Preventing Inappropriate Signals Pre- and Post-Ligand Perception by a Toggle-Switch Mechanism of ERECTA.

Dynamic control of signaling events requires swift regulation of receptors at an active state. By focusing on Arabidopsis ERECTA (ER) receptor kinase, which perceives peptide ligands to control multiple developmental processes, we report a mechanism preventing inappropriate receptor activity. The ER C-terminal tail (ER_CT) functions as an autoinhibitory domain: its removal confers higher kinase activity and hyperactivity during inflorescence and stomatal development. ER_CT is required for the binding of a receptor kinase inhibitor, BKI1, and two U-box E3 ligases PUB30 and PUB31 that inactivate activated ER. We further identify ER_CT as a phosphodomain transphosphorylated by the co-receptor BAK1. The phosphorylation impacts the tail structure, likely releasing from autoinhibition. The phosphonull version enhances BKI1 association, whereas the phosphomimetic version promotes PUB30/31 association. Thus, ER_CT acts as an off-on-off toggle switch, facilitating the release of BKI1 inhibition, enabling signal activation, and swiftly turning over the receptors afterwards. Our results elucidate a mechanism fine-tuning receptor signaling via a phosphoswitch module, keeping the receptor at a low basal state and ensuring the robust yet transient activation upon ligand perception.

CRISPR-Cas9 screen of E3 ubiquitin ligases identifies TRAF2 and UHRF1 as regulators of HIV latency in primary human T cells.

During HIV infection of CD4+ T cells, ubiquitin pathways are essential to viral replication and host innate immune response; however, the role of specific E3 ubiquitin ligases is not well understood. Proteomics analyses identified 116 single-subunit E3 ubiquitin ligases expressed in activated primary human CD4+ T cells. Using a CRISPR-based arrayed spreading infectivity assay, we systematically knocked out 116 E3s from activated primary CD4+ T cells and infected them with NL4-3 GFP reporter HIV-1. We found 10 E3s significantly positively or negatively affected HIV infection in activated primary CD4+ T cells, including UHRF1 (pro-viral) and TRAF2 (anti-viral). Furthermore, deletion of either TRAF2 or UHRF1 in three JLat models of latency spontaneously increased HIV transcription. To verify this effect, we developed a CRISPR-compatible resting primary human CD4+ T cell model of latency. Using this system, we found that deletion of TRAF2 or UHRF1 initiated latency reactivation and increased virus production from primary human resting CD4+ T cells, suggesting these two E3s represent promising targets for future HIV latency reversal strategies. IMPORTANCE: HIV, the virus that causes AIDS, heavily relies on the machinery of human cells to infect and replicate. Our study focuses on the host cell's ubiquitination system which is crucial for numerous cellular processes. Many pathogens, including HIV, exploit this system to enhance their own replication and survival. E3 proteins are part of the ubiquitination pathway that are useful drug targets for host-directed therapies. We interrogated the 116 E3s found in human immune cells known as CD4+ T cells, since these are the target cells infected by HIV. Using CRISPR, a gene-editing tool, we individually removed each of these enzymes and observed the impact on HIV infection in human CD4+ T cells isolated from healthy donors. We discovered that 10 of the E3 enzymes had a significant effect on HIV infection. Two of them, TRAF2 and UHRF1, modulated HIV activity within the cells and triggered an increased release of HIV from previously dormant or "latent" cells in a new primary T cell assay. This finding could guide strategies to perturb hidden HIV reservoirs, a major hurdle to curing HIV. Our study offers insights into HIV-host interactions, identifies new factors that influence HIV infection in immune cells, and introduces a novel methodology for studying HIV infection and latency in human immune cells.

De novo protein identification in mammalian sperm using in situ cryoelectron tomography and AlphaFold2 docking.

To understand the molecular mechanisms of cellular pathways, contemporary workflows typically require multiple techniques to identify proteins, track their localization, and determine their structures in vitro. Here, we combined cellular cryoelectron tomography (cryo-ET) and AlphaFold2 modeling to address these questions and understand how mammalian sperm are built in situ. Our cellular cryo-ET and subtomogram averaging provided 6.0-Å reconstructions of axonemal microtubule structures. The well-resolved tertiary structures allowed us to unbiasedly match sperm-specific densities with 21,615 AlphaFold2-predicted protein models of the mouse proteome. We identified Tektin 5, CCDC105, and SPACA9 as novel microtubule-associated proteins. These proteins form an extensive interaction network crosslinking the lumen of axonemal doublet microtubules, suggesting their roles in modulating the mechanical properties of the filaments. Indeed, Tekt5 -/- sperm possess more deformed flagella with 180° bends. Together, our studies presented a cellular visual proteomics workflow and shed light on the in vivo functions of Tektin 5.

Proteomic and genetic analyses of influenza A viruses identify pan-viral host targets.

Influenza A Virus (IAV) is a recurring respiratory virus with limited availability of antiviral therapies. Understanding host proteins essential for IAV infection can identify targets for alternative host-directed therapies (HDTs). Using affinity purification-mass spectrometry and global phosphoproteomic and protein abundance analyses using three IAV strains (pH1N1, H3N2, H5N1) in three human cell types (A549, NHBE, THP-1), we map 332 IAV-human protein-protein interactions and identify 13 IAV-modulated kinases. Whole exome sequencing of patients who experienced severe influenza reveals several genes, including scaffold protein AHNAK, with predicted loss-of-function variants that are also identified in our proteomic analyses. Of our identified host factors, 54 significantly alter IAV infection upon siRNA knockdown, and two factors, AHNAK and coatomer subunit COPB1, are also essential for productive infection by SARS-CoV-2. Finally, 16 compounds targeting our identified host factors suppress IAV replication, with two targeting CDK2 and FLT3 showing pan-antiviral activity across influenza and coronavirus families. This study provides a comprehensive network model of IAV infection in human cells, identifying functional host targets for pan-viral HDT.

A functional map of HIV-host interactions in primary human T cells.

Human Immunodeficiency Virus (HIV) relies on host molecular machinery for replication. Systematic attempts to genetically or biochemically define these host factors have yielded hundreds of candidates, but few have been functionally validated in primary cells. Here, we target 426 genes previously implicated in the HIV lifecycle through protein interaction studies for CRISPR-Cas9-mediated knock-out in primary human CD4+ T cells in order to systematically assess their functional roles in HIV replication. We achieve efficient knockout (>50% of alleles) in 364 of the targeted genes and identify 86 candidate host factors that alter HIV infection. 47 of these factors validate by multiplex gene editing in independent donors, including 23 factors with restrictive activity. Both gene editing efficiencies and HIV-1 phenotypes are highly concordant among independent donors. Importantly, over half of these factors have not been previously described to play a functional role in HIV replication, providing numerous novel avenues for understanding HIV biology. These data further suggest that host-pathogen protein-protein interaction datasets offer an enriched source of candidates for functional host factor discovery and provide an improved understanding of the mechanics of HIV replication in primary T cells.

Restriction factor compendium for influenza A virus reveals a mechanism for evasion of autophagy.

The fate of influenza A virus (IAV) infection in the host cell depends on the balance between cellular defence mechanisms and viral evasion strategies. To illuminate the landscape of IAV cellular restriction, we generated and integrated global genetic loss-of-function screens with transcriptomics and proteomics data. Our multi-omics analysis revealed a subset of both IFN-dependent and independent cellular defence mechanisms that inhibit IAV replication. Amongst these, the autophagy regulator TBC1 domain family member 5 (TBC1D5), which binds Rab7 to enable fusion of autophagosomes and lysosomes, was found to control IAV replication in vitro and in vivo and to promote lysosomal targeting of IAV M2 protein. Notably, IAV M2 was observed to abrogate TBC1D5-Rab7 binding through a physical interaction with TBC1D5 via its cytoplasmic tail. Our results provide evidence for the molecular mechanism utilised by IAV M2 protein to escape lysosomal degradation and traffic to the cell membrane, where it supports IAV budding and growth.

Efficient generation of isogenic primary human myeloid cells using CRISPR-Cas9 ribonucleoproteins.

Genome engineering of primary human cells with CRISPR-Cas9 has revolutionized experimental and therapeutic approaches to cell biology, but human myeloid-lineage cells have remained largely genetically intractable. We present a method for the delivery of CRISPR-Cas9 ribonucleoprotein (RNP) complexes by nucleofection directly into CD14+ human monocytes purified from peripheral blood, leading to high rates of precise gene knockout. These cells can be efficiently differentiated into monocyte-derived macrophages or dendritic cells. This process yields genetically edited cells that retain transcript and protein markers of myeloid differentiation and phagocytic function. Genetic ablation of the restriction factor SAMHD1 increased HIV-1 infection >50-fold, demonstrating the power of this system for genotype-phenotype interrogation. This fast, flexible, and scalable platform can be used for genetic studies of human myeloid cells in immune signaling, inflammation, cancer immunology, host-pathogen interactions, and beyond, and could facilitate the development of myeloid cellular therapies.

Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.

Evolution of protein phosphorylation across 18 fungal species.

Living organisms have evolved protein phosphorylation, a rapid and versatile mechanism that drives signaling and regulates protein function. We report the phosphoproteomes of 18 fungal species and a phylogenetic-based approach to study phosphosite evolution. We observe rapid divergence, with only a small fraction of phosphosites conserved over hundreds of millions of years. Relative to recently acquired phosphosites, ancient sites are enriched at protein interfaces and are more likely to be functionally important, as we show for sites on H2A1 and eIF4E. We also observe a change in phosphorylation motif frequencies and kinase activities that coincides with the whole-genome duplication event. Our results provide an evolutionary history for phosphosites and suggest that rapid evolution of phosphorylation can contribute strongly to phenotypic diversity.

The proteomic landscape of triple-negative breast cancer.

Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation.

A practical recipe to survey phosphoproteomes.

The field of cellular signaling is fueled by the discovery of novel protein phosphorylation events. Phosphoproteomics focuses on the large-scale identification and characterization of serine, threonine, and tyrosine phosphorylation of proteins. Phosphopeptide enrichment followed by mass spectrometry has emerged as the most powerful technique for unbiased, discovery-driven analysis by offering high sensitivity, resolution, and speed. Methods for mass spectrometry-based phosphoproteomics analysis have improved substantially over the last decade, making the discipline more approachable to the broader scientific community. Herein we describe the status of the field of phosphoproteomics and provide a robust workflow covering the major aspects of large-scale phosphorylation analysis from phosphopeptide enrichment via IMAC to data analysis.