Identifying novel protein interactions: Proteomic methods, optimisation approaches and data analysis pipelines

Temporal Protein Complex Identification Based on Dynamic Heterogeneous Protein Information Network Representation Learning

Protein complexes, as the fundamental units of cellular function and regulation, play a crucial role in understanding the normal physiological functions of cells. Existing methods for protein complex identification attempt to introduce other biological information on top of the protein-protein interaction (PPI) network to assist in evaluating the degree of association between proteins. However, these methods usually treat protein interaction networks as flat homogeneous static networks. They cannot distinguish the roles and importance of different types of biological information, nor can they reflect the dynamic changes of protein complexes. In recent years, heterogeneous network representation learning has achieved great success in processing complex heterogeneous information and mining deep semantics. We thus propose a temporal protein complex identification method based on Dynamic Heterogeneous Protein information network Representation Learning, DHPRL. DHPRL naturally integrates multiple types of heterogeneous biological information in the cellular temporal dimension. It simultaneously models the temporal dynamic properties of proteins and the heterogeneity of biological information to improve the understanding of protein interactions and the accuracy of complex prediction. Firstly, we construct Dynamic Heterogeneous Protein Information Network (DHPIN) by integrating temporal gene expression information and GO attribute information. Then we design a dual-view collaborative contrast mechanism. Specifically, proposing to learn protein representations from two views of DHPIN (1-hop relation view and meta-path view) to model the consistency and specificity between nearest-neighbour bio information and deeper biological semantics. The dynamic PPI network is thereafter re-weighted based on the learned protein representations. Finally, we perform protein identification on the re-weighted dynamic PPI network. Extensive experimental results demonstrate that DHPRL can effectively model complicated biological information and achieve state-of-the-art performance in most cases.

Proteomic applications in identifying protein-protein interactions

There are many things that can be used to characterize a protein. Size, isoelectric point, hydrophobicity, structure (primary to quaternary), and subcellular location are just a few parameters that are used. The most important feature of a protein, however, is its function. While there are many experiments that can indicate a protein's role, identifying the molecules it interacts with is probably the most definitive way of determining its function. Owing to technology limitations, protein interactions have historically been identified on a one molecule per experiment basis. The advent of high throughput multiplexed proteomic technologies in the 1990s, however, made identifying hundreds and thousands of proteins interactions within single experiments feasible. These proteomic technologies have dramatically increased the rate at which protein-protein interactions (PPIs) are discovered. While the improvement in mass spectrometry technology was an early driving force in the rapid pace of identifying PPIs, advances in sample preparation and chromatography have recently been propelling the field. In this chapter, we will discuss the importance of identifying PPIs and describe current state-of-the-art technologies that demonstrate what is currently possible in this important area of biological research.

Identification of Kv4.2 protein complex and modifications by tandem affinity purification-mass spectrometry in primary neurons

Proteins usually form complexes to fulfill variable physiological functions. In neurons, communication relies on synapses where receptors, channels, and anchoring proteins form complexes to precisely control signal transduction, synaptic integration, and action potential firing. Although there are many published protocols to isolate protein complexes in cell lines, isolation in neurons has not been well established. Here we introduce a method that combines lentiviral protein expression with tandem affinity purification followed by mass-spectrometry (TAP-MS) to identify protein complexes in neurons. This protocol can also be used to identify post-translational modifications (PTMs) of synaptic proteins. We used the A-type voltage-gated K⁺ channel subunit Kv4.2 as the target protein. Kv4.2 is highly expressed in the hippocampus where it contributes to learning and memory through its regulation of neuronal excitability and synaptic plasticity. We tagged Kv4.2 with the calmodulin-binding-peptide (CBP) and streptavidin-binding-peptide (SBP) at its C-terminus and expressed it in neurons via lentivirus. Kv4.2 was purified by two-step TAP and samples were analyzed by MS. MS identified two prominently known Kv4.2 interacting proteins [dipeptidyl peptidase like (DPPs) and Kv channel-interacting proteins (KChIPs)] in addition to novel synaptic proteins including glutamate receptors, a calcium channel, and anchoring proteins. Co-immunoprecipitation and colocalization experiments validated the association of Kv4.2 with glutamate receptors. In addition to protein complex identification, we used TAP-MS to identify Kv4.2 phosphorylation sites. Several known and unknown phosphorylation sites were identified. These findings provide a novel path to identify protein-protein interactions and PTMs in neurons and shed light on mechanisms of neuronal signaling potentially involved in the pathology of neurological diseases.

Advances and Trends in Omics Technology Development

The human history has witnessed the rapid development of technologies such as high-throughput sequencing and mass spectrometry that led to the concept of “omics” and methodological advancement in systematically interrogating a cellular system. Yet, the ever-growing types of molecules and regulatory mechanisms being discovered have been persistently transforming our understandings on the cellular machinery. This renders cell omics seemingly, like the universe, expand with no limit and our goal toward the complete harness of the cellular system merely impossible. Therefore, it is imperative to review what has been done and is being done to predict what can be done toward the translation of omics information to disease control with minimal cell perturbation. With a focus on the “four big omics,” i.e., genomics, transcriptomics, proteomics, metabolomics, we delineate hierarchies of these omics together with their epiomics and interactomics, and review technologies developed for interrogation. We predict, among others, redoxomics as an emerging omics layer that views cell decision toward the physiological or pathological state as a fine-tuned redox balance.

GPCRs Are Optimal Regulators of Complex Biological Systems and Orchestrate the Interface between Health and Disease

GPCRs arguably represent the most effective current therapeutic targets for a plethora of diseases. GPCRs also possess a pivotal role in the regulation of the physiological balance between healthy and pathological conditions; thus, their importance in systems biology cannot be underestimated. The molecular diversity of GPCR signaling systems is likely to be closely associated with disease-associated changes in organismal tissue complexity and compartmentalization, thus enabling a nuanced GPCR-based capacity to interdict multiple disease pathomechanisms at a systemic level. GPCRs have been long considered as controllers of communication between tissues and cells. This communication involves the ligand-mediated control of cell surface receptors that then direct their stimuli to impact cell physiology. Given the tremendous success of GPCRs as therapeutic targets, considerable focus has been placed on the ability of these therapeutics to modulate diseases by acting at cell surface receptors. In the past decade, however, attention has focused upon how stable multiprotein GPCR superstructures, termed receptorsomes, both at the cell surface membrane and in the intracellular domain dictate and condition long-term GPCR activities associated with the regulation of protein expression patterns, cellular stress responses and DNA integrity management. The ability of these receptorsomes (often in the absence of typical cell surface ligands) to control complex cellular activities implicates them as key controllers of the functional balance between health and disease. A greater understanding of this function of GPCRs is likely to significantly augment our ability to further employ these proteins in a multitude of diseases.

Protein-DNA/RNA Interactions: An Overview of Investigation Methods in the -Omics Era

The fields of application of functional proteomics are not limited to the study of protein–protein interactions; they also extend to those involving protein complexes that bind DNA or RNA. These interactions affect fundamental processes such as replication, transcription, and repair in the case of DNA, as well as transport, translation, splicing, and silencing in the case of RNA. Analytical or preparative experimental approaches, both in vivo and in vitro, have been developed to isolate and identify DNA/RNA binding proteins by exploiting the advantage of the affinity shown by these proteins toward a specific oligonucleotide sequence. The present review proposes an overview of the approaches most commonly employed in proteomics applications for the identification of nucleic acid-binding proteins, such as affinity purification (AP) protocols, EMSA, chromatin purification methods, and CRISPR-based chromatin affinity purification, which are generally associated with mass spectrometry methodologies for the unbiased protein identification.

Poly(styrene-co-maleic acid)-mediated isolation of supramolecular membrane protein complexes from plant thylakoids

Derivatives of poly(styrene-co-maleic acid) (pSMA), have recently emerged as effective reagents for extracting membrane protein complexes from biological membranes. Despite recent progress in using SMAs to study artificial and bacterial membranes, very few reports have addressed their use in studying the highly abundant and well characterized thylakoid membranes. Recently, we tested the ability of twelve commercially available SMA copolymers with different physicochemical properties to extract membrane protein complexes (MPCs) from spinach thylakoid membrane. Based on the efficacy of both protein and chlorophyll extraction, we have found five highly efficient SMA copolymers: SMA® 1440, XIRAN® 25010, XIRAN® 30010, SMA® 17352, and SMA® PRO 10235, that show promise in extracting MPCs from chloroplast thylakoids. To further advance the application of these polymers for studying biomembrane organization, we have examined the composition of thylakoid supramolecular protein complexes extracted by the five SMA polymers mentioned above. Two commonly studied plants, spinach (Spinacia oleracea) and pea (Pisum sativum), were used for extraction as model biomembranes. We found that the pSMAs differentially extract protein complexes from spinach and pea thylakoids. Based on their differential activity, which correlates with the polymer chemical structure, pSMAs can be divided into two groups: unfunctionalized polymers and ester derivatives.

Identification of Protein Complexes by Using a Spatial and Temporal Active Protein Interaction Network

The rapid development of proteomics and high-throughput technologies has produced a large amount of Protein-Protein Interaction (PPI) data, which makes it possible for considering dynamic properties of protein interaction networks (PINs) instead of static properties. Identification of protein complexes from dynamic PINs becomes a vital scientific problem for understanding cellular life in the post genome era. Up to now, plenty of models or methods have been proposed for the construction of dynamic PINs to identify protein complexes. However, most of the constructed dynamic PINs just focus on the temporal dynamic information and thus overlook the spatial dynamic information of the complex biological systems. To address the limitation of the existing dynamic PIN analysis approaches, in this paper, we propose a new model-based scheme for the construction of the Spatial and Temporal Active Protein Interaction Network (ST-APIN) by integrating time-course gene expression data and subcellular location information. To evaluate the efficiency of ST-APIN, the commonly used classical clustering algorithm MCL is adopted to identify protein complexes from ST-APIN and the other three dynamic PINs, NF-APIN, DPIN, and TC-PIN. The experimental results show that, the performance of MCL on ST-APIN outperforms those on the other three dynamic PINs in terms of matching with known complexes, sensitivity, specificity, and f-measure. Furthermore, we evaluate the identified protein complexes by Gene Ontology (GO) function enrichment analysis. The validation shows that the identified protein complexes from ST-APIN are more biologically significant. This study provides a general paradigm for constructing the ST-APINs, which is essential for further understanding of molecular systems and the biomedical mechanism of complex diseases.

A yeast display immunoprecipitation screen for targeted discovery of antibodies against membrane protein complexes

Yeast display immunoprecipitation is a combinatorial library screening platform for the discovery and engineering of antibodies against membrane proteins using detergent-solubilized membrane fractions or cell lysates as antigen sources. Here, we present the extension of this method for the screening of antibodies that bind to membrane protein complexes, enabling discovery of antibodies that target antigens involved in a functional protein-protein interaction of interest. For this proof-of-concept study, we focused on the receptor-mediated endocytosis machinery at the blood-brain barrier, and adaptin 2 (AP-2) was chosen as the functional interaction hub. The goal of this study was to identify antibodies that bound to blood-brain barrier (BBB) membrane protein complexes containing AP-2. Screening of a nonimmune yeast display antibody library was carried out using detergent-solubilized BBB plasma membranes as an antigen pool, and antibodies that could interact with protein complexes containing AP-2 were identified. Downstream characterization of isolated antibodies confirmed targeting of proteins known to play important roles in membrane trafficking. This functional yeast display immunoprecipitation screen may be applied to other systems where antibodies against other functional classes of protein complexes are sought.

Evidence of association of the DISC1 interactome gene set with schizophrenia from GWAS

DISC1 was discovered as a gene disrupted by a balanced translocation in a large pedigree that segregated with major mental disorders, including schizophrenia. Further attempts to find genetic association with schizophrenia were inconclusive. Most of the biology of DISC1 was inferred from the functionality of its protein partners. Recently, a gene set constituted by DISC1 and several of its partners has been associated with cognitive performance during development, a well-known schizophrenia endophenotype, by means of burden test of rare disruptive variants. Here, we performed a gene set analysis using common variants from the largest schizophrenia genome-wide association study of the Psychiatric Genomics Consortium to test if this gene set is associated with schizophrenia. The main test was based on the MAGMA software. Several additional tests were performed to analyze the robustness of the main findings. The DISC1 interactome gene set was associated with schizophrenia (P = .0056), confirmed by an additional method (INRICH). This association was robust to removal of the major histocompatibility complex region, different definitions of gene boundaries, or different statistical gene models. Conditional analysis revealed that the association was not solely explained by higher expression in brain. Three genes from the gene set, CLIC1, DST, and PDE4B, were associated with schizophrenia at the gene level. Consideration of other DISC1 interactome gene sets revealed the importance of gene set definition. Therefore, we present the first evidence from genome-wide association studies of the role of DISC1 and interacting partners in schizophrenia susceptibility, reconciling genetic and molecular biology data.

BRCA1-No Matter How You Splice It

BRCA1 (breast cancer 1, early onset), a well-known breast cancer susceptibility gene, is a highly alternatively spliced gene. BRCA1 alternative splicing may serve as an alternative regulatory mechanism for the inactivation of the BRCA1 gene in both hereditary and sporadic breast cancers, and other BRCA1-associated cancers. The alternative transcripts of BRCA1 can mimic known functions, possess unique functions compared with the full-length BRCA1 transcript, and in some cases, appear to function in opposition to full-length BRCA1 In this review, we will summarize the functional "naturally occurring" alternative splicing transcripts of BRCA1 and then discuss the latest next-generation sequencing-based detection methods and techniques to detect alternative BRCA1 splicing patterns and their potential use in cancer diagnosis, prognosis, and therapy.

Antibiotic Discovery: Where Have We Come from, Where Do We Go?

Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.

Chromatographic separation strategies for precision mass spectrometry to study protein-protein interactions and protein phosphorylation

Investigating protein-protein interactions and protein phosphorylation can be of great significance when studying biological processes and human diseases at the molecular level. However, sample complexity, presence of low abundance proteins, and dynamic nature of the proteins often impede in achieving sufficient analytical depth in proteomics research. In this regard, chromatographic separation methodologies have played a vital role in the identification and quantification of proteins in complex sample mixtures. The combination of peptide and protein fractionation techniques with advanced high-performance mass spectrometry has allowed the researchers to successfully study the protein-protein interactions and protein phosphorylation. Several new fractionation strategies for large scale analysis of proteins and peptides have been developed to study protein-protein interactions and protein phosphorylation. These emerging chromatography methodologies have enabled the identification of several hundred protein complexes and even thousands of phosphorylation sites in a single study. In this review, we focus on current workflow strategies and chromatographic tools, highlighting their advantages and disadvantages, and examining their associated challenges and future potential.

Two-Step Coimmunoprecipitation (TIP) Enables Efficient and Highly Selective Isolation of Native Protein Complexes

Coimmunoprecipitation (co-IP) is one of the most frequently used techniques to study protein-protein (PPIs) or protein-nucleic acid interactions (PNIs). However, the presence of coprecipitated contaminants is a well-recognized issue associated with single-step co-IPs. To overcome this limitation, we developed the two-step co-IP (TIP) strategy that enables sequential coimmunoprecipitations of endogenous protein complexes. TIP can be performed with a broad range of mono- and polyclonal antibodies targeting a single protein or different components of a given complex. TIP results in a highly selective enrichment of protein complexes and thus outperforms single-step co-IPs for downstream applications such as mass spectrometry for the identification of PPIs and quantitative PCR for the analysis of PNIs. We benchmarked TIP for the identification of CD95/FAS-interacting proteins in primary human CD4⁺ T cells, which recapitulated all major known interactors, but also enabled the proteomics discovery of PPM1G and IPO7 as new interaction partners. For its feasibility and high performance, we propose TIP as an advanced tool for the isolation of highly purified protein-protein and protein-nucleic acid complexes under native expression conditions.

Supramolecular organization of NMDA receptors and the postsynaptic density

The postsynaptic density (PSD) of all vertebrate species share a highly complex proteome with ∼1000 conserved proteins that function as sophisticated molecular computational devices. Here, we review recent studies showing that this complexity can be understood in terms of the supramolecular organization of proteins, which self-assemble within a hierarchy of different length scales, including complexes, supercomplexes and nanodomains. We highlight how genetic and biochemical approaches in mice are being used to uncover the native molecular architecture of the synapse, revealing hitherto unknown molecular structures, including highly selective mechanisms for specifying the assembly of NMDAR-MAGUK supercomplexes. We propose there exists a logical framework that precisely dictates the subunit composition of synaptic complexes, supercomplexes, and nanodomains in vivo.