Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Engineered serum markers for non-invasive monitoring of gene expression in the brain

Nature Biotechnology (2024)Cite this article

Subjects

Abstract

Measurement of gene expression in the brain requires invasive analysis of brain tissue or non-invasive methods that are limited by low sensitivity. Here we introduce a method for non-invasive, multiplexed, site-specific monitoring of endogenous gene or transgene expression in the brain through engineered reporters called released markers of activity (RMAs). RMAs consist of an easily detectable reporter and a receptor-binding domain that enables transcytosis across the brain endothelium. RMAs are expressed in the brain but exit into the blood, where they can be easily measured. We show that expressing RMAs at a single mouse brain site representing approximately 1% of the brain volume provides up to a 100,000-fold signal increase over the baseline. Expression of RMAs in tens to hundreds of neurons is sufficient for their reliable detection. We demonstrate that chemogenetic activation of cells expressing Fos-responsive RMA increases serum RMA levels >6-fold compared to non-activated controls. RMAs provide a non-invasive method for repeatable, multiplexed monitoring of gene expression in the intact animal brain.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Non-invasive monitoring of gene expression in the brain with RMAs.
Fig. 2: RMA reporters translocate from the brain into the bloodstream.
Fig. 3: Gluc-RMA detects gene expression at multiple local brain regions.
Fig. 4: Detecting gene expression of specific brain cell types with high sensitivity using Gluc-RMA.
Fig. 5: Gluc-RMA detects neuronal activity in vivo.
Fig. 6: Gluc-RMA enhances BLI.

Similar content being viewed by others

Data availability

The authors declare that all data supporting the results in this study are available within the paper, its Supplementary Information and its Source Data file. Microscopy images are available from the corresponding author upon reasonable request owing to their large size and number. The plasmids designed in this study are available on Addgene (https://www.addgene.org/browse/article/28229133/). Source data are provided with this paper.

References

  1. Richiardi, J. et al. Correlated gene expression supports synchronous activity in brain networks. Science 348, 1241–1244 (2015).

    CAS  PubMed Central  Google Scholar 

  2. Minatohara, K., Akiyoshi, M. & Okuno, H. Role of immediate-early genes in synaptic plasticity and neuronal ensembles underlying the memory trace. Front. Mol. Neurosci. 8, 78 (2016).

    PubMed  PubMed Central  Google Scholar 

  3. Seidlitz, J. et al. Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders. Nat. Commun. 11, 3358 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Genove, G., DeMarco, U., Xu, H., Goins, W. F. & Ahrens, E. T. A new transgene reporter for in vivo magnetic resonance imaging. Nat. Med. 11, 450–454 (2005).

    CAS  Google Scholar 

  5. Shapiro, M. G. et al. Directed evolution of a magnetic resonance imaging contrast agent for noninvasive imaging of dopamine. Nat. Biotechnol. 28, 264–270 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Sigmund, F. et al. Bacterial encapsulins as orthogonal compartments for mammalian cell engineering. Nat. Commun. 9, 1990 (2018).

    PubMed  PubMed Central  Google Scholar 

  7. Schilling, F. et al. MRI measurements of reporter-mediated increases in transmembrane water exchange enable detection of a gene reporter. Nat. Biotechnol. 35, 75–80 (2017).

    CAS  PubMed  Google Scholar 

  8. Mukherjee, A., Wu, D., Davis, H. C. & Shapiro, M. G. Non-invasive imaging using reporter genes altering cellular water permeability. Nat. Commun. 7, 13891 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Farhadi, A., Sigmund, F., Westmeyer, G. G. & Shapiro, M. G. Genetically encodable materials for non-invasive biological imaging. Nat. Mater. 20, 585–592 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Farhadi, A., Ho, G. H., Sawyer, D. P., Bourdeau, R. W. & Shapiro, M. G. Ultrasound imaging of gene expression in mammalian cells. Science 365, 1469–1475 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Lu, G. J. et al. Acoustically modulated magnetic resonance imaging of gas-filled protein nanostructures. Nat. Mater. 17, 456–463 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Gottschalk, S. et al. Rapid volumetric optoacoustic imaging of neural dynamics across the mouse brain. Nat. Biomed. Eng. 3, 392–401 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Marvin, J. S. et al. A genetically encoded fluorescent sensor for in vivo imaging of GABA. Nat. Methods 16, 763–770 (2019).

    CAS  PubMed  Google Scholar 

  14. Ntziachristos, V. Going deeper than microscopy: the optical imaging frontier in biology. Nat. Methods 7, 603–614 (2010).

    CAS  PubMed  Google Scholar 

  15. Iwano, S. et al. Single-cell bioluminescence imaging of deep tissue in freely moving animals. Science 359, 935–939 (2018).

    CAS  PubMed  Google Scholar 

  16. de Wildt, R. M., Mundy, C. R., Gorick, B. D. & Tomlinson, I. M. Antibody arrays for high-throughput screening of antibody–antigen interactions. Nat. Biotechnol. 18, 989–994 (2000).

    PubMed  Google Scholar 

  17. Shendure, J. & Ji, H. Next-generation DNA sequencing. Nat. Biotechnol. 26, 1135–1145 (2008).

    CAS  PubMed  Google Scholar 

  18. Aebersold, R. & Mann, M. Mass spectrometry-based proteomics. Nature 422, 198–207 (2003).

    CAS  PubMed  Google Scholar 

  19. Naumova, O. Y., Lee, M., Rychkov, S. Y., Vlasova, N. V. & Grigorenko, E. L. Gene expression in the human brain: the current state of the study of specificity and spatiotemporal dynamics. Child Dev. 84, 76–88 (2013).

    PubMed  Google Scholar 

  20. Kang, H. J. et al. Spatio-temporal transcriptome of the human brain. Nature 478, 483–489 (2011).

    CAS  PubMed Central  Google Scholar 

  21. Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–628 (2008).

    CAS  PubMed  Google Scholar 

  22. Roopenian, D. C. & Akilesh, S. FcRn: the neonatal Fc receptor comes of age. Nat. Rev. Immunol. 7, 715–725 (2007).

    CAS  PubMed  Google Scholar 

  23. Rissin, D. M. et al. Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations. Nat. Biotechnol. 28, 595–599 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Swaminathan, J. et al. Highly parallel single-molecule identification of proteins in zeptomole-scale mixtures. Nat. Biotechnol. 36, 1076–1082 (2018).

    CAS  Google Scholar 

  25. Sze, J. Y., Ivanov, A. P., Cass, A. E. G. & Edel, J. B. Single molecule multiplexed nanopore protein screening in human serum using aptamer modified DNA carriers. Nat. Commun. 8, 1552 (2017).

    PubMed Central  Google Scholar 

  26. Tannous, B. A., Kim, D.-E., Fernandez, J. L., Weissleder, R. & Breakefield, X. O. Codon-optimized Gaussia luciferase cDNA for mammalian gene expression in culture and in vivo. Mol. Ther. 11, 435–443 (2005).

    CAS  PubMed  Google Scholar 

  27. Aalipour, A. et al. Engineered immune cells as highly sensitive cancer diagnostics. Nat. Biotechnol. 37, 531–539 (2019).

    CAS  PubMed Central  Google Scholar 

  28. Deane, R. et al. IgG-assisted age-dependent clearance of Alzheimer’s amyloid β peptide by the blood–brain barrier neonatal Fc receptor. J. Neurosci. 25, 11495–11503 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Cooper, P. R. et al. Efflux of monoclonal antibodies from rat brain by neonatal Fc receptor, FcRn. Brain Res. 1534, 13–21 (2013).

    CAS  Google Scholar 

  30. Zhang, Y. & Pardridge, W. M. Mediated efflux of IgG molecules from brain to blood across the blood–brain barrier. J. Neuroimmunol. 114, 168–172 (2001).

    CAS  PubMed  Google Scholar 

  31. Borrok, M. J. et al. pH-dependent binding engineering reveals an FcRn affinity threshold that governs IgG recycling. J. Biol. Chem. 290, 4282–4290 (2015).

    CAS  PubMed  Google Scholar 

  32. Westerink, R. H. S. & Ewing, A. G. The PC12 cell as model for neurosecretion. Acta Physiol. 192, 273–285 (2008).

    CAS  Google Scholar 

  33. Verhaegen, M. & Christopoulos, T. K. Recombinant Gaussia luciferase. Overexpression, purification, and analytical application of a bioluminescent reporter for DNA hybridization. Anal. Chem. 74, 4378–4385 (2002).

    CAS  Google Scholar 

  34. Oganesyan, V. et al. Structural insights into neonatal Fc receptor-based recycling mechanisms. J. Biol. Chem. 289, 7812–7824 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Medesan, C., Matesoi, D., Radu, C., Ghetie, V. & Ward, E. S. Delineation of the amino acid residues involved in transcytosis and catabolism of mouse IgG1. J. Immunol. 158, 2211–2217 (1997).

    CAS  PubMed  Google Scholar 

  36. Lee, C.-H. et al. An engineered human Fc domain that behaves like a pH-toggle switch for ultra-long circulation persistence. Nat. Commun. 10, 5031 (2019).

    PubMed  PubMed Central  Google Scholar 

  37. Herculano-Houzel, S., Mota, B. & Lent, R. Cellular scaling rules for rodent brains. Proc. Natl Acad. Sci. USA 103, 12138–12143 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Eixarch, H. et al. Transgene expression levels determine the immunogenicity of transduced hematopoietic grafts in partially myeloablated mice. Mol. Ther. 17, 1904–1909 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Pyzik, M., Kozicky, L. K., Gandhi, A. K. & Blumberg, R. S. The therapeutic age of the neonatal Fc receptor. Nat. Rev. Immunol. 23, 415–432 (2023).

    CAS  Google Scholar 

  40. Gil, G. A. et al. c-Fos activated phospholipid synthesis is required for neurite elongation in differentiating PC12 cells. Mol. Biol. Cell 15, 1881–1894 (2004).

    CAS  PubMed Central  Google Scholar 

  41. Alexander, G. M. et al. Remote control of neuronal activity in transgenic mice expressing evolved G protein-coupled receptors. Neuron 63, 27–39 (2009).

    CAS  PubMed Central  Google Scholar 

  42. Roth, B. L. DREADDs for neuroscientists. Neuron 89, 683–694 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Szablowski, J. O., Lee-Gosselin, A., Lue, B., Malounda, D. & Shapiro, M. G. Acoustically targeted chemogenetics for the non-invasive control of neural circuits. Nat. Biomed. Eng. 2, 475–484 (2018).

    CAS  Google Scholar 

  44. Sørensen, A. T. et al. A robust activity marking system for exploring active neuronal ensembles. eLife 5, e13918 (2016).

    PubMed  PubMed Central  Google Scholar 

  45. Bernau, K. et al. In vivo tracking of human neural progenitor cells in the rat brain using bioluminescence imaging. J. Neurosci. Methods 228, 67–78 (2014).

    PubMed  PubMed Central  Google Scholar 

  46. Chan, K. Y. et al. Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nat. Neurosci. 20, 1172–1179 (2017).

    CAS  PubMed Central  Google Scholar 

  47. Kobayashi, N. FcRn-mediated transcytosis of immunoglobulin G in human renal proximal tubular epithelial cells. Am. J. Physiol. Renal Physiol 282, F358–F365 (2002).

    PubMed  Google Scholar 

  48. Pyzik, M. et al. Hepatic FcRn regulates albumin homeostasis and susceptibility to liver injury. Proc. Natl Acad. Sci. USA 114, E2862–E2871 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Zetterberg, H. & Burnham, S. C. Blood-based molecular biomarkers for Alzheimer’s disease. Mol. Brain 12, 26 (2019).

    PubMed  PubMed Central  Google Scholar 

  50. Niederkofler, V. et al. Identification of serotonergic neuronal modules that affect aggressive behavior. Cell Rep. 17, 1934–1949 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Clifton, N. E. et al. Dynamic expression of genes associated with schizophrenia and bipolar disorder across development. Transl. Psychiatry 9, 74–74 (2019).

    PubMed  PubMed Central  Google Scholar 

  52. Tiklová, K. et al. Disease duration influences gene expression in neuromelanin-positive cells from Parkinsonas disease patients. Front. Mol. Neurosci 14, 763777 (2021).

    PubMed  PubMed Central  Google Scholar 

  53. Ham, S. & Lee, S.-J. V. Advances in transcriptome analysis of human brain aging. Exp. Mol. Med. 52, 1787–1797 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Pasi, K. J. et al. Multiyear follow-up of AAV5-hFVIII-SQ gene therapy for hemophilia A. N. Engl. J. Med. 382, 29–40 (2020).

    CAS  PubMed  Google Scholar 

  55. Kim, H. J. et al. Stereotactic brain injection of human umbilical cord blood mesenchymal stem cells in patients with Alzheimer’s disease dementia: a phase 1 clinical trial. Alzheimers Dement. (N Y) 1, 95–102 (2015).

    PubMed  Google Scholar 

  56. Duerinck, J. et al. Intracerebral administration of CTLA-4 and PD-1 immune checkpoint blocking monoclonal antibodies in patients with recurrent glioblastoma: a phase I clinical trial. J. Immunother. Cancer 9, e002296 (2021).

    PubMed  PubMed Central  Google Scholar 

  57. Goertsen, D. et al. AAV capsid variants with brain-wide transgene expression and decreased liver targeting after intravenous delivery in mouse and marmoset. Nat. Neurosci. 25, 106–115 (2022).

    CAS  Google Scholar 

  58. Thévenot, E. et al. Targeted delivery of self-complementary adeno-associated virus serotype 9 to the brain, using magnetic resonance imaging-guided focused ultrasound. Hum. Gene Ther. 23, 1144–1155 (2012).

    PubMed Central  Google Scholar 

  59. Nouraein, S. et al. Acoustically targeted noninvasive gene therapy in large brain volumes. Gene Ther. https://doi.org/10.1038/s41434-023-00421-1 (2023).

  60. McMahon, D., O’Reilly, M. A. & Hynynen, K. Therapeutic agent delivery across the blood–brain barrier using focused ultrasound. Annu. Rev. Biomed. Eng. 23, 89–113 (2021).

    CAS  PubMed  Google Scholar 

  61. Lipsman, N. et al. Blood–brain barrier opening in Alzheimer’s disease using MR-guided focused ultrasound. Nat. Commun. 9, 2336 (2018).

    PubMed  PubMed Central  Google Scholar 

  62. Alfaro, J. A. et al. The emerging landscape of single-molecule protein sequencing technologies. Nat. Methods 18, 604–617 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Ying, T., Feng, Y., Wang, Y., Chen, W. & Dimitrov, D. S. Monomeric IgG1 Fc molecules displaying unique Fc receptor interactions that are exploitable to treat inflammation-mediated diseases. MAbs 6, 1201–1210 (2014).

    PubMed  PubMed Central  Google Scholar 

  64. Challis, R. C. et al. Systemic AAV vectors for widespread and targeted gene delivery in rodents. Nat. Protoc. 14, 379–414 (2019).

    CAS  PubMed  Google Scholar 

  65. Lawlor, P. A., Bland, R. J., Mouravlev, A., Young, D. & During, M. J. Efficient gene delivery and selective transduction of glial cells in the mammalian brain by AAV serotypes isolated from nonhuman primates. Mol. Ther. 17, 1692–1702 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank J. J. Tabor (Rice University) for providing the pET28a bacterial expression plasmid and G. Bao (Rice University) for providing use of the ultracentrifuge. We thank V. Gradinaru (Caltech) and the Caltech CLOVER Center for providing the pUCmini-iCAP-PHP.eB and pHelper plasmids. This research was supported by the David and Lucile Packard Foundation 2021-73005 (J.O.S.), National Institute of Biomedical Imaging and Bioengineering Trailblazer Award R21EB033059 (J.O.S.), National Institute of General Medical Sciences DP2GM140923 (G.C.), National Institute on Drug Abuse R00DA043609 (G.C.) and National Institute of Neurological Disorders and Stroke F31NS125927 (J.A.W.).

Author information

Authors and Affiliations

  1. Department of Bioengineering, Rice University, Houston, TX, USA

    Sangsin Lee, Shirin Nouraein, James J. Kwon, Zhimin Huang, Boao Xia & Jerzy O. Szablowski

  2. Rice Neuroengineering Initiative, Rice University, Houston, TX, USA

    Sangsin Lee, Shirin Nouraein, Zhimin Huang, Boao Xia & Jerzy O. Szablowski

  3. Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, USA

    Shirin Nouraein & Jerzy O. Szablowski

  4. Department of Psychiatry and Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Jessica A. Wojick & Gregory Corder

  5. Applied Physics Program, Rice University, Houston, TX, USA

    Jerzy O. Szablowski

Authors
  1. Sangsin Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shirin Nouraein
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. James J. Kwon
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhimin Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jessica A. Wojick
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Boao Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gregory Corder
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jerzy O. Szablowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.O.S. and S.L. conceived and planned the research. S.L. and J.O.S. designed the experiments and wrote the paper, with input from all other authors. S.L. performed and participated in all experiments described in the study. S.N. performed AAV production. S.N. and J.A.W. performed stereotaxic injection and retro-orbital blood collection. S.N. and J.J.K. performed the histological experiments. J.J.K. maintained PC-12 and conducted the in vitro Fos activation. S.N., J.A.W., J.J.K., Z.H. and B.X. analyzed histological images. S.N. and Z.H. assisted with IVIS imaging and drug administration. Z.H. constructed plasmids for the chemogenetic experiment. B.X. maintained and transfected astrocytes and performed protein purification. G.C. provided advice on the chemogenetic experiment and experimental guidance to J.A.W.

Corresponding author

Correspondence to Jerzy O. Szablowski.

Ethics declarations

Competing interests

J.O.S. and S.L. are co-inventors on a US patent application that incorporates discoveries described in this paper. The other authors declare no competing interests.

Peer review

Peer review information

Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–11 and Sequence 1.

Reporting Summary

Supplementary Data 2

Statistical source data for Supplementary Fig. 1.

Supplementary Data 3

Statistical source data for Supplementary Fig. 3.

Supplementary Data 4

Statistical source data for Supplementary Fig. 4.

Supplementary Data 5

Statistical source data for Supplementary Fig. 5.

Supplementary Data 6

Statistical source data for Supplementary Fig. 6.

Supplementary Data 7

Statistical source data for Supplementary Fig. 7.

Supplementary Data 8

Statistical source data for Supplementary Fig. 8.

Supplementary Data 9

Statistical source data for Supplementary Fig. 9.

Supplementary Data 10

Statistical source data for Supplementary Fig. 10.

Supplementary Data 11

Statistical source data for Supplementary Fig. 11.

Source data

Source Data Fig. 2

Statistical source data for Fig. 2.

Source Data Fig. 3

Statistical source data for Fig. 3.

Source Data Fig. 4

Statistical source data for Fig. 4.

Source Data Fig. 5

Statistical source data for Fig. 5.

Source Data Fig. 6

Statistical source data for Fig. 6.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, S., Nouraein, S., Kwon, J.J. et al. Engineered serum markers for non-invasive monitoring of gene expression in the brain. Nat Biotechnol (2024). https://doi.org/10.1038/s41587-023-02087-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41587-023-02087-x

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research