Predicting the effects of parasite co-infection across species boundaries.

Predicting the effects of parasite co-infection across species boundaries.
复制标题

DOI:
10.1098/rspb.2017.2610
复制
发表时间:
2018-03-14
期刊:
Proceedings. Biological sciences
影响因子:
--
通讯作者:
Viney ME
Viney ME
中科院分区:
其他
文献类型:
--
作者:
Lello J;McClure SJ;Tyrrell K;Viney ME

文献摘要

参考文献

被引文献

相似文献

宿主同时感染寄生虫是正常的。共感染物种之间的相互作用可能产生深远的影响,包括改变寄生虫传播动力学,改变疾病严重程度和混淆寄生虫控制的尝试。尽管合并感染很重要,但目前还没有办法预测不同的寄生虫物种如何相互作用,也没有预测这些相互作用的后果。在这里,我们展示了一种方法,使这样的预测,通过确定两个线虫寄生虫群体的分类和特点的寄生虫生态位。从一个主机系统(野兔)中的两个定义的组之间的相互作用的理解,我们预测如何两个不同的线虫物种,从相同的定义的组,将在不同的主机系统(羊)的共同感染的相互作用,然后我们测试实验。我们表明,正如预测的那样,在混合感染中,血线虫捻转血矛线虫抑制绵羊免疫反应的各个方面,从而促进线虫蛇形毛圆线虫的建立和/或存活; colubriformis诱导的免疫应答对H.扭曲据我们所知,这项工作是第一次使用来自一个宿主系统的经验数据来成功预测第二宿主物种中不同共感染的具体结果。因此,这项研究迈出了第一步,确定了一个实用的框架,预测种间寄生虫在其他动物系统的相互作用。
It is normal for hosts to be co-infected by parasites. Interactions among co-infecting species can have profound consequences, including changing parasite transmission dynamics, altering disease severity and confounding attempts at parasite control. Despite the importance of co-infection, there is currently no way to predict how different parasite species may interact with one another, nor the consequences of those interactions. Here, we demonstrate a method that enables such prediction by identifying two nematode parasite groups based on taxonomy and characteristics of the parasitological niche. From an understanding of the interactions between the two defined groups in one host system (wild rabbits), we predict how two different nematode species, from the same defined groups, will interact in co-infections in a different host system (sheep), and then we test this experimentally. We show that, as predicted, in co-infections, the blood-feeding nematode Haemonchus contortus suppresses aspects of the sheep immune response, thereby facilitating the establishment and/or survival of the nematode Trichostrongylus colubriformis; and that the T. colubriformis-induced immune response negatively affects H. contortus. This work is, to our knowledge, the first to use empirical data from one host system to successfully predict the specific outcome of a different co-infection in a second host species. The study therefore takes the first step in defining a practical framework for predicting interspecific parasite interactions in other animal systems.
DOI: 10.1016/s0020-7519(05)80009-8
发表时间: 1992-05-01
影响因子: 4
作者:
COYNE, MJ;SMITH, G
通讯作者: SMITH, G
DOI: 10.1007/s11250-015-0815-6
发表时间: 2015-06-01
影响因子: 1.7
作者:
Getachew, Tesfaye;Alemu, Biruk;Notter, David Russell
通讯作者: Notter, David Russell
DOI: 10.1073/pnas.0707221105
发表时间: 2008-01-15
影响因子: 11.1
作者:
Graham, Andrea L.
通讯作者: Graham, Andrea L.
DOI: 10.1016/s0304-4017(02)00386-2
发表时间: 2003-02-28
影响因子: 2.6
作者:
Audebert, F;Vuong, PN;Durette-Desset, MC
通讯作者: Durette-Desset, MC
DOI: 10.1016/0020-7519(90)90151-c
发表时间: 1990-05-01
影响因子: 4
作者:
DOBSON, RJ;WALLER, PJ;DONALD, AD
通讯作者: DONALD, AD