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Mice infected with Mycobacterium tuberculosis are resistant to acute disease caused by secondary infection with SARS-CoV-2

['Oscar Rosas Mejia', 'Department Of Microbial Infection', 'Erin S. Gloag', 'Jianying Li', 'Pelotonia Institute For Immuno-Oncology', 'Marisa Ruane-Foster', 'Tiffany A. Claeys', 'Daniela Farkas', 'Department Of Internal Medicine', 'Division Of Pulmonary']

Date: 2022-05

Abstract Mycobacterium tuberculosis (Mtb) and SARS-CoV-2 (CoV2) are the leading causes of death due to infectious disease. Although Mtb and CoV2 both cause serious and sometimes fatal respiratory infections, the effect of Mtb infection and its associated immune response on secondary infection with CoV2 is unknown. To address this question we applied two mouse models of COVID19, using mice which were chronically infected with Mtb. In both model systems, Mtb-infected mice were resistant to the pathological consequences of secondary CoV2 infection, and CoV2 infection did not affect Mtb burdens. Single cell RNA sequencing of coinfected and monoinfected lungs demonstrated the resistance of Mtb-infected mice is associated with expansion of T and B cell subsets upon viral challenge. Collectively, these data demonstrate that Mtb infection conditions the lung environment in a manner that is not conducive to CoV2 survival.

Author summary Mycobacterium tuberculosis (Mtb) and SARS-CoV-2 (CoV2) are distinct organisms which both cause lung disease. We report the surprising observation that Mtb-infected mice are resistant to secondary infection with CoV2, with no impact on Mtb burden and resistance associating with lung T and B cell expansion.

Citation: Rosas Mejia O, Gloag ES, Li J, Ruane-Foster M, Claeys TA, Farkas D, et al. (2022) Mice infected with Mycobacterium tuberculosis are resistant to acute disease caused by secondary infection with SARS-CoV-2. PLoS Pathog 18(3): e1010093. https://doi.org/10.1371/journal.ppat.1010093 Editor: Padmini Salgame, New Jersey Medical School, UNITED STATES Received: November 8, 2021; Accepted: February 23, 2022; Published: March 24, 2022 Copyright: © 2022 Rosas Mejia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the manuscript and its Supporting Information files. Funding: This work was supported by funds from the United States National Institutes of Health (R01AI121212 to RTR; https://www.nih.gov), as well as the American Heart Association (19CDA34630005 to ESG; https://www.heart.org) and The Ohio State University (RTR and ORM; https://www.osu.edu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Introduction The world is currently in the midst of two lung disease pandemics: COVID19 and tuberculosis (TB), the causative agents of which are SARS-CoV-2 (CoV2) and Mycobacterium tuberculosis (Mtb), respectively. Although COVID19 and TB both pose enormous health challenges, especially in countries where COVID19 vaccines are scarce, it unknown what if any effect Mtb infection has on host responses to CoV2 as there are few clinical reports of Mtb/CoV2 coinfection in the absence of other comorbidities [1,2]. On the one hand, CoV2 infection may exacerbate the inflammatory response and pulmonary complications experienced by individuals with TB [3], analogous to that which is observed in the Mtb/Influenza A or Mtb/CMV coinfected individuals [4–7]. On the other hand, there is an inverse relationship between TB incidence rates and COVID19 mortality in numerous countries [8], and Mycobacterium spp express several proteins homologous to CoV2 antigens [9–11], raising the possibility that adaptive immune responses to Mtb may confer heterologous immunity against CoV2. To definitively address whether Mtb-infection impacts CoV2 elicited lung disease in a controlled setting, we applied two mouse models of COVID19 (CoV2 infection of K18-hACE2 mice [12], and mouse-adapted CoV2 [MACoV2] infection of C57BL/6 mice [13]), using mice that were chronically infected with Mtb. The results below support a model wherein Mtb infection confers resistance to secondary infection with CoV2 and its pathological consequences. The implications of these data for our understanding of COVID19 susceptibility and the limitations of our study are discussed.

Discussion Our results demonstrate that Mtb infected mice on the C57BL/6 genetic background are resistant to secondary infection with CoV2 and its pathological consequences. With regards to the mechanism of resistance, we believe the inflammatory nature of Mtb infection creates a lung environment that is inhospitable to CoV2 propagation. In the absence of Mtb, CoV2 enter cells via ACE2, propagates and triggers and inflammatory response that extends after CoV2 clearance and causes declines in lung function and death [17]. In the presence of Mtb, CoV2 entry is likely unaffected since ACE2 is abundantly expressed in the Mtb-infected lung, but the extent of CoV2 propagation is low and the immunopathological responses typically triggered in mice (i.e. weight loss, pneumonia) are muted. This is likely due to one or both of the following reasons: (1) Mtb infected lungs already contain an array of immune innate lineages which restrict CoV2, or (2) Mtb elicits an adaptive immune response that cross reacts with CoV2 antigens and offers heterologous immunity. This latter explanation is supported by recent epidemiological studies of COVID among individuals vaccinated with M. bovis BCG [18–20], which depending on the strain has significant antigenic overlap with Mtb [21,22]. The limitations of our study include its being performed in mice, which of course do not recapitulate all aspects of TB or COVID in humans, nor have we examined the long term impact of CoV2 on the host response to Mtb as we terminated our study fourteen days after CoV2 challenge. That said, we believe animal models of TB and COVID are ideal for studies of this nature because—if studies of COVID in individuals with other chronic lung diseases are any guide [23,24]—it will likely be difficult to tease apart the impact of TB on COVID outcomes in humans given that individuals with TB often have numerous other comorbidities (e.g. malnourishment, HIV) that confound interpretation. Translated to human COVID susceptibility, our results suggest that individuals infected with Mtb generate an immune response that offers a degree of protection from subsequent or secondary infection with CoV2. We believe our study raises a number of important questions which can be answered by future research, including (but not limited to) the following: Do our findings extend to other models of TB which better recapitulate the range of human disease? As expertly reviewed elsewhere [25], mice are an imperfect model of TB because they do not display the spectrum of pathology observed in humans with TB. This is especially true of mice on the C57BL/6 genetic background, which are resistant to TB in the absence of any induced or genetic immunodeficiency [26]. It will be important to test if our results can be generalized to other models which do display a greater range of TB and COVID disease forms (e.g. NHP, Diversity Outbred mice) [27–29]. Related to this is the question of whether the resistance we observed varies with the stage of TB disease, as the cellular composition, cytokine milieu and protective capacity of the TB granuloma waxes and wanes over time [30]. What is the mechanism of acute COVID disease resistance in Mtb-infected mice? Whether the expansion of B cell or CD8 T cells we observed in MtbPOSCoV2POS mice is indicative of their having protective properties in the context of co-infection can be determined via classic immunology methods such as lineage depletions and/or adoptive transfers. So too can sera from Mtb infected animals be tested for neutralizing or protective capacity against CoV2 challenge, since there may be antibodies present to the numerous mycobacterial proteins that are homologous to CoV2 antigens [9–11]. How is the human immune response to TB affected by COVID? As the acute crisis stage of the COVID pandemic has (hopefully) begun to move into the past with the advent of effective vaccines, scattered reports are emerging of interesting associations between COVID and Interferon-Gamma Release assay (IGRA) results. IGRAs are whole-blood tests which detect secretion of IFNγ in response to two or three synthetic, Mtb-specific peptides depending on the manufacturer (QuantiFERON-TB Gold In-Tube test: ESAT-6, CFP-10 & TB7.7; T-SPOT TB test: ESAT-6 & CFP-10), relative to a negative control antigen (nil) and a positive control antigen (the polyclonal mitogen phytohemagglutinin, PHA). A “positive IGRA” is indicative of active or prior Mtb infection; an “indeterminate IGRA” can stem from either an insufficient response to the positive control, or too high a background response to the negative control. Consistent with our present animal model study, Gupta et al observed that a cohort of 20 asymptomatic COVID patients were more likely to have a positive IGRA than 20 severely ill COVID patients [31], suggesting those with prior TB exposure are less likely to develop symptoms following CoV2 infection. Equally interesting are elevated rates of indeterminate IGRA in hospitalized COVID patients, due to too low IFNγ levels in the positive control blood collection tubes [32,33]. Another recent study [34] of 10 COVID patients with active TB and 11 COVID patients with latent TB shows that both groups retain their ability to respond to Mtb antigens as measured via IGRA, but (compared to 63 COVID patients with no history of TB) the blood of those with active TB (not latent TB) are less responsive to CoV2 antigens. Our animal model data would suggest this later result could be due to either the inflammatory environment limiting CoV2 replication (resulting in less viral antigens for generating an adaptive response in the first place). Alternatively since most of the T cell compartment localizes to the lung (away from the circulation) in those with active TB, due to the array of chemokines that attract both Mtb-specific and non-Mtb-specific T cells alike [35], lower CoV2 antigen responsiveness in the blood may reflect lower T cell numbers in the blood. That hospitalized individuals with COVID are often treated with corticosteroids is an additional confounder of human TB/COVID co-infection studies. Finally, TB and COVID are ongoing pandemics and our results should not be used to support any assertion that those with TB (or history of TB) will not get COVID, nor should they be used to support any assertion that those with TB (or history of TB) should not get vaccinated against COVID. Hospitalization and severe forms of COVID can now be prevented by several vaccines; the US Centers for Disease Control and Prevention, European Centre for Disease Prevention and Control, and World Health Organization each maintain updated lists of these vaccines on their respective websites (https://www.cdc.gov, https://www.ecdc.europa.eu, https://www.who.int). We do hope and anticipate that our results will be used to support future studies of patient populations and animal models to improve knowledge of the TB/COVID interaction.

Materials & methods Ethics statement All animal studies were reviewed and approved by the local Institutional Animal Care and Use Committee (OSU IACUC) prior to their onset (Approval # 2018A00000076 and 2020A00000044). SARS-CoV-2 culture, preparation and authentication All experiments involving SARS-CoV-2 followed procedures and protocols that are approved by The Ohio State University (OSU) Institutional Biosafety Committee. SARS-CoV-2, isolate USA-WA1/2020, was obtained from Biodefense and Emerging Infections Research Resources Repository (BEI Resources, Batch # 70034262). Mouse adapted SARS-CoV-2 variant strain MA10 [36] was likewise provided by BEI Resources (Cat # NR-55329). Virus was cultured, prepared and authenticated as we recently reported [37]. Namely, to establish the viral stocks used in our studies, a virus aliquot was thawed, diluted 1:10,000 in incomplete DMEM (Gibco; supplemented with 4.5 g/L D-glucose, 110 mg/L sodium pyruvate) and added to confluent VeroE6 cells (ATCC). Cells were incubated with virus for 1h (37°C, 5% CO 2 ), after which time the media was replaced with complete DMEM (i.e. DMEM prepared as above, further supplemented with 4% heat-inactivated fetal bovine serum) and the cells were incubated for 3 days (37°C, 5% CO 2 ) to allow virus propagation. After that period, visual inspection under light microscopy demonstrated near complete death of the infected VeroE6 cells. The supernatant was collected into 50mL conicals, centrifuged at low speed to remove cell debris and subsequently aliquoted, frozen and stored at -80°C. These frozen aliquots served as the stock tubes for all subsequent experiments. The live virus titer of our frozen aliquots was determined via the plaque assay described below. SARS-CoV-2 stocks were authenticated using a clinically validated clinical next-generation sequencing assay [38]. Mycobacterium tuberculosis culture, preparation and authentication All experiments involving M. tuberculosis (Mtb) followed procedures and protocols that are approved by The Ohio State University (OSU) Institutional Biosafety Committee. The virulent Mtb strain H37Rv (Trudeau Institute, Saranac Lake, NY) was grown in Proskauer Beck medium containing 0.05% tyloxapol to mid-log phase (37°C, 5% CO 2 ) and frozen in 1-ml aliquots at −80°C. The live bacteria titer of our frozen aliquots was determined via plating serial dilutions on 7H11 agar media. To authenticate our Mtb stock we confirmed that the colony morphology, in vitro growth characteristics and in vivo virulence were consistent with our previous studies using the H37Rv strain [39]. Mice All mice were treated in accordance with OSU Institutional Animal Care and Use Committee (IACUC) guidelines and approved protocols. C57BL/6 and hemizygous K18-hACE C57BL/6J mice (strain: 2B6.Cg-Tg(K18-ACE2)2Prlmn/J) were purchased from Jackson Laboratory (Bar Harbor, ME) and housed at OSU within an AALAC-accredited facility (University Laboratory Animal Resources, ULAR). Aerosol Mtb infection Mice were aerosol infected with Mtb H37Rv per our previous studies using the Glas-Col inhalation system [39]. For bacterial load determinations, the lungs, spleen, and liver were aseptically removed and individually homogenized in sterile normal saline (Gentle Macs system, program “RNA” run 2X). Serial dilutions of each organ were then plated on 7H11 and colonies counted after 2–3 weeks incubation at 37°C 5% CO 2 . Lungs from control mice were plated on post-infection Day 1 to verify the delivery of ~80 Mtb CFU. Intranasal CoV2 challenge Mice that were either uninfected (UI) or previously infected with aerosol Mtb (MtbPOS) mice were challenged with either CoV2 or MACoV2. At the time of challenge, mice were anesthetized with isoflurane, weighed and held at a semi-supine position while 50 μL of CoV2-containing PBS (2.5 × 104 PFU) or MACoV2 (2.5 × 104 PFU) was given via intranasal (i.n.) instillation. Control mice were given the same volume of sterile PBS, using the same anesthesia and i.n. instillation protocol. After i.n. instillation, each mouse was returned to its home cage, house and monitored daily for changes in weight or body condition. For viral load determinations, the lungs of challenged animals were aseptically removed and individually homogenized as described above; serial dilutions were then used in the plaque assay described below. CoV2 plaque assay A modified version of the plaque assay developed by the Diamond laboratory [40] was used to determine lung viral burdens in challenged animals, the details of which we have reported [41]. Namely, one day prior to the assay start we seeded 12-well with VeroE6 cells and incubated overnight (37°C 5% CO 2 ) such that each well was confluent by the assay start. On the day of the assay, serial dilutions of virus-containing material (e.g. lung homogenate) were prepared in cDMEM and warmed to 37°C. Media from each well of the 12-well plate was gently removed via pipette and replaced with 500uL of each virus sample dilution, the volume pipetted down the side of the well so as not to disturb the VeroE6 monolayer. The plate was incubated for 1 hr at 37°C 5% CO 2 . During this incubation period, a solution comprising a 1:0.7 mixture of cDMEM and 2% methylcellulose (viscosity: 4000 cP) was freshly made and warmed to 37°C in a water bath. After the 1 hr incubation period was over, the supernatant was removed from each well and replaced with 1 mL of the pre-warmed cDMEM:methylcellulose mixture. The culture plate was then returned to the incubator and left undisturbed for 3 days. On the final day, the cDMEM:methylcellulose mixture was removed from each well, cells were fixed with 4% para-formaldehyde in PBS (20 minutes, room temperature), washed with PBS and stained with 0.05% crystal violet (in 20% methanol). After rinsing plates with distilled water, plates were dried, and plaques were counted under a light microscope. Histology The inferior lung lobe was removed from mice and fixed in 10% formalin. Sample processing, paraffin embedding, H&E and acid fast bacilli (AFB) staining was performed by the OSU Comparative Pathology & Mouse Phenotyping Shared Resource (CPMPSR). Immunohistochemistry (IHC) was performed using a monoclonal antibody specific to SARS-CoV-2 Nucleocapsid (clone B46F; ThermoFisher) per previously reported methods [42]. Histology slides were imaged using a Nikon Ti2 widefield microscope fitted with 4x, 10x and 60x CFI Plan Fluor objectives and a DS-Fi3 color camera. Images were processed using FIJI [43] and compiled using BioRender.com. The individual and cumulative areas of each TB granuloma in MtbPOSCoV2NEG and MtbPOSCoV2POS lungs were determined using our previously reported methods [44]. ELISA CoV2 N protein levels in lung homogenates were determined using a commercially available ELISA kit (ADS Biotec), as were protein levels of the cytokines IL1β, IL6 and IFNγ (Biolegend). ELISA kits were used per manufacturer protocols. Quantitative Real Time PCR Lung RNA was extracted from the superior lung lobe using the RNeasy Mini Kit method (Qiagen) and reverse transcribed using the SuperScript VILO cDNA Synthesis Kit method (ThermoFisher). Quantitative real time PCR (qRT-PCR) was performed on a C1000 Touch Thermocycler (Bio-Rad) using SYBR Select Master Mix (Applied Biosystems) per manufacturer protocols. The primer sequences used to amplify cDNA for genes of interest were previously published [45,46]. Each biological replicate was performed in technical duplicate and data were analyzed using the ΔΔCt method. Cell purification To purify live CD45+ cells for single cell RNA sequencing, lungs from uninfected, Mtb- or MACoV2-monoinfected and Mtb/MACoV2 coinfected mice were removed and treated in an identical manner. Lungs were first digested in a DNase/collagenase mixture [47]; dead cells from the resulting slurry were then removed via negative magnetic selection using the Dead Cell Removal kit method (Miltenyi). The live cells were then mixed with CD45 microbeads (Miltenyi) and used for positive magnetic selection of live CD45+ cells. Trypan blue staining was used to confirm cell viability. Cells were the prepared for single cell partitioning via a 10X Genomics Chromium Controller using manufacturer provided protocols (10x Genomics Document Number CG000136). 1 x 104 cells per experimental group were loaded onto the Controller and partitioned, as carried out by the OSU Genomics Shared Resource core. Single cell RNA sequencing (scRNA seq) scRNA-seq libraries were prepared and analyzed using the 10X Genomics and Illumina platforms, respectively, per previously reported methods [48]. Statistical analysis All experiments were performed using randomly assigned mice without investigator blinding. All data points and p values reflect biological replicates from at least two independent experiments per figure (4 mice per group per timepoint). Statistical analysis was performed using GraphPad Prism. Unpaired, two-tailed Student t tests and one-way ANOVA tests with post hoc Tukey-Kramer corrections were used to assess statistical significance. Graphs were likewise generated in GraphPad Prism. The only exception to this were the t-distributed stochastic neighbor embedding (t-SNE), annotation and graphing associated with our scRNA analysis, which was performed with Cell Ranger and RStudio.

Supporting information S1 Fig. Lineage defining markers were similarly expressed across uninfected (UI), MtbNEGMACoV2POS, MtbPOSMACoV2NEG and MtbPOSMACoV2POS groups. The distribution and expression patterns of lineage defining genes that were used to annotate each t-SNE cluster, as shown for each individual experimental group (pooled group data are shown in Fig 5). https://doi.org/10.1371/journal.ppat.1010093.s001 (TIF)

Acknowledgments We would like to acknowledge the laboratories of Jianrong Li (OSU), Mark Peeples (OSU & Nationwide Children’s Hospital) and Jacob Yount (OSU) who grew and provided the MACoV2 used in our studies, as well as BSL3 Director Luanne Hall-Stoodley and BSL3 Research Assistant Abigail Mayer for maintaining the facilities needed for our studies.

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