Evidence-based annotation of gene function in Shewanella oneidensis MR-1 using genome-wide fitness profiling across 121 conditions.
Evidence-based annotation of gene function in Shewanella oneidensis MR-1 using genome-wide fitness profiling across 121 conditions.
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DOI：
10.1371/journal.pgen.1002385
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发表时间：
2011-11
期刊：
影响因子：
4.5
通讯作者：
Arkin AP
中科院分区：
文献类型：
--
作者：
Deutschbauer A;Price MN;Wetmore KM;Shao W;Baumohl JK;Xu Z;Nguyen M;Tamse R;Davis RW;Arkin AP
细菌中的大多数基因在实验上是未被表征的，并且不能用特定的功能来注释。鉴于细菌的多样性和基因组测序的容易性，需要高通量的方法来实验性地鉴定基因功能。在这里，我们使用标记的转座子突变体池中的金属还原细菌希瓦氏菌oneidensis MR-1探测突变体的3,355个基因在121个不同的条件下，包括不同的生长底物，替代电子受体，应力和运动。我们发现，2,350个基因具有与随机显著不同的适应度模式，其中1,230个基因（占我们检测基因总数的37%）具有足够的信号显示出强烈的生物相关性。我们发现，所有功能类别的基因都有表型，包括数百种假设，并且潜在冗余基因（与基因组中的另一个基因具有超过50%的氨基酸同一性）也可能具有不同的表型。使用健身模式，我们能够提出特定的分子功能的40个基因或操纵子，缺乏特定的注释或有不完整的注释。在一个例子中，我们证明了先前假设的基因SO_3749编码一个功能性乙酰鸟氨酸脱乙酰酶，从而填补了S. oneidensis代谢此外，我们证明孤儿组氨酸激酶SO_2742和孤儿反应调节剂SO_2648形成激活乙酰辅酶A合酶表达的信号转导途径，并且是S. oneidensis在乙酸盐作为碳源上生长。最后，我们证明，基因表达和突变体的健身相关性差，突变体健身产生更有信心的预测基因功能比基因表达。本文所述的方法可以普遍应用于创建大规模的基因-表型图谱，用于原核生物基因功能的循证注释。许多计算预测的细菌基因注释是不完整或错误的。因此，需要系统地确定细菌中基因功能的实验方法。在这里，我们描述了一种遗传方法来迎接这一挑战。我们构建了一个大的转座子突变体库中的金属还原细菌希瓦氏菌oneidensis MR-1和轮廓的健身这个集合在100多个不同的实验条件。除了识别2,000多个基因的表型外，我们还证明了突变体适应性谱可用于为酶、信号蛋白、转运蛋白和转录因子分配“基于证据”的基因注释，我们通过实验验证了其中的一个子集。
Most genes in bacteria are experimentally uncharacterized and cannot be annotated with a specific function. Given the great diversity of bacteria and the ease of genome sequencing, high-throughput approaches to identify gene function experimentally are needed. Here, we use pools of tagged transposon mutants in the metal-reducing bacterium Shewanella oneidensis MR-1 to probe the mutant fitness of 3,355 genes in 121 diverse conditions including different growth substrates, alternative electron acceptors, stresses, and motility. We find that 2,350 genes have a pattern of fitness that is significantly different from random and 1,230 of these genes (37% of our total assayed genes) have enough signal to show strong biological correlations. We find that genes in all functional categories have phenotypes, including hundreds of hypotheticals, and that potentially redundant genes (over 50% amino acid identity to another gene in the genome) are also likely to have distinct phenotypes. Using fitness patterns, we were able to propose specific molecular functions for 40 genes or operons that lacked specific annotations or had incomplete annotations. In one example, we demonstrate that the previously hypothetical gene SO_3749 encodes a functional acetylornithine deacetylase, thus filling a missing step in S. oneidensis metabolism. Additionally, we demonstrate that the orphan histidine kinase SO_2742 and orphan response regulator SO_2648 form a signal transduction pathway that activates expression of acetyl-CoA synthase and is required for S. oneidensis to grow on acetate as a carbon source. Lastly, we demonstrate that gene expression and mutant fitness are poorly correlated and that mutant fitness generates more confident predictions of gene function than does gene expression. The approach described here can be applied generally to create large-scale gene-phenotype maps for evidence-based annotation of gene function in prokaryotes. Many computationally predicted gene annotations in bacteria are incomplete or wrong. Consequently, experimental methods to systematically determine gene function in bacteria are required. Here, we describe a genetic approach to meet this challenge. We constructed a large transposon mutant library in the metal-reducing bacterium Shewanella oneidensis MR-1 and profiled the fitness of this collection in more than 100 diverse experimental conditions. In addition to identifying a phenotype for more than 2,000 genes, we demonstrate that mutant fitness profiles can be used to assign “evidence-based” gene annotations for enzymes, signaling proteins, transporters, and transcription factors, a subset of which we verify experimentally.
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