Developments in quantitative mass spectrometry for the analysis of proteome dynamics

Plant Proteome Dynamics

Proteins are intimately involved in executing and controlling virtually all cellular processes. To understand the molecular mechanisms that underlie plant phenotypes, it is essential to investigate protein expression, interactions, and modifications, to name a few. The proteome is highly dynamic in time and space, and a plethora of protein modifications, protein interactions, and network constellations are at play under specific conditions and developmental stages. Analysis of proteomes aims to characterize the entire protein complement of a particular cell type, tissue, or organism-a challenging task, given the dynamic nature of the proteome. Modern mass spectrometry-based proteomics technology can be used to address this complexity at a system-wide scale by the global identification and quantification of thousands of proteins. In this review, we present current methods and technologies employed in mass spectrometry-based proteomics and provide examples of dynamic changes in the plant proteome elucidated by proteomic approaches.

Mass spectrometric analysis of PTM dynamics using stable isotope labeled metabolic precursors in cell culture

Biological organisms represent highly dynamic systems, which are continually exposed to environmental factors and always strive to restore steady-state homeostasis. Posttranslational modifications are key regulators with which biological systems respond to external stimuli. To understand how homeostasis is restored, it is important to study the kinetics of posttranslational modifications. In this review we discuss proteomic approaches using stable isotope labeled metabolic precursors to study dynamics of posttranslational modifications in cell culture.

Peptide Level Turnover Measurements Enable the Study of Proteoform Dynamics

The coordination of protein synthesis and degradation regulating protein abundance is a fundamental process in cellular homeostasis. Today, mass spectrometry-based technologies allow determination of endogenous protein turnover on a proteome-wide scale. However, standard dynamic SILAC (Stable Isotope Labeling in Cell Culture) approaches can suffer from missing data across pulse time-points limiting the accuracy of such analysis. This issue is of particular relevance when studying protein stability at the level of proteoforms because often only single peptides distinguish between different protein products of the same gene. To address this shortcoming, we evaluated the merits of combining dynamic SILAC and tandem mass tag (TMT)-labeling of ten pulse time-points in a single experiment. Although the comparison to the standard dynamic SILAC method showed a high concordance of protein turnover rates, the pulsed SILAC-TMT approach yielded more comprehensive data (6000 proteins on average) without missing values. Replicate analysis further established that the same reproducibility of turnover rate determination can be obtained for peptides and proteins facilitating proteoform resolved investigation of protein stability. We provide several examples of differentially turned over splice variants and show that post-translational modifications can affect cellular protein half-lives. For example, N-terminally processed peptides exhibited both faster and slower turnover behavior compared with other peptides of the same protein. In addition, the suspected proteolytic processing of the fusion protein FAU was substantiated by measuring vastly different stabilities of the cleavage products. Furthermore, differential peptide turnover suggested a previously unknown mechanism of activity regulation by post-translational destabilization of cathepsin D as well as the DNA helicase BLM. Finally, our comprehensive data set facilitated a detailed evaluation of the impact of protein properties and functions on protein stability in steady-state cells and uncovered that the high turnover of respiratory chain complex I proteins might be explained by oxidative stress.

Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants

Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.

MS(3)-based quantitative proteomics using pulsed-Q dissociation

RATIONALE

Isobaric tagging reagents, such as tandem mass tags (TMT) and isobaric tags for relative and absolute quantitation (iTRAQ), are high-throughput methods that allow the analysis of multiple samples simultaneously, which reduces instrument time and error. Accuracy and precision of isobaric tags are limited, however, in tandem mass spectrometry (MS/MS) acquisition due to co-isolation and co-fragmentation of neighboring peptide peaks in precursor scans. Here we present a MS(3) method using pulsed-Q dissociation (PQD) in ion trap and Orbitrap instrumentation as a means to improve ratio distortion and maintain high numbers of identified and quantified proteins.

METHODS

Mouse brain protein digests were labeled with TMT-128, 129, 130, 131 reagents, mixed in the following molar ratios 1:1:2:5, respectively, and analyzed using HCD-MS(3) and PQD-MS(3) methods. The most intense fragment ion (termed as HCD-MS(3)-top ion or PQD-MS(3)-top ion) or y1 ion (i.e., lysine-TMT tag ion; termed as HCD-MS(3)-y1 or PQD-MS(3)-y1) in collision-induced dissociation (CID) MS/MS was selected for MS(3).

RESULTS

Calculated protein ratios obtained in HCD-MS(3)-top ion and PQD-MS(3)-top ion, HCD-MS(3)-y1, and PQD-MS(3)-y1 are accurate and PQD-MS(3) methods resulted in higher numbers of identified and quantified peptide spectral counts and proteins.

CONCLUSIONS

PQD-MS(3) methods increase the amount of MS/MS spectra collected and number of quantified proteins and are accessible to those researchers with not only an orbitrap but also an ion trap mass spectrometer.

Emerging properties of nuclear RNP biogenesis and export

RNA biology has recently seen an explosion of data due to advances in RNA sequencing, proteomic, and RNA imaging technologies. In this review, we highlight progress that has been made using these approaches in the area of nuclear RNP biogenesis and export. Excitingly, the ability to collect quantitative data at the 'omics' scale combined with measurements of transcription, decay, and transport kinetics is providing the information needed to address RNP biogenesis at a systems level. We believe this to be a necessary and critical next step that will lead to a better understanding of how RNP quality, diversity, and fate emerge from a defined set of nuclear RNP assembly and maturation steps.

Quantitative and Systems-Based Approaches for Deciphering Bacterial Membrane Interactome and Gene Function

High-throughput genomic and proteomic methods provide a concise description of the molecular constituents of a cell, whereas systems biology strives to understand the way these components function as a whole. Recent developments, such as genome editing technologies and protein epitope-tagging coupled with high-sensitivity mass-spectrometry, allow systemic studies to be performed at an unprecedented scale. Available methods can be successfully applied to various goals, both expanding fundamental knowledge and solving applied problems. In this review, we discuss the present state and future of bacterial cell envelope interactomics, with a specific focus on host-pathogen interactions and drug target discovery. Both experimental and computational methods will be outlined together with examples of their practical implementation.

Protein maturation and proteolysis in plant plastids, mitochondria, and peroxisomes

Plastids, mitochondria, and peroxisomes are key organelles with dynamic proteomes in photosynthetic eukaryotes. Their biogenesis and activity must be coordinated and require intraorganellar protein maturation, degradation, and recycling. The three organelles together are predicted to contain ∼200 presequence peptidases, proteases, aminopeptidases, and specific protease chaperones/adaptors, but the substrates and substrate selection mechanisms are poorly understood. Similarly, lifetime determinants of organellar proteins, such as N-end degrons and tagging systems, have not been identified, but the substrate recognition mechanisms likely share similarities between organelles. Novel degradomics tools for systematic analysis of protein lifetime and proteolysis could define such protease-substrate relationships, degrons, and protein lifetime. Intraorganellar proteolysis is complemented by autophagy of whole organelles or selected organellar content, as well as by cytosolic protein ubiquitination and degradation by the proteasome. This review summarizes (putative) plant organellar protease functions and substrate-protease relationships. Examples illustrate key proteolytic events.

Hijacking of host cellular functions by an intracellular parasite, the microsporidian Anncaliia algerae

Intracellular pathogens including bacteria, viruses and protozoa hijack host cell functions to access nutrients and to bypass cellular defenses and immune responses. These strategies have been acquired through selective pressure and allowed pathogens to reach an appropriate cellular niche for their survival and growth. To get new insights on how parasites hijack host cellular functions, we developed a SILAC (Stable Isotope Labeling by Amino Acids in Cell culture) quantitative proteomics workflow. Our study focused on deciphering the cross-talk in a host-parasite association, involving human foreskin fibroblasts (HFF) and the microsporidia Anncaliia algerae, a fungus related parasite with an obligate intracellular lifestyle and a strong host dependency. The host-parasite cross-talk was analyzed at five post-infection times 1, 6, 12 and 24 hours post-infection (hpi) and 8 days post-infection (dpi). A significant up-regulation of four interferon-induced proteins with tetratricopeptide repeats IFIT1, IFIT2, IFIT3 and MX1 was observed at 8 dpi suggesting a type 1 interferon (IFN) host response. Quantitative alteration of host proteins involved in biological functions such as signaling (STAT1, Ras) and reduction of the translation activity (EIF3) confirmed a host type 1 IFN response. Interestingly, the SILAC approach also allowed the detection of 148 A. algerae proteins during the kinetics of infection. Among these proteins many are involved in parasite proliferation, and an over-representation of putative secreted effectors proteins was observed. Finally our survey also suggests that A. algerae could use a transposable element as a lure strategy to escape the host innate immune system.

Protein turnover forms one of the highest maintenance costs in Lactococcus lactis

Protein turnover plays an important role in cell metabolism by regulating metabolic fluxes. Furthermore, the energy costs for protein turnover have been estimated to account for up to a third of the total energy production during cell replication and hence may represent a major limiting factor in achieving either higher biomass or production yields. This work aimed to measure the specific growth rate (μ)-dependent abundance and turnover rate of individual proteins, estimate the ATP cost for protein production and turnover, and compare this with the total energy balance and other maintenance costs. The lactic acid bacteria model organism Lactococcus lactis was used to measure protein turnover rates at μ = 0.1 and 0.5 h(-1) in chemostat experiments. Individual turnover rates were measured for ~75% of the total proteome. On average, protein turnover increased by sevenfold with a fivefold increase in growth rate, whilst biomass yield increased by 35%. The median turnover rates found were higher than the specific growth rate of the bacterium, which suggests relatively high energy consumption for protein turnover. We found that protein turnover costs alone account for 38 and 47% of the total energy produced at μ = 0.1 and 0.5 h(-1), respectively, and gene ontology groups Energy metabolism and Translation dominated synthesis costs at both growth rates studied. These results reflect the complexity of metabolic changes that occur in response to changes in environmental conditions, and signify the trade-off between biomass yield and the need to produce ATP for maintenance processes.

Analysis of isotopic labeling in peptide fragments by tandem mass spectrometry

Phenotype in multicellular organisms is the consequence of dynamic metabolic events that occur in a spatially dependent fashion. This spatial and temporal complexity presents challenges for investigating metabolism; creating a need for improved methods that effectively probe biochemical events such as amino acid biosynthesis. Isotopic labeling can provide a temporal-spatial recording of metabolic events through, for example, the description of enriched amino acids in the protein pool. Proteins are therefore an important readout of metabolism and can be assessed with modern mass spectrometers. We compared the measurement of isotopic labeling in MS2 spectra obtained from tandem mass spectrometry under either higher energy collision dissociation (HCD) or collision induced dissociation (CID) at varied energy levels. Developing soybean embryos cultured with or without 13C-labeled substrates, and Escherichia coli MG1655 enriched by feeding 7% uniformly labeled glucose served as a source of biological material for protein evaluation. CID with low energies resulted in a disproportionate amount of heavier isotopologues remaining in the precursor isotopic distribution. HCD resulted in fewer quantifiable products; however deviation from predicted distributions were small relative to the CID-based comparisons. Fragment ions have the potential to provide information on the labeling of amino acids in peptides, but our results indicate that without further development the use of this readout in quantitative methods such as metabolic flux analysis is limited.

Quantification of peptide m/z distributions from 13C-labeled cultures with high-resolution mass spectrometry

Isotopic labeling studies of primary metabolism frequently utilize GC/MS to quantify (13)C in protein-hydrolyzed amino acids. During processing some amino acids are degraded, which reduces the size of the measurement set. The advent of high-resolution mass spectrometers provides a tool to assess molecular masses of peptides with great precision and accuracy and computationally infer information about labeling in amino acids. Amino acids that are isotopically labeled during metabolism result in labeled peptides that contain spatial and temporal information that is associated with the biosynthetic origin of the protein. The quantification of isotopic labeling in peptides can therefore provide an assessment of amino acid metabolism that is specific to subcellular, cellular, or temporal conditions. A high-resolution orbital trap was used to quantify isotope labeling in peptides that were obtained from unlabeled and isotopically labeled soybean embryos and Escherichia coli cultures. Standard deviations were determined by estimating the multinomial variance associated with each element of the m/z distribution. Using the estimated variance, quantification of the m/z distribution across multiple scans was achieved by a nonlinear fitting approach. Observed m/z distributions of uniformly labeled E. coli peptides indicated no significant differences between observed and simulated m/z distributions. Alternatively, amino acid m/z distributions obtained from GC/MS were convolved to simulate peptide m/z distributions but resulted in distinct profiles due to the production of protein prior to isotopic labeling. The results indicate that peptide mass isotopologue measurements faithfully represent mass distributions, are suitable for quantification of isotope-labeling-based studies, and provide additional information over existing methods.

Chemical tools for temporally and spatially resolved mass spectrometry-based proteomics

Accurate measurements of the abundances, synthesis rates and degradation rates of cellular proteins are critical for understanding how cells and organisms respond to changes in their environments. Over the past two decades, there has been increasing interest in the use of mass spectrometry for proteomic analysis. In many systems, however, protein diversity as well as cell and tissue heterogeneity limit the usefulness of mass spectrometry-based proteomics. As a result, researchers have had difficulty in systematically identifying proteins expressed within specified time intervals, or low abundance proteins expressed in specific tissues or in a few cells in complex microbial systems. In this review, we present recently-developed tools and strategies that probe these two subsets of the proteome: proteins synthesized during well-defined time intervals--temporally resolved proteomics--and proteins expressed in predetermined cell types, cells or cellular compartments--spatially resolved proteomics--with a focus on chemical and biological mass spectrometry-based methodologies.

Tools for probing and perturbing O-GlcNAc in cells and in vivo

Intracellular glycosylation of nuclear and cytoplasmic proteins involves the addition of N-acetylglucosamine (O-GlcNAc) to serine and threonine residues. This dynamic modification occurs on hundreds of proteins and is involved in various essential biological processes. Because O-GlcNAc is substoichiometric and labile, identifying proteins and sites of modification has been challenging and generally requires proteome enrichment. Here we review recent advances on the implementation of chemical tools to perturb, to detect, and to map O-GlcNAc in living systems. Metabolic and chemoenzymatic labels along with bioorthogonal reactions and quantitative proteomics are enabling investigation of the role of O-GlcNAc in various processes including transcriptional regulation, neurodegeneration, and cell signaling.