Yeast Two-Hybrid Assay for Investigating Antiviral Innate Immunity

Yeast two-hybrid (YTH) technology is a powerful tool for studying protein interactions and has been widely used in various fields of molecular biology, including the study of antiviral innate immunity. This chapter presents detailed information and experimental procedures for identifying virus-host protein interactions involved in immune regulation using yeast two-hybrid technology.

A novel OsGST gene encoding 9glutathione reductase negatively regulates cadmium accumulation in rice

Cadmium (Cd) accumulates in rice and then moves up the food chain, causing serious health problems for humans. Glutathione S-transferase (GST) binds exogenous hazardous compounds to glutathione (GSH), which performs a variety of roles in plant responses to Cd stress. Here, Cd stimulated the transcripts of a novel OsGST gene, and the OsGST protein, which was localized in the nucleus and cytoplasm, was also induced by Cd. In OsGST deletion mutant lines generated by CRISPR/Cas9, more Cd was accumulated, and Cd hypersensitive phenotypes were observed, while transgenic lines overexpressing OsGST exhibited enhanced Cd tolerance and less Cd accumulation. Further analysis indicated that the osgst mutants exhibited considerably greater reactive oxygen species (ROS) and higher GSH level, and the antioxidant activity associated genes' expression were down-regulated, imply that OsGST controlled rice Cd accumulation and resistance through preserving the equilibrium of the GSH and redox in rice.

Assessing inorganic nanoparticle toxicity through omics approaches

In the last two decades, the development of nanotechnology has resulted in inorganic nanoparticles playing crucial roles in key industries, ranging from healthcare to energy technologies. For instance, gold and silver nanoparticles are widely used in rapid COVID-19 and flu tests, titania and zinc oxide nanoparticles are commonly found in cosmetic products, and superparamagnetic iron oxide nanoparticles have been clinically exploited as contrast agents and anti-anemia medicines. As a result, human exposure to nanomaterials is continuously increasing, raising concerns about their potential adverse health effects. Historically, the study of nanoparticle toxicity has largely relied on macroscopic observations obtained in different in vitro and in vivo models, resulting in readouts such as median lethal dose, biodistribution profile, and/or histopathological assessment. In recent years, omics methodologies, including transcriptomics, epigenomics, proteomics, metabolomics, and lipidomics, are increasingly used to characterize the biological interactions of nanomaterials, providing a better and broader understanding of their impact and mechanisms of toxicity. These approaches have been able to identify important genes and gene products that mediate toxicological effects, as well as endogenous functions and pathways dysregulated by nanoparticles. Omics methods improve our understanding of nanoparticle biology, and unravel mechanistic insights into nanomedicine-based therapies. This review aims to provide a deeper understanding and new perspectives of omics approaches to characterize the toxicity and biological interactions of inorganic nanoparticles, and improve the safety of nanoparticle applications.

Septins function in exocytosis via physical interactions with the exocyst complex in fission yeast cytokinesis

Septins can function as scaffolds for protein recruitment, membrane-bound diffusion barriers, or membrane curvature sensors. Septins are important for cytokinesis, but their exact roles are still obscure. In fission yeast, four septins (Spn1 to Spn4) accumulate at the rim of the division plane as rings. The octameric exocyst complex, which tethers exocytic vesicles to the plasma membrane, exhibits a similar localization and is essential for plasma membrane deposition during cytokinesis. Without septins, the exocyst spreads across the division plane but absent from the rim during septum formation. These results suggest that septins and the exocyst physically interact for proper localization. Indeed, we predicted six pairs of direct interactions between septin and exocyst subunits by AlphaFold2 ColabFold, most of them are confirmed by co-immunoprecipitation and yeast two-hybrid assays. Exocyst mislocalization results in mistargeting of secretory vesicles and their cargos, which leads to cell-separation delay in septin mutants. Our results indicate that septins guide the targeting of exocyst complex on the plasma membrane for vesicle tethering during cytokinesis through direct physical interactions.

Navigating the landscape of PD-1/PD-L1 imaging tracers: from challenges to opportunities

Immunotherapy targeted to immune checkpoint inhibitors, such as the program cell death receptor (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment. However, it is now well-known that PD-1/PD-L1 immunotherapy response is inconsistent among patients. The current challenge is to customize treatment regimens per patient, which could be possible if the PD-1/PD-L1 expression and dynamic landscape are known. With positron emission tomography (PET) imaging, it is possible to image these immune targets non-invasively and system-wide during therapy. A successful PET imaging tracer should meet specific criteria concerning target affinity, specificity, clearance rate and target-specific uptake, to name a few. The structural profile of such a tracer will define its properties and can be used to optimize tracers in development and design new ones. Currently, a range of PD-1/PD-L1-targeting PET tracers are available from different molecular categories that have shown impressive preclinical and clinical results, each with its own advantages and disadvantages. This review will provide an overview of current PET tracers targeting the PD-1/PD-L1 axis. Antibody, peptide, and antibody fragment tracers will be discussed with respect to their molecular characteristics and binding properties and ways to optimize them.

Nematicidal activity and action mode of a methyl-accepting chemotaxis protein from Pseudomonas syringae against Caenorhabditis elegans

The conventional phytopathogen Pseudomonas syringae reportedly possesses several virulence determinants against Caenorhabditis elegans; however, their action mechanisms remain elusive. This study reports the nematicidal activity and action receptor of a methyl-accepting chemotaxis protein (MCP03) of a wild-type P. syringae MB03 against C. elegans. Purified MCP03 exhibited nematicidal toxicity against C. elegans at a half-lethal concentration of 124.4 μg mL-1, alongside detrimental effects on the growth and brood size of C. elegans. Additionally, MCP03-treated worms exhibited severe pathological destruction of the intestine and depressed wrinkles of the cuticle. Yeast two-hybrid assays identified a subunit of COP9 signalosome, namely CSN-5, which functioned as an MCP03 action receptor. In vitro pull-down verified the binding interaction between MCP03 and CSN-5. RNA interference assays confirmed that MCP03 antagonizes CSN-5, thereby adversely affecting the brood size and cuticle integrity of C. elegans. Following MCP03 infection, the expression of genes related to reproduction, growth, and cuticle formation, such as kgb-1, unc-98, and col-117, was considerably downregulated, indicating pathological changes in MCP03-treated nematodes. Therefore, we proposed that MCP03 antagonizes CSN-5, causing lethality as well as detrimental effects on the fertility, growth, and morphogenesis of C. elegans, which can provide new insights into the signaling pathways and mechanisms underlying the nematicidal action of MCP03 toward C. elegans.

Protein features fusion using attributed network embedding for predicting protein-protein interaction

BACKGROUND

Protein-protein interactions (PPIs) hold significant importance in biology, with precise PPI prediction as a pivotal factor in comprehending cellular processes and facilitating drug design. However, experimental determination of PPIs is laborious, time-consuming, and often constrained by technical limitations.

METHODS

We introduce a new node representation method based on initial information fusion, called FFANE, which amalgamates PPI networks and protein sequence data to enhance the precision of PPIs' prediction. A Gaussian kernel similarity matrix is initially established by leveraging protein structural resemblances. Concurrently, protein sequence similarities are gauged using the Levenshtein distance, enabling the capture of diverse protein attributes. Subsequently, to construct an initial information matrix, these two feature matrices are merged by employing weighted fusion to achieve an organic amalgamation of structural and sequence details. To gain a more profound understanding of the amalgamated features, a Stacked Autoencoder (SAE) is employed for encoding learning, thereby yielding more representative feature representations. Ultimately, classification models are trained to predict PPIs by using the well-learned fusion feature.

RESULTS

When employing 5-fold cross-validation experiments on SVM, our proposed method achieved average accuracies of 94.28%, 97.69%, and 84.05% in terms of Saccharomyces cerevisiae, Homo sapiens, and Helicobacter pylori datasets, respectively.

CONCLUSION

Experimental findings across various authentic datasets validate the efficacy and superiority of this fusion feature representation approach, underscoring its potential value in bioinformatics.

An overview of aptamer: Design strategy, prominent applications, and potential challenge in plants

Aptamers, serving as highly efficient molecular recognition and biotechnology tools, have garnered increasing interest in the realm of plant science in recent years. Aptamers are synthetic single-stranded short nucleotides or peptides, that bind targets with high specificity and affinity, triggering precise biological responses. As an alternative to antibodies, aptamers present promising avenues for advancement in biological researches. Aptamers function in a range of fields, encompassing cell signaling, drug development, biosensor technology, as well as botany, agricultural and forestry sciences. In this review, we introduce classifications and screening methods of aptamers, as well as aptamer-based technologies, highlighting their significant contributions to recent advancements. With their powerful functionality and ability to bind targets with high specificity and affinity, aptamers offer promising opportunities for breakthroughs in plant research.

Three new discovery effector proteins from Candidatus Liberibacter asiaticus psy62 inhibit plant defense through interaction with AtCAT3 and AtGAPA

KEY MESSAGE

We identify three SDEs that inhibiting host defence from Candidatus Liberibacter asiaticus psy62, which is an important supplement to the pathogenesis of HLB. Candidatus Liberibacter asiaticus (CLas) is the main pathogen of citrus Huanglongbing (HLB). 38 new possible sec-dependent effectors (SDEs) of CLas psy62 were predicted by updated predictor SignalP 5.0, which 12 new SDEs were found using alkaline phosphate assay. Among them, SDE4310, SDE4435 and SDE4955 inhibited hypersensitivity reactions (HR) in Arabidopsis thaliana (Arabidopsis, At) and Nicotiana benthamiana leaves induced by pathogens, which lead to a decrease in cell death and reactive oxygen species (ROS) accumulation. And the expression levels of SDE4310, SDE4435, and SDE4955 genes elevated significantly in mild symptom citrus leaves. When SDE4310, SDE4435 and SDE4955 were overexpressed in Arabidopsis, HR pathway key genes pathogenesis-related 2 (PR2), PR5, nonexpressor of pathogenesis-related 1 (NPR1) and isochorismate synthase 1 (ICS1) expression significantly decreased and the growth of pathogen was greatly increased relative to control with Pst DC3000/AvrRps4 treatment. Our findings also indicated that SDE4310, SDE4435 and SDE4955 interacted with AtCAT3 (catalase 3) and AtGAPA (glyceraldehyde-3-phosphate dehydrogenase A). In conclusion, our results suggest that SDE4310, SDE4435 and SDE4955 are CLas psy62 effector proteins that may have redundant functions. They inhibit ROS burst and cell death by interacting with AtCAT3 and AtGAPA to negatively regulate host defense.

ARHGEF18 can promote BVDV NS5B activation of the host NF-κB signaling pathway by combining with the NS5B-palm domain

Rho guanine nucleotide exchange factor 18 (ARHGEF18) is a member of the Rho guanine nucleotide exchange factor (RhoGEF) family. RhoGEF plays an important role in the occurrence of tumors and neurological diseases; however, its involvement in host cell resistance against pathogenic microorganisms is mostly unknown. Herein, we report that bovine viral diarrhea virus (BVDV) nonstructural protein 5B (NS5B) can activate the nuclear factor kappa B (NF-κB) signaling pathway to induce an immune response. To clarify the functional domains of NS5B that activate NF-κB signaling, the six structural domains of NS5B were expressed separately: NS5B-core, NS5B-finger, NS5B-palm, NS5B-thumb, NS5B-N and NS5B-c domain. We preliminarily determined that the functional domains of NS5B that activate NF-κB signaling are the finger and palm domains. We used a bovine kidney cell cDNA library and yeast two-hybrid technology to identify that the host protein ARHGEF18 interacts with NS5B. Co-immunoprecipitation assays showed that ARHGEF18 interacts strongly with NS5B-palm. Interestingly ARHGEF18 could promote NF-κB signaling activation by BVDV NS5B. In addition silencing ARHGEF18 significantly inhibited NS5B-palm activation of NF-κB signaling. We concluded that ARHGEF18 can bind to BVDV NS5B through the palm domain to activate the NF-κB pathway. These findings provide direct evidence that BVDV NS5B induces immune responses by activating NF-κB signaling.

Detection and Analysis of Short Linear Motif-Based Protein-Protein Interactions with SLiMAn2 Web Server

Interactomics is bringing a deluge of data regarding protein-protein interactions (PPIs) which are involved in various molecular processes in all types of cells. However, this information does not easily translate into direct and precise molecular interfaces. This limits our understanding of each interaction network and prevents their efficient modulation. A lot of the detected interactions involve recognition of short linear motifs (SLiMs) by a folded domain while others rely on domain-domain interactions. Functional SLiMs hide among a lot of spurious ones, making deeper analysis of interactomes tedious. Hence, actual contacts and direct interactions are difficult to identify.Consequently, there is a need for user-friendly bioinformatic tools, enabling rapid molecular and structural analysis of SLiM-based PPIs in a protein network. In this chapter, we describe the use of the new webserver SLiMAn to help digging into SLiM-based PPIs in an interactive fashion.

Illuminating the oral microbiome and its host interactions: tools and approaches for molecular microbiology studies

Advancements in DNA sequencing technologies within the last decade have stimulated an unprecedented interest in the human microbiome, largely due the broad diversity of human diseases found to correlate with microbiome dysbiosis. As a direct consequence of these studies, a vast number of understudied and uncharacterized microbes have been identified as potential drivers of mucosal health and disease. The looming challenge in the field is to transition these observations into defined molecular mechanistic studies of symbiosis and dysbiosis. In order to meet this challenge, many of these newly identified microbes will need to be adapted for use in experimental models. Consequently, this review presents a comprehensive overview of the molecular microbiology tools and techniques that have played crucial roles in genetic studies of the bacteria found within the human oral microbiota. Here, we will use specific examples from the oral microbiome literature to illustrate the biology supporting these techniques, why they are needed in the field, and how such technologies have been implemented. It is hoped that this information can serve as a useful reference guide to help catalyze molecular microbiology studies of the many new understudied and uncharacterized species identified at different mucosal sites in the body.

Screening of Tnfaip1-Interacting Proteins in Zebrafish Embryonic cDNA Libraries Using a Yeast Two-Hybrid System

TNFAIP1 regulates cellular biological functions, including DNA replication, DNA repair, and cell cycle, by binding to target proteins. Identification of Tnfaip1-interacting proteins contributes to the understanding of the molecular regulatory mechanisms of their biological functions. In this study, 48 hpf, 72 hpf, and 96 hpf wild-type zebrafish embryo mRNAs were used to construct yeast cDNA library. The library titer was 1.12 × 107 CFU/mL, the recombination rate was 100%, and the average length of the inserted fragments was greater than 1000 bp. A total of 43 potential interacting proteins of Tnfaip1 were identified using zebrafish Tnfaip1 as a bait protein. Utilizing GO functional annotation and KEGG signaling pathway analysis, we found that these interacting proteins are mainly involved in translation, protein catabolic process, ribosome assembly, cytoskeleton formation, amino acid metabolism, and PPAR signaling pathway. Further yeast spotting analyses identified four interacting proteins of Tnfaip1, namely, Ubxn7, Tubb4b, Rpl10, and Ybx1. The Tnfaip1-interacting proteins, screened from zebrafish embryo cDNA in this study, increased our understanding of the network of Tnfaip1-interacting proteins during the earliest embryo development and provided a molecular foundation for the future exploration of tnfaip1's biological functions.

Evaluation of a Series of Turnip Mosaic Virus Chimeric Clones Reveals Two Amino Acid Sites Critical for Systemic Infection in Chinese Cabbage

Two infectious clones of turnip mosaic virus (TuMV), pKBC-1 and pKBC-8, with differential infectivity in Chinese cabbage (Brassica rapa subsp. pekinensis), were obtained. Both infected Nicotiana benthamiana systemically, inducing similar symptoms, whereas only virus KBC-8 infected Chinese cabbage systemically. To identify the determinants affecting infectivity on Chinese cabbage, chimeric clones were constructed by restriction fragment exchange between the parental clones and tested on several Chinese cabbage cultivars. Chimeric clones p1N8C and p8N1C demonstrated that the C-terminal portion of the polyprotein determines systemic infection of Chinese cabbage despite only three amino acid differences in this region, in the cylindrical inclusion (CI), viral protein genome-linked (VPg), and coat protein (CP). A second pair of hybrid constructs, pHindIII-1N8C and pHindIII-8N1C, failed to infect cultivars CR Victory and Jinseonnorang systemically, yet pHindIII-1N8C caused hypersensitive response-like lesions on inoculated leaves of these cultivars, and could systemically infect cultivars CR Chusarang and Jeongsang; this suggests that R genes effective against TuMV may exist in the first two cultivars but not the latter two. Constructs with single amino acid changes in both VPg (K2045E) and CP (Y3095H) failed to infect Chinese cabbage, implying that at least one of these two amino acid substitutions is essential for successful infection on Chinese cabbage. Successful infection by mutant KBC-8-CP-H and delayed infection with mutant HJY1-VPg-E following mutation or reversion suggested that VPg (2045K) is the residue required for infection of Chinese cabbage and involved in the interaction between VPg and eukaryotic initiation factor eIF(iso)4E, confirmed by yeast two-hybrid assay.

Combined prediction and design reveals the target recognition mechanism of an intrinsically disordered protein interaction domain

An increasing number of protein interaction domains and their targets are being found to be intrinsically disordered proteins (IDPs). The corresponding target recognition mechanisms are mostly elusive because of challenges in performing detailed structural analysis of highly dynamic IDP-IDP complexes. Here, we show that by combining recently developed computational approaches with experiments, the structure of the complex between the intrinsically disordered C-terminal domain (CTD) of protein 4.1G and its target IDP region in NuMA can be dissected at high resolution. First, we carry out systematic mutational scanning using dihydrofolate reductase-based protein complementarity analysis to identify essential interaction regions and key residues. The results are found to be highly consistent with an α/β-type complex structure predicted by AlphaFold2 (AF2). We then design mutants based on the predicted structure using a deep learning protein sequence design method. The solved crystal structure of one mutant presents the same core structure as predicted by AF2. Further computational prediction and experimental assessment indicate that the well-defined core structure is conserved across complexes of 4.1G CTD with other potential targets. Thus, we reveal that an intrinsically disordered protein interaction domain uses an α/β-type structure module formed through synergistic folding to recognize broad IDP targets. Moreover, we show that computational prediction and experiment can be jointly applied to segregate true IDP regions from the core structural domains of IDP-IDP complexes and to uncover the structure-dependent mechanisms of some otherwise elusive IDP-IDP interactions.

Combination of in vivo proximity labeling and co-immunoprecipitation identifies the host target network of a tumor-inducing effector in the fungal maize pathogen Ustilago maydis

Plant pathogens secrete effectors, which target host proteins to facilitate infection. The Ustilago maydis effector UmSee1 is required for tumor formation in the leaf during infection of maize. UmSee1 interacts with maize SGT1 (suppressor of G2 allele of skp1) and blocks its phosphorylation in vivo. In the absence of UmSee1, U. maydis cannot trigger tumor formation in the bundle sheath. However, it remains unclear which host processes are manipulated by UmSee1 and the UmSee1-SGT1 interaction to cause the observed phenotype. Proximity-dependent protein labeling involving the turbo biotin ligase tag (TurboID) for proximal labeling of proteins is a powerful tool for identifying the protein interactome. We have generated transgenic U. maydis that secretes biotin ligase-fused See1 effector (UmSee1-TurboID-3HA) directly into maize cells. This approach, in combination with conventional co-immunoprecipitation, allowed the identification of additional UmSee1 interactors in maize cells. Collectively, our data identified three ubiquitin-proteasome pathway-related proteins (ZmSIP1, ZmSIP2, and ZmSIP3) that either interact with or are close to UmSee1 during host infection of maize with U. maydis. ZmSIP3 represents a cell cycle regulator whose degradation appears to be promoted in the presence of UmSee1. Our data provide a possible explanation of the requirement for UmSee1 in tumor formation during U. maydis-Zea mays interaction.

A feature extraction free approach for protein interactome inference from co-elution data

Protein complexes are key functional units in cellular processes. High-throughput techniques, such as co-fractionation coupled with mass spectrometry (CF-MS), have advanced protein complex studies by enabling global interactome inference. However, dealing with complex fractionation characteristics to define true interactions is not a simple task, since CF-MS is prone to false positives due to the co-elution of non-interacting proteins by chance. Several computational methods have been designed to analyze CF-MS data and construct probabilistic protein-protein interaction (PPI) networks. Current methods usually first infer PPIs based on handcrafted CF-MS features, and then use clustering algorithms to form potential protein complexes. While powerful, these methods suffer from the potential bias of handcrafted features and severely imbalanced data distribution. However, the handcrafted features based on domain knowledge might introduce bias, and current methods also tend to overfit due to the severely imbalanced PPI data. To address these issues, we present a balanced end-to-end learning architecture, Software for Prediction of Interactome with Feature-extraction Free Elution Data (SPIFFED), to integrate feature representation from raw CF-MS data and interactome prediction by convolutional neural network. SPIFFED outperforms the state-of-the-art methods in predicting PPIs under the conventional imbalanced training. When trained with balanced data, SPIFFED had greatly improved sensitivity for true PPIs. Moreover, the ensemble SPIFFED model provides different voting schemes to integrate predicted PPIs from multiple CF-MS data. Using the clustering software (i.e. ClusterONE), SPIFFED allows users to infer high-confidence protein complexes depending on the CF-MS experimental designs. The source code of SPIFFED is freely available at: https://github.com/bio-it-station/SPIFFED.

Alzheimer's Disease: Significant Benefit from the Yeast-Based Models

Alzheimer's disease (AD) is an age-related, multifaceted neurological disorder associated with accumulation of aggregated proteins (amyloid Aβ and hyperphosphorylated tau), loss of synapses and neurons, and alterations in microglia. AD was recognized by the World Health Organization as a global public health priority. The pursuit of a better understanding of AD forced researchers to pay attention to well-defined single-celled yeasts. Yeasts, despite obvious limitations in application to neuroscience, show high preservation of basic biological processes with all eukaryotic organisms and offer great advantages over other disease models due to the simplicity, high growth rates on low-cost substrates, relatively simple genetic manipulations, the large knowledge base and data collections, and availability of an unprecedented amount of genomic and proteomic toolboxes and high-throughput screening techniques, inaccessible to higher organisms. Research reviewed above clearly indicates that yeast models, together with other, more simple eukaryotic models including animal models, C. elegans and Drosophila, significantly contributed to understanding Aβ and tau biology. These models allowed high throughput screening of factors and drugs that interfere with Aβ oligomerization, aggregation and toxicity, and tau hyperphosphorylation. In the future, yeast models will remain relevant, with a focus on creating novel high throughput systems to facilitate the identification of the earliest AD biomarkers among different cellular networks in order to achieve the main goal-to develop new promising therapeutic strategies to treat or prevent the disease.

Identification of Protein Complexes by Integrating Protein Abundance and Interaction Features Using a Deep Learning Strategy

Many essential cellular functions are carried out by multi-protein complexes that can be characterized by their protein-protein interactions. The interactions between protein subunits are critically dependent on the strengths of their interactions and their cellular abundances, both of which span orders of magnitude. Despite many efforts devoted to the global discovery of protein complexes by integrating large-scale protein abundance and interaction features, there is still room for improvement. Here, we integrated >7000 quantitative proteomic samples with three published affinity purification/co-fractionation mass spectrometry datasets into a deep learning framework to predict protein-protein interactions (PPIs), followed by the identification of protein complexes using a two-stage clustering strategy. Our deep-learning-technique-based classifier significantly outperformed recently published machine learning prediction models and in the process captured 5010 complexes containing over 9000 unique proteins. The vast majority of proteins in our predicted complexes exhibited low or no tissue specificity, which is an indication that the observed complexes tend to be ubiquitously expressed throughout all cell types and tissues. Interestingly, our combined approach increased the model sensitivity for low abundant proteins, which amongst other things allowed us to detect the interaction of MCM10, which connects to the replicative helicase complex via the MCM6 protein. The integration of protein abundances and their interaction features using a deep learning approach provided a comprehensive map of protein-protein interactions and a unique perspective on possible novel protein complexes.

Thanksgiving to Yeast, the HMGB Proteins History from Yeast to Cancer

Yeasts have been a part of human life since ancient times in the fermentation of many natural products used for food. In addition, in the 20th century, they became powerful tools to elucidate the functions of eukaryotic cells as soon as the techniques of molecular biology developed. Our molecular understandings of metabolism, cellular transport, DNA repair, gene expression and regulation, and the cell division cycle have all been obtained through biochemistry and genetic analysis using different yeasts. In this review, we summarize the role that yeasts have had in biological discoveries, the use of yeasts as biological tools, as well as past and on-going research projects on HMGB proteins along the way from yeast to cancer.

The cyclic peptide G4CP2 enables the modulation of galactose metabolism in yeast by interfering with GAL4 transcriptional activity

Genetically-encoded combinatorial peptide libraries are convenient tools to identify peptides to be used as therapeutics, antimicrobials and functional synthetic biology modules. Here, we report the identification and characterization of a cyclic peptide, G4CP2, that interferes with the GAL4 protein, a transcription factor responsible for the activation of galactose catabolism in yeast and widely exploited in molecular biology. G4CP2 was identified by screening CYCLIC, a Yeast Two-Hybrid-based combinatorial library of cyclic peptides developed in our laboratory. G4CP2 interferes with GAL4-mediated activation of galactose metabolic enzymes both when expressed intracellularly, as a recombinant peptide, and when provided exogenously, as a chemically-synthesized cyclic peptide. Our results support the application of G4CP2 in microbial biotechnology and, additionally, demonstrate that CYCLIC can be used as a tool for the rapid identification of peptides, virtually without any limitations with respect to the target protein. The possible biotechnological applications of cyclic peptides are also discussed.

An NBS-LRR protein in the Rpp1 locus negates the dominance of Rpp1-mediated resistance against Phakopsora pachyrhizi in soybean

The soybean Rpp1 locus confers resistance to Phakopsora pachyrhizi, causal agent of rust, and resistance is usually dominant over susceptibility. However, dominance of Rpp1-mediated resistance is lost when a resistant genotype (Rpp1 or Rpp1b) is crossed with susceptible line TMG06_0011, and the mechanism of this dominant susceptibility (DS) is unknown. Sequencing the Rpp1 region reveals that the TMG06_0011 Rpp1 locus has a single nucleotide-binding site leucine-rich repeat (NBS-LRR) gene (DS-R), whereas resistant PI 594760B (Rpp1b) is similar to PI 200492 (Rpp1) and has three NBS-LRR resistance gene candidates. Evidence that DS-R is the cause of DS was reflected in virus-induced gene silencing of DS-R in Rpp1b/DS-R or Rpp1/DS-R heterozygous plants with resistance partially restored. In heterozygous Rpp1b/DS-R plants, expression of Rpp1b candidate genes was not significantly altered, indicating no effect of DS-R on transcription. Physical interaction of the DS-R protein with candidate Rpp1b resistance proteins was supported by yeast two-hybrid studies and in silico modeling. Thus, we conclude that suppression of resistance most likely does not occur at the transcript level, but instead probably at the protein level, possibly with Rpp1 function inhibited by binding to the DS-R protein. The DS-R gene was found in other soybean lines, with an estimated allele frequency of 6% in a diverse population, and also found in wild soybean (Glycine soja). The identification of a dominant susceptible NBS-LRR gene provides insight into the behavior of NBS-LRR proteins and serves as a reminder to breeders that the dominance of an R gene can be influenced by a susceptibility allele.

A Live Cell Protein Complementation Assay for ORFeome-Wide Probing of Human HOX Interactomes

Biological pathways rely on the formation of intricate protein interaction networks called interactomes. Getting a comprehensive map of interactomes implies the development of tools that allow one to capture transient and low-affinity protein-protein interactions (PPIs) in live conditions. Here we presented an experimental strategy: the Cell-PCA (cell-based protein complementation assay), which was based on bimolecular fluorescence complementation (BiFC) for ORFeome-wide screening of proteins that interact with different bait proteins in the same live cell context, by combining high-throughput sequencing method. The specificity and sensitivity of the Cell-PCA was established by using a wild-type and a single-amino-acid-mutated HOXA9 protein, and the approach was subsequently applied to seven additional human HOX proteins. These proof-of-concept experiments revealed novel molecular properties of HOX interactomes and led to the identification of a novel cofactor of HOXB13 that promoted its proliferative activity in a cancer cell context. Taken together, our work demonstrated that the Cell-PCA was pertinent for revealing and, importantly, comparing the interactomes of different or highly related bait proteins in the same cell context.

Next-Generation Yeast Two-Hybrid Screening to Discover Protein-Protein Interactions

Yeast two-hybrid is a powerful approach to discover new protein-protein interactions. Traditional methods involve screening a target protein against a cDNA expression library and assaying individual positive colonies to identify interacting partners. Here we describe a simple approach to perform yeast two-hybrid screens of a cDNA expression library in batch liquid culture. Positive yeast cell populations are enriched under selection and then harvested en masse. Prey cDNAs are amplified and used as input for next-generation sequencing libraries for identification, quantification, and ranking.

Using PlaPPISite to Predict and Analyze Plant Protein-Protein Interaction Sites

Proteome-wide characterization of protein-protein interactions (PPIs) is crucial to understand the functional roles of protein machinery within cells systematically. With the accumulation of PPI data in different plants, the interaction details of binary PPIs, such as the three-dimensional (3D) structural contexts of interaction sites/interfaces, are urgently demanded. To meet this requirement, we have developed a comprehensive and easy-to-use database called PlaPPISite ( http://zzdlab.com/plappisite/index.php ) to present interaction details for 13 plant interactomes. Here, we provide a clear guide on how to search and view protein interaction details through the PlaPPISite database. Firstly, the running environment of our database is introduced. Secondly, the input file format is briefly introduced. Moreover, we discussed which information related to interaction sites can be achieved through several examples. In addition, some notes about PlaPPISite are also provided. More importantly, we would like to emphasize the importance of interaction site information in plant systems biology through this user guide of PlaPPISite. In particular, the easily accessible 3D structures of PPIs in the coming post-AlphaFold2 era will definitely boost the application of plant interactome to decipher the molecular mechanisms of many fundamental biological issues.

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.

ZmDWF1 regulates leaf angle in maize

Leaf angle (LA) is a critical agronomic trait enhancing grain yield under high-density planting in maize. A number of researches have been conducted in recent years to investigate the quantitative trait loci/genes responsible for LA variation, while only a few genes were identified through map-based cloning. Here we cloned the ZmDWF1 gene, which was previously reported to encode Δ24-sterol reductase in the brassinosteroids (BRs) biosynthesis pathway. Overexpression of ZmDWF1 resulted in enlarged LA, indicating that ZmDWF1 is a positive regulator of LA in maize. To reveal the regulatory framework of ZmDWF1, we conducted RNA-Sequencing and yeast-two hybrid (Y2H) screening analysis. RNA-Sequencing analyzing results indicate ZmDWF1 mainly affected expression level of genes involved in cell wall associated metabolism and hormone metabolism including BR, gibberellin, and auxin. Y2H screening with Bi-FC assay confirmed three proteins (ZmPP2C-1, ZmROF1, and ZmTWD1) interacting with ZmDWF1. We revealed a new regulatory network of ZmDWF1 gene in controlling plant architecture in maize.

MdPP2C24/37, Protein Phosphatase Type 2Cs from Apple, Interact with MdPYL2/12 to Negatively Regulate ABA Signaling in Transgenic Arabidopsis

The phytohormone abscisic acid (ABA) plays an important role in the ability of plants to cope with drought stress. As core members of the ABA signaling pathway, protein phosphatase type 2Cs (PP2Cs) have been reported in many species. However, the functions of MdPP2Cs in apple (Malus domestica) are unclear. In this study, we identified two PP2C-encoding genes, MdPP2C24/37, with conserved PP2C catalytic domains, using sequence alignment. The nucleus-located MdPP2C24/37 genes were induced by ABA or mannitol in apple. Genetic analysis revealed that overexpression of MdPP2C24/37 in Arabidopsis thaliana led to plant insensitivity to ABA or mannitol treatment, in terms of inhibiting seed germination and overall seedling establishment. The expression of stress marker genes was upregulated in MdPP2C24/37 transgenic lines. At the same time, MdPP2C24/37 transgenic lines displayed inhibited ABA-mediated stomatal closure, which led to higher water loss rates. Moreover, when exposed to drought stress, chlorophyll levels decreased and MDA and H₂O₂ levels accumulated in the MdPP2C24/37 transgenic lines. Further, MdPP2C24/37 interacted with MdPYL2/12 in vitro and vivo. The results indicate that MdPP2C24/37 act as negative regulators in response to ABA-mediated drought resistance.

A Cantú syndrome mutation produces dual effects on KATP channels by disrupting ankyrin B regulation

ATP-sensitive potassium (KATP) channels composed of Kir6.x and sulfonylurea receptor (SURs) subunits couple cellular metabolism to electrical activity. Cantú syndrome (CS) is a rare disease caused by mutations in the genes encoding Kir6.1 (KCNJ8) and SUR2A (ABCC9) that produce KATP channel hyperactivity due to a reduced channel block by physiological ATP concentrations. We functionally characterized the p.S1054Y SUR2A mutation identified in two CS carriers, who exhibited a mild phenotype although the mutation was predicted as highly pathogenic. We recorded macroscopic and single-channel currents in CHO and HEK-293 cells and measured the membrane expression of the channel subunits by biotinylation assays in HEK-293 cells. The mutation increased basal whole-cell current density and at the single-channel level, it augmented opening frequency, slope conductance, and open probability (Po), and promoted the appearance of multiple conductance levels. p.S1054Y also reduced Kir6.2 and SUR2A expression specifically at the membrane. Overexpression of ankyrin B (AnkB) prevented these gain- and loss-of-function effects, as well as the p.S1054Y-induced reduction of ATP inhibition of currents measured in inside-out macropatches. Yeast two-hybrid assays suggested that SUR2A WT and AnkB interact, while p.S1054Y interaction with AnkB is decreased. The p.E322K Kir6.2 mutation, which prevents AnkB binding to Kir6.2, produced similar biophysical alterations than p.S1054Y. Our results are the first demonstration of a CS mutation whose functional consequences involve the disruption of AnkB effects on KATP channels providing a novel mechanism by which CS mutations can reduce ATP block. Furthermore, they may help explain the mild phenotype associated with this mutation.

HrpA anchors meningococci to the dynein motor and affects the balance between apoptosis and pyroptosis

BACKGROUND

In Neisseria meningitidis the HrpA/HrpB two-partner secretion system (TPS) was implicated in diverse functions including meningococcal competition, biofilm formation, adherence to epithelial cells, intracellular survival and vacuolar escape. These diverse functions could be attributed to distinct domains of secreted HrpA.

METHODS

A yeast two-hybrid screening, in vitro pull-down assay and immunofluorescence microscopy experiments were used to investigate the interaction between HrpA and the dynein light-chain, Tctex-type 1 (DYNLT1). In silico modeling was used to analyze HrpA structure. Western blot analysis was used to investigate apoptotic and pyroptotic markers.

RESULTS

The HrpA carboxy-terminal region acts as a manganese-dependent cell lysin, while the results of a yeast two-hybrid screening demonstrated that the HrpA middle region has the ability to bind the dynein light-chain, Tctex-type 1 (DYNLT1). This interaction was confirmed by in vitro pull-down assay and immunofluorescence microscopy experiments showing co-localization of N. meningitidis with DYNLT1 in infected epithelial cells. In silico modeling revealed that the HrpA-M interface interacting with the DYNLT1 has similarity with capsid proteins of neurotropic viruses that interact with the DYNLT1. Indeed, we found that HrpA plays a key role in infection of and meningococcal trafficking within neuronal cells, and is implicated in the modulation of the balance between apoptosis and pyroptosis.

CONCLUSIONS

Our findings revealed that N. meningitidis is able to effectively infect and survive in neuronal cells, and that this ability is dependent on HrpA, which establishes a direct protein-protein interaction with DYNLTI in these cells, suggesting that the HrpA interaction with dynein could be fundamental for N. meningitidis spreading inside the neurons. Moreover, we found that the balance between apoptotic and pyroptotic pathways is heavily affected by HrpA.

A Simple Quantitative Assay for Measuring β-Galactosidase Activity Using X-Gal in Yeast-Based Interaction Analyses

Yeast-based interaction assays to determine protein-protein and protein-nucleic acid interactions commonly rely on the reconstitution of chimeric transcription factors that activate the expression of target reporter genes. The enzyme β-galactosidase (β-gal), coded by the LacZ gene of Escherichia coli, is a widely used reporter in yeast systems, and its expression is commonly assessed by evaluating its activity. X-gal (5-bromo-4-chloro-3-indolyl-β-d-galactopyranoside) is an inexpensive and sensitive substrate of β-gal, whose hydrolysis results in an intensely blue colored and easily detectable end product, 5,5'-dibromo-4,4'-dichloro-indigo. The insoluble nature of this end product, however, makes X-gal-based assays unsuitable for direct spectrophotometric absorbance quantification. As such, the use of X-gal is mostly restricted to solid-support approaches, such as colony lift or agar plate assays, which often only provide a qualitative readout. In this article, we describe a quantitative solid-phase X-gal assay to measure protein-protein interaction strength in yeast cells using a simple and low-cost experimental setup. We have optimized multiple aspects of the assay, namely sample preparation, reaction time, and quantification method, for speed and consistency. By integrating the use of a freely available ImageJ-based plugin, we have further standardized the assay for reliability and reproducibility. This improved quantitative X-gal assay can be performed in a standard molecular biology lab without the need for any specialized equipment other than an inexpensive and widely accessible smartphone camera. To exemplify the protocol, we provide detailed step-by-step instructions to perform a quantitative X-gal assay to assess the interaction between two Arabidopsis thaliana proteins, SUPPRESSOR OF PHYA-105 1 (SPA1) and PRODUCTION OF ANTHOCYANIN PIGMENT 2 (PAP2). To demonstrate the sensitivity of our assay in detecting weaker interactions, we also compare the results with a liquid-phase assay that uses ONPG (ortho-nitrophenyl-β-galactopyranoside) as a substrate for β-gal. The quantitative X-gal assay described here can easily be adapted for high-throughout interaction studies and protein domain mapping, even in yeast strains with low levels of LacZ expression. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of competent yeast cells and transformation Alternate Protocol 1: In-house preparation of yeast competent cells for use in lithium acetate (LiAc)-mediated yeast transformation Support Protocol: Long-term storage and revival of frozen yeast strain stocks Basic Protocol 2: Measuring β-galactosidase activity via the quantitative X-gal assay Alternate Protocol 2: Quantification of interaction strength using liquid ONPG assay.

Protein-protein interaction networks as miners of biological discovery

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.

Overexpression of purple acid phosphatase GmPAP2.1 confers resistance to Soybean mosaic virus in a susceptible soybean cultivar

A purple acid phosphatase, GmPAP2.1, from the soybean (Glycine max) cultivar L29 may function as a resistance factor acting against specific strains of Soybean mosaic virus (SMV). In this study, we found that overexpression of GmPAP2.1 from L29 conferred SMV resistance to a susceptible cultivar, Lee 74. We determined that GmPAP2.1 interacted with the SMV protein P1 in the chloroplasts, resulting in the up-regulation of the ICS1 gene, which in turn promoted the pathogen-induced salicylic acid (SA) pathway. SA accumulation was elevated in response to the co-expression of GmPAP2.1 and SMV, while transient knockdown of endogenous SA-related genes resulted in systemic infection by SMV strain G5H, suggesting that GmPAP2.1-derived resistance depended on the SA-pathway for the activation of a defense response. Our findings thus suggest that GmPAP2.1 purple acid phosphatase of soybean cultivar L29 functions as an SA-pathway-dependent resistance factor acting against SMV.

Exploiting the Gal4/UAS System as Plant Orthogonal Molecular Toolbox to Control Reporter Expression in Arabidopsis Protoplasts

The ability of protein domains to fold independently from the rest of the polypeptide is the principle governing the generation of fusion proteins with customized functions. A clear example is the split transcription factor system based on the yeast GAL4 protein and its cognate UAS enhancer. The rare occurrence of the UAS element in the transcriptionally sensitive regions of the Arabidopsis genome makes this transcription factor an ideal orthogonal platform to control reporter induction. Moreover, heterodimeric transcriptional complexes can be generated by exploiting posttranslational modifications hampering or promoting the interaction between GAL4-fused transcriptional partners, whenever this leads to the reconstitution of a fully functional GAL4 factor.The assembly of multiple engineered proteins into a synthetic transcriptional complex requires preliminary testing, before its components can be stably introduced into the plant genome. Mesophyll protoplast transformation represents a fast and reliable technique to test and optimize synthetic regulatory modules. Remarkable properties are the possibility to transform different combinations of plasmids (co-transformation) and the physiological resemblance of these isolated cells with the original tissue.Here we describe an extensive protocol to produce and exploit Arabidopsis mesophyll protoplasts to investigate the transcriptional output of GAL4/UAS-based complexes that are sensitive to posttranslational protein modifications.

ZipA Uses a Two-Pronged FtsZ-Binding Mechanism Necessary for Cell Division

In most bacteria, cell division is centrally organized by the FtsZ protein, which assembles into dynamic filaments at the division site along the cell membrane that interact with other key cell division proteins. In gammaproteobacteria such as Escherichia coli, FtsZ filaments are anchored to the cell membrane by two essential proteins, FtsA and ZipA. Canonically, this interaction was believed to be mediated solely by the FtsZ C-terminal peptide (CTP) domain that interacts with these and several other regulatory proteins. However, we now provide evidence of a second interaction between FtsZ and ZipA. Using site-specific photoactivated cross-linking, we identified a noncanonical FtsZ-binding site on ZipA on the opposite side from the FtsZ CTP-binding pocket. Cross-linking at this site was unaffected by the truncation of the FtsZ linker and CTP domains, indicating that this noncanonical site must interact directly with the globular core domain of FtsZ. Mutations introduced into either the canonical or noncanonical binding sites on ZipA disrupted photo-cross-linking with FtsZ and normal ZipA function in cell division, suggesting that both binding modes are important for normal cell growth and division. One mutation at the noncanonical face was also found to suppress defects of several other canonical and noncanonical site mutations in ZipA, suggesting there is some interdependence between the two sites. Taken together, these results suggest that ZipA employs a two-pronged FtsZ-binding mechanism. IMPORTANCE The tubulin homolog FtsZ plays a central early role in organizing bacterial cell division proteins at the cytoplasmic membrane. However, FtsZ does not directly interact with the membrane itself, instead relying on proteins such as FtsA to tether it to the membrane. In gammaproteobacteria, ZipA serves as a second essential membrane anchor along with FtsA. Although FtsA has a unique role in activating synthesis of the cell division septum, and ZipA may in turn activate FtsA, it was thought that both proteins interacted only with the conserved C terminus of FtsZ and were essentially interchangeable in their ability to tether FtsZ to the membrane. Here we challenge this view, providing evidence that ZipA directly contacts both the C terminus and the core domain of FtsZ. Such a two-pronged interaction between ZipA and FtsZ suggests that ZipA and FtsA may serve distinct membrane-anchoring roles for FtsZ.

Crosslinking mass spectrometry unveils novel interactions and structural distinctions in the model green alga Chlamydomonas reinhardtii

Interactomics is an emerging field that seeks to identify both transient and complex-bound protein interactions that are essential for metabolic functions. Crosslinking mass spectrometry (XL-MS) has enabled untargeted global analysis of these protein networks, permitting largescale simultaneous analysis of protein structure and interactions. Increased commercial availability of highly specific, cell permeable crosslinkers has propelled the study of these critical interactions forward, with the development of MS-cleavable crosslinkers further increasing confidence in identifications. Herein, the global interactome of the unicellular alga Chlamydomonas reinhardtii was analyzed via XL-MS by implementing the MS-cleavable disuccinimidyl sulfoxide (DSSO) crosslinker and enriching for crosslinks using strong cation exchange chromatography. Gentle lysis via repeated freeze-thaw cycles facilitated in vitro analysis of 157 protein-protein crosslinks (interlinks) and 612 peptides linked to peptides of the same protein (intralinks) at 1% FDR throughout the C. reinhardtii proteome. The interlinks confirmed known protein relationships across the cytosol and chloroplast, including coverage on 42% and 38% of the small and large ribosomal subunits, respectively. Of the 157 identified interlinks, 92% represent the first empirical evidence of interaction observed in C. reinhardtii. Several of these crosslinks point to novel associations between proteins, including the identification of a previously uncharacterized Mg-chelatase associated protein (Cre11.g477733.t1.2) bound to seven distinct lysines on Mg-chelatase (Cre06.g306300.t1.2). Additionally, the observed intralinks facilitated characterization of novel protein structures across the C. reinhardtii proteome. Together, these data establish a framework of protein-protein interactions that can be further explored to facilitate understanding of the dynamic protein landscape in C. reinhardtii.

Gene Ontology representation for transcription factor functions

Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular environment. The Gene Ontology (GO) provides a rigorously defined set of concepts that describe the functions of gene products. A GO annotation is a statement about the function of a particular gene product, represented as an association between a gene product and the biological concept a GO term defines. Critically, each GO annotation is based on traceable scientific evidence. Here, we describe the different GO terms that are associated with proteins involved in transcription and its regulation, focusing on the standard of evidence required to support these associations. This article is intended to help users of GO annotations understand how to interpret the annotations and can contribute to the consistency of GO annotations. We distinguish between three classes of activities involved in transcription or directly regulating it - general transcription factors, DNA-binding transcription factors, and transcription co-regulators.

Mechanisms Mediating the Regulation of Peroxisomal Fatty Acid Beta-Oxidation by PPARα

In mammalian cells, two cellular organelles, mitochondria and peroxisomes, share the ability to degrade fatty acid chains. Although each organelle harbors its own fatty acid β-oxidation pathway, a distinct mitochondrial system feeds the oxidative phosphorylation pathway for ATP synthesis. At the same time, the peroxisomal β-oxidation pathway participates in cellular thermogenesis. A scientific milestone in 1965 helped discover the hepatomegaly effect in rat liver by clofibrate, subsequently identified as a peroxisome proliferator in rodents and an activator of the peroxisomal fatty acid β-oxidation pathway. These peroxisome proliferators were later identified as activating ligands of Peroxisome Proliferator-Activated Receptor α (PPARα), cloned in 1990. The ligand-activated heterodimer PPARα/RXRα recognizes a DNA sequence, called PPRE (Peroxisome Proliferator Response Element), corresponding to two half-consensus hexanucleotide motifs, AGGTCA, separated by one nucleotide. Accordingly, the assembled complex containing PPRE/PPARα/RXRα/ligands/Coregulators controls the expression of the genes involved in liver peroxisomal fatty acid β-oxidation. This review mobilizes a considerable number of findings that discuss miscellaneous axes, covering the detailed expression pattern of PPARα in species and tissues, the lessons from several PPARα KO mouse models and the modulation of PPARα function by dietary micronutrients.

CLN3, at the crossroads of endocytic trafficking

The CLN3 gene was identified over two decades ago, but the primary function of the CLN3 protein remains unknown. Recessive inheritance of loss of function mutations in CLN3 are responsible for juvenile neuronal ceroid lipofuscinosis (Batten disease, or CLN3 disease), a fatal childhood onset neurodegenerative disease causing vision loss, seizures, progressive dementia, motor function loss and premature death. CLN3 is a multipass transmembrane protein that primarily localizes to endosomes and lysosomes. Defects in endocytosis, autophagy, and lysosomal function are common findings in CLN3-deficiency model systems. However, the molecular mechanisms underlying these defects have not yet been fully elucidated. In this mini-review, we will summarize the current understanding of the CLN3 protein interaction network and discuss how this knowledge is starting to delineate the molecular pathogenesis of CLN3 disease. Accumulating evidence strongly points towards CLN3 playing a role in regulation of the cytoskeleton and cytoskeletal associated proteins to tether cellular membranes, regulation of membrane complexes such as channels/transporters, and modulating the function of small GTPases to effectively mediate vesicular movement and membrane dynamics.

Heteromeric TRP Channels in Lung Inflammation

Activation of Transient Receptor Potential (TRP) channels can disrupt endothelial barrier function, as their mediated Ca²⁺ influx activates the CaM (calmodulin)/MLCK (myosin light chain kinase)-signaling pathway, and thereby rearranges the cytoskeleton, increases endothelial permeability and thus can facilitate activation of inflammatory cells and formation of pulmonary edema. Interestingly, TRP channel subunits can build heterotetramers, whereas heteromeric TRPC1/4, TRPC3/6 and TRPV1/4 are expressed in the lung endothelium and could be targeted as a protective strategy to reduce endothelial permeability in pulmonary inflammation. An update on TRP heteromers and their role in lung inflammation will be provided with this review.

Dual-fluorescent bacterial two-hybrid system for quantitative Protein-Protein interaction measurement via flow cytometry

Characterization of protein-protein interactions (PPIs) is essential for understanding cellular signal transduction pathways. However, quantitative measurement of the binding strength remains challenging. Building upon the classical bacterial adenylate cyclase two-hybrid (BACTH) system, we previously demonstrated that the relative reporter protein expression (RRPE), defined as the level of reporter expression normalized to that of the interacting protein, is an intrinsic characteristic associated with the binding strength between the two interacting proteins. In this study, we inserted fluorescent protein tdTomato in the chromosome as the reporter protein by CRISPR/Cas9 technology and employed a 12-amino acid tetracysteine (TC) to tag one of the interacting proteins, which can be further labeled by a membrane-permeable biarsenical dye. The combined use of tdTomato and TC-tag offers rapid and high-throughput analysis of the expression levels of both the reporter protein and one of the interacting proteins at the single-cell level by multicolor flow cytometry, which simplifies the quantitative measurement of PPI. The use of the as-developed RRPE-tdTomato-TC-BACTH approach was demonstrated in three demanding applications. First, binding affinities could be correctly ranked for discriminating interaction strengths with a tenfold difference or of the same order of magnitude. We demonstrate that the method is sensitive enough to discriminate affinities with a small difference of 1.4-fold. Moreover, residues involved in PPI can be easily mapped and ranked. Lastly, protein interaction inhibitors can be rapidly screened.

A Novel Cell-Based Intracellular Protein-Protein Interaction Detection Platform (SOLIS) for Multimodality Screening

Intervention in protein-protein interactions (PPIs) has tremendous effects in the molecular therapy of many diseases. To fulfill the requirements for targeting intracellular proteins, here we develop SOS-localization-based interaction screening (SOLIS), which elaborately mimics signaling via the Ras-mitogen-activated protein kinase pathway. SOLIS employs two chimeric proteins in which a membrane localization motif (CaaX) is fused at the C-terminus of a protein of interest and the catalytic domain of SOS is fused at the C-terminus of another protein of interest. Interaction between the two proteins of interest induces membrane localization of the SOS chimera and cell proliferation. Thus, the SOLIS system enables enrichment of superior binders based on cell proliferation in an intracellular PPI-dependent manner. This was verified by three major modalities against intracellular PPIs (small molecules, peptide aptamers, and intrabodies). The system worked over a broad range of affinities (K_D = 0.32-140 nM). In a screening of a site-directed randomized library, novel intrabody clones were selected on the basis of the potency of cell proliferation. Three other PPI detection methods (NanoBiT, SPR, and pull-down assays) were employed to characterize the SOLIS system, and several intrabody clones were judged as false negatives in these assays. SOLIS signals would be less sensitive to the orientation/conformation of the chimeric proteins, and this feature emerges as the advantage of SOLIS as a mammalian cytosolic PPI detection system with few false negatives.

Identification of New Interactions between Endolysosomal Tethering Factors

Proper functioning of the precisely controlled endolysosomal system is essential for maintaining the homeostasis of the entire cell. Tethering factors play pivotal roles in mediating the fusion of different transport vesicles, such as endosomes or autophagosomes with each other or with lysosomes. In this work, we uncover several new interactions between the endolysosomal tethering factors Rabenosyn-5 (Rbsn) and the HOPS and CORVET complexes. We find that Rbsn binds to the HOPS/CORVET complexes mainly via their shared subunit Vps18 and we mapped this interaction to the 773-854 region of Vps18. Based on genetic rescue experiments, the binding between Rbsn and Vps18 is required for endosomal transport and is dispensable for autophagy. Moreover, Vps18 seems to be important for β1 integrin recycling by binding to Rbsn and its known partner Vps45.

Protein Complexes Form a Basis for Complex Hybrid Incompatibility

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

Co-immunoprecipitation Assay for Blue Light-Dependent Protein Interactions in Plants

Co-immunoprecipitation (CoIP) assay has been used as a powerful and routine technique to detect in vivo protein-protein interactions. Not only can it probe stable interactions, but also it is applicable for semiquantitative and inducible protein associations. Here we describe the protocol for detecting blue light-dependent protein interactions, particularly for blue light receptor cryptochrome-mediated complex formation. In addition, we present some notes which may be helpful for common Co-IP study as well.

NGPINT: a next-generation protein-protein interaction software

Mapping protein-protein interactions at a proteome scale is critical to understanding how cellular signaling networks respond to stimuli. Since eukaryotic genomes encode thousands of proteins, testing their interactions one-by-one is a challenging prospect. High-throughput yeast-two hybrid (Y2H) assays that employ next-generation sequencing to interrogate complementary DNA (cDNA) libraries represent an alternative approach that optimizes scale, cost and effort. We present NGPINT, a robust and scalable software to identify all putative interactors of a protein using Y2H in batch culture. NGPINT combines diverse tools to align sequence reads to target genomes, reconstruct prey fragments and compute gene enrichment under reporter selection. Central to this pipeline is the identification of fusion reads containing sequences derived from both the Y2H expression plasmid and the cDNA of interest. To reduce false positives, these fusion reads are evaluated as to whether the cDNA fragment forms an in-frame translational fusion with the Y2H transcription factor. NGPINT successfully recognized 95% of interactions in simulated test runs. As proof of concept, NGPINT was tested using published data sets and it recognized all validated interactions. NGPINT can process interaction data from any biosystem with an available genome or transcriptome reference, thus facilitating the discovery of protein-protein interactions in model and non-model organisms.

Experimental Approaches to Identify Host Factors Important for Influenza Virus

An ever-expanding toolkit of experimental methods provides the means to discover and characterize host factors important for influenza virus. Here, we describe common methods for investigating genetic relationships and physical interactions between virus and host. A comprehensive knowledge of host:virus interactions is key to understanding how influenza virus exploits the host cell and to potentially identify vulnerabilities that may be manipulated to prevent or treat disease.

State-of-the-Art Technologies for Understanding Brassinosteroid Signaling Networks

Brassinosteroids, the steroid hormones of plants, control physiological and developmental processes through its signaling pathway. The major brassinosteroid signaling network components, from the receptor to transcription factors, have been identified in the past two decades. The development of biotechnologies has driven the identification of novel brassinosteroid signaling components, even revealing several crosstalks between brassinosteroid and other plant signaling pathways. Herein, we would like to summarize the identification and improvement of several representative brassinosteroid signaling components through the development of new technologies, including brassinosteroid-insensitive 1 (BRI1), BRI1-associated kinase 1 (BAK1), BR-insensitive 2 (BIN2), BRI1 kinase inhibitor 1 (BKI1), BRI1-suppressor 1 (BSU1), BR signaling kinases (BSKs), BRI1 ethyl methanesulfonate suppressor 1 (BES1), and brassinazole resistant 1 (BZR1). Furthermore, improvement of BR signaling knowledge, such as the function of BKI1, BES1 and its homologous through clustered regularly interspaced short palindromic repeats (CRISPR), the regulation of BIN2 through single-molecule methods, and the new in vivo interactors of BIN2 identified by proximity labeling are described. Among these technologies, recent advanced methods proximity labeling and single-molecule methods will be reviewed in detail to provide insights to brassinosteroid and other phytohormone signaling pathway studies.

A composite filter for low FDR of protein-protein interactions detected by in vivo cross-linking

In vivo chemical cross-linking combined with LCMSMS of digested extracts (in vivo CX-MS) can reveal stable and dynamic protein-protein interactions at proteome-wide scale and at peptide level. In vivo CX-MS requires a membrane permeable and cleavable cross-linker and a fast and sensitive search engine to identify the linked peptides. Here we explore the use of the search engine pLink 2 to identify cross-links induced in exponentially growing Bacillus subtilis cells treated in culture with bis(succinimidyl)-3-azidomethyl-glutarate (BAMG). Cross-linked peptide pairs were identified by pLink 2 in very short time at an overall FDR of <5%. To also obtain a FDR <5% for non-redundant inter-protein cross-linked peptide pairs additional threshold values were applied for matched fragment intensity and for the numbers of unambiguous y and b ions assigned to both composite peptides. Also the mass- and charge-dependent retention times of target peptides purified by diagonal strong cation exchange chromatography were used as a criterion to distinguish true from false positives. After application of the composite filter new protein-protein interactions were revealed among others between the global transcriptional repressor AbrB and elongation factor Tu and between the essential protein YlaN of unknown function and the ferric uptake repressor Fur. SIGNIFICANCE: Important for reliable identification of PPIs by chemical cross-linking in vivo is a low FDR of non-redundant inter-protein peptide pairs. Here we describe how to recognize the presence of spurious interactions in a dataset of cross-linked peptide pairs enriched by 2D strong cation exchange chromatography and identified by LCMSMS by taking into account chromatographic behavior of cross-linked peptide pairs and protein abundance of corresponding peptides. Based on these criteria we assessed that the FDR of the fraction of non-redundant inter-protein cross-linked peptide pairs was approx. 20-25% by interrogating an entire species specific database at an overall FDR of 5% or 0.1% with a search engine that otherwise scores best in sensitivity among other search engines. We have defined a composite filter to decrease this high FDR of inter-protein cross-linked peptide pairs to only about 2%.