Primary macrophages and J774 cells respond differently to infection with Mycobacterium tuberculosis - PubMed
- ️Sun Jan 01 2017
Primary macrophages and J774 cells respond differently to infection with Mycobacterium tuberculosis
Nuria Andreu et al. Sci Rep. 2017.
Abstract
Macrophages play an essential role in the early immune response to Mycobacterium tuberculosis and are the cell type preferentially infected in vivo. Primary macrophages and macrophage-like cell lines are commonly used as infection models, although the physiological relevance of cell lines, particularly for host-pathogen interaction studies, is debatable. Here we use high-throughput RNA-sequencing to analyse transcriptome dynamics of two macrophage models in response to M. tuberculosis infection. Specifically, we study the early response of bone marrow-derived mouse macrophages and cell line J774 to infection with live and γ-irradiated (killed) M. tuberculosis. We show that infection with live bacilli specifically alters the expression of host genes such as Rsad2, Ifit1/2/3 and Rig-I, whose potential roles in resistance to M. tuberculosis infection have not yet been investigated. In addition, the response of primary macrophages is faster and more intense than that of J774 cells in terms of number of differentially expressed genes and magnitude of induction/repression. Our results point to potentially novel processes leading to immune containment early during M. tuberculosis infection, and support the idea that important differences exist between primary macrophages and cell lines, which should be taken into account when choosing a macrophage model to study host-pathogen interactions.
Conflict of interest statement
The authors declare no competing financial interests.
Figures

(a) In BMDMs, and (b) in J774 infected with live M. tuberculosis or stimulated with γ-irradiated M. tuberculosis, relative to their time-matched uninfected controls, at 4 and 24 hpi (FDR < 0.05). The colour shading indicates the fold change in gene expression. The number of DEGs is indicated.

Scatterplots comparing the Log2 fold change (FC) of all the differentially expressed genes (DEGs) in BMDMs and J774 at 4 hpi (a) and 24 hpi (d). Grey dots represent genes differentially expressed in one macrophage type only. Points in shades of red represent genes differentially expressed in both data sets in the same direction. Points in shades of green represent genes differentially expressed in opposite direction. Those showing FC < |2| in either/both condition(s) are shown in light colour and those with FC > |2| in both conditions are shown in dark. The number of genes are indicated for each quadrant. (b) and (e) Venn diagrams comparing DEGs in BMDMs and J774 at 4 hpi and 24 hpi, respectively. (c) and (f) Line graphs showing the variation of the Log2FC for each DEG in common between BMDMs and J774 at 4 hpi (c) and 24 hpi (f). Lines are coloured according to the Log2FC in BMDMs (Log2FC > 4 red, 2 < Log2FC < 4 orange, 1 < Log2FC < 2 yellow, −1 > Log2FC > −2 green, −2 > Log2FC blue).

Data were analysed through the use of QIAGEN’s Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City,
www.qiagen.com/ingenuity). Pathways are ranked according to (a) the enrichment score (Fisher’s exact test P-value), and (b) the Z-score that predicts activation/repression.

Scatterplots comparing the Log2 fold change (FC) of all the differentially expressed genes (DEGs) in BMDMs at 4 hpi (a) and 24 hpi (b), and J774 at 4 hpi (c) and 24 hpi (d). Grey dots represent genes differentially expressed in one condition only. Points in shades of red represent genes differentially expressed in both data sets in the same direction. Points in shades of green represent genes differentially expressed in opposite direction. Those showing FC < |2| in either/both condition(s) are shown in light colour and those with FC > |2| in both conditions are shown in dark. The number of genes are indicated for each quadrant. A Venn diagram showing the number of DEGs in macrophages infected with live bacteria and/or stimulated with dead bacteria is shown for each macrophage type and time point.

(a) BMDMs, and (b) J774 cells. Data were analysed through the use of QIAGEN’s Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City,
www.qiagen.com/ingenuity). Pathways are ranked according to the Z-score that predicts activation/repression.
Similar articles
-
Pu W, Zhao C, Wazir J, Su Z, Niu M, Song S, Wei L, Li L, Zhang X, Shi X, Wang H. Pu W, et al. J Cell Mol Med. 2021 Nov;25(22):10504-10520. doi: 10.1111/jcmm.16980. Epub 2021 Oct 10. J Cell Mol Med. 2021. PMID: 34632719 Free PMC article.
-
Macrophage infection models for Mycobacterium tuberculosis.
Johnson BK, Abramovitch RB. Johnson BK, et al. Methods Mol Biol. 2015;1285:329-41. doi: 10.1007/978-1-4939-2450-9_20. Methods Mol Biol. 2015. PMID: 25779326
-
Zhang YW, Lin Y, Yu HY, Tian RN, Li F. Zhang YW, et al. Int J Mol Med. 2019 Oct;44(4):1243-1254. doi: 10.3892/ijmm.2019.4293. Epub 2019 Jul 30. Int J Mol Med. 2019. PMID: 31364746 Free PMC article.
-
Macrophage takeover and the host-bacilli interplay during tuberculosis.
Hussain Bhat K, Mukhopadhyay S. Hussain Bhat K, et al. Future Microbiol. 2015;10(5):853-72. doi: 10.2217/fmb.15.11. Future Microbiol. 2015. PMID: 26000654 Review.
-
Macrophage-microbe interaction: lessons learned from the pathogen Mycobacterium tuberculosis.
BoseDasgupta S, Pieters J. BoseDasgupta S, et al. Semin Immunopathol. 2018 Nov;40(6):577-591. doi: 10.1007/s00281-018-0710-0. Epub 2018 Oct 10. Semin Immunopathol. 2018. PMID: 30306257 Review.
Cited by
-
Hasankhani A, Bahrami A, Mackie S, Maghsoodi S, Alawamleh HSK, Sheybani N, Safarpoor Dehkordi F, Rajabi F, Javanmard G, Khadem H, Barkema HW, De Donato M. Hasankhani A, et al. Front Microbiol. 2022 Nov 30;13:1041314. doi: 10.3389/fmicb.2022.1041314. eCollection 2022. Front Microbiol. 2022. PMID: 36532492 Free PMC article.
-
Qiu Q, Peng A, Zhao Y, Liu D, Liu C, Qiu S, Xu J, Cheng H, Xiong W, Chen Y. Qiu Q, et al. Respir Res. 2022 May 14;23(1):125. doi: 10.1186/s12931-022-02035-4. Respir Res. 2022. PMID: 35568895 Free PMC article.
-
Denisenko E, Guler R, Mhlanga M, Suzuki H, Brombacher F, Schmeier S. Denisenko E, et al. BMC Genomics. 2019 Jan 22;20(1):71. doi: 10.1186/s12864-019-5450-6. BMC Genomics. 2019. PMID: 30669987 Free PMC article.
-
Biphasic Dynamics of Macrophage Immunometabolism during Mycobacterium tuberculosis Infection.
Shi L, Jiang Q, Bushkin Y, Subbian S, Tyagi S. Shi L, et al. mBio. 2019 Mar 26;10(2):e02550-18. doi: 10.1128/mBio.02550-18. mBio. 2019. PMID: 30914513 Free PMC article. Review.
-
Mycobacterial Nucleic Acids Modulate Host Innate Immune Responses.
Srikrishna G, Bullen CK, Bishai WR. Srikrishna G, et al. J Infect Dis Ther. 2024;12(2):1000585. Epub 2024 Apr 11. J Infect Dis Ther. 2024. PMID: 38745994 Free PMC article. No abstract available.
References
-
- Johnson B. K. & Abramovitch R. B. Macrophage infection models for Mycobacterium tuberculosis. Methods Mol Biol 1285, 329–341 (2015). - PubMed
-
- Mendoza-Coronel E. & Castanon-Arreola M. Comparative evaluation of in vitro human macrophage models for mycobacterial infection study. Pathog Dis 74, ftw052 (2016). - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Molecular Biology Databases
Research Materials