Targeting mTOR in myeloid cells prevents infection-associated inflammation

doi:10.1016/j.isci.2025.112163

. 2025 Mar 4;28(4):112163.

doi: 10.1016/j.isci.2025.112163. eCollection 2025 Apr 18.

Targeting mTOR in myeloid cells prevents infection-associated inflammation

Yohana C Toner^{1

2

3}, Jazz Munitz^{1

2

4}, Geoffrey Prevot^{1

2

4}, Judit Morla-Folch^{1

2

4}, William Wang^{1

2

4}, Yuri van Elsas^{1

2

3}, Bram Priem^{1

2

3}, Jeroen Deckers^{1

2

3}, Tom Anbergen^{1

2

3}, Thijs J Beldman³, Eliane E S Brechbühl^{1

2

5}, Muhammed D Aksu³, Athanasios Ziogas³, Sebastian A Sarlea³, Mumin Ozturk^{3

6}, Zhenhua Zhang^{7

8}, Wenchao Li^{7

8}, Yang Li^{3

7

8}, Alexander Maier^{1

2

9}, Jessica C Fernandes^{1

2

4}, Glenn A O Cremers¹⁰, Bas van Genabeek^{10

11}, Joost H C M Kreijtz¹⁰, Esther Lutgens¹², Niels P Riksen³, Henk M Janssen¹¹, Serge H M Söntjens¹¹, Freek J M Hoeben¹¹, Ewelina Kluza¹³, Gagandeep Singh^{14

15}, Evangelos J Giamarellos-Bourboulis¹⁶, Michael Schotsaert^{14

15

17

18}, Raphaël Duivenvoorden^{1

3

19}, Roy van der Meel¹³, Leo A B Joosten^{3

20}, Lei Cai²¹, Ryan E Temel²¹, Zahi A Fayad^{1

2}, Musa M Mhlanga^{6

22}, Mandy M T van Leent^{1

2

4}, Abraham J P Teunissen^{1

2

4

18}, Mihai G Netea^{3

23}, Willem J M Mulder^{1

2

3

13}

Affiliations

¹ BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
² Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
³ Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
⁴ Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁵ Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
⁶ Epigenomics & Single Cell Biophysics Group, Department of Cell Biology, FNWI, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University, 6525 GA Nijmegen, the Netherlands.
⁷ Department of Computational Biology of Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, 30625 Hannover, Germany.
⁸ TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, 30625 Hannover, Germany.
⁹ Department of Cardiology and Angiology, Heart Center Freiburg University, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany.
¹⁰ Trained Therapeutix Discovery, 5349 AB Oss, the Netherlands.
¹¹ SyMO-Chem B.V., 5612 AZ Eindhoven, the Netherlands.
¹² Department of Cardiovascular Medicine, Experimental Cardiovascular Immunology Laboratory, Mayo Clinic, Rochester, MN 55905, USA.
¹³ Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, the Netherlands.
¹⁴ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁵ Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁶ 4 Department of Internal Medicine, National and Kapodistrian University of Athens, 124 62 Athens, Greece.
¹⁷ Marc and Jennifer Lipschultz Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁸ Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁹ Department of Nephrology, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
²⁰ Department of Medical Genetics, Iuliu Hatieganu University of Medicine and Pharmacy, 400 349 Cluj-Napoca, Romania.
²¹ Department of Physiology, Saha Cardiovascular Research Center, University of Kentucky, Lexington, KY 40536, USA.
²² Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
²³ Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany.

PMID: 40177636
PMCID: PMC11964677
DOI: 10.1016/j.isci.2025.112163

Targeting mTOR in myeloid cells prevents infection-associated inflammation

Yohana C Toner et al. iScience. 2025.

. 2025 Mar 4;28(4):112163.

doi: 10.1016/j.isci.2025.112163. eCollection 2025 Apr 18.

Authors

Affiliations

¹ BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
² Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
³ Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
⁴ Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁵ Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
⁶ Epigenomics & Single Cell Biophysics Group, Department of Cell Biology, FNWI, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University, 6525 GA Nijmegen, the Netherlands.
⁷ Department of Computational Biology of Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, 30625 Hannover, Germany.
⁸ TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, 30625 Hannover, Germany.
⁹ Department of Cardiology and Angiology, Heart Center Freiburg University, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany.
¹⁰ Trained Therapeutix Discovery, 5349 AB Oss, the Netherlands.
¹¹ SyMO-Chem B.V., 5612 AZ Eindhoven, the Netherlands.
¹² Department of Cardiovascular Medicine, Experimental Cardiovascular Immunology Laboratory, Mayo Clinic, Rochester, MN 55905, USA.
¹³ Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, the Netherlands.
¹⁴ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁵ Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁶ 4 Department of Internal Medicine, National and Kapodistrian University of Athens, 124 62 Athens, Greece.
¹⁷ Marc and Jennifer Lipschultz Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁸ Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹⁹ Department of Nephrology, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
²⁰ Department of Medical Genetics, Iuliu Hatieganu University of Medicine and Pharmacy, 400 349 Cluj-Napoca, Romania.
²¹ Department of Physiology, Saha Cardiovascular Research Center, University of Kentucky, Lexington, KY 40536, USA.
²² Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
²³ Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany.

PMID: 40177636
PMCID: PMC11964677
DOI: 10.1016/j.isci.2025.112163

Abstract

Infections, cancer, and trauma can cause life-threatening hyperinflammation. In the present study, using single-cell RNA sequencing of circulating immune cells, we found that the mammalian target of rapamycin (mTOR) pathway plays a critical role in myeloid cell regulation in COVID-19 patients. Previously, we developed an mTOR-inhibiting nanobiologic (mTORi-nanobiologic) that efficiently targets myeloid cells and their progenitors in the bone marrow. In vitro, we demonstrated that mTORi-nanobiologics potently inhibit infection-associated inflammation in human primary immune cells. Next, we investigated the in vivo effect of mTORi-nanobiologics in mouse models of hyperinflammation and acute respiratory distress syndrome. Using ¹⁸F-FDG uptake and flow cytometry readouts, we found mTORi-nanobiologic therapy to efficiently reduce hematopoietic organ metabolic activity and inflammation to levels comparable to those of healthy control animals. Together, we show that regulating myelopoiesis with mTORi-nanobiologics is a compelling therapeutic strategy to prevent deleterious organ inflammation in infection-related complications.

Keywords: Biochemistry; Biological sciences; Immunology; Natural sciences.

PubMed Disclaimer

Conflict of interest statement

W.J.M.M., L.A.B.J, M.N., and Z.A.F. are founders of Trained Therapeutix Discovery (TTxD). W.J.M.M is also a shareholder and CSO at the company. W.J.M.M. is founder, CTO and shareholder of BioTrip. Z.A.F. and W.J.M.M. are members of the board of TTxD. J.H.C.M.K., B.v.G., G.A.O.C., and T.J.B. are employees at TTxD. H.M.J. is a director at SyMO-Chem. S.H.M.S. and F.J.M.H. are employees at SyMO-Chem. M.S. has received unrelated research support from ArgenX N.V., Moderna, 7Hills, and Phio Pharmaceuticals. E.J.G.-B. has received honoraria from Abbott Products Operations, bioMérieux, GSK, UCB, Sobi AB and ThermoFisher Brahms GmbH, independent educational grants from Abbott Products Operations, AbbVie, bioMérieux Inc, Johnson & Johnson, InCyte, MSD, Novartis, UCB, Sanofi, and Sobi. M.M.M. is the scientific founder of Lemba Therapeutics. No other potential conflicts of interest relevant to this article exist.

Figures

**Figure 1**
mTOR signaling pathway gene expression profiles support the use of mTORi-nanobiologics for the treatment of inflammation in COVID-19 patients (A) UMAP of scRNA-seq from the Berlin (C1), Bonn (C2), and MHH50 (C3) cohorts datasets, respectively, and UMAP of scRNA-seq from convalescent COVID-19 patients (C4). (B) Upregulated differentially expressed genes across the Berlin (C1), Bonn (C2), and MHH50 (C3) datasets. Intersection size represents the number of genes that were differentially expressed across the different comparisons, connected by dots, in the y axis. Set size represents the number of genes that were differentially expressed within each comparison on the y axis. (C) The number of upregulated mTOR genes in specific cell types in convalescent COVID-19 patients (C4 cohort). Intersection size represents the number of genes that were differentially expressed across different cell types, connected by dots, in the y axis. Set size represents the number of genes that were differentially expressed within each cell type on the y axis. Differentially expressed genes between every two disease conditions were identified using FindMarkers() function by Wilcoxon rank-sum test. Control = healthy volunteers, pDCs = plasmacytoid dendritic cells, mDCs = myeloid dendritic cells. See also Figures S1 and S2 and Tables S1 and S2.

**Figure 2**
Bone marrow-avid mTORi-nanobiologics characterization (A) Study concept overview. Nanobiologics are lipoprotein-based nanoparticles with high avidity for myeloid cells and their progenitors in the bone marrow. We have loaded nanobiologics with a lipophilic prodrug of rapamycin, which is a potent mTOR inhibitor. These mTOR-inhibiting nanobiologics (mTORi-nanobiologics) dampen bone marrow activation and reduce systemic hyperinflammation upon infection. (B) mTORi-nanobiologic’s characterization by dynamic light scattering and (C) cryo-EM. Scale bar, 50 nm.

**Figure 3**
mTORi-nanobiologics reduces inflammatory response in human monocytes *in vitro* (A) Schematic representation of trained immunity assays, employed on primary monocytes derived from healthy donors. (B) *In vitro* trained immunity assay showing TNF-α production upon LPS restimulation. (C) *In vitro* trained immunity assay showing IL-6 production upon LPS restimulation. Data in (B) and (C) are presented as mean ± SEM. Statistical analysis was performed using the Wilcoxon signed-rank test. ∗p < 0.05. See also Figure S3 and Table S3.

**Figure 4**
mTORi-nanobiologics reduce systemic inflammation (A) Schematic overview of the LPS-induced hyperinflammation mouse model. (B) Representative fused ¹⁸F-FDG PET/CT images of the spine of placebo (left panel) and mTORi-nanobiologics-treated (right panel) animals. (C) *Ex vivo* quantification of bone marrow ¹⁸F-FDG uptake (n = 7–11). (D) Representative flow cytometry plots showing Ly6C^hi monocytes in the bone marrow of control naive mice (negative control), mice with hyperinflammation (placebo control), and hyperinflammation mice treated with mTORi-nanobiologics, gated on live CD45⁺CD11b⁺lin⁻CD11c⁻ cells (left panel) and the associated quantification of bone marrow Ly-6C^hi monocytes (right panel, n = 6). (E) Representative flow cytometry plots showing neutrophils in the bone marrow of control naive mice (negative control), untreated hyperinflammation mice (placebo control), and hyperinflammation mice treated with mTORi-nanobiologics, gated on live CD45⁺ cells (left panel). The associated quantification of bone marrow neutrophils is also shown (right panel, n = 6). HI = hyperinflammation, hyperinflammation = placebo control, SUV = standardized uptake value. Data in (C)–(E) are plotted as mean ± SD. Statistical analyses were performed using the Shapiro-Wilk test, followed by one-way ANOVA (with Tukey’s multiple comparisons test) or Kruskal-Wallis (followed by Dunn’s multiple comparison test) according to Gaussian distribution. ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. See also Figure S4.

**Figure 5**
mTORi-nanobiologics reduce inflammation in ARDS mouse model (A) Schematic overview of the LPS-induced ARDS mouse model. (B) Representative fused ¹⁸F-FDG PET/CT images of the lungs of untreated (placebo control, left panel) and mTORi-nanobiologics-treated (right panel) animals. (C) *Ex vivo* quantification of bone marrow ¹⁸F-FDG uptake (n = 6–11). (D) *Ex vivo* quantification of ¹⁸F-FDG lung uptake (n = 4–9). (E) Representative flow cytometry plots showing Ly6C^hi monocytes in the bone marrow of control naive mice (negative control), untreated ARDS mice (placebo control), and ARDS mice treated with mTORi-nanobiologics, gated on live CD45⁺CD11b⁺lin⁻CD11c⁻ cells (left panel) and the associated quantification of bone marrow Ly-6C^hi monocytes (right panel, n = 6). (F) Representative flow cytometry plots showing neutrophils in the bone marrow of control naive mice (negative control), untreated ARDS mice (placebo control), and ARDS mice treated with mTORi-nanobiologics, gated on live CD45⁺ cells (left panel). The associated quantification of bone marrow neutrophils is also shown (right panel, n = 6). (G) Representative flow cytometry plots showing Ly6C^hi monocytes in the lungs of naive mice (negative control), untreated ARDS mice (placebo control), and ARDS mice treated with mTORi-nanobiologics, gated on live CD45⁺CD11b⁺lin⁻CD11c⁻ cells (left panel) and the associated quantification of lung Ly-6C^hi monocytes are also shown (right panel, n = 6). (H) Representative flow cytometry plots showing neutrophils in the lungs of control naive mice (negative control), untreated ARDS mice (placebo control), and ARDS mice treated with mTORi-nanobiologics, gated on live CD45⁺ cells (left panel). The associated quantification of lung neutrophils is also shown (right panel, n = 6). ARDS = placebo control, SUV = standardized uptake value. Data in (C)–(H) are plotted as mean ± SD. Statistical analyses were performed using the Shapiro-Wilk test, followed by one-way ANOVA (with Tukey’s multiple comparisons test) or Kruskal-Wallis (followed by Dunn’s multiple comparison test) according to Gaussian distribution. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. See also Figure S5.

See this image and copyright information in PMC

References

1. Fajgenbaum D.C., June C.H. Cytokine Storm. N. Engl. J. Med. 2020;383:2255–2273. doi: 10.1056/NEJMra2026131. - DOI - PMC - PubMed
1. Ikuta K.S., Swetschinski L.R., Robles Aguilar G., Sharara F., Mestrovic T., Gray A.P., Davis Weaver N., Wool E.E., Han C., Gershberg Hayoon A., et al. Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2022;400:2221–2248. doi: 10.1016/S0140-6736(22)02185-7. - DOI - PMC - PubMed
1. Behrens E.M., Koretzky G.A. Review: Cytokine Storm Syndrome: Looking Toward the Precision Medicine Era. Arthritis Rheumatol. 2017;69:1135–1143. doi: 10.1002/art.40071. - DOI - PubMed
1. Bos L.D.J., Ware L.B. Acute respiratory distress syndrome: causes, pathophysiology, and phenotypes. Lancet. 2022;400:1145–1156. doi: 10.1016/S0140-6736(22)01485-4. - DOI - PubMed
1. Han S., Mallampalli R.K. The acute respiratory distress syndrome: from mechanism to translation. J. Immunol. 2015;194:855–860. doi: 10.4049/jimmunol.1402513. - DOI - PMC - PubMed

LinkOut - more resources

Full Text Sources
- Elsevier Science
- PubMed Central
Miscellaneous
- NCI CPTAC Assay Portal

[1] Fajgenbaum D.C., June C.H. Cytokine Storm. N. Engl. J. Med. 2020;383:2255–2273. doi: 10.1056/NEJMra2026131. - DOI - PMC - PubMed

[2] Fajgenbaum D.C., June C.H. Cytokine Storm. N. Engl. J. Med. 2020;383:2255–2273. doi: 10.1056/NEJMra2026131. - DOI - PMC - PubMed

[3] Ikuta K.S., Swetschinski L.R., Robles Aguilar G., Sharara F., Mestrovic T., Gray A.P., Davis Weaver N., Wool E.E., Han C., Gershberg Hayoon A., et al. Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2022;400:2221–2248. doi: 10.1016/S0140-6736(22)02185-7. - DOI - PMC - PubMed

[4] Ikuta K.S., Swetschinski L.R., Robles Aguilar G., Sharara F., Mestrovic T., Gray A.P., Davis Weaver N., Wool E.E., Han C., Gershberg Hayoon A., et al. Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2022;400:2221–2248. doi: 10.1016/S0140-6736(22)02185-7. - DOI - PMC - PubMed

[5] Behrens E.M., Koretzky G.A. Review: Cytokine Storm Syndrome: Looking Toward the Precision Medicine Era. Arthritis Rheumatol. 2017;69:1135–1143. doi: 10.1002/art.40071. - DOI - PubMed

[6] Behrens E.M., Koretzky G.A. Review: Cytokine Storm Syndrome: Looking Toward the Precision Medicine Era. Arthritis Rheumatol. 2017;69:1135–1143. doi: 10.1002/art.40071. - DOI - PubMed

[7] Bos L.D.J., Ware L.B. Acute respiratory distress syndrome: causes, pathophysiology, and phenotypes. Lancet. 2022;400:1145–1156. doi: 10.1016/S0140-6736(22)01485-4. - DOI - PubMed

[8] Bos L.D.J., Ware L.B. Acute respiratory distress syndrome: causes, pathophysiology, and phenotypes. Lancet. 2022;400:1145–1156. doi: 10.1016/S0140-6736(22)01485-4. - DOI - PubMed

[9] Han S., Mallampalli R.K. The acute respiratory distress syndrome: from mechanism to translation. J. Immunol. 2015;194:855–860. doi: 10.4049/jimmunol.1402513. - DOI - PMC - PubMed

[10] Han S., Mallampalli R.K. The acute respiratory distress syndrome: from mechanism to translation. J. Immunol. 2015;194:855–860. doi: 10.4049/jimmunol.1402513. - DOI - PMC - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Targeting mTOR in myeloid cells prevents infection-associated inflammation

Affiliations

Targeting mTOR in myeloid cells prevents infection-associated inflammation

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Similar articles

References

LinkOut - more resources

Full Text Sources

Miscellaneous

Abstract

Conflict of interest statement

Figures

Similar articles

References

Related information

LinkOut - more resources

Full Text Sources

Miscellaneous