Cell-selective proteomics for biological discovery

https://doi.org/10.1016/j.cbpa.2016.12.026Get rights and content

Highlights

  • •

    Cell-selective proteomics is important in complex, heterocellular environments.

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    Innovative chemical tools enable unbiased cell-type-specific interrogation of translation.

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    Labeling methods including TRAP, CTAP, BONCAT, SORT, OP-Puro and APEX have been developed for cell-selective analysis.

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    Sequencing and mass spectrometry-based strategies complement one other in the study of protein synthesis.

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    The strengths and limitations of each analytical method must be considered carefully in the context of the biological question to be addressed.

Cells alter the proteome to respond to environmental and developmental cues. Global analysis of proteomic responses is of limited value in heterogeneous environments, where there is no ‘average’ cell. Advances in sequencing, protein labeling, mass spectrometry, and data analysis have fueled recent progress in the investigation of specific subpopulations of cells in complex systems. Here we highlight recently developed chemical tools that enable cell-selective proteomic analysis of complex biological systems, from bacterial pathogens to whole animals.

Introduction

Cellular protein synthesis changes rapidly in response to internal and external cues in ways that vary from cell to cell. Global proteomic analyses of microbial communities, tissues and organisms have provided important insights into the behavior of such systems, but can obscure the diversity of responses characteristic of different cellular subpopulations (Figure 1). Cell-selective methods for the analysis of protein synthesis are being developed to resolve proteomic changes in space and time.

Cell-type-specific transcriptomics experiments have revealed mRNA expression patterns in a wide array of biological systems, but mRNA and protein levels are often dissonant [1]. Moreover, some important elements of proteome dynamics, including post-translational modification, degradation, and localization, cannot be addressed by mRNA measurements alone [2, 3]. Until recently, changes in protein abundance in specific cells could be measured only in targeted, low-throughput experiments, but innovations in mass spectrometry and computational algorithms have facilitated the identification and quantification of thousands of proteins simultaneously from complex biological samples [4, 5, 6].

In this Opinion, we highlight recent developments in determining cell-type-specific proteomes and recommend experimental design strategies that are guided by the question at hand.

Section snippets

Cell-selective translatomics and ribosome profiling

Translatomic studies, which select for ribosome-associated transcripts, have yielded stronger correlations between transcript and protein abundances than experiments that measure steady-state mRNA levels [7]. Cell-type-specific studies have been enabled by translating ribosome affinity purification (TRAP), a method in which epitope-tagged ribosomes and their associated transcripts are captured, enriched, and subjected to amplification and deep sequencing [8]. TRAP can be rendered cell-specific

Separating cells for steady-state proteomic analysis

The earliest strategies to determine cell-specific proteomes relied on separating and purifying the cells of interest before analysis. Cells can be sorted on the basis of expression of a transgene under control of a cell-specific promoter or by antibody staining of marker epitopes. These tools are well established and have been thoughtfully reviewed [10••, 11]. Physical methods have been used for years to isolate cell types from mammalian tissues for subsequent downstream analyses [12, 13].

Metabolic labeling: trade-offs between sensitivity and perturbation

Metabolic labeling methods are temporally resolved and use an arsenal of amino acid isotopologs, noncanonical amino acids, and analogs of protein synthesis inhibitors (Figure 2). Each of these strategies can be placed under control of cell-specific genetic elements to afford cellular resolution. The choice of promoter(s) is key for these systems, and the degree of protein labeling needs to be weighed against the possibility of perturbing the system. Results should be validated via independent

Spatially restricted & subcellular proteomics

Ting and coworkers first used a mutant ascorbate peroxidase (APEX) to selectively tag proteins localized to the mitochondrial matrix [45, 46]. Unlike the cell-selective metabolic labeling methods just described, this method labels all proteins, including pre-existing proteins, within a subcellular volume. Chen et al. used this elegant strategy to characterize multiple cell types in Drosophila, including the mitochondrial matrix of muscle tissue [47••]. The Weissman laboratory has combined the

Choosing a cell-selective proteomic method

The choice of a cell-selective method of proteomic analysis should reflect careful consideration of the advantages and disadvantages of each of the available approaches (Table 1).

Physical sorting methods allow straightforward characterization of the steady-state proteome of the cell type of interest. However, removing cells from their natural environments before analysis raises concerns about artifacts, leads to limited temporal information, and sacrifices information about secreted proteins.

Conclusions and future outlook

Recent years have witnessed the introduction of powerful techniques that allow investigators to monitor protein synthesis with unprecedented resolution in space and time. Cell-specific proteomic analyses will play a key role in the identification of the mechanisms that govern cell specialization and that allow complex organisms to respond to changing environments.

Funding

Caltech research on cell-specific proteomic analysis has been supported by NIH grants R01-GM062523 and R21-AI121890, and by the Institute for Collaborative Biotechnologies through grant W911NF-09-0001 from the U.S. Army Research Office.

Note added in proof

The following reference was accidentally omitted from our discussion of the work of Niehues et al. but is added below for completeness:

Niehues S, Bussmann J, Steffes G, Erdmann I, Kohrer C, Sun LT, Wagner M, Schafer K, Wang GX, Koerdt SN et al.: Impaired protein translation in Drosophila models for Charcot-Marie-Tooth neuropathy caused by mutant tRNA synthetases. Nat Comm 2015, 6:7520.

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

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