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Metabolic labeling of secreted matrix to investigate cell–material interactions in tissue engineering and mechanobiology

Nature Protocols volume 17, pages 618–648 (2022)Cite this article

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Abstract

Re-creating features of the native extracellular matrix (ECM) with engineered biomaterials has become a valuable tool to probe the influence of ECM properties on cellular functions (e.g., differentiation) and toward the engineering of tissues. However, characterization of newly secreted (nascent) matrix and turnover, which are important in the context of cells interacting with these biomaterials, has been limited by a lack of tools. We developed a protocol to visualize and quantify the spatiotemporal evolution of newly synthesized and deposited matrix by cells that are either cultured atop (2D) or embedded within (3D) biomaterial systems (e.g., hydrogels, fibrous matrices). This technique relies on the incorporation of a noncanonical amino acid (azidohomoalanine) into proteins as they are synthesized. Deposited nascent ECM components are then visualized with fluorescent cyclooctynes via copper-free cycloaddition for spatiotemporal analysis or modified with cleavable biotin probes for identification. Here we describe the preparation of hyaluronic acid hydrogels through ultraviolet or visible light induced cross-linking for 2D and 3D cell culture, as well as the fluorescent labeling of nascent ECM deposited by cells during culture. We also provide protocols for secondary immunofluorescence of specific ECM components and ImageJ-based ECM quantification methods. Hyaluronic acid polymer synthesis takes 2 weeks to complete, and hydrogel formation for 2D or 3D cell culture is performed in 2–3 h. Lastly, we detail the identification of nascent proteins, including enrichment, preparation and analysis with mass spectrometry, which can be completed in 10 d.

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Fig. 1: Overview of the nascent matrix labeling approach.
Fig. 2: Application of metabolic labeling to monitor nascent protein accumulation at the cell–hydrogel interface in 3D hydrogels.
Fig. 3: Application of nascent protein labeling to assess cell mechanobiologic response atop 2D biomaterials.
Fig. 4: Application of nascent protein labeling to probe mechanosensing and spreading in 3D hydrogels.
Fig. 5: Enrichment of AHA-labeled proteins within engineered hydrogels in vitro and from murine embryos in vivo.
Fig. 6: Hydrogel preparation for 2D and 3D cell culture studies.
Fig. 7: Quantification of nascent matrix thickness in ImageJ.

Data availability

All the data generated or analyzed during this study are included within this article or references cited and the Supplementary Information. Proteomics data are available in the MassIVE repository (https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=11535f3c322649d88e9225d42f5dd9d3). Additional information is available from the corresponding author on request.

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Acknowledgements

The authors are grateful for financial support from the National Institutes of Health (R01 AR077362, R01 AR056624, R01 AR071359 and K99 HL151670), as well as the Center for Engineering MechanoBiology through the National Science Foundation’s STC Program (CMMI 15-48571), and technical support from Christopher Ebmeier of the ‘Central Analytical Mass Spectrometry Facility and W.M. Keck Foundation Proteomics Resource’ at the University of Colorado Boulder. The authors thank C.M. McLeod, E.D. Bonnevie and J.H. Galarraga for helpful discussions.

Author information

Author notes

  1. Claudia Loebel

    Present address: Department of Materials Science & Engineering, University of Michigan, Ann Arbor, USA

  2. Jason A. Burdick

    Present address: BioFrontiers Institute and Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA

Authors and Affiliations

  1. Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

    Claudia Loebel, Robert L. Mauck & Jason A. Burdick

  2. Translational Musculoskeletal Research Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA

    Claudia Loebel, Robert L. Mauck & Jason A. Burdick

  3. Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA

    Aya M. Saleh & Sarah Calve

  4. Purdue University Interdisciplinary Life Sciences Program, Purdue University, West Lafayette, IN, USA

    Kathryn R. Jacobson & Sarah Calve

  5. Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, PA, USA

    Ryan Daniels, Robert L. Mauck & Jason A. Burdick

  6. Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, USA

    Sarah Calve

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Contributions

C.L., A.M.S., K.R.J. and R.D. performed the experiments and analyzed the data. All authors wrote the manuscript, and R.L.M., S.C. and J.A.B. supervised the research.

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Correspondence to Jason A. Burdick.

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Nature Protocols thanks Manuel Mayr and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key references using this protocol

Loebel, C. et. al. Nat. Mater. 18, 883–891 (2019): https://doi.org/10.1038/s41563-019-0307-6

McLeod, C. M. & Mauck, R. L. Sci. Rep. 6, 38852 (2016): https://doi.org/10.1038/srep38852

Bonnevie, E. D. et al. Nat. Biomed. Eng. 3, 998–1008 (2019): https://doi.org/10.1038/s41551-019-0458-4

Loebel, C. et. al. Adv. Funct. Mater. 30, 1909802 (2020): https://doi.org/10.1002/adfm.201909802

Saleh, A. M. et al. Cell Mol. Bioeng. 12, 495–509 (2019): https://doi.org/10.1007/s12195-019-00592-1

Key data used in this protocol

Loebel, C. et. al. Nat. Mater. 18, 883–891 (2019): https://doi.org/10.1038/s41563-019-0307-6

Saleh, A. M. et al. Cell Mol. Bioeng. 12, 495–509 (2019): https://doi.org/10.1007/s12195-019-00592-1

Extended data

Extended Data Fig. 1 Viability of cells cultured in different concentrations of AHA.

Chondrocytes were cultured for 7 days within nondegradable hyaluronic acid hydrogels in chondrogenic media supplemented with different concentrations of AHA and cell viability quantified through live-dead staining (n = 4 hydrogels, mean ± SD, **p ≤ 0.01, by one-way ANOVA with Bonferroni post hoc).

Extended Data Fig. 2 Comparison of nascent protein labeling after and before cell fixation.

Representative images of a maximum intensity z-projection of methionine containing nascent proteins labeled with fluorophore-conjugated cyclooctynes (DBCO-488) after (left) and before (right) adding the fixative. Cells were cultured for 3 days within MMP-degradable hyaluronic acid (HA) hydrogels (media supplemented with azidohomoalanine, AHA). Red lines indicate cell boundaries identified with cell membrane staining. Scale bar, 20 µm. Adapted with permission from ref. 30.

Extended Data Fig. 3 Quantification of nascent matrix volume and area in ImageJ.

a Quantification of nascent matrix volume: Acquire z-stack confocal images of the nascent ECM and cell membrane, transform into 3D object, and split the channels into single 3D images using ImageJ (i). To obtain an image of the nascent matrix only, adjust the threshold for each channel with ‘Otsu thresholding’ and subtract the ‘cell’ image from the ‘nascent matrix’ image (ii). Use the ImageJ ‘3D object counter’ function to measure the nascent matrix volume (iii). Scale bars, 50 µm. b Quantification of nascent matrix area: Acquire z-stack confocal images of the nascent matrix and cell membrane, and split the channels into single z-stack images using ImageJ (i). To obtain an image of the nascent matrix only, adjust the threshold for each channel with ‘Otsu thresholding’ and subtract the ‘cell’ image from the ‘nascent matrix’ image (ii). Use the ImageJ ‘Analyze particles’ function in max projection to measure the nascent matrix area (iii). Scale bars, 50 µm.

Extended Data Fig. 4 Analysis of newly synthesized proteome deposited by chondrocytes within 3D hydrogels.

a Western blot analysis of AHA-labeled and control samples cultured in methionine containing media (Met) showing the influence of iodoacetamide (IAA), sodium ascorbate (SA) and aminoguanidine (AG) at varied concentrations on the efficiency of the click reaction and unspecific labeling. b Western blot analysis of AHA-labeled and Met samples showing the influence of resin to protein ratio on the enrichment and nonspecific binding of labeled proteins by NeutrAvidin affinity purification.

Extended Data Fig. 5 Parameter settings for identification of newly synthesized proteins.

MaxQuant and instrument parameters for identification and quantification.

Extended Data Fig. 6 Diagram illustrating the classification of proteins.

Description of how to classify proteins as cytosolic, nuclear, membrane, cytoskeletal or matrisome-related based on the Gene Ontology Consortium and the Matrisome Project.

Extended Data Fig. 7 Analysis of protein and peptide concentrations during sample preparation.

a Measured protein concentrations using the Pierce Coomassie (Bradford) Protein Assay at step 59 (Start), step 69 (click-reac.) and step 83 (cleaved), n = 6, mean ± SD, color-coded individual points represent one biological replicate. b Measured peptide concentrations using the Pierce Quantitative Fluorometric Peptide Assay at step 88 (Trypsin/LysC), step 89 (SDS removal) and step 94 (C18 clean-up), n = 9, mean ± SD, color-coded individual points represent one biological replicate.

Supplementary information

Supplementary Information

Supplementary Method: LC-MS/MS analysis.

Reporting Summary

Supplementary Table 1

Identification and analysis of newly synthesized proteins. proteinGroups (the Original ‘proteinGroups’ data generated by MaxQuant), Filtered Proteins (Filtered protein IDs and intensities used for downstream data analysis) and Data Analyses (ECM proteins identified with fold change calculations and annotations).

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Loebel, C., Saleh, A.M., Jacobson, K.R. et al. Metabolic labeling of secreted matrix to investigate cell–material interactions in tissue engineering and mechanobiology. Nat Protoc 17, 618–648 (2022). https://doi.org/10.1038/s41596-021-00652-9

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