Nielsen Kaare M, Bøhn Thomas, Townsend Jeffrey P
Department of Pharmacy, Faculty of Health Sciences, University of Tromsø Tromsø, Norway ; GenØk-Centre for Biosafety, The Science Park Tromsø, Norway.
Department of Biostatistics, Yale University New Haven, CT, USA ; Program in Computational Biology and Bioinformatics, Yale University New Haven, CT, USA ; Program in Microbiology, Yale University New Haven, CT, USA.
Front Microbiol. 2014 Jan 7;4:415. doi: 10.3389/fmicb.2013.00415.
Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research.
水平基因转移（HGT）使细菌能够获取、共享和重组遗传变异，从而产生仅通过突变过程无法获得的遗传多样性。在大多数情况下，对进化上成功的HGT事件的观察依赖于最初罕见事件的结果，这些事件会在新宿主中产生新功能，并对宿主适应性产生积极影响。相反，由于转化体缺乏复制成功，细菌群体中发生的绝大多数HGT事件将无法被检测到。此外，其他对新宿主非常有益的HGT事件可能由于与供体生物体缺乏物理接近性、缺乏合适的基因转移机制、遗传兼容性以及时空发生的随机性而无法发生。在细菌群体中检测HGT事件的实验尝试通常集中在转化细胞或其直接后代上。然而，在大型结构化群体中发生的罕见HGT事件不太可能达到能够立即识别它们的相对群体规模；抗生素赋予的异常强烈的正选择情况除外。大多数HGT事件预计不会将宿主存活的可能性改变到如此极端的程度，只会使宿主适应性发生微小变化。由于细菌群体规模庞大且涉及时间尺度，HGT的过程和结果往往不适合进行实验研究。因此，对具有不同HGT速率和由此产生的适应性变化的细菌生长动态进行群体遗传建模，对于指导采样设计和预测在实验室或自然环境中发生HGT时的实际检测时间框架是必要的。在这里，我们回顾关键的群体遗传参数，考虑它们的复杂性，并突出有待进一步研究的知识空白。
