Publications

2021
Slavov N. Driving Single Cell Proteomics Forward with Innovation. Journal of Proteome Research. 2021. Publisher's VersionAbstract
Current single-cell mass spectrometry (MS) methods can quantify thousands of peptides per single cell while detecting peptide-like features that may support the quantification of 10-fold more peptides. This 10-fold gain might be attained by innovations in data acquisition and interpretation even while using existing instrumentation. This perspective discusses possible directions for such innovations with the aim to stimulate community efforts for increasing the coverage and quantitative accuracy of single proteomics while simultaneously decreasing missing data. Parallel improvements in instrumentation, sample preparation, and peptide separation will afford additional gains. Together, these synergistic routes for innovation project a rapid growth in the capabilities of MS based single-cell protein analysis. These gains will directly empower applications of single-cell proteomics to biomedical research.
Slavov N. Increasing proteomics throughput. Nature Biotechnology. 2021;39 (7) :809–810. Publisher's VersionAbstract
A new dimension for analyzing mass spectrometry data allows rapid quantification of up to 70 % more peptides.
Slavov N. Measuring Protein Shapes in Living Cells. Journal of Proteome Research. 2021 :null. Publisher's VersionAbstract
Proteins fold into intricate shapes, known as conformations. The activation of many signal transduction proteins, kinases, and transcription factors requires a change in their conformations. Thus the conformation of a protein can indicate its biological activity. This importance of conformational changes has stimulated the development of numerous methods for analyzing protein conformations and interactions, such as native mass spectrometry and cryoelectron microscopy. These methods may achieve detailed characterizations of protein conformations, but they require highly purified proteins; they are challenged by the complexity of in vivo proteomes.
Leduc A, Huffman RG, Slavov N. Droplet sample preparation for single-cell proteomics applied to the cell cycle. bioRxiv. 2021. Publisher's VersionAbstract
Many biological functions, such as the cell division cycle, are intrinsically single-cell processes regulated in part by protein synthesis and degradation. Investigating such processes has motivated the development of single-cell mass spectrometry (MS) proteomics. To further advance single-cell MS proteomics, we developed a method for automated nano-ProteOmic sample Preparation (nPOP). nPOP uses piezo acoustic dispensing to isolate individual cells in 300 picoliter volumes and performs all subsequent preparation steps in small droplets on a hydrophobic slide. This allows massively parallel sample preparation, including lysing, digesting, and labeling individual cells in volumes below 20 nl. Single-cell protein analysis using nPOP classified cells by cell type and by cell cycle phase. Furthermore, the data allowed us to quantify the covariation between cell cycle protein markers and thousands of proteins. Based on this covariation, we identify cell cycle associated proteins and functions that are shared across cell types and those that differ between cell types.Competing Interest StatementThe authors have declared no competing interest.
Petelski AA, Emmott E, Leduc A, Huffman RG, Specht H, Perlman DH, Slavov N. Multiplexed single-cell proteomics using SCoPE2. bioRxiv. 2021. Publisher's VersionAbstract
Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying over 1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Isobaric carrier based multiplexed single-cell proteomics is a scalable, reliable, and cost-effective method that can be fully automated and implemented on widely available equipment. It uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. Here we describe an automated Single Cell ProtEomics (SCoPE2) workflow that allows analyzing about 200 single cells per 24 hours using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis.Competing Interest StatementThe authors have declared no competing interest.
Specht H, Emmott E, Petelski AA, Huffman RG, Perlman DH, Serra M, Kharchenko P, Koller A, Slavov N. Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2. Genome Biology. 2021;22 (1) :50. Publisher's VersionAbstract

Background Macrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of the limitations of quantitative single-cell protein analysis.

Results To overcome this limitation, we develop SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantifies over 3042 proteins in 1490 single monocytes and macrophages in 10 days of instrument time, and the quantified proteins allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. Parallel measurements of transcripts by 10× Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus, SCoPE2 supports quantification with improved count statistics. This allowed exploring regulatory interactions, such as interactions between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53.

Conclusions Even in a homogeneous environment, macrophage proteomes are heterogeneous. This heterogeneity correlates to the inflammatory axis of classically and alternatively activated macrophages. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.

Specht H, Slavov N. Optimizing Accuracy and Depth of Protein Quantification in Experiments Using Isobaric Carriers. Journal of Proteome Research. 2021;20 (1) :880-887. Publisher's Version
Slavov N. Single-cell protein analysis by mass spectrometry. Current Opinion in Chemical Biology. 2021;60 :1 - 9. Publisher's VersionAbstract
Human physiology and pathology arise from the coordinated interactions of diverse single cells. However, analyzing single cells has been limited by the low sensitivity and throughput of analytical methods. DNA sequencing has recently made such analysis feasible for nucleic acids but single-cell protein analysis remains limited. Mass spectrometry is the most powerful method for protein analysis, but its application to single cells faces three major challenges: efficiently delivering proteins/peptides to mass spectrometry detectors, identifying their sequences, and scaling the analysis to many thousands of single cells. These challenges have motivated corresponding solutions, including SCoPE design multiplexing and clean, automated, and miniaturized sample preparation. Synergistically applied, these solutions enable quantifying thousands of proteins across many single cells and establish a solid foundation for further advances. Building upon this foundation, the SCoPE concept will enable analyzing subcellular organelles and posttranslational modifications, while increases in multiplexing capabilities will increase the throughput and decrease cost.
2020
Specht H, Emmott E, Petelski A, Huffman RG, Perlman DH, Serra M, Kharchenko P, Koller A, Slavov N. Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity. bioRxiv. 2020. Publisher's VersionAbstract
The fate and physiology of individual cells are controlled by proteins. Yet, our ability to quantitatively analyze proteins in single cells has remained limited. To overcome this barrier, we developed SCoPE2. It substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enabled us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiated into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantified over 3,042 proteins in 1,490 single monocytes and macrophages in ten days of instrument time, and the quantified proteins allowed us to discern single cells by cell type. Furthermore, the data uncovered a continuous gradient of proteome states for the macrophage-like cells, suggesting that macrophage heterogeneity may emerge even in the absence of polarizing cytokines. Parallel measurements of transcripts by 10x Genomics scRNA-seq suggest that our measurements sampled 20-fold more protein copies than RNA copies per gene, and thus SCoPE2 supports quantification with improved count statistics. Joint analysis of the data illustrates how variability across single cells can reveal transcriptional and post-transcriptional gene regulation. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass-spectrometry.Competing Interest StatementThe authors have declared no competing interest.
Petelski AA, Slavov N. Analyzing Ribosome Remodeling in Health and Disease. PROTEOMICS. 2020;20 (17-18) :2000039. Publisher's VersionAbstract
Abstract Increasing evidence suggests that ribosomes actively regulate protein synthesis. However, much of this evidence is indirect, leaving this layer of gene regulation largely unexplored, in part due to methodological limitations. Indeed, evidence is reviewed demonstrating that commonly used methods, such as transcriptomics, are inadequate because the variability in mRNAs coding for ribosomal proteins (RP) does not necessarily correspond to RP variability. Thus protein remodeling of ribosomes should be investigated by methods that allow direct quantification of RPs, ideally of isolated ribosomes. Such methods are reviewed, focusing on mass spectrometry and emphasizing method-specific biases and approaches to control these biases. It is argued that using multiple complementary methods can help reduce the danger of interpreting reproducible systematic biases as evidence for ribosome remodeling.
Specht H, Slavov N. Optimizing accuracy and depth of protein quantification in experiments using isobaric carriers. bioRxiv. 2020. Publisher's VersionAbstract
The isobaric carrier approach, which combines small isobarically-labeled samples with a larger isobarically-labeled carrier sample, is finding diverse applications in ultrasensitive mass-spectrometry analysis of very small samples, such as single cells. To inform the growing use of isobaric carriers, we characterized the trade-offs of using isobaric carriers in controlled experiments with complex human proteomes. The data indicate that isobaric carriers directly enhances peptide sequence identification without simultaneously increasing the number of protein copies sampled from small samples. The results also indicate strategies for optimizing the amount of isobaric carrier and analytical parameters, such as ion accumulation time, for different priorities such as improved quantification or increased number of identified proteins. Balancing these trade-offs enables adapting isobaric carrier experiments to different applications, such as quantifying proteins from limited biopses or organoids, building single-cell atlases, or modeling protein networks in single cells. In all cases, the reliability of protein quantification should be estimated and incorporated in all subsequent analysis. We expect that these guidelines will aid explicit incorporation of the characterized trade-offs in experimental designs and transparent error propagation in data analysis.Competing Interest StatementThe authors have declared no competing interest.
Petelski AA, Slavov N. Analyzing ribosome remodeling in health and disease. 2020. Publisher's VersionAbstract
Increasing evidence suggests that ribosomes actively regulate protein synthesis. However, much of this evidence is indirect, leaving this layer of gene regulation largely unexplored, in part due to methodological limitations. Indeed, we review evidence demonstrating that commonly used methods, such as transcriptomics, are inadequate because the variability in mRNAs coding for ribosomal proteins (RP) does not necessarily correspond to RP variability. Thus protein remodeling of ribosomes should be investigated by methods that allow direct quantification of RPs, ideally of isolated ribosomes. We review such methods, with emphasis on their biases and approaches to control these biases. We argue that using multiple complementary methods can help reduce the danger of interpreting reproducible systematic biases as evidence for ribosome remodeling.
Slavov N. Single-cell protein analysis by mass-spectrometry. 2020. Publisher's VersionAbstract
Human physiology and pathology arise from the coordinated interactions of diverse single cells. However, analyzing single cells has been limited by the low sensitivity and throughput of analytical methods. DNA sequencing has recently made such analysis feasible for nucleic acids, but single-cell protein analysis remains limited. Mass-spectrometry is the most powerful method for protein analysis, but its application to single cells faces three major challenges: Efficiently delivering proteins/peptides to MS detectors, identifying their sequences, and scaling the analysis to many thousands of single cells. These challenges have motivated corresponding solutions, including SCoPE-design multiplexing and clean, automated, and miniaturized sample preparation. Synergistically applied, these solutions enable quantifying thousands of proteins across many single cells and establish a solid foundation for further advances. Building upon this foundation, the SCoPE concept will enable analyzing subcellular organelles and post-translational modifications while increases in multiplexing capabilities will increase the throughput and decrease cost.
Slavov N. Unpicking the proteome in single cells. Science. 2020;367 (6477) :512–513. Publisher's Version
2019
Slavov N, Anikeeva P, Boyden E, Brangwynne C, Cissé II, Fiehn O, Fromme P, Gingras AC, Greene CS, Heard E, et al. Voices in methods development. Nature Methods. 2019;16 (10) :945–951.
Specht H, Emmott E, Petelski A, Huffman RG, Perlman DH, Serra M, Kharchenko P, Koller A, Slavov N. Single-cell mass-spectrometry quantifies the emergence of macrophage heterogeneity. bioRxiv. 2019. Publisher's VersionAbstract
The fate and physiology of individual cells are controlled by protein interactions. Yet, our ability to quantitatively analyze proteins in single cells has remained limited. To overcome this barrier, we developed SCoPE2. It lowers cost and hands-on time by introducing automated and miniaturized sample preparation while substantially increasing quantitative accuracy. These advances enabled us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiated into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantified over 2,700 proteins in 1,018 single monocytes and macrophages in ten days of instrument time, and the quantified proteins allowed us to discern single cells by cell type. Furthermore, the data uncovered a continuous gradient of proteome states for the macrophage-like cells, suggesting that macrophage heterogeneity may emerge even in the absence of polarizing cytokines. Parallel measurements of transcripts by 10x Genomics scRNA-seq suggest that SCoPE2 samples 20-fold more copies per gene, thus supporting quantification with improved count statistics. Joint analysis of the data indicated that most genes had similar responses at the protein and RNA levels, though the responses of hundreds of genes differed. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass-spectrometry.
Huffman RG, Chen A, Specht H, Slavov N. DO-MS: Data-Driven Optimization of Mass Spectrometry Methods. Journal of Proteome Research. 2019;18 (6) :2493-2500. Publisher's VersionAbstract
The performance of ultrasensitive liquid chromatography and tandem mass spectrometry (LC-MS/MS) methods, such as single-cell proteomics by mass spectrometry (SCoPE-MS), depends on multiple interdependent parameters. This interdependence makes it challenging to specifically pinpoint the sources of problems in the LC-MS/MS methods and approaches for resolving them. For example, a low signal at the MS2 level can be due to poor LC separation, ionization, apex targeting, ion transfer, or ion detection. We sought to specifically diagnose such problems by interactively visualizing data from all levels of bottom-up LC-MS/MS analysis. Many software packages, such as MaxQuant, already provide such data, and we developed an open source platform for their interactive visualization and analysis: Data-driven Optimization of MS (DO-MS). We found that in many cases DO-MS not only specifically diagnosed LC-MS/MS problems but also enabled us to rationally optimize them. For example, by using DO-MS to optimize the sampling of the elution peak apexes, we increased ion accumulation times and apex sampling, which resulted in a 370% more efficient delivery of ions for MS2 analysis. DO-MS is easy to install and use, and its GUI allows for interactive data subsetting and high-quality figure generation. The modular design of DO-MS facilitates customization and expansion. DO-MS v1.0.8 is available for download from GitHub: https://github.com/SlavovLab/DO-MS. Additional documentation is available at https://do-ms.slavovlab.net.
Chen AT, Franks A, Slavov N. DART-ID increases single-cell proteome coverage. PLOS Computational Biology. 2019;15 (7) :1-30. Publisher's VersionAbstract
Author summary Identifying and quantifying proteins in single cells gives researchers the ability to tackle complex biological problems that involve single cell heterogeneity, such as the treatment of solid tumors. Mass spectrometry analysis of peptides can identify their sequence from their masses and the masses of their fragment ion, but often times these pieces of evidence are insufficient for a confident peptide identification. This problem is exacerbated when analyzing lowly abundant samples such as single cells. To identify even peptides with weak mass spectra, DART-ID incorporates their retention time—the time when they elute from the liquid chromatography used to physically separate them. We present both a novel method of aligning the retention times of peptides across experiments, as well as a rigorous framework for using the estimated retention times to enhance peptide sequence identification. Incorporating the retention time as additional evidence leads to a substantial increase in the number of samples in which proteins are confidently identified and quantified.
Specht H, Emmott E, Koller T, Slavov N. High-throughput single-cell proteomics quantifies the emergence of macrophage heterogeneity. bioRxiv. 2019. Publisher's VersionAbstract
The fate and physiology of individual cells are controlled by networks of proteins. Yet, our ability to quantitatively analyze protein networks in single cells has remained limited. To overcome this barrier, we developed SCoPE2. It integrates concepts from Single-Cell ProtEomics by Mass Spectrometry (SCoPE-MS) with automated and miniaturized sample preparation, substantially lowering cost and hands-on time. SCoPE2 uses data-driven analytics to optimize instrument parameters for sampling more ion copies per protein, thus supporting quantification with improved count statistics. These advances enabled us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiated into macrophage-like cells in the absence of polarizing cytokines. We used SCoPE2 to quantify over 2,000 proteins in 356 single monocytes and macrophages in about 85 hours of instrument time, and the quantified proteins allowed us to discern single cells by cell type. Furthermore, the data uncovered a continuous gradient of proteome states for the macrophage-like cells, suggesting that macrophage heterogeneity may emerge even in the absence of polarizing cytokines. Our methodology lays the foundation for quantitative analysis of protein networks at single-cell resolution.
Emmott E, Jovanovic M, Slavov N. Approaches for Studying Ribosome Specialization. Trends in Biochemical Sciences. 2019;44 (5) :478 - 479. Publisher's VersionAbstract
Contrary to the textbook model, recent measurements demonstrated unexpected diversity in ribosomal composition that likely enables specialized translational functions. Methods based on liquid chromatography coupled to tandem mass-spectrometry (LC-MS/MS) enable direct quantification of ribosomal proteins with high specificity, accuracy, and throughput. LC-MS/MS can be ‘top-down’, analyzing intact proteins, or more commonly ‘bottom-up’, where proteins are digested to peptides prior to analysis. Changes to rRNA can be examined using either LC-MS/MS or sequencing-based approaches. The regulation of protein synthesis by specialized ribosomes can be examined by multiple methods. These include the popular ‘Ribo-Seq’ method for analyzing ribosome density on a given mRNA, as well as LC-MS/MS approaches incorporating pulse-labelling with stable isotopes (SILAC) to monitor protein synthesis and degradation.

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