Optimizing Linear Ion-Trap Data-Independent Acquisition toward Single-Cell Proteomics

Rapid assay development for low input targeted proteomics using a versatile linear ion trap

Advances in proteomics and mass spectrometry enable the study of limited cell populations, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive low-mass specificity measurements, these instruments are effectively restricted to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. Here, we describe a workflow using a hybrid quadrupole-LIT instrument that rapidly develops targeted proteomics assays from global data-independent acquisition (DIA) measurements without high-mass accuracy. Using an automated software approach for scheduling parallel reaction monitoring assays (PRM), we show consistent quantification across three orders of magnitude in a matched-matrix background. We demonstrate measuring low-level proteins such as transcription factors and cytokines with quantitative linearity below two orders of magnitude in a 1 ng background proteome without requiring stable isotope-labeled standards. From a 1 ng sample, we found clear consistency between proteins in subsets of CD4+ and CD8+ T cells measured using high dimensional flow cytometry and LIT-based proteomics. Based on these results, we believe hybrid quadrupole-LIT instruments represent a valuable solution to expanding mass spectrometry in a wide variety of laboratory settings.

Data acquisition approaches for single cell proteomics

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.

Spatial Proteomics towards cellular Resolution

INTRODUCTION

Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level.

AREAS COVERED

This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution.

EXPERT OPINION

The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. Achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

Theoretical Assessment of Indistinguishable Peptides in Mass Spectrometry-Based Proteomics

Mass-spectrometry-based proteomics has advanced with the integration of experimental and predicted spectral libraries, which have significantly improved peptide identification in complex search spaces. However, challenges persist in distinguishing some peptides with close retention times and nearly identical fragmentation patterns. In this study, we conducted a theoretical assessment to quantify the prevalence of indistinguishable peptides within the human canonical proteome and immunopeptidome using state-of-the-art retention time and spectrum prediction models. By quantifying the proportion of peptides posing challenges to unequivocal identification, we set the theoretical nonaccessible portion within a given proteome, and underscore the effectiveness of contemporary analytical methodologies in resolving the complexity of the human proteome and immunopeptidome via mass spectrometry.

Recent advances and challenges in single cell protein (SCP) technologies for food and feed production

The global population is increasing, with a predicted demand for 1250 million tonnes of animal-derived protein by 2050, which will be difficult to meet. Single-cell protein (SCP) offers a sustainable solution. This review covers SCP production mechanisms, microbial and substrate choices, and advancements in metabolic engineering and CRISPR-Cas. It emphasizes second-generation substrates and fermentation for a circular economy. Despite challenges like high nucleic acid content, SCP promises to solve the global nutrition problem.

On the use of tandem mass spectra acquired from samples of evolutionarily distant organisms to validate methods for false discovery rate estimation

Estimating the false discovery rate (FDR) of peptide identifications is a key step in proteomics data analysis, and many methods have been proposed for this purpose. Recently, an entrapment-inspired protocol to validate methods for FDR estimation appeared in articles showcasing new spectral library search tools. That validation approach involves generating incorrect spectral matches by searching spectra from evolutionarily distant organisms (entrapment queries) against the original target search space. Although this approach may appear similar to the solutions using entrapment databases, it represents a distinct conceptual framework whose correctness has not been verified yet. In this viewpoint, we first discussed the background of the entrapment-based validation protocols and then conducted a few simple computational experiments to verify the assumptions behind them. The results reveal that entrapment databases may, in some implementations, be a reasonable choice for validation, while the assumptions underpinning validation protocols based on entrapment queries are likely to be violated in practice. This article also highlights the need for well-designed frameworks for validating FDR estimation methods in proteomics.

Rapid assay development for low input targeted proteomics using a versatile linear ion trap

Advances in proteomics and mass spectrometry enable the study of limited cell populations, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive low-mass accuracy measurements, these instruments are effectively restricted to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. Here, we describe a workflow using a new hybrid quadrupole-LIT instrument that rapidly develops targeted proteomics assays from global data-independent acquisition (DIA) measurements without needing high-mass accuracy. Using an automated software approach for scheduling parallel reaction monitoring assays (PRM), we show consistent quantification across three orders of magnitude in a matched-matrix background. We demonstrate measuring low-level proteins such as transcription factors and cytokines with quantitative linearity below two orders of magnitude in a 1 ng background proteome without requiring stable isotope-labeled standards. From a 1 ng sample, we found clear consistency between proteins in subsets of CD4+ and CD8+ T cells measured using high dimensional flow cytometry and LIT-based proteomics. Based on these results, we believe hybrid quadrupole-LIT instruments represent an economical solution to democratizing mass spectrometry in a wide variety of laboratory settings.

Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification

Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities, and future perspectives of this approach and its impact on mass spectrometry-based proteomics.

A workflow for targeted proteomics assay development using a versatile linear ion trap

Advances in proteomics and mass spectrometry have enabled the study of limited cell populations, such as single-cell proteomics, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive nominal resolution measurements, these instruments are effectively limited to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. We demonstrate a workflow using a newly released, hybrid quadrupole-LIT instrument for developing targeted proteomics assays from global data-independent acquisition (DIA) measurements without needing high-mass accuracy. Gas-phase fraction-based DIA enables rapid target library generation in the same background chemical matrix as each quantitative injection. Using a new software tool embedded within EncyclopeDIA for scheduling parallel reaction monitoring assays, we show consistent quantification across three orders of magnitude of input material. Using this approach, we demonstrate measuring peptide quantitative linearity down to 25x dilution in a background of only a 1 ng proteome without requiring stable isotope labeled standards. At 1 ng total protein on column, we found clear consistency between immune cell populations measured using flow cytometry and immune markers measured using LIT-based proteomics. We believe hybrid quadrupole-LIT instruments represent an economic solution to democratizing mass spectrometry in a wide variety of laboratory settings.

Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition

Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.