Interaction landscape of membrane-protein complexes in Saccharomyces cerevisiae

Meta-analysis of dispensable essential genes and their interactions with bypass suppressors

Genes have been historically classified as essential or non-essential based on their requirement for viability. However, genomic mutations can sometimes bypass the requirement for an essential gene, challenging the binary classification of gene essentiality. Such dispensable essential genes represent a valuable model for understanding the incomplete penetrance of loss-of-function mutations often observed in natural populations. Here, we compiled data from multiple studies on essential gene dispensability in Saccharomyces cerevisiae to comprehensively characterize these genes. In analyses spanning different evolutionary timescales, dispensable essential genes exhibited distinct phylogenetic properties compared with other essential and non-essential genes. Integration of interactions with suppressor genes that can bypass the gene essentiality revealed the high functional modularity of the bypass suppression network. Furthermore, dispensable essential and bypass suppressor gene pairs reflected simultaneous changes in the mutational landscape of S. cerevisiae strains. Importantly, species in which dispensable essential genes were non-essential tended to carry bypass suppressor mutations in their genomes. Overall, our study offers a comprehensive view of dispensable essential genes and illustrates how their interactions with bypass suppressors reflect evolutionary outcomes.

Co-fractionation-mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain

Human mitochondrial (mt) protein assemblies are vital for neuronal and brain function, and their alteration contributes to many human disorders, e.g., neurodegenerative diseases resulting from abnormal protein-protein interactions (PPIs). Knowledge of the composition of mt protein complexes is, however, still limited. Affinity purification mass spectrometry (MS) and proximity-dependent biotinylation MS have defined protein partners of some mt proteins, but are too technically challenging and laborious to be practical for analyzing large numbers of samples at the proteome level, e.g., for the study of neuronal or brain-specific mt assemblies, as well as altered mtPPIs on a proteome-wide scale for a disease of interest in brain regions, disease tissues or neurons derived from patients. To address this challenge, we adapted a co-fractionation-MS platform to survey native mt assemblies in adult mouse brain and in human NTERA-2 embryonal carcinoma stem cells or differentiated neuronal-like cells. The workflow consists of orthogonal separations of mt extracts isolated from chemically cross-linked samples to stabilize PPIs, data-dependent acquisition MS to identify co-eluted mt protein profiles from collected fractions and a computational scoring pipeline to predict mtPPIs, followed by network partitioning to define complexes linked to mt functions as well as those essential for neuronal and brain physiological homeostasis. We developed an R/CRAN software package, Macromolecular Assemblies from Co-elution Profiles for automated scoring of co-fractionation-MS data to define complexes from mtPPI networks. Presently, the co-fractionation-MS procedure takes 1.5-3.5 d of proteomic sample preparation, 31 d of MS data acquisition and 8.5 d of data analyses to produce meaningful biological insights.

The social and structural architecture of the yeast protein interactome

Cellular functions are mediated by protein-protein interactions, and mapping the interactome provides fundamental insights into biological systems. Affinity purification coupled to mass spectrometry is an ideal tool for such mapping, but it has been difficult to identify low copy number complexes, membrane complexes and complexes that are disrupted by protein tagging. As a result, our current knowledge of the interactome is far from complete, and assessing the reliability of reported interactions is challenging. Here we develop a sensitive high-throughput method using highly reproducible affinity enrichment coupled to mass spectrometry combined with a quantitative two-dimensional analysis strategy to comprehensively map the interactome of Saccharomyces cerevisiae. Thousand-fold reduced volumes in 96-well format enabled replicate analysis of the endogenous GFP-tagged library covering the entire expressed yeast proteome1. The 4,159 pull-downs generated a highly structured network of 3,927 proteins connected by 31,004 interactions, doubling the number of proteins and tripling the number of reliable interactions compared with existing interactome maps2. This includes very-low-abundance epigenetic complexes, organellar membrane complexes and non-taggable complexes inferred by abundance correlation. This nearly saturated interactome reveals that the vast majority of yeast proteins are highly connected, with an average of 16 interactors. Similar to social networks between humans, the average shortest distance between proteins is 4.2 interactions. AlphaFold-Multimer provided novel insights into the functional roles of previously uncharacterized proteins in complexes. Our web portal ( www.yeast-interactome.org ) enables extensive exploration of the interactome dataset.

Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retention

Gene duplication is common across the tree of life, including yeast and humans, and contributes to genomic robustness. In this study, we examined changes in the subcellular localization and abundance of proteins in response to the deletion of their paralogs originating from the whole-genome duplication event, which is a largely unexplored mechanism of functional divergence. We performed a systematic single-cell imaging analysis of protein dynamics and screened subcellular redistribution of proteins, capturing their localization and abundance changes, providing insight into forces determining paralog retention. Paralogs showed dependency, whereby proteins required their paralog to maintain their native abundance or localization, more often than compensation. Network feature analysis suggested the importance of functional redundancy and rewiring of protein and genetic interactions underlying redistribution response of paralogs. Translation of non-canonical protein isoform emerged as a novel compensatory mechanism. This study provides new insights into paralog retention and evolutionary forces that shape genomes.

Protein-protein interaction and site prediction using transfer learning

The advanced language models have enabled us to recognize protein-protein interactions (PPIs) and interaction sites using protein sequences or structures. Here, we trained the MindSpore ProteinBERT (MP-BERT) model, a Bidirectional Encoder Representation from Transformers, using protein pairs as inputs, making it suitable for identifying PPIs and their respective interaction sites. The pretrained model (MP-BERT) was fine-tuned as MPB-PPI (MP-BERT on PPI) and demonstrated its superiority over the state-of-the-art models on diverse benchmark datasets for predicting PPIs. Moreover, the model's capability to recognize PPIs among various organisms was evaluated on multiple organisms. An amalgamated organism model was designed, exhibiting a high level of generalization across the majority of organisms and attaining an accuracy of 92.65%. The model was also customized to predict interaction site propensity by fine-tuning it with PPI site data as MPB-PPISP. Our method facilitates the prediction of both PPIs and their interaction sites, thereby illustrating the potency of transfer learning in dealing with the protein pair task.

Identification and characterization of protein interactions with the major Niemann-Pick type C disease protein in yeast reveals pathways of therapeutic potential

Niemann-Pick type C (NP-C) disease is a rare lysosomal storage disease caused by mutations in NPC1 (95% cases) or NPC2 (5% cases). These proteins function together in cholesterol egress from the lysosome, whereby upon mutation, cholesterol and other lipids accumulate causing major pathologies. However, it is not fully understood how cholesterol is transported from NPC1 residing at the lysosomal membrane to the endoplasmic reticulum (ER) and plasma membrane. The yeast ortholog of NPC1, Niemann-Pick type C-related protein-1 (Ncr1), functions similarly to NPC1; when transfected into a mammalian cell lacking NPC1, Ncr1 rescues the diagnostic hallmarks of cholesterol and sphingolipid accumulation. Here, we aimed to identify and characterize protein-protein interactions (PPIs) with the yeast Ncr1 protein. A genome-wide split-ubiquitin membrane yeast two-hybrid (MYTH) protein interaction screen identified 11 ER membrane-localized, full-length proteins interacting with Ncr1 at the lysosomal/vacuolar membrane. These highlight the importance of ER-vacuole membrane interface and include PPIs with the Cyb5/Cbr1 electron transfer system, the ceramide synthase complex, and the Sec61/Sbh1 protein translocation complex. These PPIs were not detected in a sterol auxotrophy condition and thus depend on normal sterol metabolism. To provide biological context for the Ncr1-Cyb5 PPI, a yeast strain lacking this PPI (via gene deletions) exhibited altered levels of sterols and sphingolipids including increased levels of glucosylceramide that mimic NP-C disease. Overall, the results herein provide new physical and genetic interaction models to further use the yeast model of NP-C disease to better understand human NP-C disease.

Building the Environmental Chemical-Protein Interaction Network (eCPIN): An Exposome-Wide Strategy for Bioactive Chemical Contaminant Identification

Although advancements in nontargeted analysis have made it possible to detect hundreds of chemical contaminants in a single run, the current environmental toxicology approaches lag behind, precluding the transition from analytical chemistry efforts to health risk assessment. We herein highlighted a recently developed "top-down" bioanalytical method, protein Affinity Purification with Nontargeted Analysis (APNA), to screen for bioactive chemical contaminants at the "exposome-wide" level. To achieve this, a tagged functional protein is employed as a "bait" to directly isolate bioactive chemical contaminants from environmental mixtures, which are further identified by nontargeted analysis. Advantages of this protein-guided approach, including the discovery of new bioactive ligands as well as new protein targets for known chemical contaminants, were highlighted by several case studies. Encouraged by these successful applications, we further proposed a framework, i.e., the environmental Chemical-Protein Interaction Network (eCPIN), to construct a complete map of the 7 billion binary interactions between all chemical contaminants (>350,000) and human proteins (∼20,000) via APNA. The eCPIN could be established in three stages through strategically prioritizing the ∼20,000 human proteins, such as focusing on the 48 nuclear receptors (e.g., thyroid hormone receptors) in the first stage. The eCPIN will provide an unprecedented throughput for screening bioactive chemical contaminants at the exposome-wide level and facilitate the identification of molecular initiating events at the proteome-wide level.

Development of a Method Combining Peptidiscs and Proteomics to Identify, Stabilize, and Purify a Detergent-Sensitive Membrane Protein Assembly

The peptidisc membrane mimetic enables global reconstitution of the bacterial membrane proteome into water-soluble detergent-free particles, termed peptidisc libraries. We present here a method that combines peptidisc libraries and chromosomal-level gene tagging technology with affinity purification and mass spectrometry (AP/MS) to stabilize and identify fragile membrane protein complexes that exist at native expression levels. This method circumvents common artifacts caused by bait protein overproduction and protein complex dissociation due to lengthy exposure to detergents during protein isolation. Using the Escherichia coli Sec system as a case study, we identify an expanded version of the translocon, termed the HMD complex, consisting of nine different integral membrane subunits. This complex is stable in peptidiscs but dissociates in detergents. Guided by this native-level proteomic information, we design and validate a procedure that enables purification of the HMD complex with minimal protein dissociation. These results highlight the utility of peptidiscs and AP/MS to discover and stabilize fragile membrane protein assemblies. Data are available via ProteomeXchange with identifier PXD032315.

Antigen identification and high-throughput interaction mapping by reprogramming viral entry

Deciphering immune recognition is critical for understanding a broad range of diseases and for the development of effective vaccines and immunotherapies. Efforts to do so are limited by a lack of technologies capable of simultaneously capturing the complexity of adaptive immunoreceptor repertoires and the landscape of potential antigens. To address this, we present receptor-antigen pairing by targeted retroviruses, which combines viral pseudotyping and molecular engineering approaches to enable one-pot library-on-library interaction screens by displaying antigens on the surface of lentiviruses and encoding their identity in the viral genome. Antigen-specific viral infection of cell lines expressing human T or B cell receptors allows readout of both antigen and receptor identities via single-cell sequencing. The resulting system is modular, scalable and compatible with any cell type. These techniques provide a suite of tools for targeted viral entry, molecular engineering and interaction screens with broad potential applications.

The mechanisms of integral membrane protein biogenesis

Roughly one quarter of all genes code for integral membrane proteins that are inserted into the plasma membrane of prokaryotes or the endoplasmic reticulum membrane of eukaryotes. Multiple pathways are used for the targeting and insertion of membrane proteins on the basis of their topological and biophysical characteristics. Multipass membrane proteins span the membrane multiple times and face the additional challenges of intramembrane folding. In many cases, integral membrane proteins require assembly with other proteins to form multi-subunit membrane protein complexes. Recent biochemical and structural analyses have provided considerable clarity regarding the molecular basis of membrane protein targeting and insertion, with tantalizing new insights into the poorly understood processes of multipass membrane protein biogenesis and multi-subunit protein complex assembly.

The evolving biology of the proton‐coupled folate transporter: New insights into regulation, structure, and mechanism

The human proton‐coupled folate transporter (PCFT; SLC46A1) or hPCFT was identified in 2006 as the principal folate transporter involved in the intestinal absorption of dietary folates. A rare autosomal recessive hereditary folate malabsorption syndrome is attributable to human SLC46A1 variants. The recognition that hPCFT was highly expressed in many tumors stimulated substantial interest in its potential for cytotoxic drug targeting, taking advantage of its high‐level transport activity under acidic pH conditions that characterize many tumors and its modest expression in most normal tissues. To better understand the basis for variations in hPCFT levels between tissues including human tumors, studies have examined the transcriptional regulation of hPCFT including the roles of CpG hypermethylation and critical transcription factors and cis elements. Additional focus involved identifying key structural and functional determinants of hPCFT transport that, combined with homology models based on structural homologies to the bacterial transporters GlpT and LacY, have enabled new structural and mechanistic insights. Recently, cryo‐electron microscopy structures of chicken PCFT in a substrate‐free state and in complex with the antifolate pemetrexed were reported, providing further structural insights into determinants of (anti)folate recognition and the mechanism of pH‐regulated (anti)folate transport by PCFT. Like many major facilitator proteins, hPCFT exists as a homo‐oligomer, and evidence suggests that homo‐oligomerization of hPCFT monomeric proteins may be important for its intracellular trafficking and/or transport function. Better understanding of the structure, function and regulation of hPCFT should facilitate the rational development of new therapeutic strategies for conditions associated with folate deficiency, as well as cancer.

Early Secretory Pathway-Associated Proteins SsEmp24 and SsErv25 Are Involved in Morphogenesis and Pathogenicity in a Filamentous Phytopathogenic Fungus

Proper protein secretion is critical for fungal development and pathogenesis. However, the potential roles of proteins involved in the early secretory pathway are largely undescribed in filamentous fungi. p24 proteins are cargo receptors that cycle between the endoplasmic reticulum (ER) and Golgi apparatus in the early secretory pathway and recruit cargo proteins to nascent vesicles. This study characterized the function of two p24 family proteins (SsEmp24 and SsErv25) in a phytopathogenic fungus, Sclerotinia sclerotiorum. Both SsEmp24 and SsErv25 were upregulated during the early stages of S. sclerotiorum infection. ΔSsEmp24 mutant and ΔSsErv25 mutant displayed abnormal vegetative growth and sclerotium formation, were defective in infection cushion formation, and showed lower virulence on host plants. ΔSsEmp24 mutant had a more severe abnormal phenotype than ΔSsErv25 mutant, implying that SsEmp24 could play a central role in the early secretory pathway. Similar to their Saccharomyces cerevisiae counterparts, SsEmp24 interacted with SsErv25 and predominantly colocalized in the ER or nuclear envelope. The absence of SsEmp24 or SsErv25 led to defective in protein secretion in S. sclerotiorum, including the pathogenicity-related extracellular hydrolytic enzymes and effectors. It is proposed that SsEmp24 and SsErv25, components in the early secretory pathway, are involved in modulating morphogenesis and pathogenicity in S. sclerotiorum by mediating protein secretion. IMPORTANCE Understanding the reproduction and pathogenesis mechanism of phytopathogens could provide new opinions to effectively control fungal diseases. Although it has been known that effectors and extracellular hydrolytic enzymes secreted by phytopathogenic fungi play important roles in fungus-host interactions, the secretion system for the delivery of virulence factors to the host is still largely undescribed. Although the role of the early secretory pathway-associated p24 proteins in S. cerevisiae has been well characterized, the function of these proteins in filamentous fungi was scarcely known prior to this study. The present research provides evidence that p24 proteins participate in the reproduction and pathogenesis of phytopathogenic fungi through the mediation of protein secretion. This research advances our understanding of p24 proteins in filamentous phytopathogenic fungi. In addition, the candidate cargos of the two p24 proteins, SsEmp24 and SsErv25, were screened out by comparative proteomics, which could aid the identification of novel development and virulence-associated factors in phytopathogenic fungi.

Ionic Liquid-Based Extraction System for In-Depth Analysis of Membrane Protein Complexes

Limited by the rare efficient extraction system in extracting hydrophobic membrane protein complexes (MPCs) without compromising the stability of protein-protein interactions (PPIs), the in-depth functional study of MPCs has lagged far behind. In this study, the first systematic screening of ionic liquids (ILs) was performed and showed that triethylammonium acetate (TEAA) IL exhibited excellent performance in stabilizing PPIs, which was further confirmed by molecular docking simulations. By combining TEAA with the conventional detergent Nonidet P-40 (NP-40), a novel IL-based extraction system, i-TAN (TEAA IL with 1% NP-40), was proposed, which demonstrated superior performance in extracting and stabilizing MPCs, attributed to its larger size, more uniform distribution, and closer-to-neutral microenvironment of micelles. Extraction of MPCs with i-TAN allowed the confident identification of more hydrophobic EGFR-interacting proteins that are easily dissociated during the extraction process. Quantitative analysis of the difference in EGFR complexes between trastuzumab-sensitive and trastuzumab-resistant breast cancer cells provided comprehensive insights to understand the drug resistance mechanism, suggesting that i-TAN has great potential in interactomics and functional analysis of MPCs. This study provides a novel strategy for MPC extraction and downstream processing.

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Numerous brain regions have been identified as contributing to withdrawal behaviors, but it is unclear the way in which these brain regions as a whole lead to withdrawal. The search for a final common brain pathway that is involved in withdrawal remains elusive. To address this question, we implanted osmotic minipumps containing either saline, nicotine (24 mg/kg/d), cocaine (60 mg/kg/d), or methamphetamine (4 mg/kg/d) for one week in male C57BL/6J mice. After one week, the minipumps were removed and brains collected 8 h (saline, nicotine, and cocaine) or 12 h (methamphetamine) after removal. We then performed single-cell whole-brain imaging of neural activity during the withdrawal period when brains were collected. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical-driven to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway associated with withdrawal.

Ist2 recruits the lipid transporters Osh6/7 to ER-PM contacts to maintain phospholipid metabolism

ER-plasma membrane (PM) contacts are proposed to be held together by distinct families of tethering proteins, which in yeast include the VAP homologues Scs2/22, the extended-synaptotagmin homologues Tcb1/2/3, and the TMEM16 homologue Ist2. It is unclear whether these tethers act redundantly or whether individual tethers have specific functions at contacts. Here, we show that Ist2 directly recruits the phosphatidylserine (PS) transport proteins and ORP family members Osh6 and Osh7 to ER-PM contacts through a binding site located in Ist2's disordered C-terminal tethering region. This interaction is required for phosphatidylethanolamine (PE) production by the PS decarboxylase Psd2, whereby PS transported from the ER to the PM by Osh6/7 is endocytosed to the site of Psd2 in endosomes/Golgi/vacuoles. This role for Ist2 and Osh6/7 in nonvesicular PS transport is specific, as other tethers/transport proteins do not compensate. Thus, we identify a molecular link between the ORP and TMEM16 families and a role for endocytosis of PS in PE synthesis.

Systematic analysis of bypass suppression of essential genes

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.

Legionella pneumophila LegC7 effector protein drives aberrant endoplasmic reticulum:endosome contacts in yeast

Legionella pneumophila is a facultative intracellular bacterial pathogen, causing the severe form of pneumonia known as Legionnaires' disease. Legionella actively alters host organelle trafficking through the activities of "effector" proteins secreted via a type-IVB secretion system, in order to construct the bacteria-laden Legionella-containing vacuole (LCV) and prevent lysosomal degradation. The LCV is created with membrane derived from host endoplasmic reticulum (ER), secretory vesicles and phagosomes, although the precise molecular mechanisms that drive its synthesis remain poorly understood. In an effort to characterize the in vivo activity of the LegC7/YlfA SNARE-like effector protein from Legionella in the context of eukaryotic membrane trafficking in yeast, we find that LegC7 interacts with the Emp46p/Emp47p ER-to-Golgi glycoprotein cargo adapter complex, alters ER morphology and induces aberrant ER:endosome interactions, as measured by visualization of ER cargo degradation, reconstitution of split-GFP proteins and enhanced oxidation of the ER lumen. LegC7-dependent toxicity, disruption of ER morphology and ER:endosome fusion events were dependent upon endosomal VPS class C tethering complexes and the endosomal t-SNARE, Pep12p. This work establishes a model in which LegC7 functions to recruit host ER material to the bacterial phagosome during infection by driving ER:endosome contacts, potentially through interaction with host membrane tethering complexes and/or cargo adapters.

Environmental robustness of the global yeast genetic interaction network

Phenotypes associated with genetic variants can be altered by interactions with other genetic variants (GxG), with the environment (GxE), or both (GxGxE). Yeast genetic interactions have been mapped on a global scale, but the environmental influence on the plasticity of genetic networks has not been examined systematically. To assess environmental rewiring of genetic networks, we examined 14 diverse conditions and scored 30,000 functionally representative yeast gene pairs for dynamic, differential interactions. Different conditions revealed novel differential interactions, which often uncovered functional connections between distantly related gene pairs. However, the majority of observed genetic interactions remained unchanged in different conditions, suggesting that the global yeast genetic interaction network is robust to environmental perturbation and captures the fundamental functional architecture of a eukaryotic cell.

Analysing the yeast complexome-the Complex Portal rising to the challenge

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.

Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning

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Fast and accurate prediction of transmembrane protein interaction sites.

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First ever computational survey of interaction sites in membrane proteins.

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10-30% of amino acid positions predicted to be involved in interactions.

Interactions between transmembrane (TM) proteins are fundamental for a wide spectrum of cellular functions, but precise molecular details of these interactions remain largely unknown due to the scarcity of experimentally determined three-dimensional complex structures. Computational techniques are therefore required for a large-scale annotation of interaction sites in TM proteins. Here, we present a novel deep-learning approach, DeepTMInter, for sequence-based prediction of interaction sites in α-helical TM proteins based on their topological, physiochemical, and evolutionary properties. Using a combination of ultra-deep residual neural networks with a stacked generalization ensemble technique DeepTMInter significantly outperforms existing methods, achieving the AUC/AUCPR values of 0.689/0.598. Across the main functional families of human transmembrane proteins, the percentage of amino acid sites predicted to be involved in interactions typically ranges between 10% and 25%, and up to 30% in ion channels. DeepTMInter is available as a standalone package at https://github.com/2003100127/deeptminter. The training and benchmarking datasets are available at https://data.mendeley.com/datasets/2t8kgwzp35.

Analysis of transient membrane protein interactions by single-molecule diffusional mobility shift assay

Various repertoires of membrane protein interactions determine cellular responses to diverse environments around cells dynamically in space and time. Current assays, however, have limitations in unraveling these interactions in the physiological states in a living cell due to the lack of capability to probe the transient nature of these interactions on the crowded membrane. Here, we present a simple and robust assay that enables the investigation of transient protein interactions in living cells by using the single-molecule diffusional mobility shift assay (smDIMSA). Utilizing smDIMSA, we uncovered the interaction profile of EGFR with various membrane proteins and demonstrated the promiscuity of these interactions depending on the cancer cell line. The transient interaction profile obtained by smDIMSA will provide critical information to comprehend the crosstalk among various receptors on the plasma membrane.

Protein Complexes Form a Basis for Complex Hybrid Incompatibility

Proteins are the workhorses of the cell and execute many of their functions by interacting with other proteins forming protein complexes. Multi-protein complexes are an admixture of subunits, change their interaction partners, and modulate their functions and cellular physiology in response to environmental changes. When two species mate, the hybrid offspring are usually inviable or sterile because of large-scale differences in the genetic makeup between the two parents causing incompatible genetic interactions. Such reciprocal-sign epistasis between inter-specific alleles is not limited to incompatible interactions between just one gene pair; and, usually involves multiple genes. Many of these multi-locus incompatibilities show visible defects, only in the presence of all the interactions, making it hard to characterize. Understanding the dynamics of protein-protein interactions (PPIs) leading to multi-protein complexes is better suited to characterize multi-locus incompatibilities, compared to studying them with traditional approaches of genetics and molecular biology. The advances in omics technologies, which includes genomics, transcriptomics, and proteomics can help achieve this end. This is especially relevant when studying non-model organisms. Here, we discuss the recent progress in the understanding of hybrid genetic incompatibility; omics technologies, and how together they have helped in characterizing protein complexes and in turn multi-locus incompatibilities. We also review advances in bioinformatic techniques suitable for this purpose and propose directions for leveraging the knowledge gained from model-organisms to identify genetic incompatibilities in non-model organisms.

Production of Multi-subunit Membrane Protein Complexes

Membrane proteins constitute an important class of proteins for medical, pharmaceutical, and biotechnological reasons. Understanding the structure and function of membrane proteins and their complexes is of key importance, but the progress in this area is slow because of the difficulties to produce them in sufficient quality and quantity. Overexpression of membrane proteins is often restricted by the limited capability of translocation systems to integrate proteins into the membrane and to fold them properly. Purification of membrane proteins requires their isolation from the membrane, which is a further challenge. The choice of expression system, detergents, and purification tags is therefore an important decision. Here, we present a protocol for expression in bacteria and isolation of a seven-subunit membrane protein complex, the bacterial holo-translocon, which can serve as a starting point for the production of other membrane protein complexes for structural and functional studies.

Crosstalk of promoter and terminator during RNA polymerase II transcription cycle

The transcription cycle of RNAPII is comprised of three consecutive steps; initiation, elongation and termination. It has been assumed that the initiation and termination steps occur in spatial isolation, essentially as independent events. A growing body of evidence, however, has challenged this dogma. First, factors involved in initiation and termination exhibit both a genetic and a physical interaction during transcription. Second, the initiation and termination factors have been found to occupy both ends of a transcribing gene. Third, physical interaction of initiation and termination factors occupying distal ends of a gene sometime results in the entire terminator region of a genes looping back and contact its cognate promoter, thereby forming a looped gene architecture during transcription. A logical interpretation of these findings is that the initiation and termination steps of transcription do not occur in isolation. There is extensive communication of factors occupying promoter and terminator ends of a gene during transcription cycle. This review entails a discussion of the promoter-terminator crosstalk and its implication in the context of transcription.

Sphingolipids and Inositol Phosphates Regulate the Tau Protein Phosphorylation Status in Humanized Yeast

Hyperphosphorylation of protein tau is a hallmark of Alzheimer's disease (AD). Changes in energy and lipid metabolism have been correlated with the late onset of this neurological disorder. However, it is uncertain if metabolic dysregulation is a consequence of AD or one of the initiating factors of AD pathophysiology. Also, it is unclear whether variations in lipid metabolism regulate the phosphorylation state of tau. Here, we show that in humanized yeast, tau hyperphosphorylation is stimulated by glucose starvation in coincidence with the downregulation of Pho85, the yeast ortholog of CDK5. Changes in inositol phosphate (IP) signaling, which has a central role in energy metabolism, altered tau phosphorylation. Lack of inositol hexakisphosphate kinases Kcs1 and Vip1 (IP6 and IP7 kinases in mammals) increased tau hyperphosphorylation. Similar effects were found by mutation of IPK2 (inositol polyphosphate multikinase), or PLC1, the yeast phospholipase C gene. These effects may be explained by IP-mediated regulation of Pho85. Indeed, this appeared to be the case for plc1, ipk2, and kcs1. However, the effects of Vip1 on tau phosphorylation were independent of the presence of Pho85, suggesting additional mechanisms. Interestingly, kcs1 and vip1 strains, like pho85, displayed dysregulated sphingolipid (SL) metabolism. Moreover, genetic and pharmacological inhibition of SL biosynthesis stimulated the appearance of hyperphosphorylated forms of tau, while increased flux through the pathway reduced its abundance. Finally, we demonstrated that Sit4, the yeast ortholog of human PP2A protein phosphatase, is a downstream effector of SL signaling in mediating the tau phosphorylation state. Altogether, our results add new knowledge on the molecular effectors involved in tauopathies and identify new targets for pharmacological intervention.

Toward Electrophoretic Separation of Membrane Proteins in Supported n-Bilayers

Membrane proteins are key constituents of the proteome of cells but are poorly characterized, mainly because they are difficult to solubilize. Proteome analysis involves separating proteins as a preliminary step toward their characterization. Currently, the most common method is "solubilizing" them with sophisticated detergent and lipid mixtures for later separation via, for instance, sodium dodecyl sulfate polyacrylamide gel electrophoresis. However, this later step induces loss of 3D structure (denaturation). Migration in a medium that mimics the cell membrane should therefore be more appropriate. Here, we present a successful electrophoretic separation of a mixture first of two and then of three different membrane objects in supported n-bilayers. These "objects" are composed of membrane proteins sulfide quinone reductase and α-hemolysin. Sulfide quinone reductase forms an object from three monomers together and self-inserts into the upper leaflet. α-Hemolysin inserts as a spanning heptamer into a bilayer or can build stable dimers of α-hemolysin heptamers under certain conditions. By appropriately adjusting the pH, it proved possible to move them in different ways. This work holds promise for separating membrane proteins without losing their 3D structure, thus their bioactivity, within a lipidic environment that is closer to physiological conditions and for building drug/diagnostic platforms.

Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes

Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies - Spearman and Kendall correlations - and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric-Euclidean distance-delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.

Mass Spectrometry Untangles Plant Membrane Protein Signaling Networks

Plasma membranes (PMs) act as primary cellular checkpoints for sensing signals and controlling solute transport. Membrane proteins communicate with intracellular processes through protein interaction networks. Deciphering these signaling networks provides crucial information for elucidating in vivo cellular regulation. Large-scale proteomics enables system-wide characterization of the membrane proteome, identification of ligand-receptor pairs, and elucidation of signals originating at membranes. In this review we assess recent progress in the development of mass spectrometry (MS)-based proteomic pipelines for determining membrane signaling pathways. We focus in particular on current techniques for the analysis of membrane protein phosphorylation and interaction, and how these proteins may be connected to downstream changes in gene expression, metabolism, and physiology.

Leveraging Neural Networks in Preclinical Alcohol Research

Alcohol use disorder is a pervasive healthcare issue with significant socioeconomic consequences. There is a plethora of neural imaging techniques available at the clinical and preclinical level, including magnetic resonance imaging and three-dimensional (3D) tissue imaging techniques. Network-based approaches can be applied to imaging data to create neural networks that model the functional and structural connectivity of the brain. These networks can be used to changes to brain-wide neural signaling caused by brain states associated with alcohol use. Neural networks can be further used to identify key brain regions or neural "hubs" involved in alcohol drinking. Here, we briefly review the current imaging and neurocircuit manipulation methods. Then, we discuss clinical and preclinical studies using network-based approaches related to substance use disorders and alcohol drinking. Finally, we discuss how preclinical 3D imaging in combination with network approaches can be applied alone and in combination with other approaches to better understand alcohol drinking.

Complementary α-arrestin-ubiquitin ligase complexes control nutrient transporter endocytosis in response to amino acids

How cells adjust nutrient transport across their membranes is incompletely understood. Previously, we have shown that S. cerevisiae broadly re-configures the nutrient transporters at the plasma membrane in response to amino acid availability, through endocytosis of sugar- and amino acid transporters (AATs) (Müller et al., 2015). A genome-wide screen now revealed that the selective endocytosis of four AATs during starvation required the α-arrestin family protein Art2/Ecm21, an adaptor for the ubiquitin ligase Rsp5, and its induction through the general amino acid control pathway. Art2 uses a basic patch to recognize C-terminal acidic sorting motifs in AATs and thereby instructs Rsp5 to ubiquitinate proximal lysine residues. When amino acids are in excess, Rsp5 instead uses TORC1-activated Art1 to detect N-terminal acidic sorting motifs within the same AATs, which initiates exclusive substrate-induced endocytosis. Thus, amino acid excess or starvation activate complementary α-arrestin-Rsp5-complexes to control selective endocytosis and adapt nutrient acquisition.

Exploring whole-genome duplicate gene retention with complex genetic interaction analysis

Whole-genome duplication has played a central role in the genome evolution of many organisms, including the human genome. Most duplicated genes are eliminated, and factors that influence the retention of persisting duplicates remain poorly understood. We describe a systematic complex genetic interaction analysis with yeast paralogs derived from the whole-genome duplication event. Mapping of digenic interactions for a deletion mutant of each paralog, and of trigenic interactions for the double mutant, provides insight into their roles and a quantitative measure of their functional redundancy. Trigenic interaction analysis distinguishes two classes of paralogs: a more functionally divergent subset and another that retained more functional overlap. Gene feature analysis and modeling suggest that evolutionary trajectories of duplicated genes are dictated by combined functional and structural entanglement factors.

Osh6 requires Ist2 for localization to ER-PM contacts and efficient phosphatidylserine transport in budding yeast

Osh6 and Osh7 are lipid transfer proteins (LTPs) that move phosphatidylserine (PS) from the endoplasmic reticulum (ER) to the plasma membrane (PM). High PS levels at the PM are key for many cellular functions. Intriguingly, Osh6 and Osh7 localize to ER-PM contact sites, although they lack membrane-targeting motifs, in contrast to multidomain LTPs that both bridge membranes and convey lipids. We show that Osh6 localization to contact sites depends on its interaction with the cytosolic tail of the ER-PM tether Ist2, a homolog of TMEM16 proteins. We identify a motif in the Ist2 tail, conserved in yeasts, as the Osh6-binding region, and we map an Ist2-binding surface on Osh6. Mutations in the Ist2 tail phenocopy osh6Δ osh7Δ deletion: they decrease cellular PS levels and block PS transport to the PM. Our study unveils an unexpected partnership between a TMEM16-like protein and a soluble LTP, which together mediate lipid transport at contact sites.This article has an associated First Person interview with the first author of the paper.

His-Tagged Peptidiscs Enable Affinity Purification of the Membrane Proteome for Downstream Mass Spectrometry Analysis

Characterization of the integral membrane proteome by mass spectrometry (MS) remains challenging due its high complexity and inherent insolubility. In a typical experiment, the cellular membranes are isolated, the proteins are solubilized and fractionated, and the detergent micelles are removed before MS analysis. Detergents are not compatible with mass spectrometry, however, and their removal from biological samples often results in reduced protein identification. As an alternative to detergents, we recently developed the peptidisc membrane mimetic, which allows entrapment of the cell envelope proteome into water-soluble particles, termed a "peptidisc library". Here, we employ a His-tagged version of the peptidisc peptide scaffold to enrich the reconstituted membrane proteome by affinity chromatography. This purification step reduces the sample complexity by depleting ribosomal and soluble proteins that often cosediment with cellular membranes. As a result, the peptidisc library is enriched in low-abundance membrane proteins. We apply this method to survey changes in the membrane proteome upon depletion of the SecDFyajC complex, the ancillary subunit of the Sec translocon. In the depleted strain, we detect increased membrane localization of the motor ATPase SecA, along with increased levels of an unannotated inner membrane protein, YibN. Together, these results demonstrate the utility of the peptidisc for global purification of membrane proteins and for monitoring change in the membrane proteome.

Proximity Dependent Biotinylation: Key Enzymes and Adaptation to Proteomics Approaches

The study of protein subcellular distribution, their assembly into complexes and the set of proteins with which they interact with is essential to our understanding of fundamental biological processes. Complementary to traditional assays, proximity-dependent biotinylation (PDB) approaches coupled with mass spectrometry (such as BioID or APEX) have emerged as powerful techniques to study proximal protein interactions and the subcellular proteome in the context of living cells and organisms. Since their introduction in 2012, PDB approaches have been used in an increasing number of studies and the enzymes themselves have been subjected to intensive optimization. How these enzymes have been optimized and considerations for their use in proteomics experiments are important questions. Here, we review the structural diversity and mechanisms of the two main classes of PDB enzymes: the biotin protein ligases (BioID) and the peroxidases (APEX). We describe the engineering of these enzymes for PDB and review emerging applications, including the development of PDB for coincidence detection (split-PDB). Lastly, we briefly review enzyme selection and experimental design guidelines and reflect on the labeling chemistries and their implication for data interpretation.

A Quantitative Tri-fluorescent Yeast Two-hybrid System: From Flow Cytometry to In cellula Affinities

We present a technological advancement for the estimation of the affinities of Protein-Protein Interactions (PPIs) in living cells. A novel set of vectors is introduced that enables a quantitative yeast two-hybrid system based on fluorescent fusion proteins. The vectors allow simultaneous quantification of the reaction partners (Bait and Prey) and the reporter at the single-cell level by flow cytometry. We validate the applicability of this system on a small but diverse set of PPIs (eleven protein families from six organisms) with different affinities; the dissociation constants range from 117 pm to 17 μm After only two hours of reaction, expression of the reporter can be detected even for the weakest PPI. Through a simple gating analysis, it is possible to select only cells with identical expression levels of the reaction partners. As a result of this standardization of expression levels, the mean reporter levels directly reflect the affinities of the studied PPIs. With a set of PPIs with known affinities, it is straightforward to construct an affinity ladder that permits rapid classification of PPIs with thus far unknown affinities. Conventional software can be used for this analysis. To permit automated analysis, we provide a graphical user interface for the Python-based FlowCytometryTools package.

Prebiotic Peptides: Molecular Hubs in the Origin of Life

The fundamental roles that peptides and proteins play in today's biology makes it almost indisputable that peptides were key players in the origin of life. Insofar as it is appropriate to extrapolate back from extant biology to the prebiotic world, one must acknowledge the critical importance that interconnected molecular networks, likely with peptides as key components, would have played in life's origin. In this review, we summarize chemical processes involving peptides that could have contributed to early chemical evolution, with an emphasis on molecular interactions between peptides and other classes of organic molecules. We first summarize mechanisms by which amino acids and similar building blocks could have been produced and elaborated into proto-peptides. Next, non-covalent interactions of peptides with other peptides as well as with nucleic acids, lipids, carbohydrates, metal ions, and aromatic molecules are discussed in relation to the possible roles of such interactions in chemical evolution of structure and function. Finally, we describe research involving structural alternatives to peptides and covalent adducts between amino acids/peptides and other classes of molecules. We propose that ample future breakthroughs in origin-of-life chemistry will stem from investigations of interconnected chemical systems in which synergistic interactions between different classes of molecules emerge.

An ABCG Transporter Functions in Rab Localization and Lysosome-Related Organelle Biogenesis in Caenorhabditis elegans

ABC transporters couple ATP hydrolysis to the transport of substrates across cellular membranes. This protein superfamily has diverse activities resulting from differences in their cargo and subcellular localization. Our work investigates the role of the ABCG family member WHT-2 in the biogenesis of gut granules, a Caenorhabditis elegans lysosome-related organelle. In addition to being required for the accumulation of birefringent material within gut granules, WHT-2 is necessary for the localization of gut granule proteins when trafficking pathways to this organelle are partially disrupted. The role of WHT-2 in gut granule protein targeting is likely linked to its function in Rab GTPase localization. We show that WHT-2 promotes the gut granule association of the Rab32 family member GLO-1 and the endolysosomal RAB-7, identifying a novel function for an ABC transporter. WHT-2 localizes to gut granules where it could play a direct role in controlling Rab localization. Loss of CCZ-1 and GLO-3, which likely function as a guanine nucleotide exchange factor (GEF) for GLO-1, lead to similar disruption of GLO-1 localization. We show that CCZ-1, like GLO-3, is localized to gut granules. WHT-2 does not direct the gut granule association of the GLO-1 GEF and our results point to WHT-2 functioning differently than GLO-3 and CCZ-1 Point mutations in WHT-2 that inhibit its transport activity, but not its subcellular localization, lead to the loss of GLO-1 from gut granules, while other WHT-2 activities are not completely disrupted, suggesting that WHT-2 functions in organelle biogenesis through transport-dependent and transport-independent activities.

Systematic genetics and single-cell imaging reveal widespread morphological pleiotropy and cell-to-cell variability

Our ability to understand the genotype-to-phenotype relationship is hindered by the lack of detailed understanding of phenotypes at a single-cell level. To systematically assess cell-to-cell phenotypic variability, we combined automated yeast genetics, high-content screening and neural network-based image analysis of single cells, focussing on genes that influence the architecture of four subcellular compartments of the endocytic pathway as a model system. Our unbiased assessment of the morphology of these compartments-endocytic patch, actin patch, late endosome and vacuole-identified 17 distinct mutant phenotypes associated with ~1,600 genes (~30% of all yeast genes). Approximately half of these mutants exhibited multiple phenotypes, highlighting the extent of morphological pleiotropy. Quantitative analysis also revealed that incomplete penetrance was prevalent, with the majority of mutants exhibiting substantial variability in phenotype at the single-cell level. Our single-cell analysis enabled exploration of factors that contribute to incomplete penetrance and cellular heterogeneity, including replicative age, organelle inheritance and response to stress.

Brain-wide functional architecture remodeling by alcohol dependence and abstinence

Alcohol abuse and alcohol dependence are key factors in the development of alcohol use disorder, which is a pervasive societal problem with substantial economic, medical, and psychiatric consequences. Although our understanding of the neurocircuitry that underlies alcohol use has improved, novel brain regions that are involved in alcohol use and novel biomarkers of alcohol use need to be identified. The present study used a single-cell whole-brain imaging approach to 1) assess whether abstinence from alcohol in an animal model of alcohol dependence alters the functional architecture of brain activity and modularity, 2) validate our current knowledge of the neurocircuitry of alcohol abstinence, and 3) discover brain regions that may be involved in alcohol use. Alcohol abstinence resulted in the whole-brain reorganization of functional architecture in mice and a pronounced decrease in modularity that was not observed in nondependent moderate drinkers. Structuring of the alcohol abstinence network revealed three major brain modules: 1) extended amygdala module, 2) midbrain striatal module, and 3) cortico-hippocampo-thalamic module, reminiscent of the three-stage theory. Many hub brain regions that control this network were identified, including several that have been previously overlooked in alcohol research. These results identify brain targets for future research and demonstrate that alcohol use and dependence remodel brain-wide functional architecture to decrease modularity. Further studies are needed to determine whether the changes in coactivation and modularity that are associated with alcohol abstinence are causal features of alcohol dependence or a consequence of excessive drinking and alcohol exposure.

Human cytomegalovirus interactome analysis identifies degradation hubs, domain associations and viral protein functions

Human cytomegalovirus (HCMV) extensively modulates host cells, downregulating >900 human proteins during viral replication and degrading ≥133 proteins shortly after infection. The mechanism of degradation of most host proteins remains unresolved, and the functions of many viral proteins are incompletely characterised. We performed a mass spectrometry-based interactome analysis of 169 tagged, stably-expressed canonical strain Merlin HCMV proteins, and two non-canonical HCMV proteins, in infected cells. This identified a network of >3400 virus-host and >150 virus-virus protein interactions, providing insights into functions for multiple viral genes. Domain analysis predicted binding of the viral UL25 protein to SH3 domains of NCK Adaptor Protein-1. Viral interacting proteins were identified for 31/133 degraded host targets. Finally, the uncharacterised, non-canonical ORFL147C protein was found to interact with elements of the mRNA splicing machinery, and a mutational study suggested its importance in viral replication. The interactome data will be important for future studies of herpesvirus infection.

Membrane Dynamics in Health and Disease: Impact on Cellular Signalling

Biological membranes display a staggering complexity of lipids and proteins orchestrating cellular functions. Superior analytical tools coupled with numerous functional cellular screens have enabled us to query their role in cellular signalling, trafficking, guiding protein structure and function-all of which rely on the dynamic membrane lipid properties indispensable for proper cellular functions. Alteration of these has led to emergence of various pathological conditions, thus opening an area of lipid-centric therapeutic approaches. This perspective is a short summary of the dynamic properties of membranes essential for proper cellular functions, dictating both protein and lipid functions, and mis-regulated in diseases. Towards the end, we focus on some challenges lying ahead and potential means to tackle the same, mainly underscored by multi-disciplinary approaches.

Conformational switching of chiral colloidal rafts regulates raft-raft attractions and repulsions

Membrane-mediated particle interactions depend both on the properties of the particles themselves and the membrane environment in which they are suspended. Experiments have shown that chiral rod-like inclusions dissolved in a colloidal membrane of opposite handedness assemble into colloidal rafts, which are finite-sized reconfigurable droplets consisting of a large but precisely defined number of rods. We systematically tune the chirality of the background membrane and find that, in the achiral limit, colloidal rafts acquire complex structural properties and interactions. In particular, rafts can switch between 2 chiral states of opposite handedness, which alters the nature of the membrane-mediated raft-raft interactions. Rafts with the same chirality have long-ranged repulsions, while those with opposite chirality acquire attractions with a well-defined minimum. Both attractive and repulsive interactions are qualitatively explained by a continuum model that accounts for the coupling between the membrane thickness and the local tilt of the constituent rods. These switchable interactions enable assembly of colloidal rafts into intricate higher-order architectures, including stable tetrameric clusters and "ionic crystallites" of counter-twisting domains organized on a binary square lattice. Furthermore, the properties of individual rafts, such as their sizes, are controlled by their complexation with other rafts. The emergence of these complex behaviors can be rationalized purely in terms of generic couplings between compositional and orientational order of fluids of rod-like elements. Thus, the uncovered principles might have relevance for conventional lipid bilayers, in which the assembly of higher-order structures is also mediated by complex membrane-mediated interactions.

EPIC: software toolkit for elution profile-based inference of protein complexes

Protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We and others previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (chromatographic fractionation-mass spectrometry, CF-MS), but the resulting data are challenging to process and interpret. Here, we describe EPIC (elution profile-based inference of complexes), a software toolkit for automated scoring of large-scale CF-MS data to define high-confidence multi-component macromolecules from diverse biological specimens. As a case study, we used EPIC to map the global interactome of Caenorhabditis elegans, defining 612 putative worm protein complexes linked to diverse biological processes. These included novel subunits and assemblies unique to nematodes that we validated using orthogonal methods. The open source EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/).

Profiling the Escherichia coli membrane protein interactome captured in Peptidisc libraries

Protein-correlation-profiling (PCP), in combination with quantitative proteomics, has emerged as a high-throughput method for the rapid identification of dynamic protein complexes in native conditions. While PCP has been successfully applied to soluble proteomes, characterization of the membrane interactome has lagged, partly due to the necessary use of detergents to maintain protein solubility. Here, we apply the peptidisc, a ‘one-size fits all’ membrane mimetic, for the capture of the Escherichia coli cell envelope proteome and its high-resolution fractionation in the absence of detergent. Analysis of the SILAC-labeled peptidisc library via PCP allows generation of over 4900 possible binary interactions out of >700,000 random associations. Using well-characterized membrane protein systems such as the SecY translocon, the Bam complex and the MetNI transporter, we demonstrate that our dataset is a useful resource for identifying transient and surprisingly novel protein interactions. For example, we discover a trans-periplasmic supercomplex comprising subunits of the Bam and Sec machineries, including membrane-bound chaperones YfgM and PpiD. We identify RcsF and OmpA as bone fide interactors of BamA, and we show that MetQ association with the ABC transporter MetNI depends on its N-terminal lipid anchor. We also discover NlpA as a novel interactor of MetNI complex. Most of these interactions are largely undetected by standard detergent-based purification. Together, the peptidisc workflow applied to the proteomic field is emerging as a promising novel approach to characterize membrane protein interactions under native expression conditions and without genetic manipulation.

Proteomic Analysis of the β-Arrestin Interactomes

Protein-protein interaction is crucial to protein function and cellular signaling. A number of approaches were developed and applied to characterize protein-protein interactions in the past decades. In recent years, mass spectrometry (MS)-based proteomic methods have emerged as powerful tools to identify protein binding partners in a global and high-throughput manner. In this chapter, we describe the proteomic methods used to characterize the whole sets of proteins associated with β-arrestins (β-arrestin interactomes). The method starts with co-immunoprecipitation (co-IP) of β-arrestin signaling complexes from cells followed by protease digestion and LC/MS/MS analysis (liquid chromatography/tandem mass spectrometry) of proteins in the β-arrestin signaling complexes. To investigate changes in the amounts of binding partners under different conditions, we also describe a SILAC (stable isotope labeling by amino acids in cell culture) method to obtain quantitative information for β-arrestin interactomes.

Membrane phospholipid alteration causes chronic ER stress through early degradation of homeostatic ER-resident proteins

Phospholipid homeostasis in biological membranes is essential to maintain functions of organelles such as the endoplasmic reticulum. Phospholipid perturbation has been associated to cellular stress responses. However, in most cases, the implication of membrane lipid changes to homeostatic cellular response has not been clearly defined. Previously, we reported that Saccharomyces cerevisiae adapts to lipid bilayer stress by upregulating several protein quality control pathways such as the endoplasmic reticulum-associated degradation (ERAD) pathway and the unfolded protein response (UPR). Surprisingly, we observed certain ER-resident transmembrane proteins, which form part of the UPR programme, to be destabilised under lipid bilayer stress. Among these, the protein translocon subunit Sbh1 was prematurely degraded by membrane stiffening at the ER. Moreover, our findings suggest that the Doa10 complex recognises free Sbh1 that becomes increasingly accessible during lipid bilayer stress, perhaps due to the change in ER membrane properties. Premature removal of key ER-resident transmembrane proteins might be an underlying cause of chronic ER stress as a result of lipid bilayer stress.

Interfaces Between Alpha-helical Integral Membrane Proteins: Characterization, Prediction, and Docking

Protein-protein interaction (PPI) is an essential mechanism by which proteins perform their biological functions. For globular proteins, the molecular characteristics of such interactions have been well analyzed, and many computational tools are available for predicting PPI sites and constructing structural models of the complex. In contrast, little is known about the molecular features of the interaction between integral membrane proteins (IMPs) and few methods exist for constructing structural models of their complexes. Here, we analyze the interfaces from a non-redundant set of complexes of α-helical IMPs whose structures have been determined to a high resolution. We find that the interface is not significantly different from the rest of the surface in terms of average hydrophobicity. However, the interface is significantly better conserved and, on average, inter-subunit contacting residue pairs correlate more strongly than non-contacting pairs, especially in obligate complexes. We also develop a neural network-based method, with an area under the receiver operating characteristic curve of 0.75 and a Pearson correlation coefficient of 0.70, for predicting interface residues and their weighted contact numbers (WCNs). We further show that predicted interface residues and their WCNs can be used as restraints to reconstruct the structure α-helical IMP dimers through docking for fourteen out of a benchmark set of sixteen complexes. The RMSD100 values of the best-docked ligand subunit to its native structure are <2.5 Å for these fourteen cases. The structural analysis conducted in this work provides molecular details about the interface between α-helical IMPs and the WCN restraints represent an efficient means to score α-helical IMP docking candidates.

Exploring a Tumor-Intrinsic PD-L1 Signal with Proximity-Dependent Biotin Identification in Lung Cancer Cells

Blocking the PD-L1/PD-1 interaction with an antibody produces a durable response in patients with diverse advanced cancers. However, it remains elusive on whether the engagement of PD-L1 to PD-1 leads to tumor-intrinsic signaling. In this study, we aim to explore novel protein substrates participating in transducing this tumor-intrinsic PD-L1 signaling. To this end, we performed a BioID (proximity-dependent biotin identification) assay, in which we fused PD-L1 to BirA* (a promiscuous mutant of bacterial biotin ligase BirA) and overexpressed it in the lung adenocarcinoma A549 cell line. Through streptavidin affinity capture and mass spectrometry analysis, we identified 57 candidate proteins including 18 PD-L1/PD-1-interaction-dependent neighbors. In addition to this, 9 out of 57 candidates were involved in the EGFR signaling pathway, which is known to play a critical role in tumorigenesis and multiple therapeutic resistances of lung cancer. This study will provide a new insight in understanding tumor-intrinsic PD-L1-signaling effectors of lung cancer.