EAGER:  High-throughput, culture-independent technique identifying cyanobacteria infections to improve understanding of carbon biogeochemical cycling

GSTDTAP

项目编号	1820652
	EAGER: High-throughput, culture-independent technique identifying cyanobacteria infections to improve understanding of carbon biogeochemical cycling
	Sarah Preheim
主持机构	Johns Hopkins University
项目开始年	2018
	2018-03-01
项目结束日期	2020-02-29
资助机构	US-NSF
项目类别	Standard Grant
项目经费	297545(USD)
国家	美国
语种	英语
英文摘要	Viruses in the ocean are 10 times more abundant than bacteria and kill 10-66% of bacterial cells daily. Viral infections of bacteria, such as of photosynthetic cyanobacteria that form the base of the food web, impact the flow of energy and carbon within the marine ecosystem. Thus, viral infections dramatically alter important biogeochemical and ecological factors in the ocean, such as how much carbon dioxide is respired or how many fish the ocean ecosystem can sustain. Despite their importance in the ocean ecosystem, researchers do not know the answer to the most basic question of viral biology for most environmental viruses: which bacteria do different viruses infect? Identifying these infections could help researchers understand more about how viruses shape the ecosystem through infections of keystone microbial species, infections of microbes with unique characteristics, or infection patterns that promote microbial community stability. This project is to develop a cost-effective method to substantially increase the number of infections identified within natural microbial communities. The researchers are applying this novel method to determine viral infections in cyanobacteria in the Chesapeake Bay and compare the results to standard approaches to determine viral infections. This technique can be widely used to transform our understanding of how viruses impact many ecosystems, since it is cost-effective, does not need specialized equipment and can be adapted to target different viral populations. Additionally, this project provides research opportunities for undergraduate and high school students, including underrepresented minority students and women. To develop a high-throughput, culture-independent technique to identify infections in the environment, the researchers are optimizing a previously developed method, emulsion paired concatenation-isolation PCR (epicPCR). Adapting epicPCR for viral-host associations will identify interactions by isolating actively infected single cells within a microdroplet to retain the physical proximity of the host and viral DNA during DNA extraction. Next, fusion PCR is done within the microdroplet to allow host rRNA genes to fuse to viral marker genes, such as g20 or ribonucleotide reductase, retained within the same bead. Only rRNA genes successfully fused to viral markers are amplified. Finally, high-throughput sequencing is done on the resulting fusion products. This approach is cultivation-independent, screens a larger fraction of diversity within the sample than traditional approaches, requires little additional equipment compared to microfluidic approaches, and can be scaled up to hundreds of samples because the amount of sequencing required to deeply sample a single environment is low compared to shotgun metagenomic sequencing. Although this technique will be limited to viral marker genes and suffers from the biases of PCR, it still offers great potential to investigate viral-host interactions across a large number of environments. The method is being applied to determine how viral infections influence cynaobacterial blooms in the Chesapeake Bay. The researchers will also compare the results of epicPCR to culture-based, single-cell, and bioinformatics based methods of host-virus associations to identify biases, limitations and caveats of various approaches. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/72341
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Sarah Preheim.EAGER: High-throughput, culture-independent technique identifying cyanobacteria infections to improve understanding of carbon biogeochemical cycling.2018.