Noninvasive PET tracking of post-transplant gut microbiota in living mice

Purpose The role that gut microbiota plays in determining the efficacy of the anti-tumor effect of immune checkpoint inhibitors is gaining increasing attention, and fecal bacterial transplantation has been recognized as a promising strategy for improving or rescuing the effect of immune checkpoint inhibition. However, techniques for the precise monitoring of in vivo bacterial behaviors after transplantation are limited. In this study, we aimed to use metabolic labeling and subsequent positron emission tomography (PET) imaging to track the in vivo behaviors of gut bacteria that are responsible for the efficacy of anti-PD-1 therapy in living mice. Methods The antitumor effect of anti-PD-1 blockade was tested in a low-response 4T1 syngeneic mouse model with or without fecal transplantation and with or without broad-spectrum antibiotic imipenem treatment. High-throughput sequencing analyses of 16S rRNA gene amplicons in feces of 4T1 tumor-bearing mice pre- and post-anti-PD-1 treatment were performed. The identified bacteria, Bacteroides fragilis ( B. fragilis ), were labeled with 64 Cu and fluorescence dye by the metabolic labeling of N 3 followed by click chemistry. In vivo PET and optical imaging of B. fragilis were performed in mice after oral gavage. Results The disturbance of gut microbiota reduced the efficacy of anti-PD-1 treatment, and the combination of B. fragilis gavage and PD-1 blockade was beneficial in rescuing the antitumor effect of anti-PD-1 therapy. Metabolic oligosaccharide engineering and biorthogonal click chemistry resulted in successful B. fragilis labeling with 64 Cu and fluorescence dye with high in vitro and in vivo stability and no effect on viability. PET imaging successfully detected the in vivo behaviors of B. fragilis after transplantation. Conclusion PET tracking by metabolic labeling is a powerful, noninvasive tool for the real-time tracking and quantitative imaging of gut microbiota. This strategy is clinically translatable and may also be extended to the PET tracking of other functional cells to guide cell-based adoptive therapies.

[1]  F. Marincola,et al.  Commensal Bacteria Control Cancer Response to Therapy by Modulating the Tumor Microenvironment , 2013, Science.

[2]  Carolyn R Bertozzi,et al.  Bioorthogonal chemistry: fishing for selectivity in a sea of functionality. , 2009, Angewandte Chemie.

[3]  P. Langella,et al.  Lactobacillus casei BL23 regulates Treg and Th17 T-cell populations and reduces DMH-associated colorectal cancer , 2016, Journal of Gastroenterology.

[4]  Sanjiv S Gambhir,et al.  Molecular imaging techniques in body imaging. , 2007, Radiology.

[5]  Nicola C. Reading,et al.  In vivo imaging and tracking of host–microbiota interactions via metabolic labeling of gut anaerobic bacteria , 2015, Nature Medicine.

[6]  E. Warren,et al.  Analysis of transgene-specific immune responses that limit the in vivo persistence of adoptively transferred HSV-TK-modified donor T cells after allogeneic hematopoietic cell transplantation. , 2006, Blood.

[7]  Yuntao Zhu,et al.  Selective Imaging of Gram-Negative and Gram-Positive Microbiotas in the Mouse Gut. , 2017, Biochemistry.

[8]  H. Akaza,et al.  Preventive effect of a Lactobacillus casei preparation on the recurrence of superficial bladder cancer in a double-blind trial. The BLP Study Group. , 1995, European urology.

[9]  R. Weissleder Scaling down imaging: molecular mapping of cancer in mice , 2002, Nature Reviews Cancer.

[10]  Y. Aso,et al.  Prophylactic effect of a Lactobacillus casei preparation on the recurrence of superficial bladder cancer. BLP Study Group. , 1992, Urologia internationalis.

[11]  Ross A Soo,et al.  De-novo and acquired resistance to immune checkpoint targeting. , 2017, The Lancet. Oncology.

[12]  Jason B. Williams,et al.  Commensal Bifidobacterium promotes antitumor immunity and facilitates anti–PD-L1 efficacy , 2015, Science.

[13]  Jennifer A. Prescher,et al.  Chemistry in living systems , 2005, Nature chemical biology.

[14]  Christopher H. Contag,et al.  In vivo imaging using bioluminescence: a tool for probing graft-versus-host disease , 2006, Nature Reviews Immunology.

[15]  Steven A. Rosenberg,et al.  Raising the Bar: The Curative Potential of Human Cancer Immunotherapy , 2012, Science Translational Medicine.

[16]  G. Ren,et al.  Imaging of activated T cells as an early predictor of immune response to anti-PD-1 therapy. , 2019, Cancer research.

[17]  K. Yarema,et al.  Metabolic oligosaccharide engineering: perspectives, applications, and future directions. , 2007, Molecular bioSystems.

[18]  M. Atkins,et al.  Predictive biomarkers for checkpoint inhibitor-based immunotherapy. , 2016, The Lancet. Oncology.

[19]  George Sgouros,et al.  Imaging, Biodistribution, and Dosimetry of Radionuclide-Labeled PD-L1 Antibody in an Immunocompetent Mouse Model of Breast Cancer. , 2016, Cancer research.

[20]  E. Le Chatelier,et al.  Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients , 2018, Science.

[21]  M. Pomper,et al.  Imaging Enterobacteriaceae infection in vivo with 18F-fluorodeoxysorbitol positron emission tomography , 2014, Science Translational Medicine.

[22]  I. Durán,et al.  Biomarkers of response to PD-1/PD-L1 inhibition. , 2017, Critical reviews in oncology/hematology.

[23]  F. Hodi,et al.  Monitoring immune-checkpoint blockade: response evaluation and biomarker development , 2017, Nature Reviews Clinical Oncology.

[24]  R. Weissleder Molecular imaging: exploring the next frontier. , 1999, Radiology.

[25]  Laurence Zitvogel,et al.  Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors , 2018, Science.

[26]  W. Oyen,et al.  Noninvasive Imaging of Tumor PD-L1 Expression Using Radiolabeled Anti-PD-L1 Antibodies. , 2015, Cancer research.

[27]  Fan Wang,et al.  A near-infrared phthalocyanine dye-labeled agent for integrin αvβ6-targeted theranostics of pancreatic cancer. , 2015, Biomaterials.

[28]  F. Ginhoux,et al.  Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota , 2015, Science.

[29]  I. Mellman,et al.  Oncology meets immunology: the cancer-immunity cycle. , 2013, Immunity.

[30]  Gianni Panagiotou,et al.  Probiotics modulated gut microbiota suppresses hepatocellular carcinoma growth in mice , 2016, Proceedings of the National Academy of Sciences.

[31]  Hannah M. Wexler,et al.  Bacteroides: the Good, the Bad, and the Nitty-Gritty , 2007, Clinical Microbiology Reviews.