Chemical-genetic interrogation of RNA polymerase mutants reveals structure-function relationships and physiological tradeoffs.

The multi-subunit bacterial RNA polymerase (RNAP) and its associated regulators carry out transcription and integrate myriad regulatory signals. Numerous studies have interrogated RNAP mechanism, and RNAP mutations drive Escherichia coli adaptation to many health- and industry-relevant environments, yet a paucity of systematic analyses hampers our understanding of the fitness trade-offs from altering RNAP function. Here, we conduct a chemical-genetic analysis of a library of RNAP mutants. We discover phenotypes for non-essential insertions, show that clustering mutant phenotypes increases their predictive power for drawing functional inferences, and demonstrate that some RNA polymerase mutants both decrease average cell length and prevent killing by cell-wall targeting antibiotics. Our findings demonstrate that RNAP chemical-genetic interactions provide a general platform for interrogating structure-function relationships in vivo and for identifying physiological trade-offs of mutations, including those relevant for disease and biotechnology. This strategy should have broad utility for illuminating the role of other important protein complexes.

From systems to structure - using genetic data to model protein structures.

Understanding the effects of genetic variation is a fundamental problem in biology that requires methods to analyse both physical and functional consequences of sequence changes at systems-wide and mechanistic scales. To achieve a systems view, protein interaction networks map which proteins physically interact, while genetic interaction networks inform on the phenotypic consequences of perturbing these protein interactions. Until recently, understanding the molecular mechanisms that underlie these interactions often required biophysical methods to determine the structures of the proteins involved. The past decade has seen the emergence of new approaches based on coevolution, deep mutational scanning and genome-scale genetic or chemical-genetic interaction mapping that enable modelling of the structures of individual proteins or protein complexes. Here, we review the emerging use of large-scale genetic datasets and deep learning approaches to model protein structures and their interactions, and discuss the integration of structural data from different sources.

From structure to systems: high-resolution, quantitative genetic analysis of RNA polymerase II.

RNA polymerase II (RNAPII) lies at the core of dynamic control of gene expression. Using 53 RNAPII point mutants, we generated a point mutant epistatic miniarray profile (pE-MAP) comprising ∼60,000 quantitative genetic interactions in Saccharomyces cerevisiae. This analysis enabled functional assignment of RNAPII subdomains and uncovered connections between individual regions and other protein complexes. Using splicing microarrays and mutants that alter elongation rates in vitro, we found an inverse relationship between RNAPII speed and in vivo splicing efficiency. Furthermore, the pE-MAP classified fast and slow mutants that favor upstream and downstream start site selection, respectively. The striking coordination of polymerization rate with transcription initiation and splicing suggests that transcription rate is tuned to regulate multiple gene expression steps. The pE-MAP approach provides a powerful strategy to understand other multifunctional machines at amino acid resolution.

Evolution of enhanced innate immune evasion by SARS-CoV-2.

The emergence of SARS-CoV-2 variants of concern suggests viral adaptation to enhance human-to-human transmission1,2. Although much effort has focused on the characterization of changes in the spike protein in variants of concern, mutations outside of spike are likely to contribute to adaptation. Here, using unbiased abundance proteomics, phosphoproteomics, RNA sequencing and viral replication assays, we show that isolates of the Alpha (B.1.1.7) variant3 suppress innate immune responses in airway epithelial cells more effectively than first-wave isolates. We found that the Alpha variant has markedly increased subgenomic RNA and protein levels of the nucleocapsid protein (N), Orf9b and Orf6-all known innate immune antagonists. Expression of Orf9b alone suppressed the innate immune response through interaction with TOM70, a mitochondrial protein that is required for activation of the RNA-sensing adaptor MAVS. Moreover, the activity of Orf9b and its association with TOM70 was regulated by phosphorylation. We propose that more effective innate immune suppression, through enhanced expression of specific viral antagonist proteins, increases the likelihood of successful transmission of the Alpha variant, and may increase in vivo replication and duration of infection4. The importance of mutations outside the spike coding region in the adaptation of SARS-CoV-2 to humans is underscored by the observation that similar mutations exist in the N and Orf9b regulatory regions of the Delta and Omicron variants.

Systems-level effects of allosteric perturbations to a model molecular switch.

Molecular switch proteins whose cycling between states is controlled by opposing regulators1,2 are central to biological signal transduction. As switch proteins function within highly connected interaction networks3, the fundamental question arises of how functional specificity is achieved when different processes share common regulators. Here we show that functional specificity of the small GTPase switch protein Gsp1 in Saccharomyces cerevisiae (the homologue of the human protein RAN)4 is linked to differential sensitivity of biological processes to different kinetics of the Gsp1 (RAN) switch cycle. We make 55 targeted point mutations to individual protein interaction interfaces of Gsp1 (RAN) and show through quantitative genetic5 and physical interaction mapping that Gsp1 (RAN) interface perturbations have widespread cellular consequences. Contrary to expectation, the cellular effects of the interface mutations group by their biophysical effects on kinetic parameters of the GTPase switch cycle and not by the targeted interfaces. Instead, we show that interface mutations allosterically tune the GTPase cycle kinetics. These results suggest a model in which protein partner binding, or post-translational modifications at distal sites, could act as allosteric regulators of GTPase switching. Similar mechanisms may underlie regulation by other GTPases, and other biological switches. Furthermore, our integrative platform to determine the quantitative consequences of molecular perturbations may help to explain the effects of disease mutations that target central molecular switches.

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing.

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

Functional organization of the S. cerevisiae phosphorylation network.

Reversible protein phosphorylation is a signaling mechanism involved in all cellular processes. To create a systems view of the signaling apparatus in budding yeast, we generated an epistatic miniarray profile (E-MAP) comprised of 100,000 pairwise, quantitative genetic interactions, including virtually all protein and small-molecule kinases and phosphatases as well as key cellular regulators. Quantitative genetic interaction mapping reveals factors working in compensatory pathways (negative genetic interactions) or those operating in linear pathways (positive genetic interactions). We found an enrichment of positive genetic interactions between kinases, phosphatases, and their substrates. In addition, we assembled a higher-order map from sets of three genes that display strong interactions with one another: triplets enriched for functional connectivity. The resulting network view provides insights into signaling pathway regulation and reveals a link between the cell-cycle kinase, Cak1, the Fus3 MAP kinase, and a pathway that regulates chromatin integrity during transcription by RNA polymerase II.

A lipid E-MAP identifies Ubx2 as a critical regulator of lipid saturation and lipid bilayer stress.

Biological membranes are complex, and the mechanisms underlying their homeostasis are incompletely understood. Here, we present a quantitative genetic interaction map (E-MAP) focused on various aspects of lipid biology, including lipid metabolism, sorting, and trafficking. This E-MAP contains ∼250,000 negative and positive genetic interaction scores and identifies a molecular crosstalk of protein quality control pathways with lipid bilayer homeostasis. Ubx2p, a component of the endoplasmic-reticulum-associated degradation pathway, surfaces as a key upstream regulator of the essential fatty acid (FA) desaturase Ole1p. Loss of Ubx2p affects the transcriptional control of OLE1, resulting in impaired FA desaturation and a severe shift toward more saturated membrane lipids. Both the induction of the unfolded protein response and aberrant nuclear membrane morphologies observed in cells lacking UBX2 are suppressed by the supplementation of unsaturated FAs. Our results point toward the existence of dedicated bilayer stress responses for membrane homeostasis.

Nonsense-mediated decay regulates key components of homologous recombination.

Cells frequently experience DNA damage that requires repair by homologous recombination (HR). Proteins involved in HR are carefully coordinated to ensure proper and efficient repair without interfering with normal cellular processes. In Saccharomyces cerevisiae, Rad55 functions in the early steps of HR and is regulated in response to DNA damage through phosphorylation by the Mec1 and Rad53 kinases of the DNA damage response. To further identify regulatory processes that target HR, we performed a high-throughput genetic interaction screen with RAD55 phosphorylation site mutants. Genes involved in the mRNA quality control process, nonsense-mediated decay (NMD), were found to genetically interact with rad55 phospho-site mutants. Further characterization revealed that RAD55 transcript and protein levels are regulated by NMD. Regulation of HR by NMD extends to multiple targets beyond RAD55, including RAD51, RAD54 and RAD57 Finally, we demonstrate that loss of NMD results in an increase in recombination rates and resistance to the DNA damaging agent methyl methanesulfonate, suggesting this pathway negatively regulates HR under normal growth conditions.

A genetic interaction map of RNA-processing factors reveals links between Sem1/Dss1-containing complexes and mRNA export and splicing.

We used a quantitative, high-density genetic interaction map, or E-MAP (Epistatic MiniArray Profile), to interrogate the relationships within and between RNA-processing pathways. Due to their complexity and the essential roles of many of the components, these pathways have been difficult to functionally dissect. Here, we report the results for 107,155 individual interactions involving 552 mutations, 166 of which are hypomorphic alleles of essential genes. Our data enabled the discovery of links between components of the mRNA export and splicing machineries and Sem1/Dss1, a component of the 19S proteasome. In particular, we demonstrate that Sem1 has a proteasome-independent role in mRNA export as a functional component of the Sac3-Thp1 complex. Sem1 also interacts with Csn12, a component of the COP9 signalosome. Finally, we show that Csn12 plays a role in pre-mRNA splicing, which is independent of other signalosome components. Thus, Sem1 is involved in three separate and functionally distinct complexes.

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution: exploring the applications of high-resolution genetic interaction mapping of point mutations.

We have achieved a residue-level resolution of genetic interaction mapping - a technique that measures how the function of one gene is affected by the alteration of a second gene - by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine.

Adventures in time and space: splicing efficiency and RNA polymerase II elongation rate.

Control of pre-mRNA splicing is a critical part of the eukaryotic gene expression process. Extensive evidence indicates that transcription and splicing are spatiotemporally coordinated and that most splicing events occur co-transcriptionally. A kinetic coupling model has been proposed in metazoans to describe how changing RNA Polymerase II (RNAPII) elongation rate can impact which alternative splice sites are used. In Saccharomyces cerevisiae, in which most spliced genes have only a single intron and splice sites adhere to a strong consensus sequence, we recently observed that splicing efficiency was sensitive to mutations in RNAPII that increase or decrease its elongation rate. Our data revealed that RNAPII speed and splicing efficiency are generally anti-correlated: at many genes, increased elongation rate caused decreased splicing efficiency, while decreased elongation rate increased splicing efficiency. An improved splicing phenotype was also observed upon deletion of SUB1, a condition in which elongation rate is slowed. We discuss these data in the context of a growing field and expand the kinetic coupling model to apply to both alternative splicing and splicing efficiency.

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.

RNA polymerase II carboxyl-terminal domain phosphorylation regulates protein stability of the Set2 methyltransferase and histone H3 di- and trimethylation at lysine 36.

Methylation of lysine 36 on histone H3 (H3K36) is catalyzed by the Set2 methyltransferase and is linked to transcriptional regulation. Previous studies have shown that trimethylation of H3K36 by Set2 is directed through its association with the phosphorylated repeats of the RNA polymerase C-terminal domain (RNAPII CTD). Here, we show that disruption of this interaction through the use of yeast mutants defective in CTD phosphorylation at serine 2 results in a destabilization of Set2 protein levels and H3K36 methylation. Consistent with this, we find that Set2 has a short half-life and is co-regulated, with RNAPII CTD phosphorylation levels, during logarithmic growth in yeast. To probe the functional consequence of uncoupling Set2-RNAPII regulation, we expressed a truncated and more stable form of Set2 that is capable of dimethylation but not trimethylation in vivo. Results of high throughput synthetic genetic analyses show that this Set2 variant has distinct genetics from either SET2 or set2Δ and is synthetically sick or lethal with a number of transcription elongation mutants. Collectively, these results provide molecular insight into the regulation of Set2 protein levels that influence H3K36 methylation states.

SALIGN: a web server for alignment of multiple protein sequences and structures.

SUMMARY: Accurate alignment of protein sequences and/or structures is crucial for many biological analyses, including functional annotation of proteins, classifying protein sequences into families, and comparative protein structure modeling. Described here is a web interface to SALIGN, the versatile protein multiple sequence/structure alignment module of MODELLER. The web server automatically determines the best alignment procedure based on the inputs, while allowing the user to override default parameter values. Multiple alignments are guided by a dendrogram computed from a matrix of all pairwise alignment scores. When aligning sequences to structures, SALIGN uses structural environment information to place gaps optimally. If two multiple sequence alignments of related proteins are input to the server, a profile-profile alignment is performed. All features of the server have been previously optimized for accuracy, especially in the contexts of comparative modeling and identification of interacting protein partners. AVAILABILITY: The SALIGN web server is freely accessible to the academic community at http://salilab.org/salign. SALIGN is a module of the MODELLER software, also freely available to academic users (http://salilab.org/modeller). CONTACT: sali@salilab.org; madhusudhan@bii.a-star.edu.sg.

ModBase, a database of annotated comparative protein structure models, and associated resources.

ModBase (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by ModPipe, an automated modeling pipeline that relies primarily on Modeller for fold assignment, sequence-structure alignment, model building and model assessment (http://salilab.org/modeller/). ModBase currently contains 10,355,444 reliable models for domains in 2,421,920 unique protein sequences. ModBase allows users to update comparative models on demand, and request modeling of additional sequences through an interface to the ModWeb modeling server (http://salilab.org/modweb). ModBase models are available through the ModBase interface as well as the Protein Model Portal (http://www.proteinmodelportal.org/). Recently developed associated resources include the SALIGN server for multiple sequence and structure alignment (http://salilab.org/salign), the ModEval server for predicting the accuracy of protein structure models (http://salilab.org/modeval), the PCSS server for predicting which peptides bind to a given protein (http://salilab.org/pcss) and the FoXS server for calculating and fitting Small Angle X-ray Scattering profiles (http://salilab.org/foxs).

Integrative structure determination of histones H3 and H4 using genetic interactions.

Integrative structure modeling is increasingly used for determining the architectures of biological assemblies, especially those that are structurally heterogeneous. Recently, we reported on how to convert in vivo genetic interaction measurements into spatial restraints for structural modeling: first, phenotypic profiles are generated for each point mutation and thousands of gene deletions or environmental perturbations. Following, the phenotypic profile similarities are converted into distance restraints on the pairs of mutated residues. We illustrate the approach by determining the structure of the histone H3-H4 complex. The method is implemented in our open-source IMP program, expanding the structural biology toolbox by allowing structural characterization based on in vivo data without the need to purify the target system. We compare genetic interaction measurements to other sources of structural information, such as residue coevolution and deep-learning structure prediction of complex subunits. We also suggest that determining genetic interactions could benefit from new technologies, such as CRISPR-Cas9 approaches to gene editing, especially for mammalian cells. Finally, we highlight the opportunity for using genetic interactions to determine recalcitrant biomolecular structures, such as those of disordered proteins, transient protein assemblies, and host-pathogen protein complexes.

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.

Individual lysine acetylations on the N terminus of Saccharomyces cerevisiae H2A.Z are highly but not differentially regulated.

The multi-functional histone variant Htz1 (Saccharomyces cerevisiae H2A.Z) is acetylated on up to four N-terminal lysines at positions 3, 8, 10, and 14. It has thus been posited that specific acetylated forms of the histone could regulate distinct roles. Antibodies against Htz1-K8(Ac), -K10(Ac), and -K14(Ac) show that all three modifications are added by Esa1 acetyltransferase and removed by Hda1 deacetylase. Completely unacetylatable htz1 alleles exhibit widespread interactions in genome scale genetic screening. However, singly mutated (e.g. htz1-K8R) or singly acetylable (e.g. the triple mutant htz1-K3R/K10R/K14R) alleles show no significant defects in these analyses. This suggests that the N-terminal acetylations on Htz1 are internally redundant. Further supporting this proposal, each acetylation decays with similar kinetics when Htz1 transcription is repressed, and proteomic screening did not find a single condition in which one Htz1(Ac) was differentially regulated. However, whereas the individual acetylations on Htz1 may be redundant, they are not dispensable. Completely unacetylatable htz1 alleles display genetic interactions and phenotypes in common with and distinct from htz1Δ. In addition, each Htz1 N-terminal lysine is deacetylated by Hda1 in response to benomyl and reacetylated when this agent is removed. Such active regulation suggests that acetylation plays a significant role in Htz1 function.