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105 result(s) for "Boni, Maciej F."
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Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm
Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was introduced for an exact nonparametric mosaicism statistic that gave high-precision P values for putative recombinants. This exact computation meant that multiple-comparisons corrected P values also had high precision, which is crucial when performing millions or billions of tests in large databases. Here, we introduce an improvement to the algorithmic complexity of this computation from O(mn3) to O(mn2), where m and n are the numbers of recombination-informative sites in the candidate recombinant. This new computation allows for recombination analysis to be performed in alignments with thousands of polymorphic sites. Benchmark runs are presented on viral genome sequence alignments, new features are introduced, and applications outside recombination analysis are discussed.
Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen
Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses . In contrast, our analysis detects evidence for significant positive episodic diversifying selection acting at the base of the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. While an undiscovered “facilitating” intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human–human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus.
Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic
There are outstanding evolutionary questions on the recent emergence of human coronavirus SARS-CoV-2 including the role of reservoir species, the role of recombination and its time of divergence from animal viruses. We find that the sarbecoviruses—the viral subgenus containing SARS-CoV and SARS-CoV-2—undergo frequent recombination and exhibit spatially structured genetic diversity on a regional scale in China. SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor-binding motif, important for specificity to human ACE2 receptors, appears to be an ancestral trait shared with bat viruses and not one acquired recently via recombination. To employ phylogenetic dating methods, recombinant regions of a 68-genome sarbecovirus alignment were removed with three independent methods. Bayesian evolutionary rate and divergence date estimates were shown to be consistent for these three approaches and for two different prior specifications of evolutionary rates based on HCoV-OC43 and MERS-CoV. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir were estimated as 1948 (95% highest posterior density (HPD): 1879–1999), 1969 (95% HPD: 1930–2000) and 1982 (95% HPD: 1948–2009), indicating that the lineage giving rise to SARS-CoV-2 has been circulating unnoticed in bats for decades. In this manuscript, the authors address evolutionary questions on the emergence of SARS-CoV-2. They find that SARS-CoV-2 is not a recombinant of any sarbecoviruses detected to date, and that the bat and pangolin sequences most closely related to SARS-CoV-2 probably diverged several decades ago or possibly earlier from human SARS-CoV-2 samples.
Impact of human mobility on the emergence of dengue epidemics in Pakistan
The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness.
Preventing antimalarial drug resistance with triple artemisinin-based combination therapies
Increasing levels of artemisinin and partner drug resistance threaten malaria control and elimination globally. Triple artemisinin-based combination therapies (TACTs) which combine artemisinin derivatives with two partner drugs are efficacious and well tolerated in clinical trials, including in areas of multidrug-resistant malaria. Whether early TACT adoption could delay the emergence and spread of antimalarial drug resistance is a question of vital importance. Using two independent individual-based models of Plasmodium falciparum epidemiology and evolution, we evaluated whether introduction of either artesunate-mefloquine-piperaquine or artemether-lumefantrine-amodiaquine resulted in lower long-term artemisinin-resistance levels and treatment failure rates compared with continued ACT use. We show that introduction of TACTs could significantly delay the emergence and spread of artemisinin resistance and treatment failure, extending the useful therapeutic life of current antimalarial drugs, and improving the chances of malaria elimination. We conclude that immediate introduction of TACTs should be considered by policy makers in areas of emerging artemisinin resistance. Triple artemisinin-based combination therapies have shown high efficacy for treatment of malaria in preliminary studies. Here, the authors use mathematical modelling to assess whether these therapies could also delay the emergence and spread of antimalarial drug resistance when compared against frontline therapies.
Vaccination and antigenic drift in influenza
The relationship between influenza antigenic drift and vaccination lies at the intersection of evolutionary biology and public health, and it must be viewed and analyzed in both contexts simultaneously. In this paper, I review what is known about the effects of antigenic drift on vaccination and the effects of vaccination on antigenic drift, and I suggest some simple ways to detect the presence of antigenic drift in seasonal influenza data. If antigenic drift occurs on the time scale of a single influenza season, it may be associated with the presence of herd immunity at the beginning of the season and may indicate a need to monitor for vaccine updates at the end of the season. The relationship between antigenic drift and vaccination must also be viewed in the context of the global circulation of influenza strains and the seeding of local and regional epidemics. In the data sets I consider – from New Zealand, New York, and France – antigenic drift can be statistically detected during some seasons, and seeding of epidemics appears to be endogenous sometimes and exogenous at other times. Improved detection of short-term antigenic drift and epidemic seeding would significantly benefit influenza monitoring efforts and vaccine selection.
An Exact Nonparametric Method for Inferring Mosaic Structure in Sequence Triplets
Statistical tests for detecting mosaic structure or recombination among nucleotide sequences usually rely on identifying a pattern or a signal that would be unlikely to appear under clonal reproduction. Dozens of such tests have been described, but many are hampered by long running times, confounding of selection and recombination, and/or inability to isolate the mosaic-producing event. We introduce a test that is exact, nonparametric, rapidly computable, free of the infinite-sites assumption, able to distinguish between recombination and variation in mutation/fixation rates, and able to identify the breakpoints and sequences involved in the mosaic-producing event. Our test considers three sequences at a time: two parent sequences that may have recombined, with one or two breakpoints, to form the third sequence (the child sequence). Excess similarity of the child sequence to a candidate recombinant of the parents is a sign of recombination; we take the maximum value of this excess similarity as our test statistic Δm,n,b. We present a method for rapidly calculating the distribution of Δm,n,b and demonstrate that it has comparable power to and a much improved running time over previous methods, especially in detecting recombination in large data sets.
The Community As the Patient in Malaria-Endemic Areas: Preempting Drug Resistance with Multiple First-Line Therapies
Abbreviations: ACT, Artemisinin combination therapy; AS-MQ, artesunate-mefloquine; DHA-PPQ, dihydroartemisinin-piperaquine; NMCP, national malaria control program; MFT, multiple first-line therapies; WHO, World Health Organization Provenance: Not commissioned; externally peer-reviewed Summary Points * Combination therapy is an effective way to delay or prevent drug-resistance evolution in malaria, but we do not take full advantage of its potential. * Deploying multiple first-line combination therapies allows us to challenge parasite populations with many different types of drugs, and thus delay and slow down drug-resistance evolution more than with a single combination therapy. * We must take a preemptive, not reactive, policy approach to drug-resistance management in malaria. When or if new antimalarial compounds such as cipargamin (KAE609), the imidazolopiperazine KAF156, artefenomel (OZ439), and ferroquine pass through the necessary safety and efficacy trials and are adopted for wide distribution for treating uncomplicated malaria, they will be deployed as combinations, but they will still need to be introduced into the public health system in such a way that their presence does not immediately create substantial pressure for drug-resistant genotypes to evolve.
Assessing emergence risk of double-resistant and triple-resistant genotypes of Plasmodium falciparum
Delaying and slowing antimalarial drug resistance evolution is a priority for malaria-endemic countries. Until novel therapies become available, the mainstay of antimalarial treatment will continue to be artemisinin-based combination therapy (ACT). Deployment of different ACTs can be optimized to minimize evolutionary pressure for drug resistance by deploying them as a set of co-equal multiple first-line therapies (MFT) rather than rotating therapies in and out of use. Here, we consider one potential detriment of MFT policies, namely, that the simultaneous deployment of multiple ACTs could drive the evolution of different resistance alleles concurrently and that these resistance alleles could then be brought together by recombination into double-resistant or triple-resistant parasites. Using an individual-based model, we compare MFT and cycling policies in malaria transmission settings ranging from 0.1% to 50% prevalence. We define a total risk measure for multi-drug resistance (MDR) by summing the area under the genotype-frequency curves (AUC) of double- and triple-resistant genotypes. When prevalence ≥ 1%, total MDR risk ranges from statistically similar to 80% lower under MFT policies than under cycling policies, irrespective of whether resistance is imported or emerges de novo. At 0.1% prevalence, there is little statistical difference in MDR risk between MFT and cycling. Emergence of malaria parasites resistant to artemisinin has prompted the need for new drug regimens to ensure effective treatment. In this simulation study, the authors evaluate the risk of multidrug resistance under regimens with either concurrent or cyclic use of different first-line therapies.
Estimating the force of infection of four dengue serotypes from serological studies in two regions of Vietnam
Dengue is endemic in Vietnam with circulation of all four serotypes (DENV1-4) all year-round. It is hard to estimate the disease’s true serotype-specific transmission patterns from cases due to its high asymptomatic rate, low reporting rate and complex immunity and transmission dynamics. Seroprevalence studies have been used to great effect for understanding patterns of dengue transmission. We tested 991 population serum samples (ages 1–30 years, collected 2013 to 2017), 531 from Ho Chi Minh City and 460 from Khanh Hoa in Vietnam, using a flavivirus protein microarray assay. By applying our previously developed inference framework to the antibody profiles from this assay, we can (1) determine proportions of a population that have not been infected or infected, once, or more than once, and (2) infer the infecting serotype in those infected once. With these data, we then use mathematical models to estimate the force of infection (FOI) for all four DENV serotypes in HCMC and KH over 35 years up to 2017. Models with time-varying or serotype-specific DENV FOI assumptions fit the data better than constant FOI. Annual dengue FOI ranged from 0.005 (95%CI: 0.003–0.008) to 0.201 (95%CI: 0.174–0.228). FOI varied across serotypes, higher for DENV1 (95%CI: 0.033–0.048) and DENV2 (95%CI: 0.018–0.039) than DENV3 (95%CI: 0.007–0.010) and DENV4 (95%CI: 0.010–0.016). The use of the PMA on serial age-stratified cross-sectional samples increases the amount of information on transmission and population immunity, and should be considered for future dengue serological surveys, particularly to understand population immunity given vaccines with differential efficacy against serotypes, however, there remains limits to what can be inferred even using this assay.