A Bacterial Cell-Based Assay To Study SARS-CoV-2 Protein-Protein Interactions

Understanding how virally encoded proteins interact with one another is essential in elucidating basic viral biology, providing a foundation for therapeutic discovery. Here, we describe the use of a versatile bacterium-based system to investigate the interactions of the protein set encoded by SARS-CoV-2, the virus responsible for the current COVID-19 pandemic.

Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

A bacteria-based assay to study SARS-CoV-2 protein-protein interactions

Methods for detecting and dissecting the interactions of virally encoded proteins are essential for probing basic viral biology and providing a foundation for therapeutic advances. The dearth of targeted therapeutics for the treatment of COVID-19, an ongoing global health crisis, underscores the importance of gaining a deeper understanding of the interactions of SARS-CoV-2-encoded proteins. Here we describe the use of a convenient bacteria-based two-hybrid (B2H) system to analyze the SARS-CoV-2 proteome. We identify sixteen distinct intraviral protein-protein interactions (PPIs), involving sixteen proteins. We find that many of the identified proteins interact with more than one partner. We further show how our system facilitates the genetic dissection of these interactions, enabling the identification of selectively disruptive mutations. We also describe a modified B2H system that permits the detection of disulfide bond-dependent PPIs in the normally reducing Escherichia coli cytoplasm and we use this system to detect the interaction of the SARS-CoV-2 spike protein receptor-binding domain (RBD) with its cognate cell surface receptor ACE2. We then examine how the RBD-ACE2 interaction is perturbed by several RBD amino acid substitutions found in currently circulating SARS-CoV-2 variants. Our findings illustrate the utility of a genetically tractable bacterial system for probing the interactions of viral proteins and investigating the effects of emerging mutations. In principle, the system could also facilitate the identification of potential therapeutics that disrupt specific interactions of virally encoded proteins. More generally, our findings establish the feasibility of using a B2H system to detect and dissect disulfide bond-dependent interactions of eukaryotic proteins.

Deep-coverage spatiotemporal proteome of the picoeukaryote Ostreococcus tauri reveals differential effects of environmental and endogenous 24-hour rhythms

The cellular landscape changes dramatically over the course of a 24 h day. The proteome responds directly to daily environmental cycles and is additionally regulated by the circadian clock. To quantify the relative contribution of diurnal versus circadian regulation, we mapped proteome dynamics under light:dark cycles compared with constant light. Using Ostreococcus tauri, a prototypical eukaryotic cell, we achieved 85% coverage, which allowed an unprecedented insight into the identity of proteins that facilitate rhythmic cellular functions. The overlap between diurnally- and circadian-regulated proteins was modest and these proteins exhibited different phases of oscillation between the two conditions. Transcript oscillations were generally poorly predictive of protein oscillations, in which a far lower relative amplitude was observed. We observed coordination between the rhythmic regulation of organelle-encoded proteins with the nuclear-encoded proteins that are targeted to organelles. Rhythmic transmembrane proteins showed a different phase distribution compared with rhythmic soluble proteins, indicating the existence of a circadian regulatory process specific to the biogenesis and/or degradation of membrane proteins. Our observations argue that the cellular spatiotemporal proteome is shaped by a complex interaction between intrinsic and extrinsic regulatory factors through rhythmic regulation at the transcriptional as well as post-transcriptional, translational, and post-translational levels.

Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acids exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution dataset for transmembrane helices from a variety of sampled set of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

SARS-CoV-2 Membrane Glycoprotein M Triggers Apoptosis With the Assistance of Nucleocapsid Protein N in Cells

The pandemic of COVID-19 by SARS-CoV-2 has become a global disaster. However, we still don’t know how specific SARS-CoV-2-encoded proteins contribute to viral pathogenicity. We found that SARS-CoV-2-encoded membrane glycoprotein M could induce caspase-dependent apoptosis via interacting with PDK1 and inhibiting the activation of PDK1-PKB/Akt signaling. Our investigation further revealed that SARS-CoV-2-encoded nucleocapsid protein N could specifically enhance the M-induced apoptosis via interacting with both M and PDK1, therefore strengthening M-mediated attenuation of PDK1-PKB/Akt interaction. Furthermore, when the M-N interaction was disrupted via certain rationally designed peptides, the PDK1-PKB/Akt signaling was restored, and the boosting activity of N on the M-triggered apoptosis was abolished. Overall, our findings uncovered a novel mechanism by which SARS-CoV-2-encoded M triggers apoptosis with the assistance of N, which expands our understanding of the two key proteins of SARS-CoV-2 and sheds light on the pathogenicity of this life-threatening virus.