Dating the emergence of human pathogens

doi:10.1126/science.abc5746

GSTDTAP > 气候变化

DOI	10.1126/science.abc5746
	Dating the emergence of human pathogens
	Simon Y. W. Ho; Sebastián Duchêne
	2020-06-19
发表期刊	Science
出版年	2020
英文摘要	Understanding the emergence and evolution of human pathogens plays a pivotal role in epidemiology and in predicting the trajectories of outbreaks. The application of phylogenetic methods to pathogen genomes has provided a range of insights into their evolutionary dynamics ([ 1 ][1]). In many cases, phylogenetic methods can use the sampling dates of the genomes to reconstruct the evolutionary time scales of viruses, bacteria, and other pathogens. Ancient genomes can increase the power of these approaches by narrowing the estimated time window of pathogen emergence and by augmenting the evolutionary temporal signal in the genetic data. On page 1367 of this issue, Düx et al. ([ 2 ][2]) show how a century-old genome of Measles morbillivirus , extracted from human lung tissue, can help efforts to pinpoint the time of emergence of measles. A distinctive feature shared by many human pathogens is that their evolution can be observed over epidemiological time scales. These pathogens can undergo measurable genetic change even between successive sampling dates. The evolutionary rates of these pathogens can be estimated by analyzing their genomes while taking the sampling dates into account ([ 3 ][3]). Datasets that are amenable to such analysis are referred to as having “temporal signal” ([ 4 ][4]). Strong temporal signals are often detected in analyses of rapidly evolving RNA viruses. However, they can also be detected in genomic data from more slowly evolving bacteria, as demonstrated in studies of the tuberculosis pathogen Mycobacterium tuberculosis ([ 5 ][5]) and Salmonella enterica ([ 6 ][6]). Conversely, temporal signals have proven to be rather more elusive in some pathogens, such as the bacterium that causes leprosy, Mycobacterium leprae ([ 7 ][7]). The temporal signal can be amplified by widening the sampling period, which is most effectively done by sequencing genomes from samples in historical collections or from archaeological remains. These efforts have been substantially aided by advances in molecular techniques and sequencing technology. However, obtaining genomic data from RNA viruses (such as the measles virus), which degrade rapidly in the environment, continues to be extremely challenging ([ 8 ][8]). In this regard, the sequencing of a century-old genome of the measles virus by Düx et al. is a profound achievement. Increasing the temporal signal in the measles virus genomic dataset leads to a more accurate estimate of the evolutionary rate of the pathogen, which allows inference of the date of the common ancestor of the sampled lineages with greater confidence. This date places a minimum bound on the emergence of the pathogen in humans (see the figure), because the common ancestor implies a human-to-human transmission event. ![Figure][9] Pinpointing the emergence of human pathogens The emergence of human pathogens can be bracketed between their divergence from their closest relatives and the common ancestor of all sampled lineages of the pathogen. Including ancient genomes expands the sampling period and can reveal extinct lineages of the pathogen. GRAPHIC: H. BISHOP/ SCIENCE The inclusion of ancient genomes can also push back the date of the common ancestor of the pathogen by sampling extinct lineages ([ 8 ][8]). In this way, ancient genomes are able to cast light on a hidden period of evolutionary history, an effect that is seen in the analysis of the measles virus by Düx et al. and in previous studies of the bacterium S. enterica ([ 6 ][6]), smallpox (variola) virus ([ 9 ][10]), and the plague bacterium Yersinia pestis ([ 10 ][11]). Sampling extinct lineages is particularly important for pathogens that have undergone recent reductions in genetic diversity. These include viruses that have been subject to large-scale vaccination programs, such as measles (as reported by Düx et al. ), as well as those that have been targeted by extensive treatment and prevention strategies, such as human immunodeficiency virus type 1 (HIV-1) ([ 11 ][12]). In these cases, there is likely to have been a substantial assortment of extinct lineages that have not left any traces in the present-day population of the pathogen. The maximum age of a pathogen's emergence in humans is bounded by its evolutionary divergence from its closest known relative. Düx et al. estimated that the measles virus diverged from its closest relative, the cattle pathogen Rinderpest morbillivirus , more than two millennia ago. The authors then posited that the establishment of measles in humans coincided with population growth in Eurasia between 2000 and 2500 years ago, although it could have occurred much more recently. This estimate is consistent with other studies that have suggested that the rise of human settlements facilitated the spread of some infectious pathogens, including the plague bacterium ([ 12 ][13]). For pathogens with sources that are less well understood, the window of uncertainty can be narrowed by searching for close relatives of the pathogen. Such a search can be targeted at candidate reservoir hosts or can involve a broader survey of pathogen diversity across wildlife. For example, the growing application of metagenomics (nontargeted genome sequencing) approaches has led to a staggering expansion of the known diversity of viruses ([ 13 ][14]), while revealing that animal hosts can carry a wide range of viruses in abundance. Nevertheless, huge swathes of the virosphere remain unexplored. Phylogenetic dating analyses of pathogens have come under the spotlight in the ongoing coronavirus disease 2019 (COVID-19) pandemic. The closest known relative of the causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a coronavirus from a horseshoe bat, but these two viruses diverged from each other several decades ago ([ 14 ][15]). The most recent common ancestor of sampled SARS-CoV-2 genomes has been dated to late November to early December 2019 ([ 15 ][16]). The gap between these two events has hindered attempts to identify the reservoir host of SARS-CoV-2 and the timing of the zoonotic spillover into human hosts. Further genomic data from historical and ancient samples, along with more comprehensive and intensive surveys of viruses harbored in wildlife, will lead to continued refinements of the time scales of emergence and evolution of human pathogens. 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领域	气候变化 ; 资源环境
URL	查看原文
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/276683
专题	气候变化资源环境科学
推荐引用方式 GB/T 7714	Simon Y. W. Ho,Sebastián Duchêne. Dating the emergence of human pathogens[J]. Science,2020.
APA	Simon Y. W. Ho,&Sebastián Duchêne.(2020).Dating the emergence of human pathogens.Science.
MLA	Simon Y. W. Ho,et al."Dating the emergence of human pathogens".Science (2020).