Quantitative Temporal in Vivo Proteomics Deciphers the Transition of Virus-Driven Myeloid Cells into M2 Macrophages.
Quantitative Temporal in Vivo Proteomics Deciphers the Transition of Virus-Driven Myeloid Cells into M2 Macrophages.
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DOI:
10.1021/acs.jproteome.7b00425
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发表时间:
2017-09-01
影响因子:
4.4
通讯作者:
Gujar S
中科院分区:
文献类型:
--
作者:
Clements DR;Murphy JP;Sterea A;Kennedy BE;Kim Y;Helson E;Almasi S;Holay N;Konda P;Paulo JA;Sharif T;Lee PW;Weekes MP;Gygi SP;Gujar S
Myeloid cells play a central role in the context of viral eradication, yet precisely how these cells differentiate throughout the course of acute infections is poorly understood. In this study, we have developed a novel quantitative temporal in vivo proteomics (QTiPs) platform to capture proteomic signatures of temporally transitioning virus-driven myeloid cells directly in situ, thus taking into consideration host–virus interactions throughout the course of an infection. QTiPs, in combination with phenotypic, functional, and metabolic analyses, elucidated a pivotal role for inflammatory CD11b+, Ly6G–, Ly6Chigh-low cells in antiviral immune response and viral clearance. Most importantly, the time-resolved QTiPs data set showed the transition of CD11b+, Ly6G–, Ly6Chigh-low cells into M2-like macrophages, which displayed increased antigen-presentation capacities and bioenergetic demands late in infection. We elucidated the pivotal role of myeloid cells in virus clearance and show how these cells phenotypically, functionally, and metabolically undergo a timely transition from inflammatory to M2-like macrophages in vivo. With respect to the growing appreciation for in vivo examination of viral–host interactions and for the role of myeloid cells, this study elucidates the use of quantitative proteomics to reveal the role and response of distinct immune cell populations throughout the course of virus infection.
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影响因子:
4.7
作者:
Gujar SA;Lee PW
通讯作者:
Lee PW
影响因子:
3.7
作者:
Boutté AM;McDonald WH;Shyr Y;Yang L;Lin PC
通讯作者:
Lin PC
影响因子:
3.4
作者:
Guo M;Härtlova A;Dill BD;Prescott AR;Gierliński M;Trost M
通讯作者:
Trost M
影响因子:
28.3
作者:
Lachmandas, Ekta;Boutens, Lily;Stienstra, Rinke
通讯作者:
Stienstra, Rinke
DOI:
10.1073/pnas.1525360113
发表时间:
2016-04-19
影响因子:
11.1
作者:
Kloepper, Jonas;Riedemann, Lars;Jain, Rakesh K.
通讯作者:
Jain, Rakesh K.