Proteomic traits vary across taxa in a coastal Antarctic phytoplankton bloom.
Proteomic traits vary across taxa in a coastal Antarctic phytoplankton bloom.
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DOI：
10.1038/s41396-021-01084-9
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发表时间：
2022-03
期刊：
影响因子：
--
通讯作者：
Bertrand EM
中科院分区：
文献类型：
--
作者：
McCain JSP;Allen AE;Bertrand EM
蛋白质的生产和使用在微生物中受到强烈的选择，但蛋白质组水平的特征如何与生态策略相关尚不清楚。我们通过南极浮游植物水华利用原位代谢蛋白质组学鉴定和量化了真核微生物和细菌的蛋白质组特征。不同的类群，而不是不同的环境条件，根据它们的核糖体和光合作用蛋白质组比例形成了不同的簇，我们认为这些特征与生态差异有关。我们定义并使用了一个代表调控成本的蛋白质组学指标，这表明在我们夏季南大洋研究地点观察到的所有分类群中，SAR11的调控成本最低。同生植物的调控成本低于硅藻，这可能支持了罗斯海从同生植物到硅藻的水华进程。我们能够通过评估代谢蛋白质组学中的各种偏倚来源来做出这些蛋白质组特征推断，为该领域的研究人员提供实用的建议。我们已经量化了真核生物和细菌分类群中的几个蛋白质组特征(核糖体和光合作用蛋白质组比例、调节成本)，然后可以将这些特征纳入反映资源分配策略的基于特征的微生物群落模型。
Production and use of proteins is under strong selection in microbes, but it is unclear how proteome-level traits relate to ecological strategies. We identified and quantified proteomic traits of eukaryotic microbes and bacteria through an Antarctic phytoplankton bloom using in situ metaproteomics. Different taxa, rather than different environmental conditions, formed distinct clusters based on their ribosomal and photosynthetic proteomic proportions, and we propose that these characteristics relate to ecological differences. We defined and used a proteomic proxy for regulatory cost, which showed that SAR11 had the lowest regulatory cost of any taxa we observed at our summertime Southern Ocean study site. Haptophytes had lower regulatory cost than diatoms, which may underpin haptophyte-to-diatom bloom progression in the Ross Sea. We were able to make these proteomic trait inferences by assessing various sources of bias in metaproteomics, providing practical recommendations for researchers in the field. We have quantified several proteomic traits (ribosomal and photosynthetic proteomic proportions, regulatory cost) in eukaryotic and bacterial taxa, which can then be incorporated into trait-based models of microbial communities that reflect resource allocation strategies.
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DOI：
10.1073/pnas.2107238118
发表时间：
2021-07-27
影响因子：
11.1
作者：
Jabre LJ;Allen AE;McCain JSP;McCrow JP;Tenenbaum N;Spackeen JL;Sipler RE;Green BR;Bronk DA;Hutchins DA;Bertrand EM
通讯作者：
Bertrand EM
影响因子：
64.8
作者：
Dekel, E;Alon, U
通讯作者：
Alon, U
影响因子：
3.7
作者：
Mangoni, Olga;Saggiomo, Vincenzo;Saggiomo, Maria
通讯作者：
Saggiomo, Maria
DOI：
10.1073/pnas.1421993112
发表时间：
2015-04-28
影响因子：
11.1
作者：
Alexander, Harriet;Jenkins, Bethany D.;Dyhrman, Sonya T.
通讯作者：
Dyhrman, Sonya T.
DOI：
10.1073/pnas.1619573114
发表时间：
2017-04-11
影响因子：
11.1
作者：
Braakman, Rogier;Follows, Michael J.;Chisholm, Sallie W.
通讯作者：
Chisholm, Sallie W.