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. 2021 Jan 27;22(1):50.
doi: 10.1186/s13059-021-02267-5.

Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2

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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2

Harrison Specht et al. Genome Biol. .
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Abstract

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.

Conflict of interest statement

The authors declare that they have no competing financial interests.

Correspondence: Correspondence and materials requests should be addressed to nslavov@alum.mit.edu

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. 2021 Jan 1;20(1):880-887.
doi: 10.1021/acs.jproteome.0c00675. Epub 2020 Nov 14.

Optimizing Accuracy and Depth of Protein Quantification in Experiments Using Isobaric Carriers

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Optimizing Accuracy and Depth of Protein Quantification in Experiments Using Isobaric Carriers

Harrison Specht et al. J Proteome Res. .
Free PMC article

Abstract

The isobaric carrier approach, which combines small isobarically labeled samples with a larger isobarically labeled carrier sample, finds diverse applications in ultrasensitive mass spectrometry analysis of very small samples, such as single cells. To enhance 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 enhance 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 an increased number of identified proteins. Balancing these trade-offs enables adapting isobaric carrier experiments to different applications, such as quantifying proteins from limited biopsies 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 analyses. We expect that these guidelines will aid in explicit incorporation of the characterized trade-offs in experimental designs and transparent error propagation in data analysis.

Keywords: benchmarking; data reliability; isobaric carrier; optimizing mass spectrometry analysis; quantification accuracy; single-cell proteomics.

Conflict of interest statement

The authors declare no competing financial interest.

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. 2020 Sep;20(17-18):e2000039.
doi: 10.1002/pmic.202000039. Epub 2020 Sep 7.

Analyzing Ribosome Remodeling in Health and Disease

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Analyzing Ribosome Remodeling in Health and Disease

Aleksandra A Petelski et al. Proteomics. 2020 Sep.
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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.

Keywords: complementary mass spectrometry methods; post-transcriptional regulation; ribosome specialization.

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Conflict of Interest

The authors declare no conflict of interest.

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. 2020 Jun 28;60:1-9.
doi: 10.1016/j.cbpa.2020.04.018. Online ahead of print.

Single-cell protein analysis by mass spectrometry

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Single-cell protein analysis by mass spectrometry

Nikolai Slavov. Curr Opin Chem Biol. .
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Abstract

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.

Keywords: Isobaric carrier; Mass-spectrometry; Sample preparation; Single-cell analysis; Single-cell proteomics; Systems biology.

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. 2020 Jan 31;367(6477):512-513.
doi: 10.1126/science.aaz6695.

Unpicking the proteome in single cells

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Unpicking the proteome in single cells

Nikolai Slavov. Science. .
Free PMC article
No abstract available

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. 2019 Oct;16(10):945-951.
doi: 10.1038/s41592-019-0585-6.

Voices in methods development

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Voices in methods development

Polina Anikeeva et al. Nat Methods. 2019 Oct.
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Abstract

To mark the 15th anniversary of Nature Methods, we asked scientists from across diverse fields of basic biology research for their views on the most exciting and essential methodological challenges that their communities are poised to tackle in the near future.

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. 2019 Jul 1;15(7):e1007082.
doi: 10.1371/journal.pcbi.1007082. eCollection 2019 Jul.

DART-ID increases single-cell proteome coverage

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DART-ID increases single-cell proteome coverage

Albert Tian Chen et al. PLoS Comput Biol. .
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Abstract

Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30-50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells. DART-ID can be applied to diverse experimental designs and is freely available at http://dart-id.slavovlab.net.

Conflict of interest statement

The authors have declared that no competing interests exist.

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. 2019 Jun 7;18(6):2493-2500.
doi: 10.1021/acs.jproteome.9b00039. Epub 2019 May 28.

DO-MS: Data-Driven Optimization of Mass Spectrometry Methods

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DO-MS: Data-Driven Optimization of Mass Spectrometry Methods

R Gray Huffman et al. J Proteome Res. .
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Abstract

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 .

Keywords: MaxQuant; R; Shiny; method development; optimizing mass spectrometry; quality control; single-cell analysis; single-cell proteomics by mass spectrometry; ultrasensitive proteomics; visualization.

Conflict of interest statement

The authors declare no competing financial interest.

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. 2019 May;44(5):478-479.
doi: 10.1016/j.tibs.2019.01.008. Epub 2019 Feb 18.

Approaches for Studying Ribosome Specialization

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Approaches for Studying Ribosome Specialization

Edward Emmott et al. Trends Biochem Sci. 2019 May.
Free PMC article

Abstract

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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. 2019 Feb;44(2):95-109.
doi: 10.1016/j.tibs.2018.10.009. Epub 2018 Nov 22.

Ribosome Stoichiometry: From Form to Function

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Review

Ribosome Stoichiometry: From Form to Function

Edward Emmott et al. Trends Biochem Sci. 2019 Feb.
Free PMC article

Abstract

The existence of eukaryotic ribosomes with distinct ribosomal protein (RP) stoichiometry and regulatory roles in protein synthesis has been speculated for over 60 years. Recent advances in mass spectrometry (MS) and high-throughput analysis have begun to identify and characterize distinct ribosome stoichiometry in yeast and mammalian systems. In addition to RP stoichiometry, ribosomes host a vast array of protein modifications, effectively expanding the number of human RPs from 80 to many thousands of distinct proteoforms. Is it possible that these proteoforms combine to function as a 'ribosome code' to tune protein synthesis? We outline the specific benefits that translational regulation by specialized ribosomes can offer and discuss the means and methodologies available to correlate and characterize RP stoichiometry with function. We highlight previous research with a focus on formulating hypotheses that can guide future experiments and crack the ribosome code.

Keywords: heterogeneity; mass spectrometry; ribosome; stoichiometry; translation.

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