Predictive evolutionary modelling for influenza virus by site-based dynamics of mutations.

Influenza virus continuously evolves to escape human adaptive immunity and generates seasonal epidemics. Therefore, influenza vaccine strains need to be updated annually for the upcoming flu season to ensure vaccine effectiveness. We develop a computational approach, beth-1, to forecast virus evolution and select representative virus for influenza vaccine. The method involves modelling site-wise mutation fitness. Informed by virus genome and population sero-positivity, we calibrate transition time of mutations and project the fitness landscape to future time, based on which beth-1 selects the optimal vaccine strain. In season-to-season prediction in historical data for the influenza A pH1N1 and H3N2 viruses, beth-1 demonstrates superior genetic matching compared to existing approaches. In prospective validations, the model shows superior or non-inferior genetic matching and neutralization against circulating virus in mice immunization experiments compared to the current vaccine. The method offers a promising and ready-to-use tool to facilitate vaccine strain selection for the influenza virus through capturing heterogeneous evolutionary dynamics over genome space-time and linking molecular variants to population immune response.

A jingmenvirus RNA-dependent RNA polymerase structurally resembles the flavivirus counterpart but with different features at the initiation phase.

Jingmenviruses are a category of emerging segmented viruses that have garnered global attention in recent years, and are close relatives of the flaviviruses in the Flaviviridae family. One of their genome segments encodes NSP1 homologous to flavivirus NS5. NSP1 comprises both the methyltransferase (MTase) and RNA-dependent RNA polymerase (RdRP) modules playing essential roles in viral genome replication and capping. Here we solved a 1.8-Å resolution crystal structure of the NSP1 RdRP module from Jingmen tick virus (JMTV), the type species of jingmenviruses. The structure highly resembles flavivirus NS5 RdRP despite a sequence identity less than 30%. NSP1 RdRP enzymatic properties were dissected in a comparative setting with several representative Flaviviridae RdRPs included. Our data indicate that JMTV NSP1 produces characteristic 3-mer abortive products similar to the hepatitis C virus RdRP, and exhibits the highest preference of terminal initiation and shorter-primer usage. Unlike flavivirus NS5, JMTV RdRP may require the MTase for optimal transition from initiation to elongation, as an MTase-less NSP1 construct produced more 4-5-mer intermediate products than the full-length protein. Taken together, this work consolidates the evolutionary relationship between the jingmenvirus group and the Flaviviridae family, providing a basis to the further understanding of their viral replication/transcription process.

SARS-CoV-2 RNA-Dependent RNA Polymerase Follows Asynchronous Translocation Pathway for Viral Transcription and Replication.

Translocation is one essential step for the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) to exert viral replication and transcription. Although cryo-EM structures of SARS-CoV-2 RdRp are available, the molecular mechanisms of dynamic translocation remain elusive. Herein, we constructed a Markov state model based on extensive molecular dynamics simulations to elucidate the translocation dynamics of the SARS-CoV-2 RdRp. We identified two intermediates that pinpoint the rate-limiting step of translocation and characterize the asynchronous movement of the template-primer duplex. The 3'-terminal nucleotide in the primer strand lags behind due to the uneven distribution of protein-RNA interactions, while the translocation of the template strand is delayed by the hurdle residue K500. Even so, the two strands share the same "ratchet" to stabilize the polymerase in the post-translocation state, suggesting a Brownian-ratchet model. Overall, our study provides intriguing insights into SARS-CoV-2 replication and transcription, which would open a new avenue for drug discoveries.

Rapid microfluidics prototyping through variotherm desktop injection molding for multiplex diagnostics.

In this work, we demonstrate an inexpensive method of prototyping microfluidics using a desktop injection molding machine. A centrifugal microfluidic device with a novel central filling mechanism was developed to demonstrate the technique. We overcame the limitations of desktop machines in replicating microfluidic features by variotherm heating and cooling the mold between 50 °C and 110 °C within two minutes. Variotherm heating enabled good replication of microfeatures, with a coefficient of variation averaging only 3.6% attained for the measured widths of 100 µm wide molded channels. Using this methodology, we produced functional polystyrene centrifugal microfluidic chips, capable of aliquoting fluids into 5.0 µL reaction chambers with 97.5% accuracy. We performed allele-specific loop-mediated isothermal amplification (AS-LAMP) reactions for genotyping CYP2C19 alleles on these chips. Readouts were generated using optical pH sensors integrated onto chips, by drop-casting sensor precursor solutions into reaction chambers before final chip assembly. Positive reactions could be discerned by decreases in pH sensor fluorescence, thresholded against negative control reactions lacking the primers for nucleic acid amplification and with time-to-results averaging 38 minutes. Variotherm desktop injection molding can enable researchers to prototype microfluidic devices more cost-effectively, in an iterative fashion, due to reduced costs of smaller, in-house molds. Designs prototyped this way can be directly translated to mass production, enhancing their commercialization potential and positive impacts.

Predicting the antigenic evolution of SARS-COV-2 with deep learning.

The relentless evolution of SARS-CoV-2 poses a significant threat to public health, as it adapts to immune pressure from vaccines and natural infections. Gaining insights into potential antigenic changes is critical but challenging due to the vast sequence space. Here, we introduce the Machine Learning-guided Antigenic Evolution Prediction (MLAEP), which combines structure modeling, multi-task learning, and genetic algorithms to predict the viral fitness landscape and explore antigenic evolution via in silico directed evolution. By analyzing existing SARS-CoV-2 variants, MLAEP accurately infers variant order along antigenic evolutionary trajectories, correlating with corresponding sampling time. Our approach identified novel mutations in immunocompromised COVID-19 patients and emerging variants like XBB1.5. Additionally, MLAEP predictions were validated through in vitro neutralizing antibody binding assays, demonstrating that the predicted variants exhibited enhanced immune evasion. By profiling existing variants and predicting potential antigenic changes, MLAEP aids in vaccine development and enhances preparedness against future SARS-CoV-2 variants.

Effectiveness of heterologous and homologous covid-19 vaccine regimens: living systematic review with network meta-analysis.

OBJECTIVE: To evaluate the effectiveness of heterologous and homologous covid-19 vaccine regimens with and without boosting in preventing covid-19 related infection, hospital admission, and death. DESIGN: Living systematic review and network meta-analysis. DATA SOURCES: World Health Organization covid-19 databases, including 38 sources of published studies and preprints. STUDY SELECTION: Randomised controlled trials, cohort studies, and case-control studies. METHODS: 38 WHO covid-19 databases were searched on a weekly basis from 8 March 2022 to 31 July 2022. Studies that assessed the effectiveness of heterologous and homologous covid-19 vaccine regimens with or without a booster were identified. Studies were eligible when they reported the number of documented, symptomatic, severe covid-19 infections, covid-19 related hospital admissions, or covid-19 related deaths among populations that were vaccinated and unvaccinated. The primary measure was vaccine effectiveness calculated as 1−odds ratio. Secondary measures were surface under the cumulative ranking curve (SUCRA) scores and the relative effects for pairwise comparisons. The risk of bias was evaluated by using the risk of bias in non-randomised studies of interventions (ROBINS-I) tool for all cohort and case-control studies. The Cochrane risk of bias tool (version 2; ROB-2) was used to assess randomised controlled trials. RESULTS: The second iteration of the analysis comprised 63 studies. 25 combinations of covid-19 vaccine regimens were identified, of which three doses of mRNA vaccine were found to be 93% (95% credible interval 70% to 98%) effective against asymptomatic or symptomatic covid-19 infections for non-delta or non-omicron related infections. Heterologous boosting using two dose adenovirus vector vaccines with one dose mRNA vaccine showed a vaccine effectiveness of 94% (72% to 99%) against non-delta or non-omicron related asymptomatic or symptomatic infections. Three doses of mRNA vaccine were found to be the most effective in reducing non-delta or non-omicron related hospital admission (96%, 82% to 99%). The vaccine effectiveness against death in people who received three doses of mRNA vaccine remains uncertain owing to confounders. The estimate for a four dose mRNA vaccine regimen was of low certainty, as only one study on the effectiveness of four doses could be included in this update. More evidence on four dose regimens will be needed to accurately assess the effectiveness of a fourth vaccine dose. For people with delta or omicron related infection, a two dose regimen of an adenovirus vector vaccine with one dose of mRNA booster was 77% (42% to 91%) effective against asymptomatic or symptomatic covid-19 infections, and a three dose regimen of a mRNA vaccine was 93% (76% to 98%) effective against covid-19 related hospital admission. CONCLUSION: An mRNA booster is recommended to supplement any primary vaccine course. Heterologous and homologous three dose regimens work comparably well in preventing covid-19 infections, even against different variants. The effectiveness of three dose vaccine regimens against covid-19 related death remains uncertain. SYSTEMATIC REVIEW REGISTRATION: This review was not registered. The protocol is included in the supplementary document. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 1 of the original article published on 31 May 2022 (BMJ 2022;377:e069989), and previous versions can be found as data supplements (https://www.bmj.com/content/377/bmj-2022-069989/related). When citing this paper please consider adding the version number and date of access for clarity.

Uncovering mechanisms of RT-LAMP colorimetric SARS-CoV-2 detection to improve assay reliability.

Improved diagnostics are needed to manage the ongoing COVID-19 pandemic. In this study, we enhanced the color changes and sensitivity of colorimetric SARS-CoV-2 RT-LAMP assays based on triarylmethane dyes. We determined a mechanism for the color changes and obtained sensitivities of 10 RNA copies per microliter.

Diagnostic performances of common nucleic acid tests for SARS-CoV-2 in hospitals and clinics: a systematic review and meta-analysis.

BACKGROUND: An optimised standard experimental setup across different hospitals is urgently needed to ensure consistency in nucleic acid test results for SARS-CoV-2 detection. A standard comparison across different nucleic acid tests and their optimal experimental setups is not present. We assessed the performance of three common nucleic acid tests, namely digital PCR (dPCR), quantitative PCR (qPCR), and loop-mediated isothermal amplification (LAMP), to detect SARS-CoV-2 in clinical settings. METHODS: In this systematic review and meta-analysis we compared sensitivity and specificity of qPCR, dPCR, and LAMP and their performances when different experimental setups (namely specimen type used, use of RNA extraction, primer-probe sets, and RNA extraction methods) are applied. We searched PubMed, BioRxiv, MedRxiv, SciFinder, and ScienceDirect for studies and preprints published between Feb 29 and Dec 15, 2020. Included dPCR, qPCR, and LAMP studies using any type of human specimens should report the number of true-positive, true-negative, false-positive, and false-negative cases with Emergency Use Authorization (EUA)-approved PCR assays as the comparator. Studies with a sample size of less than ten, descriptive studies, case studies, reviews, and duplicated studies were excluded. Pooled sensitivity and specificity were computed from the true and false positive and negative cases using Reitsma's bivariate random-effects and bivariate latent class models. Test performance reported in area under the curve (AUC) of the three nucleic acid tests was further compared by pooling studies with similar experimental setups (eg, tests that used RNA extracted pharyngeal swabs but with either the open reading frame 1ab or the N primer). Heterogeneity was assessed and reported in I 2 and τ2. FINDINGS: Our search identified 1277 studies of which we included 66 studies (11 dPCR, 32 qPCR, and 23 LAMP) with 15 017 clinical samples in total in our systematic review and 52 studies in our meta-analysis. dPCR had the highest pooled diagnostic sensitivity (94·1%, 95% CI 88·9-96·6, by Reitsma's model and 95·8%, 54·9-100·0, by latent class model), followed by qPCR (92·7%, 88·3-95·6, and 93·4%, 60·9-99·9) and LAMP (83·3%, 76·9-88·2, and 86·2%, 20·7-99·9), using EUA-approved PCR kits as the reference standard. LAMP was the most specific with a pooled estimate of 96·3% (93·8-97·8) by Reitsma's model and 94·3% (49·1-100·0) by latent class model, followed by qPCR (92·9%, 87·2-96·2, and 93·1%, 47·1-100·0) and dPCR (78·5%, 57·4-90·8, and 73·8%, 0·9-100·0). The overall heterogeneity was I 2 0·5% (τ2 2·79) for dPCR studies, 0% (4·60) for qPCR studies, and 0% (3·96) for LAMP studies. AUCs of the three nucleic acid tests were the highest and differed the least between tests (ie, AUC>0·98 for all tests) when performed with RNA extracted pharyngeal swabs using SARS-CoV-2 open reading frame 1ab primer. INTERPRETATION: All three nucleic acid tests consistently perform better with pharyngeal swabs using SARS-CoV-2 open reading frame 1ab primer with RNA extraction. dPCR was shown to be the most sensitive, followed by qPCR and LAMP. However, their accuracy does not differ significantly. Instead, accuracy depends on specific experimental conditions, implying that more efforts should be directed to optimising the experimental setups for the nucleic acid tests. Hence, our results could be a reference for optimising and establishing a standard nucleic acid test protocol that is applicable in laboratories worldwide. FUNDING: University Grants Committee and The Chinese University of Hong Kong.

Entropy of stapled peptide inhibitors in free state is the major contributor to the improvement of binding affinity with the GK domain.

Stapled peptides are promising protein-protein interaction (PPI) inhibitors that can increase the binding potency. Different from small-molecule inhibitors in which the binding mainly depends on energetic interactions with their protein targets, the binding of stapled peptides has long been suggested to be benefited from entropy. However, it remains challenging to reveal the molecular features that lead to this entropy gain, which could originate from the stabilization of the stapled peptide in solution or from the increased flexibility of the complex upon binding. This hinders the rational design of stapled peptides as PPI inhibitors. Using the guanylate kinase (GK) domain of the postsynaptic density protein 95 (PSD-95) as the target, we quantified the enthalpic and entropic contributions by combining isothermal titration calorimetry (ITC), X-ray crystallography, and free energy calculations based on all-atom molecular dynamics (MD) simulations. We successfully designed a stapled peptide inhibitor (staple 1) of the PSD-95 GK domain that led to a 25-fold increase in the binding affinity (from tens of µMs to 1.36 µM) with high cell permeability. We showed that entropy indeed greatly enhanced the binding affinity and the entropy gain was mainly due to the constrained-helix structure of the stapled peptide in solution (free state). Based on staple 1, we further designed two other stapled peptides (staple 2 and 3), which exerted even larger entropy gains compared to staple 1 because of their more flexible bound complexes (bound state). However, for staple 2 and 3, the overall binding affinities were not improved, as the loose binding in their bound states led to an enthalpic loss that largely compensated the excess entropy gain. Our work suggests that increasing the stability of the stapled peptide in free solution is an effective strategy for the rational design of stapled peptides as PPI inhibitors.

A novel mechanism of enhanced transcription activity and fidelity for influenza A viral RNA-dependent RNA polymerase.

During RNA elongation, the influenza A viral (IAV) RNA-dependent RNA polymerase (RdRp) residues in the active site interact with the triphosphate moiety of nucleoside triphosphate (NTP) for catalysis. The molecular mechanisms by which they control the rate and fidelity of NTP incorporation remain elusive. Here, we demonstrated through enzymology, virology and computational approaches that the R239 and K235 in the PB1 subunit of RdRp are critical to controlling the activity and fidelity of transcription. Contrary to common beliefs that high-fidelity RdRp variants exert a slower incorporation rate, we discovered a first-of-its-kind, single lysine-to-arginine mutation on K235 exhibited enhanced fidelity and activity compared with wild-type. In particular, we employed a single-turnover NTP incorporation assay for the first time on IAV RdRp to show that K235R mutant RdRp possessed a 1.9-fold increase in the transcription activity of the cognate NTP and a 4.6-fold increase in fidelity compared to wild-type. Our all-atom molecular dynamics simulations further elucidated that the higher activity is attributed to the shorter distance between K235R and the triphosphate moiety of NTP compared with wild-type. These results provide novel insights into NTP incorporation and fidelity control mechanisms, which lay the foundation for the rational design of IAV vaccine and antiviral targets.

The mechanism of action of T-705 as a unique delayed chain terminator on influenza viral polymerase transcription.

Favipiravir (T-705) has been developed as a potent anti-influenza drug and exhibited a strong inhibition effect against a broad spectrum of RNA viruses. Its active form, ribofuranosyl-triphosphate (T-705-RTP), functions as a competitive substrate for the RNA-dependent RNA polymerase (RdRp) of the influenza A virus (IAV). However, the exact inhibitory mechanisms of T-705 remain elusive and subject to a long-standing debate. Although T-705 has been proposed to inhibit transcription by acting as a chain terminator, it is also paradoxically suggested to be a mutagen towards IAV RdRp by inducing mutations due to its ambiguous base pairing of C and U. Here, we combined biochemical assay with molecular dynamics (MD) simulations to elucidate the molecular mechanism underlying the inhibitory functions exerted by T-705 in IAV RdRp. Our in vitro transcription assay illustrated that IAV RdRp could recognize T-705 as a purine analogue and incorporate it into the nascent RNA strand. Incorporating a single T-705 is incapable of inhibiting transcription as extra natural nucleotides can be progressively added. However, when two consecutive T-705 are incorporated, viral transcription is completely terminated. MD simulations reveal that the sequential appearance of two T-705 in the nascent strand destabilizes the active site and disrupts the base stacking of the nascent RNA. Altogether, our results provide a plausible explanation for the inhibitory roles of T-705 targeting IAV RdRp by integrating the computational and experimental methods. Our study also offers a comprehensive platform to investigate the inhibition effect of antivirals and a novel explanation for the designing of anti-flu drugs.

Role of bacterial RNA polymerase gate opening dynamics in DNA loading and antibiotics inhibition elucidated by quasi-Markov State Model.

To initiate transcription, the holoenzyme (RNA polymerase [RNAP] in complex with σ factor) loads the promoter DNA via the flexible loading gate created by the clamp and ß-lobe, yet their roles in DNA loading have not been characterized. We used a quasi-Markov State Model (qMSM) built from extensive molecular dynamics simulations to elucidate the dynamics of Thermus aquaticus holoenzyme's gate opening. We showed that during gate opening, ß-lobe oscillates four orders of magnitude faster than the clamp, whose opening depends on the Switch 2's structure. Myxopyronin, an antibiotic that binds to Switch 2, was shown to undergo a conformational selection mechanism to inhibit clamp opening. Importantly, we reveal a critical but undiscovered role of ß-lobe, whose opening is sufficient for DNA loading even when the clamp is partially closed. These findings open the opportunity for the development of antibiotics targeting ß-lobe of RNAP. Finally, we have shown that our qMSMs, which encode non-Markovian dynamics based on the generalized master equation formalism, hold great potential to be widely applied to study biomolecular dynamics.

1'-Ribose cyano substitution allows Remdesivir to effectively inhibit nucleotide addition and proofreading during SARS-CoV-2 viral RNA replication.

COVID-19 has recently caused a global health crisis and an effective interventional therapy is urgently needed. Remdesivir is one effective inhibitor for SARS-CoV-2 viral RNA replication. It supersedes other NTP analogues because it not only terminates the polymerization activity of RNA-dependent RNA polymerase (RdRp), but also inhibits the proofreading activity of intrinsic exoribonuclease (ExoN). Even though the static structure of Remdesivir binding to RdRp has been solved and biochemical experiments have suggested it to be a "delayed chain terminator", the underlying molecular mechanisms is not fully understood. Here, we performed all-atom molecular dynamics (MD) simulations with an accumulated simulation time of 24 microseconds to elucidate the inhibitory mechanism of Remdesivir on nucleotide addition and proofreading. We found that when Remdesivir locates at an upstream site in RdRp, the 1'-cyano group experiences electrostatic interactions with a salt bridge (Asp865-Lys593), which subsequently halts translocation. Our findings can supplement the current understanding of the delayed chain termination exerted by Remdesivir and provide an alternative molecular explanation about Remdesivir's inhibitory mechanism. Such inhibition also reduces the likelihood of Remdesivir to be cleaved by ExoN acting on 3'-terminal nucleotides. Furthermore, our study also suggests that Remdesivir's 1'-cyano group can disrupt the cleavage site of ExoN via steric interactions, leading to a further reduction in the cleavage efficiency. Our work provides plausible and novel mechanisms at the molecular level of how Remdesivir inhibits viral RNA replication, and our findings may guide rational design for new treatments of COVID-19 targeting viral replication.

EmPC-seq: Accurate RNA-sequencing and Bioinformatics Platform to Map RNA Polymerases and Remove Background Error.

Transcription errors can substantially affect metabolic processes in organisms by altering the epigenome and causing misincorporations in mRNA, which is translated into aberrant mutant proteins. Moreover, within eukaryotic genomes there are specific Transcription Error-Enriched genomic Loci (TEELs) which are transcribed by RNA polymerases with significantly higher error rates and hypothesized to have implications in cancer, aging, and diseases such as Down syndrome and Alzheimer's. Therefore, research into transcription errors is of growing importance within the field of genetics. Nevertheless, methodological barriers limit the progress in accurately identifying transcription errors. Pro-Seq and NET-Seq can purify nascent RNA and map RNA polymerases along the genome but cannot be used to identify transcriptional mutations. Here we present background Error Model-coupled Precision nuclear run-on Circular-sequencing (EmPC-seq), a method combining a nuclear run-on assay and circular sequencing with a background error model to precisely detect nascent transcription errors and effectively discern TEELs within the genome.

Elucidating molecular mechanisms of functional conformational changes of proteins via Markov state models.

Functional conformational changes of proteins can facilitate numerous biological events in cells. The Markov state model (MSM) built from molecular dynamics simulations provide a powerful approach to study them. We here introduce a protocol that is tailor-made for constructing MSMs to study the functional conformational changes of proteins. In this protocol, one of the important steps is to select proper molecular features that can collectively describe the slowest timescales of conformational changes of interest. We recommend spectral oASIS, the modified version of oASIS, as a promising approach for automatic feature selection. Recently developed deep learning methods could also serve efficient approaches for selecting features and finding collective variables. Using DNA repair enzymes and RNA polymerases as examples, we review recent applications of MSMs to elucidate molecular mechanisms of functional conformational changes. Finally, we discuss remaining challenges and future perspectives for constructing MSMs to study functional conformational changes of proteins.

Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling.

RNA polymerase transcribes certain genomic loci with higher errors rates. These transcription error-enriched genomic loci (TEELs) have implications in disease. Current deep-sequencing methods cannot distinguish TEELs from post-transcriptional modifications, stochastic transcription errors, and technical noise, impeding efforts to elucidate the mechanisms linking TEELs to disease. Here, we describe background error model-coupled precision nuclear run-on circular-sequencing (EmPC-seq) to discern genomic regions enriched for transcription misincorporations. EmPC-seq innovatively combines a nuclear run-on assay for capturing nascent RNA before post-transcriptional modifications, a circular-sequencing step that sequences the same nascent RNA molecules multiple times to improve accuracy, and a statistical model for distinguishing error-enriched regions among stochastic polymerase errors. Applying EmPC-seq to the ribosomal RNA transcriptome, we show that TEELs of RNA polymerase I are not randomly distributed but clustered together, with higher error frequencies at nascent transcript 3' ends. Our study establishes a reliable method of identifying TEELs with nucleotide precision, which can help elucidate their molecular origins.

Remdesivir, lopinavir, emetine, and homoharringtonine inhibit SARS-CoV-2 replication in vitro.

An escalating pandemic by the novel SARS-CoV-2 virus is impacting global health and effective therapeutic options are urgently needed. We evaluated the in vitro antiviral effect of compounds that were previously reported to inhibit coronavirus replication and compounds that are currently under evaluation in clinical trials for SARS-CoV-2 patients. We report the antiviral effect of remdesivir, lopinavir, homorringtonine, and emetine against SARS-CoV-2 virus in Vero E6 cells with the estimated 50% effective concentration at 23.15 µM, 26.63 µM, 2.55 µM and 0.46 µM, respectively. Ribavirin or favipiravir that are currently evaluated under clinical trials showed no inhibition at 100 µM. Synergy between remdesivir and emetine was observed, and remdesivir at 6.25 µM in combination with emetine at 0.195 µM may achieve 64.9% inhibition in viral yield. Combinational therapy may help to reduce the effective concentration of compounds below the therapeutic plasma concentrations and provide better clinical benefits.