Induced Pluripotent Stem Cell Differentiation Protocols

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• What are Induced Pluripotent Stem Cells?
• iPSC Collection
• Frequently Asked Questions about iPSCs
• Related Products
• References

What are Induced Pluripotent Stem Cells?

Adult somatic cells can be reprogrammed into induced pluripotent stem cells (iPSCs) with the overexpression of key reprogramming genes (OCT4, KLF4, SOX2, cMYC, NANOG and LIN28). Human iPSCs have the unique ability to differentiate into any cell type of the body including:

• Ectodermal: Neuron, Astrocyte, Oligodendrocyte, Retinal Epithelial Cell (RPE), Epidermal, Hair and Keratinocytes.
• Endodermal: Hepatocyte, Pancreatic β-islet Cell, Intestinal Epithelial Cell, Lung Alveolar Cells.
• Mesodermal: Hematopoietic, Endothelial Cell, Cardiomyocyte, Smooth Muscle Cell, Skeletal Muscle Cell, Renal cell, Adipocyte, Chondrocyte and Osteocytes.

Figure 1. iPSC Pathway

iPSC Collection

We offer a large collection of cell culture media, supplements, bioactive small molecules, and growth factors used to control the cell fate of human iPSCs. The table below highlights the most widely used protocols, media and characterization antibodies used to differentiate human iPSCs into different cell lineages.

Differentiated Cell Type	Media and Supplements	Characterization Antibodies	Reference
Neural Stem Cell	DMEM/F12, Glutamine, Neurobasal Media, N2, B27, SB431542, CHIR99021, Compound E, Human LIF, Noggin, bFGF, EGF Order Complete Media	Nestin, PAX6, OTX2	Highly efficient neural conversion of human ES and iPS cells by dual inhibition of SMAD signaling1
Cortical Neuron	DMEM/F12, Glutamine, Neurobasal Media, N2, B27, SB431542, CHIR99021, Compound E, Noggin, bFGF, EGF Order Complete Media	MAP2, TBR1, CTIP2, VGLUT1	Directed differentiation of human pluripotent stem cells to cerebral cortex neurons and neural networks2
Dopaminergic Neuron	DMEM/F12, Glutamine, Neurobasal Media, N2, B27, SB431542, CHIR99021, Compound E, Human LIF, SHH, FGF8, BDNF, GDNF, TGFβ3, cAMP Order Complete Media	TH, TUJ-1, LMX1A, FOXA2, NURR1	Directed differentiation of dopamine neurons from human pluripotent stem cells3
Motor Neurons	DMEM/F12, Glutamine, Neurobasal Media, N2, B27, SB431542, CHIR99021, Compound E, all-trans retinoic acid (ATRA), SHH, BDNF, CNTF, GDNF	Nestin, TUJ-1, ChAT, Islet1, Hb9, Hoxa2	Directed differentiation of human-induced pluripotent stem cells generates active motor neurons4
Astrocyte	DMEM/F12, Glutamine, B27, nonessential amino acids, Penicillin-Streptomycin, FBS, bFGF, CNTF, BMP4, Activin A, Heregulin 1β, IGF-1	GFAP, TUJ-1, CD44	Efficient Generation of Astrocytes from Human Pluripotent Stem Cells in Defined Conditions5
Oligodendrocyte	DMEM/F12, Glutamine, Neurobasal Media, N2, B27, SB431542, CHIR99021, Compound E, Human LIF, all-trans retinoic acid (ATRA), SHH, SAG, PDGF, IGF-I, NT3, Insulin, T3, cAMP	PAX6, OLIG2, NKX2.2, O4, SOX10, MBP, MAP2	Efficient Generation of Myelinating Oligodendrocytes from Primary Progressive Multiple Sclerosis Patients by Induced Pluripotent Stem Cells6
Cardiomyocyte	RPMI 1640, B27, rH-albumin, L-ascorbic acid 2-phosphate, Lactate, CHIR99021, Wnt-C59	TNNT2, α-SMA, α-Actinin, vWF, MLC2A, MLC2V	Chemically defined generation of human cardiomyocytes7
Skeletal Muscle	IMDM, FBS, Glutamine, Penicillin-Streptomycin, nonessential amino acids, 2-mercaptoethanol, oleic acid, linoleic acid, iron sulfate, sodium ferric gluconate, Horse Serum, Y-27632, bFGF	CD13, CD31, CD56, CD44, CD45, CD49b, CD146, MyHC	Efficient derivation and inducible differentiation of expandable skeletal myogenic cells from human ES and patient-specific iPS cells8
Vascular Endothelial/ Smooth Muscle	DMEM/F12, Glutamine, Neurobasal Media, N2, B27, CHIR99021, BIO, Y-27632, BMP4, VEGF, Forskolin, PDGF-BB, Activin A, Heparin	CD31, CD144, vWF, I-CAM1, SMA, MyHC, VECAD, PECAM	Generation of vascular endothelial and smooth muscle cells from human pluripotent stem cells9
Hepatocyte	RPMI 1640, B27, Activin A, BMP4, bFGF, HGF, Oncostatin M	FOXA2, SOX17, GATA4, HNF4-α, AFP, ALB	Highly Efficient Generation of Human Hepatocyte–like Cells from Induced Pluripotent Stem Cells10
Pancreatic β-cell	DMEM/F12, IMDM, bovine serum albumin, N2, B27, ITS, BMP4, Activin A, FGF7, Noggin, bFGF, EGF, nicotinamide, Exendin-4, all-trans retinoic acid (ATRA)	PDX1, FOXA2, SOX9, HNF1β, c-peptide, Insulin, Somatostatin	Highly efficient differentiation of human ES cells and iPS cells into mature pancreatic insulin-producing cells11
Lung	DMEM/F12, Glutamine, B27, N2, ascorbic acid, monothioglycerol, bovine serum albumin, Penicillin-Streptomycin, Y-27632, Dorsomorphin, SB431542, IWP2, CHIR99021, BMP4, bFGF, Activin A, FGF-10, FGF7,  EGF, all-all-trans retinoic acid (ATRA)	FOXA2, SOX2, NKX2.1, p63	Efficient generation of lung and airway epithelial cells from human pluripotent stem cells12

Frequently Asked Questions about iPSCs

1. Where are the challenges with stem cell differentiation, especially with respect to iPSCs?

• Efficiency and Reproducibility: Despite advancements, directing iPSCs to differentiate into specific cell types can still be inconsistent. Improving the consistency and reliability of differentiation protocols is crucial for their broader application in research and clinical settings. Furthermore, different iPSC lines may exhibit varying efficiencies in differentiating into specific germ layers, with some iPSC lines showing enhanced differentiation towards mesoderm compared to endoderm, and vice versa.
• Heterogeneity of Differentiated Cell Populations: Even successful differentiation often results in heterogeneous cell populations with varying maturity, functionality, and purity. Controlling for and minimizing this heterogeneity is essential for obtaining uniform and functional cell populations for downstream applications.
• Maturation and Functionality: Achieving mature and functional iPSC-derived cells is challenging. Many cell types may exhibit immature phenotypes or functional deficiencies compared to native counterparts, so improving differentiation protocols is vital for enhancing clinical translation.
• Scale-Up and Automation: Scalable and automated differentiation platforms are needed to produce large quantities of consistent and high-quality cell products for clinical applications. Developing robust manufacturing processes to meet regulatory standards is crucial for commercialization.

2. How can scientists improve their stem cell differentiation results?

• Optimize Culture Conditions: Fine-tuning the culture medium composition, including growth factors, cytokines, small molecules, and supplements, can significantly influence the differentiation efficiency and specificity of stem cells. Iterative optimization of culture conditions based on systematic experimentation and feedback is essential for achieving reproducible and robust differentiation outcomes.
• Use Defined and Chemically Defined Media: Transitioning from complex and undefined culture systems to defined and chemically defined media formulations reduces variability and enhances the control over differentiation processes. Defined media formulations contain only well-characterized components facilitate standardization, scalability, and regulatory compliance, particularly for clinical applications.
• Employ Biomimetic Culture Systems: Mimicking the physiological microenvironment of cells by utilizing biomimetic culture systems, such as 3D scaffolds, organ-on-a-chip platforms, and co-culture systems, enhances the relevance and fidelity of in vitro differentiation models. These systems provide spatial cues, cell-cell interactions, and mechanical stimuli that better recapitulate tissue architecture and function, promoting more physiologically relevant differentiation outcomes.

You can also integrate multi-omics approaches, utilize single-cell analysis, employ genome editing for precision control, and implement machine learning and data integration to improve differentiation results. 

3. What are the biggest mistakes you see researchers making with iPSC differentiation protocols?

While researchers continue to make significant progress in stem cell differentiation protocols, several common mistakes can hinder the success and reproducibility of their experiments, such as:

• Lack of Optimization: Failing to thoroughly optimize differentiation protocols for specific cell types and experimental conditions can lead to variable or inconsistent outcomes. Researchers may overlook the importance of systematically testing various culture conditions, including growth factors, cytokines, substrate properties, and culture duration, to identify the optimal conditions for robust and reproducible differentiation.
• Inadequate Characterization: Insufficient characterization of differentiated cell populations can obscure the heterogeneity, maturity, and functionality of the cells produced. Researchers may overlook the need for comprehensive phenotypic and functional analyses, including immunostaining, flow cytometry, gene expression profiling, and functional assays, to validate the identity and quality of differentiated cells.
• Failure to Address Heterogeneity: Ignoring or inadequately addressing the heterogeneity within differentiated cell populations can compromise the reliability and interpretability of experimental results. Researchers may overlook the importance of purifying or enriching specific cell subsets, such as using fluorescence-activated cell sorting (FACS) or magnetic cell sorting, to obtain homogeneous cell populations for downstream analyses or applications.
• Poor Reproducibility: Neglecting to document and standardize experimental procedures, reagent preparations, and cell handling protocols can impede reproducibility across different laboratories or experiments. Researchers may overlook the significance of maintaining detailed records, following standardized operating procedures, and sharing protocols and reagents with the scientific community to facilitate reproducibility and transparency.
• Ignoring Quality Control Measures: Underestimating the importance of quality control measures, such as monitoring cell viability, purity, and sterility throughout the differentiation process, can lead to experimental artifacts or contamination issues. Researchers may overlook the need for regular cell line authentication, mycoplasma testing, and endotoxin screening to ensure the integrity and safety of cell cultures.
• Overreliance on 2D Culture Systems: Relying solely on traditional 2D culture systems without considering the limitations of these platforms in recapitulating complex tissue architecture and microenvironmental cues can yield suboptimal differentiation outcomes. Researchers may overlook the advantages of employing 3D culture systems, organoid models, or microfluidic devices to better mimic in vivo tissue physiology and enhance differentiation efficiency and functionality.
• Insufficient Data Analysis and Interpretation: Inadequate data analysis and interpretation can lead to misinterpretation or oversimplification of complex experimental results. Researchers may overlook the importance of applying appropriate statistical methods, data visualization techniques, and computational tools to analyze high-dimensional datasets and extract meaningful insights from their experiments.

4. How can technology help with stem cell differentiation protocols and results?

Technology plays a pivotal role in advancing stem cell differentiation protocols and improving the outcomes of these experiments in several ways:

1. High-Throughput Screening (HTS): Automated platforms equipped with robotics, liquid handling systems, and imaging devices enable high-throughput screening of large compound libraries or culture conditions to identify factors that promote or inhibit stem cell differentiation. HTS accelerates the discovery of novel small molecules, growth factors, or culture media formulations that enhance differentiation efficiency and specificity.
2. Omics Technologies: Advances in genomics, transcriptomics, proteomics, and metabolomics allow for comprehensive profiling of stem cells and their differentiated progeny at the molecular level. Integration of multi-omics data provides insights into the regulatory networks, signaling pathways, and key biomarkers associated with different stages of differentiation, guiding the optimization of differentiation protocols and the identification of novel targets for modulating cell fate decisions.
3. Genome Editing Tools: Precise genome editing technologies, such as CRISPR-Cas9, enable targeted manipulation of gene expression, epigenetic modifications, and signaling pathways involved in stem cell differentiation. Genome editing allows researchers to engineer stem cells with desired phenotypic traits, enhance differentiation efficiency, and model genetic diseases in vitro, facilitating the study of disease mechanisms and the development of personalized therapies.

References

1. Chambers SM, Fasano CA, Papapetrou EP, Tomishima M, Sadelain M, Studer L. 2009. Highly efficient neural conversion of human ES and iPS cells by dual inhibition of SMAD signaling. Nat Biotechnol. 27(3):275-280. https://doi.org/10.1038/nbt.1529

2. Shi Y, Kirwan P, Livesey FJ. 2012. Directed differentiation of human pluripotent stem cells to cerebral cortex neurons and neural networks. Nat Protoc. 7(10):1836-1846. https://doi.org/10.1038/nprot.2012.116

3. Ma L, Liu Y, Zhang S. 2011. Directed Differentiation of Dopamine Neurons from Human Pluripotent Stem Cells.411-418. https://doi.org/10.1007/978-1-61779-201-4_30

4. Karumbayaram S, Novitch BG, Patterson M, Umbach JA, Richter L, Lindgren A, Conway AE, Clark AT, Goldman SA, Plath K, et al. 2009. Directed Differentiation of Human-Induced Pluripotent Stem Cells Generates Active Motor Neurons. 27(4):806-811. https://doi.org/10.1002/stem.31

5. Shaltouki A, Peng J, Liu Q, Rao MS, Zeng X. 2013. Efficient Generation of Astrocytes from Human Pluripotent Stem Cells in Defined Conditions. 31(5):941-952. https://doi.org/10.1002/stem.1334

6. Douvaras P, Wang J, Zimmer M, Hanchuk S, O’Bara M, Sadiq S, Sim F, Goldman J, Fossati V. 2014. Efficient Generation of Myelinating Oligodendrocytes from Primary Progressive Multiple Sclerosis Patients by Induced Pluripotent Stem Cells. Stem Cell Reports. 3(2):250-259. https://doi.org/10.1016/j.stemcr.2014.06.012

7. Burridge PW, Matsa E, Shukla P, Lin ZC, Churko JM, Ebert AD, Lan F, Diecke S, Huber B, Mordwinkin NM, et al. 2014. Chemically defined generation of human cardiomyocytes. Nat Methods. 11(8):855-860. https://doi.org/10.1038/nmeth.2999

8. Maffioletti SM, Gerli MFM, Ragazzi M, Dastidar S, Benedetti S, Loperfido M, VandenDriessche T, Chuah MK, Tedesco FS. 2015. Efficient derivation and inducible differentiation of expandable skeletal myogenic cells from human ES and patient-specific iPS cells. Nat Protoc. 10(7):941-958. https://doi.org/10.1038/nprot.2015.057

9. Patsch C, Challet-Meylan L, Thoma EC, Urich E, Heckel T, O’Sullivan JF, Grainger SJ, Kapp FG, Sun L, Christensen K, et al. 2015. Generation of vascular endothelial and smooth muscle cells from human pluripotent stem cells. Nat Cell Biol. 17(8):994-1003. https://doi.org/10.1038/ncb3205

10. Si-Tayeb K, Noto FK, Nagaoka M, Li J, Battle MA, Duris C, North PE, Dalton S, Duncan SA. 2010. Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells. Hepatology. 51(1):297-305. https://doi.org/10.1002/hep.23354

11. Zhang D, Jiang W, Liu M, Sui X, Yin X, Chen S, Shi Y, Deng H. 2009. Highly efficient differentiation of human ES cells and iPS cells into mature pancreatic insulin-producing cells. Cell Res. 19(4):429-438. https://doi.org/10.1038/cr.2009.28

12. Huang SXL, Islam MN, O'Neill J, Hu Z, Yang Y, Chen Y, Mumau M, Green MD, Vunjak-Novakovic G, Bhattacharya J, et al. 2014. Efficient generation of lung and airway epithelial cells from human pluripotent stem cells. Nat Biotechnol. 32(1):84-91. https://doi.org/10.1038/nbt.2754