Abstract
Tuberculosis (TB) is one of the most potent infectious diseases in the world, causing more deaths than any other single infectious agent. TB infection is caused by inhalation of Mycobacterium tuberculosis (Mtb) and subsequent phagocytosis and migration into the lung tissue by innate immune cells (e.g., alveolar macrophages, neutrophils, and dendritic cells), resulting in the formation of a fused mass of immune cells known as the granuloma. Considered the pathological hallmark of TB, the granuloma is a complex microenvironment that is crucial for pathogen containment as well as pathogen survival. Disruption of the delicate granuloma microenvironment via numerous stimuli, such as variations in cytokine secretions, nutrient availability, and the makeup of immune cell population, can lead to an active infection. Herein, we present a novel in vitro model to examine the soluble factor signaling between a mycobacterial infection and its surrounding environment. Adapting a newly developed suspended microfluidic platform, known as Stacks, we established a modular microscale infection model containing human immune cells and a model mycobacterial strain that can easily integrate with different microenvironmental cues through simple spatial and temporal “stacking” of each module of the platform. We validate the establishment of suspended microscale (4 μL) infection cultures that secrete increased levels of proinflammatory factors IL-6, VEGF, and TNFα upon infection and form 3D aggregates (granuloma model) encapsulating the mycobacteria. As a proof of concept to demonstrate the capability of our platform to examine soluble factor signaling, we cocultured an in vitro angiogenesis model with the granuloma model and quantified morphology changes in endothelial structures as a result of culture conditions (P < 0.05 when comparing infected vs. uninfected coculture systems). We envision our modular in vitro granuloma model can be further expanded and adapted for studies focusing on the complex interplay between granulomatous structures and their surrounding microenvironment, as well as a complementary tool to augment in vivo signaling and mechanistic studies.
Highlights
Tuberculosis (TB) is one of the most potent infectious diseases in the world, causing more deaths than any other single infectious agent (World Health Organization, 2019)
Induction of angiogenic processes by Mycobacterium tuberculosis (Mtb) in the microenvironment surrounding a granuloma have been linked to pro-pathogen outcomes (Oehlers et al, 2015; Osherov and Ben-Ami, 2016), while treatment with anti-angiogenic factors can be a potential treatment option to improve the effects of existing drug regiments (Datta et al, 2015)
To further understand the signaling environment and timeline of these phenomena, we created a novel in vitro granuloma model that can be used to study soluble factor signaling between the granuloma and its surrounding microenvironment
Summary
Tuberculosis (TB) is one of the most potent infectious diseases in the world, causing more deaths than any other single infectious agent (World Health Organization, 2019). Deciphering the impact of microenvironment variations around the granuloma remains a significant challenge, and researchers often rely on in vivo animal models or biological samples (e.g., blood and tissue biopsy), considered the gold standard for studying TB, to reconstruct this complex environment These methods have laid the foundation for understanding the pathogenesis and immunology behind TB, yet many existing in vivo models do not accurately recapitulate Mtb infection as seen in humans ( recent advances in mouse models and the established zebrafish/M. marinum model are closing this gap) (Cronan and Tobin, 2014; Myllymäki et al, 2016; Gern et al, 2017; Zhan et al, 2017; Cronan et al, 2018; Yong et al, 2018). Human-derived biological samples provide detailed cellular information regarding the granuloma, the immune response, and disease status (Guyot-Revol et al, 2006; Berry et al, 2010; Darboe et al, 2019; Ogongo et al, 2020), but are inherently limited as they only reflect a singular point in time, rather than the dynamic interactions that occur during the early stages of infection or disease progression
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
