Three-dimensional in vivo monitoring of mycobacterial infections and therapeutic efficacy based on tissue-clearing technology CUBIC

Three-dimensional in vivo monitoring of mycobacterial infections and therapeutic efficacy based on tissue-clearing technology CUBIC | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Three-dimensional in vivo monitoring of mycobacterial infections and therapeutic efficacy based on tissue-clearing technology CUBIC Mariko Hakamata, Akihito Nishiyama, Erina Inouchi, Akira Yokoyama, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2537112/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Mycobacteria are a continuous threat to human health. They include various species, such as Mycobacterium tuberculosis ( M. tuberculosis ), which is an intracellular parasite of mammals, and the most virulent and non-tuberculous mycobacteria (NTM), namely, M. avium , which are environmental bacteria causing intractable NTM diseases. An infection model of transparent zebrafish and fish-infectious M. marinum was established to better understand the in vivo behavior of mycobacteria under the pressure of host immune responses. However, the fish model does not fully replicate mammalian immunity. Here, we demonstrate that a clear, unobstructed brain/body imaging cocktail and computational analysis (CUBIC)-based infection (CUBIC-infection) analysis enables comprehensive mycobacterial profiling of the whole lung. We assessed the in vivo kinetics of mycobacterial infection along with fluorescent protein-expressing recombinant mycobacteria. We detected mycobacterium at a single bacterial level and counted bacterial numbers, which was comparable to the colony-forming units of organ homogenates. CUBIC-infection analysis distinguished in vivo spatiotemporal behavior of M. tuberculosis , M. tuberculosis variant Bacillus Calmette-Guerin, and M. avium in mice. Furthermore, it monitored spatiotemporal information on the therapeutic efficacies of anti-tuberculosis drugs and an anti-lymphangiogenesis agent. Our data suggest that CUBIC-infection analysis is a powerful tool for understanding mycobacterial infections in mammals and developing therapeutic agents. Biological sciences/Microbiology Biological sciences/Microbiology/Bacteriology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Tuberculosis (TB), which is a pulmonary infection caused by Mycobacterium tuberculosis ( M. tuberculosis ), is one of the top 10 causes of death worldwide and a leading cause of death from a single infectious agent [ 1 ] . An estimated 10.6 million people were infected, and 1.6 million died in 2021 [ 1 ] . The standard treatment for TB includes multiple anti-TB drugs, such as isoniazid (INH), rifampin (RIF), ethambutol, and pyrazinamide [ 2 ] . However, owing to the alarming increase in drug-resistant TB, the disease cannot be controlled with current chemotherapy alone [ 2 ] . Therefore, novel therapeutic approaches are required to treat TB. Considering the need for new treatments, many researchers have attempted to elucidate the immune system’s role in disease pathogenesis. For example, after infection with M. tuberculosis , it is phagocytosed by alveolar macrophages in the lungs. Subsequently, various immune cells are recruited from the circulation to the site of infection, which leads to granuloma formation. Lymphatics play a critical role in transporting dendritic cells of the immune system, which may contain bacterial, viral, or fungal peptides, to T and B-cell cells in the lymph nodes. However, the structure of the lymphatic vessels during infection is still not fully understood because of the inherent limitations of the imaging system. Lymphangiogenesis is induced during neonatal development and post-development (inflammation, infection, and tumor growth) by vascular endothelial growth factor (VEGF)-C and VEGF-D binding to vessel-expressed VEGF receptor 3 (VEGFR-3) [ 3 – 6 ] . In addition, lymphangiogenesis is induced by mycobacterial granulomas via VEGFR-3 and supports systemic T-cell responses against mycobacterial antigens [ 7 ] . Although a previous study showed that inhibition of VEGFR-3 reduces the number of bacteria, it is not understood how significantly it reduces bacterial growth compared with existing TB drugs. The prevalence of pulmonary infections caused by non-tuberculous mycobacteria (NTM) is increasing worldwide [ 8 , 9 ] . Although the NTM family consists of approximately 170 species of mycobacteria, human lung disease is primarily caused by species of M. avium complex (MAC), M. kansasii , and M. abscessus [ 10 ] . TB is transmitted through the inhalation of aerosol droplets containing M. tuberculosis ; however, NTM disease is mostly disseminated through aerosols originating from the environment. NTM lung disease comprises the following five clinical diseases: nodular/bronchiectatic (NB) disease, fibrocavitary (FC) disease, solitary pulmonary nodules, disseminated diseases, and hypersensitivity-like disease [ 11 ] . The FC type usually develops in middle-aged male smokers and is accompanied by apical fibrocavitary lesions. If left untreated, it can progress quickly, leading to extensive lung destruction and respiratory failure [ 11 , 12 ] . In contrast, the NB type occurs predominantly in postmenopausal, nonsmoking females with frequent involvement in the right middle lobe or lingula, and it progresses considerably slower than the FC type [ 11 , 13 ] . Therefore, mycobacteria, such as M. tuberculosis and MAC, are life-threatening in humans. Bacterial characteristics and host factors influence the susceptibility and manifestation of infection and the outcome of treatment [ 13 , 14 ] . Although multiple pathologies with a distinct local milieu (bacterial burden, antibiotic exposure, and host response) can coexist simultaneously within the same subject and change independently over time, the current tools cannot optimally measure these distinct pathologies or spatiotemporal changes. Therefore, to better understand the in vivo behavior of mycobacteria under the pressure of host immune responses, an infection model of transparent zebrafish and fish-infectious M. marinum has been established [ 15 – 18 ] . However, the fish model does not fully replicate mammalian immunity. Recently, total organ imaging enabled by a method that makes an organ transparent, namely, tissue clearing, has been developed and used in various fields of research [ 19 , 20 ] . Studies using tissue-clearing methods, such as the passive clarity technique and ethyl cinnamate, have also been used for fluorescence-labeled M. tuberculosis in infected mouse lungs [ 21 , 22 ] . Although they analyzed the size or shape of granulomas, no report exists on a detailed evaluation of the progression of infection using 3-dimensional (3D) imaging. The hydrophilic chemical-based method called clear, unobstructed brain/body imaging cocktails and computational analysis (CUBIC), developed recently, enables the capture of high-resolution 3D images without sectioning of mouse organs [ 23 ] . This tissue-clearing approach is currently mainly used in neuroscience research and has been employed to analyze diseases, including cancer [ 24 ] . However, analysis of infectious diseases using the CUBIC technique has not been reported. In this study, we aimed to demonstrate CUBIC-based infection (CUBIC-infection). We analyzed the in vivo kinetics of mycobacteria three-dimensionally using the CUBIC method and the following three types of fluorescent protein-expressing recombinant mycobacteria: virulent M. tuberculosis , attenuated vaccine strain; M. tuberculosis variant Bacillus Calmette-Guerin (BCG), and M. avium . We analyzed the progression of three types of mycobacterial infections using a combination of light-sheet fluorescence microscopy (LSFM) and confocal laser scanning microscopy (CLSM). Furthermore, we evaluated the lymphatic vessels in the lungs of mice infected with M. tuberculosis . Finally, we evaluated the therapeutic effect of an inhibitor of lymphangiogenesis compared with that of existing antibacterial agents. This provides a novel and useful tool for understanding mycobacterial infections in mammals and developing therapeutic agents. Results 1. Construction of mycobacterial strains expressing a fluorescent protein for in vivo imaging We constructed fluorescent protein-expressing recombinant bacteria to analyze the in vivo kinetics of mycobacteria. BCG and M. tuberculosis H37Rv transformed with a plasmid encoding DsRed [25] were grown in a mycobacterial complete medium with 20 μg/ml kanamycin at 37°C. M. avium 104 transformed with a plasmid encoding enhanced green fluorescent protein (EGFP) (a kind gift from Prof. Todd Primm) was grown in mycobacteria complete medium with 50 μg/ml hygromycin B at 37°C [26] . After incubation of the strains in the presence of kanamycin or hygromycin B, bacterial cells were stained with 4',6-diamidino-2-phenylindole (DAPI) and analyzed using fluorescence microscopy. Fluorescence microscopy revealed that BCG and M. tuberculosis expressed DsRed (red). M. avium cells expressed EGFP (green) (Fig. 1). The control was M. tuberculosis, which did not express any fluorescent protein. 2. The CUBIC protocol enables the whole-lung imaging of intravenous and intranasal infection models First, we established experimental whole-lung imaging models of intravenous (i. v.) and intranasal (i. n.) infection. C57BL/6 mice were infected intravenously with 1.2 x 10 6 colony-forming units (CFU) or intranasally with 0.6 x 10 6 CFU of DsRed-expressing BCG. Subsequently, we compared the mice treated with phosphate-buffered saline (PBS) using the same methods as those used for the experimental group in both cases. The day after infection, the lungs were excised, and we started clearing them according to the whole-lung clearing protocol (Fig. 2A). The excised lungs were fixed overnight in paraformaldehyde. After washing several times with PBS, the samples were kept at 4°C and further cleared using CUBIC-L for delipidation from day 7. After washing with PBS on day 12, the refractive index (RI) was adjusted using the CUBIC-R. After clearing the lungs, imaging was performed using a combination of LSFM and CLSM. It required 18 days to obtain images at this time; however, in the shortest time, it could be accomplished in 10–14 days [24] . This means that we can obtain results faster from the imaging of CUBIC analysis than counting CFU after 3 weeks of incubation. Fluorescence signals were successfully detected in the lungs of the mice, suggesting that CUBIC-infection analysis applies to fluorescent protein-expressing recombinant mycobacteria (Fig. 2B). Magnified 3D images of the lungs were obtained using CLSM (Fig. 2B, right panels). Notably, the 3D animations of the lung made it easier to observe the fluorescent bacteria in the lungs (Supplementary Video.S1). We also observed the following experiments using the same method. 3. The CUBIC-Infection analysis applies to statistical spatiotemporal analysis during the initial steps of infectious disease progression Statistical spatiotemporal analysis of lung infections can be a powerful tool for infectious disease research. To visualize the time-dependent progression of TB, an experimental M. tuberculosis- infected lung model was used in combination with CUBIC infection analysis. C57BL/6 mice were intranasally infected with 1.0 x 10 6 CFU of DsRed-expressing M. tuberculosis . We categorized the mice into two groups (n=4–5/group at each time point); in the first group, fluorescent foci were detected by CUBIC-infection analysis (Fig. 3A), and in the second group, mice lungs were homogenized, and CFU was counted in each lung. The number and images of bacteria were confirmed on days 1, 14, and 28 post-infection. On the day after the infection, the bacteria were clearly visualized (Fig. 3A and Supplementary Video.S2). Numerous bacteria spread throughout the lung were drastically eliminated on day 14 post-infection, and the bacteria remaining in the lung appeared to aggregate (Fig. 3A). On day 28 post-infection, bacterial aggregation was more clearly observed (Fig. 3A and B), suggesting that aggregations likely reflected granuloma by the immune response of the host. In addition, we showed that the resolution of these 3D images was significantly high to discriminate between individual bacterial cells and was comparable to that of 2D hematoxylin and eosin (HE) slice images, which were obtained after CUBIC-infection analysis (Fig. 3A, right panels). Next, we analyzed the number and location of bacteria in the lungs using the Imaris software (Fig. 3B). These points were used to plot the bacterial parts. It is possible to identify the location of this point on the x-, y-, and z-axes. Finally, we evaluated where the bacteria were most abundant in the lungs by calculating the median value for each of the x-, y-, and z-axes. It was estimated that most bacteria were located in or near the main bronchus on the day after infection. We investigated the relationship between CFU and the number of bacteria calculated using CUBIC analysis (Fig. 3C). The CFUs in the lungs decreased 2 weeks after infection and increased slightly 4 weeks after infection. By combining CFU and fluorescence-based foci number or volume data, it is possible to have a deeper discussion of the relationship between the number of bacteria and lesion development. When combined, CUBIC-infection analysis enabled statistical and spatiotemporal time-course analyses during the initial steps of infectious disease progression. 4. The CUBIC-infection analysis enables monitoring of the different patterns of mycobacterial infection Pathogenic mycobacteria induce the formation of complex cellular aggregates called granulomas, which are the hallmarks of mycobacterial infections [27,28] . This provides the Mycobacterium with a niche where it can survive and be protected from damage by the host's immune response over long periods [29] . M. avium is a causative pathogen of pulmonary NTM diseases. Similar to the more virulent M. tuberculosis , M. avium causes chronic infections in mice, with the development of tissue granulomas [30,31] . To observe the difference in bacterial aggregation between non-pathogenic and pathogenic mycobacteria, we compared the lungs after intranasal infection with the following three types of mycobacteria: BCG, M. avium, and M. tuberculosis . C57BL/6 mice were intranasally infected with 1.0 x 10 6 CFU of DsRed-expressing BCG and 3.0 x 10 5 CFU of GFP-expressing M. avium . Similar to the experimental method, the imaging analysis of the infected lungs was confirmed on days 1, 14, and 28 after infection. On day 28 after infection, BCG appeared to be in individual bacterial forms, whereas M. avium appeared to form small branching nodules gathering several bacteria (Fig. 4A). In M. tuberculosis , individual bacteria could not be confirmed, and large aggregations of bacteria were observed. In the cross-sectional images, the differences in the aggregates of each Mycobacterium can be observed more clearly. These differences were comparable to the degree of inflammatory foci in HE-stained images. In addition, we found each Mycobacterium in Ziehl-Neelsen stained images, which were obtained after CUBIC-infection analysis. Next, we compared the volume distribution of bacterial aggregates for each Mycobacterium (Fig. 4B). Although the volume distribution of aggregates did not change significantly in the BCG, the volume distribution of M. tuberculosis and M. avium increased over time. Interestingly, we also observed differences in the sites of bacterial aggregation. The distribution of BCG and M. avium was not biased in the lungs even on day 28 after infection; however, M. tuberculosis tended to accumulate more in the upper lobe (Fig. 4C). These results may be consistent with the clinical and radiographic diagnoses of pulmonary TB and NTM diseases [13] . Similar to M. tuberculosis , we investigated the relationship between CFU and the number and average volume of bacteria calculated using the CUBIC-infection analysis in BCG and M. avium (Fig. 4D). Therefore, both the bacterial cell number and the volume of bacterial aggregation were almost comparable with CFU. These results suggest that each Mycobacterium has a different tendency to form bacterial aggregates, which may be related to granuloma formation. When combined, CUBIC-infection analysis enabled us to identify different patterns of each bacterial infection from the initial stage of infection. 5. M. tuberculosis infection in severely immunocompromised non-obese diabetic/severe combined immunodeficiency mice The tuberculous granuloma, which is a central feature of mycobacterial infection, is a hallmark of TB infection and disease [29] . These structures are formed by epithelioid macrophages surrounding a cellular necrotic region with a rim of T- and B-lymphocytes [27-29] . The non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mice were created by transferring a SCID mutation into a NOD mouse. The uniqueness of this mouse model is derived from the lack of function of B, T, and NK cells [32] . Therefore, we used M. tuberculosis infection in NOD-SCID mice to investigate the form of bacterial aggregation without an immune response by such lymphocytes. Five NOD/SCID mice were intranasally infected with 1.0 x 10 3 CFU of DsRed-expressing M. tuberculosis . All NOD/SCID mice were sacrificed on day 98 after infection. In addition, four mouse lungs were homogenized for counting CFU, and one was analyzed using the CUBIC-infection analysis. We observed large bacterial aggregation in the NOD/SCID mouse lungs (Fig. 5A). Similar to C57BL/6 mice, it was suggested that the volume of bacterial aggregations in the lung would increase in NOD/SCID mice, in parallel with the CFU of the lung (Fig. 5B). This indicates that M. tuberculosis tends to aggregate, despite a lack of immune function related to T-, B-l, and NK-cells. 6. The CUBIC-infection analysis enables the evaluation of the therapeutic effect of anti-TB drugs in vivo and visualizes lymphangiogenesis in M. tuberculosis infection Granuloma inflammation is a characteristic of many autoimmune and infectious diseases [29] . These granulomas are usually characterized by the concomitant development of hypoxia, which acts as a stimulus for vascularization [33] . Vascularization in animal models of TB is mediated by angiogenesis and lymphangiogenesis. Although the primary role of vascularization of granulomas could be to establish a pathway for immune cell transport within the structure, angiogenesis could also benefit M. tuberculosis growth within the granuloma or its spread to distal sites [29] . Particularly, lymphangiogenesis stimulated by mycobacterial infection promotes systemic T-cell responses against M. tuberculosis infection [7] . VEGF -C and VEGF-D are the main factors in lymphangiogenesis and signal through VEGF receptor 3 (VEGFR3) [34] . Systemic levels of VEGF-C have been reported to be higher in active pulmonary TB than in both latent TB and no TB infections [35] . Here, we attempted to establish a therapeutic evaluation system for M. tuberculosis infection in the lungs and examined the relationship between M. tuberculosis infection and lymphoid vessels by infection analysis. C57BL/6 mice were intranasally infected with M. tuberculosis and treated with the anti-TB drugs INH and RIF to assess the chemotherapeutic response in the mouse lungs. We also treated M. tuberculosis -infected mice with the VEGFR3 inhibitor MAZ51 (a receptor tyrosine kinase inhibitor [36] ). Twenty-eight days after M. tuberculosis infection, the proliferation of bacteria tended to be suppressed in the drug-treated groups (Fig. 6A and 6B). Notably, many foci were still detected on the bronchial wall in the drug treatment groups, which might have been dormant or resistant to anti-TB drugs (Fig. 6A). Although no significant difference was found in the CFU and total volume of bacterial aggregation, all drugs significantly reduced the number of foci calculated using CUBIC analysis (Fig. 6B). Particularly, 1 week of lymphangiogenesis-blocking treatment with MAZ51 resulted in a drastic reduction in bacteria. Next, we examined the volume of lymphatic vessels in the lungs after infection in each group using the 3D immunohistochemical analysis. We used a VEGFR3 antibody to visualize lymphatic endothelial cells as previously reported [24] and measured VEGF-C concentrations in serum from mice 28 days after infection with M. tuberculosis . Many lymphatic vessels were detected in the untreated group, where the accumulation of bacteria was high (Fig. 6C). In the treatment group, VEGFR3+Area per lung and VEGF-C concentration in the serum of mice tended to be suppressed (Fig. 6C and 6D). These data indicate that new lymphatic vessels play a crucial role in the growth of M. tuberculosis in the early stages of infection. When combined, the CUBIC-infection analysis can be used to evaluate the in vivo effects of anti-TB agents. Discussion Fluorescent proteins, bioluminescence, and reporter enzyme fluorescence have been employed for in vivo imaging and successfully used for the real-time detection of M. tuberculosis in live animals and cells [17,37−39] . These in vivo imaging studies of fluorescent protein-expressing M. tuberculosis reported the number of bacteria based on the intensity of the fluorescence signal. However, it has been challenging to specify bacteria at a single-cell resolution in the 3D structure of living animals. Additionally, host-immune interactions occur within various 3D tissues and can result in the formation of complex structures. However, visualizing these host–microbe interactions in intact tissues remains difficult. Here, we demonstrate that recently developed CUBIC techniques enable high-resolution imaging of infection in the whole mouse lung tissue infected with mycobacteria. The novelty of this study lies in its innovative approach to visualizing bacterial reactions during infection. Using CUBIC-infection analysis, we observed immune-mediated elimination of bacteria and bacterial aggregation. CUBIC-infection analysis also enables statistical spatiotemporal analysis during the initial stages of infectious disease progression. Furthermore, since lung clearing uses the whole lung sample, macroscopic analysis, such as shape, volume, and distribution of granuloma, can be performed simultaneously with microscopic analysis. We found that the basic tissue pathology was well preserved by HE staining, and we detected the bacteria in the CUBIC-treated samples using Ziehl–Neelsen staining. These observations indicate that CUBIC-infection analysis could bridge the resolution gap between conventional in vivo bioluminescence imaging and 2D histology. Therefore, in the future, it will be possible to further analyze the interaction between immune cells, such as macrophages and bacteria, three-dimensionally using immunohistochemical methods or genome-editing technology. Drug-resistant TB is a public health concern worldwide. For decades, the number of patients infected with M. tuberculosis who are resistant to the most effective drugs against TB has continued to increase [ 1 ] . Therefore, to prevent the increase in drug-resistant TB, it is necessary to properly use existing anti-TB drugs and discover new antimycobacterial agents effective against multidrug-resistant M. tuberculosis . Our data showed that CUBIC-infection analysis could quantitatively evaluate the therapeutic effects of anti-TB drugs. In addition, we investigated the relationship between the lymphatic vessels in mouse lungs and bacteria using immunohistochemical techniques. Our data showed that lymphangiogenesis during infection was reduced by the inhibition of VEGFR3, and the growth of M. tuberculosis can be suppressed by inhibiting lymphangiogenesis in the early stages of infection. Our data suggest that M. tuberculosis induces lymphangiogenesis, which promotes mycobacterial growth and increases the spread of the infection to new tissue sites. This result is consistent with a previously reported model where mycobacterial-induced granulomas around lymphatic vessels in infected tissues resulted in VEGF-C-mediated lymphangiogenesis via vessel-expressed VEGFR3 [ 7 ] . Anti-angiogenic therapies in combination with anti-TB drugs can enhance treatment in patients with TB [ 40 , 41 ] . Our CUBIC-infection analysis agreed with the effectiveness of anti-lymphangiogenic therapies as host-targeting TB therapy. Generally, TB has two clinical states: frequent long-term latency and active disease. Approximately one-quarter of the world’s human population is asymptomatically infected with M. tuberculosis , a state known as latent TB infection (LTBI) [ 1 ] . LTBI is a large source of the disease; generally, 5–10% of patients with LTBI develop active TB during their lifetime [ 42 ] . Therefore, identifying drug targets against the dormant state of M. tuberculosis is critical to successfully eradicate TB. Our data showed that CUBIC-infection analysis could detect M. tuberculosis bacilli, even after treatment with anti-TB drugs (Fig. 6 ). It may be directly visible that TB relapse after administration of the immunosuppressive drugs [ 43 , 44 ] . Therefore, CUBIC-infection analysis may be an effective tool for investigating the effects of new drugs that target LTBI. Evaluation of 3D imaging of M. tuberculosis -infected lungs using another tissue-clearing technique was reported in the past [ 21 , 22 ] ; however, this is the first report of a model using CUBIC. Although conventional methods can also evaluate granuloma masses, capturing single bacterial cells in clear mouse lungs is difficult because of their low resolution. The high resolution of CUBIC enables the observation of bacteria at the single-cell level and the progression of infection over time. In addition, since the trachea and lymphatic vessels are clearly depicted, it is useful to investigate the relationship between the bacteria and host organs. In conclusion, we found that CUBIC-infection analysis can detect bacteria at a single-cell resolution in infected mouse lungs. This analysis can visualize the progression patterns for each bacterium and evaluate the effects of drugs. We suggest that CUBIC-infection analysis provides critical information for developing curative treatments for mycobacterial infections. Methods Bacterial strains, culture media, and general reagents All mycobacterial strains were grown in Middlebrook 7H9 broth (BD, Franklin Lakes, NJ, USA) supplemented with 0.2% (v/v) glycerol, 0.05% (v/v) Tween 80 (MP Biomedicals, Santa Ana, CA, USA), 10% ADC enrichment (5% bovine serum albumin [Wako Pure Chemical Industries, Osaka, Japan], 0.81% sodium chloride, and 2% D-glucose) (7H9-ADC broth) or on mycobacteria 7H10 agar (BD) supplemented with 0.5% (v/v) glycerol and 10% OADC enrichment (ADC enrichment supplemented with 0.06% [v/v] oleic acid) (7H10-OADC agar). In addition, appropriate antibiotics were added to the medium to maintain the specific genotypes of each strain. Hygromycin B, kanamycin, and RIF were purchased from Wako Pure Chemical Industries (Osaka, Japan). INH was purchased from Sigma–Aldrich. Plasmid Construction Dr. Todd Primm (University of Sam Houston, State) kindly provided M. avium 104 transformed with a plasmid encoding EGFP. In addition, the plasmid encoding DsRed was used as previously described. This plasmid was introduced into BCG and M. tuberculosis by electroporation, and kanamycin-resistant BCG colonies were selected after 3 weeks of culture on Middlebrook 7H10-OADC agar in the presence of 20 µg/ml kanamycin. The expression of GFP and DsRed was confirmed using a BZ-X700 Series fluorescence microscope (Keyence, Osaka, Japan). Fluorescence microscopic analysis The harvested bacterial cells were treated with 10 µg/ml DAPI (Thermo Fisher Scientific) at room temperature for 20 min under protection from light. The stained cells were centrifuged at 6000 rpm for 5 min and mounted on a slide after treatment with 4% paraformaldehyde containing 10 µg/ml DAPI. The bacterial cells were visualized with an x100 oil immersion objective using an All-in-one BZ-X700 Series fluorescence microscope. Slides of triplicate cultures from numerous randomly selected microscopic fields were analyzed. Mouse infections This study was reported in accordance with ARRIVE guidelines ( https://arriveguidelines.org).Th e Animal Care and Use Committee of the Graduate School of Medicine, University of Niigata, approved all experimental procedures and housing conditions. All animals were cared for and treated humanely, following the Institutional Guidelines for Experiments Using Animals. Female C57BL/6 mice, 7 weeks of age (Japan Clea, Suita, Osaka, Japan), were inoculated intravenously or intranasally with 0.6–1.2 x 10 6 CFUs of DsRed-expressing BCG, M. tuberculosis , and GFP-expressing M. avium and assigned to groups (n = 4–5/group). On day 1 and 2 and 4 weeks of infection, the lungs of mice were removed aseptically and homogenized individually with 4.5 ml sterile distilled water. After a 10-fold serial dilution, a smear plate for each lung homogenate was prepared by spreading 0.1 ml of each diluted solution on a 7H10-OADC agar. Mycobacterial colonies were counted 3 weeks after culture. Anti-TB treatment was conducted with four mice per group, randomly selected, by administration of RIF (10 mg/kg) and INH (25 mg/kg), intragastrically 5 days per week for 7 days before harvest at 21 days post-infection. DsRed-expressing M. tuberculosis -infected mice were treated with 10 mg/kg/day MAZ51 (EMD Millipore, Billerica, MA) in 50 µl of dimethyl sulfoxide for 7 days before harvest at 21 days post-infection. At each time point, a group of animals in each treatment category was necropsied, lungs were imaged, and homogenized for CFU determination. The CUBIC protocol for whole-lung clearing To prepare whole-organ clearing samples, female C57BL/6 mice were sacrificed under anesthesia with midazolam (4 mg/kg; Fuji Seiyaku, Toyama, Japan), medetomidine (0.75 mg/kg, Nihon Zenyaku, Fukushima, Japan), and butorphanol (5 mg/kg, Meiji Seika, Tokyo, Japan) tartrate (MMB) combination; subsequently, they perfused with 20 ml of PBS (pH 7.4) and 30 ml of 4% (w/v) Paraformaldehyde (PFA) (163-20145, FUJIFILM) in PBS via the left ventricle of the heart. The excised organs were post-fixed in 4% (w/v) PFA at 4°C for 24 hours. The specimens were washed with PBS three times for more than 2 hours to remove the PFA immediately before cleaning. The fixed organs were immersed in CUBIC-L with gentle shaking at 37°C for 5 days. CUBIC-L was exchanged on day 2. After decolorization and delipidation, the organs were washed three times with PBS at room temperature for more than 2 hours. The organs were further immersed in 50% (v/v) CUBIC-R (1:1 mixture of water and CUBIC-R) for more than 6 hours and then in CUBIC-R at room temperature with gentle shaking for at least 1 day. 3D immunostaining of CUBIC samples After decolorization and delipidation, organ samples were subjected to immunostaining with 1:100 diluted antibodies in a staining buffer composed of 0.5% (v/v) Triton X-100, 0.25% casein (37528, Thermo Fisher Scientific, Waltham, MA) and 0.01% sodium azide (195-11092, WAKO, Osaka, Japan) for 3 days at room temperature with shaking. The stained samples were washed three times with PBS at room temperature with rotation; subsequently, they were immersed in CUBIC-R. The following antibodies were used for staining: Mouse VEGFR3/Flt4 antibody (AF743, R&D Systems, Minneapolis, MN, USA) and donkey anti-goat immunoglobulin G (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor 647 (A-21447, Thermo Fisher Scientific, Waltham, MA). Microscopy Whole-organ images were acquired using custom-built LSFM (Olympus, Tokyo, Japan). Images were captured using a 0.63 × objective lens (numerical aperture = 0.15, working distance = 87 mm) with a digital zoom from 1 × to 1.25 × zoom. Lasers of 488 nm and 532 nm were used for image acquisition. The stage was moved moth in the lateral and axial directions to cover the whole organ. When the stage was moved in the axial direction, the detection objective lens was synchronically moved to the axial direction to avoid defocusing. Furthermore, high-resolution images for cell profiling were acquired using CLSM (FLUOVIEW FV1200, Olympus). Images were captured using a 25 × objective lens (numerical aperture = 1.0, working distance = 8.0 mm) with a digital zoom from 1 × to 2 × zoom. Lasers of 488 nm and 532 nm were used for image acquisition. Refractive index (RI) matched sample was immersed in a mixture of silicon oil HIVAC-F4 (RI = 1.555, Shin-Etsu Chemical Co., Ltd., Tokyo, Japan) and mineral oil (RI = 1.467, M8410, Sigma–Aldrich) during image acquisition. 3D-rendered images were visualized, captured, and analyzed using the Imaris software (version 7.7.1 and 8.1.2, Bitplane AG, Zurich, Switzerland). Image data processing and analysis All raw image data were collected in lossless 16-bit Tagged Image File Format. 3D-rendered images were visualized and captured using the Imaris software (version 7.6.4, 7.7.1, and 8.1.2, Bitplane). The brightness, contrast, and gamma of the 3D-rendered images were manually adjusted using the software when visualized. Subsequently, the 3D images were used for image analysis using the Imaris software. For the quantification of infections, an appropriate threshold of signals from reporter proteins was selected in each experiment, and surface analysis was performed using the Imaris software. An appropriate threshold of signals was selected in each experiment, and spot analysis was performed using the Imaris software to count the cell number. Histological Examination After CUBIC analysis, the entire lung was washed with PBS and resected. As previously described, the samples were embedded in paraffin and subjected to HE and Ziehl–Neelsen staining. Statistical Analyses The significance of the results was determined using the Student’s t-test or analysis of variance, as appropriate. Statistical significance was set at P < 0.05. In the figures, *represents P < 0.05, ** represents P < 0.01, and *** represents P < 0.001. Declarations Data availability The data supporting this study’s findings are available in the article and its supplementary material. Acknowledgments We are grateful to Dr. Takahiro Hakamata, Ms. Yuko Kobayashi, Haruka Kobayashi, Sara Matsumoto, and Satoko Matsumoto for their assistance and encouragement. This research was supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science to Mariko Hakamata and Sohkichi Matsumoto (21KK0136), AMED-CREST (22gm1610009h0001), and the Research Program on Emerging and Re-emerging Infectious Diseases from AMED to Akihito Nishiyama (19fk0108090), and Sohkichi Matsumoto (21fk0108497s0101). This study was also supported by the United States–Japan Cooperative Medical Science Program against Tuberculosis and Leprosy. The funders had no role in the study design, data collection and interpretation, or decision to submit the work for publication. Author contributions M.H., A.N., K.T., and S.M. conceived the project and designed the study. M.H., E.I., A.Y., S.K., G.G., and T.Y. performed experiments. M.H., A.N., G.G., and S.M. wrote the main manuscript text. H.M., Y.O., Y.T., R.O., T.P., T.K., K.T., and S.M. supervised all aspect of the project. All authors reviewed the manuscript. 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McCune, R. M., Jr. & Tompsett, R. Fate of Mycobacterium tuberculosis in mouse tissues as determined by the microbial enumeration technique. I. The persistence of drug-susceptible tubercle bacilli in the tissues despite prolonged antimicrobial therapy. J. Exp. Med. 104 , 737-762 (1956). Scanga, C. A. et al. Reactivation of latent tuberculosis: variations on the Cornell murine model. Infect. Immun. 67 , 4531-4538 (1999). Additional Declarations No competing interests reported. Supplementary Files CUBICFiguresuuplementaryver.pptx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2537112","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":174402016,"identity":"bcc98529-d9d1-4d59-a2c9-38dd8aae8b24","order_by":0,"name":"Mariko Hakamata","email":"data:image/png;base64,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","orcid":"","institution":"Niigata University School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Mariko","middleName":"","lastName":"Hakamata","suffix":""},{"id":174402018,"identity":"9928035f-31ce-467d-903b-74356634c930","order_by":1,"name":"Akihito Nishiyama","email":"","orcid":"","institution":"Niigata University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akihito","middleName":"","lastName":"Nishiyama","suffix":""},{"id":174402020,"identity":"019177ca-1660-4953-9151-9b352f635f69","order_by":2,"name":"Erina Inouchi","email":"","orcid":"","institution":"Niigata University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Erina","middleName":"","lastName":"Inouchi","suffix":""},{"id":174402022,"identity":"a9ec568f-b6d5-4c94-9ea3-e5ca20acd329","order_by":3,"name":"Akira Yokoyama","email":"","orcid":"","institution":"Niigata University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Yokoyama","suffix":""},{"id":174402023,"identity":"acb008bd-d73a-4ccf-9733-150fdaf4ba23","order_by":4,"name":"Shaban A. 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The cells were stained with DAPI and analyzed using a fluorescence microscope. Bright-field images (Bright), DAPI-stained images (DAPI), fluorescent microscopic images of DsRed (red) and GFP (green), and merged images (merge) of representative cells are shown. Scale bars: 5 μm\u003c/p\u003e\n\u003cp\u003eGFP, green fluorescent protein; DAPI, 4',6-diamidino-2-phenylindole; BCG, Bacillus Calmette-Guerin\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/4652ade62f62a0c5ce194241.png"},{"id":32716480,"identity":"7ddf99a1-1783-4532-a3d5-22e04e430789","added_by":"auto","created_at":"2023-02-09 16:46:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":473962,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWhole-lung imaging of infection at single-cell resolution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Whole-lung clearing protocol in 18 days and transmission images of whole lungs from adult C57BL/6 mice. (B) Whole-lung imaging of the experimental lung infection model by intravenous (i.v) and intranasal (i.n) injection with PBS or DsRed-fluorescent BCG in C57BL/6 mice. These images show the lungs on the day after infection. We can also observe this in Video. S1.\u003c/p\u003e\n\u003cp\u003ePBS, phosphate-buffered saline; BCG, Bacillus Calmette-Guerin\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/ea9590e073b7a85030004258.png"},{"id":32716014,"identity":"ee9e9741-4fdb-4a3c-b4a2-dfb21cdf761e","added_by":"auto","created_at":"2023-02-09 16:38:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":827185,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatiotemporal dynamics of infectious progression in an experimental lung infection model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Time course images of the experimental lung infection model with DsRed-fluorescent \u003cem\u003eM. tuberculosis\u003c/em\u003e in C57BL/6 mice. C57BL/6 mice were intranasally injected with Ds-Red-fluorescent \u003cem\u003eM. tuberculosis. \u003c/em\u003eThe 3D images of the lung samples at days 1, 14, and 28 post-infection are shown. (B) Quantification of bacteria distribution in C57BL/6 mice. Spot and surface analyses were applied to the sample images on days 1 and 28 post-infection. (C) Quantification of the cell number and the average volume of bacterial aggregations in C57BL/6 mice. The number and the average volume of foci from (A) are shown. The animal number at each time point is n=3–4. Data represent mean ± SD.\u003c/p\u003e\n\u003cp\u003e3D, three-dimensional; SD, standard deviation\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/7a6b090a08caa284f5d11879.png"},{"id":32716016,"identity":"f966c729-6b69-49ec-83e7-aca9d1ee1d5b","added_by":"auto","created_at":"2023-02-09 16:38:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":268355,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferent progression patterns of the three mycobacteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Lung imaging of the experimental infection models with \u003cem\u003eM. tuberculosis var BCG\u003c/em\u003e,\u003cem\u003e M. tuberculosis,\u003c/em\u003e and \u003cem\u003eM. avium \u003c/em\u003ein C57BL/6 mice. C57BL/6 mice were intranasally injected with Ds-Red-fluorescent\u003cem\u003e BCG\u003c/em\u003e, \u003cem\u003eM. tuberculosis, \u003c/em\u003eand GFP-fluorescent \u003cem\u003eM. avium. \u003c/em\u003eThe 3D images of the lung samples at day 28 post-infection are shown. The typical HE staining patterns of each Mycobacterium after CUBIC-infection analysis, including cell aggregates, are shown. The Ziehl–Neelsen stained images obtained after CUBIC-infection analysis show each Mycobacterium. (B) Quantification of the volume distribution of cell aggregations in C57BL/6 mice. Surface analysis was applied to the sample images on days 1, 14, and 28 post-infection. The animal number at each time point is n = 3–4. Data represent mean ± SD. (C) Quantification of each bacterial distribution from (A) in C57BL/6 mice. (D) Quantification of the cell number and the average volume of bacterial aggregations of \u003cem\u003eBCG\u003c/em\u003e and \u003cem\u003eM. avium\u003c/em\u003e in C57BL/6 mice. The animal number at each time point is n = 4–5. Data represent mean ± SD.\u003c/p\u003e\n\u003cp\u003eGFP, green fluorescent protein; BCG, Bacillus Calmette-Guerin; 3D, three-dimensional; SD, standard deviation; HE, hematoxylin and eosin\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/84048849085c9e381945b84f.png"},{"id":32716017,"identity":"c2731825-8bc1-488a-a3c9-1ec25e044556","added_by":"auto","created_at":"2023-02-09 16:38:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":500058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eObservation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eM. tuberculosis-\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003einfected NOD/SCID mouse lungs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Representative images of the experimental lung infection model with DsRed-fluorescent \u003cem\u003eM. tuberculosis\u003c/em\u003e in NOD/SCID mice. NOD/SCID mice were intranasally injected with Ds-Red-fluorescent \u003cem\u003eM. tuberculosis\u003c/em\u003e. The 3D images of the lung sample at day 98 post-infection are shown. (B) Quantification of the cell number, the total volume of bacterial aggregations, and volume distribution of cell aggregations in NOD/SCID.\u003c/p\u003e\n\u003cp\u003eNOD, non-obese diabetic; SCID, severe combined immunodeficiency; 3D, three-dimensional\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/47b44bb429f149a159cd1c32.png"},{"id":32716479,"identity":"15b90289-ccfa-4ef8-8cbe-4530ee3c70f7","added_by":"auto","created_at":"2023-02-09 16:46:06","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":630776,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQuantitative evaluation of the therapeutic effects of anti-TB drugs and inhibitors of VEGFR3 in an experimental lung infection model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) In vivo therapeutic efficacy of the drugs. The 3D images of the lung samples are shown (\u003cem\u003eM. tuberculosis\u003c/em\u003e, DsRed). (B) Quantification of the pharmacotherapeutic effects of anti-TB drugs and inhibitors of VEGFR3. The animal number in each group is n = 4. Data represent mean ± SD. (C) In vivo 3D images of lymphatic vessels in the lung samples are shown. Surface analysis was applied to the images in Fig. 6A. (D) Quantification of the volume of lymphatic vessels after treatment (Left panel). The animal number in each group is n = 4. Data represent mean ± SD. Quantification of the VEGF-C concentration in mice serum by ELISA.\u003c/p\u003e\n\u003cp\u003eVEGF, vascular endothelial growth factor; 3D, three-dimensional; SD, standard deviation; TB, tuberculosis\u003cstrong\u003e;\u003c/strong\u003e ELISA,\u003cstrong\u003e \u003c/strong\u003eenzyme-linked immunoassay; VEGFR3, vascular endothelial growth factor receptor 3\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/4d2810aa9834af4307db6880.png"},{"id":33482442,"identity":"d0cfddb2-5aab-48a4-930c-44af92b561ff","added_by":"auto","created_at":"2023-02-27 06:44:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3401628,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/26ab90ad-2a78-439b-b2df-b4a39bb49651.pdf"},{"id":32716018,"identity":"1f4d3681-9c1c-4f7b-a33a-0a8c480057e2","added_by":"auto","created_at":"2023-02-09 16:38:07","extension":"pptx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":32884125,"visible":true,"origin":"","legend":"","description":"","filename":"CUBICFiguresuuplementaryver.pptx","url":"https://assets-eu.researchsquare.com/files/rs-2537112/v1/60aacd8d4331761a3705fbe2.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Three-dimensional in vivo monitoring of mycobacterial infections and therapeutic efficacy based on tissue-clearing technology CUBIC","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTuberculosis (TB), which is a pulmonary infection caused by \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e (\u003cem\u003eM. tuberculosis\u003c/em\u003e), is one of the top 10 causes of death worldwide and a leading cause of death from a single infectious agent\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. An estimated 10.6\u0026nbsp;million people were infected, and 1.6\u0026nbsp;million died in 2021\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. The standard treatment for TB includes multiple anti-TB drugs, such as isoniazid (INH), rifampin (RIF), ethambutol, and pyrazinamide\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. However, owing to the alarming increase in drug-resistant TB, the disease cannot be controlled with current chemotherapy alone\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Therefore, novel therapeutic approaches are required to treat TB.\u003c/p\u003e \u003cp\u003eConsidering the need for new treatments, many researchers have attempted to elucidate the immune system\u0026rsquo;s role in disease pathogenesis. For example, after infection with \u003cem\u003eM. tuberculosis\u003c/em\u003e, it is phagocytosed by alveolar macrophages in the lungs.\u003c/p\u003e \u003cp\u003eSubsequently, various immune cells are recruited from the circulation to the site of infection, which leads to granuloma formation. Lymphatics play a critical role in transporting dendritic cells of the immune system, which may contain bacterial, viral, or fungal peptides, to T and B-cell cells in the lymph nodes. However, the structure of the lymphatic vessels during infection is still not fully understood because of the inherent limitations of the imaging system. Lymphangiogenesis is induced during neonatal development and post-development (inflammation, infection, and tumor growth) by vascular endothelial growth factor (VEGF)-C and VEGF-D binding to vessel-expressed VEGF receptor 3 (VEGFR-3)\u003csup\u003e[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In addition, lymphangiogenesis is induced by mycobacterial granulomas via VEGFR-3 and supports systemic T-cell responses against mycobacterial antigens \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Although a previous study showed that inhibition of VEGFR-3 reduces the number of bacteria, it is not understood how significantly it reduces bacterial growth compared with existing TB drugs.\u003c/p\u003e \u003cp\u003eThe prevalence of pulmonary infections caused by non-tuberculous mycobacteria (NTM) is increasing worldwide\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Although the NTM family consists of approximately 170 species of mycobacteria, human lung disease is primarily caused by species of \u003cem\u003eM. avium\u003c/em\u003e complex (MAC), \u003cem\u003eM. kansasii\u003c/em\u003e, and \u003cem\u003eM. abscessus\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. TB is transmitted through the inhalation of aerosol droplets containing \u003cem\u003eM. tuberculosis\u003c/em\u003e; however, NTM disease is mostly disseminated through aerosols originating from the environment. NTM lung disease comprises the following five clinical diseases: nodular/bronchiectatic (NB) disease, fibrocavitary (FC) disease, solitary pulmonary nodules, disseminated diseases, and hypersensitivity-like disease\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. The FC type usually develops in middle-aged male smokers and is accompanied by apical fibrocavitary lesions. If left untreated, it can progress quickly, leading to extensive lung destruction and respiratory failure\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. In contrast, the NB type occurs predominantly in postmenopausal, nonsmoking females with frequent involvement in the right middle lobe or lingula, and it progresses considerably slower than the FC type\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, mycobacteria, such as \u003cem\u003eM. tuberculosis\u003c/em\u003e and MAC, are life-threatening in humans. Bacterial characteristics and host factors influence the susceptibility and manifestation of infection and the outcome of treatment\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Although multiple pathologies with a distinct local milieu (bacterial burden, antibiotic exposure, and host response) can coexist simultaneously within the same subject and change independently over time, the current tools cannot optimally measure these distinct pathologies or spatiotemporal changes. Therefore, to better understand the \u003cem\u003ein vivo\u003c/em\u003e behavior of mycobacteria under the pressure of host immune responses, an infection model of transparent zebrafish and fish-infectious \u003cem\u003eM. marinum\u003c/em\u003e has been established\u003csup\u003e[\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. However, the fish model does not fully replicate mammalian immunity.\u003c/p\u003e \u003cp\u003eRecently, total organ imaging enabled by a method that makes an organ transparent, namely, tissue clearing, has been developed and used in various fields of research\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Studies using tissue-clearing methods, such as the passive clarity technique and ethyl cinnamate, have also been used for fluorescence-labeled \u003cem\u003eM. tuberculosis\u003c/em\u003e in infected mouse lungs\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Although they analyzed the size or shape of granulomas, no report exists on a detailed evaluation of the progression of infection using 3-dimensional (3D) imaging.\u003c/p\u003e \u003cp\u003eThe hydrophilic chemical-based method called clear, unobstructed brain/body imaging cocktails and computational analysis (CUBIC), developed recently, enables the capture of high-resolution 3D images without sectioning of mouse organs\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis tissue-clearing approach is currently mainly used in neuroscience research and has been employed to analyze diseases, including cancer\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. However, analysis of infectious diseases using the CUBIC technique has not been reported.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to demonstrate CUBIC-based infection (CUBIC-infection). We analyzed the \u003cem\u003ein vivo\u003c/em\u003e kinetics of mycobacteria three-dimensionally using the CUBIC method and the following three types of fluorescent protein-expressing recombinant mycobacteria: virulent \u003cem\u003eM. tuberculosis\u003c/em\u003e, attenuated vaccine strain; \u003cem\u003eM. tuberculosis\u003c/em\u003e variant Bacillus Calmette-Guerin (BCG), and \u003cem\u003eM. avium\u003c/em\u003e. We analyzed the progression of three types of mycobacterial infections using a combination of light-sheet fluorescence microscopy (LSFM) and confocal laser scanning microscopy (CLSM). Furthermore, we evaluated the lymphatic vessels in the lungs of mice infected with \u003cem\u003eM. tuberculosis\u003c/em\u003e. Finally, we evaluated the therapeutic effect of an inhibitor of lymphangiogenesis compared with that of existing antibacterial agents. This provides a novel and useful tool for understanding mycobacterial infections in mammals and developing therapeutic agents.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. Construction of mycobacterial strains expressing a fluorescent protein for \u003cem\u003ein vivo\u003c/em\u003e imaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe constructed fluorescent protein-expressing recombinant bacteria to analyze the \u003cem\u003ein vivo\u003c/em\u003e kinetics of mycobacteria. BCG and \u003cem\u003eM. tuberculosis\u0026nbsp;\u003c/em\u003eH37Rv transformed with a plasmid encoding DsRed\u003csup\u003e[25]\u003c/sup\u003e were grown in a mycobacterial complete medium with 20 \u0026mu;g/ml kanamycin at 37\u0026deg;C. \u003cem\u003eM. avium\u0026nbsp;\u003c/em\u003e104 transformed with a plasmid encoding enhanced green fluorescent protein (EGFP) (a kind gift from Prof. Todd Primm) was grown in mycobacteria complete medium with 50 \u0026mu;g/ml hygromycin B at 37\u0026deg;C \u003csup\u003e[26]\u003c/sup\u003e. After incubation of the strains in the presence of kanamycin or hygromycin B, bacterial cells were stained with 4\u0026apos;,6-diamidino-2-phenylindole (DAPI) and analyzed using fluorescence microscopy. Fluorescence microscopy revealed that BCG and \u003cem\u003eM. tuberculosis\u003c/em\u003e expressed DsRed (red). \u003cem\u003eM. avium\u003c/em\u003e cells expressed EGFP (green) (Fig. 1). The control was \u003cem\u003eM. tuberculosis,\u003c/em\u003e which did not express any fluorescent protein. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. The CUBIC protocol enables the whole-lung imaging of intravenous and intranasal infection models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, we established experimental whole-lung imaging models of intravenous (i. v.) and intranasal (i. n.) infection. C57BL/6 mice were infected intravenously with 1.2 x 10\u003csup\u003e6\u0026nbsp;\u003c/sup\u003ecolony-forming units (CFU) or intranasally with 0.6 x 10\u003csup\u003e6\u0026nbsp;\u003c/sup\u003eCFU of DsRed-expressing BCG. Subsequently, we compared the mice treated with phosphate-buffered saline (PBS) using the same methods as those used for the experimental group in both cases. The day after infection, the lungs were excised, and we started clearing them according to the whole-lung clearing protocol (Fig. 2A). The excised lungs were fixed overnight in paraformaldehyde. After washing several times with PBS, the samples were kept at 4\u0026deg;C and further cleared using CUBIC-L for delipidation from day 7. After washing with PBS on day 12, the refractive index (RI) was adjusted using the CUBIC-R. After clearing the lungs, imaging was performed using a combination of LSFM and CLSM. It required 18 days to obtain images at this time; however, in the shortest time, it could be accomplished in 10\u0026ndash;14 days\u003csup\u003e[24]\u003c/sup\u003e. This means that we can obtain results faster from the imaging of CUBIC analysis than counting CFU after 3 weeks of incubation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFluorescence signals were successfully detected in the lungs of the mice, suggesting that CUBIC-infection analysis applies to fluorescent protein-expressing recombinant mycobacteria (Fig. 2B). Magnified 3D images of the lungs were obtained using CLSM (Fig. 2B, right panels). Notably, the 3D animations of the lung made it easier to observe the fluorescent bacteria in the lungs (Supplementary Video.S1). We also observed the following experiments using the same method.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e3. The CUBIC-Infection analysis applies to statistical spatiotemporal analysis during the initial steps of infectious disease progression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical spatiotemporal analysis of lung infections can be a powerful tool for infectious disease research. To visualize the time-dependent progression of TB, an experimental \u003cem\u003eM. tuberculosis-\u003c/em\u003einfected lung model was used in combination with CUBIC infection analysis. C57BL/6 mice were intranasally infected with 1.0 x 10\u003csup\u003e6\u0026nbsp;\u003c/sup\u003eCFU of DsRed-expressing \u003cem\u003eM. tuberculosis\u003c/em\u003e. We categorized the mice into two groups (n=4\u0026ndash;5/group at each time point); in the first group, fluorescent foci were detected by CUBIC-infection analysis (Fig. 3A), and in the second group, mice lungs were homogenized, and CFU was counted in each lung. The number and images of bacteria were confirmed on days 1, 14, and 28 post-infection.\u003c/p\u003e\n\u003cp\u003eOn the day after the infection, the bacteria were clearly visualized (Fig. 3A and Supplementary Video.S2). Numerous bacteria spread throughout the lung were drastically eliminated on day 14 post-infection, and the bacteria remaining in the lung appeared to aggregate (Fig. 3A). On day 28 post-infection, bacterial aggregation was more clearly observed (Fig. 3A and B), suggesting that aggregations likely reflected granuloma by the immune response of the host. In addition, we showed that the resolution of these 3D images was significantly high to discriminate between individual bacterial cells and was comparable to that of 2D hematoxylin and eosin (HE) slice images, which were obtained after CUBIC-infection analysis (Fig. 3A, right panels).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, we analyzed the number and location of bacteria in the lungs using the Imaris software (Fig. 3B). These points were used to plot the bacterial parts. It is possible to identify the location of this point on the x-, y-, and z-axes. Finally, we evaluated where the bacteria were most abundant in the lungs by calculating the median value for each of the x-, y-, and z-axes. It was estimated that most bacteria were located in or near the main bronchus on the day after infection.\u003c/p\u003e\n\u003cp\u003eWe investigated the relationship between CFU and the number of bacteria calculated using CUBIC analysis (Fig. 3C). The CFUs in the lungs decreased 2 weeks after infection and increased slightly 4 weeks after infection. By combining CFU and fluorescence-based foci number or volume data, it is possible to have a deeper discussion of the relationship between the number of bacteria and lesion development. When combined, CUBIC-infection analysis enabled statistical and spatiotemporal time-course analyses during the initial steps of infectious disease progression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. The CUBIC-infection analysis enables monitoring of the different patterns of mycobacterial infection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePathogenic mycobacteria induce the formation of complex cellular aggregates called granulomas, which are the hallmarks of mycobacterial infections\u003csup\u003e[27,28]\u003c/sup\u003e. This provides the Mycobacterium with a niche where it can survive and be protected from damage by the host\u0026apos;s immune response over long periods \u003csup\u003e[29]\u003c/sup\u003e. \u003cem\u003eM. avium\u003c/em\u003e is a causative pathogen of pulmonary NTM diseases. Similar to the more virulent \u003cem\u003eM. tuberculosis\u003c/em\u003e, \u003cem\u003eM. avium\u003c/em\u003e causes chronic infections in mice, with the development of tissue granulomas\u003csup\u003e[30,31]\u003c/sup\u003e. To observe the difference in bacterial aggregation between non-pathogenic and pathogenic mycobacteria, we compared the lungs after intranasal infection with the following three types of mycobacteria: BCG, \u003cem\u003eM. avium,\u003c/em\u003e and\u003cem\u003e\u0026nbsp;M. tuberculosis\u003c/em\u003e. C57BL/6 mice were intranasally infected with 1.0 x 10\u003csup\u003e6\u0026nbsp;\u003c/sup\u003eCFU of DsRed-expressing BCG and 3.0 x 10\u003csup\u003e5\u003c/sup\u003e CFU of GFP-expressing \u003cem\u003eM. avium\u003c/em\u003e. Similar to the experimental method, the imaging analysis of the infected lungs was confirmed on days 1, 14, and 28 after infection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn day 28 after infection, BCG appeared to be in individual bacterial forms, whereas \u003cem\u003eM. avium\u003c/em\u003e appeared to form small branching nodules gathering several bacteria (Fig. 4A). In \u003cem\u003eM. tuberculosis\u003c/em\u003e, individual bacteria could not be confirmed, and large aggregations of bacteria were observed. In the cross-sectional images, the differences in the aggregates of each Mycobacterium can be observed more clearly. These differences were comparable to the degree of inflammatory foci in HE-stained images. In addition, we found each Mycobacterium in Ziehl-Neelsen stained images, which were obtained after CUBIC-infection analysis. Next, we compared the volume distribution of bacterial aggregates for each Mycobacterium (Fig. 4B). Although the volume distribution of aggregates did not change significantly in the BCG, the volume distribution of \u003cem\u003eM. tuberculosis\u003c/em\u003e and \u003cem\u003eM. avium\u003c/em\u003e increased over time. Interestingly, we also observed differences in the sites of bacterial aggregation. The distribution of BCG and \u003cem\u003eM. avium\u003c/em\u003e was not biased in the lungs even on day 28 after infection; however, \u003cem\u003eM. tuberculosis\u0026nbsp;\u003c/em\u003etended to accumulate more in the upper lobe\u0026nbsp;(Fig. 4C). These results may be consistent with the clinical and radiographic diagnoses of pulmonary TB and NTM diseases\u003csup\u003e[13]\u003c/sup\u003e. Similar to\u003cem\u003e\u0026nbsp;M. tuberculosis\u003c/em\u003e, we investigated the relationship between CFU and the number and average volume of bacteria calculated using the CUBIC-infection analysis in BCG\u003cem\u003e\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;M. avium\u0026nbsp;\u003c/em\u003e(Fig. 4D).\u003c/p\u003e\n\u003cp\u003eTherefore, both the bacterial cell number and the volume of bacterial aggregation were almost comparable with CFU. These results suggest that each Mycobacterium has a different tendency to form bacterial aggregates, which may be related to granuloma formation. When combined, CUBIC-infection analysis enabled us to identify different patterns of each bacterial infection from the initial stage of infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e5. M. tuberculosis\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;infection in severely immunocompromised non-obese diabetic/severe combined immunodeficiency mice\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe tuberculous granuloma, which is a central feature of mycobacterial infection, is a hallmark of TB infection and disease\u003csup\u003e[29]\u003c/sup\u003e. These structures are formed by epithelioid macrophages surrounding a cellular necrotic region with a rim of T- and B-lymphocytes \u003csup\u003e[27-29]\u003c/sup\u003e. The non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mice were created by transferring a SCID mutation into a NOD mouse. The uniqueness of this mouse model is derived from the lack of function of B, T,\u0026nbsp;and NK cells\u003csup\u003e[32]\u003c/sup\u003e. Therefore, we used \u003cem\u003eM. tuberculosis\u003c/em\u003e infection in NOD-SCID mice to investigate the form of bacterial aggregation without an immune response by such lymphocytes. Five NOD/SCID mice were intranasally infected with 1.0 x 10\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eCFU of DsRed-expressing \u003cem\u003eM. tuberculosis\u003c/em\u003e. All NOD/SCID mice were sacrificed on day 98 after infection. In addition, four mouse lungs were homogenized for counting CFU, and one was analyzed using the CUBIC-infection analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe observed large bacterial aggregation in the NOD/SCID mouse lungs (Fig. 5A). Similar to C57BL/6 mice, it was suggested that the volume of bacterial aggregations in the lung would increase in NOD/SCID mice, in parallel with the CFU of the lung (Fig. 5B). This indicates that\u003cem\u003e\u0026nbsp;M. tuberculosis\u003c/em\u003e tends to aggregate, despite a lack of immune function related to T-, B-l, and NK-cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. The CUBIC-infection analysis enables the evaluation of the therapeutic effect of anti-TB drugs \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003eand visualizes lymphangiogenesis in \u003ci\u003eM. tuberculosis\u0026nbsp;\u003c/i\u003einfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGranuloma inflammation is a characteristic of many autoimmune and infectious diseases\u003csup\u003e[29]\u003c/sup\u003e. These granulomas are usually characterized by the concomitant development of hypoxia, which acts as a stimulus for vascularization\u003csup\u003e[33]\u003c/sup\u003e. Vascularization in animal models of TB is mediated by angiogenesis and lymphangiogenesis. Although the primary role of vascularization of granulomas could be to establish a pathway for immune cell transport within the structure, angiogenesis could also benefit \u003cem\u003eM. tuberculosis\u0026nbsp;\u003c/em\u003egrowth within the granuloma or its spread to distal sites\u003csup\u003e[29]\u003c/sup\u003e. Particularly, lymphangiogenesis stimulated by mycobacterial infection promotes systemic T-cell responses against \u003cem\u003eM. tuberculosis\u003c/em\u003e infection\u003csup\u003e[7]\u003c/sup\u003e. VEGF -C and VEGF-D are the main factors in lymphangiogenesis and signal through VEGF receptor 3 (VEGFR3)\u003csup\u003e[34]\u003c/sup\u003e. Systemic levels of VEGF-C have been reported to be higher in active pulmonary TB than in both latent TB and no TB infections \u003csup\u003e[35]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Here, we attempted to establish a therapeutic evaluation system for \u003cem\u003eM. tuberculosis\u003c/em\u003e infection in the lungs and examined the relationship between \u003cem\u003eM. tuberculosis\u0026nbsp;\u003c/em\u003einfection and lymphoid vessels by infection analysis. C57BL/6 mice were intranasally infected with \u003cem\u003eM. tuberculosis\u003c/em\u003e and treated with the anti-TB drugs INH and RIF to assess the chemotherapeutic response in the mouse lungs. We also treated \u003cem\u003eM. tuberculosis\u003c/em\u003e-infected mice with the VEGFR3 inhibitor MAZ51 (a receptor tyrosine kinase inhibitor\u003csup\u003e[36]\u003c/sup\u003e). Twenty-eight days after \u003cem\u003eM. tuberculosis\u003c/em\u003e infection, the proliferation of bacteria tended to be suppressed in the drug-treated groups (Fig. 6A and 6B). Notably, many foci were still detected on the bronchial wall in the drug treatment groups, which might have been dormant or resistant to anti-TB drugs (Fig. 6A). Although no significant difference was found in the CFU and total volume of bacterial aggregation, all drugs significantly reduced the number of foci calculated using CUBIC analysis (Fig. 6B). Particularly, 1 week of lymphangiogenesis-blocking treatment with MAZ51 resulted in a drastic reduction in bacteria.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, we examined the volume of lymphatic vessels in the lungs after infection in each group using the 3D immunohistochemical analysis. We used a VEGFR3 antibody to visualize lymphatic endothelial cells as previously reported\u003csup\u003e[24]\u003c/sup\u003e and measured VEGF-C concentrations in serum from mice 28 days after infection with \u003cem\u003eM. tuberculosis\u003c/em\u003e. Many lymphatic vessels were detected in the untreated group, where the accumulation of bacteria was high (Fig. 6C). In the treatment group, VEGFR3+Area per lung and VEGF-C concentration in the serum of mice tended to be suppressed (Fig. 6C and 6D). These data indicate that new lymphatic vessels play a crucial role in the growth of \u003cem\u003eM. tuberculosis\u003c/em\u003e in the early stages of infection. When combined, the CUBIC-infection analysis can be used to evaluate the in vivo effects of anti-TB agents.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eFluorescent proteins, bioluminescence, and reporter enzyme fluorescence have been employed for \u003cem\u003ein vivo\u003c/em\u003e imaging and successfully used for the real-time detection of \u003cem\u003eM. tuberculosis\u003c/em\u003e in live animals and cells \u003csup\u003e[17,37\u0026minus;39]\u003c/sup\u003e. These \u003cem\u003ein vivo\u003c/em\u003e imaging studies of fluorescent protein-expressing \u003cem\u003eM. tuberculosis\u003c/em\u003e reported the number of bacteria based on the intensity of the fluorescence signal. However, it has been challenging to specify bacteria at a single-cell resolution in the 3D structure of living animals. Additionally, host-immune interactions occur within various 3D tissues and can result in the formation of complex structures. However, visualizing these host\u0026ndash;microbe interactions in intact tissues remains difficult. Here, we demonstrate that recently developed CUBIC techniques enable high-resolution imaging of infection in the whole mouse lung tissue infected with mycobacteria. The novelty of this study lies in its innovative approach to visualizing bacterial reactions during infection. Using CUBIC-infection analysis, we observed immune-mediated elimination of bacteria and bacterial aggregation. CUBIC-infection analysis also enables statistical spatiotemporal analysis during the initial stages of infectious disease progression.\u003c/p\u003e \u003cp\u003eFurthermore, since lung clearing uses the whole lung sample, macroscopic analysis, such as shape, volume, and distribution of granuloma, can be performed simultaneously with microscopic analysis. We found that the basic tissue pathology was well preserved by HE staining, and we detected the bacteria in the CUBIC-treated samples using Ziehl\u0026ndash;Neelsen staining. These observations indicate that CUBIC-infection analysis could bridge the resolution gap between conventional \u003cem\u003ein vivo\u003c/em\u003e bioluminescence imaging and 2D histology. Therefore, in the future, it will be possible to further analyze the interaction between immune cells, such as macrophages and bacteria, three-dimensionally using immunohistochemical methods or genome-editing technology.\u003c/p\u003e \u003cp\u003eDrug-resistant TB is a public health concern worldwide. For decades, the number of patients infected with \u003cem\u003eM. tuberculosis\u003c/em\u003e who are resistant to the most effective drugs against TB has continued to increase\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Therefore, to prevent the increase in drug-resistant TB, it is necessary to properly use existing anti-TB drugs and discover new antimycobacterial agents effective against multidrug-resistant \u003cem\u003eM. tuberculosis\u003c/em\u003e. Our data showed that CUBIC-infection analysis could quantitatively evaluate the therapeutic effects of anti-TB drugs. In addition, we investigated the relationship between the lymphatic vessels in mouse lungs and bacteria using immunohistochemical techniques. Our data showed that lymphangiogenesis during infection was reduced by the inhibition of VEGFR3, and the growth of \u003cem\u003eM. tuberculosis\u003c/em\u003e can be suppressed by inhibiting lymphangiogenesis in the early stages of infection. Our data suggest that \u003cem\u003eM. tuberculosis\u003c/em\u003e induces lymphangiogenesis, which promotes mycobacterial growth and increases the spread of the infection to new tissue sites. This result is consistent with a previously reported model where mycobacterial-induced granulomas around lymphatic vessels in infected tissues resulted in VEGF-C-mediated lymphangiogenesis via vessel-expressed VEGFR3\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Anti-angiogenic therapies in combination with anti-TB drugs can enhance treatment in patients with TB\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e. Our CUBIC-infection analysis agreed with the effectiveness of anti-lymphangiogenic therapies as host-targeting TB therapy.\u003c/p\u003e \u003cp\u003eGenerally, TB has two clinical states: frequent long-term latency and active disease. Approximately one-quarter of the world\u0026rsquo;s human population is asymptomatically infected with \u003cem\u003eM. tuberculosis\u003c/em\u003e, a state known as latent TB infection (LTBI)\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. LTBI is a large source of the disease; generally, 5\u0026ndash;10% of patients with LTBI develop active TB during their lifetime\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. Therefore, identifying drug targets against the dormant state of \u003cem\u003eM. tuberculosis\u003c/em\u003e is critical to successfully eradicate TB. Our data showed that CUBIC-infection analysis could detect \u003cem\u003eM. tuberculosis\u003c/em\u003e bacilli, even after treatment with anti-TB drugs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). It may be directly visible that TB relapse after administration of the immunosuppressive drugs\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Therefore, CUBIC-infection analysis may be an effective tool for investigating the effects of new drugs that target LTBI.\u003c/p\u003e \u003cp\u003eEvaluation of 3D imaging of \u003cem\u003eM. tuberculosis\u003c/em\u003e-infected lungs using another tissue-clearing technique was reported in the past\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e; however, this is the first report of a model using CUBIC. Although conventional methods can also evaluate granuloma masses, capturing single bacterial cells in clear mouse lungs is difficult because of their low resolution. The high resolution of CUBIC enables the observation of bacteria at the single-cell level and the progression of infection over time. In addition, since the trachea and lymphatic vessels are clearly depicted, it is useful to investigate the relationship between the bacteria and host organs.\u003c/p\u003e \u003cp\u003eIn conclusion, we found that CUBIC-infection analysis can detect bacteria at a single-cell resolution in infected mouse lungs. This analysis can visualize the progression patterns for each bacterium and evaluate the effects of drugs. We suggest that CUBIC-infection analysis provides critical information for developing curative treatments for mycobacterial infections.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBacterial strains, culture media, and general reagents\u003c/h2\u003e \u003cp\u003eAll mycobacterial strains were grown in Middlebrook 7H9 broth (BD, Franklin Lakes, NJ, USA) supplemented with 0.2% (v/v) glycerol, 0.05% (v/v) Tween 80 (MP Biomedicals, Santa Ana, CA, USA), 10% ADC enrichment (5% bovine serum albumin [Wako Pure Chemical Industries, Osaka, Japan], 0.81% sodium chloride, and 2% D-glucose) (7H9-ADC broth) or on mycobacteria 7H10 agar (BD) supplemented with 0.5% (v/v) glycerol and 10% OADC enrichment (ADC enrichment supplemented with 0.06% [v/v] oleic acid) (7H10-OADC agar). In addition, appropriate antibiotics were added to the medium to maintain the specific genotypes of each strain. Hygromycin B, kanamycin, and RIF were purchased from Wako Pure Chemical Industries (Osaka, Japan). INH was purchased from Sigma\u0026ndash;Aldrich.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePlasmid Construction\u003c/h3\u003e\n\u003cp\u003eDr. Todd Primm (University of Sam Houston, State) kindly provided \u003cem\u003eM. avium\u003c/em\u003e 104 transformed with a plasmid encoding EGFP. In addition, the plasmid encoding DsRed was used as previously described. This plasmid was introduced into BCG and \u003cem\u003eM. tuberculosis\u003c/em\u003e by electroporation, and kanamycin-resistant BCG colonies were selected after 3 weeks of culture on Middlebrook 7H10-OADC agar in the presence of 20 \u0026micro;g/ml kanamycin. The expression of GFP and DsRed was confirmed using a BZ-X700 Series fluorescence microscope (Keyence, Osaka, Japan).\u003c/p\u003e\n\u003ch3\u003eFluorescence microscopic analysis\u003c/h3\u003e\n\u003cp\u003eThe harvested bacterial cells were treated with 10 \u0026micro;g/ml DAPI (Thermo Fisher Scientific) at room temperature for 20 min under protection from light. The stained cells were centrifuged at 6000 rpm for 5 min and mounted on a slide after treatment with 4% paraformaldehyde containing 10 \u0026micro;g/ml DAPI. The bacterial cells were visualized with an x100 oil immersion objective using an All-in-one BZ-X700 Series fluorescence microscope. Slides of triplicate cultures from numerous randomly selected microscopic fields were analyzed.\u003c/p\u003e\n\u003ch3\u003eMouse infections\u003c/h3\u003e\n\u003cp\u003eThis study was reported in accordance with ARRIVE guidelines (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://arriveguidelines.org).Th\u003c/span\u003e\u003cspan address=\"https://arriveguidelines.org).Th\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003ee Animal Care and Use Committee of the Graduate School of Medicine, University of Niigata, approved all experimental procedures and housing conditions. All animals were cared for and treated humanely, following the Institutional Guidelines for Experiments Using Animals. Female C57BL/6 mice, 7 weeks of age (Japan Clea, Suita, Osaka, Japan), were inoculated intravenously or intranasally with 0.6\u0026ndash;1.2 x 10\u003csup\u003e6\u003c/sup\u003e CFUs of DsRed-expressing BCG, \u003cem\u003eM. tuberculosis\u003c/em\u003e, and GFP-expressing \u003cem\u003eM. avium\u003c/em\u003e and assigned to groups (n\u0026thinsp;=\u0026thinsp;4\u0026ndash;5/group). On day 1 and 2 and 4 weeks of infection, the lungs of mice were removed aseptically and homogenized individually with 4.5 ml sterile distilled water. After a 10-fold serial dilution, a smear plate for each lung homogenate was prepared by spreading 0.1 ml of each diluted solution on a 7H10-OADC agar. Mycobacterial colonies were counted 3 weeks after culture. Anti-TB treatment was conducted with four mice per group, randomly selected, by administration of RIF (10 mg/kg) and INH (25 mg/kg), intragastrically 5 days per week for 7 days before harvest at 21 days post-infection. DsRed-expressing \u003cem\u003eM. tuberculosis\u003c/em\u003e-infected mice were treated with 10 mg/kg/day MAZ51 (EMD Millipore, Billerica, MA) in 50 \u0026micro;l of dimethyl sulfoxide for 7 days before harvest at 21 days post-infection. At each time point, a group of animals in each treatment category was necropsied, lungs were imaged, and homogenized for CFU determination.\u003c/p\u003e\n\u003ch3\u003eThe CUBIC protocol for whole-lung clearing\u003c/h3\u003e\n\u003cp\u003eTo prepare whole-organ clearing samples, female C57BL/6 mice were sacrificed under anesthesia with midazolam (4 mg/kg; Fuji Seiyaku, Toyama, Japan), medetomidine (0.75 mg/kg, Nihon Zenyaku, Fukushima, Japan), and butorphanol (5 mg/kg, Meiji Seika, Tokyo, Japan) tartrate (MMB) combination; subsequently, they perfused with 20 ml of PBS (pH 7.4) and 30 ml of 4% (w/v) Paraformaldehyde (PFA) (163-20145, FUJIFILM) in PBS via the left ventricle of the heart. The excised organs were post-fixed in 4% (w/v) PFA at 4\u0026deg;C for 24 hours. The specimens were washed with PBS three times for more than 2 hours to remove the PFA immediately before cleaning. The fixed organs were immersed in CUBIC-L with gentle shaking at 37\u0026deg;C for 5 days. CUBIC-L was exchanged on day 2. After decolorization and delipidation, the organs were washed three times with PBS at room temperature for more than 2 hours. The organs were further immersed in 50% (v/v) CUBIC-R (1:1 mixture of water and CUBIC-R) for more than 6 hours and then in CUBIC-R at room temperature with gentle shaking for at least 1 day.\u003c/p\u003e\n\u003ch3\u003e3D immunostaining of CUBIC samples\u003c/h3\u003e\n\u003cp\u003eAfter decolorization and delipidation, organ samples were subjected to immunostaining with 1:100 diluted antibodies in a staining buffer composed of 0.5% (v/v) Triton X-100, 0.25% casein (37528, Thermo Fisher Scientific, Waltham, MA) and 0.01% sodium azide (195-11092, WAKO, Osaka, Japan) for 3 days at room temperature with shaking. The stained samples were washed three times with PBS at room temperature with rotation; subsequently, they were immersed in CUBIC-R. The following antibodies were used for staining: Mouse VEGFR3/Flt4 antibody (AF743, R\u0026amp;D Systems, Minneapolis, MN, USA) and donkey anti-goat immunoglobulin G (H\u0026thinsp;+\u0026thinsp;L) Cross-Adsorbed Secondary Antibody, Alexa Fluor 647 (A-21447, Thermo Fisher Scientific, Waltham, MA).\u003c/p\u003e\n\u003ch3\u003eMicroscopy\u003c/h3\u003e\n\u003cp\u003eWhole-organ images were acquired using custom-built LSFM (Olympus, Tokyo, Japan). Images were captured using a 0.63 \u0026times; objective lens (numerical aperture\u0026thinsp;=\u0026thinsp;0.15, working distance\u0026thinsp;=\u0026thinsp;87 mm) with a digital zoom from 1 \u0026times; to 1.25 \u0026times; zoom. Lasers of 488 nm and 532 nm were used for image acquisition. The stage was moved moth in the lateral and axial directions to cover the whole organ. When the stage was moved in the axial direction, the detection objective lens was synchronically moved to the axial direction to avoid defocusing. Furthermore, high-resolution images for cell profiling were acquired using CLSM (FLUOVIEW FV1200, Olympus). Images were captured using a 25 \u0026times; objective lens (numerical aperture\u0026thinsp;=\u0026thinsp;1.0, working distance\u0026thinsp;=\u0026thinsp;8.0 mm) with a digital zoom from 1 \u0026times; to 2 \u0026times; zoom. Lasers of 488 nm and 532 nm were used for image acquisition. Refractive index (RI) matched sample was immersed in a mixture of silicon oil HIVAC-F4 (RI\u0026thinsp;=\u0026thinsp;1.555, Shin-Etsu Chemical Co., Ltd., Tokyo, Japan) and mineral oil (RI\u0026thinsp;=\u0026thinsp;1.467, M8410, Sigma\u0026ndash;Aldrich) during image acquisition. 3D-rendered images were visualized, captured, and analyzed using the Imaris software (version 7.7.1 and 8.1.2, Bitplane AG, Zurich, Switzerland).\u003c/p\u003e\n\u003ch3\u003eImage data processing and analysis\u003c/h3\u003e\n\u003cp\u003eAll raw image data were collected in lossless 16-bit Tagged Image File Format. 3D-rendered images were visualized and captured using the Imaris software (version 7.6.4, 7.7.1, and 8.1.2, Bitplane). The brightness, contrast, and gamma of the 3D-rendered images were manually adjusted using the software when visualized. Subsequently, the 3D images were used for image analysis using the Imaris software. For the quantification of infections, an appropriate threshold of signals from reporter proteins was selected in each experiment, and surface analysis was performed using the Imaris software. An appropriate threshold of signals was selected in each experiment, and spot analysis was performed using the Imaris software to count the cell number.\u003c/p\u003e\n\u003ch3\u003eHistological Examination\u003c/h3\u003e\n\u003cp\u003eAfter CUBIC analysis, the entire lung was washed with PBS and resected. As previously described, the samples were embedded in paraffin and subjected to HE and Ziehl\u0026ndash;Neelsen staining.\u003c/p\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eThe significance of the results was determined using the Student\u0026rsquo;s t-test or analysis of variance, as appropriate. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. In the figures, *represents \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** represents \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and *** represents \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study\u0026rsquo;s findings are available in the article and its supplementary material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to Dr. Takahiro Hakamata, Ms. Yuko Kobayashi, Haruka Kobayashi, Sara Matsumoto, and Satoko Matsumoto for their assistance and encouragement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science to Mariko Hakamata and Sohkichi Matsumoto (21KK0136), AMED-CREST (22gm1610009h0001), and the Research Program on Emerging and Re-emerging Infectious Diseases from AMED to Akihito Nishiyama (19fk0108090), and Sohkichi Matsumoto (21fk0108497s0101). This study was also supported by the United States\u0026ndash;Japan Cooperative Medical Science Program against Tuberculosis and Leprosy. The funders had no role in the study design, data collection and interpretation, or decision to submit the work for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.H., A.N., K.T., and S.M. conceived the project and designed the study. M.H., E.I., A.Y., S.K., G.G., and T.Y. performed experiments. M.H., A.N., G.G., and S.M. wrote the main manuscript text. H.M., Y.O., Y.T., R.O., T.P., T.K., K.T., and S.M. supervised all aspect of the project. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. 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They include various species, such as \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003e(\u003cem\u003eM. tuberculosis\u003c/em\u003e), which is an intracellular parasite of mammals, and the most virulent and non-tuberculous mycobacteria (NTM), namely, \u003cem\u003eM. avium\u003c/em\u003e, which are environmental bacteria causing intractable NTM diseases. An infection model of transparent zebrafish and fish-infectious \u003cem\u003eM. marinum\u003c/em\u003e was established to better understand the \u003cem\u003ein vivo \u003c/em\u003ebehavior of mycobacteria under the pressure of host immune responses. However, the fish model does not fully replicate mammalian immunity. Here, we demonstrate that a clear, unobstructed brain/body imaging cocktail and computational analysis (CUBIC)-based infection (CUBIC-infection) analysis enables comprehensive mycobacterial profiling of the whole lung. We assessed the \u003cem\u003ein vivo\u003c/em\u003e kinetics of mycobacterial infection along with fluorescent protein-expressing recombinant mycobacteria. We detected \u003cem\u003emycobacterium\u003c/em\u003e at a single bacterial level and counted bacterial numbers, which was comparable to the colony-forming units of organ homogenates. CUBIC-infection analysis distinguished \u003cem\u003ein vivo\u003c/em\u003e spatiotemporal behavior of \u003cem\u003eM. tuberculosis\u003c/em\u003e, \u003cem\u003eM. tuberculosis\u003c/em\u003evariant Bacillus Calmette-Guerin, and \u003cem\u003eM. avium\u003c/em\u003e in mice. Furthermore, it monitored spatiotemporal information on the therapeutic efficacies of anti-tuberculosis drugs and an anti-lymphangiogenesis agent. Our data suggest that CUBIC-infection analysis is a powerful tool for understanding mycobacterial infections in mammals and developing therapeutic agents.\u003c/p\u003e","manuscriptTitle":"Three-dimensional in vivo monitoring of mycobacterial infections and therapeutic efficacy based on tissue-clearing technology CUBIC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-02-09 16:38:01","doi":"10.21203/rs.3.rs-2537112/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"227c42b3-14bd-4eb3-8b7e-e606ef8a16e5","owner":[],"postedDate":"February 9th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":19048500,"name":"Biological sciences/Microbiology"},{"id":19048501,"name":"Biological sciences/Microbiology/Bacteriology"}],"tags":[],"updatedAt":"2023-02-27T06:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2023-02-09 16:38:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2537112","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2537112","identity":"rs-2537112","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}