most predominant serovar (35.1%) identified from retail fresh vegetables in all of the wet markets. All S. Weltevreden isolates (100%) were susceptible to nine antibiotics examined. Thus, retail fresh vegetables were considered as an important potential vehicle of Salmonella transmission to humans in the Mekong Delta. These results provide important data for preventing and controlling human salmonellosis in this area.

Adapting a Low-Cost and Open-Source Commercial Pipetting Robot for Nanoliter Liquid Handling.

Low-volume liquid handling capabilities in bioanalytical workflows can dramatically improve sample processing efficiency and reduce reagent costs, yet many commercial nanoliter liquid handlers cost tens of thousands of dollars or more. We have successfully adapted a low-cost and open-source commercial pipetting robot, the Opentrons OT-1, to accurately aspirate and dispense nanoliter volumes. Based on fluorescence measurements, the modified OT-1 was able to reproducibly transfer 50 nL of water with less than 3% measurement error and 5% coefficient of variation (CV). For 15 nL transfers, the volume measurements indicated less than 4% error and 4% CV. We applied this platform to the preparation of low-nanogram proteomic samples for liquid chromatography-mass spectrometry analysis, demonstrating that the modified OT-1 is an effective platform for nanoliter liquid handling. At a total materials cost of less than $6000, including the commercial liquid handler and all modifications, this system is also far less expensive than other platforms with similar capabilities, placing automated nanoliter handling within reach of a far broader scientific community.

Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling.

Recent advances in sample preparation and analysis have enabled direct profiling of protein expression in single mammalian cells and other trace samples. Several techniques to prepare and analyze low-input samples employ custom fluidics for nanoliter sample processing and manual sample injection onto a specialized separation column. While being effective, these highly specialized systems require significant expertise to fabricate and operate, which has greatly limited implementation in most proteomic laboratories. Here, we report a fully automated platform termed autoPOTS (automated preparation in one pot for trace samples) that uses only commercially available instrumentation for sample processing and analysis. An unmodified, low-cost commercial robotic pipetting platform was utilized for one-pot sample preparation. We used low-volume 384-well plates and periodically added water or buffer to the microwells to compensate for limited evaporation during sample incubation. Prepared samples were analyzed directly from the well plate with a commercial autosampler that was modified with a 10-port valve for compatibility with 30 µm i.d. nanoLC columns. We used autoPOTS to analyze 1-500 HeLa cells and observed only a moderate reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to our previously developed nanoPOTS platform. To evaluate clinical feasibility, we identified an average of 1095 protein groups from ∼130 sorted B or T lymphocytes. We anticipate that the straightforward implementation of autoPOTS will make it an attractive option for low-input and single-cell proteomics in many laboratories.

In-Depth Mass Spectrometry-Based Single-Cell and Nanoscale Proteomics.

Leukemic stem cells are highly dynamic and heterogeneous. Analysis of leukemic stem cells at the single-cell level should provide a wealth of insights that would not be possible using bulk measurements. Mass spectrometry (MS)-based proteomic workflows can quantify hundreds or thousands of proteins from a biological sample and has proven invaluable for biomedical research, but samples comprising large numbers of cells are typically required due to limited sensitivity. Recent developments in sample processing, chromatographic separations, and MS instrumentation are now extending in-depth proteome profiling to single mammalian cells. Here, we describe specific techniques that increase the sensitivity of single-cell proteomics by orders of magnitude, enabling the promise of single-cell proteomics to become a reality. We anticipate such techniques can significantly advance the understanding of leukemic stem cells.