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Engineered nascent living human tissues with unit programmability

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Pedro Lavrador at University of Aveiro
Pedro Lavrador
Beatriz S. Moura at University of Aveiro
Beatriz S. Moura
José Almeida-Pinto at University of Aveiro
José Almeida-Pinto
Vítor M Gaspar at University of Aveiro
Vítor M Gaspar
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Abstract and Figures

Leveraging human cells as materials precursors is a promising approach for fabricating living materials with tissue-like functionalities and cellular programmability. Here we describe a set of cellular units with metabolically engineered glycoproteins that allow cells to tether together to function as macrotissue building blocks and bioeffectors. The generated human living materials, termed as Cellgels, can be rapidly assembled in a wide variety of programmable three-dimensional configurations with physiologically relevant cell densities (up to 10⁸ cells per cm³), tunable mechanical properties and handleability. Cellgels inherit the ability of living cells to sense and respond to their environment, showing autonomous tissue-integrative behaviour, mechanical maturation, biological self-healing, biospecific adhesion and capacity to promote wound healing. These living features also enable the modular bottom-up assembly of multiscale constructs, which are reminiscent of human tissue interfaces with heterogeneous composition. This technology can potentially be extended to any human cell type, unlocking the possibility for fabricating living materials that harness the intrinsic biofunctionalities of biological systems.
Assembly of human-based living gel-like materials This technology leverages metabolic glycoengineering to functionalize a broad variety of human cellular building blocks, namely, hASCs, hUVECs, hDFs and hPANC-1s. Through an endogenously driven process, bioorthogonal azide groups are readily installed into cell-surface glycoproteins for posterior SPAAC coupling with a complementary cell-tethering glycosaminoglycan derivative. Under the proposed strategy, cells serve simultaneously as biodynamic crosslinking nodes and the primary building blocks of tissue-dense human living materials with unit programmability.
Assembly of human-based living gel-like materials This technology leverages metabolic glycoengineering to functionalize a broad variety of human cellular building blocks, namely, hASCs, hUVECs, hDFs and hPANC-1s. Through an endogenously driven process, bioorthogonal azide groups are readily installed into cell-surface glycoproteins for posterior SPAAC coupling with a complementary cell-tethering glycosaminoglycan derivative. Under the proposed strategy, cells serve simultaneously as biodynamic crosslinking nodes and the primary building blocks of tissue-dense human living materials with unit programmability.
… 
Cellular engineering and assembly of cell-rich bioarchitectures a, Fluorescence microscopy of metabolic glycoengineered hASCs incubated with different Ac4ManNAz doses for 24 h. Green channel, cell-surface azides; blue channel, cell nuclei. Scale bars, 100 µm. b, Flow cytometry of azide-bearing hASCs under increasing Ac4ManNAz doses. Representative histograms (left) and mean fluorescence intensity (MFI) normalized to the highest dose group (right). DBCO-PEG4-rhodamine110, dibenzocyclooctyne-poly(ethylene glycol)4-carboxyrhodamine110. Data represented as mean ± s.d., n = 6 replicates. *P = 0.0354 (10 µM versus 50 µM), *P = 0.0143 (10 µM versus 100 µM), one-way analysis of variance (ANOVA) with Tukey’s multiple comparisons test. c, Distribution of cellular and biomaterial (HA-DBCO) mass content in living materials. d, Cellgels’ morphological programmability and free-standing features across different geometrical configurations. Constructs were assembled via polydimethylsiloxane templates (cylinder, hexagon and prism), agarose micromoulds (micro-toroids) and superhydrophobic surfaces (beads). Scale bars, 1 cm (top), 5 mm (bottom), and 2 mm (bottom-right, inset). e, Micrograph and scanning electron microscopy of disk-shaped constructs matured for 24 h. Scale bars, 500 µm (top), and 100 µm (bottom). f, Cellgels showing a broad range of tissue-like densities, matured for 24 h. Scale bar, 5 mm. Source data
Cellular engineering and assembly of cell-rich bioarchitectures a, Fluorescence microscopy of metabolic glycoengineered hASCs incubated with different Ac4ManNAz doses for 24 h. Green channel, cell-surface azides; blue channel, cell nuclei. Scale bars, 100 µm. b, Flow cytometry of azide-bearing hASCs under increasing Ac4ManNAz doses. Representative histograms (left) and mean fluorescence intensity (MFI) normalized to the highest dose group (right). DBCO-PEG4-rhodamine110, dibenzocyclooctyne-poly(ethylene glycol)4-carboxyrhodamine110. Data represented as mean ± s.d., n = 6 replicates. *P = 0.0354 (10 µM versus 50 µM), *P = 0.0143 (10 µM versus 100 µM), one-way analysis of variance (ANOVA) with Tukey’s multiple comparisons test. c, Distribution of cellular and biomaterial (HA-DBCO) mass content in living materials. d, Cellgels’ morphological programmability and free-standing features across different geometrical configurations. Constructs were assembled via polydimethylsiloxane templates (cylinder, hexagon and prism), agarose micromoulds (micro-toroids) and superhydrophobic surfaces (beads). Scale bars, 1 cm (top), 5 mm (bottom), and 2 mm (bottom-right, inset). e, Micrograph and scanning electron microscopy of disk-shaped constructs matured for 24 h. Scale bars, 500 µm (top), and 100 µm (bottom). f, Cellgels showing a broad range of tissue-like densities, matured for 24 h. Scale bar, 5 mm. Source data
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Cellgel bioarchitecture characterization a, Hierarchical clustered heatmap and donut plots of DEGs among 2D azide-bearing hASCs and 3D Cellgels. b, PCA of gene expression profiles. c, Volcano plot of transcriptome changes. d,e, Heatmaps of DEGs related to ECM organization (d) and growth factors (e). f, Secreted proteins annotated in the Matrisome Project database. g, Top-five most abundant secreted proteins. Data represented as mean ± s.d., n = 5 Cellgel replicates. h, Fluorescence microscopy of cellular morphology in Cellgels (day 7). Red channel, F-actin; blue channel, cell nuclei. Scale bar, 200 µm. i, Bioorthogonal labelling of cell-tethering component in Cellgels (day 7). Green channel, HA-DBCO; blue channel; cell nuclei. Scale bars, 200 µm. j, Cellgels self-supportive features during maturation. Scale bars, 5 mm. k, Evolution of de novo total collagen deposited during maturation. Data represented as mean ± s.d., n = 4 Cellgel replicates. **P = 0.0085, *P = 0.0202, one-way ANOVA with Tukey’s multiple comparisons test. l, Mechanical maturation along time. Data represented as mean ± s.d., n = 8 Cellgel replicates over 2 independent experiments. *P = 0.0323, **P = 0.0015, ****P < 0.0001, one-way ANOVA with Tukey’s multiple comparisons test. m, Influence of azide cell density and HA-DBCO content on storage modulus (G′), determined by amplitude sweep rheology. Data represented as mean ± s.d., n = 5 Cellgel replicates. Left, **P = 0.0068, ***P = 0.00014, ****P < 0.0001; right, *P = 0.0193, ****P < 0.0001; one-way ANOVA with Tukey’s multiple comparisons test. n, Confocal imaging of Cellgels’ tissue-integrative ability over time. The inset highlights the cellular network migration into adjacent tissue-mimetic environments (Matrigel). Red channel, F-actin. Scale bar, 200 µm. The right panel is a 3D representation of the Cellgel/Matrigel interface. Source data
Cellgel bioarchitecture characterization a, Hierarchical clustered heatmap and donut plots of DEGs among 2D azide-bearing hASCs and 3D Cellgels. b, PCA of gene expression profiles. c, Volcano plot of transcriptome changes. d,e, Heatmaps of DEGs related to ECM organization (d) and growth factors (e). f, Secreted proteins annotated in the Matrisome Project database. g, Top-five most abundant secreted proteins. Data represented as mean ± s.d., n = 5 Cellgel replicates. h, Fluorescence microscopy of cellular morphology in Cellgels (day 7). Red channel, F-actin; blue channel, cell nuclei. Scale bar, 200 µm. i, Bioorthogonal labelling of cell-tethering component in Cellgels (day 7). Green channel, HA-DBCO; blue channel; cell nuclei. Scale bars, 200 µm. j, Cellgels self-supportive features during maturation. Scale bars, 5 mm. k, Evolution of de novo total collagen deposited during maturation. Data represented as mean ± s.d., n = 4 Cellgel replicates. **P = 0.0085, *P = 0.0202, one-way ANOVA with Tukey’s multiple comparisons test. l, Mechanical maturation along time. Data represented as mean ± s.d., n = 8 Cellgel replicates over 2 independent experiments. *P = 0.0323, **P = 0.0015, ****P < 0.0001, one-way ANOVA with Tukey’s multiple comparisons test. m, Influence of azide cell density and HA-DBCO content on storage modulus (G′), determined by amplitude sweep rheology. Data represented as mean ± s.d., n = 5 Cellgel replicates. Left, **P = 0.0068, ***P = 0.00014, ****P < 0.0001; right, *P = 0.0193, ****P < 0.0001; one-way ANOVA with Tukey’s multiple comparisons test. n, Confocal imaging of Cellgels’ tissue-integrative ability over time. The inset highlights the cellular network migration into adjacent tissue-mimetic environments (Matrigel). Red channel, F-actin. Scale bar, 200 µm. The right panel is a 3D representation of the Cellgel/Matrigel interface. Source data
… 
Cellgels present selective adhesion and biological self-healing properties a,b, Evaluation of biospecific adhesion to bioinert (a) and tissue-mimetic (b) hydrogel microenvironments. Scale bars, 1 cm. c, Self-sustaining and gap-bridging capabilities. d, Cellgels as ex vivo tissue fillers in porcine skin defects. Constructs were stained with blue food colouring for visualization. e, Demonstration of tissue adhesion in three different tissues (skin, liver and heart). Scale bars, 5 mm. f, Tissue adhesion energy of Cellgel–tissue assemblies, after 24 h. Tissue-on-tissue assemblies served as negative controls for adhesion. Data represented as mean ± s.d., n = 10 Cellgel–tissue assemblies over 3 independent experiments. ****P < 0.0001, one-way ANOVA with Tukey’s multiple comparisons test. g,h, Demonstration of the adhesive performance of Cellgel–tissue assemblies during extension (g) and vertical suspension (h). i,j, 3D representation (i) and micrograph (j) of cell-mediated self-healing following critical damage. Scale bar, 5 mm. k, Self-healed structure following 7 days in culture. Scale bar, 5 mm. l, Self-healed constructs show a seamless structure under mechanical stretching. m, Scanning electron microscopy of self-healed interfaces between two Cellgel pieces. Scale bars, 50 µm and 100 µm (inset). n, Schematic and micrograph showcasing self-healing of fluorescently labelled opposing halves into a two-segmented cuboid. Scale bars, 5 mm. o,p, Confocal imaging of fluorescently labelled Cellgel halves self-healed into cuboids (o) and disks (p) after 7 days. Top right: normalized line fluorescence intensity profile across the constructs. Green channel, DiO-hASCs; red channel, DiD-hASCs. Scale bars, 1 mm. Source data
Cellgels present selective adhesion and biological self-healing properties a,b, Evaluation of biospecific adhesion to bioinert (a) and tissue-mimetic (b) hydrogel microenvironments. Scale bars, 1 cm. c, Self-sustaining and gap-bridging capabilities. d, Cellgels as ex vivo tissue fillers in porcine skin defects. Constructs were stained with blue food colouring for visualization. e, Demonstration of tissue adhesion in three different tissues (skin, liver and heart). Scale bars, 5 mm. f, Tissue adhesion energy of Cellgel–tissue assemblies, after 24 h. Tissue-on-tissue assemblies served as negative controls for adhesion. Data represented as mean ± s.d., n = 10 Cellgel–tissue assemblies over 3 independent experiments. ****P < 0.0001, one-way ANOVA with Tukey’s multiple comparisons test. g,h, Demonstration of the adhesive performance of Cellgel–tissue assemblies during extension (g) and vertical suspension (h). i,j, 3D representation (i) and micrograph (j) of cell-mediated self-healing following critical damage. Scale bar, 5 mm. k, Self-healed structure following 7 days in culture. Scale bar, 5 mm. l, Self-healed constructs show a seamless structure under mechanical stretching. m, Scanning electron microscopy of self-healed interfaces between two Cellgel pieces. Scale bars, 50 µm and 100 µm (inset). n, Schematic and micrograph showcasing self-healing of fluorescently labelled opposing halves into a two-segmented cuboid. Scale bars, 5 mm. o,p, Confocal imaging of fluorescently labelled Cellgel halves self-healed into cuboids (o) and disks (p) after 7 days. Top right: normalized line fluorescence intensity profile across the constructs. Green channel, DiO-hASCs; red channel, DiD-hASCs. Scale bars, 1 mm. Source data
… 
Modular fabrication of multicomponent Cellgel-based assemblies a,b, 3D representation (a) and micrographs (b) of modular Cellgel–hydrogel hybrid constructs. Scale bars, 5 mm. c, Generation of hybrid perfusable architectures by embedding hollow hydrogel fibres (gelatin/alginate composition, Gel/Alg) within Cellgel constructs. Scale bars, 500 µm (top left), 1 cm (bottom left), 1 cm (right). d,e, Confocal imaging of stratified constructs with different concentric configurations (Cellgel versus hASC-laden GelMA inner cores). Top right: normalized line fluorescence intensity profile across the constructs. Green channel, DiO-hASCs; red channel, DiD-hASCs. Scale bars, 1 mm. f, Confocal images of heterotypic Cellgels comprising two different cell types (hASCs and hDFs) combined at varying ratios (0%, 25%, 50%, 75%, 100%). The distinct cellular building blocks (hASCs and hDFs) were labelled with DiD and DiO fluorophores, respectively. Green channel, DiO-hDFs; red channel, DiD-hASCs. Scale bars, 100 µm. g–i, 3D representation (g) and micrographs (h,i) of spatially defined heterogeneous Cellgel–Cellgel assemblies. Scale bars, 5 mm. j, Confocal imaging of multicellular constructs demonstrating the possibility to encode heterogeneous composition in human-based living materials. Top right: normalized line fluorescence intensity profile across the construct. Green channel, DiO-hDFs; red channel, DiD-hASCs. Scale bars, 2 mm. Source data
+1
Modular fabrication of multicomponent Cellgel-based assemblies a,b, 3D representation (a) and micrographs (b) of modular Cellgel–hydrogel hybrid constructs. Scale bars, 5 mm. c, Generation of hybrid perfusable architectures by embedding hollow hydrogel fibres (gelatin/alginate composition, Gel/Alg) within Cellgel constructs. Scale bars, 500 µm (top left), 1 cm (bottom left), 1 cm (right). d,e, Confocal imaging of stratified constructs with different concentric configurations (Cellgel versus hASC-laden GelMA inner cores). Top right: normalized line fluorescence intensity profile across the constructs. Green channel, DiO-hASCs; red channel, DiD-hASCs. Scale bars, 1 mm. f, Confocal images of heterotypic Cellgels comprising two different cell types (hASCs and hDFs) combined at varying ratios (0%, 25%, 50%, 75%, 100%). The distinct cellular building blocks (hASCs and hDFs) were labelled with DiD and DiO fluorophores, respectively. Green channel, DiO-hDFs; red channel, DiD-hASCs. Scale bars, 100 µm. g–i, 3D representation (g) and micrographs (h,i) of spatially defined heterogeneous Cellgel–Cellgel assemblies. Scale bars, 5 mm. j, Confocal imaging of multicellular constructs demonstrating the possibility to encode heterogeneous composition in human-based living materials. Top right: normalized line fluorescence intensity profile across the construct. Green channel, DiO-hDFs; red channel, DiD-hASCs. Scale bars, 2 mm. Source data
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Nature Materials | Volume 24 | January 2025 | 143–154 143
nature materials
https://doi.org/10.1038/s41563-024-01958-1
Article
Engineered nascent living human tissues
with unit programmability
Pedro Lavrador   , Beatriz S. Moura   , José Almeida-Pinto   ,
Vítor M. Gaspar    & João F. Mano   
Leveraging human cells as materials precursors is a promising approach
for fabricating living materials with tissue-like functionalities and
cellular programmability. Here we describe a set of cellular units with
metabolically engineered glycoproteins that allow cells to tether together
to function as macrotissue building blocks and bioeectors. The generated
human living materials, termed as Cellgels, can be rapidly assembled
in a wide variety of programmable three-dimensional congurations
with physiologically relevant cell densities (up to 108 cells per cm3),
tunable mechanical properties and handleability. Cellgels inherit the
ability of living cells to sense and respond to their environment, showing
autonomous tissue-integrative behaviour, mechanical maturation,
biological self-healing, biospecic adhesion and capacity to promote
wound healing. These living features also enable the modular bottom-up
assembly of multiscale constructs, which are reminiscent of human
tissue interfaces with heterogeneous composition. This technology can
potentially be extended to any human cell type, unlocking the possibility
for fabricating living materials that harness the i nt ri nsic b io fu nc ti on alities
of biological s ys te ms.
Throughout development, cells are continuously orchestrated and
materialized as collective assemblies, eventually culminating in a fully
functional human body
1,2
. Owing to their cell-rich nature, native tissues
can be viewed as dynamic materials capable of interpreting their envi-
ronment, operating as instructive biofactories (for example, bioactive
signalling cues and extracellular matrix (ECM) components), as well
as recognizing incoming stimuli and adapting their biological proper-
ties accordingly
3
. Despite remarkable progress in stimuli-responsive
materials that mimic the adaptive nature of living tissues
4,5
, cells convey
unique living attributes that are beyond the reach of current synthetic
and semi-synthetic biomaterials6,7.
This perspective has fuelled the pursuit of engineered living
materials, which seeks to maximize the extent of life-like properties
in engineered tissue constructs for potentiating their biomimicry
and biofunctionality8,9. Recent endeavours in this emerging field have
yielded living materials functioning as cellular glues10, or equipped with
on-demand biomineralization
9
, programmable biomolecule-secreting
capabilities and feedback-response modules11–13. Drawing inspira-
tion from these prokaryotic-based systems, there is a great interest
in materializing mammalian cells as living, self-scaffolding building
blocks of biofunctional constructs reproducing tissue composition,
high cell density, autonomous matrix remodelling and mechanical
maturation, among other dynamic features characteristic of biological
tissues (tissue folding and morphogenesis)
14,15
. Still, leveraging human
cells as functional materials for fabricating macroscale tissue mimetics
has remained underexplored. Conventional cell-rich living materials
are typically spherical microaggregates and cell sheets that offer lim-
ited three-dimensionality and are difficult to handle and process into
large-scale constructs
2
. While larger fibre-like constructs have been
fabricated using three-dimensional (3D) bioprinting or hanging-drop
methodologies
16,17
, these approaches still require moderate assembly
times or rely on a combination of technologies encompassing multiple
steps to produce and collect living materials, often with geometrical
restrictions. To overcome this, an alternative is to use cell-surface
Received: 13 June 2021
Accepted: 25 June 2024
Published online: 8 August 2024
Check for updates
CICECO – Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Aveiro, Portugal. e-mail: vm.gaspar@ua.pt; jmano@ua.pt
Content courtesy of Springer Nature, terms of use apply. Rights reserved
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  • J CELL SCI
The extracellular matrix (ECM) is a complex meshwork of proteins that forms the scaffold of all tissues in multicellular organisms. It plays critical roles in all aspects of life: from orchestrating cell migration during development, to supporting tissue repair. It also plays critical roles in the etiology or progression of diseases. To study this compartment, we defined the compendium of all genes encoding ECM and ECM-associated proteins for multiple organisms. We termed this compendium the "matrisome" and further classified matrisome components into different structural or functional categories. This nomenclature is now largely adopted by the research community to annotate -omics datasets and has contributed to advance both fundamental and translational ECM research. Here, we report the development of Matrisome AnalyzeR, a suite of tools including a web-based application (https://sites.google.com/uic.edu/matrisome/tools/matrisome-analyzer) and an R package (https://github.com/Matrisome/MatrisomeAnalyzeR). The web application can be used by anyone interested in annotating, classifying, and tabulating matrisome molecules in large datasets without requiring programming knowledge. The companion R package is available to more experienced users, interested in processing larger datasets or in additional data visualization options.
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Levitational 3D Bioassembly and Density‐Based Spatial Coding of Levitoids
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Self‐assembly of cells into functional bioarchitectures with microscale spatial topographies are prevalent in nature. Despite the advances to recapitulate the native‐like microenvironment in vitro,fabrication of soft living materials with a deterministic control on the composition, functionality, and geometry, is still challenging. Here, a versatile, paramagnetically tunable, levitational biofabrication technique within a ring‐magnet system, RM‐LEV, is developed to assemble single cells or heterogeneous multicellular living architectures in a scaffold‐free manner. The self‐assembly and contactless biofabrication of multiple cell types into 3D multicellular “levitospheres” is demonstrated, where cellular positions are guided by levitation and density, simultaneously. Inherent density and diamagnetism of different cell types are leveraged to manipulate the geometry and self‐assembly of levitospheres into larger complex 3D structures, termed as “levitoids”. This approach is further applied to manipulate, position, and culture levitoids within a 3D hydrogel matrix under levitation, which preserves their viability and functionality. Thus, this study provides a foundation to create spatially heterogeneous 3D cellular assemblies with density‐coded bio‐architectures—which is not previously realized using magnetic levitation. This density‐based coding approach can be beneficial to study the cross‐talk between different cell types within spheroids and organoids, and be broadly applied to 3D bioprinting, tissue engineering, cancer, and neuroscience research.
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Microfluidic bioprinting of tough hydrogel-based vascular conduits for functional blood vessels
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Full-text available
  • Oct 2022
Three-dimensional (3D) bioprinting of vascular tissues that are mechanically and functionally comparable to their native counterparts is an unmet challenge. Here, we developed a tough double-network hydrogel (bio)ink for microfluidic (bio)printing of mono- and dual-layered hollow conduits to recreate vein- and artery-like tissues, respectively. The tough hydrogel consisted of energy-dissipative ionically cross-linked alginate and elastic enzyme-cross-linked gelatin. The 3D bioprinted venous and arterial conduits exhibited key functionalities of respective vessels including relevant mechanical properties, perfusability, barrier performance, expressions of specific markers, and susceptibility to severe acute respiratory syndrome coronavirus 2 pseudo-viral infection. Notably, the arterial conduits revealed physiological vasoconstriction and vasodilatation responses. We further explored the feasibility of these conduits for vascular anastomosis. Together, our study presents biofabrication of mechanically and functionally relevant vascular conduits, showcasing their potentials as vascular models for disease studies in vitro and as grafts for vascular surgeries in vivo, possibly serving broad biomedical applications in the future.
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Complex heatmap visualization
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Full-text available
  • Aug 2022
Heatmap is a widely used statistical visualization method on matrix‐like data to reveal similar patterns shared by subsets of rows and columns. In the R programming language, there are many packages that make heatmaps. Among them, the ComplexHeatmap package provides the richest toolset for constructing highly customizable heatmaps. ComplexHeatmap can easily establish connections between multisource information by automatically concatenating and adjusting a list of heatmaps as well as complex annotations, which makes it widely applied in data analysis in many fields, especially in bioinformatics, to find hidden structures in the data. In this article, we give a comprehensive introduction to the current state of ComplexHeatmap, including its modular design, its rich functionalities, and its broad applications. Complex heatmap is a powerful visualization method for revealing associations between multiple sources of information. We have developed an R package named ComplexHeatmap that provides comprehensive functionalities for heatmap visualization. It has been widely used in the bioinformatics community. We give a comprehensive introduction to the current state of ComplexHeatmap in this article. Complex heatmap is a powerful visualization method for revealing associations between multiple sources of information. We have developed an R package named ComplexHeatmap that provides comprehensive functionalities for heatmap visualization. It has been widely used in the bioinformatics community. We give a comprehensive introduction to the current state of ComplexHeatmap in this article. Complex heatmap is a powerful visualization method for revealing associations between multiple sources of information. We have developed an R package named ComplexHeatmap that provides comprehensive functionalities for heatmap visualization. It has been widely used in the bioinformatics community. We give a comprehensive introduction to the current state of ComplexHeatmap in this article.
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Advancing Tissue Decellularized Hydrogels for Engineering Human Organoids
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The extracellular matrix plays a critical role in bioinstructing cellular self‐assembly and spatial (re)configuration processes that culminate in human organoids in vitro generation and maturation. Considering the importance of the supporting matrix, herein is showcased the most recent advances in the bioengineering of decellularized tissue hydrogels for generating organoids and assembloids. Key design blueprints, characterization methodologies, and extracellular matrix processing toolboxes are comprehensively discussed in light of current advances. Such enabling approaches provide the grounds for engineering next‐generation tissue‐specific hydrogels with close‐to‐native biomolecular signatures and user‐tailored biophysical properties that may potentiate organoids physiomimetic potential. In a forward looking perspective, the combination of tissue‐specific decellularized hydrogels with increasingly complex multicellular assemblies and bottom‐up cell engineering technologies may unravel unprecedented tissue‐like physiological responses and further advance the exploitation of organoids and assembloids as human disease surrogates or as patient‐tailored living therapeutics.
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Programmable Living Units for Emulating Pancreatic Tumor‐Stroma Interplay
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  • Apr 2022
Bioengineering close‐to‐native in vitro models that emulate tumors bioarchitecture and microenvironment is highly appreciable for improving disease modeling toolboxes. Herein, pancreatic cancer living units—so termed cancer‐on‐a‐bead models—are generated. Such user‐programmable in vitro platforms exhibit biomimetic multicompartmentalization and tunable integration of cancer associated stromal elements. These stratified units can be rapidly assembled in‐air, exhibit reproducible morphological features, tunable size, and recapitulate spatially resolved tumor‐stroma extracellular matrix (ECM) niches. Compartmentalization of pancreatic cancer and stromal cells in well‐defined ECM microenvironments stimulates the secretion of key biomolecular effectors including transforming growth factor β and Interleukin 1‐β, closely emulating the signatures of human pancreatic tumors. Cancer‐on‐a‐bead models also display increased drug resistance to chemotherapeutics when compared to their reductionistic counterparts, reinforcing the importance to differentially model ECM components inclusion and their spatial stratification as observed in vivo. Beyond providing a universal technology that enables spatial modularity in tumor‐stroma elements bioengineering, a scalable, in‐air fabrication of ECM‐tunable 3D platforms that can be leveraged for recapitulating differential matrix composition occurring in other human neoplasias is provided here.
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SignalP 6.0 predicts all five types of signal peptides using protein language models
Article
Full-text available
  • Jul 2022
  • NAT BIOTECHNOL
Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data.
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Engineering mammalian living materials towards clinically relevant therapeutics
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Full-text available
  • Dec 2021
Engineered living materials represent a new generation of human-made biotherapeutics that are highly attractive for a myriad of medical applications. In essence, such cell-rich platforms provide encodable bioactivities with extended lifetimes and environmental multi-adaptability currently unattainable in conventional biomaterial platforms. Emerging cell bioengineering tools are herein discussed from the perspective of materializing living cells as cooperative building blocks that drive the assembly of multiscale living materials. Owing to their living character, pristine cellular units can also be imparted with additional therapeutically-relevant biofunctionalities. On this focus, the most recent advances on the engineering of mammalian living materials and their biomedical applications are herein outlined, alongside with a critical perspective on major roadblocks hindering their realistic clinical translation. All in all, transposing the concept of leveraging living materials as autologous tissue-building entities and/or self-regulated biotherapeutics opens new realms for improving precision and personalized medicine strategies in the foreseeable future.
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Partial Coated Stem Cells with Bioinspired Silica as New Generation of Cellular Hybrid Materials
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The manipulation of cell surfaces in anchorage‐dependent cells can help overcome difficulties presented during cell handling and application. Silica‐based protective mechanisms existing in free‐floating microorganisms may be used as inspiration for sustaining human cell survival in suspension. Gathering on this, herein human adipose‐derived mesenchymal stem cells (hASCs) are partially coated with a hard silica layer that operates as a supporting platform for individual cells in suspension. Inspired by the organic templates involved in biosilicification, a novel chitosan (CHT) derivative displaying fully natural quaternary amine moieties is synthetized via a rapid, one‐pot strategy. Silicification is promoted on individual hASCs surfaces via a two‐step process: a priming step onto previously adhered cell with this CHT derivative, followed by a biocompatible sol–gel process. hASCs holding a silica backpack exhibit enhanced cell survival in suspension conditions and can spread and acquire a more adherent phenotype. This new protocol for cell‐surface modification also provides a new generation of hybrid materials with functionalization of the silica backpack, which can be applied to different areas such as tissue engineering, biosensing, drug delivery, and targeted cell‐based therapies. Silica partial coatings on the surface of human adipose‐derived mesenchymal stem cells are a novel and disruptive concept. The formation of these tough supports improves single‐cell survival and functionality in suspension environments. Also, these hybrid cells can be functionalized through silica with different molecules opening the possibility for various applications from sensing to drug delivery and microtissue formation.
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