Selective EMC subunits act as molecular tethers of intracellular organelles exploited during viral entry

Sigma-1 receptor recruits LC3 mRNA to ER-associated omegasomes to promote localized LC3 translation enabling functional autophagy

Autophagosome formation initiated on the endoplasmic reticulum (ER)-associated omegasome requires LC3. Translational regulation of LC3 biosynthesis is unexplored. Here we demonstrate that LC3 mRNA is recruited to omegasomes by directly binding to the ER transmembrane Sigma-1 receptor (S1R). Cell-based and in vitro reconstitution experiments show that S1R interacts with the 3' UTR of LC3 mRNA and ribosomes to promote LC3 translation. Strikingly, the 3' UTR of LC3 is also required for LC3 protein lipidation, thereby linking the mRNA-3' UTR to LC3 function. An autophagy-defective S1R mutant responsible for amyotrophic lateral sclerosis cannot bind LC3 mRNA or induce LC3 translation. We propose a model wherein S1R de-represses LC3 mRNA via its 3' UTR at the ER, enabling LC3 biosynthesis and lipidation. Because several other LC3-related proteins use the same mechanism, our data reveal a conserved pathway for localized translation essential for autophagosome biogenesis with insights illuminating the molecular basis of a neurodegenerative disease.

The BICD2 dynein cargo adaptor binds to the HPV16 L2 capsid protein and promotes HPV infection

During entry, human papillomavirus (HPV) traffics from the endosome to the trans Golgi network (TGN) and Golgi and then the nucleus to cause infection. Although dynein is thought to play a role in HPV infection, how this host motor recruits the virus to support infection and which entry step(s) requires dynein are unclear. Here we show that the dynein cargo adaptor BICD2 binds to the HPV L2 capsid protein during entry, recruiting HPV to dynein for transport of the virus along the endosome-TGN/Golgi axis to promote infection. In the absence of BICD2 function, HPV accumulates in the endosome and TGN and infection is inhibited. Cell-based and in vitro binding studies identified a short segment near the C-terminus of L2 that can directly interact with BICD2. Our results reveal the molecular basis by which the dynein motor captures HPV to promote infection and identify this virus as a novel cargo of the BICD2 dynein adaptor.

Host Subcellular Organelles: Targets of Viral Manipulation

Viruses have evolved sophisticated mechanisms to manipulate host cell processes and utilize intracellular organelles to facilitate their replication. These complex interactions between viruses and cellular organelles allow them to hijack the cellular machinery and impair homeostasis. Moreover, viral infection alters the cell membrane's structure and composition and induces vesicle formation to facilitate intracellular trafficking of viral components. However, the research focus has predominantly been on the immune response elicited by viruses, often overlooking the significant alterations that viruses induce in cellular organelles. Gaining a deeper understanding of these virus-induced cellular changes is crucial for elucidating the full life cycle of viruses and developing potent antiviral therapies. Exploring virus-induced cellular changes could substantially improve our understanding of viral infection mechanisms.

Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

How host ER membrane chaperones and morphogenic proteins support virus infection

The multi-functional endoplasmic reticulum (ER) is exploited by viruses to cause infection. Morphologically, this organelle is a highly interconnected membranous network consisting of sheets and tubules whose levels are dynamic, changing in response to cellular conditions. Functionally, the ER is responsible for protein synthesis, folding, secretion and degradation, as well as Ca2+ homeostasis and lipid biosynthesis, with each event catalyzed by defined ER factors. Strikingly, these ER host factors are hijacked by viruses to support different infection steps, including entry, translation, replication, assembly and egress. Although the full repertoire of these ER factors that are hijacked is unknown, recent studies have uncovered several ER membrane machineries that are exploited by viruses - ranging from polyomavirus to flavivirus and coronavirus - to facilitate different steps of their life cycle. These discoveries should provide better understanding of virus infection mechanisms, potentially leading to the development of more effective anti-viral therapies.

Proximity Labeling in Plants

Proteins are workhorses in the cell; they form stable and more often dynamic, transient protein-protein interactions, assemblies, and networks and have an intimate interplay with DNA and RNA. These network interactions underlie fundamental biological processes and play essential roles in cellular function. The proximity-dependent biotinylation labeling approach combined with mass spectrometry (PL-MS) has recently emerged as a powerful technique to dissect the complex cellular network at the molecular level. In PL-MS, by fusing a genetically encoded proximity-labeling (PL) enzyme to a protein or a localization signal peptide, the enzyme is targeted to a protein complex of interest or to an organelle, allowing labeling of proximity proteins within a zoom radius. These biotinylated proteins can then be captured by streptavidin beads and identified and quantified by mass spectrometry. Recently engineered PL enzymes such as TurboID have a much-improved enzymatic activity, enabling spatiotemporal mapping with a dramatically increased signal-to-noise ratio. PL-MS has revolutionized the way we perform proteomics by overcoming several hurdles imposed by traditional technology, such as biochemical fractionation and affinity purification mass spectrometry. In this review, we focus on biotin ligase-based PL-MS applications that have been, or are likely to be, adopted by the plant field. We discuss the experimental designs and review the different choices for engineered biotin ligases, enrichment, and quantification strategies. Lastly, we review the validation and discuss future perspectives.

Magnaporthe oryzae endoplasmic reticulum membrane complex regulates the biogenesis of membrane proteins for pathogenicity

In eukaryotes, the majority of newly synthesized integral membrane proteins are inserted into the endoplasmic reticulum (ER) membrane before transferred to their functional sites. The conserved ER membrane complex (EMC) takes part in the insertion process for tail-anchored membrane proteins. However, the function of EMC in phytopathogenic fungi has not been characterized. Here, we report the identification and functional characterization of two EMC subunits MoEmc5 and MoEmc2 in Magnaporthe oryzae. The knockout mutants ΔMoemc5 and ΔMoemc2 exhibit substantial defect in autophagy, pathogenicity, cell wall integrity, and magnesium ion sensitivity. We demonstrate that the autophagy process was severely impaired in the ΔMoemc5 and ΔMoemc2 mutants because of the low-protein steady-state level of Atg9, the sole membrane-associated autophagy protein. Furthermore, the protein level of membrane proteins Chs4, Fks1, and MoMnr2 is also significantly reduced in the ΔMoemc5 and ΔMoemc2 strains, leading to their supersensitivity to Calcofluor white, Congo red, and magnesium. In addition, MoEmc5, but not MoEmc2, acts as a magnesium transporter independent of its EMC function. Magnaporthe oryzae EMC regulates the biogenesis of membrane proteins for autophagy and virulence; therefore, EMC subunits could be potential targets for fungicide design in the future.

Tensor decomposition based feature extraction and classification to detect natural selection from genomic data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under non-convex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data while preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx , which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

HPV is a cargo for the COPI sorting complex during virus entry

During entry, human papillomavirus (HPV) traffics from the cell surface to the endosome and then to the trans-Golgi network (TGN) and Golgi apparatus. HPV must transit across the TGN/Golgi and exit these compartments to reach the nucleus to cause infection, although how these steps are accomplished is unclear. Combining cellular fractionation, unbiased proteomics, and gene knockdown strategies, we identified the coat protein complex I (COPI), a highly conserved protein complex that facilitates retrograde trafficking of cellular cargos, as a host factor required for HPV infection. Upon TGN/Golgi arrival, the cytoplasmic segment of HPV L2 binds directly to COPI. COPI depletion causes the accumulation of HPV in the TGN/Golgi, resembling the fate of a COPI binding-defective L2 mutant. We propose that the L2-COPI interaction drives HPV trafficking through the TGN and Golgi stacks during virus entry. This shows that an incoming virus is a cargo of the COPI complex.

EMC3 regulates mesenchymal cell survival via control of the mitotic spindle assembly

Eukaryotic cells transit through the cell cycle to produce two daughter cells. Dysregulation of the cell cycle leads to cell death or tumorigenesis. Herein, we found a subunit of the ER membrane complex, EMC3, as a key regulator of cell cycle. Conditional deletion of Emc3 in mouse embryonic mesoderm led to reduced size and patterning defects of multiple organs. Emc3 deficiency impaired cell proliferation, causing spindle assembly defects, chromosome mis-segregation, cell cycle arrest at G2/M, and apoptosis. Upon entry into mitosis, mesenchymal cells upregulate EMC3 protein levels and localize EMC3 to the mitotic centrosomes. Further analysis indicated that EMC3 works together with VCP to tightly regulate the levels and activity of Aurora A, an essential factor for centrosome function and mitotic spindle assembly: while overexpression of EMC3 or VCP degraded Aurora A, their loss led to increased Aurora A stability but reduced Aurora A phosphorylation in mitosis.

Components of the LINC and NPC complexes coordinately target and translocate a virus into the nucleus to promote infection

Nuclear entry represents the final and decisive infection step for most DNA viruses, although how this is accomplished by some viruses is unclear. Polyomavirus SV40 transports from the cell surface through the endosome, the endoplasmic reticulum, and the cytosol from where it enters the nucleus to cause infection. Here we elucidate the nuclear entry mechanism of SV40. Our results show that cytosol-localized SV40 is targeted to the nuclear envelope by directly engaging Nesprin-2 of the linker of nucleoskeleton and cytoskeleton (LINC) nuclear membrane complex. Additionally, we identify the NUP188 subunit of the nuclear pore complex (NPC) as a new Nesprin-2-interacting partner. This physical proximity positions the NPC to capture SV40 upon release from Nesprin-2, enabling the channel to facilitate nuclear translocation of the virus. Strikingly, SV40 disassembles during nuclear entry, generating a viral genome-VP1-VP3 subcomplex that efficiently crosses the NPC to enter the nucleus. Our results reveal how two major nuclear membrane protein complexes are exploited to promote targeting and translocation of a virus into the nucleus.

A specific EMC subunit supports Dengue virus infection by promoting virus membrane fusion essential for cytosolic genome delivery

Dengue virus (DENV) represents the most common human arboviral infection, yet its cellular entry mechanism remains unclear. The multi-subunit endoplasmic reticulum membrane complex (EMC) supports DENV infection, in part, by assisting the biosynthesis of viral proteins critical for downstream replication steps. Intriguingly, the EMC has also been shown to act at an earlier step prior to viral protein biogenesis, although this event is not well-defined. Here we demonstrate that the EMC subunit EMC4 promotes fusion of the DENV and endosomal membranes during entry, enabling delivery of the viral genome into the cytosol which is then targeted to the ER for viral protein biosynthesis. We also found that EMC4 mediates ER-to-endosome transfer of phosphatidylserine, a phospholipid whose presence in the endosome facilitates DENV-endosomal membrane fusion. These findings clarify the EMC-dependent DENV early entry step, suggesting a mechanism by which an ER-localized host factor can regulate viral fusion at the endosome.

EMC is required for biogenesis of Xport-A, an essential chaperone of Rhodopsin-1 and the TRP channel

The ER membrane protein complex (EMC) is required for the biogenesis of a subset of tail anchored (TA) and polytopic membrane proteins, including Rhodopsin-1 (Rh1) and the TRP channel. To understand the physiological implications of EMC-dependent membrane protein biogenesis, we perform a bioinformatic identification of Drosophila TA proteins. From 254 predicted TA proteins, screening in larval eye discs identified two proteins that require EMC for their biogenesis: fan and Xport-A. Fan is required for male fertility in Drosophila and we show that EMC is also required for this process. Xport-A is essential for the biogenesis of both Rh1 and TRP, raising the possibility that disruption of Rh1 and TRP biogenesis in EMC mutants is secondary to the Xport-A defect. We show that EMC is required for Xport-A TMD membrane insertion and that EMC-independent Xport-A mutants rescue Rh1 and TRP biogenesis in EMC mutants. Finally, our work also reveals a role for Xport-A in a glycosylation-dependent triage mechanism during Rh1 biogenesis in the endoplasmic reticulum.

Proximity labeling approaches to study protein complexes during virus infection

Cellular compartmentalization of proteins and protein complex formation allow cells to tightly control biological processes. Therefore, understanding the subcellular localization and interactions of a specific protein is crucial to uncover its biological function. The advent of proximity labeling (PL) has reshaped cellular proteomics in infection biology. PL utilizes a genetically modified enzyme that generates a "labeling cloud" by covalently labeling proteins in close proximity to the enzyme. Fusion of a PL enzyme to a specific antibody or a "bait" protein of interest in combination with affinity enrichment mass spectrometry (AE-MS) enables the isolation and identification of the cellular proximity proteome, or proxisome. This powerful methodology has been paramount for the mapping of membrane or membraneless organelles as well as for the understanding of hard-to-purify protein complexes, such as those of transmembrane proteins. Unsurprisingly, more and more infection biology research groups have recognized the potential of PL for the identification of host-pathogen interactions. In this chapter, we introduce the enzymes commonly used for PL labeling as well as recent promising advancements and summarize the major achievements in organelle mapping and nucleic acid PL. Moreover, we comprehensively describe the research on host-pathogen interactions using PL, giving special attention to studies in the field of virology.

Sending mixed signals: polyomavirus entry and trafficking

Polyomaviruses are mostly non-pathogenic, yet some can cause human disease especially under conditions of immunosuppression, including JC, BK, and Merkel cell polyomaviruses. Direct interactions between viruses and the host early during infection dictate the outcome of disease, many of which remain enigmatic. However, significant work in recent years has contributed to our understanding of how this virus family establishes an infection, largely due to advances made for animal polyomaviruses murine and SV40. Here we summarize the major findings that have contributed to our understanding of polyomavirus entry, trafficking, disassembly, signaling, and immune evasion during the infectious process and highlight major unknowns in these processes that are open areas of study.

ER functions are exploited by viruses to support distinct stages of their life cycle

The endoplasmic reticulum (ER), with its expansive membranous system and a vast network of chaperones, enzymes, sensors, and ion channels, orchestrates diverse cellular functions, ranging from protein synthesis, folding, secretion, and degradation to lipid biogenesis and calcium homeostasis. Strikingly, some of the functions of the ER are exploited by viruses to promote their life cycles. During entry, viruses must penetrate a host membrane and reach an intracellular destination to express and replicate their genomes. These events lead to the assembly of new viral progenies that exit the host cell, thereby initiating further rounds of infection. In this review, we highlight how three distinct viruses - polyomavirus, flavivirus, and coronavirus - co-opt key functions of the ER to cause infection. We anticipate that illuminating this virus-ER interplay will provide rational therapeutic approaches to combat the virus-induced diseases.

Proximity labeling in mammalian cells with TurboID and split-TurboID

This protocol describes the use of TurboID and split-TurboID in proximity labeling applications for mapping protein-protein interactions and subcellular proteomes in live mammalian cells. TurboID is an engineered biotin ligase that uses ATP to convert biotin into biotin-AMP, a reactive intermediate that covalently labels proximal proteins. Optimized using directed evolution, TurboID has substantially higher activity than previously described biotin ligase-related proximity labeling methods, such as BioID, enabling higher temporal resolution and broader application in vivo. Split-TurboID consists of two inactive fragments of TurboID that can be reconstituted through protein-protein interactions or organelle-organelle interactions, which can facilitate greater targeting specificity than full-length enzymes alone. Proteins biotinylated by TurboID or split-TurboID are then enriched with streptavidin beads and identified by mass spectrometry. Here, we describe fusion construct design and characterization (variable timing), proteomic sample preparation (5-7 d), mass spectrometric data acquisition (2 d), and proteomic data analysis (1 week).

Role of the early secretory pathway in SARS-CoV-2 infection

Similar to other RNA viruses, SARS-CoV-2 must (1) enter a target/host cell, (2) reprogram it to ensure its replication, (3) exit the host cell, and (4) repeat this cycle for exponential growth. During the exit step, the virus hijacks the sophisticated machineries that host cells employ to correctly fold, assemble, and transport proteins along the exocytic pathway. Therefore, secretory pathway-mediated assemblage and excretion of infective particles represent appealing targets to reduce the efficacy of virus biogenesis, if not to block it completely. Here, we analyze and discuss the contribution of the molecular machines operating in the early secretory pathway in the biogenesis of SARS-CoV-2 and their relevance for potential antiviral targeting. The fact that these molecular machines are conserved throughout evolution, together with the redundancy and tissue specificity of their components, provides opportunities in the search for unique proteins essential for SARS-CoV-2 biology that could also be targeted with therapeutic objectives. Finally, we provide an overview of recent evidence implicating proteins of the early secretory pathway as potential antiviral targets with effective therapeutic applications.