SAINT: probabilistic scoring of affinity purification-mass spectrometry data

mTORC1-chaperonin CCT signaling regulates m6A RNA methylation to suppress autophagy

Mechanistic Target of Rapamycin Complex 1 (mTORC1) is a central regulator of cell growth and metabolism that senses and integrates nutritional and environmental cues with cellular responses. Recent studies have revealed critical roles of mTORC1 in RNA biogenesis and processing. Here, we find that the m6A methyltransferase complex (MTC) is a downstream effector of mTORC1 during autophagy in Drosophila and human cells. Furthermore, we show that the Chaperonin Containing Tailless complex polypeptide 1 (CCT) complex, which facilitates protein folding, acts as a link between mTORC1 and MTC. The mTORC1 activates the chaperonin CCT complex to stabilize MTC, thereby increasing m6A levels on the messenger RNAs encoding autophagy-related genes, leading to their degradation and suppression of autophagy. Altogether, our study reveals an evolutionarily conserved mechanism linking mTORC1 signaling with m6A RNA methylation and demonstrates their roles in suppressing autophagy.

STAU2 protein level is controlled by caspases and the CHK1 pathway and regulates cell cycle progression in the non-transformed hTERT-RPE1 cells

Background

Staufen2 (STAU2) is an RNA binding protein involved in the posttranscriptional regulation of gene expression. In neurons, STAU2 is required to maintain the balance between differentiation and proliferation of neural stem cells through asymmetric cell division. However, the importance of controlling STAU2 expression for cell cycle progression is not clear in non-neuronal dividing cells. We recently showed that STAU2 transcription is inhibited in response to DNA-damage due to E2F1 displacement from the STAU2 gene promoter. We now study the regulation of STAU2 steady-state levels in unstressed cells and its consequence for cell proliferation.

Results

CRISPR/Cas9-mediated and RNAi-dependent STAU2 depletion in the non-transformed hTERT-RPE1 cells both facilitate cell proliferation suggesting that STAU2 expression influences pathway(s) linked to cell cycle controls. Such effects are not observed in the CRISPR STAU2-KO cancer HCT116 cells nor in the STAU2-RNAi-depleted HeLa cells. Interestingly, a physiological decrease in the steady-state level of STAU2 is controlled by caspases. This effect of peptidases is counterbalanced by the activity of the CHK1 pathway suggesting that STAU2 partial degradation/stabilization fines tune cell cycle progression in unstressed cells. A large-scale proteomic analysis using STAU2/biotinylase fusion protein identifies known STAU2 interactors involved in RNA translation, localization, splicing, or decay confirming the role of STAU2 in the posttranscriptional regulation of gene expression. In addition, several proteins found in the nucleolus, including proteins of the ribosome biogenesis pathway and of the DNA damage response, are found in close proximity to STAU2. Strikingly, many of these proteins are linked to the kinase CHK1 pathway, reinforcing the link between STAU2 functions and the CHK1 pathway. Indeed, inhibition of the CHK1 pathway for 4 h dissociates STAU2 from proteins involved in translation and RNA metabolism.

Conclusions

These results indicate that STAU2 is involved in pathway(s) that control(s) cell proliferation, likely via mechanisms of posttranscriptional regulation, ribonucleoprotein complex assembly, genome integrity and/or checkpoint controls. The mechanism by which STAU2 regulates cell growth likely involves caspases and the kinase CHK1 pathway.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12860-021-00352-y.

SUMOylation regulates the protein network and chromatin accessibility at glucocorticoid receptor-binding sites

Glucocorticoid receptor (GR) is an essential transcription factor (TF), controlling metabolism, development and immune responses. SUMOylation regulates chromatin occupancy and target gene expression of GR in a locus-selective manner, but the mechanism of regulation has remained elusive. Here, we identify the protein network around chromatin-bound GR by using selective isolation of chromatin-associated proteins and show that the network is affected by receptor SUMOylation, with several nuclear receptor coregulators and chromatin modifiers preferring interaction with SUMOylation-deficient GR and proteins implicated in transcriptional repression preferring interaction with SUMOylation-competent GR. This difference is reflected in our chromatin binding, chromatin accessibility and gene expression data, showing that the SUMOylation-deficient GR is more potent in binding and opening chromatin at glucocorticoid-regulated enhancers and inducing expression of target loci. Blockage of SUMOylation by a SUMO-activating enzyme inhibitor (ML-792) phenocopied to a large extent the consequences of GR SUMOylation deficiency on chromatin binding and target gene expression. Our results thus show that SUMOylation modulates the specificity of GR by regulating its chromatin protein network and accessibility at GR-bound enhancers. We speculate that many other SUMOylated TFs utilize a similar regulatory mechanism.

Proximity-dependent Mapping of the Androgen Receptor Identifies Kruppel-like Factor 4 as a Functional Partner

Prostate cancer (PCa) is the most frequently diagnosed cancer in men and the third cause of cancer mortality. PCa initiation and growth are driven by the androgen receptor (AR). The AR is activated by androgens such as testosterone and controls prostatic cell proliferation and survival. Here, we report an AR signaling network generated using BioID proximity labeling proteomics in androgen-dependent LAPC4 cells. We identified 31 AR-associated proteins in nonstimulated cells. Strikingly, the AR signaling network increased to 182 and 200 proteins, upon 24 h or 72 h of androgenic stimulation, respectively, for a total of 267 nonredundant AR-associated candidates. Among the latter group, we identified 213 proteins that were not previously reported in databases. Many of these new AR-associated proteins are involved in DNA metabolism, RNA processing, and RNA polymerase II transcription. Moreover, we identified 44 transcription factors, including the Kru¨ppel-like factor 4 (KLF4), which were found interacting in androgen-stimulated cells. Interestingly, KLF4 repressed the well-characterized AR-dependent transcription of the KLK3 (PSA) gene; AR and KLF4 also colocalized genome-wide. Taken together, our data report an expanded high-confidence proximity network for AR, which will be instrumental to further dissect the molecular mechanisms underlying androgen signaling in PCa cells.

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BioID proteomics identifies 267 androgen receptor (AR)-associated candidates

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Krüppel-like factor 4 (KLF4) is a new AR interaction partner

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AR and KLF4 colocalize genome-wide on >4000 genes, including KLK3 (PSA)

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KLF4 acts as a repressor for the AR target gene KLK3 (PSA)

The proximal proteome of 17 SARS-CoV-2 proteins links to disrupted antiviral signaling and host translation

Viral proteins localize within subcellular compartments to subvert host machinery and promote pathogenesis. To study SARS-CoV-2 biology, we generated an atlas of 2422 human proteins vicinal to 17 SARS-CoV-2 viral proteins using proximity proteomics. This identified viral proteins at specific intracellular locations, such as association of accessary proteins with intracellular membranes, and projected SARS-CoV-2 impacts on innate immune signaling, ER-Golgi transport, and protein translation. It identified viral protein adjacency to specific host proteins whose regulatory variants are linked to COVID-19 severity, including the TRIM4 interferon signaling regulator which was found proximal to the SARS-CoV-2 M protein. Viral NSP1 protein adjacency to the EIF3 complex was associated with inhibited host protein translation whereas ORF6 localization with MAVS was associated with inhibited RIG-I 2CARD-mediated IFNB1 promoter activation. Quantitative proteomics identified candidate host targets for the NSP5 protease, with specific functional cleavage sequences in host proteins CWC22 and FANCD2. This data resource identifies host factors proximal to viral proteins in living human cells and nominates pathogenic mechanisms employed by SARS-CoV-2.

Author Summary

SARS-CoV-2 is the latest pathogenic coronavirus to emerge as a public health threat. We create a database of proximal host proteins to 17 SARS-CoV-2 viral proteins. We validate that NSP1 is proximal to the EIF3 translation initiation complex and is a potent inhibitor of translation. We also identify ORF6 antagonism of RNA-mediate innate immune signaling. We produce a database of potential host targets of the viral protease NSP5, and create a fluorescence-based assay to screen cleavage of peptide sequences. We believe that this data will be useful for identifying roles for many of the uncharacterized SARS-CoV-2 proteins and provide insights into the pathogenicity of new or emerging coronaviruses.

Open Science Resources for the Mass Spectrometry-Based Analysis of SARS-CoV-2

The SARS-CoV-2 virus is the causative agent of the 2020 pandemic leading to the COVID-19 respiratory disease. With many scientific and humanitarian efforts ongoing to develop diagnostic tests, vaccines, and treatments for COVID-19, and to prevent the spread of SARS-CoV-2, mass spectrometry research, including proteomics, is playing a role in determining the biology of this viral infection. Proteomics studies are starting to lead to an understanding of the roles of viral and host proteins during SARS-CoV-2 infection, their protein-protein interactions, and post-translational modifications. This is beginning to provide insights into potential therapeutic targets or diagnostic strategies that can be used to reduce the long-term burden of the pandemic. However, the extraordinary situation caused by the global pandemic is also highlighting the need to improve mass spectrometry data and workflow sharing. We therefore describe freely available data and computational resources that can facilitate and assist the mass spectrometry-based analysis of SARS-CoV-2. We exemplify this by reanalyzing a virus-host interactome data set to detect protein-protein interactions and identify host proteins that could potentially be used as targets for drug repurposing.

Phosphorylated tau interactome in the human Alzheimer's disease brain

Accumulation of phosphorylated tau is a key pathological feature of Alzheimer's disease. Phosphorylated tau accumulation causes synaptic impairment, neuronal dysfunction and formation of neurofibrillary tangles. The pathological actions of phosphorylated tau are mediated by surrounding neuronal proteins; however, a comprehensive understanding of the proteins that phosphorylated tau interacts with in Alzheimer's disease is surprisingly limited. Therefore, the aim of this study was to determine the phosphorylated tau interactome. To this end, we used two complementary proteomics approaches: (i) quantitative proteomics was performed on neurofibrillary tangles microdissected from patients with advanced Alzheimer's disease; and (ii) affinity purification-mass spectrometry was used to identify which of these proteins specifically bound to phosphorylated tau. We identified 542 proteins in neurofibrillary tangles. This included the abundant detection of many proteins known to be present in neurofibrillary tangles such as tau, ubiquitin, neurofilament proteins and apolipoprotein E. Affinity purification-mass spectrometry confirmed that 75 proteins present in neurofibrillary tangles interacted with PHF1-immunoreactive phosphorylated tau. Twenty-nine of these proteins have been previously associated with phosphorylated tau, therefore validating our proteomic approach. More importantly, 34 proteins had previously been associated with total tau, but not yet linked directly to phosphorylated tau (e.g. synaptic protein VAMP2, vacuolar-ATPase subunit ATP6V0D1); therefore, we provide new evidence that they directly interact with phosphorylated tau in Alzheimer's disease. In addition, we also identified 12 novel proteins, not previously known to be physiologically or pathologically associated with tau (e.g. RNA binding protein HNRNPA1). Network analysis showed that the phosphorylated tau interactome was enriched in proteins involved in the protein ubiquitination pathway and phagosome maturation. Importantly, we were able to pinpoint specific proteins that phosphorylated tau interacts with in these pathways for the first time, therefore providing novel potential pathogenic mechanisms that can be explored in future studies. Combined, our results reveal new potential drug targets for the treatment of tauopathies and provide insight into how phosphorylated tau mediates its toxicity in Alzheimer's disease.

Protein Interaction Network Biology in Neuroscience

Mapping the intricate networks of cellular proteins in the human brain has the potential to address unsolved questions in molecular neuroscience, including the molecular basis of cognition, synaptic plasticity, long-term potentiation, learning, and memory. Perturbations to the protein-protein interaction networks (PPIN) present in neurons, glia, and other cell-types have been linked to multifactorial neurological disorders. Yet while knowledge of brain PPINs is steadily improving, the complexity and dynamic nature of the heterogeneous central nervous system in normal and disease contexts poses a formidable experimental challenge. In this review, the recent applications of functional proteomics and systems biology approaches to study PPINs central to normal neuronal function, during neurodevelopment, and in neurodegenerative disorders are summarized. How systematic PPIN analysis offers a unique mechanistic framework to explore intra- and inter-cellular functional modules governing neuronal activity and brain function is also discussed. Finally, future technological advancements needed to address outstanding questions facing neuroscience are outlined.

The FUS gene is dual-coding with both proteins contributing to FUS-mediated toxicity

Novel functional coding sequences (altORFs) are camouflaged within annotated ones (CDS) in a different reading frame. We show here that an altORF is nested in the FUS CDS, encoding a conserved 170 amino acid protein, altFUS. AltFUS is endogenously expressed in human tissues, notably in the motor cortex and motor neurons. Over-expression of wild-type FUS and/or amyotrophic lateral sclerosis-linked FUS mutants is known to trigger toxic mechanisms in different models. These include inhibition of autophagy, loss of mitochondrial potential and accumulation of cytoplasmic aggregates. We find that altFUS, not FUS, is responsible for the inhibition of autophagy, and pivotal in mitochondrial potential loss and accumulation of cytoplasmic aggregates. Suppression of altFUS expression in a Drosophila model of FUS-related toxicity protects against neurodegeneration. Some mutations found in ALS patients are overlooked because of their synonymous effect on the FUS protein. Yet, we show they exert a deleterious effect causing missense mutations in the overlapping altFUS protein. These findings demonstrate that FUS is a bicistronic gene and suggests that both proteins, FUS and altFUS, cooperate in toxic mechanisms.

Same but different - Molecular comparison of human KTI12 and PSTK

Kti12 and PSTK are closely related and highly similar proteins implicated in different aspects of tRNA metabolism. Kti12 has been identified as an essential regulatory factor of the Elongator complex, involved in the modification of uridine bases in eukaryotic tRNAs. PSTK phosphorylates the tRNA^Sec-bound amino acid serine, which is required to synthesize selenocysteine. Kti12 and PSTK have previously been studied independently in various organisms, but only appear simultaneously in some animalia, including humans. As Kti12- and PSTK-related pathways are clinically relevant, it is of prime importance to understand their biological functions and mutual relationship in humans. Here, we use different tRNA substrates to directly compare the enzymatic activities of purified human KTI12 and human PSTK proteins. Our complementary Co-IP and BioID2 approaches in human cells confirm that Elongator is the main interaction partner of KTI12 but additionally indicate potential links to proteins involved in vesicular transport, RNA metabolism and deubiquitination. Moreover, we identify and validate a yet uncharacterized interaction between PSTK and γ-taxilin. Foremost, we demonstrate that human KTI12 and PSTK do not share interactors or influence their respective biological functions. Our data provide a comprehensive analysis of the regulatory networks controlling the activity of the human Elongator complex and selenocysteine biosynthesis.

Mass spectrometry-based protein-protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.

System-Wide Profiling of Protein Complexes Via Size Exclusion Chromatography-Mass Spectrometry (SEC-MS)

In living cells, most proteins are organized in stable or transient functional assemblies, protein complexes, which control a multitude of vital cellular processes such as cell cycle progression, metabolism, and signal transduction. Over several decades, specific protein complexes have been analyzed by structural biology methods, initially X-ray crystallography and more recently single particle cryoEM. In parallel, mass spectrometry (MS)-based methods including in vitro affinity-purification coupled to MS or in vivo protein proximity-dependent labeling methods have proven particularly effective to detect complexes, thus nominating new assemblies for structural analysis. Those approaches, however, are either of limited in throughput or require specifically engineered protein systems.In this chapter, we present protocols for a workflow that supports the parallel analysis of multiple complexes from the same biological sample with respect to abundance, subunit composition, and stoichiometry. It consists of the separation of native complexes by size-exclusion chromatography (SEC) and the subsequent mass spectrometric analysis of the proteins in consecutive SEC fractions. In particular, we describe (1) optimized conditions to achieve native protein complex separation by SEC, (2) the preparation of the SEC fractions for MS analysis, (3) the acquisition of the MS data at high throughput via SWATH/DIA (data-independent analysis) mass spectrometry and short chromatographic gradients, and (4) a set of bioinformatic tools for the targeted analysis of protein complexes. Altogether, the parallel measurement of a high number of complexes from a single biological sample results in unprecedented system-level insights into the remodeling of cellular protein complexes in response to perturbations of a broad range of cellular systems.

The axonal sorting activity of pseudorabies virus Us9 protein depends on the state of neuronal maturation

Alpha-herpesviruses establish a life-long infection in the nervous system of the affected host; while this infection is restricted to peripheral neurons in a healthy host, the reactivated virus can spread within the neuronal circuitry, such as to the brain, in compromised individuals and lead to adverse health outcomes. Pseudorabies virus (PRV), an alpha-herpesvirus, requires the viral protein Us9 to sort virus particles into axons and facilitate neuronal spread. Us9 sorts virus particles by mediating the interaction of virus particles with neuronal transport machinery. Here, we report that Us9-mediated regulation of axonal sorting also depends on the state of neuronal maturation. Specifically, the development of dendrites and axons is accompanied with proteomic changes that influence neuronal processes. Immature superior cervical ganglionic neurons (SCGs) have rudimentary neurites that lack markers of mature axons. Immature SCGs can be infected by PRV, but they show markedly reduced Us9-dependent regulation of sorting, and increased Us9-independent transport of particles into neurites. Mature SCGs have relatively higher abundances of proteins characteristic of vesicle-transport machinery. We also identify Us9-associated neuronal proteins that can contribute to axonal sorting and subsequent anterograde spread of virus particles in axons. We show that SMPD4/nsMase3, a sphingomyelinase abundant in lipid-rafts, associates with Us9 and is a negative regulator of PRV sorting into axons and neuronal spread, a potential antiviral function.

Adenoviral protein E4orf4 interacts with the polarity protein Par3 to induce nuclear rupture and tumor cell death

The tumor cell–selective killing activity of the adenovirus type 2 early region 4 ORF4 (E4orf4) protein is poorly defined at the molecular level. Here, we show that the tumoricidal effect of E4orf4 is typified by changes in nuclear dynamics that depend on its interaction with the polarity protein Par3 and actomyosin contractility. Mechanistically, E4orf4 induced a high incidence of nuclear bleb formation and repetitive nuclear ruptures, which promoted nuclear efflux of E4orf4 and loss of nuclear integrity. This process was regulated by nucleocytoskeletal connections, Par3 clustering proximal to nuclear lamina folds, and retrograde movement of actin bundles that correlated with nuclear ruptures. Significantly, Par3 also regulated the incidence of spontaneous nuclear ruptures facilitated by the downmodulation of lamins. This work uncovered a novel role for Par3 in controlling the actin-dependent forces acting on the nuclear envelope to remodel nuclear shape, which might be a defining feature of tumor cells that is harnessed by E4orf4.

SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles

Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state. A record of this paper's transparent peer review process is included in the Supplemental Information.

A Novel Proteomic Method Reveals NLS Tagging of T-DM1 Contravenes Classical Nuclear Transport in a Model of HER2-Positive Breast Cancer

The next breakthrough for protein therapeutics is effective intracellular delivery and accumulation within target cells. Nuclear localization signal (NLS)-tagged therapeutics have been hindered by the lack of efficient nuclear localization due to endosome entrapment. Although development of strategies for tagging therapeutics with technologies capable of increased membrane penetration has resulted in proportional increased potency, nonspecific membrane penetration limits target specificity and, hence, widespread clinical success. There is a long-standing idea that nuclear localization of NLS-tagged agents occurs exclusively via classical nuclear transport. In the present study, we modified the antibody-drug conjugate trastuzumab-emtansine (T-DM1) with a classical NLS linked to cholic acid (cell accumulator [Accum]) that enables modified antibodies to escape endosome entrapment and increase nuclear localization efficiency without abrogating receptor targeting. In parallel, we developed a proteomics-based method to evaluate nuclear transport. Accum-modified T-DM1 significantly enhanced cytotoxic efficacy in the human epidermal growth factor receptor 2 (HER2)-positive SKBR3 breast cancer system. We discovered that efficacy was dependent on the nonclassical importin-7. Our evaluation reveals that when multiple classical NLS tagging occurs, cationic charge build-up as opposed to sequence dominates and becomes a substrate for importin-7. This study results in an effective target cell-specific NLS therapeutic and a general approach to guide future NLS-based development initiatives.

Guanine Nucleotide-Binding Protein-Like 1 (GNL1) binds RNA G-quadruplex structures in genes associated with Parkinson's disease

RNAs are highly regulated at the post-transcriptional level in neurodegenerative diseases and just a few mutations can significantly affect the fate of neuronal cells. To date, the impact of G-quadruplex (G4) regulation in neurodegenerative diseases like Parkinson’s disease (PD) has not been analysed. In this study, in silico potential G4s located in deregulated genes related to the nervous system were initially identified and were found to be significantly enriched. Several G4 sequences found in the 5ʹ untranslated regions (5ʹUTR) of mRNAs associated with Parkinson’s disease were demonstrated to in fact fold in vitro by biochemical assays. Subcloning of the full-length 5ʹUTRs of these candidates upstream of a luciferase reporter system led to the demonstration that the G4s of both Parkin RBR E3 Ubiquitin Protein Ligase (PRKN) and Vacuolar Protein Sorting-Associated Protein 35 (VPS35) significantly repressed the translation of both genes in SH-SY5Y cells. Subsequently, a strategy of using label-free RNA affinity purification assays with either of these two G4 sequences as bait isolated the Guanine Nucleotide-Binding Protein-Like 1 (GNL1). The latter was shown to have a higher affinity for the G4 sequences than for their mutated version. This study sheds light on new RNA G-quadruplexes located in genes dysregulated in Parkinson disease and a new G4-binding protein, GNL1.

The Genetic and Physical Interactomes of the Saccharomyces cerevisiae Hrq1 Helicase

The human genome encodes five RecQ helicases (RECQL1, BLM, WRN, RECQL4, and RECQL5) that participate in various processes underpinning genomic stability. Of these enzymes, the disease-associated RECQL4 is comparatively understudied due to a variety of technical challenges. However, Saccharomyces cerevisiae encodes a functional homolog of RECQL4 called Hrq1, which is more amenable to experimentation and has recently been shown to be involved in DNA inter-strand crosslink (ICL) repair and telomere maintenance. To expand our understanding of Hrq1 and the RecQ4 subfamily of helicases in general, we took a multi-omics approach to define the Hrq1 interactome in yeast. Using synthetic genetic array analysis, we found that mutations of genes involved in processes such as DNA repair, chromosome segregation, and transcription synthetically interact with deletion of HRQ1 and the catalytically inactive hrq1-K318A allele. Pull-down of tagged Hrq1 and mass spectrometry identification of interacting partners similarly underscored links to these processes and others. Focusing on transcription, we found that hrq1 mutant cells are sensitive to caffeine and that mutation of HRQ1 alters the expression levels of hundreds of genes. In the case of hrq1-K318A, several of the most highly upregulated genes encode proteins of unknown function whose expression levels are also increased by DNA ICL damage. Together, our results suggest a heretofore unrecognized role for Hrq1 in transcription, as well as novel members of the Hrq1 ICL repair pathway. These data expand our understanding of RecQ4 subfamily helicase biology and help to explain why mutations in human RECQL4 cause diseases of genomic instability.

A Novel Proximity Biotinylation Assay Based on the Self-Associating Split GFP1-10/11

Proximity biotinylation was developed to detect physiologically relevant protein–protein interactions in living cells. In this method, the protein of interest is tagged with a promiscuous biotin ligase, such as BioID or BioID2, which produces activated biotin that reacts with nearby proteins; these proteins can subsequently be purified and identified by mass spectrometry. Here we report a novel modification of this technique by combining it with a self-associating split-GFP system in which we exploit the high-affinity interaction between GFP1–10 and GFP11 to recruit BioID2 to the protein of interest. As a test case, we fused GFP11 to clathrin light chain (CLTB) and BioID2 to GFP1–10. Co-expression of GFP11-CLTB and BioID2-GFP1–10 yielded a green fluorescent complex that co-localized with clathrin heavy chain. To facilitate removal of non-specifically biotinylated proteins, we generated an inducible cell line expressing BioID2-GFP1–10. Proximity biotinylation in this cell line with GFP11-CLTB yielded a higher percentage of biologically relevant interactions than direct fusion of BioID2 to CLTB. Thus, this system can be used to monitor expression and localization of BioID bait proteins and to identify protein–protein interactions.

Protein interactome of the Cancerous Inhibitor of protein phosphatase 2A (CIP2A) in Th17 cells

Cancerous inhibitor of protein phosphatase 2A (CIP2A) is involved in immune response, cancer progression, and Alzheimer's disease. However, an understanding of the mechanistic basis of its function in this wide spectrum of physiological and pathological processes is limited due to its poorly characterized interaction networks. Here we present the first systematic characterization of the CIP2A interactome by affinity-purification mass spectrometry combined with validation by selected reaction monitoring targeted mass spectrometry (SRM-MS) analysis in T helper (Th) 17 (Th17) cells. In addition to the known regulatory subunits of protein phosphatase 2A (PP2A), the catalytic subunits of protein PP2A were found to be interacting with CIP2A. Furthermore, the regulatory (PPP1R18, and PPP1R12A) and catalytic (PPP1CA) subunits of phosphatase PP1 were identified among the top novel CIP2A interactors. Evaluation of the ontologies associated with the proteins in this interactome revealed that they were linked with RNA metabolic processing and splicing, protein traffic, cytoskeleton regulation and ubiquitin-mediated protein degradation processes. Taken together, this network of protein-protein interactions will be important for understanding and further exploring the biological processes and mechanisms regulated by CIP2A both in physiological and pathological conditions.

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The first characterisation of the CIP2A interactome in Th17 ​cells.

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Key interactions validated by targeted SRM-MS proteomics, western blot and confocal microscopy.

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Pathway analysis of the interactome revealed interrelationships with proteins across a broad range of cellular processes.

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The study identifies for the first time the interaction of phosphatase PP1 with CIP2A.

Proximal Protein Interaction Landscape of RAS Paralogs

Simple Summary

RAS paralogs (HRAS, NRAS and KRAS) are of major interest in biology because they are involved in developmental disorders (e.g., Costello and Noonan syndromes) and in a broad variety of human neoplasia. Many research groups have devoted tremendous efforts to deepen our understanding of the RAS proteins functions and regulations, notably through identifying their functional protein partners. However, while most of these studies were focused on pathogenic RAS mutants, much less research has been dedicated to deciphering the normal activities of RAS paralogs. However, such characterization appears as a prerequisite to clearly identify pathogenic features. We delineated and compared the wild type RAS paralogs proximal interactomes. We detected more than 800 RAS high confident proximal interactors, either shared between paralogs or unique, and validated a subset of data through proximity ligation assays-based validation. Our results describe differential interactors enrichment between RAS paralogs and uncover novel ties between RAS signaling and cellular metabolism. We believe that our findings will support further studies aiming at better understanding how RAS paralogs could be differentially involved in discrete cellular processes and could serve as a basis to template oncogenic mechanism investigations.

Abstract

RAS proteins (KRAS, NRAS and HRAS) are frequently activated in different cancer types (e.g., non-small cell lung cancer, colorectal cancer, melanoma and bladder cancer). For many years, their activities were considered redundant due to their high degree of sequence homology (80% identity) and their shared upstream and downstream protein partners. However, the high conservation of the Hyper-Variable-Region across mammalian species, the preferential activation of different RAS proteins in specific tumor types and the specific post-translational modifications and plasma membrane-localization of each paralog suggest they could ensure discrete functions. To gain insights into RAS proteins specificities, we explored their proximal protein–protein interaction landscapes using the proximity-dependent biotin identification technology (BioID) in Flp-In T-REx 293 cell lines stably transfected and inducibly expressing wild type KRAS4B, NRAS or HRAS. We identified more than 800 high-confidence proximal interactors, allowing us to propose an unprecedented comparative analysis of wild type RAS paralogs protein networks. These data bring novel information on poorly characterized RAS functions, e.g., its putative involvement in metabolic pathways, and on shared as well as paralog-specific protein networks that could partially explain the complexity of RAS functions. These networks of protein interactions open numerous avenues to better understand RAS paralogs biological activities.

Computational Identification of Human Biological Processes and Protein Sequence Motifs Putatively Targeted by SARS-CoV-2 Proteins Using Protein-Protein Interaction Networks

While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK 293 cells published by Gordon et al. (Nature2020, 583, 459-468) to reveal processes that are potentially affected by the virus and putative protein binding sites. Specifically, we performed a set of network-based functional and sequence motif enrichment analyses on SARS-CoV-2-interacting human proteins and on PPI networks generated by supplementing viral-host PPIs with known interactions. Using a novel implementation of our GoNet algorithm, we identified 329 Gene Ontology terms for which the SARS-CoV-2-interacting human proteins are significantly clustered in PPI networks. Furthermore, we present a novel protein sequence motif discovery approach, LESMoN-Pro, that identified 9 amino acid motifs for which the associated proteins are clustered in PPI networks. Together, these results provide insights into the processes and sequence motifs that are putatively implicated in SARS-CoV-2 infection and could lead to potential therapeutic targets.

Nucleotide Binding, Evolutionary Insights, and Interaction Partners of the Pseudokinase Unc-51-like Kinase 4

Unc-51-like kinase 4 (ULK4) is a pseudokinase that has been linked to the development of several diseases. Even though sequence motifs required for ATP binding in kinases are lacking, ULK4 still tightly binds ATP and the presence of the co-factor is required for structural stability of ULK4. Here, we present a high-resolution structure of a ULK4-ATPγS complex revealing a highly unusual ATP binding mode in which the lack of the canonical VAIK motif lysine is compensated by K39, located N-terminal to αC. Evolutionary analysis suggests that degradation of active site motifs in metazoan ULK4 has co-occurred with an ULK4-specific activation loop, which stabilizes the C helix. In addition, cellular interaction studies using BioID and biochemical validation data revealed high confidence interactors of the pseudokinase and armadillo repeat domains. Many of the identified ULK4 interaction partners were centrosomal and tubulin-associated proteins and several active kinases suggesting interesting regulatory roles for ULK4.

The adenoviral protein E4orf4: a probing tool to decipher mechanical stress-induced nuclear envelope remodeling in tumor cells

The human adenovirus (Ad) type 2/5 early region 4 (E4) ORF4 protein (E4orf4) exerts a remarkable tumor cell-selective killing activity in mammalian cells. This indicates that E4orf4 can target tumor cell-defining features and is a unique tool to probe cancer cell vulnerabilities. Recently, we found that E4orf4, through an interaction with the polarity protein PAR3, subverts nuclear envelope (NE) remodeling processes in a tumor cell-selective manner. In this Perspective, we outline mechanical signals that modify nuclear dynamics and tumor cell behavior to highlight potential mechanisms for E4orf4's tumoricidal activity. Through an analysis of E4orf4's cellular targets, we define a protein subnetwork that comprises phosphatase systems interconnected to polarity protein hubs, which could contribute to enhanced NE plasticity. We infer that elucidating E4orf4's protein network at a functional level could uncover key mechanisms of NE remodeling that define the tumor cell phenotype.

RNA aptamer capture of macromolecular complexes for mass spectrometry analysis

Specific genomic functions are dictated by macromolecular complexes (MCs) containing multiple proteins. Affinity purification of these complexes, often using antibodies, followed by mass spectrometry (MS) has revolutionized our ability to identify the composition of MCs. However, conventional immunoprecipitations suffer from contaminating antibody/serum-derived peptides that limit the sensitivity of detection for low-abundant interacting partners using MS. Here, we present AptA-MS (aptamer affinity-mass spectrometry), a robust strategy primarily using a specific, high-affinity RNA aptamer against Green Fluorescent Protein (GFP) to identify interactors of a GFP-tagged protein of interest by high-resolution MS. Utilizing this approach, we have identified the known molecular chaperones that interact with human Heat Shock Factor 1 (HSF1), and observed an increased association with several proteins upon heat shock, including translation elongation factors and histones. HSF1 is known to be regulated by multiple post-translational modifications (PTMs), and we observe both known and new sites of modifications on HSF1. We show that AptA-MS provides a dramatic target enrichment and detection sensitivity in evolutionarily diverse organisms and allows identification of PTMs without the need for modification-specific enrichments. In combination with the expanding libraries of GFP-tagged cell lines, this strategy offers a general, inexpensive, and high-resolution alternative to conventional approaches for studying MCs.

Kir2.1 Interactome Mapping Uncovers PKP4 as a Modulator of the Kir2.1-Regulated Inward Rectifier Potassium Currents

Kir2.1, a strong inward rectifier potassium channel encoded by the KCNJ2 gene, is a key regulator of the resting membrane potential of the cardiomyocyte and plays an important role in controlling ventricular excitation and action potential duration in the human heart. Mutations in KCNJ2 result in inheritable cardiac diseases in humans, e.g. the type-1 Andersen-Tawil syndrome (ATS1). Understanding the molecular mechanisms that govern the regulation of inward rectifier potassium currents by Kir2.1 in both normal and disease contexts should help uncover novel targets for therapeutic intervention in ATS1 and other Kir2.1-associated channelopathies. The information available to date on protein-protein interactions involving Kir2.1 channels remains limited. Additional efforts are necessary to provide a comprehensive map of the Kir2.1 interactome. Here we describe the generation of a comprehensive map of the Kir2.1 interactome using the proximity-labeling approach BioID. Most of the 218 high-confidence Kir2.1 channel interactions we identified are novel and encompass various molecular mechanisms of Kir2.1 function, ranging from intracellular trafficking to cross-talk with the insulin-like growth factor receptor signaling pathway, as well as lysosomal degradation. Our map also explores the variations in the interactome profiles of Kir2.1WTversus Kir2.1Δ314-315, a trafficking deficient ATS1 mutant, thus uncovering molecular mechanisms whose malfunctions may underlie ATS1 disease. Finally, using patch-clamp analysis, we validate the functional relevance of PKP4, one of our top BioID interactors, to the modulation of Kir2.1-controlled inward rectifier potassium currents. Our results validate the power of our BioID approach in identifying functionally relevant Kir2.1 interactors and underline the value of our Kir2.1 interactome as a repository for numerous novel biological hypotheses on Kir2.1 and Kir2.1-associated diseases.

Multiplexed Proximity Biotinylation Coupled to Mass Spectrometry for Defining Integrin Adhesion Complexes

BioID, a proximity biotinylation technique, offers a valuable approach to examine the interactions occurring within protein complexes that complements traditional protein biochemical methods. BioID has various advantages that are beneficial to the study of complexes, including an ability to detect insoluble and transient proteins. We have applied BioID to the study of integrin adhesion complexes (IACs), which are located at the junction between the plasma membrane and actin cytoskeleton. The use of multiple BioID baits enables a complex-wide, spatial annotation of IACs, which in turn facilitates the detection of novel proximal interactors and provides insights into IAC architecture. This article describes the labeling and affinity purification of IAC-proximal proteins and their analysis by label-free quantitative mass spectrometry. The article also outlines steps to identify high-confidence proximity interactors, and to interrogate the topology and functional relevance of proximity interaction networks through bioinformatic analyses. © 2020 The Authors. Basic Protocol 1: Proximity biotinylation of integrin adhesion complex components Basic Protocol 2: Mass spectrometry data processing by MaxQuant and detection of high-confidence proximal interactors Basic Protocol 3: Bioinformatic analysis and data visualization.

Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant

Ion mobility brings an additional dimension of separation to LC-MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (∼30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (∼10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis.

Mycobacterium tuberculosis Rv0991c Is a Redox-Regulated Molecular Chaperone

M. tuberculosis infections are responsible for more than 1 million deaths per year. Developing effective strategies to combat this disease requires a greater understanding of M. tuberculosis biology. As in all cells, protein quality control is essential for the viability of M. tuberculosis, which likely faces proteotoxic stress within a host. Here, we identify an M. tuberculosis protein, Ruc, that gains chaperone activity upon oxidation. Ruc represents a previously unrecognized family of redox-regulated chaperones found throughout the bacterial superkingdom. Additionally, we found that oxidized Ruc promotes the protein-folding activity of the essential M. tuberculosis Hsp70 chaperone system. This work contributes to a growing body of evidence that oxidative stress provides a particular strain on cellular protein stability.

The bacterial pathogen Mycobacterium tuberculosis is the leading cause of death by an infectious disease among humans. Here, we describe a previously uncharacterized M. tuberculosis protein, Rv0991c, as a molecular chaperone that is activated by oxidation. Rv0991c has homologs in most bacterial lineages and appears to function analogously to the well-characterized Escherichia coli redox-regulated chaperone Hsp33, despite a dissimilar protein sequence. Rv0991c is transcriptionally coregulated with hsp60 and hsp70 chaperone genes in M. tuberculosis, suggesting that Rv0991c functions with these chaperones in maintaining protein quality control. Supporting this hypothesis, we found that, like oxidized Hsp33, oxidized Rv0991c prevents the aggregation of a model unfolded protein in vitro and promotes its refolding by the M. tuberculosis Hsp70 chaperone system. Furthermore, Rv0991c interacts with DnaK and can associate with many other M. tuberculosis proteins. We therefore propose that Rv0991c, which we named “Ruc” (redox-regulated protein with unstructured C terminus), represents a founding member of a new chaperone family that protects M. tuberculosis and other species from proteotoxicity during oxidative stress.

Structure of the essential inner membrane lipopolysaccharide-PbgA complex

Lipopolysaccharide (LPS) resides in the outer membrane of Gram-negative bacteria where it is responsible for barrier function^1,2. LPS can cause death as a result of septic shock, and its lipid A core is the target of polymyxin antibiotics^3,4. Despite the clinical importance of polymyxins and the emergence of multidrug resistant strains⁵, our understanding of the bacterial factors that regulate LPS biogenesis is incomplete. Here we characterize the inner membrane protein PbgA and report that its depletion attenuates the virulence of Escherichia coli by reducing levels of LPS and outer membrane integrity. In contrast to previous claims that PbgA functions as a cardiolipin transporter^6-9, our structural analyses and physiological studies identify a lipid A-binding motif along the periplasmic leaflet of the inner membrane. Synthetic PbgA-derived peptides selectively bind to LPS in vitro and inhibit the growth of diverse Gram-negative bacteria, including polymyxin-resistant strains. Proteomic, genetic and pharmacological experiments uncover a model in which direct periplasmic sensing of LPS by PbgA coordinates the biosynthesis of lipid A by regulating the stability of LpxC, a key cytoplasmic biosynthetic enzyme^10-12. In summary, we find that PbgA has an unexpected but essential role in the regulation of LPS biogenesis, presents a new structural basis for the selective recognition of lipids, and provides opportunities for future antibiotic discovery.

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

Affinity purification coupled with mass spectrometry (AP-MS) and proximity-dependent biotinylation identification (BioID) methods have made substantial contributions to interaction proteomics studies. Whereas AP-MS results in the identification of proteins that are in a stable complex, BioID labels and identifies proteins that are in close proximity to the bait, resulting in overlapping yet distinct protein identifications. Integration of AP-MS and BioID data has been shown to comprehensively characterize a protein's molecular context, but interactome analysis using both methods in parallel is still labor and resource intense with respect to cell line generation and protein purification. Therefore, we developed the Multiple Approaches Combined (MAC)-tag workflow, which allows for both AP-MS and BioID analysis with a single construct and with almost identical protein purification and mass spectrometry (MS) identification procedures. We have applied the MAC-tag workflow to a selection of subcellular markers to provide a global view of the cellular protein interactome landscape. This localization database is accessible via our online platform ( http://proteomics.fi ) to predict the cellular localization of a protein of interest (POI) depending on its identified interactors. In this protocol, we present the detailed three-stage procedure for the MAC-tag workflow: (1) cell line generation for the MAC-tagged POI; (2) parallel AP-MS and BioID protein purification followed by MS analysis; and (3) protein interaction data analysis, data filtration and visualization with our localization visualization platform. The entire procedure can be completed within 25 d.

The Zika Virus Capsid Disrupts Corticogenesis by Suppressing Dicer Activity and miRNA Biogenesis

Zika virus (ZIKV) causes microcephaly and disrupts neurogenesis. Dicer-mediated miRNA biogenesis is required for embryonic brain development and has been suggested to be disrupted upon ZIKV infection. Here we mapped the ZIKV-host interactome in neural stem cells (NSCs) and found that Dicer is specifically targeted by the capsid from ZIKV, but not other flaviviruses, to facilitate ZIKV infection. We identified a capsid mutant (H41R) that loses this interaction and does not suppress Dicer activity. Consistently, ZIKV-H41R is less virulent and does not inhibit neurogenesis in vitro or corticogenesis in utero. Epidemic ZIKV strains contain capsid mutations that increase Dicer binding affinity and enhance pathogenicity. ZIKV-infected NSCs show global dampening of miRNA production, including key miRNAs linked to neurogenesis, which is not observed after ZIKV-H41R infection. Together these findings show that capsid-dependent suppression of Dicer is a major determinant of ZIKV immune evasion and pathogenesis and may underlie ZIKV-related microcephaly.

Variability in Streptavidin-Sepharose Matrix Quality Can Significantly Affect Proximity-Dependent Biotinylation (BioID) Data

Due to their ease of use and high binding affinity, streptavidin-based purification tools have become widely used for isolating biotinylated compounds from complex mixtures. We and others routinely use streptavidin-sepharose matrices to isolate biotinylated polypeptides generated in proximity-dependent biotinylation approaches, such as BioID or APEX. However, we noted sporadic, substantial variation in the quality of BioID experiments performed in the same laboratories over time, using seemingly identical protocols. Identifying the source of this problem, here, we highlight considerable variability in streptavidin contamination derived from different production lots of streptavidin-sepharose beads from the same manufacturer and demonstrate that high levels of streptavidin peptide contamination can have detrimental effects on BioID data. We also describe two simple, rapid approaches to assess the degree of streptavidin "shedding" from individual lots of the sepharose matrix before use to avoid the use of lower quality reagent.

TBL1XR1 Mutations Drive Extranodal Lymphoma by Inducing a Pro-tumorigenic Memory Fate

The most aggressive B cell lymphomas frequently manifest extranodal distribution and carry somatic mutations in the poorly characterized gene TBL1XR1. Here, we show that TBL1XR1 mutations skew the humoral immune response toward generating abnormal immature memory B cells (MB), while impairing plasma cell differentiation. At the molecular level, TBL1XR1 mutants co-opt SMRT/HDAC3 repressor complexes toward binding the MB cell transcription factor (TF) BACH2 at the expense of the germinal center (GC) TF BCL6, leading to pre-memory transcriptional reprogramming and cell-fate bias. Upon antigen recall, TBL1XR1 mutant MB cells fail to differentiate into plasma cells and instead preferentially reenter new GC reactions, providing evidence for a cyclic reentry lymphomagenesis mechanism. Ultimately, TBL1XR1 alterations lead to a striking extranodal immunoblastic lymphoma phenotype that mimics the human disease. Both human and murine lymphomas feature expanded MB-like cell populations, consistent with a MB-cell origin and delineating an unforeseen pathway for malignant transformation of the immune system.

Global Interactome Mapping of Mitochondrial Intermembrane Space Proteases Identifies a Novel Function for HTRA2

A number of unique proteases localize to specific sub-compartments of the mitochondria, but the functions of these enzymes are poorly defined. Here, in vivo proximity-dependent biotinylation (BioID) is used to map the interactomes of seven proteases localized to the mitochondrial intermembrane space (IMS). In total, 802 high confidence proximity interactions with 342 unique proteins are identified. While all seven proteases co-localized with the IMS markers OPA1 and CLPB, 230 of the interacting partners are unique to just one or two protease bait proteins, highlighting the ability of BioID to differentiate unique interactomes within the confined space of the IMS. Notably, high-temperature requirement peptidase 2 (HTRA2) interacts with eight of 13 components of the mitochondrial intermembrane space bridging (MIB) complex, a multiprotein assembly essential for the maintenance of mitochondrial cristae structure. Knockdown of HTRA2 disrupts cristae in HEK 293 and OCI-AML2 cells, and leads to increased intracellular levels of the MIB subunit IMMT. Using a cell-free assay it is demonstrated that HTRA2 can degrade recombinant IMMT but not two other core MIB complex subunits, SAMM50 and CHCHD3. The IMS protease interactome thus represents a rich dataset that can be mined to uncover novel IMS protease biology.

FKBP5 Regulates RIG-I-Mediated NF-κB Activation and Influenza A Virus Infection

Influenza A virus (IAV) is a highly transmissible respiratory pathogen and is a constant threat to global health with considerable economic and social impact. Influenza viral RNA is sensed by host pattern recognition receptors (PRRs), such as the Toll-like receptor 7 (TLR7) and retinoic acid-inducible gene I (RIG-I). The activation of these PRRs instigates the interferon regulatory factor (IRF) and nuclear factor kappa B (NF-κB) signaling pathways that induce the expression of interferon-stimulated genes (ISGs) and inflammatory genes. FK506-binding protein 5 (FKBP5) has been implied in the IκBα kinase (IKK) complex. However, the role of FKBP5 in the RIG-I signaling and IAV infection is not well elucidated. Here, we demonstrate that the knockout of FKBP5 increases IAV infection. Furthermore, FKBP5 binds IKKα, which is critical for RIG-I-induced innate immune responses and ISG expression. Taken together, FKBP5 is a novel anti-influenza host factor that restricts IAV infection by the activation of RIG-I-mediated NF-κB signaling.

Chromatin-Bound Proteome Profiling by Genome Capture

De novo identification of chromatin interactors can reveal unexpected pathways relevant to physiology and human disease. Inspired by the DNA mediated chromatin pull-down (Dm-ChP) technology (also known as iPOND [isolation of proteins on nascent DNA]) for the proteomic characterization of nascent DNA, we have recently reported a new experimental protocol that allows for the identification of proteins on total DNA (iPOTD) for bulk chromatome profiling and de novo identification of chromatin-bound proteins. Here, we detail a step-by-step protocol to survey the cellular chromatin-bound proteome in a simple, robust, and unbiased manner. For complete details on the use and execution of this protocol, please refer to Aranda et al. (2019).

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

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

Genome-Wide CRISPR-Cas9 Screens Expose Genetic Vulnerabilities and Mechanisms of Temozolomide Sensitivity in Glioblastoma Stem Cells

Glioblastoma therapies have remained elusive due to limitations in understanding mechanisms of growth and survival of the tumorigenic population. Using CRISPR-Cas9 approaches in patient-derived GBM stem cells (GSCs) to interrogate function of the coding genome, we identify actionable pathways responsible for growth, which reveal the gene-essential circuitry of GBM stemness and proliferation. In particular, we characterize members of the SOX transcription factor family, SOCS3, USP8, and DOT1L, and protein ufmylation as important for GSC growth. Additionally, we reveal mechanisms of temozolomide resistance that could lead to combination strategies. By reaching beyond static genome analysis of bulk tumors, with a genome-wide functional approach, we reveal genetic dependencies within a broad range of biological processes to provide increased understanding of GBM growth and treatment resistance.

Probing Protein Interaction Networks by Combining MS-Based Proteomics and Structural Data Integration

Protein-protein interactions play a major role in the molecular machinery of life, and various techniques such as AP-MS are dedicated to their identification. However, those techniques return lists of proteins devoid of organizational structure, not detailing which proteins interact with which others. Proposing a hierarchical view of the interactions between the members of the flat list becomes highly tedious for large data sets when done by hand. To help hierarchize this data, we introduce a new bioinformatics protocol that integrates information of the multimeric protein 3D structures available in the Protein Data Bank using remote homology detection, as well as information related to Short Linear Motifs and interaction data from the BioGRID. We illustrate on two unrelated use-cases of different complexity how our approach can be useful to decipher the network of interactions hidden in the list of input proteins, and how it provides added value compared to state-of-the-art resources such as Interactome3D or STRING. Particularly, we show the added value of using homology detection to distinguish between orthologs and paralogs, and to distinguish between core obligate and more facultative interactions. We also demonstrate the potential of considering interactions occurring through Short Linear Motifs.

Non-proteolytic ubiquitination of OTULIN regulates NF-κB signaling pathway

NF-κB signaling regulates diverse processes such as cell death, inflammation, immunity, and cancer. The activity of NF-κB is controlled by methionine 1-linked linear polyubiquitin, which is assembled by the linear ubiquitin chain assembly complex (LUBAC) and the ubiquitin-conjugating enzyme UBE2L3. Recent studies found that the deubiquitinase OTULIN breaks the linear ubiquitin chain, thus inhibiting NF-κB signaling. Despite the essential role of OTULIN in NF-κB signaling has been established, the regulatory mechanism for OTULIN is not well elucidated. To discover the potential regulators of OTULIN, we analyzed the OTULIN protein complex by proteomics and revealed several OTULIN-binding proteins, including LUBAC and tripartite motif-containing protein 32 (TRIM32). TRIM32 is known to activate NF-κB signaling, but the mechanism is not clear. Genetic complement experiments found that TRIM32 is upstream of OTULIN and TRIM32-mediated NF-κB activation is dependent on OTULIN. Mutagenesis of the E3 ligase domain showed that the E3 ligase activity is essential for TRIM32-mediated NF-κB activation. Further experiments found that TRIM32 conjugates polyubiquitin onto OTULIN and the polyubiquitin blocks the interaction between HOIP and OTULIN, thereby activating NF-κB signaling. Taken together, we report a novel regulatory mechanism by which TRIM32-mediated non-proteolytic ubiquitination of OTULIN impedes the access of OTULIN to the LUBAC and promotes NF-κB activation.

Emerging proteomic approaches to identify the underlying pathophysiology of neurodevelopmental and neurodegenerative disorders

Proteomics is the large-scale study of the total protein content and their overall function within a cell through multiple facets of research. Advancements in proteomic methods have moved past the simple quantification of proteins to the identification of post-translational modifications (PTMs) and the ability to probe interactions between these proteins, spatially and temporally. Increased sensitivity and resolution of mass spectrometers and sample preparation protocols have drastically reduced the large amount of cells required and the experimental variability that had previously hindered its use in studying human neurological disorders. Proteomics offers a new perspective to study the altered molecular pathways and networks that are associated with autism spectrum disorders (ASD). The differences between the transcriptome and proteome, combined with the various types of post-translation modifications that regulate protein function and localization, highlight a novel level of research that has not been appropriately investigated. In this review, we will discuss strategies using proteomics to study ASD and other neurological disorders, with a focus on how these approaches can be combined with induced pluripotent stem cell (iPSC) studies. Proteomic analysis of iPSC-derived neurons have already been used to measure changes in the proteome caused by patient mutations, analyze changes in PTMs that resulted in altered biological pathways, and identify potential biomarkers. Further advancements in both proteomic techniques and human iPSC differentiation protocols will continue to push the field towards better understanding ASD disease pathophysiology. Proteomics using iPSC-derived neurons from individuals with ASD offers a window for observing the altered proteome, which is necessary in the future development of therapeutics against specific targets.

The SHCA adapter protein cooperates with lipoma-preferred partner in the regulation of adhesion dynamics and invadopodia formation

SHC adaptor protein (SHCA) and lipoma-preferred partner (LPP) mediate transforming growth factor β (TGFβ)-induced breast cancer cell migration and invasion. Reduced expression of either protein diminishes breast cancer lung metastasis, but the reason for this effect is unclear. Here, using total internal reflection fluorescence (TIRF) microscopy, we found that TGFβ enhanced the assembly and disassembly rates of paxillin-containing adhesions in an SHCA-dependent manner through the phosphorylation of the specific SHCA tyrosine residues Tyr-239, Tyr-240, and Tyr-313. Using a BioID proximity labeling approach, we show that SHCA exists in a complex with a variety of actin cytoskeletal proteins, including paxillin and LPP. Consistent with a functional interaction between SHCA and LPP, TGFβ-induced LPP localization to cellular adhesions depended on SHCA. Once localized to the adhesions, LPP was required for TGFβ-induced increases in cell migration and adhesion dynamics. Mutations that impaired LPP localization to adhesions (mLIM1) or impeded interactions with the actin cytoskeleton via α-actinin (ΔABD) abrogated migratory responses to TGFβ. Live-cell TIRF microscopy revealed that SHCA clustering at the cell membrane preceded LPP recruitment. We therefore hypothesize that, in the presence of TGFβ, SHCA promotes the formation of small, dynamic adhesions by acting as a nucleator of focal complex formation. Finally, we defined a previously unknown function for SHCA in the formation of invadopodia, a process that also required LPP. Our results reveal that SHCA controls the formation and function of adhesions and invadopodia, two key cellular structures required for breast cancer metastasis.

Diversity in Aβ deposit morphology and secondary proteome insolubility across models of Alzheimer-type amyloidosis

A hallmark pathology of Alzheimer's disease (AD) is the formation of amyloid β (Aβ) deposits that exhibit diverse localization and morphologies, ranging from diffuse to cored-neuritic deposits in brain parenchyma, with cerebral vascular deposition in leptomeningeal and parenchymal compartments. Most AD brains exhibit the full spectrum of pathologic Aβ morphologies. In the course of studies to model AD amyloidosis, we have generated multiple transgenic mouse models that vary in the nature of the transgene constructs that are expressed; including the species origin of Aβ peptides, the levels and length of Aβ that is deposited, and whether mutant presenilin 1 (PS1) is co-expressed. These models recapitulate features of human AD amyloidosis, but interestingly some models can produce pathology in which one type of Aβ morphology dominates. In prior studies of mice that primarily develop cored-neuritic deposits, we determined that Aβ deposition is associated with changes in cytosolic protein solubility in which a subset of proteins become detergent-insoluble, indicative of secondary proteome instability. Here, we survey changes in cytosolic protein solubility across seven different transgenic mouse models that exhibit a range of Aβ deposit morphologies. We find a surprisingly diverse range of changes in proteome solubility across these models. Mice that deposit human Aβ40 and Aβ42 in cored-neuritic plaques had the most robust changes in proteome solubility. Insoluble cytosolic proteins were also detected in the brains of mice that develop diffuse Aβ42 deposits but to a lesser extent. Notably, mice with cored deposits containing only Aβ42 had relatively few proteins that became detergent-insoluble. Our data provide new insight into the diversity of biological effects that can be attributed to different types of Aβ pathology and support the view that fibrillar cored-neuritic plaque pathology is the more disruptive Aβ pathology in the Alzheimer's cascade.

Methods of Computational Interactomics for Investigating Interactions of Human Proteoforms

Human genome contains ca. 20,000 protein-coding genes that could be translated into millions of unique protein species (proteoforms). Proteoforms coded by a single gene often have different functions, which implies different protein partners. By interacting with each other, proteoforms create a network reflecting the dynamics of cellular processes in an organism. Perturbations of protein-protein interactions change the network topology, which often triggers pathological processes. Studying proteoforms is a relatively new research area in proteomics, and this is why there are comparatively few experimental studies on the interaction of proteoforms. Bioinformatics tools can facilitate such studies by providing valuable complementary information to the experimental data and, in particular, expanding the possibilities of the studies of proteoform interactions.

Systems analysis of RhoGEF and RhoGAP regulatory proteins reveals spatially organized RAC1 signalling from integrin adhesions

Rho GTPases are central regulators of the cytoskeleton and, in humans, are controlled by 145 multidomain guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs). How Rho signalling patterns are established in dynamic cell spaces to control cellular morphogenesis is unclear. Through a family-wide characterization of substrate specificities, interactomes and localization, we reveal at the systems level how RhoGEFs and RhoGAPs contextualize and spatiotemporally control Rho signalling. These proteins are widely autoinhibited to allow local regulation, form complexes to jointly coordinate their networks and provide positional information for signalling. RhoGAPs are more promiscuous than RhoGEFs to confine Rho activity gradients. Our resource enabled us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling CDC42-RHOA crosstalk. Moreover, we show that integrin adhesions spatially segregate GEFs and GAPs to shape RAC1 activity zones in response to mechanical cues. This mechanism controls the protrusion and contraction dynamics fundamental to cell motility. Our systems analysis of Rho regulators is key to revealing emergent organization principles of Rho signalling.

Polypharmacological Perturbation of the 14-3-3 Adaptor Protein Interactome Stimulates Neurite Outgrowth

Targeting protein-protein interactions (PPIs) is a promising approach in the development of drugs for many indications. 14-3-3 proteins are a family of phosphoprotein-binding molecules with critical functions in dozens of cell signaling networks. 14-3-3s are abundant in the central nervous system, and the small molecule fusicoccin-A (FC-A), a tool compound that can be used to manipulate 14-3-3 PPIs, enhances neurite outgrowth in cultured neurons. New semisynthetic FC-A derivatives with improved binding affinity for 14-3-3 complexes have recently been developed. Here, we use a series of screens that identify these compounds as potent inducers of neurite outgrowth through a polypharmacological mechanism. Using proteomics and X-ray crystallography, we discover that these compounds extensively regulate the 14-3-3 interactome by stabilizing specific PPIs, while disrupting others. These results provide new insights into the development of drugs to target 14-3-3 PPIs, a potential therapeutic strategy for CNS diseases.

Bait Correlation Improves Interactor Identification by Tandem Mass Tag-Affinity Purification-Mass Spectrometry

The quantitative multiplexing capacity of isobaric tandem mass tags (TMT) has increased the throughput of affinity purification mass spectrometry (AP-MS) to characterize protein interaction networks of immunoprecipitated bait proteins. However, variable bait levels between replicates can convolute interactor identification. We compared the Student's t-test and Pearson's R correlation as methods to generate t-statistics and assessed the significance of interactors following TMT-AP-MS. Using a simple linear model of protein recovery in immunoprecipitates to simulate reporter ion ratio distributions, we found that correlation-derived t-statistics protect against bait variance while robustly controlling type I errors (false positives). We experimentally determined the performance of these two approaches for determining t-statistics under two experimental conditions: irreversible prey association to the Hsp40 mutant DNAJB8^H31Q followed by stringent washing, and reversible association to 14-3-3ζ with gentle washing. Correlation-derived t-statistics performed at least as well as Student's t-statistics for each sample and with substantial improvement in performance for experiments with high bait-level variance. Deliberately varying bait levels over a large range fails to improve selectivity but does increase the robustness between runs. The use of correlation-derived t-statistics should improve identification of interactors using TMT-AP-MS. Data are available via ProteomeXchange with identifier PXD016613.