目前,，科學(xué)家已經(jīng)破譯了一個關(guān)鍵的分子通路,，該通路能夠使機體從細菌和其他的微生物中辨別出病毒。這項研究為哺乳動物中免疫細胞抵御不同病原體的機制提供了深入的理解,。
這項研究結(jié)果發(fā)布在9月3日Science的網(wǎng)絡(luò)版本上,。
他們的這項發(fā)現(xiàn)闡述了人類生物學(xué)一個重要的問題，即免疫細胞如何識別不同的病原體,，并產(chǎn)生不同的免疫應(yīng)答,。該研究負(fù)責(zé)人Nir Hacohen介紹說，他們現(xiàn)在已經(jīng)深入探究了該通路控制的重要生物學(xué)過程,，這為疾病治療和疫苗設(shè)計提供了新的思路,。
值得一提的還有研究過程中使用的方法。這種方法不僅全面而且適用于大部分的生物學(xué)系統(tǒng),，也可用于實驗室,。
和計算機類似，細胞會接收和處理信息,，然后讀取信息流并通過一系列復(fù)雜的通路處理信息,，并產(chǎn)生適當(dāng)?shù)膽?yīng)答。但與計算機不同的是哺乳動物細胞內(nèi)的通路是由大量的基因網(wǎng)絡(luò)以及相應(yīng)的蛋白組成的,。
該研究關(guān)注了人類的樹突細胞,，并發(fā)現(xiàn)了一個重要的分子通路。這項發(fā)現(xiàn)有助于人類自身免疫和其他相關(guān)疾病的研究,，加深了對遺傳易感性以及其他免疫失調(diào)的理解,。(生物谷Bioon.com)
生物谷推薦原始出處：
Science 3 September 2009 DOI: 10.1126/science.1179050
Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses
Ido Amit, Manuel Garber, Nicolas Chevrier, Ana Paula Leite, Yoni Donner, Thomas Eisenhaure, Mitchell Guttman, Jennifer K. Grenier, Weibo Li, Or Zuk, Lisa A. Schubert, Brian Birditt, Tal Shay, Alon Goren, Xiaolan Zhang, Zachary Smith, Raquel Deering, Rebecca C. McDonald, Moran Cabili, Bradley E. Bernstein, John L. Rinn, Alex Meissner, David E. Root, Nir Hacohen, Aviv Regev
1 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.; Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129 USA.; Harvard Medical School, Boston, MA 02115, USA.; MIT, Department of Biology, Cambridge, MA 02142, USA.
2 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.
3 Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129 USA.; Harvard Medical School, Boston, MA 02115, USA.
4 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.; Computational and Systems Biology, MIT Cambridge, MA 02139, USA.
5 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.; MIT, Department of Biology, Cambridge, MA 02142, USA.
6 NanoString Technologies, 530 Fairview Ave. N, Suite 2000, Seattle, WA 98109, USA.
7 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.; Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129 USA.; Harvard Medical School, Boston, MA 02115, USA.
Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data, yet have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We apply this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells (DCs) to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins and constructed a network model consisting of two dozen core regulators and 76 fine-tuners that help explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.
