Combined proximity labeling and affinity purification-mass spectrometry workflow for mapping and visualizing protein interaction networks

Central role of SUMOylation in the regulation of chromatin interactions and transcriptional outputs of the androgen receptor in prostate cancer cells

The androgen receptor (AR) is pivotal in prostate cancer (PCa) progression and represents a critical therapeutic target. AR-mediated gene regulation involves intricate interactions with nuclear proteins, with many mediating and undergoing post-translational modifications that present alternative therapeutic avenues. Through chromatin proteomics in PCa cells, we identified SUMO ligases together with nuclear receptor coregulators and pioneer transcription factors within the AR's protein network. Intriguingly, this network displayed a significant association with SUMO2/3. To elucidate the influence of SUMOylation on AR chromatin interactions and subsequent gene regulation, we inhibited SUMOylation using ML-792 (SUMOi). While androgens generally facilitated the co-occupancy of SUMO2/3 and AR on chromatin, SUMOi induced divergent effects dependent on the type of AR-binding site (ARB). SUMOi augmented AR's pioneer-like binding on inaccessible chromatin regions abundant in androgen response elements (AREs) and diminished its interaction with accessible chromatin regions sparse in AREs yet rich in pioneer transcription factor motifs. The SUMOi-impacted ARBs divergently influenced AR-regulated genes; those associated with AR-mediated activation played roles in negative regulation of cell proliferation, while those with AR-mediated repression were involved in pattern formation. In conclusion, our findings underscore the pervasive influence of SUMOylation in shaping AR's role in PCa cells, potentially unveiling new therapeutic strategies.

DSBSO-Based XL-MS Analysis of Breast Cancer PDX Tissues to Delineate Protein Interaction Network in Clinical Samples

Protein-protein interactions (PPIs) are fundamental to understanding biological systems as protein complexes are the active molecular modules critical for carrying out cellular functions. Dysfunctional PPIs have been associated with various diseases including cancer. Systems-wide PPI analysis not only sheds light on pathological mechanisms, but also represents a paradigm in identifying potential therapeutic targets. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for defining endogenous PPIs of cellular networks. While proteome-wide studies have been performed in cell lysates, intact cells and tissues, applications of XL-MS in clinical samples have not been reported. In this study, we adopted a DSBSO-based in vivo XL-MS platform to map interaction landscapes from two breast cancer patient-derived xenograft (PDX) models. As a result, we have generated a PDX interaction network comprising 2,557 human proteins and identified interactions unique to breast cancer subtypes. Interestingly, most of the observed differences in PPIs correlated well with protein abundance changes determined by TMT-based proteome quantitation. Collectively, this work has demonstrated the feasibility of XL-MS analysis in clinical samples, and established an analytical workflow for tissue cross-linking that can be generalized for mapping PPIs from patient samples in the future to dissect disease-relevant cellular networks.

Integrin signalling in joint development, homeostasis and osteoarthritis

Integrins are key regulators of cell-matrix interactions during joint development and joint tissue homeostasis, as well as in the development of osteoarthritis (OA). The signalling cascades initiated by the interactions of integrins with a complex network of extracellular matrix (ECM) components and intracellular adaptor proteins orchestrate cellular responses necessary for maintaining joint tissue integrity. Dysregulated integrin signalling, triggered by matrix degradation products such as matrikines, disrupts this delicate balance, tipping the scales towards an environment conducive to OA pathogenesis. The interplay between integrin signalling and growth factor pathways further underscores the multifaceted nature of OA. Moreover, emerging insights into the role of endocytic trafficking in regulating integrin signalling add a new layer of complexity to the understanding of OA development. To harness the therapeutic potential of targeting integrins for mitigation of OA, comprehensive understanding of their molecular mechanisms across joint tissues is imperative. Ultimately, deciphering the complexities of integrin signalling will advance the ability to treat OA and alleviate its global burden.

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Structure and interactions of the endogenous human Commander complex

The Commander complex, a 16-protein assembly, plays multiple roles in cell homeostasis, cell cycle and immune response. It consists of copper-metabolism Murr1 domain proteins (COMMD1-10), coiled-coil domain-containing proteins (CCDC22 and CCDC93), DENND10 and the Retriever subcomplex (VPS26C, VPS29 and VPS35L), all expressed ubiquitously in the body and linked to various diseases. Here, we report the structure and key interactions of the endogenous human Commander complex by cryogenic-electron microscopy and mass spectrometry-based proteomics. The complex consists of a stable core of COMMD1-10 and an effector containing DENND10 and Retriever, scaffolded together by CCDC22 and CCDC93. We establish the composition of Commander and reveal major interaction interfaces. These findings clarify its roles in intracellular transport, and uncover a strong association with cilium assembly, and centrosome and centriole functions.

A splice site variant in MADD affects hormone expression in pancreatic β cells and pituitary gonadotropes

MAPK activating death domain (MADD) is a multifunctional protein regulating small GTPases RAB3 and RAB27, MAPK signaling, and cell survival. Polymorphisms in the MADD locus are associated with glycemic traits, but patients with biallelic variants in MADD manifest a complex syndrome affecting nervous, endocrine, exocrine, and hematological systems. We identified a homozygous splice site variant in MADD in 2 siblings with developmental delay, diabetes, congenital hypogonadotropic hypogonadism, and growth hormone deficiency. This variant led to skipping of exon 30 and in-frame deletion of 36 amino acids. To elucidate how this mutation causes pleiotropic endocrine phenotypes, we generated relevant cellular models with deletion of MADD exon 30 (dex30). We observed reduced numbers of β cells, decreased insulin content, and increased proinsulin-to-insulin ratio in dex30 human embryonic stem cell-derived pancreatic islets. Concordantly, dex30 led to decreased insulin expression in human β cell line EndoC-βH1. Furthermore, dex30 resulted in decreased luteinizing hormone expression in mouse pituitary gonadotrope cell line LβT2 but did not affect ontogeny of stem cell-derived GnRH neurons. Protein-protein interactions of wild-type and dex30 MADD revealed changes affecting multiple signaling pathways, while the GDP/GTP exchange activity of dex30 MADD remained intact. Our results suggest MADD-specific processes regulate hormone expression in pancreatic β cells and pituitary gonadotropes.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Distinct functions for the paralogous RBM41 and U11/U12-65K proteins in the minor spliceosome

Here, we identify RBM41 as a novel unique protein component of the minor spliceosome. RBM41 has no previously recognized cellular function but has been identified as a paralog of U11/U12-65K, a known unique component of the U11/U12 di-snRNP. Both proteins use their highly similar C-terminal RRMs to bind to 3'-terminal stem-loops in U12 and U6atac snRNAs with comparable affinity. Our BioID data indicate that the unique N-terminal domain of RBM41 is necessary for its association with complexes containing DHX8, an RNA helicase, which in the major spliceosome drives the release of mature mRNA from the spliceosome. Consistently, we show that RBM41 associates with excised U12-type intron lariats, is present in the U12 mono-snRNP, and is enriched in Cajal bodies, together suggesting that RBM41 functions in the post-splicing steps of the minor spliceosome assembly/disassembly cycle. This contrasts with U11/U12-65K, which uses its N-terminal region to interact with U11 snRNP during intron recognition. Finally, while RBM41 knockout cells are viable, they show alterations in U12-type 3' splice site usage. Together, our results highlight the role of the 3'-terminal stem-loop of U12 snRNA as a dynamic binding platform for the U11/U12-65K and RBM41 proteins, which function at distinct stages of the assembly/disassembly cycle.

Systematic profiling of ale yeast protein dynamics across fermentation and repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is among the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout 2 fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.

Uncovering the proximal proteome of CTR1 through TurboID-mediated proximity labeling

Protein-protein interactions play a crucial role in driving cellular processes and enabling appropriate physiological responses in organisms. The plant hormone ethylene signaling pathway is complex and regulated by the spatiotemporal regulation of its signaling molecules. Constitutive Triple Response 1 (CTR1), a key negative regulator of the pathway, regulates the function of Ethylene-Insensitive 2 (EIN2), a positive regulator of ethylene signaling, at the endoplasmic reticulum (ER) through phosphorylation. Our recent study revealed that CTR1 can also translocate from the ER to the nucleus in response to ethylene and positively regulate ethylene responses by stabilizing EIN3. To gain further insights into the role of CTR1 in plants, we used TurboID-based proximity labeling and mass spectrometry to identify the proximal proteomes of CTR1 in Nicotiana benthamiana. The identified proximal proteins include known ethylene signaling components, as well as proteins involved in diverse cellular processes such as mitochondrial respiration, mRNA metabolism, and organelle biogenesis. Our study demonstrates the feasibility of proximity labeling using the N. benthamiana transient expression system and identifies the potential interactors of CTR1 in vivo, uncovering the potential roles of CTR1 in a wide range of cellular processes.

Interaction network of human early embryonic transcription factors

Embryonic genome activation (EGA) occurs during preimplantation development and is characterized by the initiation of de novo transcription from the embryonic genome. Despite its importance, the regulation of EGA and the transcription factors involved in this process are poorly understood. Paired-like homeobox (PRDL) family proteins are implicated as potential transcriptional regulators of EGA, yet the PRDL-mediated gene regulatory networks remain uncharacterized. To investigate the function of PRDL proteins, we are identifying the molecular interactions and the functions of a subset family of the Eutherian Totipotent Cell Homeobox (ETCHbox) proteins, seven PRDL family proteins and six other transcription factors (TFs), all suggested to participate in transcriptional regulation during preimplantation. Using mass spectrometry-based interactomics methods, AP-MS and proximity-dependent biotin labeling, and chromatin immunoprecipitation sequencing we derive the comprehensive regulatory networks of these preimplantation TFs. By these interactomics tools we identify more than a thousand high-confidence interactions for the 21 studied bait proteins with more than 300 interacting proteins. We also establish that TPRX2, currently assigned as pseudogene, is a transcriptional activator.

Oncogenic KEAP1 mutations activate TRAF2-NFκB signaling to prevent apoptosis in lung cancer cells

The Kelch-like ECH-associated protein 1 (KEAP1) - Nuclear factor erythroid 2 -related factor 2 (NRF2) pathway is the major transcriptional stress response system in cells against oxidative and electrophilic stress. NRF2 is frequently constitutively active in many cancers, rendering the cells resistant to chemo- and radiotherapy. Loss-of-function (LOF) mutations in the repressor protein KEAP1 are common in non-small cell lung cancer, particularly adenocarcinoma. While the mutations can occur throughout the gene, they are enriched in certain areas, indicating that these may have unique functional importance. In this study, we show that in the GSEA analysis of TCGA lung adenocarcinoma RNA-seq data, the KEAP1 mutations in R320 and R470 were associated with enhanced Tumor Necrosis Factor alpha (TNFα) - Nuclear Factor kappa subunit B (NFκB) signaling as well as MYC and MTORC1 pathways. To address the functional role of these hotspot mutations, affinity purification and mass spectrometry (AP-MS) analysis of wild type (wt) KEAP1 and its mutation forms, R320Q and R470C were employed to interrogate differences in the protein interactome. We identified TNF receptor associated factor 2 (TRAF2) as a putative protein interaction partner. Both mutant KEAP1 forms showed increased interaction with TRAF2 and other anti-apoptotic proteins, suggesting that apoptosis signalling could be affected by the protein interactions. A549 lung adenocarcinoma cells overexpressing mutant KEAP1 showed high TRAF2-mediated NFκB activity and increased protection against apoptosis, XIAP being one of the key proteins involved in anti-apoptotic signalling. To conclude, KEAP1 R320Q and R470C and its interaction with TRAF2 leads to activation of NFκB pathway, thereby protecting against apoptosis.

Mitochondrial proteome research: the road ahead

Mitochondria are multifaceted organelles with key roles in anabolic and catabolic metabolism, bioenergetics, cellular signalling and nutrient sensing, and programmed cell death processes. Their diverse functions are enabled by a sophisticated set of protein components encoded by the nuclear and mitochondrial genomes. The extent and complexity of the mitochondrial proteome remained unclear for decades. This began to change 20 years ago when, driven by the emergence of mass spectrometry-based proteomics, the first draft mitochondrial proteomes were established. In the ensuing decades, further technological and computational advances helped to refine these 'maps', with current estimates of the core mammalian mitochondrial proteome ranging from 1,000 to 1,500 proteins. The creation of these compendia provided a systemic view of an organelle previously studied primarily in a reductionist fashion and has accelerated both basic scientific discovery and the diagnosis and treatment of human disease. Yet numerous challenges remain in understanding mitochondrial biology and translating this knowledge into the medical context. In this Roadmap, we propose a path forward for refining the mitochondrial protein map to enhance its discovery and therapeutic potential. We discuss how emerging technologies can assist the detection of new mitochondrial proteins, reveal their patterns of expression across diverse tissues and cell types, and provide key information on proteoforms. We highlight the power of an enhanced map for systematically defining the functions of its members. Finally, we examine the utility of an expanded, functionally annotated mitochondrial proteome in a translational setting for aiding both diagnosis of mitochondrial disease and targeting of mitochondria for treatment.

Exploring the Spatial Landscape of the Estrogen Receptor Proximal Proteome With Antibody-Based Proximity Labeling

Estrogen receptor α (ERα) drives the transcription of genes involved in breast cancer (BC) progression, relying on coregulatory protein recruitment for its transcriptional and biological activities. Mutation of ERα as well as aberrant recruitment of its regulatory proteins contribute to tumor adaptation and drug resistance. Therefore, understanding the dynamic changes in ERα protein interaction networks is crucial for elucidating drug resistance mechanisms in BC. Despite progress in studying ERα-associated proteins, capturing subcellular transient interactions remains challenging and, as a result, significant number of important interactions remain undiscovered. In this study, we employed biotinylation by antibody recognition (BAR), an innovative antibody-based proximity labeling (PL) approach, coupled with mass spectrometry to investigate the ERα proximal proteome and its changes associated with resistance to aromatase inhibition, a key therapy used in the treatment of ERα-positive BC. We show that BAR successfully detected most of the known ERα interactors and mainly identified nuclear proteins, using either an epitope tag or endogenous antibody to target ERα. We further describe the ERα proximal proteome rewiring associated with resistance applying BAR to a panel of isogenic cell lines modeling tumor adaptation in the clinic. Interestingly, we find that ERα associates with some of the canonical cofactors in resistant cells and several proximal proteome changes are due to increased expression of ERα. Resistant models also show decreased levels of estrogen-regulated genes. Sensitive and resistant cells harboring a mutation in the ERα (Y537C) revealed a similar proximal proteome. We provide an ERα proximal protein network covering several novel ERα-proximal partners. These include proteins involved in highly dynamic processes such as sumoylation and ubiquitination difficult to detect with traditional protein interaction approaches. Overall, we present BAR as an effective approach to investigate the ERα proximal proteome in a spatial context and demonstrate its application in different experimental conditions.

GTPBP8 is required for mitoribosomal biogenesis and mitochondrial translation

Mitochondrial translation occurs on the mitochondrial ribosome, also known as the mitoribosome. The assembly of mitoribosomes is a highly coordinated process. During mitoribosome biogenesis, various assembly factors transiently associate with the nascent ribosome, facilitating the accurate and efficient construction of the mitoribosome. However, the specific factors involved in the assembly process, the precise mechanisms, and the cellular compartments involved in this vital process are not yet fully understood. In this study, we discovered a crucial role for GTP-binding protein 8 (GTPBP8) in the assembly of the mitoribosomal large subunit (mt-LSU) and mitochondrial translation. GTPBP8 is identified as a novel GTPase located in the matrix and peripherally bound to the inner mitochondrial membrane. Importantly, GTPBP8 is specifically associated with the mt-LSU during its assembly. Depletion of GTPBP8 leads to an abnormal accumulation of mt-LSU, indicating that GTPBP8 is critical for proper mt-LSU assembly. Furthermore, the absence of GTPBP8 results in reduced levels of fully assembled 55S monosomes. This impaired assembly leads to compromised mitochondrial translation and, consequently, impaired mitochondrial function. The identification of GTPBP8 as an important player in these processes provides new insights into the molecular mechanisms underlying mitochondrial protein synthesis and its regulation.

Higher-Order Structural Organization of the Mitochondrial Proteome Charted by In Situ Cross-Linking Mass Spectrometry

Mitochondria are densely packed with proteins, of which most are involved physically or more transiently in protein-protein interactions (PPIs). Mitochondria host among others all enzymes of the Krebs cycle and the oxidative phosphorylation pathway and are foremost associated with cellular bioenergetics. However, mitochondria are also important contributors to apoptotic cell death and contain their own genome indicating that they play additionally an eminent role in processes beyond bioenergetics. Despite intense efforts in identifying and characterizing mitochondrial protein complexes by structural biology and proteomics techniques, many PPIs have remained elusive. Several of these (membrane embedded) PPIs are less stable in vitro hampering their characterization by most contemporary methods in structural biology. Particularly in these cases, cross-linking mass spectrometry (XL-MS) has proven valuable for the in-depth characterization of mitochondrial protein complexes in situ. Here, we highlight experimental strategies for the analysis of proteome-wide PPIs in mitochondria using XL-MS. We showcase the ability of in situ XL-MS as a tool to map suborganelle interactions and topologies and aid in refining structural models of protein complexes. We describe some of the most recent technological advances in XL-MS that may benefit the in situ characterization of PPIs even further, especially when combined with electron microscopy and structural modeling.

Exposing the small protein load of bacterial life

The ever-growing repertoire of genomic techniques continues to expand our understanding of the true diversity and richness of prokaryotic genomes. Riboproteogenomics laid the foundation for dynamic studies of previously overlooked genomic elements. Most strikingly, bacterial genomes were revealed to harbor robust repertoires of small open reading frames (sORFs) encoding a diverse and broadly expressed range of small proteins, or sORF-encoded polypeptides (SEPs). In recent years, continuous efforts led to great improvements in the annotation and characterization of such proteins, yet many challenges remain to fully comprehend the pervasive nature of small proteins and their impact on bacterial biology. In this work, we review the recent developments in the dynamic field of bacterial genome reannotation, catalog the important biological roles carried out by small proteins and identify challenges obstructing the way to full understanding of these elusive proteins.

High-Efficiency Enrichment by Saturating Nanoliters of Protein Affinity Media

Affinity-purification mass spectrometry (AP-MS) is an established technique for identifying protein-protein interactions (PPIs). The basic technology involves immobilizing a high-specificity ligand to a solid-phase support (e.g., an agarose or magnetic bead) to pull down protein(s) of interest from cell lysates. Although these supports are engineered to minimize interactions with background protein, the conventional method recovers mostly nonspecific binders. The law of mass action for dilute solutions has taught us to use an excess of beads to capture all target proteins, especially weakly interacting ones. However, modern microbead technology presents a binding environment that is much different from a dilute solution. We describe a fluidic platform that captures and processes ultralow nanoliter quantities of magnetic particles, simultaneously increasing the efficiency of PPI detection and strongly suppressing nonspecific binding. We demonstrate the concept with synthetic mixtures of tagged protein and illustrate performance with a variety of AP-MS experiment types. These include a BioID experiment targeting lamin-A interactors from HeLa cells and pulldowns using GFP-tagged proteins associated with a double-strand DNA repair mechanism. We show that efficient extraction requires saturation of the solid-phase support and that <10 nL of beads is sufficient to generate comprehensive protein interaction maps.

Systematic Profiling of Ale Yeast Protein Dynamics across Fermentation and Repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is amongst the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout two fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.

A Transformer-Based Ensemble Framework for the Prediction of Protein-Protein Interaction Sites

The identification of protein-protein interaction (PPI) sites is essential in the research of protein function and the discovery of new drugs. So far, a variety of computational tools based on machine learning have been developed to accelerate the identification of PPI sites. However, existing methods suffer from the low predictive accuracy or the limited scope of application. Specifically, some methods learned only global or local sequential features, leading to low predictive accuracy, while others achieved improved performance by extracting residue interactions from structures but were limited in their application scope for the serious dependence on precise structure information. There is an urgent need to develop a method that integrates comprehensive information to realize proteome-wide accurate profiling of PPI sites. Herein, a novel ensemble framework for PPI sites prediction, EnsemPPIS, was therefore proposed based on transformer and gated convolutional networks. EnsemPPIS can effectively capture not only global and local patterns but also residue interactions. Specifically, EnsemPPIS was unique in (a) extracting residue interactions from protein sequences with transformer and (b) further integrating global and local sequential features with the ensemble learning strategy. Compared with various existing methods, EnsemPPIS exhibited either superior performance or broader applicability on multiple PPI sites prediction tasks. Moreover, pattern analysis based on the interpretability of EnsemPPIS demonstrated that EnsemPPIS was fully capable of learning residue interactions within the local structure of PPI sites using only sequence information. The web server of EnsemPPIS is freely available at http://idrblab.org/ensemppis.

The Impact of ETV6-NTRK3 Oncogenic Gene Fusions on Molecular and Signaling Pathway Alterations

Chromosomal translocations creating fusion genes are common cancer drivers. The oncogenic ETV6-NTRK3 (EN) gene fusion joins the sterile alpha domain of the ETV6 transcription factor with the tyrosine kinase domain of the neurotrophin-3 receptor NTRK3. Four EN variants with alternating break points have since been detected in a wide range of human cancers. To provide molecular level insight into EN oncogenesis, we employed a proximity labeling mass spectrometry approach to define the molecular context of the fusions. We identify in total 237 high-confidence interactors, which link EN fusions to several key signaling pathways, including ERBB, insulin and JAK/STAT. We then assessed the effects of EN variants on these pathways, and showed that the pan NTRK inhibitor Selitrectinib (LOXO-195) inhibits the oncogenic activity of EN2, the most common variant. This systems-level analysis defines the molecular framework in which EN oncofusions operate to promote cancer and provides some mechanisms for therapeutics.

In vivo Polycystin-1 interactome using a novel Pkd1 knock-in mouse model

PKD1 is the most commonly mutated gene causing autosomal dominant polycystic kidney disease (ADPKD). It encodes Polycystin-1 (PC1), a putative membrane protein that undergoes a set of incompletely characterized post-transcriptional cleavage steps and has been reported to localize in multiple subcellular locations, including the primary cilium and mitochondria. However, direct visualization of PC1 and detailed characterization of its binding partners remain challenging. We now report a new mouse model with HA epitopes and eGFP knocked-in frame into the endogenous mouse Pkd1 gene by CRISPR/Cas9. Using this model, we sought to visualize endogenous PC1-eGFP and performed affinity-purification mass spectrometry (AP-MS) and network analyses. We show that the modified Pkd1 allele is fully functional but the eGFP-tagged protein cannot be detected without signal amplification by secondary antibodies. Using nanobody-coupled beads and large quantities of tissue, AP-MS identified an in vivo PC1 interactome, which is enriched for mitochondrial proteins and components of metabolic pathways. These studies suggest this mouse model and interactome data will be useful to understand PC1 function, but that new methods and brighter tags will be required to track endogenous PC1.

Structural characterization of protein-material interfacial interactions using lysine reactivity profiling-mass spectrometry

Understanding how proteins and materials interact is useful for evaluating the safety of biomedical micro/nanomaterials, toxicity estimation and design of nano-drugs and catalytic activity improvement of bio-inorganic functional hybrids. However, characterizing the interfacial molecular details of protein-micro/nanomaterial hybrids remains a great challenge. This protocol describes the lysine reactivity profiling-mass spectrometry strategy for determining which parts of a protein are interacting with the micro/nanomaterials. Lysine residues occur frequently on hydrophilic protein surfaces, and their reactivity is dependent on the accessibility of their amine groups. The accessibility of a lysine residue is lower when it is in contact with another object; allosteric effects resulting from this interaction might reduce or increase the reactivity of remote lysine residues. Lysine reactivity is therefore a useful indicator of protein localization orientation, interaction sequence regions, binding sites and modulated protein structures in the protein-material hybrids. We describe the optimized two-step isotope dimethyl labeling strategy for protein-material hybrids under their native and denaturing conditions in sequence. The comparative quantification results of lysine reactivity are only dependent on the native microenvironments of lysine local structures. We also highlight other critical steps including protein digestion, elution from materials, data processing and interfacial structure analysis. The two-step isotope labeling steps need ~5 h, and the whole protocol including digestion, liquid chromatography-tandem mass spectrometry, data processing and structure analysis needs ~3-5 d.

Chemical labeling and proteomics for characterization of unannotated small and alternative open reading frame-encoded polypeptides

Thousands of unannotated small and alternative open reading frames (smORFs and alt-ORFs, respectively) have recently been revealed in mammalian genomes. While hundreds of mammalian smORF- and alt-ORF-encoded proteins (SEPs and alt-proteins, respectively) affect cell proliferation, the overwhelming majority of smORFs and alt-ORFs remain uncharacterized at the molecular level. Complicating the task of identifying the biological roles of smORFs and alt-ORFs, the SEPs and alt-proteins that they encode exhibit limited sequence homology to protein domains of known function. Experimental techniques for the functionalization of these gene classes are therefore required. Approaches combining chemical labeling and quantitative proteomics have greatly advanced our ability to identify and characterize functional SEPs and alt-proteins in high throughput. In this review, we briefly describe the principles of proteomic discovery of SEPs and alt-proteins, then summarize how these technologies interface with chemical labeling for identification of SEPs and alt-proteins with specific properties, as well as in defining the interactome of SEPs and alt-proteins.

Investigating the dynamics of protein-protein interactions in plants

Both stable and transient protein interactions play an important role in the complex assemblies required for the proper functioning of living cells. Several methods have been developed to monitor protein-protein interactions in plants. However, the detection of dynamic protein complexes is very challenging, with few technologies available for this purpose. Here, we developed a new platform using the plant UBIQUITIN promoter to drive transgene expression and thereby to detect protein interactions in planta. Typically, to decide which side of the protein to link the tags, the subcellular localization of the protein fused either N-terminal or C-terminal mCitrine was firstly confirmed by using eight different specific mCherry markers. Following stable or transient protein expression in plants, the protein interaction network was detected by affinity purification mass spectrometry. These interactions were subsequently confirmed by bimolecular fluorescence complementation (BiFC), bioluminescence resonance energy transfer and co-immunoprecipitation assays. The dynamics of these interactions were monitored by Förster resonance energy transfer (FRET) and split-nano luciferase, whilst the ternary protein complex association was monitored by BiFC-FRET. Using the canonical glycolytic metabolon as an example, the interaction between these enzymes was characterized under conditions that mimic physiologically relevant energy statuses.

Phosphoproteomic Approaches for Identifying Phosphatase and Kinase Substrates

Protein phosphorylation is a ubiquitous post-translational modification controlled by the opposing activities of protein kinases and phosphatases, which regulate diverse biological processes in all kingdoms of life. One of the key challenges to a complete understanding of phosphoregulatory networks is the unambiguous identification of kinase and phosphatase substrates. Liquid chromatography-coupled mass spectrometry (LC-MS/MS) and associated phosphoproteomic tools enable global surveys of phosphoproteome changes in response to signaling events or perturbation of phosphoregulatory network components. Despite the power of LC-MS/MS, it is still challenging to directly link kinases and phosphatases to specific substrate phosphorylation sites in many experiments. Here, we survey common LC-MS/MS-based phosphoproteomic workflows for identifying protein kinase and phosphatase substrates, noting key advantages and limitations of each. We conclude by discussing the value of inducible degradation technologies coupled with phosphoproteomics as a new approach that overcomes some limitations of current methods for substrate identification of kinases, phosphatases, and other regulatory enzymes.

MAPKAP Kinase-2 phosphorylation of PABPC1 controls its interaction with 14-3-3 proteins after DNA damage: A combined kinase and protein array approach

14-3-3 proteins play critical roles in controlling multiple aspects of the cellular response to stress and DNA damage including regulation of metabolism, cell cycle progression, cell migration, and apoptotic cell death by binding to protein substrates of basophilic protein kinases following their phosphorylation on specific serine/threonine residues. Although over 200 mammalian proteins that bind to 14-3-3 have been identified, largely through proteomic studies, in many cases the relevant protein kinase responsible for conferring 14-3-3-binding to these proteins is not known. To facilitate the identification of kinase-specific 14-3-3 clients, we developed a biochemical approach using high-density protein filter arrays and identified the translational regulatory molecule PABPC1 as a substrate for Chk1 and MAPKAP Kinase-2 (MK2) in vitro, and for MK2 in vivo, whose phosphorylation results in 14-3-3-binding. We identify Ser-470 on PABPC1 within the linker region connecting the RRM domains to the PABC domain as the critical 14-3-3-binding site, and demonstrate that loss of PABPC1 binding to 14-3-3 results in increased cell proliferation and decreased cell death in response to UV-induced DNA damage.

Septins and K63 ubiquitin chains are present in separate bacterial microdomains during autophagy of entrapped Shigella

During host cell invasion, Shigella escapes to the cytosol and polymerizes actin for cell-to-cell spread. To restrict cell-to-cell spread, host cells employ cell-autonomous immune responses including antibacterial autophagy and septin cage entrapment. How septins interact with the autophagy process to target Shigella for destruction is poorly understood. Here, we employed a correlative light and cryo-soft X-ray tomography (cryo-SXT) pipeline to study Shigella septin cage entrapment in its near-native state. Quantitative cryo-SXT showed that Shigella fragments mitochondria and enabled visualization of X-ray-dense structures (∼30 nm resolution) surrounding Shigella entrapped in septin cages. Using Airyscan confocal microscopy, we observed lysine 63 (K63)-linked ubiquitin chains decorating septin-cage-entrapped Shigella. Remarkably, septins and K63 chains are present in separate bacterial microdomains, indicating they are recruited separately during antibacterial autophagy. Cryo-SXT and live-cell imaging revealed an interaction between septins and LC3B-positive membranes during autophagy of Shigella. Together, these findings demonstrate how septin-caged Shigella are targeted for autophagy and provide fundamental insights into autophagy-cytoskeleton interactions.

Comprehensive characterization of the embryonic factor LEUTX

The paired-like homeobox transcription factor LEUTX is expressed in human preimplantation embryos between the 4- and 8-cell stages, and then silenced in somatic tissues. To characterize the function of LEUTX, we performed a multiomic characterization of LEUTX using two proteomics methods and three genome-wide sequencing approaches. Our results show that LEUTX stably interacts with the EP300 and CBP histone acetyltransferases through its 9 amino acid transactivation domain (9aaTAD), as mutation of this domain abolishes the interactions. LEUTX targets genomic cis-regulatory sequences that overlap with repetitive elements, and through these elements it is suggested to regulate the expression of its downstream genes. We find LEUTX to be a transcriptional activator, upregulating several genes linked to preimplantation development as well as 8-cell-like markers, such as DPPA3 and ZNF280A. Our results support a role for LEUTX in preimplantation development as an enhancer binding protein and as a potent transcriptional activator.

Applying genetic technologies to combat infectious diseases in aquaculture

Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies-sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.

Iron-tracking strategies: Chaperones capture iron in the cytosolic labile iron pool

Cells express hundreds of iron-dependent enzymes that rely on the iron cofactors heme, iron-sulfur clusters, and mono-or di-nuclear iron centers for activity. Cells require systems for both the assembly and the distribution of iron cofactors to their cognate enzymes. Proteins involved in the binding and trafficking of iron ions in the cytosol, called cytosolic iron chaperones, have been identified and characterized in mammalian cells. The first identified iron chaperone, poly C-binding protein 1 (PCBP1), has also been studied in mice using genetic models of conditional deletion in tissues specialized for iron handling. Studies of iron trafficking in mouse tissues have necessitated the development of new approaches, which have revealed new roles for PCBP1 in the management of cytosolic iron. These approaches can be applied to investigate use of other nutrient metals in mammals.

Characterization of Expanded Gamma Delta T Cells from Atypical X-SCID Patient Reveals Preserved Function and IL2RG-Mediated Signaling

Abnormally high γδ T cell numbers among individuals with atypical SCID have been reported but detailed immunophenotyping and functional characterization of these expanded γδ T cells are limited. We have previously reported atypical SCID phenotype caused by hypomorphic IL2RG (NM_000206.3) c.172C > T;p.(Pro58Ser) variant. Here, we have further investigated the index patient's abnormally large γδ T cell population in terms of function and phenotype by studying IL2RG cell surface expression, STAT tyrosine phosphorylation and blast formation in response to interleukin stimulation, immunophenotyping, TCRvγ sequencing, and target cell killing. In contrast to his ⍺β T cells, the patient's γδ T cells showed normal IL2RG cell surface expression and normal or enhanced IL2RG-mediated signaling. Vδ2 + population was proportionally increased with a preponderance of memory phenotypes and high overall tendency towards perforin expression. The patient's γδ T cells showed enhanced cytotoxicity towards A549 cancer cells. His TCRvγ repertoire was versatile but sequencing of IL2RG revealed a novel c.534C > A; p.(Phe178Leu) somatic missense variant restricted to γδ T cells. Over time this variant became predominant in γδ T cells, though initially present only in part of them. IL2RG-Pro58Ser/Phe178Leu variant showed higher cell surface expression compared to IL2RG-Pro58Ser variant in stable HEK293 cell lines, suggesting that somatic p.(Phe178Leu) variant may at least partially rescue the pathogenic effect of germline p.(Pro58Ser) variant. In conclusion, our report indicates that expansion of γδ T cells associated with atypical SCID needs further studying and cannot exclusively be deemed as a homeostatic response to low numbers of conventional T cells.

Recruitment of TRIM33 to cell-context specific PML nuclear bodies regulates nodal signaling in mESCs

TRIM33 is a chromatin reader required for mammalian mesendoderm differentiation after activation of Nodal signaling, while its role in mESCs is still elusive. Here, we report that TRIM33 co-localizes with promyelocytic leukemia nuclear bodies (PML-NBs) specifically in mESCs, to mediate Nodal signaling-directed transcription of Lefty1/2. We show that TRIM33 puncta formation in mESCs depends on PML and on specific assembly of PML-NBs. Moreover, TRIM33 and PML co-regulate Lefty1/2 expression in mESCs, with both PML protein and formation of mESCs-specific PML-NBs being required for TRIM33 recruitment to these loci, and PML-NBs directly associating with the Lefty1/2 loci. Finally, a TurboID proximity-labeling experiment confirmed that TRIM33 is highly enriched only in mESCs-specific PML-NBs. Thus, our study supports a model in which TRIM33 condensates regulate Nodal signaling-directed transcription in mESCs and shows that PML-NBs can recruit distinct sets of client proteins in a cell-context-dependent manner.

Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications

Membrane proteins mediate a wide spectrum of biological processes, such as signal transduction and cell communication. Due to the arduous and costly nature inherent to the experimental process, membrane proteins have long been devoid of well-resolved atomic-level tertiary structures and, consequently, the understanding of their functional roles underlying a multitude of life activities has been hampered. Currently, computational tools dedicated to furthering the structure-function understanding are primarily focused on utilizing intelligent algorithms to address a variety of site-wise prediction problems (e.g., topology and interaction sites), but are scattered across different computing sources. Moreover, the recent advent of deep learning techniques has immensely expedited the development of computational tools for membrane protein-related prediction problems. Given the growing number of applications optimized particularly by manifold deep neural networks, we herein provide a review on the current status of computational strategies mainly in membrane protein type classification, topology identification, interaction site detection, and pathogenic effect prediction. Meanwhile, we provide an overview of how the entire prediction process proceeds, including database collection, data pre-processing, feature extraction, and method selection. This review is expected to be useful for developing more extendable computational tools specific to membrane proteins.

Bioinformatics approaches for unveiling virus-host interactions

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

Building Protein-Protein Interaction Graph Database Using Neo4j

A cell's various components interact with each other in a coordinated manner to respond to environmental cues and intracellular signals. Compared to the other biological networks, the protein-protein interaction (PPI) is mostly responsible for maintaining signaling pathways. Increasing numbers of experimentally verified and predicted PPIs in plants demand a scalable platform to deal with large and complex datasets. Network/graph data can be organized and analyzed using different tools. This chapter uses Neo4j, a graph database management system, to store and analyze plant PPI networks. To make the graph database and analyze network centrality, we used Arabidopsis interactome-1 main (AI-1MAIN) PPI network.

Analyzing Protein Interactions by MAC-Tag Approaches

Proteomics methods such as affinity purification (AP) and proximity-dependent labeling (PL) coupled with mass spectrometry (MS) are currently commonly utilized to define interaction landscapes. BioID is one of the PL approaches, and it employs the expression of bait proteins fused to a nonspecific biotin ligase (BirA*), to induce in vivo biotinylation of proximal proteins. We developed the multiple approaches combined (MAC)-tag workflow, which allows for both AP and BioID analysis with a single construct and with almost identical protein purification and MS identification procedures. MAC-tag is a well-established method and has been widely used. Recent developed PL tags such as BioID2 and UltraID are smaller versions of BirA* with faster labeling efficiency. We therefore incorporate these tags into our system to develop MAC2-tag (containing BioID2) and MAC3-tag (containing UltraID) to overcome potential limitations of the original MAC-tag system and broaden the spectrum of applications for MAC-tags. Here, we describe a detailed procedure for the MAC-tag system workflow including cell line generation for the MAC/MAC2/MAC3-tagged protein of interest (POI), sample preparation for AP and PL protein purification, and MS analysis.

Structural Studies Reveal that Endosomal Cations Promote Formation of Infectious Coxsackievirus A9 A-Particles, Facilitating RNA and VP4 Release

Coxsackievirus A9 (CVA9), an enterovirus, is a common cause of pediatric aseptic meningitis and neonatal sepsis. During cell entry, enterovirus capsids undergo conformational changes leading to expansion, formation of large pores, externalization of VP1 N termini, and loss of the lipid factor from VP1. Factors such as receptor binding, heat, and acidic pH can trigger capsid expansion in some enteroviruses. Here, we show that fatty acid-free bovine serum albumin or neutral endosomal ionic conditions can independently prime CVA9 for expansion and genome release. Our results showed that CVA9 treatment with albumin or endosomal ions generated a heterogeneous population of virions, which could be physically separated by asymmetric flow field flow fractionation and computationally by cryo-electron microscopy (cryo-EM) and image processing. We report cryo-EM structures of CVA9 A-particles obtained by albumin or endosomal ion treatment and a control nonexpanded virion to 3.5, 3.3, and 2.9 Å resolution, respectively. Whereas albumin promoted stable expanded virions, the endosomal ionic concentrations induced unstable CVA9 virions which easily disintegrated, losing their genome. Loss of most of the VP4 molecules and exposure of negatively charged amino acid residues in the capsid's interior after expansion created a repulsive viral RNA-capsid interface, aiding genome release. IMPORTANCE Coxsackievirus A9 (CVA9) is a common cause of meningitis and neonatal sepsis. The triggers and mode of action of RNA release into the cell unusually do not require receptor interaction. Rather, a slow process in the endosome, independent of low pH, is required. Here, we show by biophysical separation, cryogenic electron microscopy, and image reconstruction that albumin and buffers mimicking the endosomal ion composition can separately and together expand and prime CVA9 for uncoating. Furthermore, we show in these expanded particles that VP4 is present at only ~10% of the occupancy found in the virion, VP1 is externalized, and the genome is repelled by the negatively charged, repulsive inner surface of the capsid that occurs due to the expansion. Thus, we can now link observations from cell biology of infection with the physical processes that occur in the capsid to promote genome uncoating.

Heterozygous premature termination in zinc-finger domain of Krüppel-like factor 2 gene associates with dysregulated immunity

Krüppel-like factor 2 (KLF2) is a transcription factor with significant roles in development, maturation, differentiation, and proliferation of several cell types. In immune cells, KLF2 regulates maturation and trafficking of lymphocytes and monocytes. KLF2 participates in regulation of the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway. Although pulmonary arterial hypertension (PAH) related to KLF2 genetic variant has been suggested, genetic role of KLF2 associated with immune dysregulation has not been described. We identified a family whose members suffered from lymphopenia, autoimmunity, and malignancy. Whole exome sequencing revealed a KLF2 p.(Glu318Argfs*87) mutation disrupting the highly conserved zinc finger domain. We show a reduced amount of KLF2 protein, defective nuclear localization and altered protein-protein interactome. The phenotypically variable positive cases presented with B and T cell lymphopenia and abnormalities in B and T cell maturation including low naive T cell counts and low CD27+IgD-IgM- switched memory B cells. KLF2 target gene (CD62L) expression was affected. Although the percentage of (CD25+FOXP3+, CD25+CD127-) regulatory T cells (Treg) was high, the naive Treg cells (CD45RA+) were absent. Serum IgG1 levels were low and findings in one case were consistent with common variable immunodeficiency (CVID). Transcription of NF-κβ pathway genes and p65/RelA phosphorylation were not significantly affected. Inflammasome activity, transcription of genes related with JAK/STAT pathway and interferon signature were also comparable to controls. Evidence of PAH was not found. In conclusion, KLF2 variant may be associated with familial immune dysregulation. Although the KLF2 deficient family members in our study suffered from lymphopenia, autoimmunity or malignancy, additional study cohorts are required to confirm our observations.

Mapping of the plant SnRK1 kinase signalling network reveals a key regulatory role for the class II T6P synthase-like proteins

The central metabolic regulator SnRK1 controls plant growth and survival upon activation by energy depletion, but detailed molecular insight into its regulation and downstream targets is limited. Here we used phosphoproteomics to infer the sucrose-dependent processes targeted upon starvation by kinases as SnRK1, corroborating the relation of SnRK1 with metabolic enzymes and transcriptional regulators, while also pointing to SnRK1 control of intracellular trafficking. Next, we integrated affinity purification, proximity labelling and crosslinking mass spectrometry to map the protein interaction landscape, composition and structure of the SnRK1 heterotrimer, providing insight in its plant-specific regulation. At the intersection of this multi-dimensional interactome, we discovered a strong association of SnRK1 with class II T6P synthase (TPS)-like proteins. Biochemical and cellular assays show that TPS-like proteins function as negative regulators of SnRK1. Next to stable interactions with the TPS-like proteins, similar intricate connections were found with known regulators, suggesting that plants utilize an extended kinase complex to fine-tune SnRK1 activity for optimal responses to metabolic stress.

Deciphering Spatial Protein-Protein Interactions in Brain Using Proximity Labeling

Cellular biomolecular complexes including protein-protein, protein-RNA, and protein-DNA interactions regulate and execute most biological functions. In particular in brain, protein-protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell-cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte-neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.

Common variable immunodeficiency in two kindreds with heterogeneous phenotypes caused by novel heterozygous NFKB1 mutations

NFKB1 haploinsufficiengcy was first described in 2015 in three families with common variable immunodeficiency (CVID), presenting heterogeneously with symptoms of increased infectious susceptibility, skin lesions, malignant lymphoproliferation and autoimmunity. The described mutations all led to a rapid degradation of the mutant protein, resulting in a p50 haploinsufficient state. Since then, more than 50 other mutations have been reported, located throughout different domains of NFKB1 with the majority situated in the N-terminal Rel homology domain (RHD). The clinical spectrum has also expanded with possible disease manifestations in almost any organ system. In silico prediction tools are often used to estimate the pathogenicity of NFKB1 variants but to prove causality between disease and genetic findings, further downstream functional validation is required. In this report, we studied 2 families with CVID and two novel variants in NFKB1 (c.1638-2A>G and c.787G>C). Both mutations affected mRNA and/or protein expression of NFKB1 and resulted in excessive NLRP3 inflammasome activation in patient macrophages and upregulated interferon stimulated gene expression. Protein-protein interaction analysis demonstrated a loss of interaction with NFKB1 interaction partners for the p.V263L mutation. In conclusion, we proved pathogenicity of two novel variants in NFKB1 in two families with CVID characterized by variable and incomplete penetrance.

Detrimental NFKB1 missense variants affecting the Rel-homology domain of p105/p50

Most of the currently known heterozygous pathogenic NFKB1 (Nuclear factor kappa B subunit 1) variants comprise deleterious defects such as severe truncations, internal deletions, and frameshift variants. Collectively, these represent the most frequent monogenic cause of common variable immunodeficiency (CVID) identified so far. NFKB1 encodes the transcription factor precursor p105 which undergoes limited proteasomal processing of its C-terminal half to generate the mature NF-κB subunit p50. Whereas p105/p50 haploinsufficiency due to devastating genetic damages and protein loss is a well-known disease mechanism, the pathogenic significance of numerous NFKB1 missense variants still remains uncertain and/or unexplored, due to the unavailability of accurate test procedures to confirm causality. In this study we functionally characterized 47 distinct missense variants residing within the N-terminal domains, thus affecting both proteins, the p105 precursor and the processed p50. Following transient overexpression of EGFP-fused mutant p105 and p50 in HEK293T cells, we used fluorescence microscopy, Western blotting, electrophoretic mobility shift assays (EMSA), and reporter assays to analyze their effects on subcellular localization, protein stability and precursor processing, DNA binding, and on the RelA-dependent target promoter activation, respectively. We found nine missense variants to cause harmful damage with intensified protein decay, while two variants left protein stability unaffected but caused a loss of the DNA-binding activity. Seven of the analyzed single amino acid changes caused ambiguous protein defects and four variants were associated with only minor adverse effects. For 25 variants, test results were indistinguishable from those of the wildtype controls, hence, their pathogenic impact remained elusive. In summary, we show that pathogenic missense variants affecting the Rel-homology domain may cause protein-decaying defects, thus resembling the disease-mechanisms of p105/p50 haploinsufficiency or may cause DNA-binding deficiency. However, rare variants (with a population frequency of less than 0.01%) with minor abnormalities or with neutral tests should still be considered as potentially pathogenic, until suitable tests have approved them being benign.

Molecular Interactions Between Leptosphaeria maculans and Brassica Species

Canola is an important oilseed crop, providing food, feed, and fuel around the world. However, blackleg disease, caused by the ascomycete Leptosphaeria maculans, causes significant yield losses annually. With the recent advances in genomic technologies, the understanding of the Brassica napus-L. maculans interaction has rapidly increased, with numerous Avr and R genes cloned, setting this system up as a model organism for studying plant-pathogen associations. Although the B. napus-L. maculans interaction follows Flor's gene-for-gene hypothesis for qualitative resistance, it also puts some unique spins on the interaction. This review discusses the current status of the host-pathogen interaction and highlights some of the future gaps that need addressing moving forward.

Construction of a Mass-Tagged Oligo Probe Set for Revealing Protein Ratiometric Relationship Associated with EGFR-HER2 Heterodimerization in Living Cells

Protein dimerization, as the most common form of protein-protein interaction, can manifest more significant roles in cellular signaling than individual monomers. For example, excessive formation of EGFR-HER2 dimer has been implicated in cancer development and therapeutic resistance in addition to the overexpression of EGFR and HER2 proteins. Thus, quantitative evaluation of these heterodimers in living cells and revelation of their ratiometric relationship with protein monomers in dimerization may provide insights into clinical cancer management. To achieve this goal, the prerequisite is protein heterodimer quantification. Given the current lack of quantitative methods, we constructed a mass-tagged oligo nanoprobe set for quantification of EGFR-HER2 dimer in living cells. The mass-tagged oligo nanoprobe set contained two targeting probes (nucleic acid aptamers), a connector probe, a hairpin probe, and a photocleavable mass-tagged probe. Two distinct aptamers can recognize target protein monomers and initiate the subsequent hybridization cascade involving binding to the connector probe, formation of an initiator strand, opening of a hairpin probe, and ensuing hybridization with a photocleavable mass-tagged probe. Ultimately, the mass tag was released under ultraviolet light and then subjected to mass spectrometric analysis. In this way, the information regarding the interaction between two protein monomers was successfully converted to the quantitative signal of the mass tag. Using the assay, the expression level of EGFR-HER2 dimer and its relationship with individual protein monomers were determined in four breast cancer cell lines. We are among the first to obtain the absolute level of protein heterodimer, and this quantitative information may be vital in understanding the molecular basis of cancer.

SubCellBarCode: integrated workflow for robust spatial proteomics by mass spectrometry

The molecular functions of a protein are defined by its inherent properties in relation to its environment and interaction network. Within a cell, this environment and network are defined by the subcellular location of the protein. Consequently, it is crucial to know the localization of a protein to fully understand its functions. Recently, we have developed a mass spectrometry- (MS) and bioinformatics-based pipeline to generate a proteome-wide resource for protein subcellular localization across multiple human cancer cell lines ( www.subcellbarcode.org ). Here, we present a detailed wet-lab protocol spanning from subcellular fractionation to MS-sample preparation and analysis. A key feature of this protocol is that it includes all generated cell fractions without discarding any material during the fractionation process. We also describe the subsequent quantitative MS-data analysis, machine learning-based classification, differential localization analysis and visualization of the output. For broad applicability, we evaluated the pipeline by using MS data generated by two different peptide pre-fractionation approaches, namely high-resolution isoelectric focusing and high-pH reverse-phase fractionation, as well as direct analysis without pre-fractionation by using long-gradient liquid chromatography-MS. Moreover, an R package covering the dry-lab part of the method was developed and made available through Bioconductor. The method is straightforward and robust, and the entire protocol, from cell harvest to classification output, can be performed within 1-2 weeks. The protocol enables accurate classification of proteins to 15 compartments and 4 neighborhoods, visualization of the output data and differential localization analysis including treatment-induced protein relocalization, condition-dependent localization or cell type-specific localization. The SubCellBarCode package is freely available at https://bioconductor.org/packages/devel/bioc/html/SubCellBarCode.html .

Physical and functional interactome atlas of human receptor tyrosine kinases

Much cell‐to‐cell communication is facilitated by cell surface receptor tyrosine kinases (RTKs). These proteins phosphorylate their downstream cytoplasmic substrates in response to stimuli such as growth factors. Despite their central roles, the functions of many RTKs are still poorly understood. To resolve the lack of systematic knowledge, we apply three complementary methods to map the molecular context and substrate profiles of RTKs. We use affinity purification coupled to mass spectrometry (AP‐MS) to characterize stable binding partners and RTK–protein complexes, proximity‐dependent biotin identification (BioID) to identify transient and proximal interactions, and an in vitro kinase assay to identify RTK substrates. To identify how kinase interactions depend on kinase activity, we also use kinase‐deficient mutants. Our data represent a comprehensive, systemic mapping of RTK interactions and substrates. This resource adds information regarding well‐studied RTKs, offers insights into the functions of less well‐studied RTKs, and highlights RTK‐RTK interactions and shared signaling pathways.

Nuclear Receptor Coregulators in Hormone-Dependent Cancers

Nuclear receptors (NRs) function collectively as a transcriptional signaling network that mediates gene regulatory actions to either maintain cellular homeostasis in response to hormonal, dietary and other environmental factors, or act as orphan receptors with no known ligand. NR complexes are large and interact with multiple protein partners, collectively termed coregulators. Coregulators are essential for regulating NR activity and can dictate whether a target gene is activated or repressed by a variety of mechanisms including the regulation of chromatin accessibility. Altered expression of coregulators contributes to a variety of hormone-dependent cancers including breast and prostate cancers. Therefore, understanding the mechanisms by which coregulators interact with and modulate the activity of NRs provides opportunities to develop better prognostic and diagnostic approaches, as well as novel therapeutic targets. This review aims to gather and summarize recent studies, techniques and bioinformatics methods used to identify distorted NR coregulator interactions that contribute as cancer drivers in hormone-dependent cancers.

New insights into the molecular mechanisms of ROR1, ROR2, and PTK7 signaling from the proteomics and pharmacological modulation of ROR1 interactome

ROR1, ROR2, and PTK7 are Wnt ligand-binding members of the receptor tyrosine kinase family. Despite their lack of catalytic activity, these receptors regulate skeletal, cardiorespiratory, and neurological development during embryonic and fetal stages. However, their overexpression in adult tissue is strongly connected to tumor development and metastasis, suggesting a strong pharmacological potential for these molecules. Wnt5a ligand can activate these receptors, but lead to divergent signaling and functional outcomes through mechanisms that remain largely unknown. Here, we developed a cellular model by stably expressing ROR1, ROR2, and PTK7 in BaF3 cells that allowed us to readily investigate side-by-side their signaling capability and functional outcome. We applied proteomic profiling to BaF3 clones and identified distinctive roles for ROR1, ROR2, and PTK7 pseudokinases in modulating the expression of proteins involved in cytoskeleton dynamics, apoptotic, and metabolic signaling. Functionally, we show that ROR1 expression enhances cell survival and Wnt-mediated cell proliferation, while ROR2 and PTK7 expression is linked to cell migration. We also demonstrate that the distal C-terminal regions of ROR1 and ROR2 are required for receptors stability and downstream signaling. To probe the pharmacological modulation of ROR1 oncogenic signaling, we used affinity purification coupled to mass spectrometry (AP-MS) and proximity-dependent biotin identification (BioID) to map its interactome before and after binding of GZD824, a small molecule inhibitor previously shown to bind to the ROR1 pseudokinase domain. Our findings bring new insight into the molecular mechanisms of ROR1, ROR2, and PTK7, and highlight the therapeutic potential of targeting ROR1 with small molecule inhibitors binding to its vestigial ATP-binding site.