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Ludwig van Beethoven (1770–1827) remains among the most influential and popular classical music composers. Health problems significantly impacted his career as a composer and pianist, including progressive hearing loss, recurring gastrointestinal complaints, and liver disease. In 1802, Beethoven requested that following his death, his disease be described and made public. Medical biographers have since proposed numerous hypotheses, including many substantially heritable conditions. Here we attempt a genomic analysis of Beethoven in order to elucidate potential underlying genetic and infectious causes of his illnesses. We incorporated improvements in ancient DNA methods into existing protocols for ancient hair samples, enabling the sequencing of high-coverage genomes from small quantities of historical hair. We analyzed eight independently sourced locks of hair attributed to Beethoven, five of which originated from a single European male. We deemed these matching samples to be almost certainly authentic and sequenced Beethoven’s genome to 24-fold genomic coverage. Although we could not identify a genetic explanation for Beethoven's hearing disorder or gastrointestinal problems, we found that Beethoven had a genetic predisposition for liver disease. Metagenomic analyses revealed furthermore that Beethoven had a hepatitis B infection during at least the months prior to his death. Together with the genetic predisposition and his broadly accepted alcohol consumption, these present plausible explanations for Beethoven’s severe liver disease, which culminated in his death. Unexpectedly, an analysis of Y chromosomes sequenced from five living members of the Van Beethoven patrilineage revealed the occurrence of an extra-pair paternity event in Ludwig van Beethoven’s patrilineal ancestry. Introduction Results - Authentication of hair samples - Genetic variants associated with somatic disease - Hepatitis B virus DNA recovered from Beethoven’s hair Discussion - Authenticity of Beethoven’s genome - Comparison with living individuals’ genomes - Origins of Beethoven’s diseases - Hepatitis B virus DNA in Beethoven’s hair - Future directions

Coronaviruses have a broad host range and exhibit high zoonotic potential. In this chapter, we describe their genomic organization in terms of encoded proteins and provide an introduction to the peculiar discontinuous transcription mechanism. Further, we present evolutionary conserved genomic RNA secondary structure features, which are involved in the complex replication mechanism. With a focus on computational methods, we review the emergence of SARS-CoV-2 starting with the 2019 strains. In that context, we also discuss the debated hypothesis of whether SARS-CoV-2 was created in a laboratory. We focus on the molecular evolution and the epidemiological dynamics of this recently emerged pathogen and we explain how variants of concern are detected and characterised. COVID-19, the disease caused by SARS-CoV-2, can spread through different transmission routes and also depends on a number of risk factors. We describe how current computational models of viral epidemiology, or more specifically, phylodynamics, have facilitated and will continue to enable a better understanding of the epidemic dynamics of SARS-CoV-2.

Coronaviruses have a broad host range and exhibit high zoonotic potential. In this chapter, we describe their genomic organization in terms of encoded proteins and provide an introduction to the peculiar discontinuous transcription mechanism. Further, we present evolutionary conserved genomic RNA secondary structure features, which are involved in the complex replication mechanism. With a focus on computational methods, we review the emergence of SARS-CoV-2 starting with the 2019 strains. In that context, we also discuss the debated hypothesis of whether SARS-CoV-2 was created in a laboratory. We focus on the molecular evolution and the epidemiological dynamics of this recently emerged pathogen and we explain how variants of concern are detected and characterised. COVID-19, the disease caused by SARS-CoV-2, can spread through different transmission routes and also depends on a number of risk factors. We describe how current computational models of viral epidemiology, or more specifically, phylodynamics, have facilitated and will continue to enable a better understanding of the epidemic dynamics of SARS-CoV-2.

SARS-CoV-2 can infect human cells through the recognition of the human angiotensin-converting enzyme 2 (ACE2) receptors. This affinity is given by six amino acid located in the receptor binding domain (RBD) region within the Spike protein. Genetic recombination involving bat and pangolin Sarbecoviruses, and natural selection have been proposed as possible explanations for the acquisition of these amino acids. In this study we employed Bayesian phylogenetics to jointly reconstruct the phylogeny of the RBD among human, bat and pangolin Sarbecoviruses and detect recombination events affecting this region of the genome. A recombination event involving RaTG13, the closest relative of SARS-CoV-2 that lacks five of the six residues, and an unsampled Sarbecovirus lineage was detected. This result suggests that the key amino acids were likely present in the common ancestor of SARS-CoV-2 and RaTG13, with the latter losing five of the amino acids as the result of recombination.

The bacterial pathogen Yersinia pestis gave rise to devastating outbreaks throughout human history, and ancient DNA evidence has shown it afflicted human populations as far back as the Neolithic. Y. pestis genomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to its emergence from a Yersinia pseudotuberculosis-like progenitor; however, the number of reconstructed LNBA genomes are too few to explore its diversity during this critical period of development. Here, we present 17 Y. pestis genomes dating to 5,000 to 2,500 y BP from a wide geographic expanse across Eurasia. This increased dataset enabled us to explore correlations between temporal, geographical, and genetic distance. Our results suggest a nonflea-adapted and potentially extinct single lineage that persisted over millennia without significant parallel diversification, accompanied by rapid dispersal across continents throughout this period, a trend not observed in other pathogens for which ancient genomes are available. A stepwise pattern of gene loss provides further clues on its early evolution and potential adaptation. We also discover the presence of the flea-adapted form of Y. pestis in Bronze Age Iberia, previously only identified in in the Caucasus and the Volga regions, suggesting a much wider geographic spread of this form of Y. pestis. Together, these data reveal the dynamic nature of plague’s formative years in terms of its early evolution and ecology.

BackgroundPlague is a zoonotic disease caused by the bacterium Yersinia pestis, highly prevalent in the Central Highlands, a mountainous region in the center of Madagascar. After a plague-free period of over 60 years in the northwestern coast city of Mahajanga, the disease reappeared in 1991 and caused several outbreaks until 1999. Previous research indicates that the disease was reintroduced to the city of Mahajanga from the Central Highlands instead of reemerging from a local reservoir. However, it is not clear how many reintroductions occurred and when they took place.Methodology/Principal findingsIn this study we applied a Bayesian phylogeographic model to detect and date migrations of Y. pestis between the two locations that could be linked to the re-emergence of plague in Mahajanga. Genome sequences of 300 Y. pestis strains sampled between 1964 and 2012 were analyzed. Four migrations from the Central Highlands to Mahajanga were detected. Two resulted in persistent transmission in humans, one was responsible for most of the human cases recorded between 1995 and 1999, while the other produced plague cases in 1991 and 1992. We dated the emergence of the Y. pestis sub-branch 1.ORI3, which is only present in Madagascar and Turkey, to the beginning of the 20th century, using a Bayesian molecular dating analysis. The split between 1.ORI3 and its ancestor lineage 1.ORI2 was dated to the second half of the 19th century.Conclusions/SignificanceOur results indicate that two independent migrations from the Central Highlands caused the plague outbreaks in Mahajanga during the 1990s, with both introductions occurring during the early 1980s. They happened over a decade before the detection of human cases, thus the pathogen likely survived in wild reservoirs until the spillover to humans was possible. This study demonstrates the value of Bayesian phylogenetics in elucidating the re-emergence of infectious diseases.Author summaryIn 1991 human cases of plague were reported in the city of Mahajanga, located in the west coast of Madagascar, after 60 years without human cases. Existing evidence suggests that Yersinia pestis, the causal agent of the disease, was reintroduced to the city from a mountainous region known as the Central Highlands. We performed a phylogeographic analysis on 300 Y. pestis genome sequences to determine how many migrations of the pathogen between the two locations were related to the reappearance of the disease in Mahajanga. The results revealed that two migrations from the Central Highlands were the cause of the outbreaks of plague in the west coast of the country during the 1990s. We also aimed to date the emergence of the Y.pestis variant that circulates in Madagascar and is also present in Turkey. To do this, we conducted a molecular dating analysis using an extended data set of 445 sequences, which contained sequences from Turkey and India (the country from which the pathogen was exported to Madagascar for the first time). The analysis indicated that this particular variant emerged in the first decade of the 20th century.

[Significance] The bacterium Yersinia pestis has caused numerous historically documented outbreaks of plague and research using ancient DNA could demonstrate that it already affected human populations during the Neolithic. However, the pathogen’s genetic diversity, geographic spread, and transmission dynamics during this early period of Y. pestis evolution are largely unexplored. Here, we describe a set of ancient plague genomes up to 5,000 y old from across Eurasia. Our data demonstrate that two genetically distinct forms of Y. pestis evolved in parallel and were both distributed across vast geographic distances, potentially occupying different ecological niches. Interpreted within the archeological context, our results suggest that the spread of plague during this period was linked to increased human mobility and intensification of animal husbandry., The bacterial pathogen Yersinia pestis gave rise to devastating outbreaks throughout human history, and ancient DNA evidence has shown it afflicted human populations as far back as the Neolithic. Y. pestis genomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to its emergence from a Yersinia pseudotuberculosis-like progenitor; however, the number of reconstructed LNBA genomes are too few to explore its diversity during this critical period of development. Here, we present 17 Y. pestis genomes dating to 5,000 to 2,500 y BP from a wide geographic expanse across Eurasia. This increased dataset enabled us to explore correlations between temporal, geographical, and genetic distance. Our results suggest a nonflea-adapted and potentially extinct single lineage that persisted over millennia without significant parallel diversification, accompanied by rapid dispersal across continents throughout this period, a trend not observed in other pathogens for which ancient genomes are available. A stepwise pattern of gene loss provides further clues on its early evolution and potential adaptation. We also discover the presence of the flea-adapted form of Y. pestis in Bronze Age Iberia, previously only identified in in the Caucasus and the Volga regions, suggesting a much wider geographic spread of this form of Y. pestis. Together, these data reveal the dynamic nature of plague’s formative years in terms of its early evolution and ecology., This study was funded by the Max Planck Society, Max Planck Harvard Research Center for the Archaeoscience of the Ancient Mediterranean and the European Research Council under the European Union’s Horizon 2020 research and innovation program under Grant Agreement 771234 – PALEoRIDER (to W.H.), 856453 – HistoGenes (to J.K.), and 834616 – ARCHCAUCASUS (to S.H.). The Heidelberg Academy of Science financed the genetic and archeological research on human individuals from the Augsburg region within the project WIN Kolleg: “Times of Upheaval: Changes of Society and Landscape at the Beginning of the Bronze Age. M.E. was supported by the award “Praemium Academiae” of the Czech Academy of Sciences. M.D. was supported by the project RVO 67985912 of the Institute of Archaeology of the Czech Academy of Sciences, Prague. I.O. was supported by the Ramón y Cajal grant from Ministerio de Ciencia e Innovación, Spanish Government (RYC2019-027909-I). A. H€ubner was supported by the Deutsche Forschungsgemeinschaft under Germany’s Excellence Strategy (EXC 2051 – Project-ID 390713860). J.F.-E. and J.A.M.-A. were supported by the Diputación Foral de Alava, IT 1223-19, Gobierno Vasco. A. Buzhilova was supported by the Center of Information Technologies and Systems (CITIS), Moscow, Russia 121041500329-0. L. M., L.B.D., and E. Khussainova were supported by the Grant AP08856654, Ministry of Education and Science of the Republic of Kazakhstan. A. Beisenov was supported by the Grant AP08857177, Ministry of Education and Science of the Republic of Kazakhstan.

Ethiopia is one of the sub-Saharan countries hit hard by the HIV epidemic. Previous studies have shown that subtype C dominates the Ethiopian HIV-1 epidemic, but the evolutionary and temporal dynamics of HIV-1 in Ethiopia have not been closely scrutinized. Understanding the evolutionary and epidemiological pattern of HIV is vital to monitor the spread, evaluate and implement HIV prevention strategies.We analyzed 1,276 Ethiopian HIV-1 subtype C polymerase (Our analysis revealed that the Ethiopian HIV-1 epidemic originated from two independent introductions at the beginning of the 1970s and 1980s from eastern and southern African countries, respectively, followed by epidemic growth reaching its maximum in the early 1990s. We identified three large clusters with a majority of Ethiopian sequences. Phylodynamic analyses revealed that all three clusters were characterized by high transmission rates during the early epidemic, followed by a decline in HIV-1 transmissions after 1990. RThe rapid decline in the HIV epidemic took place a decade before introducing antiretroviral therapy in Ethiopia and coincided with early behavioral, preventive, and awareness interventions implemented in the country. Our findings highlight the importance of behavioral interventions and antiretroviral therapy scale-up to halt and maintain HIV transmissions at low levels (R

It has been hypothesized that the Neolithic transition towards an agricultural and pastoralist economy facilitated the emergence of human adapted pathogens. Here, we recovered eight Salmonella enterica subsp. enterica genomes from human skeletons of transitional foragers, pastoralists, and agro-pastoralists in western Eurasia that were up to 6,500 years old. Despite the high genetic diversity of S. enterica all ancient bacterial genomes clustered in a single previously uncharacterized branch that contains S. enterica adapted to multiple mammalian species. All ancient bacterial genomes from prehistoric (agro-)pastoralists fall within a part of this branch that also includes the human-specific S. enterica Paratyphi C, illustrating the evolution of a human pathogen over a period of five thousand years. Bacterial genomic comparisons suggest that the earlier ancient strains were not host specific, differed in pathogenic potential, and experienced convergent pseudogenization that accompanied their downstream host adaptation. These observations support the concept that the emergence of human adapted S. enterica is linked to human cultural transformations.

Bayesian phylogenetic methods provide a set of tools to efficiently evaluate large linguistic datasets by reconstructing phylogenies—family trees—that represent the history of language families. These methods provide a powerful way to test hypotheses about prehistory, regarding the subgrouping, origins, expansion, and timing of the languages and their speakers. Through phylogenetics, we gain insights into the process of language evolution in general and into how fast individual features change in particular. This article introduces Bayesian phylogenetics as applied to languages. We describe substitution models for cognate evolution, molecular clock models for the evolutionary rate along the branches of a tree, and tree generating processes suitable for linguistic data. We explain how to find the best-suited model using path sampling or nested sampling. The theoretical background of these models is supplemented by a practical tutorial describing how to set up a Bayesian phylogenetic analysis using the software tool BEAST2. 1. Introduction 2. Bayesian phylogenetics 3. Models of evolution 4. Rate variation and calibration 5. Tree priors 6. Choosing the best analysis 7. Exploring the space of trees using BEAST2 8. Hypothesis testing with trees 9. Conclusion

Healthcare-associated outbreaks of vancomycin-resistant Enterococcus faecium (VREfm) are a worldwide problem with increasing prevalence. The genomic plasticity of this hospital-adapted pathogen contributes to its efficient spread despite infection control measures. Here, we aimed to identify the genomic and phenotypic determinants of healthcare-associated transmission of VREfm. We assessed the VREfm transmission networks at the tertiary-care University Hospital of Zurich (USZ) between October 2014 and February 2018 and investigated microevolutionary dynamics of this pathogen. We performed whole-genome sequencing for the 69 VREfm isolates collected during this timeframe and assessed the population structure and variability of the vancomycin resistance transposon. Phylogenomic analysis allowed us to reconstruct transmission networks and to unveil external or indirect transmission networks, not detectable by traditional surveillance. Notably, it unveiled a persistent clone, sampled 31 times over a 29-month period. Exploring the evolutionary dynamics of this clone and characterizing the phenotypic consequences revealed the spread of a variant with decreased daptomycin susceptibility and the acquired ability to utilize N-acetyl-galactosamine (GalNAc), one of the primary constituents of the human gut mucins. This nutrient utilization advantage was conferred by a novel plasmid, termed pELF_USZ, which exhibited a linear topology. This plasmid, which was harbored by two distinct clones, was transferable by conjugation. Overall, this work provides an example of the potential of the integration of epidemiological, functional genomic and evolutionary perspectives to understand adaptation strategies contributing to the successful spread of VREfm.Significance statementSequencing microbial pathogens causing outbreaks has become a common practice to characterize transmission networks. In addition to the signal provided by vertical evolution, bacterial genomes harbor mobile genetic elements, shared horizontally between clones. While macroevolutionary studies have revealed an important role of plasmids and genes encoding carbohydrate utilization systems in the adaptation of Enterococcus faecium to the hospital environment, mechanisms of dissemination and the specific function of many of these genetic determinants remain to be elucidated. Here, we characterize a plasmid providing a nutrient utilization advantage and show evidence for its clonal and horizontal spread at a local scale. Further studies integrating epidemiological, functional genomics and evolutionary perspectives will be critical to identify changes shaping the success of this pathogen.

Background After a year of the global SARS-CoV-2 pandemic, a highly dynamic genetic diversity is surfacing. Among nearly 1000 reported virus lineages, dominant lineages such as B.1.1.7 or B.1.351 attract media attention with questions regarding vaccine efficiency and transmission potential. In response to the pandemic, the Jena University Hospital began sequencing SARS-CoV-2 samples in Thuringia in early 2020.Methods Viral RNA was sequenced in tiled amplicons using Nanopore sequencing. Subsequently, bioinformatic workflows were used to process the generated data. As a genomic background, 9,642 representative SARS-CoV-2 genomes (1,917 of German origin) were extracted from more than 300.000 genomes.Results In a comprehensive bioinformatics analysis, we have set Thuringian isolates in the German, European and global context. In Thuringia, a largely rural German region without an international airport and a population density below the German average, we discovered many of the common “EU lineages”. German samples are scattered across eight major clades, and Thuringian samples occupy four of them.Conclusion The rapid emergence and spread of novel variants are of great concern as these lineages could transmit more efficiently, evade current vaccine efforts or undermine diagnostic test accuracy. To anticipate and mitigate these threats, a continuous molecular surveillance is essential.Key messagesBioinformatics analysis of 1,917, 4,251, and 3,474 SARS-CoV-2 genomes from Germany, the EU (except Germany), and non-EU, respectively, subsampled from more than 300,000 public genomes and placed in the context of Thuringian sequencesConstant antigenic drift for SARS-CoV-2 and no clear pattern or clustering is visible in Thuringia based on the current number of samplesCurrently over 100 described lineages are identified in Germany and only a subset (9) are detected in Thuringia so far, most likely due to genetic undersamplingFrom a national perspective, it is likely that high-frequency lineages, which are currently spreading throughout Europe, will eventually also reach ThuringiaSystematic and dense molecular surveillance via whole-genome sequencing is needed to detect concerning new lineages early, limit spread and adjust vaccines if necessaryCompeting Interest StatementThe authors have declared no competing interest.Funding StatementThe work is funded by the German Ministry of Education and Research (BMBF), grant number 01KX2021, and the Thuringian Region Government, grant number TZUZI82094.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:not applicableAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data is available on GISAID. Introduction Methods - Nanopore sequencing and genome reconstruction - Time tree creation Results - Most highly prevalent SARS-CoV-2 lineages in Germany detected in Thuringia - Genetic divergence and current lineage distribution Discussion

Hepatitis B virus (HBV) has been infecting humans for millennia and remains a global health problem, but its past diversity and dispersal routes are largely unknown. We generated HBV genomic data from 137 Eurasians and Native Americans dated between ~10,500 and ~400 years ago. We date the most recent common ancestor of all HBV lineages to between ~20,000 and 12,000 years ago, with the virus present in European and South American hunter-gatherers during the early Holocene. After the European Neolithic transition, Mesolithic HBV strains were replaced by a lineage likely disseminated by early farmers that prevailed throughout western Eurasia for ~4000 years, declining around the end of the 2nd millennium BCE. The only remnant of this prehistoric HBV diversity is the rare genotype G, which appears to have reemerged during the HIV pandemic., The research was funded by the Max Planck Society, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (771234–PALEoRIDER, to W.H.; 805268–CoDisEASe to K. Bos; 834616–ARCHCAUCASUS to S.H.), the Slovak Academy of Sciences and the European Union’s Seventh Framework Programme and Marie Curie Actions under the Programme SASPRO (1340/03/03 to P.C.R.), the ERA.NET RUS Plus–S&T programm of the European Union’s Seventh Framework Programme (277–BIOARCCAUCASUS to S.Re. and S.H.), the Werner Siemens Stiftung (“Paleobiochemistry”, to CW), the Award Praemium Academiae of the Czech Academy of Sciences (to M.E.), the Institute of Archaeology of the Czech Academy of Sciences (RVO 67985912, to M.Dobe.), the Russian Foundation for Basic Research (19-09-00354a, to M.K.K. and V.V.K.; 19-78-10053 to SSh), the German Research Foundation (DFG-HA-5407/4-1–INTERACT to W.H. and RE2688/2 to S.Re.), the French National Research Agency (ANR-17-FRAL-0010–INTERACT, to M.F.D., M.Ri., S.Ro., S.Sai., D.Bi., and P.Le.), the Wenner-Gren Dissertation Fieldwork Grant (9558 to S.Sab.), and the Ministry of Education and Science of the Republic of Kazakhstan (AP08856654 to L.B.D., L.M., and E.Kh. and AP08857177 to A.Z.B.).

Syphilis is a globally re-emerging disease, which has marked European history with a devastating epidemic at the end of the 15th century. Together with non-venereal treponemal diseases, like bejel and yaws, which are found today in subtropical and tropical regions, it currently poses a substantial health threat worldwide. The origins and spread of treponemal diseases remain unresolved, including syphilis’ potential introduction into Europe from the Americas. Here, we present the first genetic data from archaeological human remains reflecting a high diversity of Treponema pallidum in early modern Europe. Our study demonstrates that a variety of strains related to both venereal syphilis and yaws-causing T. pallidum subspecies were already present in Northern Europe in the early modern period. We also discovered a previously unknown T. pallidum lineage recovered as a sister group to yaws- and bejel-causing lineages. These findings imply a more complex pattern of geographical distribution and etiology of early treponemal epidemics than previously understood., Current Biology, 30 (19), ISSN:0960-9822, ISSN:1879-0445

SummarySexually transmitted (venereal) syphilis marked European history with a devastating epidemic at the end of the 15thcentury, and is currently re-emerging globally. Together with non-venereal treponemal diseases, like bejel and yaws, found in subtropical and tropical regions, it poses a prevailing health threat worldwide. The origins and spread of treponemal diseases remain unresolved, including syphilis’ potential introduction into Europe from the Americas. Here, we present the first genetic data from archaeological human remains reflecting a previously unknown diversity ofTreponema pallidumin historical Europe. Our study demonstrates that a variety of strains related to both venereal syphilis and yaws were already present in Northern Europe in the early modern period. We also discovered a previously unknownT. pallidumlineage recovered as a sister group to yaws and bejel. These findings imply a more complex pattern of geographical prevalence and etiology of early treponemal epidemics than previously understood.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causesthe infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformaticstools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection,understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to getinsight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for theroutine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemicand evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets anddevelopment of therapeutic strategies. For each tool, we briefly describe its use case and how it advances researchspecifically for SARS-CoV-2. Fil: Hufsky, Franziska. Friedrich Schiller University Jena; Alemania Fil: Lamkiewicz, Kevin. Friedrich Schiller University Jena; Alemania Fil: Almeida, Alexandre. the Wellcome Sanger Institute; Reino Unido Fil: Aouacheria, Abdel. Centre National de la Recherche Scientifique; Francia Fil: Arighi, Cecilia. Biocuration and Literature Access at PIR; Estados Unidos Fil: Bateman, Alex. European Bioinformatics Institute. Head of Protein Sequence Resources; Reino Unido Fil: Baumbach, Jan. Universitat Technical Zu Munich; Alemania Fil: Beerenwinkel, Niko. Universitat Technical Zu Munich; Alemania Fil: Brandt, Christian. Jena University Hospital; Alemania Fil: Cacciabue, Marco Polo Domingo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación En Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Chuguransky, Sara Rocío. European Bioinformatics Institute; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Drechsel, Oliver. Robert Koch-Institute; Alemania Fil: Finn, Robert D.. Biocurator for Pfam and InterPro databases; Reino Unido Fil: Fritz, Adrian. Helmholtz Centre for Infection Research; Alemania Fil: Fuchs, Stephan. Robert Koch-Institute; Alemania Fil: Hattab, Georges. University Marburg; Alemania Fil: Hauschild, Anne Christin. University Marburg; Alemania Fil: Heider, Dominik. University Marburg; Alemania Fil: Hoffmann, Marie. Freie Universität Berlin; Alemania Fil: Hölzer, Martin. Friedrich Schiller University Jena; Alemania Fil: Hoops, Stefan. University of Virginia; Estados Unidos Fil: Kaderali, Lars. University Medicine Greifswald; Alemania Fil: Kalvari, Ioanna. European Bioinformatics Institute; Reino Unido Fil: von Kleist, Max. Robert Koch-Institute; Alemania Fil: Kmiecinski, Renó. Robert Koch-Institute; Alemania Fil: Kühnert, Denise. Max Planck Institute for the Science of Human History; Alemania Fil: Lasso, Gorka. Albert Einstein College of Medicine; Estados Unidos Fil: Libin, Pieter. Hasselt University; Bélgica Fil: List, Markus. Universitat Technical Zu Munich; Alemania Fil: Löchel, Hannah F.. University Marburg; Alemania

The multi-type birth-death model with sampling is a phylodynamic model which enables quantification of past population dynamics in structured populations, based on phylogenetic trees. The BEAST 2 package bdmm implements an algorithm for numerically computing the probability density of a phylogenetic tree given the population dynamic parameters under this model. In the initial release of bdmm, analyses were limited to trees consisting of up to approximately 250 genetic samples for numerical reasons. We implemented important algorithmic changes to bdmm which dramatically increase the number of genetic samples that can be analyzed, and improve the numerical robustness and efficiency of the calculations. Being able to use bigger datasets leads to improved precision of parameter estimates. Furthermore, we report on several model extensions to bdmm, inspired by properties common to empirical datasets. We apply this improved algorithm to two partly overlapping datasets of Influenza A virus HA sequences sampled around the world, one with 500 samples, the other with only 175, for comparison. We report and compare the global migration patterns and seasonal dynamics inferred from each dataset.AvailabilityThe latest release with our updates, bdmm 0.3.5, is freely available as an open access package of BEAST 2. The source code can be accessed at https://github.com/denisekuehnert/bdmm.

We study human origins from the related disciplines of archaeology, palaeoanthropology and allied geosciences, which are driven forward by making new discoveries in the field. Collectively, our scientific ecosystem informs climate change policy, heritage management and conservation practices. The pandemic has forced an inevitable pause on our work, but several scientific studies now indicate that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), may be here to stay. Critically for fieldwork and related travel considerations, the pandemic will increasingly display temporally and spatially fragmented peaks and troughs7. Complicating this is the fact that affected countries are not consistent in their public health decisions and application of World Health Organization (WHO) guidance, particularly in terms of easing containment measures. Regional and country-based variations in the availability and quality of appropriate healthcare also underline the importance of protecting at risk communities. [excerpt], peer-reviewed

We used Bayesian evolutionary analysis to study linguistic data and infer phylogenetic trees of language evolution. Languages were encoded as binary strings indicating the presence or absence of members of cognate classes, the equivalence of classes of words with similar meaning, and shared ancestry. These strings formed the alignment data used to compute the posterior likelihood of a tree with respect to Bayes’ formula. Informative priors are crucial for testing hypotheses regarding the age of common ancestry and divergence times and should include as much available information as possible. Here, we investigated the birth–death process as a method to construct tree priors specifically suitable for modeling the evolution of cognate data. To test these models, we will use a dataset of the languages from Vanuatu, an island nation featuring world’s highest language density.

Bayesian phylogenetic analysis allows for the estimation of the time to the most recent common ancestor (tMRCA) of sequences sampled at different times, as long as they prove to be ‘measurably evolving’, which means that the time between sampling dates was long enough to allow the appearance of a measurable amount of genetic changes. This ‘temporal signal’ can be tested with the software TempEst (Rambaut et al. 2016), which generates a regression of the root-to-tip genetic distance on sampling times and finds the best-fitting root that produces the lowest residual sum of squares. For the case of pathogen single nucleotide polymorphism (SNP) alignments, containing both modern and ancient sequences, it is common to find positions with unknown nucleotides (gaps) that could generate problems in the phylogenetic reconstruction. Thus, the use of complete deletion alignments is fairly common. This practice, however, could cause the loss of potentially important information, so we aim to identify the most suitable deletion threshold for the proportion of unknown sites allowed for a given alignment before proceeding to analyze the data in BEAST. Here, I present the temporal signal of 204 whole-genome sequences of Yersinia pestis, a zoonotic gram-negative bacteria and causal agent of the bubonic, pneumonic, and systemic plagues. I demonstrate measurable temporal signal for the alignment with thresholds of 0–10 per cent for the proportion of unknown sites per SNP. The results showed that a complete deletion alignment presented the lowest correlation and greatest residual mean squared values. The best threshold depends on the method used to find the best root, but appears to be between 7–9 per cent.

The last century has witnessed progress in the study of ancient infectious disease from purely medical descriptions of past ailments to dynamic interpretations of past population health that draw upon multiple perspectives. The recent adoption of high-throughput DNA sequencing has led to an expanded understanding of pathogen presence, evolution, and ecology across the globe. This genomic revolution has led to the identification of disease-causing microbes in both expected and unexpected contexts, while also providing for the genomic characterization of ancient pathogens previously believed to be unattainable by available methods. In this review we explore the development of DNA-based ancient pathogen research, the specialized methods and tools that have emerged to authenticate and explore infectious disease of the past, and the unique challenges that persist in molecular paleopathology. We offer guidelines to mitigate the impact of these challenges, which will allow for more reliable interpretations of data in this rapidly evolving field of investigation.

The forced relocation of several thousand Africans during Mexico?s historic period has so far been documented mostly through archival sources, which provide only sparse detail on their origins and lived experience. Here, we employ a bioarchaeological approach to explore the life history of three 16th century Africans from a mass burial at the San José de los Naturales Royal Hospital in Mexico City. Our approach draws together ancient genomic data, osteological analysis, strontium isotope data from tooth enamel, δ13C and δ15N isotope data from dentine, and ethnohistorical information to reveal unprecedented detail on their origins and health. Analyses of skeletal features, radiogenic isotopes, and genetic data from uniparental, genome-wide, and human leukocyte antigen (HLA) markers are consistent with a Sub-Saharan African origin for all three individuals. Complete genomes of Treponema pallidum sub. pertenue (causative agent of yaws) and hepatitis B virus (HBV) recovered from these individuals provide insight into their health as related to infectious disease. Phylogenetic analysis of both pathogens reveals their close relationship to strains circulating in current West African populations, lending support to their origins in this region. The further relationship between the treponemal genome retrieved and a treponemal genome previously typed in an individual from Colonial Mexico highlights the role of the transatlantic slave trade in the introduction and dissemination of pathogens into the New World. Putting together all lines of evidence, we were able to create a biological portrait of three individuals whose life stories have long been silenced by disreputable historical events.

As multi-drug resistant tuberculosis (MDR-TB) continues to spread, investigating the transmission potential of different drug-resistant strains becomes an ever more pressing topic in public health. While phylogenetic and transmission tree inferences provide valuable insight into possible transmission chains, phylodynamic inference combines evolutionary and epidemiological analyses to estimate the parameters of the underlying epidemiological processes, allowing us to describe the overall dynamics of disease spread in the population. In this study, we introduce an approach to Mycobacterium tuberculosis (M. tuberculosis) phylodynamic analysis employing an existing computationally efficient model to quantify the transmission fitness costs of drug resistance with respect to drug-sensitive strains. To determine the accuracy and precision of our approach, we first perform a simulation study, mimicking the simultaneous spread of drug-sensitive and drug-resistant tuberculosis (TB) strains. We analyse the simulated transmission trees using the phylodynamic multi-type birth–death model (MTBD, (Kühnert et al., 2016)) within the BEAST2 framework and show that this model can estimate the parameters of the epidemic well, despite the simplifying assumptions that MTBD makes compared to the complex TB transmission dynamics used for simulation. We then apply the MTBD model to an M. tuberculosis lineage 4 dataset that primarily consists of MDR sequences. Some of the MDR strains additionally exhibit resistance to pyrazinamide — an important first-line anti-tuberculosis drug. Our results support the previously proposed hypothesis that pyrazinamide resistance confers a transmission fitness cost to the bacterium, which we quantify for the given dataset. Importantly, our sensitivity analyses show that the estimates are robust to different prior distributions on the resistance acquisition rate, but are affected by the size of the dataset – i.e. we estimate a higher fitness cost when using fewer sequences for analysis. Overall, we propose that MTBD can be used to quantify the transmission fitness cost for a wide range of pathogens where the strains can be appropriately divided into two or more categories with distinct properties., Epidemics, 36, ISSN:1878-0067, ISSN:1755-4365

HIV-1 non-B infections have been increasing in Europe for several years. In Germany, subtype A belongs to the most abundant non-B subtypes showing an increasing prevalence of 8.3% among new infections in 2016. Here we trace the origin and examine the current spread of the German HIV-1 subtype A epidemic. Bayesian coalescence and birth-death analyses were performed with 180 German HIV-1 pol sequences and 528 related and publicly available sequences to reconstruct the population dynamics and fluctuations for each of the transmission groups. Our reconstructions indicate two distinct sources of the German subtype A epidemic, with an Eastern European and an Eastern African lineage both cocirculating in the country. A total of 13 German-origin clusters were identified; among these, 6 clusters showed recent activity. Introductions leading to further countrywide spread originated predominantly from Eastern Africa when introduced before 2005. Since 2005, however, spreading introductions have occurred exclusively within the Eastern European clade. Moreover, we observed changes in the main route of subtype A transmission. The beginning of the German epidemic (1985 to 1995) was dominated by heterosexual transmission of the Eastern African lineage. Since 2005, transmissions among German men who have sex with men (MSM) have been increasing and have been associated with the Eastern European lineage. Infections among people who inject drugs dominated between 1998 and 2005. Our findings on HIV-1 subtype A infections provide new insights into the spread of this virus and extend the understanding of the HIV epidemic in Germany. IMPORTANCE HIV-1 subtype A is the second most prevalent subtype worldwide, with a high prevalence in Eastern Africa and Eastern Europe. However, an increase of non-B infections, including subtype A infections, has been observed in Germany and other European countries. There has simultaneously been an increased flow of refugees into Europe and especially into Germany, raising the question of whether the surge in non-B infections resulted from this increased immigration or whether German transmission chains are mainly involved. This study is the first comprehensive subtype A study from a western European country analyzing in detail its phylogenetic origin, the impact of various transmission routes, and its current spread. The results and conclusions presented provide new and substantial insights for virologists, epidemiologists, and the general public health sector. In this regard, they should be useful to those authorities responsible for developing public health intervention strategies to combat the further spread of HIV/AIDS.

The origin of Yersinia pestis and the early stages of its evolution are fundamental subjects of investigation given its high virulence and mortality that resulted from past pandemics. Although the earliest evidence of Y. pestis infections in humans has been identified in Late Neolithic/Bronze Age Eurasia (LNBA 5000–3500y BP), these strains lack key genetic components required for flea adaptation, thus making their mode of transmission and disease presentation in humans unclear. Here, we reconstruct ancient Y. pestis genomes from individuals associated with the Late Bronze Age period (~3800 BP) in the Samara region of modern-day Russia. We show clear distinctions between our new strains and the LNBA lineage, and suggest that the full ability for flea-mediated transmission causing bubonic plague evolved more than 1000 years earlier than previously suggested. Finally, we propose that several Y. pestis lineages were established during the Bronze Age, some of which persist to the present day., Yersinia pestis has caused infections (plague) in humans since the Early Bronze Age (5000 years ago). Here, Spyrou et al. reconstruct Y. pestis genomes from Late Bronze Age individuals, and find genomic evidence compatible with flea-mediated transmission causing bubonic plague.