Abstract

Background

   Induced pluripotent stem cell-derived fibroblasts (iFBs) hold promise
   for autologous disease modelling, but their ability to replicate
   tissue-specific fibroblast characteristics remains unclear. Fibroblasts
   exhibit significant heterogeneity, with distinct subtypes playing
   critical roles in organ function and integrity. This study investigates
   whether iFBs can acquire tissue-specific transcriptional profiles
   through co-culture with cells from different germ layers, including
   skin (keratinocytes), heart (cardiomyocytes), gut (intestinal cells),
   and lung (bronchial epithelial cells).

Methods

   iFBs were co-cultured directly or indirectly with organ-specific cell
   types, followed by bulk RNA sequencing and pathway analysis.
   Transcriptional profiles were compared to primary fibroblasts using
   principal component analysis (PCA), large single-cell databases of over
   20,000 cells for single-cell deconvolution and targeted qPCR
   validation. Statistical significance was assessed via one-way ANOVA.

Results

   Transcriptomic analysis revealed that iFBs exhibit transcriptional
   plasticity, adopting molecular phenotypes aligned with their co-culture
   environment across all germ layers. Paracrine signalling induced
   transient tissue-specific changes in indirectly co-cultured iFBs, but
   sustained interactions were required for stable adaptations. Pathway
   analysis highlighted functional shifts, such as TGF-β activation in
   cardiac iFBs and ECM remodelling in dermal iFBs. However, single-cell
   deconvolution showed incomplete tissue specification, with iFBs
   retaining mixed fibroblast subpopulations.

Conclusions

   These findings demonstrate that iFBs can adopt tissue-specific
   transcriptional profiles, supporting their potential for modelling
   fibrotic microenvironments in 3D in vitro systems. However, the partial
   and transient nature of these adaptations underscores the need to
   validate whether transcriptional changes translate to functional
   fibroblast behaviours, such as ECM dysregulation or aberrant TGF-β
   signalling, in complex tissue models. Optimising co-culture conditions
   to stabilise these phenotypes will be critical for leveraging iFBs in
   fibrosis research, drug screening, and personalised disease modelling.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s13287-025-04537-6.

   Keywords: iPSCs, Fibroblast heterogeneity, iPSC-derived fibroblasts,
   Single-cell deconvolution, Fibroblast plasticity, Organ-specific
   fibroblasts

Introduction

   Human-based (disease) models, including organoids, bioengineered 3D
   tissue models and organ-on-chip setups, aim to bridge the gap between
   traditional 2D cell cultures, animal-based in vivo models and the
   physiological complexity of native human tissues and organs. As such,
   human-based models offer a controlled environment to investigate
   cell-cell interactions, extracellular matrix (ECM)– cell interactions,
   and tissue-specific functions while minimising interspecies-related
   differences inherent to animal studies. Achieving high levels of
   biomimicry requires the integration of all tissue-relevant cell types
   to accurately replicate the complex (patho) physiological interactions
   that occur in vivo [[38]1].

   Fibroblasts, which are present in all connective tissues, are crucial
   for maintaining structural integrity and homeostasis by synthesising
   and remodelling ECM and orchestrating cellular responses during injury
   repair, inflammation, and other stress-related processes [[39]2].
   Fibroblasts are highly heterogenous and exist in distinct subtypes
   contributing to crucial roles in organ integrity and cellular
   interactions [[40]3]. This heterogeneity, in which fewer than 20% of
   fibroblast-enriched genes overlapped between four organs (heart,
   skeletal muscle, intestine, and bladder), reflects their diverse
   functions across organs, including structural support, fibrosis, immune
   modulation, and tissue repair [[41]4]. Dermal fibroblasts for example
   contribute to skin homeostasis by participating in wound healing and
   producing different ECM components relative to cardiac fibroblasts
   which regulate myocardial structure and contribute to electrical
   conduction in the heart [[42]5, [43]6].

   Organ-specific fibroblasts play a crucial role in developing complex 2D
   and 3D disease models, particularly in the context of autologous
   human-based systems. However, the limited availability of primary
   fibroblasts from certain organs (e.g., the heart) has made induced
   pluripotent stem cell (iPSC)-derived fibroblasts (iFBs) an essential
   alternative. iFBs have been successfully applied in a wide range of
   contexts, both as standalone models and within co-culture systems
   [[44]7, [45]8]. These cells offer distinct advantages for patient
   specific disease modelling, by ensuring donor-donor variability and
   allogeneic interactions do not confound experimental readouts. This is
   particularly important in immunological contexts, where the influence
   of genetic differences between donors can confound experimental
   outcomes [[46]9].

   However, the ability of iFBs to replicate the tissue-specific
   characteristics and functional plasticity of native fibroblasts remains
   underexplored. A key challenge has been the lack of specific markers to
   define fibroblast identity and function. A recent review of over 3,000
   studies highlighted the difficulty in identifying specific fibroblast
   markers [[47]10]. Despite advances in single-cell RNA sequencing, the
   absence of reliable markers makes it difficult to determine whether
   generated iFBs are universal precursors or organ-specific subtypes,
   limiting their application in complex disease models.

   To address these challenges, this study investigates whether iFBs can
   acquire tissue-specific transcriptional profiles when co-cultured with
   cells from three germ layers: cardiomyocytes (mesoderm), keratinocytes
   (ectoderm), and bronchial and intestinal epithelial cells (endoderm).
   Using a direct co-culture setup, we analysed transcriptional changes in
   iFBs by bulk RNA-Seq, comparing them to independently cultured iFBs and
   assessing the impact of direct versus indirect co-culture, where cell
   contact is eliminated in the latter. Our findings demonstrate that iFBs
   exhibit transcriptional plasticity, responding dynamically to
   co-culture environments across all germ layers. This suggests their
   potential for integration into complex human-based models but
   highlights the necessity of sustained interaction for stable
   tissue-specific adaptations.

Materials and methods

Human tissue material and maintenance

   Adult stem cell (ASC)-derived jejunal cells (intestinal cells) were
   expanded as organoids in EIF medium (Advanced DMEM/F12, Primocin™ at
   100 µg/ml, GlutaMAX at 1x, HEPES at 10mM, Y-27632 at 10µM, B27
   supplement at 1x, NAC at 1mM, EGF at 50ng/ml, Gastrin I at 10nM, TGF-β
   inhibitor (A83-01) at 0.5µM, WNT Surrogate-Fc Fusion Protein at 0.5nM,
   Rspo3-Fc Conditioned Medium at 1 µg/ml, Noggin at 50ng/ml, IGF-I at
   100ng/ml, FGF-2 at 50 ng/ml, and Prostaglandin E2 at 1µM) and then
   seeded at 750 000 cells/cm^2 onto transwells pre-coated with Matrigel
   diluted at a ratio of 1:50, to form monolayers for terminal
   differentiation.

   Keratinocytes were cultivated in EpiLife (ThermoScientific, USA)
   supplemented with Human Keratinocyte Growth Supplement
   (ThermoScientific, USA) on untreated tissue-culture plastics at an
   initial cell density of 10 000 cells/cm^2. Normal human bronchial
   epithelial cells (NHBE) and lung fibroblasts (NHLFb) were purchased
   from Epithelix (Switzerland). NHBEs were cultured in PneumaCult Ex Plus
   (STEMCELL Technologies, Canada) on untreated tissue-culture plastics at
   an initial cell density of 20 000 cells/cm^2. Human intestinal
   fibroblasts were purchased from ScienCell (USA). Human cardiac
   fibroblasts (306v-05a, Cell Applications Inc) were kindly obtained as a
   gift from Prof. Sophie van Linthout (Berlin Institute of Health Center
   for Regenerative Therapies, Germany). All primary fibroblasts were
   cultured in Fibroblast growth medium (FGM: DMEM (Sigma, D6546)
   supplemented with 10% FBS, 2mM L-glutamine and 400U/ml
   Penicillin/Streptomycin) at an initial cell density of 5 000
   cells/cm^2.

iPSC maintenance and iFB generation

   iPSCs were cultured in E8 MDC-HomeBrew medium (Technology Platform
   Pluripotent Stem Cells of the Max Delbrück Center, Germany). Cells were
   passaged using TrypLE Express (Gibco, USA) and plated in culture medium
   supplemented with 1.2 µg/mL iMatrix-511 (NP892-011, Reprocell, Japan)
   for adhesion and 10µM Y-27,632 (1254, Tocris, UK). Medium was refreshed
   daily.

   iPSCs were differentiated into iFBs by adapting a previously published
   protocol [[48]11] after being seeded at 2 × 10^4 cells/cm^2 on
   iMatrix-511 in E8 medium with 10µM Y-27,632. The next day,
   differentiation began in CnT-PR-F (CellnTEC, Switzerland), 10% FBS,
   25ng/mL BMP4, transitioning to Fibroblast Growth Medium (FGM) on Day 4.
   From Days 6–10, 10µM SB-43,125 was added to prevent myofibroblast
   transition. Basic iFB characterisation is found in Fig. [49]1.

Fig. 1.

   Fig. 1
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   (A) Immunofluorescence staining against pluripotency markers OCT4 and
   NANOG expressed in iPSCs. (B) Brightfield progression of iPSC to iFB
   from day 0 to day 4. (C) Immunofluorescence staining against vimentin
   and alpha smooth actin (ASMA). (D) Relative quantification of vimentin
   and PDGFRA transcript expression in iPSC vs iFB. All data are presented
   as mean ± SEM

Generation of iPSC-derived cardiomyocytes

   At ~ 90% iPSC confluence, cardiac differentiation was initiated in
   RPMI-1640 + B27 (1:50) (without insulin) (Gibco, USA) with CHIR99021
   (Tocris, UK) (8µM Day 0; 4µM Day 1), followed by 5µM IWR-1 (Tocris, UK)
   on Day 3. On Day 7, cells were switched to RPMI-1640 + B27 (with
   insulin). Spontaneous contractions typically began around Days 8–10.
   All media from Days 0–7 contained 30µM L-ascorbic acid (Sigma-Aldrich,
   USA).

Co-culture of iFBs setup

Preparation of iFBs

   On day 10 post-differentiation initiation, iFBs were passaged using
   0.25% trypsin-EDTA for 5 min at 37 °C. Following detachment, cells were
   collected in FGM, counted using a hemocytometer, and resuspended in
   culture medium. For co-culture experiments, iFBs were seeded at 3 000
   cells/cm^2 onto the Matrigel-coated basal side of inverted transwell
   inserts (Corning, USA). Cells were allowed to adhere and settle for
   45 min at 37 °C in a humidified incubator with 5% CO₂. The inserts were
   then placed into standard culture wells containing FGM supplemented
   with 10µM Y-27,632 for submerged culture. Cells were maintained under
   these conditions for 24 h prior to the introduction of organ-specific
   cell types.

Direct co-culture setup

   The following day, keratinocytes, NHBEs, iPSC-derived cardiomyocytes,
   or ASC-derived jejunal cells (Fig. [51]S1) were seeded on the apical
   side of the same transwell insert at an appropriate cell density for
   each cell type. This configuration allowed cells to be placed in close
   proximity on opposite sides of the same porous membrane, allowing
   localised signalling, thereby constituting a direct co-culture system.
   Direct co-cultures were maintained for 7 days in respective media
   (RPMI-1640 + B27 with insulin for cardiac, EpiLife for dermal,
   PneumaCult ExPlus for pulmonary, EIF for intestinal). iFBs were then
   collected for analysis; control iFBs were maintained separately but in
   the same media for direct comparison.

Indirect co-culture setup

   For indirect co-culture, iFBs were seeded on a Matrigel-coated plate at
   a cell density of 3 × 10^4 cm^2; a transwell with organ-specific cells
   was placed above. After 7 days, some co-cultures were harvested, while
   others had the insert removed and were cultured for another 7 days to
   assess the persistence of co-culture effects.

Harvesting of cells

   After the specified culture period, iFBs were harvested by gentle
   scraping. The cells from multiple wells were pooled, washed with PBS,
   and processed immediately or stored at − 80 °C for subsequent analyses.
   All experiments were performed in triplicate to ensure reproducibility.

RNA quantification

   The quantity and quality of the RNA samples were assessed using the
   following methods. Preliminary quality control was performed on 1%
   agarose gel electrophoresis to test RNA degradation and potential
   contamination. Sample purity and preliminary quantitation were measured
   using Bioanalyzer 2100 (Agilent Technologies, USA) and it was also used
   to check the RNA integrity and final quantitation.

Library construction, quality control and sequencing of the library

   For library preparation, we used the Novogene NGS RNA Library Prep Set
   (PT042). The mRNA present in the total RNA sample was isolated with
   magnetic beads of oligos d(T)25 (Vazyme, China). This method is known
   as polyA-tailed mRNA enrichment. Subsequently, mRNA was randomly
   fragmented and cDNA synthesis proceeds using random hexamers and the
   reverse transcriptase enzyme. Once the synthesis of the first chain was
   finished, the second chain was synthesised with the addition of an
   Illumina buffer (non-directional library preparation). With this and
   together with the presence of dNTPs, RNase H and polymerase I from E.
   Coli, the second chain was obtained by Nick translation. Resulting
   products underwent purification, end-repair, A-tailing and adapter
   ligation. Fragments of the appropriate size were enriched by PCR, where
   indexed P5 (AATGATACGGCGACCACCGAGA (5’-3’)) and P7
   (CGTATGCCGTCTTCTGCTTG-P7’ (5’-3’)) primers were introduced with final
   products purified.

   The library was checked with Qubit 2.0 (Invitrogen, USA) and real-time
   PCR (Thermo Fisher Scientific, USA) for quantification and bioanalyzer
   Agilent 2100 for size distribution detection. Quantified libraries were
   pooled and sequenced on the Illumina Novaseq X platform, according to
   effective library concentration and data amount using the paired-end
   150 strategy (PE150).

RNA-seq and principal component analysis

   Reads were mapped against the human genome v. GRCh38
   ([52]http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/human/),
   p7 using the STAR aligner [[53]12] v. 2.7.3a
   ([54]https://github.com/alexdobin/star/releases). Gene counts were
   obtained through featureCounts program [[55]13] v. 2.0.3
   ([56]http://subread.sourceforge.net). Counts were log-normalised using
   the rlog function from the DESeq2 package [[57]14] v. 1.38
   ([58]https://bioconductor.org/packages/DESeq2/). Principal components
   were calculated using the R function prcomp, and Pearson correlation
   coefficients were calculated between the samples using the principal
   components.

Pathway enrichment analysis

   Selected KEGG pathways were retrieved using the keggList() and
   keggGet() functions from the KEGGREST R package. Gene symbols were
   extracted and standardised to uppercase. Ensembl gene IDs from the
   expression matrix were mapped to HGNC symbols using the biomaRt package
   (hsapiens_gene_ensembl dataset). Differential expression results were
   obtained from a custom pipeline built with the Rseasnap package
   ([59]https://github.com/bihealth/Rseasnap). For each group comparison,
   genes with|log₂ fold change| ≥ 1 and adjusted p-value (padj) ≤ 0.05
   were selected. For each pathway, the top 10 DEGs were identified and
   visualised in heatmaps using the pheatmap package.

Single-cell semiprofiler

   Single-cell deconvolution of bulk RNAseq data was done as according to
   Wang et al. [[60]15]. This approach allowed us to estimate deeply the
   composition of cell types within complex tissue samples by leveraging
   reference single-cell transcriptomic data. As our reference single-cell
   transcriptomic data, we utilised the comprehensive dataset from the
   Tabula Sapiens project, which provides a high-resolution single-cell
   transcriptomic atlas across multiple human tissues [[61]15].

   To tailor this reference dataset to our specific analysis, we applied
   filtering criteria to isolate and retain only cells annotated as
   fibroblasts. Additional filtering was applied, selecting up to 2,000
   cells per subtype with at least 1,000 cells, and removed low-quality
   cells (expressing < 200 genes or genes detected in < 5 cells) to
   construct a refined fibroblast-specific reference matrix. As we lacked
   single-cell RNA-seq data from our own samples, this curated dataset
   served as a biologically relevant reference under the assumption that
   primary fibroblast subtype diversity is broadly representative of our
   iFB populations (Fig. [62]S4).

   The resulting fibroblast-specific single-cell profiles were integrated
   into the scSemiProfiler model to estimate the relative abundance and
   heterogeneity of fibroblast populations within our iFB bulk RNA-seq
   samples.

Targeted gene expression via RT-qPCR

   For targeted gene expression analysis, markers were selected due to
   their expression in organ-resident fibroblasts. For example, POSTN and
   TBX20 mark cardiac fibroblasts involved in ECM remodelling and heart
   development; KRT14 and MMP2 are indicative of dermal identity; NPNT and
   HHIP reflect pulmonary fibroblast functions linked to lung matrix
   interactions; and BMP4, FBLN1, and CXCL12 serve as markers for
   intestinal fibroblasts, with CXCL12 reflecting broader fibroblast
   activity.

   Total RNA was extracted from iFBs. Briefly, models were lysed in
   PureLink RNA Mini Kit lysis buffer (Invitrogen, USA). RNA was isolated
   according to the manufacturer’s protocol. Total RNA was quantified, and
   cDNA was synthesised, using iScript™ cDNA Synthesis Kit (Bio-Rad
   Laboratories, USA). The subsequent RT-qPCR was performed using SYBR
   Green I Master Mix (Bio-Rad Laboratories, USA). 18 S served as a
   housekeeping gene control. Primer sequences are listed in Supplemental
   Table [63]1.

Statistical analysis

   Statistical analysis was performed with RStudio Version 2024.09.1 + 394
   and GraphPad Prism 10 (Version 10.4.1) software. Values are expressed
   as means ± SEM from at least three biological replicates. A one-way
   ANOVA was used for the comparison of > two parametric groups. P <.05
   were considered statistically significant.

Results

iPSC-derived fibroblasts exhibit mesenchymal features and loss of
pluripotency

   To confirm the generation of fibroblast-like cells from iPSCs, we
   performed morphological and molecular characterisation across early
   stages of differentiation. Immunofluorescence staining confirmed the
   expression of canonical pluripotency markers OCT4 and NANOG in
   undifferentiated iPSCs, indicating a robust starting pluripotent
   population (Fig. [64]1A). Upon initiation of differentiation, iPSCs
   underwent marked morphological changes between day 0 and day 4,
   adopting an elongated, spindle-shaped morphology characteristic of
   mesenchymal cells (Fig. [65]1B).

   Consistent with a mesenchymal transition, immunofluorescence analysis
   at day 10 revealed high expression of vimentin and α-smooth muscle
   actin (ASMA), both markers associated with fibroblast identity and
   cytoskeletal reorganisation (Fig. [66]1C). At the transcriptional
   level, qPCR analysis demonstrated a significant upregulation of
   vimentin and PDGFRA, two key fibroblast-associated genes, in iFBs
   compared to undifferentiated iPSCs (Fig. [67]1D). These data confirm
   successful downregulation of pluripotency and acquisition of
   fibroblast-like characteristics prior to co-culture.

Co-cultured iFB RNAseq analysis

   To assess transcriptional responses of iFBs in different
   microenvironments, iFBs were co-cultured with human keratinocytes
   (KCs), bronchial epithelial cells (NHBE), myocardial cells (iPSC-CMs),
   and intestinal cells (Fig. [68]2A). Each co-culture was maintained in
   cell-specific media, with corresponding medium-only controls. Following
   co-culture, iFBs were subjected to bulk RNA-sequencing. PCA-based
   correlation and expression heatmaps (Fig. [69]2B, Fig. [70]S4) revealed
   clustering of co-cultured iFBs with primary fibroblasts from their
   respective dermal, cardiac, and pulmonary tissues, indicating
   transcriptional alignment and similarity. This clustering was
   consistent across three independent iPSC lines.

Fig. 2.

   [71]Fig. 2
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   (A) Schematic representation illustrating culture conditions leading to
   iFB differentiation, followed by co-culture configurations for cardiac,
   dermal, pulmonary, and intestinal cells on the apical side of the
   transwell with fibroblasts seeded on the underside of the transwell.
   (B) PCA correlation heatmap comparing RNA-seq datasets of iFBs with
   cardiac (cFB), dermal (dFB), and normal human lung fibroblasts (NHLFs),
   and intestinal fibroblasts demonstrating tissue-specific
   transcriptional adaptations. (C) Expression of organ-specific
   fibroblast markers across all four iFB-co-cultures relative to
   independently cultured iFBs in fibroblast maintenance medium, FGM,
   measured via qPCR. All data are presented as mean ± SEM, n = 3 per cell
   line per condition. One-way ANOVA was performed, *P <.05, **P <.01,
   ***P <.001, P****<0.0001

   To validate transcriptional adaptations, we performed a head-to-head
   comparison of co-cultured iFBs with tissue-derived fibroblasts,
   selecting key markers based on their known relevance to specific organ
   environments. Targeted qPCR analysis (Fig. [73]2C) showed varying
   degrees of organ specificity, consistent with Fig. [74]2B and Fig.
   [75]S3A. POSTN, MMP2, and NPNT were preferentially upregulated in
   cardiac, dermal, and pulmonary iFB co-cultures, respectively. In
   contrast, HHIP and KRT14 were broadly induced across multiple
   co-culture conditions. As a representative sample, HHIP was tested in
   both primary cardiac and lung fibroblasts, with no significant
   difference in gene expression found between them (Fig. [76]S3B). BMP4
   and FBLN1 exhibited strong induction in intestinal co-cultures but were
   also significantly elevated in other contexts. For example, FBLN1 was
   also upregulated in dermal conditions, and BMP4 showed increased
   expression across all co-culture conditions compared to controls
   (Fig. [77]2C).

Pathway enrichment analysis

   Pathway analysis of differentially expressed genes revealed that iFBs
   respond to co-culture conditions with distinct transcriptional
   adaptations (Fig. [78]3, Fig. [79]S3A), though overall pathway
   enrichment was modest across the pathways examined. Compared to iFBs
   maintained in tissue-specific basal medium alone, co-cultured iFBs
   exhibited significant alterations in key signalling pathways associated
   with tissue-specific fibroblast function.

Fig. 3.

   [80]Fig. 3
   [81]Open in a new tab

   Heatmaps depicting differentially expressed (DE) genes across key KEGG
   pathways in iFBs. Groups include iFBs co-cultured with iPSC-derived
   cardiomyocytes (coculture_ipsc_cm), keratinocytes (coculture_kc), NHBEs
   (coculture_nhbe), and ASC-derived jejunal cells (coculture_jejunum)
   compared to the expression of independently cultured iFBs in the
   respective basal medium of co-culture e.g. EpiLife, PneumaCult ExPlus

   In cardiac co-cultures, genes within the TGF-β signalling pathway were
   significantly upregulated. Calcium signalling components were also
   elevated. Wnt signalling showed strong context-specific modulation:
   cardiac iFBs upregulated WNT7A, LGR5, and SOX17, while dermal iFBs
   exhibited a general downregulation of these Wnt related genes.

   The ECM receptor interaction pathway was notably enriched in dermal
   iFBs, with a diverse expression profile suggesting robust ECM
   remodelling activity. In contrast, pulmonary iFBs, while clustering
   near primary lung fibroblasts in global transcriptional space
   (Fig. [82]2, Fig. [83]S4), exhibited limited activation of canonical
   pathways associated with lung fibroblast identity.

   Distinct pathway activation patterns were also observed between
   intestinal and pulmonary iFBs, despite their shared endodermal origin.
   PI3K-Akt pathway components were significantly upregulated in
   intestinal co-cultures (Fig. [84]S2C), and fibroblasts derived from
   intestinal and pulmonary co-cultures clustered separately in PCA
   analysis and volcano plot (Fig. [85]2B, Fig. [86]S2B), indicating
   transcriptional divergence.

Single-cell deconvolution

   To further characterise the transcriptional profiles of iFBs, we
   applied scSemiProfiler to deconvolute bulk RNA-seq data and infer
   single-cell-like transcriptomes (Fig. [87]4). This analysis generated
   inferred single-cell-like transcriptomes, which were subsequently
   compared to a reference atlas of over 20,000 fibroblast single-cell
   RNA-seq profiles from the Tabula Sapiens database [[88]15, [89]16].
   Across all co-culture conditions, iFBs exhibited heterogeneous
   transcriptional identities, comprising a mixture of fibroblast subtypes
   rather than converging on a uniform, tissue-specific signature.

Fig. 4.

   [90]Fig. 4
   [91]Open in a new tab

   The stacked bar plot represents the proportional distribution of
   fibroblast subtypes across iFB conditions, as inferred from
   SemiProfiler against a reference set of over 20,000 primary fibroblast
   single-cell RNA sequencing profiles. “Other Fibroblasts” (a
   heterogeneous pool spanning various organs such as liver, uterine, and
   mammary tissues)

   Compared to their iFB Medium Control counterparts, direct co-culture
   with tissue-specific cells led to an increased representation of
   relevant fibroblast subtypes—cardiac, dermal, intestinal (small and
   large), and pulmonary (distal, medial, proximal), and a concurrent
   reduction in “Other” fibroblasts, defined as 21 reference fibroblast
   types not targeted in this study (e.g., bladder, liver, pancreas).
   Cardiac and dermal co-cultured iFBs adopted a tissue-specific
   fibroblast subtype of above 25% each after 7 days of co-culture. iFBs
   with intestinal co-culture displayed an increased proportion of both
   large (purple) and small (red) intestinal fibroblasts, without
   appearing to distinctly favour one over another. Large intestinal
   fibroblasts and pulmonary distal fibroblasts only appeared visibly
   present in their respective iFB intestinal and pulmonary co-cultures.
   All iFB populations retained mixed transcriptomic contributions from
   both targeted and non-targeted fibroblast lineages.

Direct vs. indirect co-culture

   In indirect co-culture systems utilising transwell inserts to
   physically separate iFBs from organ-specific cells (Fig. [92]5A), we
   observed persistent morphological adaptations in cardiac and dermal
   iFBs when comparing co-cultured versus medium-only controls
   (Fig. [93]5B). These changes were accompanied by detectable
   transcriptional shifts, with some changes substantially attenuated
   compared to direct co-culture conditions where iFBs interact with
   neighbouring cells across a shared transwell membrane (Fig. [94]5C).

Fig. 5.

   [95]Fig. 5
   [96]Open in a new tab

   (A) Scheme of direct and indirect co-culture systems, illustrating the
   transwell configuration for indirect co-culture. (B) Representative
   bright-field images of iFBs after 7 days of indirect co-culture and 7
   days post-co-culture with cardiac, dermal, pulmonary, and intestinal
   cells. (C) Transcript expression of organ-specific markers measured via
   qPCR. “Indirect” refers to transwell co-culture conditions where iFBs
   were continuously exposed to paracrine signals. “Indirect (removed)”
   indicates iFBs that were co-cultured indirectly, then removed from
   co-culture and cultured alone for an additional 7 days prior to
   analysis. Abbreviations: NHLFb– normal human lung fibroblast; cFB–
   cardiac fibroblast; dFB– dermal fibroblast. Data are presented as
   mean ± SEM, n = 3 cell lines per condition. One-way ANOVA was
   performed, *P <.05, **P <.01, ***P <.001, P****<0.0001

   For instance, in direct co-culture, MMP2 and FBLN1 transcript levels
   approached those of primary fibroblasts (MMP2 fold-change = 0.86, FBLN1
   fold-change = 1.06, relative to primary fibroblasts), whereas in
   indirect co-culture they remained lower (MMP2 fold-change = 0.42, FBLN1
   fold-change = 0.28, relative to primary fibroblasts). Markers such as
   POSTN, TBX20, and HHIP however retained elevated expression under
   indirect conditions relative to isolated iFBs without co-culture.

   Some transcriptional responses to indirect co-culture were not
   maintained upon removal of the paracrine stimulus. For example, TBX20
   expression declined from a fold-change of 0.77 during co-culture to
   0.26 post-removal, suggesting transient effects. Morphological changes
   were more pronounced between the different media controls than between
   the culture conditions (Fig. [97]5B).

Discussion

   This study set out to determine whether iFBs can acquire
   transcriptional tissue-specific traits through co-culture with
   epithelial and mesoderm cells from different organs. Using a
   transwell-based co-culture system, we explored the transcriptional
   plasticity of iFBs with the ultimate aim of assessing their suitability
   for integration into complex, human-based models of high biomimicry.
   Our data demonstrate that iFBs exhibit notable transcriptional
   plasticity in response to co-culture with cells from all three distinct
   germ layers, clustering alongside their primary fibroblast counterparts
   in the PCA heatmap. This responsiveness was consistent across multiple
   iPSC lines, suggesting that co-culture indeed contextually tune iFBs,
   potentially bypassing the need for lineage-specific differentiation
   protocols. Although fibroblast plasticity is well-established [[98]17,
   [99]18] this finding demonstrates that iFBs acquire transcriptional
   traits of mesodermal, ectodermal, and endodermal fibroblasts when
   exposed to diverse tissue-specific microenvironments.

   To evaluate the fidelity of this plasticity, we assessed the expression
   of markers enriched in organ-resident fibroblasts. While several
   organ-specific markers, such as POSTN (cardiac FB) and MMP2 (dermal
   FB), showed tissue-paired upregulation, others, including BMP4 and
   FBLN1, were induced across multiple co-culture conditions, despite
   their intestinal fibroblast associations [[100]19, [101]20]. This
   pattern may reflect either shared fibroblast programs or generalised
   responses to juxtacrine/paracrine signals [[102]3, [103]20]. These
   observations are consistent with the known limitations of classical
   fibroblast markers [[104]20] which often lack strict tissue exclusivity
   due to overlapping roles in ECM remodelling, wound repair, and
   inflammation. For instance, the widespread induction of BMP4 across
   conditions, despite its role in intestinal mesenchyme development
   [[105]19] points to a conserved epithelial-mesenchymal signalling that
   transcends tissue boundaries. Collectively, these findings emphasise
   iFB flexibility in diverse microenvironments and highlight the ongoing
   challenge of defining truly lineage-restricted fibroblast markers.

   Building on these observations, we investigated whether iFB
   transcriptional plasticity translates into pathway-level differences
   across co-culture conditions. Fibroblasts behaviour is finely tuned to
   their organ of origin and varies considerably across both
   organ-specific and intra-organ subtypes [[106]3, [107]21]. In cardiac
   co-cultures, for example, genes in the TGF-β pathway were upregulated,
   in line with the central role of cardiac fibroblasts in myocardial
   repair [[108]22] alongside elevated calcium signalling genes supporting
   cardiomyocyte electrophysiology and excitation-contraction coupling
   [[109]23].

   In contrast, iFBs cultured in non-cardiac environments exhibited
   distinct and sometimes opposing transcriptional programmes. Wnt
   signalling was modulated in a context-dependent manner: cardiac
   co-cultured iFBs upregulated WNT7A, LGR5, and SOX17, genes associated
   with cardiac development and regeneration [[110]24–[111]26] whereas
   downregulated Wnt-related components in dermal iFBs may be indicative
   of a quiescent fibroblast state focussing on skin barrier maintenance
   over active regeneration [[112]27, [113]28]. Dermal iFBs also displayed
   broad expression in the ECM receptor interaction pathway, underscoring
   the complex and diverse roles of dermal fibroblasts in ECM remodelling
   across fibroblast populations in the skin [[114]29].

   Pulmonary iFB co-cultures presented a more complex picture. iFBs
   co-cultured with NHBEs clustered with primary lung fibroblasts at a
   global level (Fig. [115]2B, Fig. [116]S4), but failed to activate
   canonical lung pathways such as TGF-β/Smad [[117]30], suggesting that
   tissue-specific traits may be underrepresented in our setup.
   Interestingly, despite their shared endodermal origin, intestinal and
   pulmonary iFBs exhibited divergent pathway activation profiles. This
   divergence likely reflects organ-specific physiological demands: lung
   fibroblasts prioritise structural maintenance and immune modulation to
   sustain barrier integrity in a relatively low-turnover environment,
   whereas intestinal fibroblasts promote PI3K-Akt pathway activity to
   support rapid epithelial renewal and mucosal repair in the intestine’s
   high-renewal niche [[118]31].

   The modest pathway enrichment across co-culture conditions may reflect
   a relatively quiescent iFBs state, absent of activating cues. For
   example, pulmonary fibrosis-associated markers like CTHRC1 were not
   induced [[119]32] suggesting that pro-inflammatory, mechanical or
   injury-related cues are necessary to reveal key tissue-specific
   features.

   To reconcile global and pathway-level discrepancies, we applied
   scSemiProfiler to deconvolute bulk RNA-seq data against Tabula Sapiens
   fibroblast references. Rather than adopting uniform organ-specific