Ecological niche modeling of Bacillus anthracis on three continents: evidence for genetic-ecological divergence?
Ecological niche modeling of Bacillus anthracis on three continents: evidence for genetic-ecological divergence?
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DOI：
10.1371/journal.pone.0072451
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Blackburn JK
中科院分区：
文献类型：
--
作者：
Mullins JC;Garofolo G;Van Ert M;Fasanella A;Lukhnova L;Hugh-Jones ME;Blackburn JK
我们模拟了在美国、意大利和哈萨克斯坦的全球成功的炭疽杆菌亚系的生态位，以更好地了解炭疽的地理分布以及区域人口与生态之间的潜在关联。国家特定的生态位模型的开发和快速转移到其他国家，以确定病原体的存在是否可以准确地预测新的景观。本地模型准确地预测了每个国家内的流行地区，但转移的模型未能预测国外的已知发生。虽然应考虑变量选择和遗传数据的局限性的影响，结果表明不同的生态协会的B。炭疽菌种群在每个国家，并可能反映生态位专业化的亚系。我们的研究结果提供了指导，为这种病原体开发准确的生态位模型，模型应开发区域，本地景观，并考虑到人口遗传学。进一步的基因组分析将提高我们对B的遗传生态动力学的理解。炭疽病在这些国家蔓延，并可能导致更精确的监测和积极的疫苗接种计划的预测模型。进一步的研究应评估本地和转移模型的变量选择的影响。
We modeled the ecological niche of a globally successful Bacillus anthracis sublineage in the United States, Italy and Kazakhstan to better understand the geographic distribution of anthrax and potential associations between regional populations and ecology. Country-specific ecological-niche models were developed and reciprocally transferred to the other countries to determine if pathogen presence could be accurately predicted on novel landscapes. Native models accurately predicted endemic areas within each country, but transferred models failed to predict known occurrences in the outside countries. While the effects of variable selection and limitations of the genetic data should be considered, results suggest differing ecological associations for the B. anthracis populations within each country and may reflect niche specialization within the sublineage. Our findings provide guidance for developing accurate ecological niche models for this pathogen; models should be developed regionally, on the native landscape, and with consideration to population genetics. Further genomic analysis will improve our understanding of the genetic-ecological dynamics of B. anthracis across these countries and may lead to more refined predictive models for surveillance and proactive vaccination programs. Further studies should evaluate the impact of variable selection of native and transferred models.
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影响因子：
6.7
作者：
Fisher, Matthew C;Hanage, William P;de Hoog, Sybren;Johnson, Elizabeth;Smith, Michael D;White, Nicholas J;Vanittanakom, Nongnuch
通讯作者：
Vanittanakom, Nongnuch
影响因子：
3.8
作者：
Beyer W;Bellan S;Eberle G;Ganz HH;Getz WM;Haumacher R;Hilss KA;Kilian W;Lazak J;Turner WC;Turnbull PC
通讯作者：
Turnbull PC
影响因子：
3.3
作者：
Broennimann, Olivier;Guisan, Antoine
通讯作者：
Guisan, Antoine
影响因子：
1.3
作者：
Blackburn, Jason K.;Curtis, Andrew;Hugh-Jones, Martin E.
通讯作者：
Hugh-Jones, Martin E.
影响因子：
3.9
作者：
Araujo, Miguel B.;Guisan, Antoine
通讯作者：
Guisan, Antoine