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Post-COVID-19 conditions, also known as “long COVID”, has significantly impacted the lives of many individuals, but the risk factors for this condition are poorly understood. In this study, we performed a retrospective EHR analysis of 89,843 individuals at a multi-state health system in the United States with PCR-confirmed COVID-19, including 1,086 patients diagnosed with long COVID and 1,086 matched controls not diagnosed with long COVID. For these two cohorts, we evaluated a wide range of clinical covariates, including laboratory tests, medication orders, phenotypes recorded in the clinical notes, and outcomes. We found that chronic pulmonary disease (CPD) was significantly more common as a pre-existing condition for the long COVID cohort than the control cohort (odds ratio: 1.9, 95% CI: [1.5, 2.6]). Additionally, long-COVID patients were more likely to have a history of migraine (odds ratio: 2.2, 95% CI: [1.6, 3.1]) and fibromyalgia (odds ratio: 2.3, 95% CI: [1.3, 3.8]). During the acute infection phase, the following lab measurements were abnormal in the long COVID cohort: high triglycerides (meanlongCOVID: 278.5 mg/dL vs. meancontrol: 141.4 mg/dL), low HDL cholesterol levels (meanlongCOVID: 38.4 mg/dL vs. meancontrol: 52.5 mg/dL), and high neutrophil-lymphocyte ratio (meanlongCOVID: 10.7 vs. meancontrol: 7.2). The hospitalization rate during the acute infection phase was also higher in the long COVID cohort compared to the control cohort (ratelongCOVID: 5% vs. ratecontrol: 1%). Overall, this study suggests that the severity of acute infection and a history of CPD, migraine, CFS, or fibromyalgia may be risk factors for long COVID symptoms. Our findings motivate clinical studies to evaluate whether suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

The COVID-19 pandemic has seen the persistent emergence of immune-evasive SARS-CoV-2 variants under the selection pressure of natural and vaccination-acquired immunity. However, it is currently challenging to quantify how immunologically distinct a new variant is compared to all the prior variants to which a population has been exposed. Here, we define “Distinctiveness” of SARS-CoV-2 sequences based on a proteome-wide comparison with all prior sequences from the same geographical region. We observe a correlation between Distinctiveness relative to contemporary sequences and future change in prevalence of a newly circulating lineage (Pearson r = 0.75), suggesting that the Distinctiveness of emergent SARS-CoV-2 lineages is associated with their epidemiological fitness. We further show that the average Distinctiveness of sequences belonging to a lineage, relative to the Distinctiveness of other sequences that occur at the same place and time (n = 944 location/time data points), is predictive of future increases in prevalence (Area Under the Curve, AUC = 0.88 [95% confidence interval 0.86 to 0.90]). By assessing the Delta variant in India versus Brazil, we show that the same lineage can have different Distinctiveness-contributing positions in different geographical regions depending on the other variants that previously circulated in those regions. Finally, we find that positions that constitute epitopes contribute disproportionately (20-fold higher than the average position) to Distinctiveness. Overall, this study suggests that real-time assessment of new SARS-CoV-2 variants in the context of prior regional herd exposure via Distinctiveness can augment genomic surveillance efforts.

The emergence of a heavily mutated SARS-CoV-2 variant (Omicron; B.1.1.529/BA.1/BA.2) and its rapid spread globally created public health alarms. Characterizing the mutational profile of Omicron is necessary to interpret its shared or distinctive clinical phenotypes with other SARS-CoV-2 variants. We compared the mutations of Omicron with prior variants of concern (Alpha, Beta, Gamma, Delta), variants of interest (Lambda, Mu, Eta, Iota and Kappa), and ∼1500 SARS-CoV-2 lineages constituting ∼5.8 million SARS-CoV-2 genomes. Omicron’s Spike protein has 26 amino acid mutations (23 substitutions, two deletions and one insertion) that are distinct compared to other variants of concern. Whereas the substitution and deletion mutations have appeared in previous SARS-CoV-2 lineages, the insertion mutation (ins214EPE) has not been previously observed in any other SARS-CoV-2 lineage. Here, we discuss various mechanisms through which the nucleotide sequence encoding for ins214EPE could have been acquired and highlight the plausibility of template switching via either the human transcriptome or prior viral genomes. Analysis of homology of the inserted nucleotide sequence and flanking regions suggests that this template switching event could have involved the genomes of SARS-CoV-2 variants (e.g. B.1.1 strain), other human coronaviruses that infect the same host cells as SARS-CoV-2 (e.g. HCoV-OC43 or HCoV-229E), or a human transcript expressed in a host cell that was infected by the Omicron precursor. Whether ins214EPE impacts the epidemiological or clinical properties of Omicron (e.g. transmissibility) warrants further investigation. There is also a need to understand whether human host cells are being exploited by SARS-CoV-2 as an ‘evolutionary sandbox’ for inter-viral or host-virus genomic interplay to produce new SARS-CoV-2 variants.

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged and outcompeted previously circulating strains, resulting in repeated COVID-19 surges, reinfections, and breakthrough infections in vaccinated individuals. With over 5 million SARS-CoV-2 genomes sequenced globally over the last 2 years, there is unprecedented data to decipher how competitive viral evolution results in the emergence of fitter SARS-CoV-2 variants. Much attention has been directed to studying how specific mutations in the Spike protein impact its binding to the ACE2 receptor or viral neutralization by antibodies, but there is limited knowledge of a genomic signature that is shared primarily by the sequential dominant variants. Here we introduce a methodology to quantify the genome-wide distinctiveness of polynucleotide fragments of various lengths (3-to 240-mers) that constitute SARS-CoV-2 sequences (freely available at https://academia.nferx.com/GENI). Compared to standard phylogenetic distance metrics and overall mutational load, the quantification of distinctive 9-mer polynucleotides provides a higher resolution of separation between VOCs (Reference = 89, IQR: 65-108; Alpha = 166, IQR: 150-182; Beta 130, IQR: 113-147; Gamma = 165, IQR: 152-180; Delta = 234, IQR: 216-253; and Omicron = 294, IQR: 287-315). Omicron’s exceptionally high genomic distinctiveness may confer a competitive advantage over both prior VOCs (including Delta) and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Expanding on this analysis, evaluation of genomic distinctiveness weighted by intra-lineage 9-mer conservation for 1,363 lineages annotated in GISAID highlights that genomic distinctiveness has increased over time (R2=0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed till date. This study demonstrates the value of characterizing new SARS-CoV-2 variants by their genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known functionally or antigenically salient sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that real-time monitoring of genomic distinctiveness would aid in more rapid assessment of viral fitness.

An important aspect of cellular function is the correct targeting and delivery of newly synthesized proteins. Central to this task is the machinery of the Sec translocon, a transmembrane channel that is involved in both the translocation of nascent proteins across cell membranes and the integration of proteins into the membrane. Considerable experimental and computational effort has focused on the Sec translocon and its role in nascent protein biosynthesis, including the correct folding and expression of integral membrane proteins. However, the use of molecular simulation methods to explore Sec-facilitated protein biosynthesis is hindered by the large system sizes and long (i.e., minute) time scales involved. In this work, we describe the development and application of a coarse-grained simulation approach that addresses these challenges and allows for direct comparison with both in vivo and in vitro experiments. The method reproduces a wide range of experimental observations, providing new insights into the underlying molecular mechanisms, predictions for new experiments, and a strategy for the rational enhancement of membrane protein expression levels.

Acute cardiac injury has been observed in a subset of COVID-19 patients, but the molecular basis for this clinical phenotype is unknown. It has been hypothesized that molecular mimicry may play a role in triggering an autoimmune inflammatory reaction in some individuals after SARS-CoV-2 infection. Here we investigate if linear peptides contained in proteins that are primarily expressed in the heart also occur in the SARS-CoV-2 proteome. Specifically, we compared the library of 136,704 8-mer peptides from 144 human proteins (including splicing variants) to 9,926 8-mers from all 17 viral proteins in the reference SARS-CoV-2 proteome. No 8-mers were exactly identical between the reference human proteome and the reference SARS-CoV-2 proteome. However, there were 45 8-mers that differed by only one amino acid when compared to the reference SARS-CoV-2 proteome. Interestingly, analysis of protein-coding mutations from 141,456 individuals showed that one of these 8-mers from the SARS-CoV-2 Replicase polyprotein 1a/1ab (KIALKGGK) is identical to aMYH6peptide encoded by the c.5410C>A (Q1804K) genetic variation, which has been observed at low prevalence in Africans/African Americans (0.08%), East Asians (0.3%), South Asians (0.06%) and Latino/Admixed Americans (0.003%). Furthermore, analysis of 4.85 million SARS-CoV-2 genomes from over 200 countries shows that viral evolution has already resulted in 20 additional 8-mer peptides that are identical to human heart-enriched proteins encoded by reference sequences or genetic variants. Whether such mimicry contributes to cardiac inflammation during or after COVID-19 illness warrants further experimental evaluation. We suggest that SARS-CoV-2 variants harboring peptides identical to human cardiac proteins should be investigated as ‘viral variants of cardiac interest’.

Recent reports on waning of COVID-19 vaccine induced immunity have led to the approval and roll-out of additional dose and booster vaccinations. At risk individuals are receiving additional vaccine dose(s), in addition to the regimen that was tested in clinical trials. The risks and the adverse event profiles associated with these additional vaccine doses are currently not well understood. Here, we performed a retrospective study analyzing vaccine-associated adverse events using electronic health records (EHRs) of individuals that have received three doses of mRNA-based COVID-19 vaccines (n = 47,999). By comparing symptoms reported in 2-week time periods after each vaccine dose and in a 2-week period before the 1st vaccine dose, we assessed the risk associated with 3rd dose vaccination, for both BNT162b2 and mRNA-1273. Reporting of severe adverse events remained low after the 3rd vaccine dose, with rates of pericarditis (0.01%, 0%-0.02% 95% CI), anaphylaxis (0.00%, 0%-0.01% 95% CI), myocarditis (0.00%, 0%-0.01% 95% CI), and cerebral venous sinus thrombosis (no cases), consistent with earlier studies. Significantly more individuals (p-value < 0.05) report low-severity adverse events after their 3rd dose compared with after their 2nd dose, including fatigue (4.92% after 3rd dose vs 3.47% after 2nd dose), lymphadenopathy (2.89% vs 2.07%), nausea (2.62% vs 2.04%), headache (2.47% vs 2.07%), arthralgia (2.12% vs 1.70%), myalgia (1.99% vs 1.63%), diarrhea (1.70% vs 1.24%), fever (1.11% vs 0.81%), vomiting (1.10% vs 0.80%), and chills (0.47% vs 0.36%). Our results show that although 3rd dose vaccination against SARS-CoV-2 infection led to increased reporting of low-severity adverse events, risk of severe adverse events remained comparable to the standard 2-dose regime. This study provides support for the safety of 3rd vaccination doses of individuals that are at high-risk of severe COVID-19 and breakthrough infection.

SARS-CoV-2 breakthrough infections have been increasingly reported in fully vaccinated individuals. We conducted a test-negative case-control study to assess the durability of protection after full vaccination with BNT162b2, defined as 14 days after the second dose, against polymerase chain reaction (PCR)-confirmed symptomatic SARS-CoV-2 infection, in a national medical practice between February 1, 2021 and August 22, 2021. We fit conditional logistic regression (CLR) models stratified on residential county and calendar time of testing to assess the association between time elapsed since vaccination and the odds of symptomatic infection or non-COVID-19 hospitalization (negative control), adjusted for several covariates. The primary population included 652 individuals who had a positive symptomatic test after full vaccination with BNT162b2 (cases) and 5,946 individuals with at least one negative symptomatic test after full vaccination (controls). The adjusted odds of symptomatic infection were higher 120 days after full vaccination versus at the date of full vaccination (Odds Ratio [OR]: 3.21, 95% confidence interval [CI]: 1.33-7.74). Importantly, the odds of infection were still lower 150 days after the first BNT162b2 dose as compared to 4 days after the first dose (OR: 0.3, 95% CI: 0.19-0.45), when immune protection approximates the unvaccinated status. Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. The odds of experiencing a non-COVID-19 hospitalization decreased with time since vaccination, suggesting a possible underestimation of waning protection by this approach due to confounding factors. Taken together, these data constitute an early signal for waning protection against symptomatic illness while also providing reassurance that BNT162b2 continues to protect against symptomatic SARS-CoV-2 infection several months after full vaccination. Continued surveillance of COVID-19 vaccine durability, particularly against severe disease, is critical to guide effective and equitable strategies to respond to the pandemic, including distribution of booster doses, development of new vaccines, and implementation of both pharmaceutical and nonpharmaceutical interventions.

Although clinical trials and real-world studies have affirmed the effectiveness and safety of the FDA-authorized COVID-19 vaccines, reports of breakthrough infections and persistent emergence of new variants highlight the need to vigilantly monitor the effectiveness of these vaccines. Here we compare the effectiveness of two full-length Spike protein-encoding mRNA vaccines from Moderna (mRNA-1273) and Pfizer/BioNTech (BNT162b2) in the Mayo Clinic Health System over time from January to July 2021, during which either the Alpha or Delta variant was highly prevalent. We defined cohorts of vaccinated and unvaccinated individuals from Minnesota (n = 25,589 each) matched on age, sex, race, history of prior SARS-CoV-2 PCR testing, and date of full vaccination. Both vaccines were highly effective during this study period against SARS-CoV-2 infection (mRNA-1273: 86%, 95%CI: 81-90.6%; BNT162b2: 76%, 95%CI: 69-81%) and COVID-19 associated hospitalization (mRNA-1273: 91.6%, 95% CI: 81-97%; BNT162b2: 85%, 95% CI: 73-93%). However, in July, the effectiveness against infection was considerably lower for mRNA-1273 (76%, 95% CI: 58-87%) with an even more pronounced reduction in effectiveness for BNT162b2 (42%, 95% CI: 13-62%). Notably, the Delta variant prevalence in Minnesota increased from 0.7% in May to over 70% in July whereas the Alpha variant prevalence decreased from 85% to 13% over the same time period. Comparing rates of infection between matched individuals fully vaccinated with mRNA-1273 versus BNT162b2 across Mayo Clinic Health System sites in multiple states (Minnesota, Wisconsin, Arizona, Florida, and Iowa), mRNA-1273 conferred a two-fold risk reduction against breakthrough infection compared to BNT162b2 (IRR = 0.50, 95% CI: 0.39-0.64). In Florida, which is currently experiencing its largest COVID-19 surge to date, the risk of infection in July after full vaccination with mRNA-1273 was about 60% lower than after full vaccination with BNT162b2 (IRR: 0.39, 95% CI: 0.24-0.62). Our observational study highlights that while both mRNA COVID-19 vaccines strongly protect against infection and severe disease, further evaluation of mechanisms underlying differences in their effectiveness such as dosing regimens and vaccine composition are warranted. Declaration of Interests: AP, PJL, ES, MJN, JC, AJV, and VS are employees of nference and have financial interests in the company. nference is collaborating with Moderna, Pfizer, Janssen, and other bio-pharmaceutical companies on data science initiatives unrelated to this study. These collaborations had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. JCO receives personal fees from Elsevier and Bates College, and receives small grants from nference, Inc, outside the submitted work. ADB is supported by grants from NIAID (grants AI110173 and AI120698), Amfar (#109593), and Mayo Clinic (HH Shieck Khalifa Bib Zayed Al-Nahyan Named Professorship of Infectious Diseases). ADB is a paid consultant for Abbvie, Gilead, Freedom Tunnel, Pinetree therapeutics Primmune, Immunome and Flambeau Diagnostics, is a paid member of the DSMB for Corvus Pharmaceuticals, Equilium, and Excision Biotherapeutics, has received fees for speaking for Reach MD and Medscape, owns equity for scientific advisory work in Zentalis and nference, and is founder and President of Splissen Therapeutics. MDS received grant funding from Pfizer via Duke University for a vaccine side effect registry. JH, JCO, AV, MDS and ADB are employees of the Mayo Clinic. The Mayo Clinic may stand to gain financially from the successful outcome of the research. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and is being conducted in compliance with Mayo Clinic Conflict of Interest policies. Ethics Approval Statement: This study was reviewed and approved by the Mayo Clinic Institutional Review Board (IRB 20-003278) as a minimal risk study. The approved IRB was titled: Study of COVID-19 patient characteristics with augmented curation of Electronic Health Records (EHR) to inform strategic and operational decisions with the Mayo Clinic. The study was deemed exempt by the Mayo Clinic Institutional Review Board and waived from consent. The following resource provides further information on the Mayo Clinic Institutional Review Board and adherence to basic ethical principles underlying the conduct of research, and ensuring that the rights and well-being of potential research subjects are adequately protected: www.mayo.edu/research/institutional-review-board/overview.

Variants of SARS-CoV-2 are evolving under a combination of immune selective pressure in infected hosts and natural genetic drift, raising a global alarm regarding the durability of COVID-19 vaccines. Here, we conducted longitudinal analysis over 1.8 million SARS-CoV-2 genomes from 183 countries or territories to capture vaccination-associated viral evolutionary patterns. To augment this macroscale analysis, we performed viral genome sequencing in 23 vaccine breakthrough COVID-19 patients and 30 unvaccinated COVID-19 patients for whom we also conducted machine-augmented curation of the electronic health records (EHRs). Strikingly, we find the diversity of the SARS-CoV-2 lineages is declining at the country-level with increased rate of mass vaccination (n = 25 countries, mean correlation coefficient = −0.72, S.D. = 0.20). Given that the COVID-19 vaccines leverage B-cell and T-cell epitopes, analysis of mutation rates shows neutralizing B-cell epitopes to be particularly more mutated than comparable amino acid clusters (4.3-fold, p < 0.001). Prospective validation of these macroscale evolutionary patterns using clinically annotated SARS-CoV-2 whole genome sequences confirms that vaccine breakthrough patients indeed harbor viruses with significantly lower diversity in known B cell epitopes compared to unvaccinated COVID-19 patients (2.3-fold, 95% C.I. 1.4-3.7). Incidentally, in these study cohorts, vaccinated breakthrough patients also displayed fewer COVID-associated complications and pre-existing conditions relative to unvaccinated COVID-19 patients. This study presents the first known evidence that COVID-19 vaccines are fundamentally restricting the evolutionary and antigenic escape pathways accessible to SARS-CoV-2. The societal benefit of mass vaccination may consequently go far beyond the widely reported mitigation of SARS-CoV-2 infection risk and amelioration of community transmission, to include stemming of rampant viral evolution.

Force-sensitive arrest peptides regulate protein biosynthesis by stalling the ribosome as they are translated. Synthesis can be resumed when the nascent arrest peptide experiences a pulling force of sufficient magnitude to break the stall. Efficient stalling is dependent on the specific identity of a large number of amino acids, including amino acids which are tens of angstroms away from the peptidyl transferase center (PTC). The mechanism of force-induced restart and the role of these essential amino acids far from the PTC is currently unknown. We use hundreds of independent molecular dynamics trajectories spanning over 120 μs in combination with kinetic analysis to characterize the barriers along the force-induced restarting pathway for the arrest peptide SecM. We find that the essential amino acids far from the PTC play a major role in controlling the transduction of applied force. In successive states along the stall-breaking pathway, the applied force propagates up the nascent chain until it reaches the C-terminus of SecM and the PTC, inducing conformational changes that allow for restart of translation. A similar mechanism of force propagation through multiple states is observed in the VemP stall-breaking pathway, but secondary structure in VemP allows for heterogeneity in the order of transitions through intermediate states. Results from both arrest peptides explain how residues that are tens of angstroms away from the catalytic center of the ribosome impact stalling efficiency by mediating the response to an applied force and shielding the amino acids responsible for maintaining the stalled state of the PTC.Significance StatementAs nascent proteins are synthesized by the ribosome, their interactions with the environment can create pulling forces on the nascent protein that can be transmitted to the ribosome’s catalytic center. These forces can affect the rate and even the outcome of translation. We use simulations to characterize the pathway of force transduction along arrest peptides and discover how secondary structure in the nascent protein and its interactions with the ribosome exit tunnel impede force propagation. This explains how amino acids in arrest peptides that are tens of angstroms away from the ribosome’s catalytic center contribute to stalling, and, more broadly, suggests how structural features in the nascent protein dictate the ribosome’s ability to functionally respond to its environment.

The death toll of the COVID-19 pandemic has been unprecedented, due to both the high number of SARS-CoV-2 infections and the seriousness of the disease resulting from these infections. Here, we present mortality rates and case fatality rates for COVID-19 over the past year compared with other historic leading causes of death in the United States. Among the risk categories considered, COVID-19 is the third leading cause of death for individuals 40 years old and over, with an overall annual mortality rate of 325 deaths per 100K individuals, behind only cancer (385 deaths per 100K individuals) and heart disease (412 deaths per 100K individuals). In addition, for individuals 40 years old and over, the case fatality rate for COVID-19 is greater than the case fatality rate for motor vehicle accidents. In particular, for the age group 40-49, the relative case fatality rate of COVID-19 is 1.5 fold (95% CI: [1.3, 1.7]) that of a motor vehicle accident, demonstrating that SARS-CoV-2 infection may be significantly more dangerous than a car crash for this age group. For older adults, COVID-19 is even more dangerous, and the relative case fatality rate of COVID-19 is 29.4 fold (95% CI: [23.2, 35.7]) that of a motor vehicle accident for individuals over 80 years old. On the other hand, motor vehicle accidents have a 4.5 fold (95% CI: [3.9, 5.1]) greater relative case fatality rate compared to COVID-19 for the age group of 20-29 years. These results highlight the severity of the COVID-19 pandemic especially for adults above 40 years of age and underscore the need for large-scale preventative measures to mitigate risks for these populations. Given that FDA-authorized COVID-19 vaccines have now been validated by multiple studies for their outstanding real-world effectiveness and safety, vaccination of all individuals who are over 40 years of age is one of the most pressing public health priorities of our time.

The influenza B M2 protein forms a water-filled tetrameric channel to conduct protons across the lipid membrane. To understand how channel water mediates proton transport, we have investigated the water orientation and dynamics using solid-state NMR spectroscopy and molecular dynamics (MD) simulations. 13C-detected water 1H NMR relaxation times indicate that water has faster rotational motion in the low-pH open channel than in the high-pH closed channel. Despite this faster dynamics, the open-channel water shows higher orientational order, as manifested by larger motionally-averaged 1H chemical shift anisotropies. MD simulations indicate that this order is induced by the cationic proton-selective histidine at low pH. Furthermore, the water network has fewer hydrogen-bonding bottlenecks in the open state than in the closed state. Thus, faster dynamics and higher orientational order of water molecules in the open channel establish the water network structure that is necessary for proton hopping., To understand how water in the channel made of the influenza B M2 protein mediates proton transport across the lipid membrane, Gelenter et al. investigate the water orientation and dynamics. This study suggests that faster dynamics and higher orientational order of water molecules in the open channel compared to the closed one establish the water network structure that is necessary for proton hopping.

Background Two US Food and Drug Administration (FDA)-authorized coronavirus disease 2019 (COVID-19) mRNA vaccines, BNT162b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna), have demonstrated high efficacy in large phase 3 randomized clinical trials. It is important to assess their effectiveness in a real-world setting. Methods This is a retrospective analysis of 136,532 individuals in the Mayo Clinic health system (Arizona, Florida, Iowa, Minnesota, and Wisconsin) with PCR testing data between December 1, 2020 and April 20, 2021. We compared clinical outcomes for a vaccinated cohort of 68,266 individuals who received at least one dose of either vaccine (nBNT162b2 = 51,795; nmRNA-1273 = 16,471) and an unvaccinated control cohort of 68,266 individuals propensity matched based on relevant demographic, clinical, and geographic features. We estimated real-world vaccine effectiveness by comparing incidence rates of positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR testing and COVID-19-associated hospitalization and intensive care unit (ICU) admission starting 7 days after the second vaccine dose. Findings The real-world vaccine effectiveness of preventing SARS-CoV-2 infection was 86.1% (95% confidence interval [CI]: 82.4%–89.1%) for BNT162b2 and 93.3% (95% CI: 85.7%–97.4%) for mRNA-1273. BNT162b2 and mRNA-1273 were 88.8% (95% CI: 75.5%–95.7%) and 86.0% (95% CI: 71.6%–93.9%) effective in preventing COVID-19-associated hospitalization. Both vaccines were 100% effective (95% CIBNT162b2: 51.4%–100%; 95% CImRNA-1273: 43.3%–100%) in preventing COVID-19-associated ICU admission. Conclusions BNT162b2 and mRNA-1273 are effective in a real-world setting and are associated with reduced rates of SARS-CoV-2 infection and decreased burden of COVID-19 on the healthcare system. Funding This study was funded by nference., Graphical abstract, Context and significance This is a study of the COVID-19 vaccines developed by Pfizer/BioNTech and Moderna. Although these vaccines have been shown to be effective in clinical trials, it is important to confirm that they work well in practice. The results from this study show that these vaccines are effective in reducing the risk of COVID-19 infection, COVID-19-associated hospitalization, and COVID-19-associated ICU admission. As one of the largest real-world evidence studies of COVID-19 vaccine effectiveness in the United States to date, this study provides strong evidence that COVID-19 vaccines work well in practice., Pawlowski et al. assess the real-world effectiveness of the BNT162b2 and mRNA-1273 COVID-19 vaccines among 136,532 individuals. They compare infection, hospitalization, and ICU admission rates between vaccinated and propensity-matched unvaccinated individuals. They find that both vaccines protect against SARS-CoV-2 infection and severe COVID-19.

Large Phase 3 clinical trials of the two FDA-authorized COVID-19 vaccines, mRNA-1273 (Moderna) and BNT162b2 (Pfizer/BioNTech), have demonstrated efficacies of 94.1% (n = 30,420, 95% CI: 89.3-96.8) and 95% (n = 43,448, 95% CI: 90.3-97.6) in preventing symptomatic COVID-19, respectively. Given the ongoing vaccine rollout to healthcare personnel and residents of long-term care facilities, here we provide a preliminary assessment of real-world vaccination efficacy in 62,138 individuals from the Mayo Clinic and associated health system (Arizona, Florida, Minnesota, Wisconsin) between December 1st2020 and February 8th2021. Our retrospective analysis contrasts 31,069 individuals receiving at least one dose of either vaccine with 31,069 unvaccinated individuals who are propensity-matched based on demographics, location (zip code), and number of prior SARS-CoV-2 PCR tests. 8,041 individuals received two doses of a COVID-19 vaccine and were at risk for infection at least 36 days after their first dose. Administration of two COVID-19 vaccine doses was 88.7% effective in preventing SARS-CoV-2 infection (95% CI: 68.4-97.1%) with onset at least 36 days after the first dose. Furthermore, vaccinated patients who were subsequently diagnosed with COVID-19 had significantly lower 14-day hospital admission rates than propensity-matched unvaccinated COVID-19 patients (3.7% vs. 9.2%; Relative Risk: 0.4; p-value: 0.007). Building upon the previous randomized trials of these vaccines, this study demonstrates their real-world effectiveness in reducing the rates of SARS-CoV-2 infection and COVID-19 severity among individuals at highest risk for infection.

Importance: Over the past year, the COVID-19 pandemic has resulted in the deaths of more than 550,000 individuals in the United States. It is important for us to understand the risks of COVID-19 in relation to other leading causes of death in order to inform public policy decisions and individual behaviors to help mitigate the highest risks. Objective: Contrast COVID-19 with historic leading causes of death. Design: We present mortality rates and case fatality rates for COVID-19 from March 2020 to March 2021 compared with other historic leading causes of death in the United States. For each risk category and 10-year age groups (0-9, 10-19, …, 70-79, ≥ 80), we report the overall mortality and case fatality rates along with the relative risks compared to COVID-19 as a baseline. There were 16 other leading causes of death considered in this analysis, including: cancer, various subtypes of cancer (brain / nervous system, breast, lung / bronchus, pancreatic, prostate, leukemia, lymphoma), cerebrovascular disease, drug overdoses, firearm homicide, heart diseases, influenza, motor vehicle accidents (overall and without restraint), and suicide. Setting: This is a population-based study. Participants: N/A. Exposures: N/A. Main Outcomes and Measures: Overall mortality (number of deaths / population) and case fatality rates (number of deaths / number of cases). Results: COVID-19 is the third leading cause of death for individuals over 40 years old, with an annual mortality rate of 325 deaths/100K, behind only cancer (385 deaths/100K) and heart disease (412 deaths/100K). In addition, for individuals over 40 years old, the case fatality rate for COVID-19 is greater than the case fatality rate for motor vehicle accidents. For the age group 40-49 years old, the relative case fatality rate for COVID-19 is 1.5 fold (95% CI: [1.3,1.7]) that of motor vehicle accidents, and this relative risk increases to 29.4 fold (95% CI: [23.2, 35.7]) for individuals over 80 years old. Conclusions and Relevance: These results highlight the severity of the COVID-19 pandemic especially for adults over 40 years old and underscore the need for large-scale preventative measures to mitigate risks for these populations. Funding Statement: This work was supported by Nference, Inc. Declaration of Interests: None reported.

International audience; The water dynamics, as characterized by the local hydrophobicity (LH), is investigated for tetrameric hemoglobin (Hb) and dimeric melittin. For the T0 to R0 transition in Hb, it is found that LH provides additional molecular-level insight into the Perutz mechanism, i.e., the breaking and formation of salt bridges at the α1/β2 and α2/β1 interface is accompanied by changes in LH. For Hb in cubic water boxes with 90 and 120 Å edge length it is observed that following a decrease in LH as a consequence of reduced water density or change of water orientation at the protein/water interface the α/β interfaces are destabilized; this is a hallmark of the Perutz stereochemical model for the T to R transition in Hb. The present work thus provides a dynamical view of the classical structural model relevant to the molecular foundations of Hb function. For dimeric melittin, earlier results by Cheng and Rossky [ Nature 1998, 392, 696−699] are confirmed and interpreted on the basis of LH from simulations in which the protein structure is frozen. For the flexible melittin dimer, the changes in the local hydration can be as much as 30% greater than for the rigid dimer, reflecting the fact that protein and water dynamics are coupled.

Background mRNA COVID-19 vaccines are safe and effective, but increasing reports of breakthrough infections highlight the need to vigilantly monitor and compare the effectiveness of these vaccines. Methods We retrospectively compared protection against symptomatic infection conferred by mRNA-1273 and BNT162b2 at Mayo Clinic sites from December 2020 to September 2021. We used a test-negative case-control design to estimate vaccine effectiveness (VE) and to compare the odds of symptomatic infection after full vaccination with mRNA-1273 versus BNT162b2, while adjusting for age, sex, race, ethnicity, geography, comorbidities, and calendar time of vaccination and testing. Findings Both vaccines were highly effective over the study duration (VEmRNA-1273: 84.1%, 95% CI: 81.6-86.2%; VEBNT162b2: 75.6%, 95% CI: 72.2-78.7%), but their effectiveness was reduced during July-September (VEmRNA-1273: 75.6%, 95% CI: 70.1-80%; VEBNT162b2: 63.5%, 95% CI: 55.8-69.9%) as compared to December-May (VEmRNA-1273: 93.7%, 95% CI: 90.4-95.9%; VEBNT162b2: 85.7%, 95% CI: 81.4-88.9%). Adjusted for demographic characteristics, clinical comorbidities, time of vaccination, and time of testing, the odds of experiencing a symptomatic breakthrough infection were lower after full vaccination with mRNA-1273 than with BNT162b2 (Odds Ratio: 0.60, 95% CI: 0.55-0.67). Conclusions Both mRNA-1273 and BNT162b2 strongly protect against symptomatic SARS-CoV-2 infection. It is imperative to continue monitoring and comparing available vaccines over time and with respect to emerging variants to inform public and global health decisions., Graphical Abstract, Puranik et al. compare the real world effectiveness of BNT162b2 and mRNA-1273 in a population of over 180,000 vaccinated individuals. While both vaccines strongly protected against symptomatic infection, their effectiveness declined in recent months. Throughout the study period, mRNA-1273 recipients had lower rates of COVID-19 diagnosis than BNT162b2 recipients.

SummaryIntegral membrane proteins (IMPs) control the flow of information and nutrients across cell membranes, yet IMP mechanistic studies are hindered by difficulties in expression. We investigate this issue by addressing the connection between IMP sequence and observed expression levels. For homologs of the IMP TatC, observed expression levels vary widely and are affected by small changes in protein sequence. The effect of sequence changes on experimentally observed expression levels strongly correlates with the simulated integration efficiency obtained from coarse-grained modeling, which is directly confirmed using an in vivo assay. Furthermore, mutations that improve the simulated integration efficiency likewise increase the experimentally observed expression levels. Demonstration of these trends in both Escherichia coli and Mycobacterium smegmatis suggests that the results are general to other expression systems. This work suggests that IMP integration is a determinant for successful expression, raising the possibility of controlling IMP expression via rational design.

During ribosomal translation, nascent polypeptide chains (NCs) undergo a variety of physical processes that determine their fate in the cell. This study utilizes a combination of arrest peptide (AP) experiments and coarse-grained molecular dynamics (CGMD) to measure and elucidate the molecular origins of forces that are exerted on NCs during co-translational membrane insertion and translocation via the Sec translocon. The approach enables deconvolution of force contributions from NC-translocon and NC-ribosome interactions, membrane partitioning, and electrostatic coupling to the membrane potential. In particular, we show that forces due to NC-lipid interactions provide a read-out of conformational changes in the Sec translocon, demonstrating that lateral gate opening only occurs when a sufficiently hydrophobic segment of NC residues reaches the translocon. The combination of experiment and theory introduced here provides a detailed picture of the molecular interactions and conformational changes during ribosomal translation that govern protein biogenesis.

The heterologous overexpression of integral membrane proteins in Escherichia coli often yields insufficient quantities of purifiable protein for applications of interest. The current study leverages a recently demonstrated link between co-translational membrane integration efficiency and protein expression levels to predict protein sequence modifications that improve expression. Membrane integration efficiencies, obtained using a coarse-grained simulation approach, robustly predicted effects on expression of the integral membrane protein TatC for a set of 140 sequence modifications, including loop-swap chimeras and single-residue mutations distributed throughout the protein sequence. Mutations that improve simulated integration efficiency were 4-fold enriched with respect to improved experimentally observed expression levels. Furthermore, the effects of double mutations on both simulated integration efficiency and experimentally observed expression levels were cumulative and largely independent, suggesting that multiple mutations can be introduced to yield higher levels of purifiable protein. This work provides a foundation for a general method for the rational overexpression of integral membrane proteins based on computationally simulated membrane integration efficiencies.

We present a coarse-grained simulation model that is capable of simulating the minute-timescale dynamics of protein translocation and membrane integration via the Sec translocon, while retaining sufficient chemical and structural detail to capture many of the sequence-specific interactions that drive these processes. The model includes accurate geometric representations of the ribosome and Sec translocon, obtained directly from experimental structures, and interactions parameterized from nearly 200 μs of residue-based coarse-grained molecular dynamics simulations. A protocol for mapping amino-acid sequences to coarse-grained beads enables the direct simulation of trajectories for the co-translational insertion of arbitrary polypeptide sequences into the Sec translocon. The model reproduces experimentally observed features of membrane protein integration, including the efficiency with which polypeptide domains integrate into the membrane, the variation in integration efficiency upon single amino-acid mutations, and the orientation of transmembrane domains. The central advantage of the model is that it connects sequence-level protein features to biological observables and timescales, enabling direct simulation for the mechanistic analysis of co-translational integration and for the engineering of membrane proteins with enhanced membrane integration efficiency., Author summary Ubiquitous across all kingdoms of life, the Sec translocon is an essential piece of molecular machinery for protein biosynthesis. The translocon is a transmembrane channel that enables the secretion of newly synthesized proteins across the lipid membrane, as well as the integration of protein domains into the membrane interior. Understanding the function and regulation of the translocon is necessary for developing a refined view of early stage protein folding and targeting in the cell. Although computational methods are well suited to elucidating the interactions of the translocon with newly synthesized proteins, conventional simulation techniques are unable to reach the exceedingly long timescales (i.e., minutes) that are relevant for protein biosynthesis. In this work, we present a novel coarse-grained approach that realistically models the ribosome/translocon/nascent-protein complex, while also allowing for the efficient simulation of biological timescales. The coarse-grained model is parameterized on the basis of extensive molecular dynamics simulations and enables the simulation of any nascent protein with only amino-acid sequence information as input. To validate the model, we perform over 26,000 simulations of protein biosynthesis, enabling direct comparison and demonstrating good agreement with a range of experimental studies describing this minute-timescale process.

We present a critical assessment of the performance of our homology model refinement method for G protein-coupled receptors (GPCRs), called LITICon that led to top ranking structures in a recent structure prediction assessment GPCRDOCK2010. GPCRs form the largest class of drug targets for which only a few crystal structures are currently available. Therefore, accurate homology models are essential for drug design in these receptors. We submitted five models each for human chemokine CXCR4 (bound to small molecule IT1t and peptide CVX15) and dopamine D3DR (bound to small molecule eticlopride) before the crystal structures were published. Our models in both CXCR4/IT1t and D3/eticlopride assessments were ranked first and second, respectively, by ligand RMSD to the crystal structures. For both receptors, we developed two types of protein models: homology models based on known GPCR crystal structures, and ab initio models based on the prediction method MembStruk. The homology-based models compared better to the crystal structures than the ab initio models. However, a robust refinement procedure for obtaining high accuracy structures is needed. We demonstrate that optimization of the helical tilt, rotation, and translation is vital for GPCR homology model refinement. As a proof of concept, our in-house refinement program LITiCon captured the distinct orientation of TM2 in CXCR4, which differs from that of adrenoreceptors. These findings would be critical for refining GPCR homology models in future.

Internal coordinate molecular dynamics (ICMD) methods provide a more natural description of a protein by using bond, angle, and torsional coordinates instead of a Cartesian coordinate representation. Freezing high-frequency bonds and angles in the ICMD model gives rise to constrained ICMD (CICMD) models. There are several theoretical aspects that need to be developed to make the CICMD method robust and widely usable. In this article, we have designed a new framework for (1) initializing velocities for nonindependent CICMD coordinates, (2) efficient computation of center of mass velocity during CICMD simulations, (3) using advanced integrators such as Runge–Kutta, Lobatto, and adaptive CVODE for CICMD simulations, and (4) cancelling out the “flying ice cube effect” that sometimes arises in Nose–Hoover dynamics. The Generalized Newton–Euler Inverse Mass Operator (GNEIMO) method is an implementation of a CICMD method that we have developed to study protein dynamics. GNEIMO allows for a hierarchy of coarse-grained simulation models based on the ability to rigidly constrain any group of atoms. In this article, we perform tests on the Lobatto and Runge–Kutta integrators to determine optimal simulation parameters. We also implement an adaptive coarse-graining tool using the GNEIMO Python interface. This tool enables the secondary structure-guided “freezing and thawing” of degrees of freedom in the molecule on the fly during molecular dynamics simulations and is shown to fold four proteins to their native topologies. With these advancements, we envision the use of the GNEIMO method in protein structure prediction, structure refinement, and in studying domain motion. © 2013 Wiley Periodicals, Inc.

Integration into the cell membrane is a key step in the biogenesis of membrane proteins. Membrane protein integration takes place at the Sec translocon and typically occurs during the ribosomal translation of the protein sequence. The study of Sec-facilitated membrane protein integration is difficult due to the roles of long-timescale dynamics and ribosomal translation. We present a coarse-grained (CG) simulation approach that is capable of reaching the experimentally relevant (i.e., minute) timescales, while retaining the level of detail required to capture amino-acid sequence level properties. The CG model enables direct simulation of co-translational integration at the Sec translocon and analysis of the resulting trajectories provides mechanistic explanations for observed experimental data. We demonstrate the use of the developed CG model to investigate the experimentally observed forces exerted on a nascent protein during co-translational membrane integration. It has been observed experimentally that the force exerted on the nascent protein depends on various factors, including the number of amino-acids that have been translated, nascent protein charge, and nascent protein hydrophobicity. Importantly, the CG model captures the effect of these factors on the force exerted on the nascent protein, enabling further analysis of the calculated trajectories to determine how the observed forces relate to the underlying physical process.

In many cases, the topology of membrane proteins is established during co-translational membrane integration. This process involves the Sec translocon, a heterotrimeric protein-conducting channel that allows for both the translocation of secreted domains across the membrane through the central pore and the integration of membrane domains directly into the lipid bilayer through a lateral opening. For many proteins, the N-terminus is retained on the cytosolic side of the membrane and forms an inverted (type II) topology that threads the C-terminus through the channel. This inverted topology is hypothesized to involve a head-first intermediate which then undergoes a step-wise inversion process to its final topology. We use a newly developed coarse-grained model to simulate the integration of the signal sequence during the elongation of the nascent chain on the minute-long timescales that are relevant to the biological process. This coarse-grained simulation method enables direct comparisons to experimentally measured energetics of ribosome-nascent chain to translocon interactions. We observe a series of pulling and pushing forces on the ribosome-nascent chain as translation proceeds and identify a head-first intermediate whose inversion is driven by the entropic confinement of nascent chain residues in the ribosome-translocon junction.

G-protein coupled receptors (GPCRs) are allosteric membrane proteins mediating cellular signaling. GPCRs exhibit multiple inactive and active conformations, and the population balance between these conformations is altered upon binding of signaling molecules (or ligands). However, the nature of the conformational ensemble or the mechanism of the conformational transitions is not well understood. We have applied a multiscale computational approach combining a coarse-grained discrete conformational sampling method with fine-grained molecular dynamics to investigate the effect of various ligands binding on the ensemble of conformations sampled by human β2-adrenergic receptor (β2AR). We show that the receptor, in the absence of any ligand, samples an extensive conformational space that includes breathing of the orthosteric ligand binding site and shear motion of the transmembrane helices 5 and 6 against the other helices. The shear motion is similar to the reorganization of the intracellular regions of TM3, TM5, and TM6 observed in the crystal structure of the active state of GPCRs. Upon ligand binding a shift in population density, as well as a reduction in the number of conformations sampled by the receptor is observed. Binding of agonist norepinephrine or partial agonist salbutamol leads to the selection of a subset of conformations that include both active and inactive state conformations, while inverse agonist carazolol selects only the inactive state conformation. Possible mechanisms for the allosteric regulation of GPCR activity by ligand binding were identified by correlating receptor-ligand interactions with receptor sidechain orientation near the G-Protein coupling region.

G-protein coupled receptors (GPCRs) are allosteric membrane proteins mediating cellular signaling. GPCRs exhibit multiple inactive and active conformations, and the population balance between these conformations is altered upon binding of signaling molecules (or ligands). However, the nature of the conformational ensemble or the mechanism of the conformational transitions is not well understood. We present a multiscale computational approach combining a coarse-grained discrete conformational sampling method with fine-grained molecular dynamics investigating the effect of various ligands binding on the ensemble of conformations sampled by human β2-adrenergic receptor (β2AR). We show that the receptor, in the absence of any ligand, samples an extensive conformational space that includes breathing of the orthosteric ligand binding site and shear motion of the transmembrane helices 5 and 6 against the other helices. The shear motion is similar to the reorganization of the intracellular regions of TM3, TM5, and TM6 observed in the crystal structure of the active state of GPCRs. The binding of agonist norepinephrine or partial agonist salbutamol leads to the selection of a subset of conformations including active and inactive state conformations, while inverse agonist carazolol selects only inactive state conformations. The dynamics of water observed during the simulations provides an explanation for the conformational changes observed in the solution-based fluorescence spectroscopic measurements on agonist activated β2AR, which could not be explained by the agonist bound β2AR crystal structure. This study shows that the receptor activation depends on both the low energy states and the range of the conformations sampled by the receptor.

The regulation of binding of G-actin to cytoplasmic domains of cell surface receptors is a common mechanism to control diverse biological processes. To model the regulation of G-actin binding to a cell surface receptor we used the cell-cell adhesion molecule carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1-S) in which G-actin binds to its short cytoplasmic domain (12 amino acids; Chen, C. J., Kirshner, J., Sherman, M. A., Hu, W., Nguyen, T., and Shively, J. E. (2007) J. Biol. Chem. 282, 5749-5760). A liposome model system demonstrates that G-actin binds to the cytosolic domain peptide of CEACAM1-S in the presence of negatively charged palmitoyl-oleoyl phosphatidylserine (POPS) liposomes and Ca(2+). In contrast, no binding of G-actin was observed in palmitoyl-oleoyl phosphatidylcholine (POPC) liposomes or when a key residue in the peptide, Phe-454, is replaced with Ala. Molecular Dynamics simulations on CEACAM1-S in an asymmetric phospholipid bilayer show migration of Ca(2+) ions to the lipid leaflet containing POPS and reveal two conformations for Phe-454 explaining the reversible availability of this residue for G-actin binding. NMR transverse relaxation optimized spectroscopic analysis of (13)C-labeled Phe-454 CEACAM1-S peptide in liposomes plus actin further confirmed the existence of two peptide conformers and the Ca(2+) dependence of actin binding. These findings explain how a receptor with a short cytoplasmic domain can recruit a cytosolic protein in a phospholipid and Ca(2+)-specific manner. In addition, this model system provides a powerful approach that can be applied to study other membrane protein interactions with their cytosolic targets.

Predicting accurate ligand poses and ligand selective receptor conformations are imperative in designing efficacious, functionally specific drugs for G-protein coupled receptors. Comparison of the crystal structures of carazolol (inverse agonist), formoterol(agonist), and agonist with G-protein mimic bound β2 Adrenergic Receptor (β2AR) shows that the agonist stabilizes a slightly different conformation when there is no G-protein bound. The G-protein bound receptor state exhibits a high affinity conformation for the agonist. Using the computational method LITiCon, we have calculated the activation pathways for full, partial and inverse agonists of β2AR, which are in agreement with fluorescence intensity lifetime measurements. MD simulations starting from various conformations along the activation pathway (total ∼1.5 μs) show that in the absence of G protein, norepinephrine (agonist) stabilizes an intermediate receptor state that is similar to the formoterol bound intermediate state without the G-protein, in agreement with the recent crystal structure of formoterol bound β2AR. Thus coupling to G protein may be needed for stabilizing the fully active state.Using Liticon method we have calculated the activation pathway of agonist bound adenosine receptor A2A starting from its inactive state. We found that water plays a important role in the docking of the antagonist as well as the agonist.We recently predicted the structures of D3 dopamine receptor and CXCR4 chemokine receptor as part of the competition for the assessment of computational methods in GPCR modeling (GPCR Dock 2010). The predicted docked poses of both the ligands are in close agreement with the crystal structures. The details of the methods and comparison with the crystal structures will be presented.

Integration into the cell membrane in the correctly folded structure is essential for membrane protein function. Membrane protein integration takes place at the Sec-translocon and typically occurs during translation of the protein sequence. Although extensive structural data is available, study of the dynamics of Sec-facilitated membrane protein integration is difficult due to roles of long-timescale dynamics and ribosomal translation. We present a coarse grain simulation approach that is capable of reaching the experimentally relevant (i.e., minute) timescales, while retaining the level of detail required for reproducing available experimental data. The CG model enables direct simulation of the dynamics of co-translational integration at the Sec-translocon and analysis of the resulting trajectories provides mechanistic explanations for observed experimental data. We will demonstrate use of this CG model to investigate thermodynamic and kinetic factors that govern membrane protein topology, integration efficiency of trans-membrane domains, and hydrophilic loop translocation.