Honey bee protein atlas at organ-level resolution.
Honey bee protein atlas at organ-level resolution.
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DOI：
10.1101/gr.155994.113
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发表时间：
2013-11
期刊：
影响因子：
7
通讯作者：
Foster LJ
中科院分区：
文献类型：
--
作者：
Chan QW;Chan MY;Logan M;Fang Y;Higo H;Foster LJ
基因组测序为我们提供了基因列表，但无法告诉我们它们的编码产物在哪里以及如何共同作用以支持生命。复杂生物体依赖于器官和组织中基因/蛋白质子集的差异表达，并且随着它们共同发挥作用以改善生物体的整体生殖适应性而进化到目前的状态。对单个器官的蛋白质组学研究有助于我们了解它们的基本功能，但这种简化的方法忽略了整个生物体的更大背景。如果一个生物体的所有器官都用同样的方法进行全面研究并一起分析，这个问题就可以避免。利用蜜蜂（Apis mellifera L.）作为一个模型系统，我们在这里报告了一个复杂生物体的初始全蛋白质组，测量了三种蜜蜂等级（蜂王、雄蜂和工蜂）中29种不同的器官/组织类型。数据显示，例如，工蚁处理环境毒素的能力更强，蚁后的信息素检测系统比它们的同伴强得多。这些数据还表明，工蜂不仅会无私地牺牲自己的生殖能力，还会牺牲自己的免疫潜力来支持蜂王。最后，蛋白质表达的器官水平分辨率提供了器官如何发育的系统见解。
Genome sequencing has provided us with gene lists but cannot tell us where and how their encoded products work together to support life. Complex organisms rely on differential expression of subsets of genes/proteins in organs and tissues, and, in concert, evolved to their present state as they function together to improve an organism's overall reproductive fitness. Proteomics studies of individual organs help us understand their basic functions, but this reductionist approach misses the larger context of the whole organism. This problem could be circumvented if all the organs in an organism were comprehensively studied by the same methodology and analyzed together. Using honey bees (Apis mellifera L.) as a model system, we report here an initial whole proteome of a complex organism, measuring 29 different organ/tissue types among the three honey bee castes: queen, drone, and worker. The data reveal that, e.g., workers have a heightened capacity to deal with environmental toxins and queens have a far more robust pheromone detection system than their nestmates. The data also suggest that workers altruistically sacrifice not only their own reproductive capacity but also their immune potential in favor of their queen. Finally, organ-level resolution of protein expression offers a systematic insight into how organs may have developed.
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影响因子：
64.5
作者：
Huttlin EL;Jedrychowski MP;Elias JE;Goswami T;Rad R;Beausoleil SA;Villén J;Haas W;Sowa ME;Gygi SP
通讯作者：
Gygi SP
影响因子：
4.4
作者：
Chan QW;Parker R;Sun Z;Deutsch EW;Foster LJ
通讯作者：
Foster LJ
影响因子：
56.9
作者：
HABERMAN.E
通讯作者：
HABERMAN.E
影响因子：
4.4
作者：
Chan QW;Melathopoulos AP;Pernal SF;Foster LJ
通讯作者：
Foster LJ
影响因子：
--
作者：
Georgieva, Dessislava;Greunke, Kerstin;Betzel, Christian
通讯作者：
Betzel, Christian