The permissive binding theory of cancer

The later stages of cancer, including the invasion and colonization of new tissues, are actively mysterious compared to earlier stages like primary tumor formation. While we lack many details about both, we do have an apparently successful explanatory framework for the earlier stages: one in which genetic mutations hold ultimate causal and explanatory power. By contrast, on both empirical and conceptual grounds, it is not currently clear that mutations alone can explain the later stages of cancer. Can a different type of molecular change do better? Here, I introduce the "permissive binding theory" of cancer, which proposes that novel protein binding interactions are the key causal and explanatory entity in invasion and metastasis. It posits that binding is more abundant at baseline than we observe because it is restricted in normal physiology; that any large perturbation to physiological state revives this baseline abundance, unleashing many new binding interactions; and that a subset of these cause the cellular functions at the heart of oncogenesis, especially invasion and metastasis. Significant physiological perturbations occur in cancer cells in very early stages, and generally become more extreme with progression, providing interactions that continually fuel invasion and metastasis. The theory is compatible with, but not limited to, causal roles for the diverse molecular changes observed in cancer (e.g. gene expression or epigenetic changes), as these generally act causally upstream of proteins, and so may exert their effects by changing the protein binding interactions that occur in the cell. This admits the possibility that molecular changes that appear quite different may actually converge in creating the same few protein complexes, simplifying our picture of invasion and metastasis. If correct, the theory offers a concrete therapeutic strategy: targeting the key novel complexes. The theory is straightforwardly testable by large-scale identification of protein interactions in different cancers.

Salivary Cystatin D Interactome in Patients with Systemic Mastocytosis: An Exploratory Study

Mastocytosis, a rare blood disorder characterized by the proliferation of clonal abnormal mast cells, has a variegated clinical spectrum and diagnosis is often difficult and delayed. Recently we proposed the cathepsin inhibitor cystatin D-R26 as a salivary candidate biomarker of systemic mastocytosis (SM). Its C26 variant is able to form multiprotein complexes (mPCs) and since protein-protein interactions (PPIs) are crucial for studying disease pathogenesis, potential markers, and therapeutic targets, we aimed to define the protein composition of the salivary cystatin D-C26 interactome associated with SM. An exploratory affinity purification-mass spectrometry method was applied on pooled salivary samples from SM patients, SM patient subgroups with and without cutaneous symptoms (SM+C and SM-C), and healthy controls (Ctrls). Interactors specifically detected in Ctrls were found to be implicated in networks associated with cell and tissue homeostasis, innate system, endopeptidase regulation, and antimicrobial protection. Interactors distinctive of SM-C patients participate to PPI networks related to glucose metabolism, protein S-nitrosylation, antibacterial humoral response, and neutrophil degranulation, while interactors specific to SM+C were mainly associated with epithelial and keratinocyte differentiation, cytoskeleton rearrangement, and immune response pathways. Proteins sensitive to redox changes, as well as proteins with immunomodulatory properties and activating mast cells, were identified in patients; many of them were involved directly in cytoskeleton rearrangement, a process crucial for mast cell activation. Although preliminary, these results demonstrate that PPI alterations of the cystatin D-C26 interactome are associated with SM and provide a basis for future investigations based on quantitative proteomic analysis and immune validation.

Molecular Mechanism of STIL Coiled-Coil Domain Oligomerization

Coiled-coil domains (CCDs) play key roles in regulating both healthy cellular processes and the pathogenesis of various diseases by controlling protein self-association and protein-protein interactions. Here, we probe the mechanism of oligomerization of a peptide representing the CCD of the STIL protein, a tetrameric multi-domain protein that is over-expressed in several cancers and associated with metastatic spread. STIL tetramerization is mediated both by an intrinsically disordered domain (STIL400-700) and a structured CCD (STIL CCD718-749). Disrupting STIL oligomerization via the CCD inhibits its activity in vivo. We describe a comprehensive biophysical and structural characterization of the concentration-dependent oligomerization of STIL CCD peptide. We combine analytical ultracentrifugation, fluorescence and circular dichroism spectroscopy to probe the STIL CCD peptide assembly in solution and determine dissociation constants of both the dimerization, (KD = 8 ± 2 µM) and tetramerization (KD = 68 ± 2 µM) of the WT STIL CCD peptide. The higher-order oligomers result in increased thermal stability and cooperativity of association. We suggest that this complex oligomerization mechanism regulates the activated levels of STIL in the cell and during centriole duplication. In addition, we present X-ray crystal structures for the CCD containing destabilising (L736E) and stabilising (Q729L) mutations, which reveal dimeric and tetrameric antiparallel coiled-coil structures, respectively. Overall, this study offers a basis for understanding the structural molecular biology of the STIL protein, and how it might be targeted to discover anti-cancer reagents.

Discriminating physiological from non-physiological interfaces in structures of protein complexes: A community-wide study

Reliably scoring and ranking candidate models of protein complexes and assigning their oligomeric state from the structure of the crystal lattice represent outstanding challenges. A community-wide effort was launched to tackle these challenges. The latest resources on protein complexes and interfaces were exploited to derive a benchmark dataset consisting of 1677 homodimer protein crystal structures, including a balanced mix of physiological and non-physiological complexes. The non-physiological complexes in the benchmark were selected to bury a similar or larger interface area than their physiological counterparts, making it more difficult for scoring functions to differentiate between them. Next, 252 functions for scoring protein-protein interfaces previously developed by 13 groups were collected and evaluated for their ability to discriminate between physiological and non-physiological complexes. A simple consensus score generated using the best performing score of each of the 13 groups, and a cross-validated Random Forest (RF) classifier were created. Both approaches showed excellent performance, with an area under the Receiver Operating Characteristic (ROC) curve of 0.93 and 0.94, respectively, outperforming individual scores developed by different groups. Additionally, AlphaFold2 engines recalled the physiological dimers with significantly higher accuracy than the non-physiological set, lending support to the reliability of our benchmark dataset annotations. Optimizing the combined power of interface scoring functions and evaluating it on challenging benchmark datasets appears to be a promising strategy.

Interactions between modified fullerenes and proteins in cancer nanotechnology

Fullerenes have numerous properties that fill the gap between small molecules and nanomaterials. Several types of chemical reaction allow their surface to be ornamented with functional groups designed to change them into 'ideal' nanodelivery systems. Improved stability, and bioavailability are important, but chemical modifications can render them practically soluble in water. 'Buckyball' fullerene scaffolds can interact with many biological targets and inhibit several proteins essential for tumorigeneses. Herein, we focus on the inhibitory properties of fullerene nanomaterials against essential proteins in cancer nanotechnology, as well as the use of dedicated proteins to improve the bioavailability of these promising nanomaterials.

Interruption of p53-MDM2 Interaction by Nutlin-3a in Human Lymphoma Cell Models Initiates a Cell-Dependent Global Effect on Transcriptome and Proteome Level

In most lymphomas, p53 signaling pathway is inactivated by various mechanisms independent to p53 gene mutations or deletions. In many cases, p53 function is largely regulated by alterations in the protein abundance levels by the action of E3 ubiquitin-protein ligase MDM2, targeting p53 to proteasome-mediated degradation. In the present study, an integrating transcriptomics and proteomics analysis was employed to investigate the effect of p53 activation by a small-molecule MDM2-antagonist, nutlin-3a, on three lymphoma cell models following p53 activation. Our analysis revealed a system-wide nutlin-3a-associated effect in all examined lymphoma types, identifying in total of 4037 differentially affected proteins involved in a plethora of pathways, with significant heterogeneity among lymphomas. Our findings include known p53-targets and novel p53 activation effects, involving transcription, translation, or degradation of protein components of pathways, such as a decrease in key members of PI3K/mTOR pathway, heat-shock response, and glycolysis, and an increase in key members of oxidative phoshosphorylation, autophagy and mitochondrial translation. Combined inhibition of HSP90 or PI3K/mTOR pathway with nutlin-3a-mediated p53-activation enhanced the apoptotic effects suggesting a promising strategy against human lymphomas. Integrated omic profiling after p53 activation offered novel insights on the regulatory role specific proteins and pathways may have in lymphomagenesis.

Research Progress on NSP11 of Porcine Reproductive and Respiratory Syndrome Virus

Porcine reproductive and respiratory syndrome (PRRS) is a virulent infectious disease caused by the PRRS virus (PRRSV). The non-structural protein 11 (NSP11) of PRRSV is a nidovirus-specific endonuclease (NendoU), which displays uridine specificity and catalytic functions conserved throughout the entire NendoU family and exerts a wide range of biological effects. This review discusses the genetic evolution of NSP11, its effects on PRRSV replication and virulence, its interaction with other PRRSV and host proteins, its regulation of host immunity, the conserved characteristics of its enzyme activity (NendoU), and its diagnosis, providing an essential theoretical basis for in-depth studies of PRRSV pathogenesis and vaccine design.

Protein Interactions in Rhodopseudomonas palustris TIE-1 Reveal the Molecular Basis for Resilient Photoferrotrophic Iron Oxidation

Rhodopseudomonas palustris is an alphaproteobacterium with impressive metabolic versatility, capable of oxidizing ferrous iron to fix carbon dioxide using light energy. Photoferrotrophic iron oxidation is one of the most ancient metabolisms, sustained by the pio operon coding for three proteins: PioB and PioA, which form an outer-membrane porin-cytochrome complex that oxidizes iron outside of the cell and transfers the electrons to the periplasmic high potential iron-sulfur protein (HIPIP) PioC, which delivers them to the light-harvesting reaction center (LH-RC). Previous studies have shown that PioA deletion is the most detrimental for iron oxidation, while, the deletion of PioC resulted in only a partial loss. The expression of another periplasmic HiPIP, designated Rpal_4085, is strongly upregulated in photoferrotrophic conditions, making it a strong candidate for a PioC substitute. However, it is unable to reduce the LH-RC. In this work we used NMR spectroscopy to map the interactions between PioC, PioA, and the LH-RC, identifying the key amino acid residues involved. We also observed that PioA directly reduces the LH-RC, and this is the most likely substitute upon PioC deletion. By contrast, Rpal_4085 demontrated significant electronic and structural differences from PioC. These differences likely explain its inability to reduce the LH-RC and highlight its distinct functional role. Overall, this work reveals the functional resilience of the pio operon pathway and further highlights the use of paramagnetic NMR for understanding key biological processes.

Functional Diversity of Homologous Oxidoreductases-Tuning of Substrate Specificity by a FAD-Stacking Residue for Iron Acquisition and Flavodoxin Reduction

Although bacterial thioredoxin reductase-like ferredoxin/flavodoxin NAD(P)⁺ oxidoreductases (FNRs) are similar in terms of primary sequences and structures, they participate in diverse biological processes by catalyzing a range of different redox reactions. Many of the reactions are critical for the growth, survival of, and infection by pathogens, and insight into the structural basis for substrate preference, specificity, and reaction kinetics is crucial for the detailed understanding of these redox pathways. Bacillus cereus (Bc) encodes three FNR paralogs, two of which have assigned distinct biological functions in bacillithiol disulfide reduction and flavodoxin (Fld) reduction. Bc FNR2, the endogenous reductase of the Fld-like protein NrdI, belongs to a distinct phylogenetic cluster of homologous oxidoreductases containing a conserved His residue stacking the FAD cofactor. In this study, we have assigned a function to FNR1, in which the His residue is replaced by a conserved Val, in the reduction of the heme-degrading monooxygenase IsdG, ultimately facilitating the release of iron in an important iron acquisition pathway. The Bc IsdG structure was solved, and IsdG-FNR1 interactions were proposed through protein-protein docking. Mutational studies and bioinformatics analyses confirmed the importance of the conserved FAD-stacking residues on the respective reaction rates, proposing a division of FNRs into four functionally unique sequence similarity clusters likely related to the nature of this residue.

Hallmarks and evolutionary drivers of cotranslational protein complex assembly

Recent discoveries have highlighted the prevalence of cotranslational assembly in proteomes, revealing a range of mechanisms that enables the assembly of protein complex subunits on the ribosome. Structural analyses have uncovered emergent properties that may inherently control whether a subunit undergoes cotranslational assembly. However, the evolutionary paths that have yielded such complexes over an extended timescale remain largely unclear. In this review, we reflect on historical experiments that contributed to the field, including breakthroughs that have made possible the proteome-wide detection of cotranslational assembly, and the technical challenges yet to be overcome. We introduce a simple framework that encapsulates the hallmarks of cotranslational assembly and discuss how results from new experiments are shaping our view of the mechanistic, structural and evolutionary factors driving the phenomenon.

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes

Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.

Construction of stable membranal CMTM6-PD-L1 full-length complex to evaluate the PD-1/PD-L1-CMTM6 interaction and develop anti-tumor anti-CMTM6 nanobody

CKLF (chemokine-like factor)-MARVEL transmembrane domain containing protein 6 (CMTM6) is a novel regulator to maintain the stability of PD-L1. CMTM6 can colocalize and interact with PD-L1 on the recycling endosomes and cell membrane, preventing PD-L1 from lysosome-mediated degradation and proteasome-mediated degradation thus increasing the half-life of PD-L1 on the cell membrane. The difficulties in obtaining stable full-length PD-L1 and CMTM6 proteins hinder the research on their structures, function as well as related drug development. Using lauryl maltose neopentyl glycol (LMNG) as the optimized detergent and a cell membrane mimetic strategy, we assembled a stable membrane-bound full-length CMTM6-PD-L1 complex with amphipol A8-35. When the PD-1/PD-L1-CMTM6 interactions were analyzed, we found that CMTM6 greatly enhanced the binding and delayed the dissociation of PD-1/PD-L1, thus affecting immunosuppressive signaling and anti-apoptotic signaling. We then used the CMTM6-PD-L1 complex as immunogens to generate immune repertoires in camels, and identified a functional anti-CMTM6 nanobody, called 1A5. We demonstrated that the anti-CMTM6 nanobody greatly decreased T-cell immunosuppression and promoted apoptotic susceptibility of tumor cells in vitro, and mainly relied on the cytotoxic effect of CD8+ T-cells to exert tumor growth inhibitory effects in CT26 tumor-bearing mice. In conclusion, the stable membrane-bound full-length CMTM6-PD-L1 complex has been successfully used in studying PD-1/PD-L1-CMTM6 interactions and CMTM6-targeting drug development, suggesting CMTM6 as a novel tumor immunotherapy target.

NMR and Patch-Clamp Characterization of Yeast Mitochondrial Pyruvate Carrier Complexes

The mitochondrial pyruvate carrier (Mpc) plays an indispensable role in the transport of pyruvates across the mitochondrial inner membrane. Despite the two distinct homologous proteins, Mpc1 and Mpc2, were identified in 2012, there are still controversies on the basic functional units and oligomeric state of Mpc complexes. In this study, yeast Mpc1 and Mpc2 proteins were expressed in a prokaryotic heterologous system. Both homo- and hetero-dimers were successfully reconstituted in mixed detergents. Interactions among Mpc monomers were recorded utilizing paramagnetic relaxation enhancement (PRE) nuclear magnetic resonance (NMR) methods. By single-channel patch-clamp assays, we discovered that both the Mpc1-Mpc2 hetero-dimer and Mpc1 homo-dimer are able to transport K⁺ ions. Furthermore, the Mpc1-Mpc2 hetero-dimer demonstrated the ability to transport pyruvates, at a rate significantly higher than that of the Mpc1 homo-dimer, indicating that it could be the basic functional unit of Mpc complexes. Our findings provide valuable insights for further structural determination and the study of the transport mechanism of Mpc complexes.

Multiplexed kinase interactome profiling quantifies cellular network activity and plasticity

Dynamic changes in protein-protein interaction (PPI) networks underlie all physiological cellular functions and drive devastating human diseases. Profiling PPI networks can, therefore, provide critical insight into disease mechanisms and identify new drug targets. Kinases are regulatory nodes in many PPI networks; yet, facile methods to systematically study kinase interactome dynamics are lacking. We describe kinobead competition and correlation analysis (kiCCA), a quantitative mass spectrometry-based chemoproteomic method for rapid and highly multiplexed profiling of endogenous kinase interactomes. Using kiCCA, we identified 1,154 PPIs of 238 kinases across 18 diverse cancer lines, quantifying context-dependent kinase interactome changes linked to cancer type, plasticity, and signaling states, thereby assembling an extensive knowledgebase for cell signaling research. We discovered drug target candidates, including an endocytic adapter-associated kinase (AAK1) complex that promotes cancer cell epithelial-mesenchymal plasticity and drug resistance. Our data demonstrate the importance of kinase interactome dynamics for cellular signaling in health and disease.

Protein interactome mapping of Porphyromonas gingivalis provides insights into the formation of the PorQ-Z complex of the type IX secretion system

Porphyromonas gingivalis is an anaerobic Gram-negative human oral pathogen highly associated with the more severe forms of periodontal disease. Porphyromonas gingivalis utilises the type IX secretion system (T9SS) to transport ∼30 cargo proteins, including multiple virulence factors, to the cell surface. The T9SS is a multiprotein system consisting of at least 20 proteins, and recently, we characterised the protein interactome of these components. Similar to the T9SS, almost all biological processes are mediated through protein-protein interactions (PPIs). Therefore, mapping PPIs is important to understand the biological functions of many proteins in P. gingivalis. Herein, we provide native migration profiles of over 1000 P. gingivalis proteins. Using the T9SS, we demonstrate that our dataset is a useful resource for identifying novel protein interactions. Using this dataset and further analysis of T9SS P. gingivalis mutants, we discover new mechanistic insights into the formation of the PorQ-Z complex of the T9SS. This dataset is a valuable resource for studies of P. gingivalis.

DDX5 mRNA-targeting antisense oligonucleotide as a new promising therapeutic in combating castration-resistant prostate cancer

The heat shock protein 27 (Hsp27) has emerged as a principal factor of the castration-resistant prostate cancer (CRPC) progression. Also, an antisense oligonucleotide (ASO) against Hsp27 (OGX-427 or apatorsen) has been assessed in different clinical trials. Here, we illustrate that Hsp27 highly regulates the expression of the human DEAD-box protein 5 (DDX5), and we define DDX5 as a novel therapeutic target for CRPC treatment. DDX5 overexpression is strongly correlated with aggressive tumor features, notably with CRPC. DDX5 downregulation using a specific ASO-based inhibitor that acts on DDX5 mRNAs inhibits cell proliferation in preclinical models, and it particularly restores the treatment sensitivity of CRPC. Interestingly, through the identification and analysis of DDX5 protein interaction networks, we have identified some specific functions of DDX5 in CRPC that could contribute actively to tumor progression and therapeutic resistance. We first present the interactions of DDX5 and the Ku70/80 heterodimer and the transcription factor IIH, thereby uncovering DDX5 roles in different DNA repair pathways. Collectively, our study highlights critical functions of DDX5 contributing to CRPC progression and provides preclinical proof of concept that a combination of ASO-directed DDX5 inhibition with a DNA damage-inducing therapy can serve as a highly potential novel strategy to treat CRPC.

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net

Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

NMR Analysis of the Interactions and Conformational Plasticity of Dynein Intermediate Chain

Cytoplasmic dynein complexes play crucial roles in intracellular transport of cellular organelles. While the motor domain of dynein is well characterized by techniques such as X-ray crystallography and cryo-electron microscopy (Cryo-EM), structural representations of dynein usually include only the more packed and easily resolved regions and omit the long flexible and poorly structured regions. One such flexible region is the N-terminal half of the intermediate chain (IC), which contains almost 300 amino acids that are predicted to be disordered. This level of disorder makes IC impossible to study by X-ray crystallography and Cryo-EM, but amenable to study by solution nuclear magnetic resonance (NMR), a powerful technique that can elucidate residue-specific information in a dynamic ensemble of structures, and transient binding interactions of associated proteins. Here, we describe the methods we use to characterize flexible and disordered proteins including protein expression, purification, sample preparation, and NMR data acquisition and analysis.

NucEnvDB: A Database of Nuclear Envelope Proteins and Their Interactions

The nuclear envelope (NE) is a double-membrane system surrounding the nucleus of eukaryotic cells. A large number of proteins are localized in the NE, performing a wide variety of functions, from the bidirectional exchange of molecules between the cytoplasm and the nucleus to chromatin tethering, genome organization, regulation of signaling cascades, and many others. Despite its importance, several aspects of the NE, including its protein-protein interactions, remain understudied. In this work, we present NucEnvDB, a publicly available database of NE proteins and their interactions. Each database entry contains useful annotation including a description of its position in the NE, its interactions with other proteins, and cross-references to major biological repositories. In addition, the database provides users with a number of visualization and analysis tools, including the ability to construct and visualize protein-protein interaction networks and perform functional enrichment analysis for clusters of NE proteins and their interaction partners. The capabilities of NucEnvDB and its analysis tools are showcased by two informative case studies, exploring protein-protein interactions in Hutchinson-Gilford progeria and during SARS-CoV-2 infection at the level of the nuclear envelope.

Co-immunoprecipitation for Assessing Protein-Protein Interactions in Agrobacterium-Mediated Transient Expression System in Nicotiana benthamiana

The characterization of protein-protein interactions (PPI) often provides functional information about a target protein. Yeast-two-hybrid (Y2H) and luminescence/fluorescence-based detections, therefore, have been widely utilized for assessing PPI. In addition, a co-immunoprecipitation (co-IP) method has also been adopted with transient protein expression in Nicotiana benthamiana (N. benthamiana) infiltrated with Agrobacterium tumefaciens. Herein, we describe a co-IP procedure in which structural maintenance of chromosome 1 (SMC1), identified from a Y2H screening, was verified as an interacting partner for microchidia 1 (MORC1), a protein well known for its function in plant immunity and epigenetics. SMC1 and MORC1 were transiently expressed in N. benthamiana when infiltrated by Agrobacterium with the respective genes. From this approach, we identified a region of SMC1 responsible for interacting with MORC1. The co-IP method, of which outputs are mainly from immunoblot analysis, provided information about target protein expression as well, which is often useful for troubleshooting. Using this feature, we showcased a PPI confirmation from our SMC1-MORC1 study in which a full-length SMC1 protein was not detectable, and, therefore, a subsequent truncated mutant analysis had to be employed for PPI verification.

Protein-Protein Interaction Network Mapping by Affinity Purification Cross-Linking Mass Spectrometry (AP-XL-MS) based Proteomics

Protein-protein interactions (PPIs) are the physical interactions formed among proteins. These interactions are primarily functional, i.e., they arise from specific biomolecular events, and each interaction interface serves a specific purpose. A significant number of methods have been developed for protein interactions in the field of proteomics in the last decade. Advanced mass spectrometry technology significantly contributed to the development of these methods. The rapid advancement of groundbreaking MS technology has greatly aided the mapping of protein interaction from large-data sets comprehensively. This chapter describes the affinity purification (AP) mass spectrometry (MS)-based methods combined with chemical cross-linking (XL) of protein complexes. This chapter includes sample preparation methods involving cell culture, cell treatments with ligands, drugs, and cross-linkers, protein extractions, affinity purification, sodium dodecyl sulfate (SDS) polyacrylamide gel separation, in-solution or in-gel digestion, liquid-chromatography, and mass spectrometry analysis of samples (LC-MS/MS). Application of a cleavable cross-linker, dual cleavable cross-linking technology (DUCCT) in combination with the affinity purification (AP) method has also been described. Methods for data analysis using unmodified and cross-linked peptide analysis are discussed.

Tandem Affinity Purification (TAP) of Interacting Prey Proteins with FLAG- and HA-Tagged Bait Proteins

Proteins often interact with each other to form complexes and play functional roles in almost all cellular processes. The study of protein-protein interactions is therefore critical to understand protein function and biological pathways. Affinity Purification coupled with Mass Spectrometry (AP-MS) is an invaluable technique for identifying the interaction partners in protein complexes. In this approach, the protein of interest is fused to an affinity tag, followed by the expression and purification of the fusion protein. The affinity-purified sample is then analyzed by mass spectrometry to identify the interaction partners of the bait proteins. In this chapter, we detail the protocol for tandem affinity purification (TAP) based on the use of the FLAG (a fusion tag with peptide sequence DYKDDDDK) and hemagglutinin (HA) peptide epitopes. The immunoprecipitation using dual-affinity tags offers the advantage of increasing the specificity of the purification with lower nonspecific-background interactions.

Cytoskeletal protein Zyxin in embryonic development: from controlling cell movements and pluripotency to regulating embryonic patterning

The Lim-domain protein Zyxin was initially identified as a minor actin cytoskeleton protein that regulates the assembly and repair of actin filaments. At the same time, additional functions revealed for Zyxin in recent decades indicate that this protein can also play an important role in regulating gene expression and cell differentiation. In this review, we analysed the data in the literature pointing to Zyxin as one of the possible molecular hubs linking morphogenetic cell movements with gene expression, stem cell status regulation and pattern formation during the most complex processes in organism life, embryogenesis.