Deep mutational scanning of hepatitis B virus reveals a mechanism for cis-preferential reverse transcription.

Hepatitis B virus (HBV) is a small double-stranded DNA virus that chronically infects 296 million people. Over half of its compact genome encodes proteins in two overlapping reading frames, and during evolution, multiple selective pressures can act on shared nucleotides. This study combines an RNA-based HBV cell culture system with deep mutational scanning (DMS) to uncouple cis- and trans-acting sequence requirements in the HBV genome. The results support a leaky ribosome scanning model for polymerase translation, provide a fitness map of the HBV polymerase at single-nucleotide resolution, and identify conserved prolines adjacent to the HBV polymerase termination codon that stall ribosomes. Further experiments indicated that stalled ribosomes tether the nascent polymerase to its template RNA, ensuring cis-preferential RNA packaging and reverse transcription of the HBV genome.

Effect of an Innovative Immunization Practice Model to Improve Population Health: Results of the Project IMPACT Immunizations Scaled Demonstration.

Background: U.S. adult vaccination rates remain low. Community pharmacists have skills and opportunity to improve this shortcoming. This study sought to evaluate an innovative practice model on identification of unmet vaccination needs and their resolution. Methods: This prospective, multi-site, multi-state, observational study was conducted in 22 community pharmacy practices in Iowa and Washington. Adults receiving influenza vaccination, medication therapy review, prescriptions for diabetes or cardiovascular disease, or another clinical encounter with a participating pharmacist from December 2017 through November 2019 were included. Pharmacists reviewed vaccination forecasts generated by clinical decision support technology based on their state immunization information system (IIS) to identify unmet vaccination needs, educate patients, and improve vaccination rates. The primary outcomes were numbers of vaccination forecast reviews, patients educated, unmet vaccination needs identified and resolved, and vaccinations administered. Secondary outcomes included numbers of vaccination declinations; times a forecasted vaccine was not recommended because a contraindication was identified by the pharmacist; and times the patients declined a forecasted vaccine due to self-reported vaccination despite lack of documentation in the state IIS. Descriptive statistics were calculated. Results: Pharmacists reviewed vaccination forecasts for 6,234 patients. The vaccination forecasts predicted there were 11,789 vaccinations needed (1.9 per person). 6,405 of the 11,789 unmet vaccination needs (54.3%) were fulfilled during the study period, including 60% on the same day. Of the forecasted needs, 1,085 (9.2%) were found to be previously administered and 59 (0.5%) contraindicated. The remaining patients received information about their personal vaccination needs and recommendations to be vaccinated. Conclusion: Availability of vaccination histories during patient encounters allowed pharmacists to identify and resolve adult vaccination needs in independent and chain community practice settings.

The relaxin receptor RXFP1 signals through a mechanism of autoinhibition.

The relaxin family peptide receptor 1 (RXFP1) is the receptor for relaxin-2, an important regulator of reproductive and cardiovascular physiology. RXFP1 is a multi-domain G protein-coupled receptor (GPCR) with an ectodomain consisting of a low-density lipoprotein receptor class A (LDLa) module and leucine-rich repeats. The mechanism of RXFP1 signal transduction is clearly distinct from that of other GPCRs, but remains very poorly understood. In the present study, we determine the cryo-electron microscopy structure of active-state human RXFP1, bound to a single-chain version of the endogenous agonist relaxin-2 and the heterotrimeric Gs protein. Evolutionary coupling analysis and structure-guided functional experiments reveal that RXFP1 signals through a mechanism of autoinhibition. Our results explain how an unusual GPCR family functions, providing a path to rational drug development targeting the relaxin receptors.

Bacterial spore germination receptors are nutrient-gated ion channels.

Bacterial spores resist antibiotics and sterilization and can remain metabolically inactive for decades, but they can rapidly germinate and resume growth in response to nutrients. Broadly conserved receptors embedded in the spore membrane detect nutrients, but how spores transduce these signals remains unclear. Here, we found that these receptors form oligomeric membrane channels. Mutations predicted to widen the channel initiated germination in the absence of nutrients, whereas those that narrow it prevented ion release and germination in response to nutrients. Expressing receptors with widened channels during vegetative growth caused loss of membrane potential and cell death, whereas the addition of germinants to cells expressing wild-type receptors triggered membrane depolarization. Therefore, germinant receptors act as nutrient-gated ion channels such that ion release initiates exit from dormancy.

Mechanical gating of the auditory transduction channel TMC1 involves the fourth and sixth transmembrane helices.

The transmembrane (TM) channel-like 1 (TMC1) and TMC2 proteins play a central role in auditory transduction, forming ion channels that convert sound into electrical signals. However, the molecular mechanism of their gating remains unknown. Here, using predicted structural models as a guide, we probed the effects of 12 mutations on the mechanical gating of the transduction currents in native hair cells of Tmc1/2-null mice expressing virally introduced TMC1 variants. Whole-cell electrophysiological recordings revealed that mutations within the pore-lining TM4 and TM6 helices modified gating, reducing the force sensitivity or shifting the open probability of the channels, or both. For some of the mutants, these changes were accompanied by a change in single-channel conductance. Our observations are in line with a model wherein conformational changes in the TM4 and TM6 helices are involved in the mechanical gating of the transduction channel.

The SpoVA membrane complex is required for dipicolinic acid import during sporulation and export during germination.

In response to starvation, endospore-forming bacteria differentiate into stress-resistant spores that can remain dormant for years yet rapidly germinate and resume growth in response to nutrients. The small molecule dipicolinic acid (DPA) plays a central role in both the stress resistance of the dormant spore and its exit from dormancy during germination. The spoVA locus is required for DPA import during sporulation and has been implicated in its export during germination, but the molecular bases are unclear. Here, we define the minimal set of proteins encoded in the Bacillus subtilis spoVA operon required for DPA import and demonstrate that these proteins form a membrane complex. Structural modeling of these components combined with mutagenesis and in vivo analysis reveal that the C and Eb subunits form a membrane channel, while the D subunit functions as a cytoplasmic plug. We show that point mutations that impair the interactions between D and the C-Eb membrane complex reduce the efficiency of DPA import during sporulation and reciprocally accelerate DPA release during germination. Our data support a model in which DPA transport into spores involves cycles of unplugging and then replugging the C-Eb membrane channel, while nutrient detection during germination triggers DPA release by unplugging it.

Natural and Designed Proteins Inspired by Extremotolerant Organisms Can Form Condensates and Attenuate Apoptosis in Human Cells.

Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis-protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlights the ability of DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.

Dormant spores sense amino acids through the B subunits of their germination receptors.

Bacteria from the orders Bacillales and Clostridiales differentiate into stress-resistant spores that can remain dormant for years, yet rapidly germinate upon nutrient sensing. How spores monitor nutrients is poorly understood but in most cases requires putative membrane receptors. The prototypical receptor from Bacillus subtilis consists of three proteins (GerAA, GerAB, GerAC) required for germination in response to L-alanine. GerAB belongs to the Amino Acid-Polyamine-Organocation superfamily of transporters. Using evolutionary co-variation analysis, we provide evidence that GerAB adopts a structure similar to an L-alanine transporter from this superfamily. We show that mutations in gerAB predicted to disrupt the ligand-binding pocket impair germination, while mutations predicted to function in L-alanine recognition enable spores to respond to L-leucine or L-serine. Finally, substitutions of bulkier residues at these positions cause constitutive germination. These data suggest that GerAB is the L-alanine sensor and that B subunits in this broadly conserved family function in nutrient detection.

Disease variant prediction with deep generative models of evolutionary data.

Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences1-3. In principle, computational methods could support the large-scale interpretation of genetic variants. However, state-of-the-art methods4-10 have relied on training machine learning models on known disease labels. As these labels are sparse, biased and of variable quality, the resulting models have been considered insufficiently reliable11. Here we propose an approach that leverages deep generative models to predict variant pathogenicity without relying on labels. By modelling the distribution of sequence variation across organisms, we implicitly capture constraints on the protein sequences that maintain fitness. Our model EVE (evolutionary model of variant effect) not only outperforms computational approaches that rely on labelled data but also performs on par with, if not better than, predictions from high-throughput experiments, which are increasingly used as evidence for variant classification12-16. We predict the pathogenicity of more than 36 million variants across 3,219 disease genes and provide evidence for the classification of more than 256,000 variants of unknown significance. Our work suggests that models of evolutionary information can provide valuable independent evidence for variant interpretation that will be widely useful in research and clinical settings.

Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences.

Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex.

Structural coordination of polymerization and crosslinking by a SEDS-bPBP peptidoglycan synthase complex.

The shape, elongation, division and sporulation (SEDS) proteins are a highly conserved family of transmembrane glycosyltransferases that work in concert with class B penicillin-binding proteins (bPBPs) to build the bacterial peptidoglycan cell wall1-6. How these proteins coordinate polymerization of new glycan strands with their crosslinking to the existing peptidoglycan meshwork is unclear. Here, we report the crystal structure of the prototypical SEDS protein RodA from Thermus thermophilus in complex with its cognate bPBP at 3.3 Å resolution. The structure reveals a 1:1 stoichiometric complex with two extensive interaction interfaces between the proteins: one in the membrane plane and the other at the extracytoplasmic surface. When in complex with a bPBP, RodA shows an approximately 10 Å shift of transmembrane helix 7 that exposes a large membrane-accessible cavity. Negative-stain electron microscopy reveals that the complex can adopt a variety of different conformations. These data define the bPBP pedestal domain as the key allosteric activator of RodA both in vitro and in vivo, explaining how a SEDS-bPBP complex can coordinate its dual enzymatic activities of peptidoglycan polymerization and crosslinking to build the cell wall.

Sequential Pulse Compression's Effect on Blood Flow in the Lower-Extremity.

CONTEXT: Several interventions are available to reduce the intensity and duration of the unwanted effects (eg, muscle soreness) associated with physical activity, such as massage, compression garments, and sequential pulse compression (SPC). Such interventions aim to increase blood flow to alleviate symptoms. However, there is a lack of evidence to support the use of SPC to alter total hemoglobin concentration (THb) in active individuals. OBJECTIVE: To examine the acute effects of a single session of SPC on hemoglobin concentration compared with a control condition. DESIGN: Single cohort, crossover design. PARTICIPANTS: Thirty-four physically active and healthy participants (females = 12 and males = 22) completed the study. INTERVENTIONS: The authors randomly assigned participants to first receive the experimental (SPC) or control condition. Measures were recorded precondition and postcondition. Participants returned to the laboratory to complete the second condition ≥24 hours after the first condition. MAIN OUTCOME MEASURES: Relative changes in THb, deoxygenated hemoglobin, and oxygenated hemoglobin measures were recorded using near-infrared spectroscopy placed on the muscle belly of the medial gastrocnemius of the dominant limb. RESULTS: SPC significantly increased THb (P < .001, d = 0.505) and oxygenated hemoglobin (P < .001, d = 0.745) change scores compared with the control condition. No statistical difference in deoxygenated hemoglobin change scores was found between the SPC and control conditions, but a medium effect size suggests potential biological significance (P = .06, d = 0.339). CONCLUSIONS: Overall, SPC increases THb to the lower-extremity and may be a viable option in the management of muscle soreness related to physical activity.

Protein Structure from Experimental Evolution.

Natural evolution encodes rich information about the structure and function of biomolecules in the genetic record. Previously, statistical analysis of co-variation patterns in natural protein families has enabled the accurate computation of 3D structures. Here, we explored generating similar information by experimental evolution, starting from a single gene and performing multiple cycles of in vitro mutagenesis and functional selection in Escherichia coli. We evolved two antibiotic resistance proteins, ß-lactamase PSE1 and acetyltransferase AAC6, and obtained hundreds of thousands of diverse functional sequences. Using evolutionary coupling analysis, we inferred residue interaction constraints that were in agreement with contacts in known 3D structures, confirming genetic encoding of structural constraints in the selected sequences. Computational protein folding with interaction constraints then yielded 3D structures with the same fold as natural relatives. This work lays the foundation for a new experimental method (3Dseq) for protein structure determination, combining evolution experiments with inference of residue interactions from sequence information. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

Protein structure prediction assisted with sparse NMR data in CASP13.

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and 15 N-1 H residual dipolar coupling data, typical of that obtained for 15 N,13 C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CASP13 also assessed whether incorporation of sparse NMR data improves the accuracy of protein structure prediction relative to nonassisted regular methods. In most cases, incorporation of sparse, noisy NMR data results in models with higher accuracy. The best NMR-assisted models were also compared with the best regular predictions of any CASP13 group for the same target. For six of 13 targets, the most accurate model provided by any NMR-assisted prediction group was more accurate than the most accurate model provided by any regular prediction group; however, for the remaining seven targets, one or more regular prediction method provided a more accurate model than even the best NMR-assisted model. These results suggest a novel approach for protein structure determination, in which advanced prediction methods are first used to generate structural models, and sparse NMR data is then used to validate and/or refine these models.

Inferring protein 3D structure from deep mutation scans.

We describe an experimental method of three-dimensional (3D) structure determination that exploits the increasing ease of high-throughput mutational scans. Inspired by the success of using natural, evolutionary sequence covariation to compute protein and RNA folds, we explored whether 'laboratory', synthetic sequence variation might also yield 3D structures. We analyzed five large-scale mutational scans and discovered that the pairs of residues with the largest positive epistasis in the experiments are sufficient to determine the 3D fold. We show that the strongest epistatic pairings from genetic screens of three proteins, a ribozyme and a protein interaction reveal 3D contacts within and between macromolecules. Using these experimental epistatic pairs, we compute ab initio folds for a GB1 domain (within 1.8 Å of the crystal structure) and a WW domain (2.1 Å). We propose strategies that reduce the number of mutants needed for contact prediction, suggesting that genomics-based techniques can efficiently predict 3D structure.

Combining Evolutionary Covariance and NMR Data for Protein Structure Determination.

Accurate protein structure determination by solution-state NMR is challenging for proteins greater than about 20kDa, for which extensive perdeuteration is generally required, providing experimental data that are incomplete (sparse) and ambiguous. However, the massive increase in evolutionary sequence information coupled with advances in methods for sequence covariance analysis can provide reliable residue-residue contact information for a protein from sequence data alone. These "evolutionary couplings (ECs)" can be combined with sparse NMR data to determine accurate 3D protein structures. This hybrid "EC-NMR" method has been developed using NMR data for several soluble proteins and validated by comparison with corresponding reference structures determined by X-ray crystallography and/or conventional NMR methods. For small proteins, only backbone resonance assignments are utilized, while for larger proteins both backbone and some sidechain methyl resonance assignments are generally required. ECs can be combined with sparse NMR data obtained on deuterated, selectively protonated protein samples to provide structures that are more accurate and complete than those obtained using such sparse NMR data alone. EC-NMR also has significant potential for analysis of protein structures from solid-state NMR data and for studies of integral membrane proteins. The requirement that ECs are consistent with NMR data recorded on a specific member of a protein family, under specific conditions, also allows identification of ECs that reflect alternative allosteric or excited states of the protein structure.

The EVcouplings Python framework for coevolutionary sequence analysis.

SUMMARY: Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. AVAILABILITY AND IMPLEMENTATION: https://github.com/debbiemarkslab/evcouplings.

Evidence that regulation of intramembrane proteolysis is mediated by substrate gating during sporulation in Bacillus subtilis.

During the morphological process of sporulation in Bacillus subtilis two adjacent daughter cells (called the mother cell and forespore) follow different programs of gene expression that are linked to each other by signal transduction pathways. At a late stage in development, a signaling pathway emanating from the forespore triggers the proteolytic activation of the mother cell transcription factor σK. Cleavage of pro-σK to its mature and active form is catalyzed by the intramembrane cleaving metalloprotease SpoIVFB (B), a Site-2 Protease (S2P) family member. B is held inactive by two mother-cell membrane proteins SpoIVFA (A) and BofA. Activation of pro-σK processing requires a site-1 signaling protease SpoIVB (IVB) that is secreted from the forespore into the space between the two cells. IVB cleaves the extracellular domain of A but how this cleavage activates intramembrane proteolysis has remained unclear. Structural studies of the Methanocaldococcus jannaschii S2P homolog identified closed (substrate-occluded) and open (substrate-accessible) conformations of the protease, but the biological relevance of these conformations has not been established. Here, using co-immunoprecipitation and fluorescence microscopy, we show that stable association between the membrane-embedded protease and its substrate requires IVB signaling. We further show that the cytoplasmic cystathionine-ß-synthase (CBS) domain of the B protease is not critical for this interaction or for pro-σK processing, suggesting the IVB-dependent interaction site is in the membrane protease domain. Finally, we provide evidence that the B protease domain adopts both open and closed conformations in vivo. Collectively, our data support a substrate-gating model in which IVB-dependent cleavage of A on one side of the membrane triggers a conformational change in the membrane-embedded protease from a closed to an open state allowing pro-σK access to the caged interior of the protease.

Cryo-electron microscopy structure of the lipid droplet-formation protein seipin.

Metabolic energy is stored in cells primarily as triacylglycerols in lipid droplets (LDs), and LD dysregulation leads to metabolic diseases. The formation of monolayer-bound LDs from the endoplasmic reticulum (ER) bilayer is poorly understood, but the ER protein seipin is essential to this process. In this study, we report a cryo-electron microscopy structure and functional characterization of Drosophila melanogaster seipin. The structure reveals a ring-shaped dodecamer with the luminal domain of each monomer resolved at ∼4.0 Å. Each luminal domain monomer exhibits two distinctive features: a hydrophobic helix (HH) positioned toward the ER bilayer and a ß-sandwich domain with structural similarity to lipid-binding proteins. This structure and our functional testing in cells suggest a model in which seipin oligomers initially detect forming LDs in the ER via HHs and subsequently act as membrane anchors to enable lipid transfer and LD growth.