Phospho-tyrosine dependent protein-protein interaction network

Pathogenic mutations of human phosphorylation sites affect protein-protein interactions

Despite their lack of a defined 3D structure, intrinsically disordered regions (IDRs) of proteins play important biological roles. Many IDRs contain short linear motifs (SLiMs) that mediate protein-protein interactions (PPIs), which can be regulated by post-translational modifications like phosphorylation. 20% of pathogenic missense mutations are found in IDRs, and understanding how such mutations affect PPIs is essential for unraveling disease mechanisms. Here, we employ peptide-based interaction proteomics to investigate 36 disease-associated mutations affecting phosphorylation sites. Our results unveil significant differences in interactomes between phosphorylated and non-phosphorylated peptides, often due to disrupted phosphorylation-dependent SLiMs. We focused on a mutation of a serine phosphorylation site in the transcription factor GATAD1, which causes dilated cardiomyopathy. We find that this phosphorylation site mediates interaction with 14-3-3 family proteins. Follow-up experiments reveal the structural basis of this interaction and suggest that 14-3-3 binding affects GATAD1 nucleocytoplasmic transport by masking a nuclear localisation signal. Our results demonstrate that pathogenic mutations of human phosphorylation sites can significantly impact protein-protein interactions, offering insights into potential molecular mechanisms underlying pathogenesis.

Expanding the Genetic Code of Xenopus laevis Embryos

The incorporation of unnatural amino acids into proteins through genetic code expansion has been successfully adapted to African claw-toed frog embryos. Six unique unnatural amino acids are incorporated site-specifically into proteins and demonstrate robust and reliable protein expression. Of these amino acids, several are caged analogues that can be used to establish conditional control over enzymatic activity. Using light or small molecule triggers, we exhibit activation and tunability of protein functions in live embryos. This approach was then applied to optical control over the activity of a RASopathy mutant of NRAS, taking advantage of generating explant cultures from Xenopus. Taken together, genetic code expansion is a robust approach in the Xenopus model to incorporate novel chemical functionalities into proteins of interest to study their function and role in a complex biological setting.

Naturally occurring T cell mutations enhance engineered T cell therapies

Adoptive T cell therapies have produced exceptional responses in a subset of patients with cancer. However, therapeutic efficacy can be hindered by poor T cell persistence and function1. In human T cell cancers, evolution of the disease positively selects for mutations that improve fitness of T cells in challenging situations analogous to those faced by therapeutic T cells. Therefore, we reasoned that these mutations could be co-opted to improve T cell therapies. Here we systematically screened the effects of 71 mutations from T cell neoplasms on T cell signalling, cytokine production and in vivo persistence in tumours. We identify a gene fusion, CARD11-PIK3R3, found in a CD4+ cutaneous T cell lymphoma2, that augments CARD11-BCL10-MALT1 complex signalling and anti-tumour efficacy of therapeutic T cells in several immunotherapy-refractory models in an antigen-dependent manner. Underscoring its potential to be deployed safely, CARD11-PIK3R3-expressing cells were followed up to 418 days after T cell transfer in vivo without evidence of malignant transformation. Collectively, our results indicate that exploiting naturally occurring mutations represents a promising approach to explore the extremes of T cell biology and discover how solutions derived from evolution of malignant T cells can improve a broad range of T cell therapies.

Discovery and Characterization of Linear Motif Mediated Protein-Protein Complexes

There are myriads of protein-protein complexes that form within the cell. In addition to classical binding events between globular domains, many protein-protein interactions involve short disordered protein regions. The latter contain so-called linear motifs binding specifically to ordered protein domain surfaces. Linear binding motifs are classified based on their consensus sequence, where only a few amino acids are conserved. In this chapter we will review experimental and in silico techniques that can be used for the discovery and characterization of linear motif mediated protein-protein complexes involved in cellular signaling, protein level and gene expression regulation.

Identification of novel genes including NAV2 associated with isolated tall stature

Very tall people attract much attention and represent a clinically and genetically heterogenous group of individuals. Identifying the genetic etiology can provide important insights into the molecular mechanisms regulating linear growth. We studied a three-generation pedigree with five isolated (non-syndromic) tall members and one individual with normal stature by whole exome sequencing; the tallest man had a height of 211 cm. Six heterozygous gene variants predicted as damaging were shared among the four genetically related tall individuals and not present in a family member with normal height. To gain insight into the putative role of these candidate genes in bone growth, we assessed the transcriptome of murine growth plate by microarray and RNA Seq. Two (Ift140, Nav2) of the six genes were well-expressed in the growth plate. Nav2 (p-value 1.91E-62) as well as Ift140 (p-value of 2.98E-06) showed significant downregulation of gene expression between the proliferative and hypertrophic zone, suggesting that these genes may be involved in the regulation of chondrocyte proliferation and/or hypertrophic differentiation. IFT140, NAV2 and SCAF11 have also significantly associated with height in GWAS studies. Pathway and network analysis indicated functional connections between IFT140, NAV2 and SCAF11 and previously associated (tall) stature genes. Knockout of the all-trans retinoic acid responsive gene, neuron navigator 2 NAV2, in Xenopus supports its functional role as a growth promotor. Collectively, our data expand the spectrum of genes with a putative role in tall stature phenotypes and, among other genes, highlight NAV2 as an interesting gene to this phenotype.

Identification of osteoarthritis-characteristic genes and immunological micro-environment features through bioinformatics and machine learning-based approaches

BACKGROUND

Osteoarthritis (OA) is a multifaceted chronic joint disease characterized by complex mechanisms. It has a detrimental impact on the quality of life for individuals in the middle-aged and elderly population while also imposing a significant socioeconomic burden. At present, there remains a lack of comprehensive understanding regarding the pathophysiology of OA. The objective of this study was to examine the genes, functional pathways, and immune infiltration characteristics associated with the development and advancement of OA.

METHODS

The Gene Expression Omnibus (GEO) database was utilized to acquire gene expression profiles. The R software was employed to conduct the screening of differentially expressed genes (DEGs) and perform enrichment analysis on these genes. The OA-characteristic genes were identified using the Weighted Gene Co-expression Network Analysis (WGCNA) and the Lasso algorithm. In addition, the infiltration levels of immune cells in cartilage were assessed using single-sample gene set enrichment analysis (ssGSEA). Subsequently, a correlation analysis was conducted to examine the relationship between immune cells and the OA-characteristic genes.

RESULTS

A total of 80 DEGs were identified. As determined by functional enrichment, these DEGs were associated with chondrocyte metabolism, apoptosis, and inflammation. Three OA-characteristic genes were identified using WGCNA and the lasso algorithm, and their expression levels were then validated using the verification set. Finally, the analysis of immune cell infiltration revealed that T cells and B cells were primarily associated with OA. In addition, Tspan2, HtrA1 demonstrated a correlation with some of the infiltrating immune cells.

CONCLUSIONS

The findings of an extensive bioinformatics analysis revealed that OA is correlated with a variety of distinct genes, functional pathways, and processes involving immune cell infiltration. The present study has successfully identified characteristic genes and functional pathways that hold potential as biomarkers for guiding drug treatment and facilitating molecular-level research on OA.

DeepSG2PPI: A Protein-Protein Interaction Prediction Method Based on Deep Learning

Protein-protein interaction (PPI) plays an important role in almost all life activities. Many protein interaction sites have been confirmed by biological experiments, but these PPI site identification methods are time-consuming and expensive. In this study, a deep learning-based PPI prediction method, named DeepSG2PPI, is developed. First, the protein sequence information is retrieved and the local context information of each amino acid residue is calculated. A two-dimensional convolutional neural network (2D-CNN) model is employed to extract features from a two-channel coding structure, in which an attention mechanism is embedded to assign higher weights to key features. Second, the global statistical information of each amino acid residue and the relationship graph between the protein and GO (Gene Ontology) function annotation are built, and the graph embedding vector is constructed to represent the biological features of the protein. Finally, a 2D-CNN model and two 1D-CNN models are combined for PPI prediction. The comparison analysis with existing algorithms shows that the DeepSG2PPI method has better performance. It provides more accurate and effective PPI site prediction, which will be helpful in reducing the cost and failure rate of biological experiments.

Association analysis of hepatocellular carcinoma-related hub proteins and hub genes

PURPOSE

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation. This paper presents an association analysis method of HCC-related hub proteins and hub genes.

EXPERIMENTAL DESIGN

Bioinformatics analysis of HCC-related DNA methylation data is carried out to clarify the molecular mechanism of HCC-related genes and to find hub genes (genes with more connections in the network) by constructing in the gene interaction network. This paper proposes an accurate prediction method of protein-protein interaction (PPI) based on deep learning model DeepSG2PPI. The trained DeepSG2PPI model predicts the interaction relationship between the synthetic proteins regulated by HCC-related genes.

RESULTS

This paper finds that four genes are the intersection of hub genes and hub proteins. The four genes are: FBL, CCNB2, ALDH18A1, and RPLP0. The association of RPLP0 gene with HCC is a new finding of this study. RPLP0 is expected to become a new biomarker for the treatment, diagnosis, and prognosis of HCC. The four proteins corresponding to the four genes are: ENSP00000221801, ENSP00000288207, ENSP00000360268, and ENSP00000449328.

CONCLUSIONS AND CLINICAL RELEVANCE

The association between the hub genes with the hub proteins is analyzed. The mutual verification of the hub genes and the hub proteins can obtain more credible HCC-related genes and proteins, which is helpful for the diagnosis, treatment, and drug development of HCC.

PLEKHS1 drives PI3Ks and remodels pathway homeostasis in PTEN-null prostate

The PIP3/PI3K network is a central regulator of metabolism and is frequently activated in cancer, commonly by loss of the PIP3/PI(3,4)P2 phosphatase, PTEN. Despite huge research investment, the drivers of the PI3K network in normal tissues and how they adapt to overactivation are unclear. We find that in healthy mouse prostate PI3K activity is driven by RTK/IRS signaling and constrained by pathway feedback. In the absence of PTEN, the network is dramatically remodeled. A poorly understood YXXM- and PIP3/PI(3,4)P2-binding PH domain-containing adaptor, PLEKHS1, became the dominant activator and was required to sustain PIP3, AKT phosphorylation, and growth in PTEN-null prostate. This was because PLEKHS1 evaded pathway-feedback and experienced enhanced PI3K- and Src-family kinase-dependent phosphorylation of Y258XXM, eliciting PI3K activation. hPLEKHS1 mRNA and activating Y419 phosphorylation of hSrc correlated with PI3K pathway activity in human prostate cancers. We propose that in PTEN-null cells receptor-independent, Src-dependent tyrosine phosphorylation of PLEKHS1 creates positive feedback that escapes homeostasis, drives PIP3 signaling, and supports tumor progression.

A Systematic Compilation of Human SH3 Domains: A Versatile Superfamily in Cellular Signaling

SRC homology 3 (SH3) domains are fundamental modules that enable the assembly of protein complexes through physical interactions with a pool of proline-rich/noncanonical motifs from partner proteins. They are widely studied modular building blocks across all five kingdoms of life and viruses, mediating various biological processes. The SH3 domains are also implicated in the development of human diseases, such as cancer, leukemia, osteoporosis, Alzheimer's disease, and various infections. A database search of the human proteome reveals the existence of 298 SH3 domains in 221 SH3 domain-containing proteins (SH3DCPs), ranging from 13 to 720 kilodaltons. A phylogenetic analysis of human SH3DCPs based on their multi-domain architecture seems to be the most practical way to classify them functionally, with regard to various physiological pathways. This review further summarizes the achievements made in the classification of SH3 domain functions, their binding specificity, and their significance for various diseases when exploiting SH3 protein modular interactions as drug targets.

Missense variant interaction scanning reveals a critical role of the FERM domain for tumor suppressor protein NF2 conformation and function

NF2 (moesin-ezrin-radixin-like [MERLIN] tumor suppressor) is frequently inactivated in cancer, where its NF2 tumor suppressor functionality is tightly coupled to protein conformation. How NF2 conformation is regulated and how NF2 conformation influences tumor suppressor activity is a largely open question. Here, we systematically characterized three NF2 conformation-dependent protein interactions utilizing deep mutational scanning interaction perturbation analyses. We identified two regions in NF2 with clustered mutations which affected conformation-dependent protein interactions. NF2 variants in the F2-F3 subdomain and the α3H helix region substantially modulated NF2 conformation and homomerization. Mutations in the F2-F3 subdomain altered proliferation in three cell lines and matched patterns of disease mutations in NF2 related-schwannomatosis. This study highlights the power of systematic mutational interaction perturbation analysis to identify missense variants impacting NF2 conformation and provides insight into NF2 tumor suppressor function.

Large-scale phosphomimetic screening identifies phospho-modulated motif-based protein interactions

Phosphorylation is a ubiquitous post-translation modification that regulates protein function by promoting, inhibiting or modulating protein-protein interactions. Hundreds of thousands of phosphosites have been identified but the vast majority have not been functionally characterised and it remains a challenge to decipher phosphorylation events modulating interactions. We generated a phosphomimetic proteomic peptide-phage display library to screen for phosphosites that modulate short linear motif-based interactions. The peptidome covers ~13,500 phospho-serine/threonine sites found in the intrinsically disordered regions of the human proteome. Each phosphosite is represented as wild-type and phosphomimetic variant. We screened 71 protein domains to identify 248 phosphosites that modulate motif-mediated interactions. Affinity measurements confirmed the phospho-modulation of 14 out of 18 tested interactions. We performed a detailed follow-up on a phospho-dependent interaction between clathrin and the mitotic spindle protein hepatoma-upregulated protein (HURP), demonstrating the essentiality of the phospho-dependency to the mitotic function of HURP. Structural characterisation of the clathrin-HURP complex elucidated the molecular basis for the phospho-dependency. Our work showcases the power of phosphomimetic ProP-PD to discover novel phospho-modulated interactions required for cellular function.

De Novo Linear Phosphorylation Site Motifs for BCR-ABL Kinase Revealed by Phospho-Proteomics in Yeast

BCR-ABL is the oncogenic fusion product of tyrosine kinase ABL1 and a highly frequent driver of acute lymphocytic leukemia (ALL) and chronic myeloid leukemia (CML). The kinase activity of BCR-ABL is strongly elevated; however, changes of substrate specificity in comparison to wild-type ABL1 kinase are less well characterized. Here, we heterologously expressed full-length BCR-ABL kinases in yeast. We exploited the proteome of living yeast as an in vivo phospho-tyrosine substrate for assaying human kinase specificity. Phospho-proteomic analysis of ABL1 and BCR-ABL isoforms p190 and p210 yielded a high-confidence data set of 1127 phospho-tyrosine sites on 821 yeast proteins. We used this data set to generate linear phosphorylation site motifs for ABL1 and the oncogenic ABL1 fusion proteins. The oncogenic kinases yielded a substantially different linear motif when compared to ABL1. Kinase set enrichment analysis with human pY-sites that have high linear motif scores well-recalled BCR-ABL driven cancer cell lines from human phospho-proteome data sets.

Where protein structure and cell diversity meet

Protein-protein interaction networks - interactomes - are charted with the hope to understand how phenotypes emerge and how they are altered in disease states. Early efforts to map interactomes have focused on the assembly of context agnostic, reference networks. However, recent studies have mapped interactomes across different cell lines and tissues, finding highly variable interactomes due to the rewiring of protein-protein interactions in different contexts. Increasing evidence points to significant links between protein structure and interactome diversity seen across cell types and tissues. We discuss how recent findings support the key role of alternative splicing and phosphorylation, two well-established regulators of protein structural and functional diversity, in defining cell type- and tissue-specific interactomes. Moreover, we show that intrinsically disordered protein regions are most favorably equipped to support interactome rewiring by acting as hubs of protein structure and function regulation.

Evolution of Protein Functional Annotation: Text Mining Study

Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. However, the neXt-CP50 Challenge is more complicated than the missing-protein challenge: the approaches and methods for solving the problem are clear, but neither the concept of protein function nor specific experimental and/or bioinformatics protocols have been standardized to address it. We proposed using a retrospective analysis of the key HPP repository, the neXtProt database, to identify the most frequently used experimental and bioinformatic methods for analyzing protein functions, and the dynamics of accumulation of functional annotations. It has been shown that the dynamics of the increase in the number of proteins with known functions are greater than the progress made in the experimental confirmation of the existence of questionable proteins in the framework of the missing-protein challenge. At the same time, the functional annotation is based on the guilty-by-association postulate, according to which, based on large-scale experiments on API-MS and Y2H, proteins with unknown functions are most likely mapped through “handshakes” to biochemical processes.

A human kinase yeast array for the identification of kinases modulating phosphorylation-dependent protein-protein interactions

Protein kinases play an important role in cellular signaling pathways and their dysregulation leads to multiple diseases, making kinases prime drug targets. While more than 500 human protein kinases are known to collectively mediate phosphorylation of over 290,000 S/T/Y sites, the activities have been characterized only for a minor, intensively studied subset. To systematically address this discrepancy, we developed a human kinase array in Saccharomyces cerevisiae as a simple readout tool to systematically assess kinase activities. For this array, we expressed 266 human kinases in four different S. cerevisiae strains and profiled ectopic growth as a proxy for kinase activity across 33 conditions. More than half of the kinases showed an activity-dependent phenotype across many conditions and in more than one strain. We then employed the kinase array to identify the kinase(s) that can modulate protein-protein interactions (PPIs). Two characterized, phosphorylation-dependent PPIs with unknown kinase-substrate relationships were analyzed in a phospho-yeast two-hybrid assay. CK2α1 and SGK2 kinases can abrogate the interaction between the spliceosomal proteins AAR2 and PRPF8, and NEK6 kinase was found to mediate the estrogen receptor (ERα) interaction with 14-3-3 proteins. The human kinase yeast array can thus be used for a variety of kinase activity-dependent readouts.

From complete cross-docking to partners identification and binding sites predictions

Proteins ensure their biological functions by interacting with each other. Hence, characterising protein interactions is fundamental for our understanding of the cellular machinery, and for improving medicine and bioengineering. Over the past years, a large body of experimental data has been accumulated on who interacts with whom and in what manner. However, these data are highly heterogeneous and sometimes contradictory, noisy, and biased. Ab initio methods provide a means to a "blind" protein-protein interaction network reconstruction. Here, we report on a molecular cross-docking-based approach for the identification of protein partners. The docking algorithm uses a coarse-grained representation of the protein structures and treats them as rigid bodies. We applied the approach to a few hundred of proteins, in the unbound conformations, and we systematically investigated the influence of several key ingredients, such as the size and quality of the interfaces, and the scoring function. We achieved some significant improvement compared to previous works, and a very high discriminative power on some specific functional classes. We provide a readout of the contributions of shape and physico-chemical complementarity, interface matching, and specificity, in the predictions. In addition, we assessed the ability of the approach to account for protein surface multiple usages, and we compared it with a sequence-based deep learning method. This work may contribute to guiding the exploitation of the large amounts of protein structural models now available toward the discovery of unexpected partners and their complex structure characterisation.

Natural genetic variation in Drosophila melanogaster reveals genes associated with Coxiella burnetii infection

The gram-negative bacterium Coxiella burnetii is the causative agent of Query (Q) fever in humans and coxiellosis in livestock. Host genetics are associated with C. burnetii pathogenesis both in humans and animals; however, it remains unknown if specific genes are associated with severity of infection. We employed the Drosophila Genetics Reference Panel to perform a genome-wide association study to identify host genetic variants that affect host survival to C. burnetii infection. The genome-wide association study identified 64 unique variants (P < 10⁻⁵) associated with 25 candidate genes. We examined the role each candidate gene contributes to host survival during C. burnetii infection using flies carrying a null mutation or RNAi knockdown of each candidate. We validated 15 of the 25 candidate genes using at least one method. This is the first report establishing involvement of many of these genes or their homologs with C. burnetii susceptibility in any system. Among the validated genes, FER and tara play roles in the JAK/STAT, JNK, and decapentaplegic/TGF-β signaling pathways which are components of known innate immune responses to C. burnetii infection. CG42673 and DIP-ε play roles in bacterial infection and synaptic signaling but have no previous association with C. burnetii pathogenesis. Furthermore, since the mammalian ortholog of CG13404 (PLGRKT) is an important regulator of macrophage function, CG13404 could play a role in host susceptibility to C. burnetii through hemocyte regulation. These insights provide a foundation for further investigation regarding the genetics of C. burnetii susceptibility across a wide variety of hosts.

Exploring absent protein function in yeast: assaying post translational modification and human genetic variation

Yeast is a valuable eukaryotic model organism that has evolved many processes conserved up to humans, yet many protein functions, including certain DNA and protein modifications, are absent. It is this absence of protein function that is fundamental to approaches using yeast as an in vivo test system to investigate human proteins. Functionality of the heterologous expressed proteins is connected to a quantitative, selectable phenotype, enabling the systematic analyses of mechanisms and specificity of DNA modification, post-translational protein modifications as well as the impact of annotated cancer mutations and coding variation on protein activity and interaction. Through continuous improvements of yeast screening systems, this is increasingly carried out on a global scale using deep mutational scanning approaches. Here we discuss the applicability of yeast systems to investigate absent human protein function with a specific focus on the impact of protein variation on protein-protein interaction modulation.

A Novel Protein-Protein Interaction between RSK3 and IκBα and a New Binding Inhibitor That Suppresses Breast Cancer Tumorigenesis

Multiple cancer-related biological processes are mediated by protein-protein interactions (PPIs). Through interactions with a variety of factors, members of the ribosomal S6 kinase (RSK) family play roles in cell cycle progression and cell proliferation. In particular, RSK3 contributes to cancer viability, but the underlying mechanisms remain unknown. We performed a kinase library screen to find IκBα PPI binding partners and identified RSK3 as a novel IκBα binding partner using a cell-based distribution assay. In addition, we discovered a new PPI inhibitor using mammalian two-hybrid (MTH) analysis. We assessed the antitumor effects of the new inhibitor using cell proliferation and colony formation assays and monitored the rate of cell death by FACS apoptosis assay. IκBα is phosphorylated by the active form of the RSK3 kinase. A small-molecule inhibitor that targets the RSK3/IκBα complex exhibited antitumor activity in breast cancer cells and increased their rate of apoptosis. RSK3 phosphorylation and RSK3/IκBα complex formation might be functionally important in breast tumorigenesis. The RSK3/IκBα-specific binding inhibitor identified in this study represents a lead compound for the development of new anticancer drugs.

Epidermal PAR-6 and PKC-3 are essential for larval development of C. elegans and organize non-centrosomal microtubules

The cortical polarity regulators PAR-6, PKC-3, and PAR-3 are essential for the polarization of a broad variety of cell types in multicellular animals. In C. elegans, the roles of the PAR proteins in embryonic development have been extensively studied, yet little is known about their functions during larval development. Using inducible protein degradation, we show that PAR-6 and PKC-3, but not PAR-3, are essential for postembryonic development. PAR-6 and PKC-3 are required in the epidermal epithelium for animal growth, molting, and the proper pattern of seam-cell divisions. Finally, we uncovered a novel role for PAR-6 in organizing non-centrosomal microtubule arrays in the epidermis. PAR-6 was required for the localization of the microtubule organizer NOCA-1/Ninein, and defects in a noca-1 mutant are highly similar to those caused by epidermal PAR-6 depletion. As NOCA-1 physically interacts with PAR-6, we propose that PAR-6 promotes non-centrosomal microtubule organization through localization of NOCA-1/Ninein.

Design of Tunable Protein Interfaces Controlled by Post-Translational Modifications

The design of protein interaction interfaces is a cornerstone of synthetic biology, where they can be used to promote the association of protein subunits into active molecular complexes or into protein nanostructures. In nature, protein interactions can be modulated by post-translational modifications (PTMs) that modify the protein interfaces with the addition and removal of various chemical groups. PTMs thus represent a means to gain control over protein interactions, yet they have seldom been considered in the design of synthetic proteins. Here, we explore the potential of a reversible PTM, serine phosphorylation, to modulate the interactions between peptides. We designed a series of interacting peptide pairs, including heterodimeric coiled coils, that contained one or more protein kinase A (PKA) recognition motifs. Our set of peptide pairs comprised interactions ranging from nanomolar to micromolar affinities. Mass spectrometry analyses showed that all peptides were excellent phosphorylation substrates of PKA, and subsequent phosphate removal could be catalyzed by lambda protein phosphatase. Binding kinetics measurements performed before and after treatment of the peptides with PKA revealed that phosphorylation of the target serines affected both the association and dissociation rates of the interacting peptides. We observed both the strengthening of interactions (up to an 11-fold decrease in K_d) and the weakening of interactions (up to a 180-fold increase in K_d). De novo-designed PTM-modulated interfaces will be useful to control the association of proteins in biological systems using protein-modifying enzymes, expanding the paradigm of self-assembly to encompass controlled assembly of engineerable protein complexes.

TSPAN9 suppresses the chemosensitivity of gastric cancer to 5-fluorouracil by promoting autophagy

Background

The issue of drug resistance in gastric cancer has attracted global attention. TSPAN9, a 4-transmembrane protein that plays an important role in tumor progression and signal transduction, has been found to be closely related to tumor invasion, metastasis, and autophagy.

Methods

Immunoblotting was used to evaluate TSPAN9 expression in parental and drug-resistant gastric cancer cells. Functional assays, such as the CCK-8 assay, were used to detect the proliferation of gastric cancer cells and the response of TSPAN9 to 5-fluorouracil (5-FU). Western blotting was used to analyze the expression of constituents of the PI3K/AKT/mTOR-mediated autophagy pathway induced by TSPAN9. Coimmunoprecipitation was performed to assess the specific mechanism by which TSPAN9 affects the PI3K pathway.

Results

We demonstrated that TSPAN9 is overexpressed in 5-FU-resistant cells compared to parental cells. 5-FU-mediated inhibition of cell proliferation can be significantly restored by increasing TSPAN9 expression, and inhibiting this expression in drug-resistant cells can restore the sensitivity of the cells to 5-FU. In addition, TSPAN9 also significantly promoted autophagy in gastric cancer cells in vitro. Further studies indicated that TSPAN9 downregulates the expression of PI3K and proteins associated with PI3K-mediated autophagy. In addition, TSPAN9 interacts with PI3K and inhibits its catalytic activity.

Conclusion

The current study reveals the important role of TSPAN9 in drug resistance to 5-FU in gastric cancer. It also provides a new target to clinically address drug-resistant gastric cancer and will contribute to the treatment strategy of this disease.

Genetics' Piece of the PI: Inferring the Origin of Complex Traits and Diseases from Proteome-Wide Protein-Protein Interaction Dynamics

How do common and rare genetic polymorphisms contribute to quantitative traits or disease risk and progression? Multiple human traits have been extensively characterized at the genomic level, revealing their complex genetic architecture. However, it is difficult to resolve the mechanisms by which specific variants contribute to a phenotype. Recently, analyses of variant effects on molecular traits have uncovered intermediate mechanisms that link sequence variation to phenotypic changes. Yet, these methods only capture a fraction of genetic contributions to phenotype. Here, in reviewing the field, it is proposed that complex traits can be understood by characterizing the dynamics of biochemical networks within living cells, and that the effects of genetic variation can be captured on these networks by using protein-protein interaction (PPI) methodologies. This synergy between PPI methodologies and the genetics of complex traits opens new avenues to investigate the molecular etiology of human diseases and to facilitate their prevention or treatment.

Defining Human Tyrosine Kinase Phosphorylation Networks Using Yeast as an In Vivo Model Substrate

Systematic assessment of tyrosine kinase-substrate relationships is fundamental to a better understanding of cellular signaling and its profound alterations in human diseases such as cancer. In human cells, such assessments are confounded by complex signaling networks, feedback loops, conditional activity, and intra-kinase redundancy. Here we address this challenge by exploiting the yeast proteome as an in vivo model substrate. We individually expressed 16 human non-receptor tyrosine kinases (NRTKs) in Saccharomyces cerevisiae and identified 3,279 kinase-substrate relationships involving 1,351 yeast phosphotyrosine (pY) sites. Based on the yeast data without prior information, we generated a set of linear kinase motifs and assigned ∼1,300 known human pY sites to specific NRTKs. Furthermore, experimentally defined pY sites for each individual kinase were shown to cluster within the yeast interactome network irrespective of linear motif information. We therefore applied a network inference approach to predict kinase-substrate relationships for more than 3,500 human proteins, providing a resource to advance our understanding of kinase biology.

Circadian regulation in human white adipose tissue revealed by transcriptome and metabolic network analysis

Studying circadian rhythms in most human tissues is hampered by difficulty in collecting serial samples. Here we reveal circadian rhythms in the transcriptome and metabolic pathways of human white adipose tissue. Subcutaneous adipose tissue was taken from seven healthy males under highly controlled 'constant routine' conditions. Five biopsies per participant were taken at six-hourly intervals for microarray analysis and in silico integrative metabolic modelling. We identified 837 transcripts exhibiting circadian expression profiles (2% of 41619 transcript targeting probes on the array), with clear separation of transcripts peaking in the morning (258 probes) and evening (579 probes). There was only partial overlap of our rhythmic transcripts with published animal adipose and human blood transcriptome data. Morning-peaking transcripts associated with regulation of gene expression, nitrogen compound metabolism, and nucleic acid biology; evening-peaking transcripts associated with organic acid metabolism, cofactor metabolism and redox activity. In silico pathway analysis further indicated circadian regulation of lipid and nucleic acid metabolism; it also predicted circadian variation in key metabolic pathways such as the citric acid cycle and branched chain amino acid degradation. In summary, in vivo circadian rhythms exist in multiple adipose metabolic pathways, including those involved in lipid metabolism, and core aspects of cellular biochemistry.

Visualizing Post-Translational Modifications in Protein Interaction Networks Using PTMOracle

Post-translational modifications (PTMs) of proteins act as key regulators of protein activity, including the regulation of protein-protein interactions (PPIs). However, exploring functional links between PTMs and PPIs can be difficult. PTMOracle is a Cytoscape app that facilitates the co-visualization and co-analysis of PTMs in the context of PPI networks. PTMOracle also allows extensive data to be integrated and co-analyzed, allowing the role of domains, motifs, and disordered regions to be considered. Here, we describe several PTMOracle protocols investigating complex PTM-associated relationships and their role in PPIs. This is assisted by OraclePainter for coloring proteins by the modifications present and visualizing these in the context of networks, by OracleTools for cross-matching PTMs with sequence feature for all nodes in the network, and by OracleResults for exploring specific proteins and visualizing their PTMs in the context of protein sequences. This unit aims to demonstrate how PTMOracle can be used to systematically explore network visualizations and generate testable hypotheses regarding the functional role of PTMs in PPIs, and how the results can be analyzed to better understand the regulatory role of PTMs in PPIs. © 2019 by John Wiley & Sons, Inc.

Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set

The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule’s interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release.

Genetic variants might exert their functional effects via influencing molecular interaction. Here, the authors present a resource featuring almost 28,000 annotations describing the effect of small sequence changes on physical protein interactions, curated by IMEx Consortium curators.

Histidine N(τ)-cyclized macrocycles as a new genre of polo-like kinase 1 polo-box domain-binding inhibitors

Transition toward peptide mimetics of reduced size is an important objective of peptide macrocyclization. We have previously shown that PLH∗SpT (2a) (where H∗ indicates the presence of a -(CH2)8Ph group at the N(π) position and pT indicates phosphothreonine) is an extremely high affinity ligand of the polo-like kinase 1 (Plk1) polo-box domain (PBD). Herein we report that C-terminal macrocyclization of 2a employing N(π),N(τ)-bis-alkylated His residues as ring junctions can be achieved in a very direct fashion. The resulting macrocycles are highly potent in biochemical assays and maintain good target selectivity for the Plk1 PBD versus the PBDs of Plk2 and Plk3. Importantly, as exemplified by 5d, our current approach permits deletion of the N-terminal "Pro-Leu" motif to yield tripeptide ligands with decreased molecular weight, which retain high affinity and show improved target selectivity. These findings could fundamentally impact the future development of peptide macrocycles in general and Plk1 PBD-binding peptide mimetics in particular.

Proteome-wide analysis of phospho-regulated PDZ domain interactions

A key function of reversible protein phosphorylation is to regulate protein-protein interactions, many of which involve short linear motifs (3-12 amino acids). Motif-based interactions are difficult to capture because of their often low-to-moderate affinities. Here, we describe phosphomimetic proteomic peptide-phage display, a powerful method for simultaneously finding motif-based interaction and pinpointing phosphorylation switches. We computationally designed an oligonucleotide library encoding human C-terminal peptides containing known or predicted Ser/Thr phosphosites and phosphomimetic variants thereof. We incorporated these oligonucleotides into a phage library and screened the PDZ (PSD-95/Dlg/ZO-1) domains of Scribble and DLG1 for interactions potentially enabled or disabled by ligand phosphorylation. We identified known and novel binders and characterized selected interactions through microscale thermophoresis, isothermal titration calorimetry, and NMR We uncover site-specific phospho-regulation of PDZ domain interactions, provide a structural framework for how PDZ domains accomplish phosphopeptide binding, and discuss ligand phosphorylation as a switching mechanism of PDZ domain interactions. The approach is readily scalable and can be used to explore the potential phospho-regulation of motif-based interactions on a large scale.

Citalopram inhibits platelet function independently of SERT-mediated 5-HT transport

Citalopram prevents serotonin (5-HT) uptake into platelets by blocking the serotonin reuptake transporter (SERT). Although some clinical data suggest that selective serotonin reuptake inhibitors (SSRIs) may affect haemostasis and thrombosis, these poorly-characterised effects are not well understood mechanistically and useful in vitro data is limited. We sought to determine whether the inhibitory effects of citalopram on platelets are mediated via its pharmacological inhibition of 5-HT transport. We quantified the inhibitory potency of (RS)-, (R)- and (S)-citalopram on platelet function. If SERT blockade is the primary mechanism for citalopram-mediated platelet inhibition, these potencies should show quantitative congruence with inhibition of 5-HT uptake. Our data show that citalopram inhibits platelet aggregation, adhesion and thromboxane production with no difference in potency between (R)- and (S)-isomers. By contrast, citalopram had a eudysmic ratio of approximately 17 (S > R) for SERT blockade. Furthermore, nanomolar concentrations of citalopram inhibited 5-HT uptake into platelets but had no effect on other platelet functions, which were inhibited by micromolar concentrations. Our data indicate that citalopram-induced inhibition of platelets in vitro is not mediated by blockade of 5-HT transport. This raises a new question for future investigation: by what mechanism(s) does citalopram inhibit platelets?

The phosphatidylinositide 3-kinase (PI3K) signaling pathway is a determinant of zileuton response in adults with asthma

Variable responsiveness to zileuton, a leukotriene antagonist used to treat asthma, may be due in part to genetic variation. While individual SNPs were previously associated with zileuton-related lung function changes, specific quantitative trait loci (QTLs) and biological pathways that may contribute have not been identified. In this study, we investigated the hypothesis that genetic variation within biological pathways is associated with zileuton response. We performed an integrative QTL mapping and pathway enrichment study to investigate data from a GWAS of zileuton response, in addition to mRNA expression profiles and leukotriene production data from lymphoblastoid cell lines (LCLs) (derived from asthmatics) that were treated with zileuton or ethanol (control). We identified 1060 QTLs jointly associated with zileuton-related differential LTB₄ production in LCLs and lung function change in patients taking zileuton, of which eight QTLs were also significantly associated with persistent LTB₄ production in LCLs following zileuton treatment (i.e., ‘poor’ responders). Four nominally significant trans-eQTLs were predicted to regulate three candidate genes (SELL, MTF2, and GAL), the expression of which was significantly reduced in LCLs following zileuton treatment. Gene and pathway enrichment analyses of QTL associations identified multiple genes and pathways, predominantly related to phosphatidyl inositol signaling via PI3K. We validated the PI3K pathway activation status in a subset of LCLs demonstrating variable zileuton-related LTB₄ production, and show that in contrast to LCLs that responded to zileuton, the PI3K pathway was activated in poor responder LCLs. Collectively, these findings demonstrate a role for the PIK3 pathway and its targets as important determinants of differential responsiveness to zileuton.

Overexpression of transmembrane protein 168 in the mouse nucleus accumbens induces anxiety and sensorimotor gating deficit

Transmembrane protein 168 (TMEM168) comprises 697 amino acid residues, including some putative transmembrane domains. It is reported that TMEM168 controls methamphetamine (METH) dependence in the nucleus accumbens (NAc) of mice. Moreover, a strong link between METH dependence-induced adaptive changes in the brain and mood disorders has been evaluated. In the present study, we investigated the effects of accumbal TMEM168 in a battery of behavioral paradigms. The adeno-associated virus (AAV) Tmem168 vector was injected into the NAc of C57BL/6J mice (NAc-TMEM mice). Subsequently, the accumbal TMEM168 mRNA was increased approximately by seven-fold when compared with the NAc-Mock mice (controls). The NAc-TMEM mice reported no change in the locomotor activity, cognitive ability, social interaction, and depression-like behaviors; however, TMEM168 overexpression enhanced anxiety in the elevated-plus maze and light/dark box test. The increased anxiety was reversed by pretreatment with the antianxiety drug diazepam (0.3 mg/kg i.p.). Moreover, the NAc-TMEM mice exhibited decreased prepulse inhibition (PPI) in the startle response test, and the induced schizophrenia-like behavior was reversed by pretreatment with the antipsychotic drug risperidone (0.01 mg/kg i.p.). Furthermore, accumbal TMEM168 overexpression decreased the basal levels of extracellular GABA in the NAc and the high K+ (100 mM)-stimulated GABA elevation; however, the total contents of GABA in the NAc remained unaffected. These results suggest that the TMEM168-regulated GABAergic neuronal system in the NAc might become a novel target while studying the etiology of anxiety and sensorimotor gating deficits.

Extended Linkers Improve the Detection of Protein-protein Interactions (PPIs) by Dihydrofolate Reductase Protein-fragment Complementation Assay (DHFR PCA) in Living Cells

Understanding the function of cellular systems requires describing how proteins assemble with each other into transient and stable complexes and to determine their spatial relationships. Among the tools available to perform these analyses on a large scale is Protein-fragment Complementation Assay based on the dihydrofolate reductase (DHFR PCA). Here we test how longer linkers between the fusion proteins and the reporter fragments affect the performance of this assay. We investigate the architecture of the RNA polymerases, the proteasome and the conserved oligomeric Golgi (COG) complexes in living cells and performed large-scale screens with these extended linkers. We show that longer linkers significantly improve the detection of protein-protein interactions and allow to measure interactions further in space than the standard ones. We identify new interactions, for instance between the retromer complex and proteins related to autophagy and endocytosis. Longer linkers thus contribute an enhanced additional tool to the existing toolsets for the detection and measurements of protein-protein interactions and protein proximity in living cells.

Involvement of the accumbal osteopontin-interacting transmembrane protein 168 in methamphetamine-induced place preference and hyperlocomotion in mice

Chronic exposure to methamphetamine causes adaptive changes in brain, which underlie dependence symptoms. We have found that the transmembrane protein 168 (TMEM168) is overexpressed in the nucleus accumbens of mice upon repeated methamphetamine administration. Here, we firstly demonstrate the inhibitory effect of TMEM168 on methamphetamine-induced behavioral changes in mice, and attempt to elucidate the mechanism of this inhibition. We overexpressed TMEM168 in the nucleus accumbens of mice by using an adeno-associated virus vector (NAc-TMEM mice). Methamphetamine-induced hyperlocomotion and conditioned place preference were attenuated in NAc-TMEM mice. Additionally, methamphetamine-induced extracellular dopamine elevation was suppressed in the nucleus accumbens of NAc-TMEM mice. Next, we identified extracellular matrix protein osteopontin as an interacting partner of TMEM168, by conducting immunoprecipitation in cultured COS-7 cells. TMEM168 overexpression in COS-7 cells induced the enhancement of extracellular and intracellular osteopontin. Similarly, osteopontin enhancement was also observed in the nucleus accumbens of NAc-TMEM mice, in in vivo studies. Furthermore, the infusion of osteopontin proteins into the nucleus accumbens of mice was found to inhibit methamphetamine-induced hyperlocomotion and conditioned place preference. Our studies suggest that the TMEM168-regulated osteopontin system is a novel target pathway for the therapy of methamphetamine dependence, via regulating the dopaminergic function in the nucleus accumbens.

Protein complex analysis: From raw protein lists to protein interaction networks

The elucidation of molecular interaction networks is one of the pivotal challenges in the study of biology. Affinity purification-mass spectrometry and other co-complex methods have become widely employed experimental techniques to identify protein complexes. These techniques typically suffer from a high number of false negatives and false positive contaminants due to technical shortcomings and purification biases. To support a diverse range of experimental designs and approaches, a large number of computational methods have been proposed to filter, infer and validate protein interaction networks from experimental pull-down MS data. Nevertheless, this expansion of available methods complicates the selection of the most optimal ones to support systems biology-driven knowledge extraction. In this review, we give an overview of the most commonly used computational methods to process and interpret co-complex results, and we discuss the issues and unsolved problems that still exist within the field. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:600-614, 2017.

Studying protein-protein interactions: progress, pitfalls and solutions

Signalling proteins are intrinsic to all biological processes and interact with each other in tightly regulated and orchestrated signalling complexes and pathways. Characterization of protein binding can help to elucidate protein function within signalling pathways. This information is vital for researchers to gain a more comprehensive knowledge of cellular networks which can then be used to develop new therapeutic strategies for disease. However, studying protein-protein interactions (PPIs) can be challenging as the interactions can be extremely transient downstream of specific environmental cues. There are many powerful techniques currently available to identify and confirm PPIs. Choosing the most appropriate range of techniques merits serious consideration. The aim of this review is to provide a starting point for researchers embarking on a PPI study. We provide an overview and point of reference for some of the many methods available to identify interactions from in silico analysis and large scale screening tools through to the methods used to validate potential PPIs. We discuss the advantages and disadvantages of each method and we also provide a workflow chart to highlight the main experimental questions to consider when planning cell lysis to maximize experimental success.

Tspan2: a tetraspanin protein involved in oligodendrogenesis and cancer metastasis

Tetraspanin 2 (Tspan2) is one of the less well-characterised members of the tetraspanin superfamily, and its precise function in different human tissue types remains to be explored. Initial studies have highlighted its possible association in neuroinflammation and carcinogenesis. In the central nervous system, Tspan2 may contribute to the early stages of the oligodendrocyte differentiation into myelin-forming glia. Furthermore, in human lung cancer, Tspan2 could be involved in the progression of the tumour metastasis by modulating cancer cell motility and invasion functions. In this review, we discuss the available evidence for the potential role of Tspan2 and introduce possible strategies for disease targeting.

PTMOracle: A Cytoscape App for Covisualizing and Coanalyzing Post-Translational Modifications in Protein Interaction Networks

Post-translational modifications of proteins (PTMs) act as key regulators of protein activity and of protein-protein interactions (PPIs). To date, it has been difficult to comprehensively explore functional links between PTMs and PPIs. To address this, we developed PTMOracle, a Cytoscape app for coanalyzing PTMs within PPI networks. PTMOracle also allows extensive data to be integrated and coanalyzed with PPI networks, allowing the role of domains, motifs, and disordered regions to be considered. For proteins of interest, or a whole proteome, PTMOracle can generate network visualizations to reveal complex PTM-associated relationships. This is assisted by OraclePainter for coloring proteins by modifications, OracleTools for network analytics, and OracleResults for exploring tabulated findings. To illustrate the use of PTMOracle, we investigate PTM-associated relationships and their role in PPIs in four case studies. In the yeast interactome and its rich set of PTMs, we construct and explore histone-associated and domain-domain interaction networks and show how integrative approaches can predict kinases involved in phosphodegrons. In the human interactome, a phosphotyrosine-associated network is analyzed but highlights the sparse nature of human PPI networks and lack of PTM-associated data. PTMOracle is open source and available at the Cytoscape app store: http://apps.cytoscape.org/apps/ptmoracle .

Rewiring of the inferred protein interactome during blood development studied with the tool PPICompare

BACKGROUND

Differential analysis of cellular conditions is a key approach towards understanding the consequences and driving causes behind biological processes such as developmental transitions or diseases. The progress of whole-genome expression profiling enabled to conveniently capture the state of a cell's transcriptome and to detect the characteristic features that distinguish cells in specific conditions. In contrast, mapping the physical protein interactome for many samples is experimentally infeasible at the moment. For the understanding of the whole system, however, it is equally important how the interactions of proteins are rewired between cellular states. To overcome this deficiency, we recently showed how condition-specific protein interaction networks that even consider alternative splicing can be inferred from transcript expression data. Here, we present the differential network analysis tool PPICompare that was specifically designed for isoform-sensitive protein interaction networks.

RESULTS

Besides detecting significant rewiring events between the interactomes of grouped samples, PPICompare infers which alterations to the transcriptome caused each rewiring event and what is the minimal set of alterations necessary to explain all between-group changes. When applied to the development of blood cells, we verified that a reasonable amount of rewiring events were reported by the tool and found that differential gene expression was the major determinant of cellular adjustments to the interactome. Alternative splicing events were consistently necessary in each developmental step to explain all significant alterations and were especially important for rewiring in the context of transcriptional control.

CONCLUSIONS

Applying PPICompare enabled us to investigate the dynamics of the human protein interactome during developmental transitions. A platform-independent implementation of the tool PPICompare is available at https://sourceforge.net/projects/ppicompare/ .

Proteome-Scale Human Interactomics

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life.

Analyses of natural variation indicates that the absence of RPS4/RRS1 and amino acid change in RPS4 cause loss of their functions and resistance to pathogens

A pair of Arabidopsis thaliana resistance proteins, RPS4 and RRS1, recognizes the cognate Avr effector from the bacterial pathogens Pseudomonas syringae pv. tomato expressing avrRps4 (Pst-avrRps4), Ralstonia solanacearum, and the fungal pathogen Colletotrichum higginsianum and leads to defense signaling activation against the pathogens. In the present study, we analyzed 14 A. thaliana accessions for natural variation in Pst-avrRps4 and C. higginsianum susceptibility, and found new compatible and incompatible Arabidopsis-pathogen interactions. We first found that A. thaliana accession Cvi-0 is susceptible to Pst-avrRps4. Interestingly, the genome sequence assembly indicated that Cvi-0 lost both RPS4 and RRS1, but not RPS4B and RRS1B, compared to the reference genome sequence from A. thaliana accession Col-0. On the other hand, the natural variation analysis of RPS4 alleles from various Arabidopsis accessions revealed that one amino-acid change, Y950H, is responsible for the loss of resistance to Pst-avrRps4 and C. higginsianum in RLD-0. Our data indicate that the amino acid change, Y950H, in RPS4 resulted in the loss of both RPS4 and RRS1 functions and resistance to pathogens.

Bioinformatics Analysis of PTM-Modified Protein Interaction Networks and Complexes

Normal cellular functioning is maintained by macromolecular machines that control both core and specialized molecular tasks. These machines are in large part multi-subunit protein complexes that undergo regulation at multiple levels, from expression of requisite components to a vast array of post-translational modifications (PTMs). PTMs such as phosphorylation, ubiquitination, and acetylation currently number more than 200,000 in the human proteome and function within all molecular pathways. Here we provide a framework for systematically studying these PTMs in the context of global protein-protein interaction networks. This analytical framework allows insight into which functions specific PTMs tend to cluster in, and furthermore which complexes either single or multiple PTM signaling pathways converge on.

The Cohesive Metastasis Phenotype in Human Prostate Cancer

A critical barrier for the successful prevention and treatment of recurrent prostate cancer is detection and eradication of metastatic and therapy-resistant disease. Despite the fall in diagnoses and mortality, the reported incidence of metastatic disease has increased 72% since 2004. Prostate cancer arises in cohesive groups as intraepithelial neoplasia, migrates through muscle and leaves the gland via perineural invasion for hematogenous dissemination. Current technological advances have shown cohesive-clusters of tumor (also known as microemboli) within the circulation. Circulating tumor cell (CTC) profiles are indicative of disseminated prostate cancer, and disseminated tumor cells (DTC) are found in cohesive-clusters, a phenotypic characteristic of both radiation- and drug-resistant tumors. Recent reports in cell biology and informatics, coupled with mass spectrometry, indicate that the integrin adhesome network provides an explanation for the biophysical ability of cohesive-clusters of tumor cells to invade thorough muscle and nerve microenvironments while maintaining adhesion-dependent therapeutic resistance. Targeting cohesive-clusters takes advantage of the known ability of extracellular matrix (ECM) adhesion to promote tumor cell survival and represents an approach that has the potential to avoid the progression to drug- and radiotherapy-resistance. In the following review we will examine the evidence for development and dissemination of cohesive-clusters in metastatic prostate cancer.

Atlas of human diseases influenced by genetic variants with extreme allele frequency differences

Genetic variants with extreme allele frequency differences (EAFD) may underlie some human health disparities across populations. To identify EAFD loci, we systematically analyzed and characterized 81 million genomic variants from 2504 unrelated individuals of 26 world populations (phase III of the 1000 Genomes Project). Our analyses revealed a total of 434 genes, 15 pathways, and 18 diseases and traits influenced by EAFD variants from five continental populations. They included known EAFD genes, such as LCT (lactose tolerance), SLC24A5 (skin pigmentation), and EDAR (hair morphology). We found many novel EAFD genes, including TBC1D2B (autophagy mediator), TRIM40 (gastrointestinal inflammatory regulator), KRT71, KRT75, KRT83, and KRTAP10-1 (hair and epithelial keratin synthesis), PIK3R3 (insulin receptor interaction), DARS (neurological disorders), and NACA2 (skin inflammatory response). Our results also showed four complex diseases significantly associated with EAFD loci, including asthma (adjusted enrichment P = 4 × 10^-8), type I diabetes (P = 6 × 10^-9), alcohol consumption (P = 0.0002), and attention deficit/hyperactivity disorder (P = 0.003). This study provides a comprehensive atlas of genes, pathways, and human diseases significantly influenced by EAFD variants.

Analyzing and interpreting genome data at the network level with ConsensusPathDB

ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq. The tool reports interaction network modules, biochemical pathways and functional information that are significantly enriched by the user's input, applying computational methods for statistical over-representation, enrichment and graph analysis. The results of this protocol can be observed within a few minutes, even with genome-wide data. The resulting network associations can be used to interpret high-throughput data mechanistically, to characterize and prioritize biomarkers, to integrate different omics levels, to design follow-up functional assay experiments and to generate topology for kinetic models at different scales.

Systematic Protein-Protein Interaction Analysis Reveals Intersubcomplex Contacts in the Nuclear Pore Complex

The nuclear pore complex (NPC) enables transport across the nuclear envelope. It is one of the largest multiprotein assemblies in the cell, built from about 30 proteins called nucleoporins (Nups), organized into distinct subcomplexes. Structure determination of the NPC is a major research goal. The assembled ∼40-112 MDa NPC can be visualized by cryoelectron tomography (cryo-ET), while Nup subcomplexes are studied crystallographically. Docking the crystal structures into the cryo-ET maps is difficult because of limited resolution. Further, intersubcomplex contacts are not well characterized. Here, we systematically investigated direct interactions between Nups. In a comprehensive, structure-based, yeast two-hybrid interaction matrix screen, we mapped protein-protein interactions in yeast and human. Benchmarking against crystallographic and coaffinity purification data from the literature demonstrated the high coverage and accuracy of the data set. Novel intersubcomplex interactions were validated biophysically in microscale thermophoresis experiments and in intact cells through protein fragment complementation. These intersubcomplex interaction data provide direct experimental evidence toward possible structural arrangements of architectural elements within the assembled NPC, or they may point to assembly intermediates. Our data favors an assembly model in which major architectural elements of the NPC, notably the Y-complex, exist in different structural contexts within the scaffold.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics

High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.