Deciphering Spatial Protein–Protein Interactions in Brain Using Proximity Labeling

Cellular biomolecular complexes including protein–protein, protein–RNA, and protein–DNA interactions regulate and execute most biological functions. In particular in brain, protein–protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell–cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte–neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.     

Functional Diversity and Evolution of the Drosophila Sperm Proteome

Spermatozoa are central to fertilization and the evolutionary fitness of sexually reproducing organisms. As such, a deeper understanding of sperm proteomes (and associated reproductive tissues) has proven critical to the advancement of the fields of sexual selection and reproductive biology. Due to their extraordinary complexity, proteome depth-of-coverage is dependent on advancements in technology and related bioinformatics, both of which have made significant advancements in the decade since the last Drosophila sperm proteome was published. Here, we provide an updated version of the Drosophila melanogaster sperm proteome (DmSP3) using improved separation and detection methods and an updated genome annotation. Combined with previous versions of the sperm proteome, the DmSP3 contains a total of 3176 proteins, and we provide the first label-free quantitation of the sperm proteome for 2125 proteins. The top 20 most abundant proteins included the structural elements α- and β-tubulins and sperm leucyl-aminopeptidases. Both gene content and protein abundance were significantly reduced on the X chromosome, consistent with prior genomic studies of X chromosome evolution. We identified 9 of the 16 Y-linked proteins, including known testis-specific male fertility factors. We also identified almost one-half of known Drosophila ribosomal proteins in the DmSP3. The role of this subset of ribosomal proteins in sperm is unknown. Surprisingly, our expanded sperm proteome also identified 122 seminal fluid proteins (Sfps), proteins originally identified in the accessory glands. We show that a significant fraction of ‘sperm-associated Sfps’ are recalcitrant to concentrated salt and detergent treatments, suggesting this subclass of Sfps are expressed in testes and may have additional functions in sperm, per se. Overall, our results add to a growing landscape of both sperm and seminal fluid protein biology and in particular provides quantitative evidence at the protein level for prior findings supporting the meiotic sex-chromosome inactivation model for male-specific gene and X chromosome evolution.     

Hypoxia Is a Dominant Remodeler of the Effector T Cell Surface Proteome Relative to Activation and Regulatory T Cell Suppression

Immunosuppressive factors in the tumor microenvironment (TME) impair T cell function and limit the antitumor immune response. T cell surface receptors and surface proteins that influence interactions and function in the TME are proven targets for cancer immunotherapy. However, how the entire surface proteome remodels in primary human T cells in response to specific suppressive factors in the TME remains to be broadly and systematically characterized. Here, using a reductionist cell culture approach with primary human T cells and stable isotopic labeling with amino acids in cell culture–based quantitative cell surface capture glycoproteomics, we examined how two immunosuppressive TME factors, regulatory T cells (Tregs) and hypoxia, globally affect the activated CD8⁺ surface proteome (surfaceome). Surprisingly, coculturing primary CD8⁺ T cells with Tregs only modestly affected the CD8⁺ surfaceome but did partially reverse activation-induced surfaceomic changes. In contrast, hypoxia drastically altered the CD8⁺ surfaceome in a manner consistent with both metabolic reprogramming and induction of an immunosuppressed state. The CD4⁺ T cell surfaceome similarly responded to hypoxia, revealing a common hypoxia-induced surface receptor program. Our surfaceomics findings suggest that hypoxic environments create a challenge for T cell activation. These studies provide global insight into how Tregs and hypoxia remodel the T cell surfaceome and we believe represent a valuable resource to inform future therapeutic efforts to enhance T cell function.     

New Views of Old Proteins: Clarifying the Enigmatic Proteome

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.     

Tissue-Characteristic Expression of Mouse Proteome

The mouse is a valuable model organism for biomedical research. Here, we established a comprehensive spectral library and the data-independent acquisition–based quantitative proteome maps for 41 mouse organs, including some rarely reported organs such as the cornea, retina, and nine paired organs. The mouse spectral library contained 178,304 peptides from 12,320 proteins, including 1678 proteins not reported in previous mouse spectral libraries. Our data suggested that organs from the nervous system and immune system expressed the most distinct proteome compared with other organs. We also found characteristic protein expression of immune-privileged organs, which may help understanding possible immune rejection after organ transplantation. Each tissue type expressed characteristic high-abundance proteins related to its physiological functions. We also uncovered some tissue-specific proteins which have not been reported previously. The testis expressed highest number of tissue-specific proteins. By comparison of nine paired organs including kidneys, testes, and adrenal glands, we found left organs exhibited higher levels of antioxidant enzymes. We also observed expression asymmetry for proteins related to the apoptotic process, tumor suppression, and organ functions between the left and right sides. This study provides a comprehensive spectral library and a quantitative proteome resource for mouse studies.     

Differential Proteome and Interactome Analysis Reveal the Basis of Pleiotropy Associated With the Histidine Methyltransferase Hpm1p

The methylation of histidine is a post-translational modification whose function is poorly understood. Methyltransferase histidine protein methyltransferase 1 (Hpm1p) monomethylates H243 in the ribosomal protein Rpl3p and represents the only known histidine methyltransferase in Saccharomyces cerevisiae. Interestingly, the hpm1 deletion strain is highly pleiotropic, with many extraribosomal phenotypes including improved growth rates in alternative carbon sources. Here, we investigate how the loss of histidine methyltransferase Hpm1p results in diverse phenotypes, through use of targeted mass spectrometry (MS), growth assays, quantitative proteomics, and differential crosslinking MS. We confirmed the localization and stoichiometry of the H243 methylation site, found unreported sensitivities of Δhpm1 yeast to nonribosomal stressors, and identified differentially abundant proteins upon hpm1 knockout with clear links to the coordination of sugar metabolism. We adapted the emerging technique of quantitative large-scale stable isotope labeling of amino acids in cell culture crosslinking MS for yeast, which resulted in the identification of 1267 unique in vivo lysine–lysine crosslinks. By reproducibly monitoring over 350 of these in WT and Δhpm1, we detected changes to protein structure or protein–protein interactions in the ribosome, membrane proteins, chromatin, and mitochondria. Importantly, these occurred independently of changes in protein abundance and could explain a number of phenotypes of Δhpm1, not addressed by expression analysis. Further to this, some phenotypes were predicted solely from changes in protein structure or interactions and could be validated by orthogonal techniques. Taken together, these studies reveal a broad role for Hpm1p in yeast and illustrate how crosslinking MS will be an essential tool for understanding complex phenotypes.     

Multidimensional Dynamics of the Proteome in the Neurodegenerative and Aging Mammalian Brain

The amount of any given protein in the brain is determined by the rates of its synthesis and destruction, which are regulated by different cellular mechanisms. Here, we combine metabolic labeling in live mice with global proteomic profiling to simultaneously quantify both the flux and amount of proteins in mouse models of neurodegeneration. In multiple models, protein turnover increases were associated with increasing pathology. This method distinguishes changes in protein expression mediated by synthesis from those mediated by degradation. In the App^NL-F knockin mouse model of Alzheimer’s disease, increased turnover resulted from imbalances in both synthesis and degradation, converging on proteins associated with synaptic vesicle recycling (Dnm1, Cltc, Rims1) and mitochondria (Fis1, Ndufv1). In contrast to disease models, aging in wild-type mice caused a widespread decrease in protein recycling associated with a decrease in autophagic flux. Overall, this simple multidimensional approach enables a comprehensive mapping of proteome dynamics and identifies affected proteins in mouse models of disease and other live animal test settings.     

Effect of Environmental Temperatures on Proteome Composition of Salmonella enterica Serovar Typhimurium

Salmonella enterica serovar Typhimurium (STM) is a major cause of gastroenteritis and transmitted by consumption of contaminated food. STM is associated to food originating from animals (pork, chicken, eggs) or plants (vegetables, fruits, nuts, and herbs). Infection of warm-blooded mammalian hosts by STM and the underlying complex regulatory network of virulence gene expression depend on various environmental conditions encountered in hosts. However, less is known about the proteome and possible regulatory networks for gene expression of STM outside the preferred host. Nutritional limitations and changes in temperature are the most obvious stresses outside the native host. Thus, we analyzed the proteome profile of STM grown in rich medium (LB medium) or minimal medium (PCN medium) at temperatures ranging from 8 °C to 37 °C. LB medium mimics the nutritional rich environment inside the host, whereas minimal PCN medium represents nutritional limitations outside the host, found during growth of fresh produce (field conditions). Further, the range of temperatures analyzed reflects conditions within natural hosts (37 °C), room temperature (20 °C), during growth under agricultural conditions (16 °C and 12 °C), and during food storage (8 °C). Implications of altered nutrient availability and growth temperature on STM proteomes were analyzed by HPLC/MS-MS and label-free quantification. Our study provides first insights into the complex adaptation of STM to various environmental temperatures, which allows STM not only to infect mammalian hosts but also to enter new infection routes that have been poorly studied so far. With the present dataset, global virulence factors, their impact on infection routes, and potential anti-infective strategies can now be investigated in detail. Especially, we were able to demonstrate functional flagella at 12 °C growth temperature for STM with an altered motility behavior.     

Proteome Remodeling of the Eye Lens at 50 Years Identified With Data-Independent Acquisition

The eye lens is responsible for focusing and transmitting light to the retina. The lens does this in the absence of organelles, yet maintains transparency for at least 5 decades before onset of age-related nuclear cataract (ARNC). It is hypothesized that oxidative stress contributes significantly to ARNC formation. It is in addition hypothesized that transparency is maintained by a microcirculation system that delivers antioxidants to the lens nucleus and exports small molecule waste. Common data-dependent acquisition methods are hindered by dynamic range of lens protein expression and provide limited context to age-related changes in the lens. In this study, we utilized data-independent acquisition mass spectrometry to analyze the urea-insoluble membrane protein fractions of 16 human lenses subdivided into three spatially distinct lens regions to characterize age-related changes, particularly concerning the lens microcirculation system and oxidative stress response. In this pilot cohort, we measured 4788 distinct protein groups, 46,681 peptides, and 7592 deamidated sequences, more than in any previous human lens data-dependent acquisition approach. Principally, we demonstrate that a significant proteome remodeling event occurs at approximately 50 years of age, resulting in metabolic preference for anaerobic glycolysis established with organelle degradation, decreased abundance of protein networks involved in calcium-dependent cell–cell contacts while retaining networks related to oxidative stress response. Furthermore, we identified multiple antioxidant transporter proteins not previously detected in the human lens and describe their spatiotemporal and age-related abundance changes. Finally, we demonstrate that aquaporin-5, among other proteins, is modified with age by post-translational modifications including deamidation and truncation. We suggest that the continued accumulation of each of these age-related outcomes in proteome remodeling contribute to decreased fiber cell permeability and result in ARNC formation.     

Comparative Proteome and Cis-Regulatory Element Analysis Reveals Specific Molecular Pathways Conserved in Dog and Human Brains

Brain development and function are governed by precisely regulated protein expressions in different regions. To date, multiregional brain proteomes have been systematically analyzed only for adult human and mouse brains. To understand the underpinnings of brain development and function, we generated proteomes from six regions of the postnatal brain at three developmental stages of domestic dogs (Canis familiaris), which are special among animals in terms of their remarkable human-like social cognitive abilities. Quantitative analysis of the spatiotemporal proteomes identified region-enriched synapse types at different developmental stages and differential myelination progression in different brain regions. Through integrative analysis of inter-regional expression patterns of orthologous proteins and genome-wide cis-regulatory element frequencies, we found that proteins related with myelination and hippocampus were highly correlated between dog and human but not between mouse and human, although mouse is phylogenetically closer to human. Moreover, the global expression patterns of neurodegenerative disease and autism spectrum disorder–associated proteins in dog brain more resemble human brain than in mouse brain. The high similarity of myelination and hippocampus-related pathways in dog and human at both proteomic and genetic levels may contribute to their shared social cognitive abilities. The inter-regional expression patterns of disease-associated proteins in the brain of different species provide important information to guide mechanistic and translational study using appropriate animal models.     

Phosphoproteome Analysis Identifies a Synaptotagmin-1-Associated Complex Involved in Ischemic Neuron Injury

Cerebral stroke is one of the leading causes of death in adults worldwide. However, the molecular mechanisms of stroke-induced neuron injury are not fully understood. Here, we obtained phosphoproteomic and proteomic profiles of the acute ischemic hippocampus by LC–MS/MS analysis. Quantitative phosphoproteomic analyses revealed that the dysregulated phosphoproteins were involved in synaptic components and neurotransmission. We further demonstrated that phosphorylation of Synaptotagmin-1 (Syt1) at the Thr112 site in cultured hippocampal neurons aggravated oxygen-glucose deprivation–induced neuronal injury. Immature neurons with low expression of Syt1 exhibit slight neuronal injury in a cerebral ischemia model. Administration of the Tat-Syt1^T112A peptide protects neurons against cerebral ischemia-induced injury in vitro and in vivo. Surprisingly, potassium voltage-gated channel subfamily KQT member 2 (Kcnq2) interacted with Syt1 and Annexin A6 (Anxa6) and alleviated Syt1-mediated neuronal injury upon oxygen-glucose deprivation treatment. These results reveal a mechanism underlying neuronal injury and may provide new targets for neuroprotection after acute cerebral ischemia onset.     

A Complex Connection Between the Diversity of Human Gastric Mucin O-Glycans,Helicobacter pylori Binding,Helicobacter Infection and Fucosylation

Helicobacter pylori colonizes the stomach of half of the human population. Most H. pylori are located in the mucus layer, which is mainly comprised by glycosylated mucins. Using mass spectrometry, we identified 631 glycans (whereof 145 were fully characterized and the remainder assigned as compositions) on mucins isolated from 14 Helicobacter spp.-infected and 14 Helicobacter spp.-noninfected stomachs. Only six identified glycans were common to all individuals, from a total of 60 to 189 glycans in each individual. An increased number of unique glycan structures together with an increased intraindividual diversity and larger interindividual variation were identified among O-glycans from Helicobacter spp.-infected stomachs compared with noninfected stomachs. H. pylori strain J99, which carries the blood group antigen–binding adhesin (BabA), the sialic acid–binding adhesin (SabA), and the LacdiNAc-binding adhesin, bound both to Lewis b (Leb)-positive and Leb-negative mucins. Among Leb-positive mucins, H. pylori J99 binding was higher to mucins from Helicobacter spp.-infected individuals than noninfected individuals. Statistical correlation analysis, binding experiments with J99 wt, and J99ΔbabAΔsabA and inhibition experiments using synthetic glycoconjugates demonstrated that the differences in H. pylori-binding ability among these four groups were governed by BabA-dependent binding to fucosylated structures. LacdiNAc levels were lower in mucins that bound to J99 lacking BabA and SabA than in mucins that did not, suggesting that LacdiNAc did not significantly contribute to the binding. We identified 24 O-glycans from Leb-negative mucins that correlated well with H. pylori binding whereof 23 contained α1,2-linked fucosylation. The large and diverse gastric glycan library identified, including structures that correlated with H. pylori binding, could be used to select glycodeterminants to experimentally investigate further for their importance in host–pathogen interactions and as candidates to develop glycan-based therapies.     

Proximity labeling technologies to illuminate glycan–protein interactions

Glycosylation is a ubiquitous post-translational modification read by glycan-binding proteins (GBP) to encode important functions, but a robust understanding of these interactions and their consequences can be challenging to uncover. Glycan-GBP interactions are transient and weak, making them difficult to capture, and glycosylation is dynamic and heterogenous, necessitating study in native cellular environments to identify endogenous ligands. Proximity labeling, an experimental innovation that labels biomolecules close to a protein of interest, has recently emerged as a powerful strategy to overcome these limitations, allowing interactors to be tagged in cells for subsequent enrichment and identification by mass spectrometry-based proteomics. We will describe this nascent technique and discuss its applications in the last five years with different GBP classes, including Siglecs, galectins, and non-human lectins.     

SIMSI-Transfer: Software-Assisted Reduction of Missing Values in Phosphoproteomic and Proteomic Isobaric Labeling Data Using Tandem Mass Spectrum Clustering

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets. To this end, we developed SIMSI-Transfer (Similarity-based Isobaric Mass Spectra 2 [MS2] Identification Transfer), a software tool that extends our previously developed software MaRaCluster (© Matthew The) by clustering similar tandem MS2 from multiple TMT experiments. SIMSI-Transfer is based on the assumption that similarity-clustered MS2 spectra represent the same peptide. Therefore, peptide identifications made by database searching in one TMT batch can be transferred to another TMT batch in which the same peptide was fragmented but not identified. To assess the validity of this approach, we tested SIMSI-Transfer on masked search engine identification results and recovered >80% of the masked identifications while controlling errors in the transfer procedure to below 1% false discovery rate. Applying SIMSI-Transfer to six published full proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium led to an increase of 26 to 45% of identified MS2 spectra with TMT quantifications. This significantly decreased the number of missing values across batches and, in turn, increased the number of peptides and proteins identified in all TMT batches by 43 to 56% and 13 to 16%, respectively.     

Harmonizing Labeling and Analytical Strategies to Obtain Protein Turnover Rates in Intact Adult Animals

Changes in the abundance of individual proteins in the proteome can be elicited by modulation of protein synthesis (the rate of input of newly synthesized proteins into the protein pool) or degradation (the rate of removal of protein molecules from the pool). A full understanding of proteome changes therefore requires a definition of the roles of these two processes in proteostasis, collectively known as protein turnover. Because protein turnover occurs even in the absence of overt changes in pool abundance, turnover measurements necessitate monitoring the flux of stable isotope–labeled precursors through the protein pool such as labeled amino acids or metabolic precursors such as ammonium chloride or heavy water. In cells in culture, the ability to manipulate precursor pools by rapid medium changes is simple, but for more complex systems such as intact animals, the approach becomes more convoluted. Individual methods bring specific complications, and the suitability of different methods has not been comprehensively explored. In this study, we compare the turnover rates of proteins across four mouse tissues, obtained from the same inbred mouse strain maintained under identical husbandry conditions, measured using either [¹³C₆]lysine or [²H₂]O as the labeling precursor. We show that for long-lived proteins, the two approaches yield essentially identical measures of the first-order rate constant for degradation. For short-lived proteins, there is a need to compensate for the slower equilibration of lysine through the precursor pools. We evaluate different approaches to provide that compensation. We conclude that both labels are suitable, but careful determination of precursor enrichment kinetics in amino acid labeling is critical and has a considerable influence on the numerical values of the derived protein turnover rates.