Studying macromolecular complex stoichiometries by peptide-based mass spectrometry

Probing Protein Complexes Composition, Stoichiometry, and Interactions by Peptide-Based Mass Spectrometry

The characterization of a protein complex by mass spectrometry can be conducted at different levels. Initial steps regard the qualitative composition of the complex and subunit identification. After that, quantitative information such as stoichiometric ratios and copy numbers for each subunit in a complex or super-complex is acquired. Peptide-based LC-MS/MS offers a wide number of methods and protocols for the characterization of protein complexes. This chapter concentrates on the applications of peptide-based LC-MS/MS for the qualitative, quantitative, and structural characterization of protein complexes focusing on subunit identification, determination of stoichiometric ratio and number of subunits per complex as well as on cross-linking mass spectrometry and hydrogen/deuterium exchange as methods for the structural investigation of the biological assemblies.

Control of intracellular pH and bicarbonate by CO2 diffusion into human sperm

The reaction of CO2 with H2O to form bicarbonate (HCO3-) and H+ controls sperm motility and fertilization via HCO3--stimulated cAMP synthesis. A complex network of signaling proteins participates in this reaction. Here, we identify key players that regulate intracellular pH (pHi) and HCO3- in human sperm by quantitative mass spectrometry (MS) and kinetic patch-clamp fluorometry. The resting pHi is set by amiloride-sensitive Na+/H+ exchange. The sperm-specific putative Na+/H+ exchanger SLC9C1, unlike its sea urchin homologue, is not gated by voltage or cAMP. Transporters and channels implied in HCO3- transport are not detected, and may be present at copy numbers < 10 molecules/sperm cell. Instead, HCO3- is produced by diffusion of CO2 into cells and readjustment of the CO2/HCO3-/H+ equilibrium. The proton channel Hv1 may serve as a unidirectional valve that blunts the acidification ensuing from HCO3- synthesis. This work provides a new framework for the study of male infertility.

Median-Based Absolute Quantification of Proteins Using Fully Unlabeled Generic Internal Standard (FUGIS)

By reporting the molar abundance of proteins, absolute quantification determines their stoichiometry in complexes, pathways, or networks. Typically, absolute quantification relies either on protein-specific isotopically labeled peptide standards or on a semiempirical calibration against the average abundance of peptides chosen from arbitrarily selected proteins. In contrast, a generic protein standard FUGIS (fully unlabeled generic internal standard) requires no isotopic labeling, chemical synthesis, or external calibration and is applicable to quantifying proteins of any organismal origin. The median intensity of the peptide peaks produced by the tryptic digestion of FUGIS is used as a single-point calibrant to determine the molar abundance of any codigested protein. Powered by FUGIS, median-based absolute quantification (MBAQ) outperformed other methods of untargeted proteome-wide absolute quantification.

Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions

Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.

Integrative structure of a 10-megadalton eukaryotic pyruvate dehydrogenase complex from native cell extracts

The pyruvate dehydrogenase complex (PDHc) is a giant enzymatic assembly involved in pyruvate oxidation. PDHc components have been characterized in isolation, but the complex's quaternary structure has remained elusive due to sheer size, heterogeneity, and plasticity. Here, we identify fully assembled Chaetomium thermophilum α-keto acid dehydrogenase complexes in native cell extracts and characterize their domain arrangements utilizing mass spectrometry, activity assays, crosslinking, electron microscopy (EM), and computational modeling. We report the cryo-EM structure of the PDHc core and observe unique features of the previously unknown native state. The asymmetric reconstruction of the 10-MDa PDHc resolves spatial proximity of its components, agrees with stoichiometric data (60 E2p:12 E3BP:∼20 E1p: ≤ 12 E3), and proposes a minimum reaction path among component enzymes. The PDHc shows the presence of a dynamic pyruvate oxidation compartment, organized by core and peripheral protein species. Our data provide a framework for further understanding PDHc and α-keto acid dehydrogenase complex structure and function.

Inferring Protein-Protein Interaction Networks From Mass Spectrometry-Based Proteomic Approaches: A Mini-Review

Studying protein-protein interaction networks provide key evidence for the underlying molecular mechanisms. Mass spectrometry-based proteomic approaches have been playing a pivotal role in deciphering these interaction networks, along with precise quantification for individual interactions. In this mini-review we discuss the available techniques and methods for qualitative and quantitative elucidation of protein-protein interaction networks. We then summarize the down-stream computational strategies for identification and quantification of interactions from those techniques. Finally, we highlight the challenges and limitations of current computational pipelines in eliminating false positive interactors, followed by a summary of the innovative algorithms to address these issues, along with the scope for future improvements.

Differential analysis of combinatorial protein complexes with CompleXChange

BACKGROUND

Although a considerable number of proteins operate as multiprotein complexes and not on their own, organism-wide studies so far are only able to quantify individual proteins or protein-coding genes in a condition-specific manner for a sizeable number of samples, but not their assemblies. Consequently, there exist large amounts of transcriptomic data and an increasing amount of data on proteome abundance, but quantitative knowledge on complexomes is missing. This deficiency impedes the applicability of the powerful tool of differential analysis in the realm of macromolecular complexes. Here, we present a pipeline for differential analysis of protein complexes based on predicted or manually assigned complexes and inferred complex abundances, which can be easily applied on a whole-genome scale.

RESULTS

We observed for simulated data that results obtained by our complex abundance estimation algorithm were in better agreement with the ground truth and physicochemically more reasonable compared to previous efforts that used linear programming while running in a fraction of the time. The practical usability of the method was assessed in the context of transcription factor complexes in human monocyte and lymphoblastoid samples. We demonstrated that our new method is robust against false-positive detection and reports deregulated complexomes that can only be partially explained by differential analysis of individual protein-coding genes. Furthermore we showed that deregulated complexes identified by the tool potentially harbor significant yet unused information content.

CONCLUSIONS

CompleXChange allows to analyze deregulation of the protein complexome on a whole-genome scale by integrating a plethora of input data that is already available. A platform-independent Java binary, a user guide with example data and the source code are freely available at https://sourceforge.net/projects/complexchange/ .

Mass Spectrometry-based Absolute Quantification of 20S Proteasome Status for Controlled Ex-vivo Expansion of Human Adipose-derived Mesenchymal Stromal/Stem Cells

The proteasome controls a multitude of cellular processes through protein degradation and has been identified as a therapeutic target in oncology. However, our understanding of its function and the development of specific modulators are hampered by the lack of a straightforward method to determine the overall proteasome status in biological samples. Here, we present a method to determine the absolute quantity and stoichiometry of ubiquitous and tissue-specific human 20S proteasome subtypes based on a robust, absolute SILAC-based multiplexed LC-Selected Reaction Monitoring (SRM) quantitative mass spectrometry assay with high precision, accuracy, and sensitivity. The method was initially optimized and validated by comparison with a reference ELISA assay and by analyzing the dynamics of catalytic subunits in HeLa cells following IFNγ-treatment and in range of human tissues. It was then successfully applied to reveal IFNγ- and O2-dependent variations of proteasome status during primary culture of Adipose-derived-mesenchymal Stromal/Stem Cells (ADSCs). The results show the critical importance of controlling the culture conditions during cell expansion for future therapeutic use in humans. We hypothesize that a shift from the standard proteasome to the immunoproteasome could serve as a predictor of immunosuppressive and differentiation capacities of ADSCs and, consequently, that quality control should include proteasomal quantification in addition to examining other essential cell parameters. The method presented also provides a new powerful tool to conduct more individualized protocols in cancer or inflammatory diseases where selective inhibition of the immunoproteasome has been shown to reduce side effects.

Local and global influences on protein turnover in neurons and glia

Regulation of protein turnover allows cells to react to their environment and maintain homeostasis. Proteins can show different turnover rates in different tissue, but little is known about protein turnover in different brain cell types. We used dynamic SILAC to determine half-lives of over 5100 proteins in rat primary hippocampal cultures as well as in neuron-enriched and glia-enriched cultures ranging from <1 to >20 days. In contrast to synaptic proteins, membrane proteins were relatively shorter-lived and mitochondrial proteins were longer-lived compared to the population. Half-lives also correlate with protein functions and the dynamics of the complexes they are incorporated in. Proteins in glia possessed shorter half-lives than the same proteins in neurons. The presence of glia sped up or slowed down the turnover of neuronal proteins. Our results demonstrate that both the cell-type of origin as well as the nature of the extracellular environment have potent influences on protein turnover.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Stoichiometry determination of macromolecular membrane protein complexes

Gaining knowledge of the structural makeup of protein complexes is critical to advance our understanding of their formation and functions. This task is particularly challenging for transmembrane protein complexes, and grows ever more imposing with increasing size of these large macromolecular structures. The last 10 years have seen a steep increase in solved high-resolution membrane protein structures due to both new and improved methods in the field, but still most structures of large transmembrane complexes remain elusive. An important first step towards the structure elucidation of these difficult complexes is the determination of their stoichiometry, which we discuss in this review. Knowing the stoichiometry of complex components not only answers unresolved structural questions and is relevant for understanding the molecular mechanisms of macromolecular machines but also supports further attempts to obtain high-resolution structures by providing constraints for structure calculations.

Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS)

Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways.This article is part of the themed issue 'Quantitative mass spectrometry'.

Revealing Higher Order Protein Structure Using Mass Spectrometry

The development of rapid, sensitive, and accurate mass spectrometric methods for measuring peptides, proteins, and even intact protein assemblies has made mass spectrometry (MS) an extraordinarily enabling tool for structural biology. Here, we provide a personal perspective of the increasingly useful role that mass spectrometric techniques are exerting during the elucidation of higher order protein structures. Areas covered in this brief perspective include MS as an enabling tool for the high resolution structural biologist, for compositional analysis of endogenous protein complexes, for stoichiometry determination, as well as for integrated approaches for the structural elucidation of protein complexes. We conclude with a vision for the future role of MS-based techniques in the development of a multi-scale molecular microscope. Graphical Abstract ᅟ.

Insights into Eukaryotic Translation Initiation from Mass Spectrometry of Macromolecular Protein Assemblies

Translation initiation in eukaryotes requires the interplay of at least 10 initiation factors that interact at the different steps of this phase of gene expression. The interactions of initiation factors and related proteins are in general controlled by phosphorylation, which serves as a regulatory switch to turn protein translation on or off. The structures of initiation factors and a complete description of their post-translational modification (PTM) status are therefore required in order to fully understand these processes. In recent years, mass spectrometry has contributed considerably to provide this information and nowadays is proving to be indispensable when studying dynamic heterogeneous protein complexes such as the eukaryotic initiation factors. Herein, we highlight mass spectrometric approaches commonly applied to identify interacting subunits and their PTMs and the structural techniques that allow the architecture of protein complexes to be assessed. We present recent structural investigations of initiation factors and their interactions with other factors and with ribosomes and we assess the models generated. These models allow us to locate PTMs within initiation factor complexes and to highlight possible roles for phosphorylation sites in regulating interaction interfaces.