Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant.

Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity.

SARS-CoV-2 can mutate and evade immunity, with consequences for efficacy of emerging vaccines and antibody therapeutics. Here, we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is a highly variable region of S and provide epidemiological, clinical, and molecular characterization of a prevalent, sentinel RBM mutation, N439K. We demonstrate N439K S protein has enhanced binding affinity to the hACE2 receptor, and N439K viruses have similar in vitro replication fitness and cause infections with similar clinical outcomes as compared to wild type. We show the N439K mutation confers resistance against several neutralizing monoclonal antibodies, including one authorized for emergency use by the US Food and Drug Administration (FDA), and reduces the activity of some polyclonal sera from persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.

Subgenomic RNA identification in SARS-CoV-2 genomic sequencing data.

We have developed periscope, a tool for the detection and quantification of subgenomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed "subgenomic RNAs." sgRNAs are produced through discontinuous transcription, which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L, which is located in the 5' UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5' end of all sgRNA. We applied periscope to 1155 SARS-CoV-2 genomes from Sheffield, United Kingdom, and validated our findings using orthogonal data sets and in vitro cell systems. By using a simple local alignment to detect reads that contain the leader sequence, we were able to identify and quantify reads arising from canonical and noncanonical sgRNA. We were able to detect all canonical sgRNAs at the expected abundances, with the exception of ORF10. A number of recurrent noncanonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/- cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing data sets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.

Sampling the reciprocal Coulomb potential in finite anisotropic cells.

We present a robust strategy to numerically sample the Coulomb potential in reciprocal space for periodic Born-von Karman cells of general shape. Our approach tackles two common issues of plane-wave based implementations of Coulomb integrals under periodic boundary conditions: the treatment of the singularity at the Brillouin-zone center and discretization errors, which can cause severe convergence problems in anisotropic cells, necessary for the calculation of low-dimensional systems. We apply our strategy to the Hartree-Fock and coupled cluster (CC) theories and discuss the consequences of different sampling strategies on different theories. We show that sampling the Coulomb potential via the widely used probe-charge Ewald method is unsuitable for CC calculations in anisotropic cells. To demonstrate the applicability of our developed approach, we study two representative, low-dimensional use cases: the infinite carbon chain, for which we report the first periodic CCSD(T) potential energy surface, and a surface slab of lithium hydride, for which we demonstrate the impact of different sampling strategies for calculating surface energies. We find that our Coulomb sampling strategy serves as a vital solution, addressing the critical need for improved accuracy in plane-wave based CC calculations for low-dimensional systems.

Electronic Free Energy Surface of the Nitrogen Dimer Using First-Principles Finite Temperature Electronic Structure Methods.

We use full configuration interaction and density matrix quantum Monte Carlo methods to calculate the electronic free energy surface of the nitrogen dimer within the free-energy Born-Oppenheimer approximation. As the temperature is raised from T = 0, we find a temperature regime in which the internal energy causes bond strengthening. At these temperatures, adding in the entropy contributions is required to cause the bond to gradually weaken with increasing temperature. We predict a thermally driven dissociation for the nitrogen dimer between 22,000 to 63,200 K depending on symmetries and basis set. Inclusion of more spatial and spin symmetries reduces the temperature required. The origin of these observations is explored using the structure of the density matrix at various temperatures and bond lengths.

Electronic specific heat capacities and entropies from density matrix quantum Monte Carlo using Gaussian process regression to find gradients of noisy data.

We present a machine learning approach to calculating electronic specific heat capacities for a variety of benchmark molecular systems. Our models are based on data from density matrix quantum Monte Carlo, which is a stochastic method that can calculate the electronic energy at finite temperature. As these energies typically have noise, numerical derivatives of the energy can be challenging to find reliably. In order to circumvent this problem, we use Gaussian process regression to model the energy and use analytical derivatives to produce the specific heat capacity. From there, we also calculate the entropy by numerical integration. We compare our results to cubic splines and finite differences in a variety of molecules in which Hamiltonians can be diagonalized exactly with full configuration interaction. We finally apply this method to look at larger molecules where exact diagonalization is not possible and make comparisons with more approximate ways to calculate the specific heat capacity and entropy.

Machine learning for a finite size correction in periodic coupled cluster theory calculations.

We introduce a straightforward Gaussian process regression (GPR) model for the transition structure factor of metal periodic coupled cluster singles and doubles (CCSD) calculations. This is inspired by the method introduced by Liao and Grüneis for interpolating over the transition structure factor to obtain a finite size correction for CCSD [K. Liao and A. Grüneis, J. Chem. Phys. 145, 141102 (2016)] and by our own prior work using the transition structure factor to efficiently converge CCSD for metals to the thermodynamic limit [Mihm et al., Nat. Comput. Sci. 1, 801 (2021)]. In our CCSD-FS-GPR method to correct for finite size errors, we fit the structure factor to a 1D function in the momentum transfer, G. We then integrate over this function by projecting it onto a k-point mesh to obtain comparisons with extrapolated results. Results are shown for lithium, sodium, and the uniform electron gas.

Piecewise interaction picture density matrix quantum Monte Carlo.

The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact N-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC (IP-DMQMC) method that overcomes the limitation of only sampling one inverse temperature point at a time, instead allowing for the sampling of a temperature range within a single calculation, thereby reducing the computational cost. At the target inverse temperature, instead of ending the simulation, we incorporate a change of picture away from the interaction picture. The resulting equations of motion have piecewise functions and use the interaction picture in the first phase of a simulation, followed by the application of the Bloch equation once the target inverse temperature is reached. We find that the performance of this method is similar to or better than the DMQMC and IP-DMQMC algorithms in a variety of molecular test systems.

Mapping bare ground in New Zealand hill-country agriculture and forestry for soil erosion risk assessment: An automated satellite remote-sensing method.

Removing vegetation cover from hill-slope land increases risk for soil erosion and delivery of sediment to waterways. In New Zealand's productive landscapes, clear-fell harvesting of forestry blocks and winter forage grazing by agricultural livestock are two significant causes of vegetation removal. Bare ground exposed by these activities varies annually and seasonally in location and spatial extent. Modelling soil erosion therefore requires temporally and spatially explicit mapping of this bare ground. We have developed an automated mapping method using time-series satellite imagery, thereby enabling wide-area coverage and ease of updating. The temporal analysis identifies land use along with the period of vegetation removal. It produces results per land parcel (in vector format) for use in a Geographic Information System. We present a description of our method, national maps and statistics of bare ground extent in New Zealand's hill-country forestry and winter forage grazing land in 2018, and an assessment of accuracy. The attributes of the mapped land parcels are designed for input into a soil erosion estimation model such as the New Zealand Universal Soil Loss Equation.

Seoul Virus Associated with Pet Rats, Scotland, UK, 2019.

We describe a case of hemorrhagic fever with renal syndrome caused by Seoul virus in a woman in Scotland, UK. Whole-genome sequencing showed the virus belonged to a lineage characterized by recent international expansion, probably driven by trade in pet rats.

Derivation and external validation of a risk score for predicting HIV-associated tuberculosis to support case finding and preventive therapy scale-up: A cohort study.

BACKGROUND: Among people living with HIV (PLHIV), more flexible and sensitive tuberculosis (TB) screening tools capable of detecting both symptomatic and subclinical active TB are needed to (1) reduce morbidity and mortality from undiagnosed TB; (2) facilitate scale-up of tuberculosis preventive therapy (TPT) while reducing inappropriate prescription of TPT to PLHIV with subclinical active TB; and (3) allow for differentiated HIV-TB care. METHODS AND FINDINGS: We used Botswana XPRES trial data for adult HIV clinic enrollees collected during 2012 to 2015 to develop a parsimonious multivariable prognostic model for active prevalent TB using both logistic regression and random forest machine learning approaches. A clinical score was derived by rescaling final model coefficients. The clinical score was developed using southern Botswana XPRES data and its accuracy validated internally, using northern Botswana data, and externally using 3 diverse cohorts of antiretroviral therapy (ART)-naive and ART-experienced PLHIV enrolled in XPHACTOR, TB Fast Track (TBFT), and Gugulethu studies from South Africa (SA). Predictive accuracy of the clinical score was compared with the World Health Organization (WHO) 4-symptom TB screen. Among 5,418 XPRES enrollees, 2,771 were included in the derivation dataset; 67% were female, median age was 34 years, median CD4 was 240 cells/µL, 189 (7%) had undiagnosed prevalent TB, and characteristics were similar between internal derivation and validation datasets. Among XPHACTOR, TBFT, and Gugulethu cohorts, median CD4 was 400, 73, and 167 cells/µL, and prevalence of TB was 5%, 10%, and 18%, respectively. Factors predictive of TB in the derivation dataset and selected for the clinical score included male sex (1 point), ≥1 WHO TB symptom (7 points), smoking history (1 point), temperature >37.5°C (6 points), body mass index (BMI) <18.5kg/m2 (2 points), and severe anemia (hemoglobin <8g/dL) (3 points). Sensitivity using WHO 4-symptom TB screen was 73%, 80%, 94%, and 94% in XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively, but increased to 88%, 87%, 97%, and 97%, when a clinical score of ≥2 was used. Negative predictive value (NPV) also increased 1%, 0.3%, 1.6%, and 1.7% in XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively, when the clinical score of ≥2 replaced WHO 4-symptom TB screen. Categorizing risk scores into low (<2), moderate (2 to 10), and high-risk categories (>10) yielded TB prevalence of 1%, 1%, 2%, and 6% in the lowest risk group and 33%, 22%, 26%, and 32% in the highest risk group for XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively. At clinical score ≥2, the number needed to screen (NNS) ranged from 5.0 in Gugulethu to 11.0 in XPHACTOR. Limitations include that the risk score has not been validated in resource-rich settings and needs further evaluation and validation in contemporary cohorts in Africa and other resource-constrained settings. CONCLUSIONS: The simple and feasible clinical score allowed for prioritization of sensitivity and NPV, which could facilitate reductions in mortality from undiagnosed TB and safer administration of TPT during proposed global scale-up efforts. Differentiation of risk by clinical score cutoff allows flexibility in designing differentiated HIV-TB care to maximize impact of available resources.

Non-epidemic HCV genotypes in low- and middle-income countries and the risk of resistance to current direct-acting antiviral regimens.

The hepatitis C virus (HCV) is an extremely diverse virus, subtypes of which are distributed variably around the world. Viral genotypes may be divided into epidemic subtypes; those that have become prevalent globally, and endemic subtypes that have a more limited distribution, mainly in Africa and Asia. The high variability of endemic strains reflects evolutionary origins in the locations where they are found. This increased genetic diversity raises the possibility of resistance to pan-genotypic direct-acting antiviral regimens. While many endemic subtypes respond well to direct-acting antiviral therapies, others, for example genotypes 1l, 3b and 4r, do not respond as well as predicted. Many genotypes that are rare in high-income countries but common in other parts of the world have not yet been fully assessed in clinical trials. Further sequencing and clinical studies in sub-Saharan Africa and Asia are indicated to monitor response to treatment and to facilitate the World Health Organization's 2030 elimination strategy.

Iron-Catalyzed Halogen Exchange of Trifluoromethyl Arenes*.

The facile production of ArCF2 X and ArCX3 from ArCF3 using catalytic iron(III)halides is reported, which constitutes the first iron-catalyzed halogen exchange for non-aromatic C-F bonds. Theoretical calculations suggest direct activation of C-F bonds by iron coordination. ArCX3 and ArCF2 X products of the reaction are synthetically valuable due to their diversification potential. In particular, chloro- and bromodifluoromethyl arenes (ArCF2 Cl, ArCF2 Br respectively) provide access to a myriad of difluoromethyl arene derivatives (ArCF2 R). To optimize for mono-halogen exchange, a statistical method called Design of Experiments was used. Optimized parameters were successfully applied to electron rich and electron deficient aromatic substrates, and to the late stage diversification of flufenoxuron, a commercial insecticide. These methods are highly practical, being run at convenient temperatures and using inexpensive common reagents.

Accelerating convergence to the thermodynamic limit with twist angle selection applied to methods beyond many-body perturbation theory.

We recently developed a scheme to use low-cost calculations to find a single twist angle where the coupled cluster doubles energy of a single calculation matches the twist-averaged coupled cluster doubles energy in a finite unit cell. We used initiator full configuration interaction quantum Monte Carlo as an example of an exact method beyond coupled cluster doubles theory to show that this selected twist angle approach had comparable accuracy in methods beyond coupled cluster. Furthermore, at least for small system sizes, we show that the same twist angle can also be found by comparing the energy directly (at the level of second-order Moller-Plesset theory), suggesting a route toward twist angle selection, which requires minimal modification to existing codes that can perform twist averaging.

Effect of tuberculosis screening and retention interventions on early antiretroviral therapy mortality in Botswana: a stepped-wedge cluster randomized trial.

BACKGROUND: Undiagnosed tuberculosis (TB) remains the most common cause of HIV-related mortality. Xpert MTB/RIF (Xpert) is being rolled out globally to improve TB diagnostic capacity. However, previous Xpert impact trials have reported that health system weaknesses blunted impact of this improved diagnostic tool. During phased Xpert rollout in Botswana, we evaluated the impact of a package of interventions comprising (1) additional support for intensified TB case finding (ICF), (2) active tracing for patients missing clinic appointments to support retention, and (3) Xpert replacing sputum-smear microscopy, on early (6-month) antiretroviral therapy (ART) mortality. METHODS: At 22 clinics, ART enrollees > 12 years old were eligible for inclusion in three phases: a retrospective standard of care (SOC), prospective enhanced care (EC), and prospective EC plus Xpert (EC+X) phase. EC and EC+X phases were implemented as a stepped-wedge trial. Participants in the EC phase received SOC plus components 1 (strengthened ICF) and 2 (active tracing) of the intervention package, and participants in the EC+X phase received SOC plus all three intervention package components. Primary and secondary objectives were to compare all-cause 6-month ART mortality between SOC and EC+X and between EC and EC+X phases, respectively. We used adjusted analyses, appropriate for study design, to control for baseline differences in individual-level factors and intra-facility correlation. RESULTS: We enrolled 14,963 eligible patients: 8980 in SOC, 1768 in EC, and 4215 in EC+X phases. Median age of ART enrollees was 35 and 64% were female. Median CD4 cell count was lower in SOC than subsequent phases (184/µL in SOC, 246/µL in EC, and 241/µL in EC+X). By 6 months of ART, 461 (5.3%) of SOC, 54 (3.2%) of EC, and 121 (3.0%) of EC+X enrollees had died. Compared with SOC, 6-month mortality was lower in the EC+X phase (adjusted hazard ratio, 0.77; 95% confidence interval, 0.61-0.97, p = 0.029). Compared with EC enrollees, 6-month mortality was similar among EC+X enrollees. CONCLUSIONS: Interventions to strengthen ICF and retention were associated with lower early ART mortality. This new evidence highlights the need to strengthen ICF and retention in many similar settings. Similar to other trials, no additional mortality benefit of replacing sputum-smear microscopy with Xpert was observed. TRIAL REGISTRATION: Retrospectively registered: ClinicalTrials.gov (NCT02538952).

Risk scores for predicting early antiretroviral therapy mortality in sub-Saharan Africa to inform who needs intensification of care: a derivation and external validation cohort study.

BACKGROUND: Clinical scores to determine early (6-month) antiretroviral therapy (ART) mortality risk have not been developed for sub-Saharan Africa (SSA), home to 70% of people living with HIV. In the absence of validated scores, WHO eligibility criteria (EC) for ART care intensification are CD4 < 200/µL or WHO stage III/IV. METHODS: We used Botswana XPRES trial data for adult ART enrollees to develop CD4-independent and CD4-dependent multivariable prognostic models for 6-month mortality. Scores were derived by rescaling coefficients. Scores were developed using the first 50% of XPRES ART enrollees, and their accuracy validated internally and externally using South African TB Fast Track (TBFT) trial data. Predictive accuracy was compared between scores and WHO EC. RESULTS: Among 5553 XPRES enrollees, 2838 were included in the derivation dataset; 68% were female and 83 (3%) died by 6 months. Among 1077 TBFT ART enrollees, 55% were female and 6% died by 6 months. Factors predictive of 6-month mortality in the derivation dataset at p < 0.01 and selected for the CD4-independent score included male gender (2 points), ≥ 1 WHO tuberculosis symptom (2 points), WHO stage III/IV (2 points), severe anemia (hemoglobin < 8 g/dL) (3 points), and temperature > 37.5 °C (2 points). The same variables plus CD4 < 200/µL (1 point) were included in the CD4-dependent score. Among XPRES enrollees, a CD4-independent score of ≥ 4 would provide 86% sensitivity and 66% specificity, whereas WHO EC would provide 83% sensitivity and 58% specificity. If WHO stage alone was used, sensitivity was 48% and specificity 89%. Among TBFT enrollees, the CD4-independent score of ≥ 4 would provide 95% sensitivity and 27% specificity, whereas WHO EC would provide 100% sensitivity but 0% specificity. Accuracy was similar between CD4-independent and CD4-dependent scores. Categorizing CD4-independent scores into low (< 4), moderate (4-6), and high risk (≥ 7) gave 6-month mortality of 1%, 4%, and 17% for XPRES and 1%, 5%, and 30% for TBFT enrollees. CONCLUSIONS: Sensitivity of the CD4-independent score was nearly twice that of WHO stage in predicting 6-month mortality and could be used in settings lacking CD4 testing to inform ART care intensification. The CD4-dependent score improved specificity versus WHO EC. Both scores should be considered for scale-up in SSA.

NECI: N-Electron Configuration Interaction with an emphasis on state-of-the-art stochastic methods.

We present NECI, a state-of-the-art implementation of the Full Configuration Interaction Quantum Monte Carlo (FCIQMC) algorithm, a method based on a stochastic application of the Hamiltonian matrix on a sparse sampling of the wave function. The program utilizes a very powerful parallelization and scales efficiently to more than 24 000 central processing unit cores. In this paper, we describe the core functionalities of NECI and its recent developments. This includes the capabilities to calculate ground and excited state energies, properties via the one- and two-body reduced density matrices, as well as spectral and Green's functions for ab initio and model systems. A number of enhancements of the bare FCIQMC algorithm are available within NECI, allowing us to use a partially deterministic formulation of the algorithm, working in a spin-adapted basis or supporting transcorrelated Hamiltonians. NECI supports the FCIDUMP file format for integrals, supplying a convenient interface to numerous quantum chemistry programs, and it is licensed under GPL-3.0.

The Influence of Redox-Innocent Donor Groups in Tetradentate Ligands Derived from o-Phenylenediamine: Electronic Structure Investigations with Nickel.

The continued development of redox-active ligands requires an understanding as to how ligand modifications and related factors affect the locus of redox activity and spin density in metal complexes. Here we describe the synthesis, characterization, and electronic structure of nickel complexes containing triaryl NNNN (1) and SNNS (2) ligands derived from o-phenylenediamine. The tetradentate ligands in 1 and 2 were investigated and compared to those in metal complexes with compositionally similar ligands to determine how ligand-centered redox properties change when redox-active flanking groups are replaced with redox-innocent NMe2 or SMe. A derivative of 2 in which the phenylene backbone was replaced with ethylene (3) was also prepared to interrogate the importance of o-phenylenediamine for ligand-centered redox activity. Cyclic voltammograms collected for 1 and 2 revealed two fully reversible ligand-centered redox events. Remarkably, several quasi-reversible ligand-centered redox waves were also observed for 3 despite the absence of the o-phenylenediamine subunit. Oxidizing 1 and 2 with silver salts containing different counteranions (BF4-, OTf-, NTf2-) allowed the electrochemically generated complexes to be analyzed as a function of different oxidation states using single-crystal X-ray diffraction (XRD), EPR spectroscopy, and S K-edge X-ray absorption spectroscopy. The experimental data are corroborated by DFT calculations, and together, they reveal how the location of unpaired spin density and electronic structure in singly and doubly oxidized salts of 1 and 2 varies depending on the coordinating ability of the counteranions and exogenous ligands such as pyridine.

An optimized twist angle to find the twist-averaged correlation energy applied to the uniform electron gas.

We explore an alternative to twist averaging in order to obtain more cost-effective and accurate extrapolations to the thermodynamic limit (TDL) for coupled cluster doubles (CCD) calculations. We seek a single twist angle to perform calculations at, instead of integrating over many random points or a grid. We introduce the concept of connectivity, a quantity derived from the nonzero four-index integrals in an MP2 calculation. This allows us to find a special twist angle that provides appropriate connectivity in the energy equation, which yields results comparable to full twist averaging. This special twist angle effectively makes the finite electron number CCD calculation represent the TDL more accurately, reducing the cost of twist-averaged CCD over Ns twist angles from Ns CCD calculations to Ns MP2 calculations plus one CCD calculation.

From patients to partners: participant-centric initiatives in biomedical research.

Advances in computing technology and bioinformatics mean that medical research is increasingly characterized by large international consortia of researchers that are reliant on large data sets and biobanks. These trends raise a number of challenges for obtaining consent, protecting participant privacy concerns and maintaining public trust. Participant-centred initiatives (PCIs) use social media technologies to address these immediate concerns, but they also provide the basis for long-term interactive partnerships. Here, we give an overview of this rapidly moving field by providing an analysis of the different PCI approaches, as well as the benefits and challenges of implementing PCIs.