Mass Spectrometry-Based Protein Complex Profiling in Time and Space

Spatiotemporal and direct capturing global substrates of lysine-modifying enzymes in living cells

Protein-modifying enzymes regulate the dynamics of myriad post-translational modification (PTM) substrates. Precise characterization of enzyme-substrate associations is essential for the molecular basis of cellular function and phenotype. Methods for direct capturing global substrates of protein-modifying enzymes in living cells are with many challenges, and yet largely unexplored. Here, we report a strategy to directly capture substrates of lysine-modifying enzymes via PTM-acceptor residue crosslinking in living cells, enabling global profiling of substrates of PTM-enzymes and validation of PTM-sites in a straightforward manner. By integrating enzymatic PTM-mechanisms, and genetically encoding residue-selective photo-crosslinker into PTM-enzymes, our strategy expands the substrate profiles of both bacterial and mammalian lysine acylation enzymes, including bacterial lysine acylases PatZ, YiaC, LplA, TmcA, and YjaB, as well as mammalian acyltransferases GCN5 and Tip60, leading to discovery of distinct yet functionally important substrates and acylation sites. The concept of direct capturing substrates of PTM-enzymes via residue crosslinking may extend to the other types of amino acid residues beyond lysine, which has the potential to facilitate the investigation of diverse types of PTMs and substrate-enzyme interactive proteomics.

Novel Ag-modified vanadate nanosheets for determination of small organic molecules with laser desorption ionization mass spectrometry

Laser desorption ionization mass spectrometry (LDI-MS) aroused intensive concerns for the merits of label-free and high-throughput analysis. Here, we designed a silver nanoparticles (AgNP)-modified indium vanadate nanosheets with doping samarium (AgNP@InVO4:Sm) nanosheets. The developed AgNP@InVO4:Sm nanosheets (AIVON) were synthesized based on the microemulsion-mediated solvothermal method and ultraviolet-assisted in situ formation of AgNP, then for the first time applied as a matrix in LDI-MS analysis. With the advantages including enhanced MS signal, little matrix-related background, high reproducibility, and good salt tolerance, AIVON exhibited much better prospect than non-modified indium vanadate nanosheets with doping samarium (IVON) and traditional organic matrix, thus allowing sensitive MS detection for a wide range of low-molecular-weight (LMW) molecules. Moreover, by coupling with headspace sampling thin-film microextraction (TFME), a kind of representative pollutant chlorophenols were identified and quantified via AIVON-assisted LDI-MS in environmental and biological samples. Volatile LMW pollutants could be preconcentrated after TFME, hence a sensitive and rapid assay with negligible sample matrix effect was realized by using AIVON-assisted LDI-MS. It is anticipated that this novel nano-matrix AIVON and the proposed TFME coupling detection strategy were of competitive merits for LDI-MS analysis in the fields of environment, biomedicine, and agriculture.

Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation

Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .

Scaled-Down Thermal Profiling and Coaggregation Analysis of the Proteome for Drug Target and Protein Interaction Analysis

Thermal proteome profiling (TPP), an experimental technique combining the cellular thermal shift assay (CETSA) with quantitative protein mass spectrometry (MS), identifies interactions of drugs and chemicals with endogenous proteins. Thermal proximity coaggregation (TPCA) profiling extended TPP to study the intracellular dynamics of protein complexes. In TPP and TPCA, samples are subjected to multiple denaturing temperatures, each requiring over 100 μg of proteins, which restricts their applications for rare cells and precious clinical samples. We developed a workflow termed STASIS (scaled-down thermal profiling and coaggregation analysis with SISPROT) that scales down the required protein to as low as 1 μg per temperature. This is achieved by heating and centrifugation using the same PCR tube, processing samples with the SISPROT technology (simple and integrated spintip-based proteomics technology), and tip-based manual fractionation of TMT-labeled peptides. We evaluate the STASIS workflow with starting protein quantities of 10, 5, and 1 μg per temperature prior to heating, identifying between 4000 and 5000 proteins with 6 h of acquisition time. Importantly, we observed a high correlation in the Tm of proteins with minimal difference in TPCA performance for predicting protein complexes. Moreover, STASIS could identify the targets of methotrexate and panobinostat with high precision with 1 μg of proteins per temperature. In conclusion, STASIS is a robust cost-effective technique for target deconvolution and extended TPCA to rare primary cells and precious clinical samples for the analysis of protein complexes.

Residue selective crosslinking of proteins through photoactivatable or proximity-enabled reactivity

Photo- and chemical crosslinking of proteins have offered various avenues for studying protein structure and protein interactions with biomolecules. Conventional photoactivatable groups generally lack reaction selectivity toward amino acid residues. New photoactivatable groups reacting with selected residues have emerged recently, increasing crosslinking efficiency and facilitating crosslink identification. Traditional chemical crosslinking usually employs highly reactive functional groups, while recent advance has developed latent reactive groups with reactivity triggered by proximity, which reduce spurious crosslinks and improve biocompatibility. The employment of these residue selective chemical functional groups, activated by light or proximity, in small molecule crosslinkers and in genetically encoded unnatural amino acids is summarized. Together with new software development in identifying protein crosslinks, residue selective crosslinking has enhanced the research of elusive protein-protein interactions in vitro, in cell lysate, and in live cells. Residue selective crosslinking is expected to expand to other methods for the investigation of various protein-biomolecule interactions.

Integrated mass spectrometry strategy for functional protein complex discovery and structural characterization

The discovery of functional protein complex and the interrogation of the complex structure-function relationship (SFR) play crucial roles in the understanding and intervention of biological processes. Affinity purification-mass spectrometry (AP-MS) has been proved as a powerful tool in the discovery of protein complexes. However, validation of these novel protein complexes as well as elucidation of their molecular interaction mechanisms are still challenging. Recently, native top-down MS (nTDMS) is rapidly developed for the structural analysis of protein complexes. In this review, we discuss the integration of AP-MS and nTDMS in the discovery and structural characterization of functional protein complexes. Further, we think the emerging artificial intelligence (AI)-based protein structure prediction is highly complementary to nTDMS and can promote each other. We expect the hybridization of integrated structural MS with AI prediction to be a powerful workflow in the discovery and SFR investigation of functional protein complexes.

Coordinate-Dependent Drift-Diffusion Reveals the Kinetic Intermediate Traps of Top7-Based Proteins

The computer-designed Top7 served as a scaffold to produce immunoreactive proteins by grafting of the 2F5 HIV-1 antibody epitope (Top7-2F5) followed by biotinylation (Top7-2F5-biotin). The resulting nonimmunoglobulin affinity proteins were effective in inducing and detecting the HIV-1 antibody. However, the grafted Top7-2F5 design led to protein aggregation, as opposed to the soluble biotinylated Top7-2F5-biotin. The structure-based model predicted that the thermodynamic cooperativity of Top7 increases after grafting and biotin-labeling, reducing their intermediate state populations. In this work, the folding kinetic traps that might contribute to the aggregation propensity are investigated by the diffusion theory. Since the engineered proteins have similar sequence and structural homology, they served as protein models to study the kinetic intermediate traps that were uncovered by characterizing the position-dependent drift-velocity (v(Q)) and the diffusion (D(Q)) coefficients. These coordinate-dependent coefficients were taken into account to obtain the folding and transition path times over the free energy transition states containing the intermediate kinetic traps. This analysis may be useful to predict the aggregated kinetic traps of scaffold-epitope proteins that might compose novel diagnostic and therapeutic platforms.

PCLassoLog: A protein complex-based, group Lasso-logistic model for cancer classification and risk protein complex discovery

Risk gene identification has attracted much attention in the past two decades. Since most genes need to be translated into proteins and cooperate with other proteins to form protein complexes to carry out cellular functions, which significantly extends the functional diversity of individual proteins, revealing the molecular mechanism of cancer from a comprehensive perspective needs to shift from identifying individual risk genes toward identifying risk protein complexes. Here, we embed protein complexes into the regularized learning framework and propose a protein complex-based, group Lasso-logistic model (PCLassoLog) to discover risk protein complexes. Experiments on deep proteomic data of two cancer types show that PCLassoLog yields superior predictive performance on independent datasets. More importantly, PCLassoLog identifies risk protein complexes that not only contain individual risk proteins but also incorporate close partners that synergize with them. Furthermore, selection probabilities are calculated and two other protein complex-based models are proposed to complement PCLassoLog in identifying reliable risk protein complexes. Based on PCLassoLog, a pan-cancer analysis is performed to identify risk protein complexes in 12 cancer types. Finally, PCLassoLog is used to discover risk protein complexes associated with gene mutation. We implement all protein complex-based models as an R package PCLassoReg, which may serve as an effective tool to discover risk protein complexes in various contexts.

Thin Films of Lanthanide Stearates as Modifiers of the Q-Sense Device Sensor for Studying Insulin Adsorption

This article presents new possibilities of using thin films of lanthanide stearates as sorbent materials. Modification of the Q-sense device resonator with monolayers of lanthanide stearates by the Langmuir-Schaeffer method made it possible to study the process of insulin protein adsorption on the surface of new thin-film sorbents. The resulting films were also characterized by compression isotherms, chemical analysis, scanning electron microscopy, and mass spectrometry. The transition of stearic acid to salt was recorded by IR spectroscopy. Using the LDI MS method, the main component of thin films, lanthanide distearate, was established. The presence of Eu²⁺ in thin films was revealed. In the case of europium stearate, the maximum value of insulin adsorption was obtained, -1.67·10^-10 mole/cm². The findings suggest the possibility of using thin films of lanthanide stearates as a sorption material for the proteomics determination of the quantitative protein content in complex fluid systems by specific adsorption on modified surfaces and isolation of such proteins from complex mixtures.

Biotin-painted proteins have thermodynamic stability switched by kinetic folding routes

Biotin-labeled proteins are widely used as tools to study protein-protein interactions and proximity in living cells. Proteomic methods broadly employ proximity-labeling technologies based on protein biotinylation in order to investigate the transient encounters of biomolecules in subcellular compartments. Biotinylation is a post-translation modification in which the biotin molecule is attached to lysine or tyrosine residues. So far, biotin-based technologies proved to be effective instruments as affinity and proximity tags. However, the influence of biotinylation on aspects such as folding, binding, mobility, thermodynamic stability, and kinetics needs to be investigated. Here, we selected two proteins [biotin carboxyl carrier protein (BCCP) and FKBP3] to test the influence of biotinylation on thermodynamic and kinetic properties. Apo (without biotin) and holo (biotinylated) protein structures were used separately to generate all-atom structure-based model simulations in a wide range of temperatures. Holo BCCP contains one biotinylation site, and FKBP3 was modeled with up to 23 biotinylated lysines. The two proteins had their estimated thermodynamic stability changed by altering their energy landscape. In all cases, after comparison between the apo and holo simulations, differences were observed on the free-energy profiles and folding routes. Energetic barriers were altered with the density of states clearly showing changes in the transition state. This study suggests that analysis of large-scale datasets of biotinylation-based proximity experiments might consider possible alterations in thermostability and folding mechanisms imposed by the attached biotins.

In-Depth In Vivo Crosslinking in Minutes by a Compact, Membrane-Permeable, and Alkynyl-Enrichable Crosslinker

Chemical crosslinking coupled with mass spectrometry (CXMS) has emerged as a powerful technique to obtain the dynamic conformations and interaction interfaces of protein complexes. Limited by the poor cell membrane permeability, chemical reactivity, and biocompatibility of crosslinkers, in vivo crosslinking to capture the dynamics of protein complexes with finer temporal resolution and higher coverage is attractive but challenging. In this work, a trifunctional crosslinker bis(succinimidyl) with propargyl tag (BSP), involving compact size, proper amphipathy, and enrichment capacity, was developed to enable better cell membrane permeability and efficient crosslinking in 5 min without obvious cellular interference. Followed by a two-step enrichment method based on click chemistry at the peptide level, 13,098 crosslinked peptides (5068 inter-crosslinked peptides and 8030 intra-crosslinked peptides) were identified under the data threshold of peptide-spectrum matches (PSMs) ≥2 on the basic of the FDR control of 1%, which was the most comprehensive dataset for homo species cells by a non-cleavable crosslinker. Besides, the interactome network comprising 1519 proteins connected by 2913 interaction edges in various intracellular compartments, as well as 80S ribosome structural dynamics, were characterized, showing the great potential of our in vivo crosslinking approach in minutes. All these results demonstrated that our developed BSP could provide a valuable toolkit for the in-depth in vivo analysis of protein-protein interactions (PPIs) and protein architectures with finer temporal resolution.

Cross-linking and mass spectrometry as a tool for studying the structural biology of ribonucleoproteins

Cross-linking and mass spectrometry (XL-MS) workflows represent an increasingly popular technique for low-resolution structural studies of macromolecular complexes. Cross-linking reactions take place in the solution state, capturing contact sites between components of a complex that represent the native, functionally relevant structure. Protein-protein XL-MS protocols are widely adopted, providing precise localization of cross-linking sites to single amino acid positions within a pair of cross-linked peptides. In contrast, protein-RNA XL-MS workflows are evolving rapidly and differ in their ability to localize interaction regions within the RNA sequence. Here, we review protein-protein and protein-RNA XL-MS workflows, and discuss their applications in studies of protein-RNA complexes. The examples highlight the complementary value of XL-MS in structural studies of protein-RNA complexes, where more established high-resolution techniques might be unable to produce conclusive data.

Selective Removal of Unhydrolyzed Monolinked Peptides from Enriched Crosslinked Peptides To Improve the Coverage of Protein Complex Analysis

Chemical crosslinking combined with mass spectrometry (CXMS) has allowed the global characterization of protein complexes with high throughput and accuracy. Although enrichable crosslinkers have been introduced to exclude the interference of regular peptides, the crosslinked peptide identification is still severely inhibited by a large amount of monolinked peptides. In this work, we proposed a strategy called MoTE (unhydrolyzed Monolinked peptide Targeting Elimination) to remove the unhydrolyzed monolinked peptides, while enriching crosslinked peptides for regular peptide removal. In this strategy, followed by the crosslinking reaction, an amine biotin reagent was used to block the unreacted reactive groups on the crosslinker, and subsequently, the crosslinked proteins were tagged by a cleavable biotin-azide ligand based on click chemistry for enrichment. The following crosslinked protein digestion, purification by streptavidin beads, and release by chemical cleavage of the biotin-azide ligand were sequentially performed. In this case, the amine biotin-blocked unhydrolyzed monolinked peptides with the unbreakable arm remained on the streptavidin beads, which realized selective removal without any additional steps. By combining in vivo crosslinking with our proposed MoTE strategy for protein complex analysis of the HeLa cell, the number of high reliability (score <E-04) interlinked peptides increased 43% in a single LC-MS run, and the structural and interaction mapping capacity for low-abundance and flexible proteins were greatly enhanced. These results demonstrated that the MoTE strategy has great potential to improve the coverage of CXMS-based protein complex analysis. Notably, it was also the first report focused on removing the highly abundant monolinked peptides.

Chemical biology approaches to study histone interactors

Protein-protein interactions (PPIs) in the nucleus play key roles in transcriptional regulation and ensure genomic stability. Critical to this are histone-mediated PPI networks, which are further fine-tuned through dynamic post-translational modification. Perturbation to these networks leads to genomic instability and disease, presenting epigenetic proteins as key therapeutic targets. This mini-review will describe progress in mapping the combinatorial histone PTM landscape, and recent chemical biology approaches to map histone interactors. Recent advances in mapping direct interactors of histone PTMs as well as local chromatin interactomes will be highlighted, with a focus on mass-spectrometry based workflows that continue to illuminate histone-mediated PPIs in unprecedented detail.

A System-Wide Spatiotemporal Characterization of ErbB Receptor Complexes by Subcellular Fractionation Integrated Quantitative Mass Spectrometry

Precise spatiotemporal regulation of protein complex assembly is essential for cells to achieve a meaningful rely of information flow via intracellular signaling networks in response to extracellular cues, whose disruption would lead to disease. Although various attempts have been made for spatial and/or temporal analysis of protein complexes, it is still a challenge to track cell-wide dynamics of a particular protein complex under physiological conditions. Here we describe a workflow that combines endogenous expression of tagged proteins, organelle marker distribution-directed subcellular fractionation, scaffold protein-mediated receptor complex purification, and targeted proteomics for spatiotemporal quantification of protein complexes in whole cell scale. We applied our method to investigate the assembly kinetics of EGF-dependent ErbB receptor complexes. After fractionation using the density gradient centrifugation and organelle assignment based on organelle markers, endogenous ErbB complex in different subcellular fractionation was efficiently enriched. By using targeted mass spectrometry, ErbB complex components that expressed medium to low level was precisely quantified with in-depth coverage, simultaneously in time and subcellular spaces. Our results revealed a sophisticated scheme of complex behaviors characterized by multiple subcomplexes with distinct molecular composition formed across subcellular fractions enriched with cytosol, plasma membrane, endosome, or mitochondria, implying organelle-specific ErbB functions. Remarkably, our results demonstrated for the first time that activated ErbB receptors might increase their signaling range through promoting a cytosolic, receptor-free subcomplex, consisting of Shc1, Grb2, Arhgef5, Garem1, and Lrrk1. These findings emphasize the potential of our strategy as a powerful tool to study spatiotemporal dynamics of protein complexes.