Proteomics-based methods for discovery, quantification, and validation of protein-protein interactions

Application of mass spectrometry for the advancement of PROTACs

The advent of targeted protein degradation technologies, particularly Proteolysis-Targeting Chimeras (PROTACs), enable the selective elimination of target proteins and open up new avenues for the treatment of various diseases. This review delves into the pivotal role of mass spectrometry (MS) in the advancement of PROTACs. MS-based methodologies serve as invaluable tools for identifying PROTAC targets, validating their efficacy, and elucidating ubiquitination sites and protein degradation dynamics. These insights profoundly enrich our comprehension of the mechanisms of action and facilitate the rational design of PROTACs. Furthermore, this review discusses the role of MS in the structural analysis of proteins and the formation of ternary complexes crucial for the activity of PROTACs. The synergy between MS and PROTAC technology holds the promise of groundbreaking advancements in drug discovery by deepening our understanding of the underlying mechanisms that govern PROTAC drug action, thereby promoting the development of innovative strategies for disease treatment.

Multi-epitope immunocapture of huntingtin reveals striatum-selective molecular signatures

Huntington's disease (HD) is a debilitating neurodegenerative disorder affecting an individual's cognitive and motor abilities. HD is caused by a mutation in the huntingtin gene producing a toxic polyglutamine-expanded protein (mHTT) and leading to degeneration in the striatum and cortex. Yet, the molecular signatures that underlie tissue-specific vulnerabilities remain unclear. Here, we investigate this aspect by leveraging multi-epitope protein interaction assays, subcellular fractionation, thermal proteome profiling, and genetic modifier assays. The use of human cell, mouse, and fly models afforded capture of distinct subcellular pools of epitope-enriched and tissue-dependent interactions linked to dysregulated cellular pathways and disease relevance. We established an HTT association with nearly all subunits of the transcriptional regulatory Mediator complex (20/26), with preferential enrichment of MED15 in the tail domain. Using HD and KO models, we find HTT modulates the subcellular localization and assembly of the Mediator. We demonstrated striatal enriched and functional interactions with regulators of calcium homeostasis and chromatin remodeling, whose disease relevance was supported by HD fly genetic modifiers assays. Altogether, we offer insights into tissue- and localization-dependent (m)HTT functions and pathobiology.

Comparison of the techniques for isolating immunoassay-suitable proteins from heterogeneous fecal samples

Immunoassays could provide valuable insights into disease biomarkers and gut health by measuring fecal proteins. However, reliably isolating intact proteins from feces is challenging due to its heterogeneous and variable composition. This paper aims to review and compare different methods for extracting proteins from fecal samples to make them suitable for immunoassay analysis. Mechanical homogenization helps release proteins by disrupting solids, while protease inhibitors preserve protein integrity. Detergents like SDS solubilize proteins by disrupting hydrophobic interactions. Organic solvents such as acetone precipitate proteins and remove contaminants. Thermal treatment denatures proteases. Immunocapture uses antibodies to purify target proteins away from interference selectively. Commercial kits contain optimized buffers but may be cost-prohibitive. Combining mechanical, chemical, and immunological techniques synergistically integrates their advantages, improving the recovery of native proteins with reduced matrix effects. While all methods have merits, tailored protocols integrating multiple mechanisms appear most promising for extracting immunoassay-suitable fecal proteins. Further optimization and standardization of such combination approaches matched to proteins and assays of interest helps expand noninvasive fecal proteome analysis.

Advance computational tools for multiomics data learning

The burgeoning field of bioinformatics has seen a surge in computational tools tailored for omics data analysis driven by the heterogeneous and high-dimensional nature of omics data. In biomedical and plant science research multi-omics data has become pivotal for predictive analytics in the era of big data necessitating sophisticated computational methodologies. This review explores a diverse array of computational approaches which play crucial role in processing, normalizing, integrating, and analyzing omics data. Notable methods such similarity-based methods, network-based approaches, correlation-based methods, Bayesian methods, fusion-based methods and multivariate techniques among others are discussed in detail, each offering unique functionalities to address the complexities of multi-omics data. Furthermore, this review underscores the significance of computational tools in advancing our understanding of data and their transformative impact on research.

Rescuing Newcastle disease virus with tag for screening viral-host interacting proteins based on highly efficient reverse genetics

The interaction between viral proteins and host proteins plays a crucial role in the process of virus infecting cells. Tags such as HA, His, and Flag do not interfere with the function of fusion proteins and are commonly used to study protein-protein interactions. Adding these tags to viral proteins will address the challenge of the lack of antibodies for screening host proteins that interact with viral proteins during infection. Obtaining viruses with tagged fusion proteins is crucial. This study established a new reverse genetic system with T7 promoter and three plasmids, which efficiently rescued Newcastle disease virus (NDV) regardless of its ability to replicate in cells. Subsequently, using this system, NDV containing a HA-tagged structural protein and NDV carrying a unique tag on each structural protein were successfully rescued. These tagged viruses replicated normally and exhibited genetic stability. Based on tag antibodies, every NDV structural protein was readily detected and showed correct subcellular localization in infected cells. After infecting cells with NDV carrying HA-tagged M protein, several proteins interacting with the M protein during the infection process were screened using HA tag antibodies. The establishment of this system laid the foundation for comprehensive exploration of the interaction between NDV proteins and host proteins.

Blueberry extract and its bioactive compounds mitigate oxidative stress and suppress human lung cancer cell (A549) growth by modulating the expression of p53/EGFR/STAT3/IL6-mediated signaling molecules

Bioactive phytocompounds are crucial components in all plants. Since the time of traditional medicine, the utilization of plants has been grounded in the potential of these bioactive compounds to treat or manage specific illnesses. These natural bioactive compounds have sparked growing interest in employing medicinal plants for addressing various conditions, such as inflammatory diseases, diabetes, and cancer. This study focuses on assessing the qualitative phytochemical composition, antioxidant potential, and cytotoxic effects of blueberry (Vaccinium sect. Cyanococcus) extract using three different solvents, namely water, ethanol, and methanol. The extract exhibited notable antioxidant activities, as evidenced by DPPH and H2O2 free radical scavenging assays. The cell viability assay also demonstrated cell growth inhibition in A549 cells. Furthermore, nine specific phytocompounds sourced from existing literature were selected for molecular docking studies against CDK6 and, AMPK key protein kinases which enhance the cancer progression. The molecular docking results also revealed favorable binding scores, with a high score of -9.5 kcal/mol in CDK6 protein and a maximum score of AMPK with targets of -8.8 kcal/mol. The selected phytocompounds' pharmacodynamic properties such as ADMET also supported the study. Furthermore, rutin stated that pre-dominantly present in blueberry plants shows a potent cytotoxicity effect in A549 cells. Functional annotations by bioinformatic analysis for rutin also revealed the strong enrichment in the involvement of PI3K/AKT1/STAT, and p53 signaling pathways. Based on this analysis, the identified rutin and other compounds hold a promising anticancer activity. Overall, the comprehensive evaluation of both in vitro and in silico data suggests that the Vaccinium sect. Cyanococcus extract could serve as a valuable source of pharmaceutical agents and may prove effective in future therapeutic applications.

Absolute protein quantification based on calibrated particle counting using electrospray-differential mobility analysis

The traceability of in vitro diagnostics or drug products is based on the accurate quantification of proteins. In this study, we developed an absolute quantification approach for proteins. This method is based on calibrated particle counting using electrospray-differential mobility analysis (ES-DMA) coupled with a condensation particle counter (CPC). The absolute concentration of proteins was quantified with the observed protein particle number measured with ES-DMA-CPC, and the detection efficiency was determined by calibrators. The measurement performance and quantitative level were verified using two certificated reference materials, BSA and NIMCmAb. The linear regression fit for the detection efficiency values of three reference materials and one highly purified protein (myoglobin, BSA, NIMCmAb and fibrinogen) indicated that the detection efficiency and the particle size distribution of these proteins exhibited a linear relationship. Moreover, to explore the suitability of the detection efficiency-particle size curve for protein quantification, the concentrations of three typical proteinaceous particles, including two high molecular weight proteins (NIST reference material 8671 and D-dimer) and one protein complex (glutathione S-transferase dimer), were determined. This work suggests that this calibrated particle counting method is an efficient approach for nondestructive, rapid and accurate quantification of proteins, especially for measuring proteinaceous particles with tremendous size and without reference standards.

Proteomics Analysis of the Polyomavirus DNA Replication Initiation Complex Reveals Novel Functional Phosphorylated Residues and Associated Proteins

Polyomavirus (PyV) Large T-antigen (LT) is the major viral regulatory protein that targets numerous cellular pathways for cellular transformation and viral replication. LT directly recruits the cellular replication factors involved in initiation of viral DNA replication through mutual interactions between LT, DNA polymerase alpha-primase (Polprim), and single-stranded DNA binding complex, (RPA). Activities and interactions of these complexes are known to be modulated by post-translational modifications; however, high-sensitivity proteomic analyses of the PTMs and proteins associated have been lacking. High-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS) of the immunoprecipitated factors (IPMS) identified 479 novel phosphorylated amino acid residues (PAARs) on the three factors; the function of one has been validated. IPMS revealed 374, 453, and 183 novel proteins associated with the three, respectively. A significant transcription-related process network identified by Gene Ontology (GO) enrichment analysis was unique to LT. Although unidentified by IPMS, the ETS protooncogene 1, transcription factor (ETS1) was significantly overconnected to our dataset indicating its involvement in PyV processes. This result was validated by demonstrating that ETS1 coimmunoprecipitates with LT. Identification of a novel PAAR that regulates PyV replication and LT's association with the protooncogenic Ets1 transcription factor demonstrates the value of these results for studies in PyV biology.

Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts

Protein-protein interactions (PPIs) drive cellular processes and responses to environmental cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning framework for studying global PPIs in dynamic contexts. Tapioca predicts de novo interactions by integrating mass spectrometry interactome data from thermal/ion denaturation or cofractionation workflows with protein properties and tissue-specific functional networks. Focusing on the thermal proximity coaggregation method, we improved the experimental workflow. Finely tuned thermal denaturation afforded increased throughput, while cell lysis optimization enhanced protein detection from different subcellular compartments. The Tapioca workflow was next leveraged to investigate viral infection dynamics. Temporal PPIs were characterized during the reactivation from latency of the oncogenic Kaposi's sarcoma-associated herpesvirus. Together with functional assays, NUCKS was identified as a proviral hub protein, and a broader role was uncovered by integrating PPI networks from alpha- and betaherpesvirus infections. Altogether, Tapioca provides a web-accessible platform for predicting PPIs in dynamic contexts.

Proteomics analysis reveals novel phosphorylated residues and associated proteins of the polyomavirus DNA replication initiation complex

Polyomavirus ( PyV ) Large T-antigen ( LT ) is the major viral regulatory protein that targets numerous cellular factors/pathways: tumor suppressors, cell cycle regulators, transcription and chromatin regulators, as well as other factors for viral replication. LT directly recruits the cellular replication factors involved in LT's recognition of the viral origin, origin unwinding, and primer synthesis which is carried out by mutual interactions between LT, DNA polymerase alpha-primase ( Polprim ), and single strand (ss) DNA binding replication protein A ( RPA ). The activities as well as interactions of these three with each other as well as other factors, are known to be modulated by post-translational modifications (PTMs); however, modern high-sensitivity proteomic analyses of the PTMs as well as proteins associated with the three have been lacking. Elution from immunoprecipitation (IP) of the three factors were subjected to high-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS). We identified 479 novel phosphorylated amino acid residues (PAARs) on the three factors: 82 PAARs on SV40 LT, 305 on the Polprim heterotetrametric complex and 92 on the RPA heterotrimeric complex. LC-MS/MS analysis also identified proteins that co-immunoprecipitated (coIP-ed) with the three factors that were not previously reported: 374 with LT, 453 with Polprim and 183 with RPA. We used a bioinformatic-based approach to analyze the proteomics data and demonstrate a highly significant "enrichment" of transcription-related process associated uniquely with LT, consistent with its role as a transcriptional regulator, as opposed to Polprim and RPA associated proteins which showed no such enrichment. The most significant cell cycle related network was regulated by ETS proto-oncogene 1 (ETS1), indicating its involvement in regulatory control of DNA replication, repair, and metabolism. The interaction between LT and ETS1 is validated and shown to be independent of nucleic acids. One of the novel phosphorylated aa residues detected on LT from this study, has been demonstrated by us to affect DNA replication activities of SV40 Large T-antigen. Our data provide substantial additional novel information on PAARs, and proteins associated with PyV LT, and the cellular Polprim-, RPA- complexes which will benefit research in DNA replication, transformation, transcription, and other viral and host cellular processes.

Quantitative Proteomics of the CDK9 Interactome Reveals a Function of the HSP90-CDC37-P-TEFb Complex for BETi-Induced HIV-1 Latency Reactivation

Brd4 has been intensively investigated as a promising drug target because of its implicated functions in oncogenesis, inflammation, and HIV-1 transcription. The formation of the Brd4-P-TEFb (CDK9/Cyclin T1) complex and its regulation of transcriptional elongation are critical for HIV latency reactivation and expression of many oncogenes. To further investigate the mechanism of the Brd4-P-TEFb complex in controlling elongation, mass spectrometry-based quantitative proteomics of the CDK9 interactome was performed. Upon treatment with the selective BET bromodomain inhibitor JQ1, 352 proteins were successfully identified with high confidence as CDK9-interacting proteins. Among them, increased bindings of HSP90 and CDC37 to CDK9 were particularly striking, and our data suggest that the HSP90-CDC37-P-TEFb complex is involved in controlling the dynamic equilibrium of the P-TEFb complex during BETi-induced reactivation of HIV-1 latency. Furthermore, the HSP90-CDC37-P-TEFb complex directly regulates HIV-1 transcription and relies on recruitment by heat shock factor 1 (HSF1) for binding to the HIV-1 promoter. These results advance the understanding of HSP90-CDC37-P-TEFb in HIV-1 latency reversal and enlighten the development of potential strategies to eradicate HIV-1 using a combination of targeted drugs.

Analysis of affinity purification-related proteomic data for studying protein-protein interaction networks in cells

During intracellular signal transduction, protein-protein interactions (PPIs) facilitate protein complex assembly to regulate protein localization and function, which are critical for numerous cellular events. Over the years, multiple techniques have been developed to characterize PPIs to elucidate roles and regulatory mechanisms of proteins. Among them, the mass spectrometry (MS)-based interactome analysis has been increasing in popularity due to its unbiased and informative manner towards understanding PPI networks. However, with MS instrumentation advancing and yielding more data than ever, the analysis of a large amount of PPI-associated proteomic data to reveal bona fide interacting proteins become challenging. Here, we review the methods and bioinformatic resources that are commonly used in analyzing large interactome-related proteomic data and propose a simple guideline for identifying novel interacting proteins for biological research.

Protein-protein interactions in plant antioxidant defense

The regulation of reactive oxygen species (ROS) levels in plants is ensured by mechanisms preventing their over accumulation, and by diverse antioxidants, including enzymes and nonenzymatic compounds. These are affected by redox conditions, posttranslational modifications, transcriptional and posttranscriptional modifications, Ca²⁺, nitric oxide (NO) and mitogen-activated protein kinase signaling pathways. Recent knowledge about protein-protein interactions (PPIs) of antioxidant enzymes advanced during last decade. The best-known examples are interactions mediated by redox buffering proteins such as thioredoxins and glutaredoxins. This review summarizes interactions of major antioxidant enzymes with regulatory and signaling proteins and their diverse functions. Such interactions are important for stability, degradation and activation of interacting partners. Moreover, PPIs of antioxidant enzymes may connect diverse metabolic processes with ROS scavenging. Proteins like receptor for activated C kinase 1 may ensure coordination of antioxidant enzymes to ensure efficient ROS regulation. Nevertheless, PPIs in antioxidant defense are understudied, and intensive research is required to define their role in complex regulation of ROS scavenging.

Protein Interactome Profiling of Stable Molecular Complexes in Biomaterial Lysate

Most proteins function as part of various complexes, forming via stable and dynamic protein-protein interactions (PPIs). The profiling of PPIs expands the fundamental knowledge about the structures, functions, and regulation patterns of protein complexes and intracellular molecular machineries. Protein interactomics aims at solving three main tasks: (1) identification of protein partners and parts of complex intracellular structures; (2) analysis of PPIs parameters (affinity, molecular-recognition specificity, kinetic rate constants, and thermodynamic-parameters determination); (3) the study of the functional role of novel PPIs. The purpose of this work is to update the current state and prospects of multi-omics approaches to profiling of proteins involved in the formation of stable complexes. Methodological paradigm includes a development of protein-extraction and -separation techniques from tissues or cellular lysates and subsequent identification of proteins using mass-spectrometry analysis. In addition, some aspects of authors' experimental platforms, based on high-performance size-exclusion chromatography, procedures of molecular fishing, and protein identification, as well as the possibilities of interactomic taxonomy of each protein, are discussed.

Protein Interaction Networks of Catalytically Active and Catalytically Inactive PqsE in Pseudomonas aeruginosa

Pseudomonas aeruginosa is a human pathogen that relies on quorum sensing to establish infections. The PqsE quorum-sensing protein is required for P. aeruginosa virulence factor production and infection. PqsE has a reported enzymatic function in the biosynthesis of the quorum-sensing autoinducer called PQS. However, this activity is redundant because, in the absence of PqsE, this role is fulfilled by alternative thioesterases. Rather, PqsE drives P. aeruginosa pathogenic traits via a protein-protein interaction with the quorum-sensing receptor/transcription factor RhlR, an interaction that enhances the affinity of RhlR for target DNA sequences. PqsE catalytic activity is dispensable for interaction with RhlR. Thus, the virulence function of PqsE can be decoupled from its catalytic function. Here, we present an immunoprecipitation-mass spectrometry method employing enhanced green fluorescent protein-PqsE fusions to define the protein interactomes of wild-type PqsE and the catalytically inactive PqsE(D73A) variant in P. aeruginosa and their dependence on RhlR. Several proteins were identified to have specific interactions with wild-type PqsE while not forming associations with PqsE(D73A). In the ΔrhlR strain, an increased number of specific PqsE interactors were identified, including the partner autoinducer synthase for RhlR, called RhlI. Collectively, these results suggest that specific protein-protein interactions depend on PqsE catalytic activity and that RhlR may prevent proteins from interacting with PqsE, possibly due to competition between RhlR and other proteins for PqsE binding. Our results provide a foundation for the identification of the in vivo PqsE catalytic function and, potentially, new proteins involved in P. aeruginosa quorum sensing. IMPORTANCE Pseudomonas aeruginosa causes hospital-borne infections in vulnerable patients, including immunocompromised individuals, burn victims, and cancer patients undergoing chemotherapy. There are no effective treatments for P. aeruginosa infections, which are usually broadly resistant to antibiotics. Animal models show that, to establish infection and to cause illness, P. aeruginosa relies on an interaction between two proteins, namely, PqsE and RhlR. There could be additional protein-protein interactions involving PqsE, which, if defined, could be exploited for the design of new therapeutic strategies to combat P. aeruginosa. Here, we reveal previously unknown protein interactions in which PqsE participates, which will be investigated for potential roles in pathogenesis.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

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

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

Dynamics of huntingtin protein interactions in the striatum identifies candidate modifiers of Huntington disease

Huntington disease (HD) is a monogenic neurodegenerative disorder with one causative gene, huntingtin (HTT). Yet, HD pathobiology is multifactorial, suggesting that cellular factors influence disease progression. Here, we define HTT protein-protein interactions (PPIs) perturbed by the mutant protein with expanded polyglutamine in the mouse striatum, a brain region with selective HD vulnerability. Using metabolically labeled tissues and immunoaffinity purification-mass spectrometry, we establish that polyglutamine-dependent modulation of HTT PPI abundances and relative stability starts at an early stage of pathogenesis in a Q140 HD mouse model. We identify direct and indirect PPIs that are also genetic disease modifiers using in-cell two-hybrid and behavioral assays in HD human cell and Drosophila models, respectively. Validated, disease-relevant mHTT-dependent interactions encompass mediators of synaptic neurotransmission (SNAREs and glutamate receptors) and lysosomal acidification (V-ATPase). Our study provides a resource for understanding mHTT-dependent dysfunction in cortico-striatal cellular networks, partly through impaired synaptic communication and endosomal-lysosomal system. A record of this paper's Transparent Peer Review process is included in the supplemental information.

Isolation and Identification of Dengue Virus Interactome with Human Plasma Proteins by Affinity Purification-Mass Spectrometry

Viral proteins evolve to benefit the interaction with host proteins during the infection and replication processes. A comprehensive understanding of virus interactome with host proteins may thus lead to the identification of molecular targets for infection inhibition. We present a procedure for isolating and identifying the dengue virus interactome with human plasma proteins. It comprises the fractionation of human plasma by anion exchange chromatography, followed by affinity purification and mass spectrometry identification of the captured proteins. This procedure was applied to the characterization of the interactions of the four serotypes of dengue virus with human plasma proteins, mediated by the domain III of the envelope protein of the virus. The resulting interactome comprises 62 proteins, six of which were validated as new direct interactions of the virus with its human host.

Large-Scale Protein Interactions Prediction by Multiple Evidence Analysis Associated With an In-Silico Curation Strategy

Predicting the physical or functional associations through protein-protein interactions (PPIs) represents an integral approach for inferring novel protein functions and discovering new drug targets during repositioning analysis. Recent advances in high-throughput data generation and multi-omics techniques have enabled large-scale PPI predictions, thus promoting several computational methods based on different levels of biological evidence. However, integrating multiple results and strategies to optimize, extract interaction features automatically and scale up the entire PPI prediction process is still challenging. Most procedures do not offer an in-silico validation process to evaluate the predicted PPIs. In this context, this paper presents the PredPrIn scientific workflow that enables PPI prediction based on multiple lines of evidence, including the structure, sequence, and functional annotation categories, by combining boosting and stacking machine learning techniques. We also present a pipeline (PPIVPro) for the validation process based on cellular co-localization filtering and a focused search of PPI evidence on scientific publications. Thus, our combined approach provides means to extensive scale training or prediction of new PPIs and a strategy to evaluate the prediction quality. PredPrIn and PPIVPro are publicly available at https://github.com/YasCoMa/predprin and https://github.com/YasCoMa/ppi_validation_process.

From Affinity to Proximity Techniques to Investigate Protein Complexes in Plants

The study of protein–protein interactions (PPIs) is fundamental in understanding the unique role of proteins within cells and their contribution to complex biological systems. While the toolkit to study PPIs has grown immensely in mammalian and unicellular eukaryote systems over recent years, application of these techniques in plants remains under-utilized. Affinity purification coupled to mass spectrometry (AP-MS) and proximity labeling coupled to mass spectrometry (PL-MS) are two powerful techniques that have significantly enhanced our understanding of PPIs. Relying on the specific binding properties of a protein to an immobilized ligand, AP is a fast, sensitive and targeted approach used to detect interactions between bait (protein of interest) and prey (interacting partners) under near-physiological conditions. Similarly, PL, which utilizes the close proximity of proteins to identify potential interacting partners, has the ability to detect transient or hydrophobic interactions under native conditions. Combined, these techniques have the potential to reveal an unprecedented spatial and temporal protein interaction network that better understands biological processes relevant to many fields of interest. In this review, we summarize the advantages and disadvantages of two increasingly common PPI determination techniques: AP-MS and PL-MS and discuss their important application to plant systems.

Visualizing protein-protein interactions in plants by rapamycin-dependent delocalization

Identifying protein-protein interactions (PPIs) is crucial for understanding biological processes. Many PPI tools are available, yet only some function within the context of a plant cell. Narrowing down even further, only a few tools allow complex multi-protein interactions to be visualized. Here, we present a conditional in vivo PPI tool for plant research that meets these criteria. Knocksideways in plants (KSP) is based on the ability of rapamycin to alter the localization of a bait protein and its interactors via the heterodimerization of FKBP and FRB domains. KSP is inherently free from many limitations of other PPI systems. This in vivo tool does not require spatial proximity of the bait and prey fluorophores and it is compatible with a broad range of fluorophores. KSP is also a conditional tool and therefore the visualization of the proteins in the absence of rapamycin acts as an internal control. We used KSP to confirm previously identified interactions in Nicotiana benthamiana leaf epidermal cells. Furthermore, the scripts that we generated allow the interactions to be quantified at high throughput. Finally, we demonstrate that KSP can easily be used to visualize complex multi-protein interactions. KSP is therefore a versatile tool with unique characteristics and applications that complements other plant PPI methods.

Interactions of HIV-1 Capsid with Host Factors and Their Implications for Developing Novel Therapeutics

The Human Immunodeficiency Virus type 1 (HIV-1) virion contains a conical shell, termed capsid, encasing the viral RNA genome. After cellular entry of the virion, the capsid is released and ensures the protection and delivery of the HIV-1 genome to the host nucleus for integration. The capsid relies on many virus-host factor interactions which are regulated spatiotemporally throughout the course of infection. In this paper, we will review the current understanding of the highly dynamic HIV-1 capsid-host interplay during the early stages of viral replication, namely intracellular capsid trafficking after viral fusion, nuclear import, uncoating, and integration of the viral genome into host chromatin. Conventional anti-retroviral therapies primarily target HIV-1 enzymes. Insights of capsid structure have resulted in a first-in-class, long-acting capsid-targeting inhibitor, GS-6207 (Lenacapavir). This inhibitor binds at the interface between capsid protein subunits, a site known to bind host factors, interferes with capsid nuclear import, HIV particle assembly, and ordered assembly. Our review will highlight capsid structure, the host factors that interact with capsid, and high-throughput screening techniques, specifically genomic and proteomic approaches, that have been and can be used to identify host factors that interact with capsid. Better structural and mechanistic insights into the capsid-host factor interactions will significantly inform the understanding of HIV-1 pathogenesis and the development of capsid-centric antiretroviral therapeutics.

Biomarkers of Neurodegeneration and Precision Therapy in Retinal Disease

Vision-threatening retinal diseases affect millions of people worldwide, representing an important public health issue (high social cost) for both technologically advanced and new-industrialized countries. Overall RD group comprises the retinitis pigmentosa, the age-related macular degeneration (AMD), the diabetic retinopathy (DR), and idiopathic epiretinal membrane formation. Endocrine, metabolic, and even lifestyles risk factors have been reported for these age-linked conditions that represent a "public priority" also in this COVID-19 emergency. Chronic inflammation and neurodegeneration characterize the disease evolution, with a consistent vitreoretinal interface impairment. As the vitreous chamber is significantly involved, the latest diagnostic technologies of imaging (retina) and biomarker detection (vitreous) have provided a huge input at both medical and surgical levels. Complement activation and immune cell recruitment/infiltration as well as detrimental intra/extracellular deposits occur in association with a reactive gliosis. The cell/tissue aging route shows a specific signal path and biomolecular profile characterized by the increased expression of several glial-derived mediators, including angiogenic/angiostatic, neurogenic, and stress-related factors (oxidative stress metabolites, inflammation, and even amyloid formation). The possibility to access vitreous chamber by collecting vitreous reflux during intravitreal injection or obtaining vitreous biopsy during a vitrectomy represents a step forward for an individualized therapy. As drug response and protein signature appear unique in each single patient, therapies should be individualized. This review addresses the current knowledge about biomarkers and pharmacological targets in these vitreoretinal diseases. As vitreous fluids might reflect the early stages of retinal sufferance and/or late stages of neurodegeneration, the possibility to modulate intravitreal levels of growth factors, in combination to anti-VEGF therapy, would open to a personalized therapy of retinal diseases.

Interrogating Host Antiviral Environments Driven by Nuclear DNA Sensing: A Multiomic Perspective

Nuclear DNA sensors are critical components of the mammalian innate immune system, recognizing the presence of pathogens and initiating immune signaling. These proteins act in the nuclei of infected cells by binding to foreign DNA, such as the viral genomes of nuclear-replicating DNA viruses herpes simplex virus type 1 (HSV-1) and human cytomegalovirus (HCMV). Upon binding to pathogenic DNA, the nuclear DNA sensors were shown to initiate antiviral cytokines, as well as to suppress viral gene expression. These host defense responses involve complex signaling processes that, through protein–protein interactions (PPIs) and post-translational modifications (PTMs), drive extensive remodeling of the cellular transcriptome, proteome, and secretome to generate an antiviral environment. As such, a holistic understanding of these changes is required to understand the mechanisms through which nuclear DNA sensors act. The advent of omics techniques has revolutionized the speed and scale at which biological research is conducted and has been used to make great strides in uncovering the molecular underpinnings of DNA sensing. Here, we review the contribution of proteomics approaches to characterizing nuclear DNA sensors via the discovery of functional PPIs and PTMs, as well as proteome and secretome changes that define a host antiviral environment. We also highlight the value of and future need for integrative multiomic efforts to gain a systems-level understanding of DNA sensors and their influence on epigenetic and transcriptomic alterations during infection.

Proteomics in Non-model Organisms: A New Analytical Frontier

For the last century we have relied on model organisms to help understand fundamental biological processes. Now, with advancements in genome sequencing, assembly, and annotation, non-model organisms may be studied with the same advanced bioanalytical toolkit as model organisms. Proteomics is one such technique, which classically relies on predicted protein sequences to catalog and measure complex proteomes across tissues and biofluids. Applying proteomics to non-model organisms can advance and accelerate biomimicry studies, biomedical advancements, veterinary medicine, agricultural research, behavioral ecology, and food safety. In this postmodel organism era, we can study almost any species, meaning that many non-model organisms are, in fact, important emerging model organisms. Herein we specifically focus on eukaryotic organisms and discuss the steps to generate sequence databases, analyze proteomic data with or without a database, and interpret results as well as future research opportunities. Proteomics is more accessible than ever before and will continue to rapidly advance in the coming years, enabling critical research and discoveries in non-model organisms that were hitherto impossible.

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

Sequences of the genomes of all-important bacterial pathogens of man, plants, and animals have been completed. Still, it is not enough to achieve complete information of all the mechanisms controlling the biological processes of an organism. Along with all advances in different proteomics technologies, proteomics has completed our knowledge of biological processes all around the world. Proteomics is a valuable technique to explain the complement of proteins in any organism. One of the fields that has been notably benefited from other systems approaches is bacterial pathogenesis. An emerging field is to use proteomics to examine the infectious agents in terms of, among many, the response the host and pathogen to the infection process, which leads to a deeper knowledge of the mechanisms of bacterial virulence. This trend also enables us to identify quantitative measurements for proteins extracted from microorganisms. The present review study is an attempt to summarize a variety of different proteomic techniques and advances. The significant applications in bacterial pathogenesis studies are also covered. Moreover, the areas where proteomics may lead the future studies are introduced.

Use of Multiple Ion Fragmentation Methods to Identify Protein Cross-Links and Facilitate Comparison of Data Interpretation Algorithms

Multiple ion fragmentation methods involving collision-induced dissociation (CID), higher-energy collisional dissociation (HCD) with regular and very high energy settings, and electron-transfer dissociation with supplementary HCD (EThcD) are implemented to improve the confidence of cross-link identifications. Three different S. cerevisiae proteasome samples cross-linked by diethyl suberthioimidate (DEST) or bis(sulfosuccinimidyl)suberate (BS³) are analyzed. Two approaches are introduced to combine interpretations from the above four methods. Working with cleavable cross-linkers such as DEST, the first approach searches for cross-link diagnostic ions and consistency among the best interpretations derived from all four MS² spectra associated with each precursor ion. Better agreement leads to a more definitive identification. Compatible with both cleavable and noncleavable cross-linkers such as BS³, the second approach multiplies scoring metrics from a number of fragmentation experiments to derive an overall best match. This significantly increases the scoring gap between the target and decoy matches. The validity of cross-links fragmented by HCD alone and identified by Kojak, MeroX, pLink, and Xi was evaluated using multiple fragmentation data. Possible ways to improve the identification credibility are discussed. Data are available via ProteomeXchange with identifier PXD018310.

Targeted Identification of Protein Interactions in Eukaryotic mRNA Translation

To identify protein-protein interactions and phosphorylated amino acid sites in eukaryotic mRNA translation, replicate TAP-MudPIT and control experiments are performed targeting Saccharomyces cerevisiae genes previously implicated in eukaryotic mRNA translation by their genetic and/or functional roles in translation initiation, elongation, termination, or interactions with ribosomal complexes. Replicate tandem affinity purifications of each targeted yeast TAP-tagged mRNA translation protein coupled with multidimensional liquid chromatography and tandem mass spectrometry analysis are used to identify and quantify copurifying proteins. To improve sensitivity and minimize spurious, nonspecific interactions, a novel cross-validation approach is employed to identify the most statistically significant protein-protein interactions. Using experimental and computational strategies discussed herein, the previously described protein composition of the canonical eukaryotic mRNA translation initiation, elongation, and termination complexes is calculated. In addition, statistically significant unpublished protein interactions and phosphorylation sites for S. cerevisiae's mRNA translation proteins and complexes are identified.

BioID Combined with Mass Spectrometry to Study Herpesvirus Protein-Protein Interaction Networks

Herpes viruses are important human pathogens that cause a wide range of diseases from skin lesions to malignancies. Protein interactions drive many cellular events and mediate a number of biochemical pathways leading to different physiological outcomes. Protein interactions between viral proteins and host proteins play significant roles in viral entry, replication and suppression of host-immune responses. Therefore, the study of virus-host interactions promises significant advancement in designing therapeutics to control infection and disease. Various approaches are employed in the field to study and identify protein interactions that combine affinity purification along with different detection methods. Advancements in protein purification and high-throughput detection methods have resulted in an unprecedented level of discovery. Here we detail the use of proximity dependent biotinylation (BioID) as a means of affinity purification coupled with the use of LC-MS/MS for the detection and identification of protein-protein interaction networks.

Hdac4 Interactions in Huntington's Disease Viewed Through the Prism of Multiomics

Huntington's disease (HD) is a monogenic disorder, driven by the expansion of a trinucleotide (CAG) repeat within the huntingtin (Htt) gene and culminating in neuronal degeneration in the brain, predominantly in the striatum and cortex. Histone deacetylase 4 (Hdac4) was previously found to contribute to the disease progression, providing a potential therapeutic target. Hdac4 knockdown reduced accumulation of misfolded Htt protein and improved HD phenotypes. However, the underlying mechanism remains unclear, given its independence on deacetylase activity and the predominant cytoplasmic Hdac4 localization in the brain. Here, we undertook a multiomics approach to uncover the function of Hdac4 in the context of HD pathogenesis. We characterized the interactome of endogenous Hdac4 in brains of HD mouse models. Alterations in interactions were investigated in response to Htt polyQ length, comparing mice with normal (Q20) and disease (Q140) Htt, at both pre- and post-symptomatic ages (2 and 10 months, respectively). Parallel analyses for Hdac5, a related class IIa Hdac, highlighted the unique interaction network established by Hdac4. To validate and distinguish interactions specifically enhanced in an HD-vulnerable brain region, we next characterized endogenous Hdac4 interactions in dissected striata from this HD mouse series. Hdac4 associations were polyQ-dependent in the striatum, but not in the whole brain, particularly in symptomatic mice. Hdac5 interactions did not exhibit polyQ dependence. To identify which Hdac4 interactions and functions could participate in HD pathogenesis, we integrated our interactome with proteome and transcriptome data sets generated from the striata. We discovered an overlap in enriched functional classes with the Hdac4 interactome, particularly in vesicular trafficking and synaptic functions, and we further validated the Hdac4 interaction with the Wiskott-Aldrich Syndrome Protein and SCAR Homolog (WASH) complex. This study expands the knowledge of Hdac4 regulation and functions in HD, adding to the understanding of the molecular underpinning of HD phenotypes.

Quantitative Interactome Proteomics Reveals a Molecular Basis for ATF6-Dependent Regulation of a Destabilized Amyloidogenic Protein

Activation of the unfolded protein response (UPR)-associated transcription factor ATF6 has emerged as a promising strategy to reduce the secretion and subsequent toxic aggregation of destabilized, amyloidogenic proteins implicated in systemic amyloid diseases. However, the molecular mechanism by which ATF6 activation reduces the secretion of amyloidogenic proteins remains poorly defined. We employ a quantitative interactomics platform to define how ATF6 activation reduces secretion of a destabilized, amyloidogenic immunoglobulin light chain (LC) associated with light-chain amyloidosis (AL). Using this platform, we show that ATF6 activation increases the targeting of this destabilized LC to a subset of pro-folding ER proteostasis factors that retains the amyloidogenic LC within the ER, preventing its secretion. Our results define a molecular basis for the ATF6-dependent reduction in destabilized LC secretion and highlight the advantage for targeting this UPR-associated transcription factor to reduce secretion of destabilized, amyloidogenic proteins implicated in AL and related systemic amyloid diseases.

Exploring the protein-protein interaction landscape in plants

Protein-protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.

Discovering cellular protein-protein interactions: Technological strategies and opportunities

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

Investigation of host-pathogen interaction between Burkholderia pseudomallei and autophagy-related protein LC3 using hydrophobic chromatography-based technique

BACKGROUND

Burkholderia pseudomallei is an intracellular bacteria causing Melioidosis, the disease widely disseminates in Southeast Asia and Northern Australia. B. pseudomallei has ability to invade various types of host cell and to interfere with host defense mechanisms, such as nitric oxide (NO). Due to the cross-talk among alternative killing mechanisms in host immune response against invading microbes, autophagy is the molecular mechanism belonging to intracellular elimination of eukaryotic cells that has been widely discussed. However, bacterial evasion strategy of B. pseudomallei and host-bacterial protein-protein interaction within autophagic machinery remain unknown.

METHODS

Here, we demonstrated the protein-protein interaction study between different strains of B. pseudomallei, including wild type PP844 and rpoS mutant, with autophagy-related protein LC3 that has been constructed, using the modified immunoaffinity hydrophobic chromatography based-technique. Liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis was utilized for identifying the eluted proteins obtained from the established column. In addition, the expression level of gene encoding candidate protein was predicted prior to verification using real-time quantitative reverse transcription PCR assay (RT-qPCR).

RESULTS

LC3 recombinant proteins could be entrapped inside the column before encountering their bacterial interacting partners. Based on affinity interaction, the binding capacity of LC3 with antibody displayed over 50% readily for hydrophobically binding with bacterial proteins. Following protein identification, bacterial ATP-binding cassette (ABC) transporter periplasmic substrate-binding protein (BPSL2203) was identified as a candidate LC3-interacting protein, which was found only in B. pseudomallei wild type. Gene expression analysis and bioinformatics of BPSL2203 were validated the proteomic result which are suggesting the role of RpoS-dependent gene regulation.

CONCLUSIONS

Remarkably, utilization of the modified immunoaffinity hydrophobic chromatography with LC-MS/MS is a convenient and reliable approach to a study in B. pseudomallei-LC3 protein-protein interaction.

HISTONE DEACETYLASE6 Acts in Concert with Histone Methyltransferases SUVH4, SUVH5, and SUVH6 to Regulate Transposon Silencing

Histone deacetylases (HDACs) play important roles in regulating gene expression. In yeast and animals, HDACs act as components of multiprotein complexes that modulate transcription during various biological processes. However, little is known about the interacting proteins of plant HDACs. To identify the plant HDAC complexes and interacting proteins, we developed an optimized workflow using immunopurification coupled to mass spectrometry-based proteomics in Arabidopsis thaliana We found that the histone deacetylase HDA6 can interact with the histone methyltransferases SUVH4, SUVH5, and SUVH6 (SUVH4/5/6). Domain analysis revealed that the C-terminal regions of HDA6 and SUVH5 are important for their interaction. Furthermore, HDA6 interacts with SUVH4/5/6 and coregulates a subset of transposons through histone H3K9 methylation and H3 deacetylation. In addition, two phosphorylated serine residues, S427 and S429, were unambiguously identified in the C-terminal region of HDA6. Phosphomimetics (amino acid substitutions that mimic a phosphorylated protein) of HDA6 resulted in increased enzymatic activity, whereas the mutation of S427 to alanine in HDA6 abolished its interaction with SUVH5 and SUVH6, suggesting that the phosphorylation of HDA6 is important for its activity and function.

Human Sirtuin 2 Localization, Transient Interactions, and Impact on the Proteome Point to Its Role in Intracellular Trafficking

Human sirtuin 2 (SIRT2) is an NAD⁺-dependent deacetylase that primarily functions in the cytoplasm, where it can regulate α-tubulin acetylation levels. SIRT2 is linked to cancer progression, neurodegeneration, and infection with bacteria or viruses. However, the current knowledge about its interactions and the means through which it exerts its functions has remained limited. Here, we aimed to gain a better understanding of its cellular functions by characterizing SIRT2 subcellular localization, the identity and relative stability of its protein interactions, and its impact on the proteome of primary human fibroblasts. To assess the relative stability of SIRT2 interactions, we used immunoaffinity purification in conjunction with both label-free and metabolic labeling quantitative mass spectrometry. In addition to the expected associations with cytoskeleton proteins, including its known substrate TUBA1A, our results reveal that SIRT2 specifically interacts with proteins functioning in membrane trafficking, secretory processes, and transcriptional regulation. By quantifying their relative stability, we found most interactions to be transient, indicating a dynamic SIRT2 environment. We discover that SIRT2 localizes to the ER-Golgi intermediate compartment (ERGIC), and that this recruitment requires an intact ER-Golgi trafficking pathway. Further expanding these findings, we used microscopy and interaction assays to establish the interaction and coregulation of SIRT2 with liprin-β1 scaffolding protein (PPFiBP1), a protein with roles in focal adhesions disassembly. As SIRT2 functions may be accomplished via interactions, enzymatic activity, and transcriptional regulation, we next assessed the impact of SIRT2 levels on the cellular proteome. SIRT2 knockdown led to changes in the levels of proteins functioning in membrane trafficking, including some of its interaction partners. Altogether, our study expands the knowledge of SIRT2 cytoplasmic functions to define a previously unrecognized involvement in intracellular trafficking pathways, which may contribute to its roles in cellular homeostasis and human diseases.

Two-dimensional blue native/SDS-PAGE analysis of whole cell lysate protein complexes of rice in response to salt stress

To understand the biology of a plant in response to stress, insight into protein-protein interactions, which almost define cell behavior, is thought to be crucial. Here, we provide a comparative complexomics analysis of leaf whole cell lysate of two rice genotypes with contrasting responses to salt using two-dimensional blue native/SDS-PAGE (2D-BN/SDS-PAGE). We aimed to identify changes in subunit composition and stoichiometry of protein complexes elicited by salt. Using mild detergent for protein complex solubilization, we were able to identify 9 protein assemblies as hetero-oligomeric and 30 as homo-oligomeric complexes. A total of 20 proteins were identified as monomers in the 2D-BN/SDS-PAGE gels. In addition to identifying known protein complexes that confirm the technical validity of our analysis, we were also able to discover novel protein-protein interactions. Interestingly, an interaction was detected for glycolytic enzymes enolase (ENO1) and triosephosphate isomerase (TPI) and also for a chlorophyll a-b binding protein and RuBisCo small subunit. To show changes in subunit composition and stoichiometry of protein assemblies during salt stress, the differential abundance of interacting proteins was compared between salt-treated and control plants. A detailed exploration of some of the protein complexes provided novel insight into the function, composition, stoichiometry and dynamics of known and previously uncharacterized protein complexes in response to salt stress.

Identification of Novel Host Interactors of Effectors Secreted by Salmonella and Citrobacter

During infection, pathogenic bacteria face an adverse environment of factors driven by both cellular and humoral defense mechanisms. To help evade the immune response and ultimately proliferate inside the host, many bacteria evolved specialized secretion systems to deliver effector proteins directly into host cells. Translocated effector proteins function to subvert host defense mechanisms. Numerous pathogenic bacteria use a specialized secretion system called type III secretion to deliver effectors into the host cell cytosol. Here, we identified 75 new host targets of Salmonella and Citrobacter effectors, which will help elucidate their mechanisms of action.

Many pathogenic bacteria of the family Enterobacteriaceae use type III secretion systems to inject virulence proteins, termed “effectors,” into the host cell cytosol. Although host-cellular activities of several effectors have been demonstrated, the function and host-targeted pathways of most of the effectors identified to date are largely undetermined. To gain insight into host proteins targeted by bacterial effectors, we performed coaffinity purification of host proteins from cell lysates using recombinant effectors from the Enterobacteriaceae intracellular pathogens Salmonella enterica serovar Typhimurium and Citrobacter rodentium. We identified 54 high-confidence host interactors for the Salmonella effectors GogA, GtgA, GtgE, SpvC, SrfH, SseL, SspH1, and SssB collectively and 21 interactors for the Citrobacter effectors EspT, NleA, NleG1, and NleK. We biochemically validated the interaction between the SrfH Salmonella protein and the extracellular signal-regulated kinase 2 (ERK2) host protein kinase, which revealed a role for this effector in regulating phosphorylation levels of this enzyme, which plays a central role in signal transduction.

IMPORTANCE During infection, pathogenic bacteria face an adverse environment of factors driven by both cellular and humoral defense mechanisms. To help evade the immune response and ultimately proliferate inside the host, many bacteria evolved specialized secretion systems to deliver effector proteins directly into host cells. Translocated effector proteins function to subvert host defense mechanisms. Numerous pathogenic bacteria use a specialized secretion system called type III secretion to deliver effectors into the host cell cytosol. Here, we identified 75 new host targets of Salmonella and Citrobacter effectors, which will help elucidate their mechanisms of action.

Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum)

Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and involved processes. This information would ease the effort and increase the efficacy for similar studies on other legumes. Public access is available at http://14.139.59.221/MauPIR/ .

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

Quantitative Analysis of Dynamic Protein Interactions during Transcription Reveals a Role for Casein Kinase II in Polymerase-associated Factor (PAF) Complex Phosphorylation and Regulation of Histone H2B Monoubiquitylation

Using affinity purification MS approaches, we have identified a novel role for casein kinase II (CKII) in the modification of the polymerase associated factor complex (PAF-C). Our data indicate that the facilitates chromatin transcription complex (FACT) interacts with CKII and may facilitate PAF complex phosphorylation. Posttranslational modification analysis of affinity-isolated PAF-C shows extensive CKII phosphorylation of all five subunits of PAF-C, although CKII subunits were not detected as interacting partners. Consistent with this, recombinant CKII or FACT-associated CKII isolated from cells can phosphorylate PAF-C in vitro, whereas no intrinsic kinase activity was detected in PAF-C samples. Significantly, PAF-C purifications combined with stable isotope labeling in cells (SILAC) quantitation for PAF-C phosphorylation from wild-type and CKII temperature-sensitive strains (cka1Δ cka2-8) showed that PAF-C phosphorylation at consensus CKII sites is significantly reduced in cka1Δ cka2-8 strains. Consistent with a role of CKII in FACT and PAF-C function, we show that decreased CKII function in vivo results in decreased levels of histone H2B lysine 123 monoubiquitylation, a modification dependent on FACT and PAF-C. Taken together, our results define a coordinated role of CKII and FACT in the regulation of RNA polymerase II transcription through chromatin via phosphorylation of PAF-C.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.