Mouse Cardiac Fibroblasts (MCF)

Overview

Mouse Cardiac Fibroblasts (MCF) is a cell model used for research applications where physiologically relevant identity and donor background support interpretation of experimental readouts. Mouse Fibroblasts derived from Heart (Cardiac) within the Cardiovascular system.

The cardiac fibroblasts (CF) are the principal cell type of the heart. They provide structural support for cardiac myocytes, are a source of paracrine growth factors, and are an important cellular component of myocardial responses to injury. CF are responsible for extracellular matrix synthesis in the heart during development and pathological conditions. Their proliferation and matrix synthesis is essential for scar formation at sites of myocardial infarction [1], cardiac fibrosis, and is often complicated by cardiac hypertrophy [2]. CF also respond to changes in microenvironments in pathological conditions by modulating integrin expression [3]. CF culture has been widely used as a model to study the cardiac matrix remodeling by physiological (exercise) and pathological (hypertension) stressors. iXCells Biotechnologies provides high quality Mouse cardiac fibroblasts (MCF), which are isolated from postnatal day 2 mouse heart and cryopreserved at P0, with >0.5 million cells in each vial. MCF express fibronectin and are negative for HIV-1, HBV, HCV, mycoplasma, bacteria, yeast, and fungi. They can further expand for 5 population doublings in Fibroblast Growth Medium (Cat# MD-0011) under the condition suggested by iXCells Biotechnologies.

Key elements and design rationale

• Cell identity: Fibroblasts (Primary Cells)
• Source context: Heart; Cardiac; Cardiovascular
• Donor background: Age: Postnatal
• Biosafety level: BSL-1 (follow your institution’s biosafety program and local regulations)

Product-specific elements (such as tissue source, donor background, and cell classification) help frame how results should be interpreted across assays and experimental conditions.

Biological background

Fibroblasts are key stromal cells that produce and remodel extracellular matrix, coordinate wound repair, and shape tissue microenvironments through paracrine signaling.

Across primary and specialty cell models, experimental outcomes can be influenced by donor heterogeneity, passage history, confluence, and media composition. For interpretation, it is common to validate key markers or functional phenotypes in the user’s assay context and to document culture variables consistently.

Research relevance and current trends

• Increasing use of primary and specialty cells to improve translational relevance for target biology and phenotypic screening.
• Adoption of 3D culture formats and co-culture systems to better capture tissue microenvironments and cell–cell interactions.
• Integration of functional readouts with single-cell and multi-omics profiling to connect phenotype with molecular state.
• Use of flow/shear and barrier-focused assays to study vascular inflammation, permeability, and angiogenic remodeling.

Common research applications

• Profile identity markers by flow cytometry or immunostaining in cultured cells
• Quantify functional responses to defined stimuli relevant to the model system
• Compare baseline phenotype across donors/conditions using gene expression profiling
• Evaluate angiogenic behavior using migration and tube-formation readouts (assay dependent)
• Screen compounds or genetic perturbations for phenotype modulation using viability or imaging endpoints

Interpretation typically focuses on how a perturbation (e.g., cytokine exposure, metabolic stress, genetic manipulation, or compound treatment) shifts marker profiles or functional readouts relative to an appropriate control matched for donor and culture variables.

Notes for experimental interpretation

• Donor-to-donor heterogeneity can influence baseline phenotype and treatment response; include biological replicates when feasible.
• Passage number, confluence, and media composition can shift gene expression and functional readouts; track and report these variables consistently.
• Contamination control (including routine mycoplasma monitoring) supports reproducibility in downstream assays.
• Use appropriate negative/positive controls for the readout (e.g., unstimulated controls, pathway agonists/antagonists) to contextualize observed changes.

SKU:BHC18500087

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