Organoids as host models for infection biology - a review of methods.
Organoids as host models for infection biology - a review of methods.
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DOI:
10.1038/s12276-021-00629-4
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发表时间:
2021-10
影响因子:
12.8
通讯作者:
Bartfeld S
中科院分区:
文献类型:
--
作者:
Aguilar C;Alves da Silva M;Saraiva M;Neyazi M;Olsson IAS;Bartfeld S
Infectious diseases are a major threat worldwide. With the alarming rise of antimicrobial resistance and emergence of new potential pathogens, a better understanding of the infection process is urgently needed. Over the last century, the development of in vitro and in vivo models has led to remarkable contributions to the current knowledge in the field of infection biology. However, applying recent advances in organoid culture technology to research infectious diseases is now taking the field to a higher level of complexity. Here, we describe the current methods available for the study of infectious diseases using organoid cultures. Using miniaturized, three-dimensional versions of organs and tissues to model infectious diseases could improve understanding of patient-specific responses and inform personalized therapies. Organoid cultures are generated from tissue-specific adult stem cells, and recreate some of the original cellular structure of a given organ or tissue. They also mimic the organ’s molecular mechanisms and responses. Sina Bartfeld at the Julius Maximilians Universität Würzburg, Germany, and coworkers reviewed recent research into organoid cultures for modeling infections and disease progression. Creating organoids from different individuals allows scientists to monitor how infections behave in unique hosts. Organoid studies have highlighted specific targets for initial infection by bacteria, identified host factors that influence disease outcomes, and clarified patient-specific responses to treatments. Future organoids should be more complex, incorporating immune and nerve cells, and even factoring in the microbiome.
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影响因子:
30.3
作者:
Burger E;Araujo A;López-Yglesias A;Rajala MW;Geng L;Levine B;Hooper LV;Burstein E;Yarovinsky F
通讯作者:
Yarovinsky F
DOI:
10.1073/pnas.1811866115
发表时间:
2018-10-02
影响因子:
11.1
作者:
Forbester JL;Lees EA;Goulding D;Forrest S;Yeung A;Speak A;Clare S;Coomber EL;Mukhopadhyay S;Kraiczy J;Schreiber F;Lawley TD;Hancock REW;Uhlig HH;Zilbauer M;Powrie F;Dougan G
通讯作者:
Dougan G
影响因子:
1.2
作者:
Dutta, Devanjali;Heo, Inha;O'Connor, Roberta
通讯作者:
O'Connor, Roberta
影响因子:
30.3
作者:
Grassart, Alexandre;Malarde, Valerie;Sauvonnet, Nathalie
通讯作者:
Sauvonnet, Nathalie
影响因子:
24.5
作者:
Boccellato F;Woelffling S;Imai-Matsushima A;Sanchez G;Goosmann C;Schmid M;Berger H;Morey P;Denecke C;Ordemann J;Meyer TF
通讯作者:
Meyer TF