发布: 2020年05月20日第10卷第10期 DOI: 10.21769/BioProtoc.3630 浏览次数: 6018
评审: Andrew OliveMeenal SinhaAnonymous reviewer(s)
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使用康可藻红素刺激冷冻保存的猪外周单个核细胞进行增殖检测,并结合FCS ExpressTM 7.18软件分析
Marlene Bravo-Parra [...] Luis G. Giménez-Lirola
2025年06月05日 1214 阅读
Abstract
Mycobacterium tuberculosis (Mtb) is transmitted by aerosol and can cause serious bacterial infection in the lung that can be fatal if left untreated. Mtb is now the leading cause of death worldwide by an infectious agent. Characterizing the early events of in vivo infection following aerosol challenge is critical for understanding how innate immune cells respond to infection but is technically challenging due to the small number of bacteria that initially infect the lung. Previous studies either evaluated Mtb-infected cells at later stages of infection when the number of bacteria in the lung is much higher or used in vitro model systems to assess the response of myeloid cells to Mtb. Here, we describe a method that uses fluorescent bacteria, a high-dose aerosol infection model, and flow cytometry to track Mtb-infected cells in the lung immediately following aerosol infection and fluorescence-activated cell sorting (FACS) to isolate naïve, bystander, and Mtb-infected cells for downstream applications, including RNA-sequencing. This protocol provides the ability to monitor Mtb-infection and cell-specific responses within the context of the lung environment, which is known to modulate the function of both resident and recruited populations. Using this protocol, we discovered that alveolar macrophages respond to Mtb infection in vivo by up-regulating a cell protective transcriptional response that is regulated by the transcription factor Nrf2 and is detrimental to early control of the bacteria.
Keywords: Mycobacterium tuberculosis (结核分枝杆菌)Background
Aerosol transmission is a critical component of the natural cycle of Mycobacterium tuberculosis (Mtb) infection, contributing to the virulence of the bacteria and leading to a unique pattern of infection in the lung (North, 1995; Riley et al., 1995; Pai et al., 2016). In order to understand the early events of infection, it is critical to be able to track the cell types that become infected and isolate those populations for downstream analysis. Studies using a standard low-dose mouse model (~100 CFU deposition) have failed to detect bacteria earlier than 14 days following infection, a time point at which Mtb can be found distributed within alveolar macrophages, neutrophils, interstitial macrophages and dendritic cells (Wolf et al., 2007; Huang et al., 2018). By pairing a high-dose infection model with fluorescent bacteria, flow cytometry, and cell sorting techniques, this protocol enables the detection of Mtb-infected cells immediately following aerosol challenge and the ability to isolate Mtb-infected populations at different time-points as disease develops. While the high-dose infection model allows for very early detection of the first cells that are infected with Mtb and for evaluation of the early dynamics of Mtb-infected cells and bacterial dissemination, it may accelerate the adaptive stages of the immune response and disease progression compared to more commonly used low-dose models. Therefore, its utility is in studying the early stages of infection (within the first two weeks) and may not be as useful in studying later stages of disease. By combining this protocol with RNA-sequencing, we identified a cell protective transcriptional response generated by Mtb-infected alveolar macrophages that is regulated by the transcription factor Nrf2 and is detrimental to early control of the bacteria (Rothchild et al., 2019). Other downstream applications include qPCR and ex vivo functional assays to characterize both infected and bystander cells. This approach is also applicable to other pulmonary infection models.
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© 2020 The Authors; exclusive licensee Bio-protocol LLC.
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Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
分类
免疫学 > 免疫细胞分离 > 骨髓细胞
免疫学 > 免疫细胞染色 > 流式细胞术
细胞生物学 > 基于细胞的分析方法 > 流式细胞术
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