In Vitro Neuroscience Toolkit

This toolkit gives in vitro neuroscientists practical steps for strengthening credibility across study planning, experimental work and post-analysis reporting. It focuses on cell identity, variability, contamination, controls, data management and transparent sharing. 
Planning your study

Authenticate cell lines 

Cell line verification should be routine practice in any in vitro laboratory. Authenticity cannot be guaranteed simply because a cell line or culture came from a commercial source. Verification can include sequencing key variable genomic regions, comparative genomic hybridisation arrays, genotype testing at relevant single nucleotide polymorphisms, and testing for chromosomal aberrations. 

Where induced pluripotent stem cell lines are used, cell banks are preferable where possible because they are more likely to provide standard operating procedures and basic quality control data. Examples in the original toolkit included the Tau Consortium, EBiSC and the UK Stem Cell Bank. 

Check regional and cell type identity 

When differentiating neural cell types from iPSCs, researchers should check regional identity carefully. Different cell lines may differ in their propensity to generate a given tissue, and epigenetic marks may bias expression of patterning genes. Each cell line and protocol combination should therefore be checked for the desired regional and cell type identity. 

Markers can be tested using immunofluorescence staining and/or RT-PCR. These should distinguish neural and non-neural identity, identify germ layer and, where relevant, distinguish telencephalon, diencephalon, midbrain, hindbrain or spinal cord. More specific regional identity should also be examined where the interpretation depends on it. 

Address variability 

For iPSC studies of neurodegenerative and other diseases, genetic background can be a major source of variability between cell lines. Small samples may miss important genetic signals. Where iPSCs are used to study genetic disease, it may be better to use more donors than to use more lines from the same donor, depending on the research question. 

Tackle batch effects 

Organoid and other three-dimensional in vitro systems can show variability between cell lines and batches. Researchers should familiarise themselves with the tissue they are trying to model, use the available literature and in vivo models to recognise what represents a good sample, and check tissue identity before taking samples forward. 

Preregister the study 

Preregistration can reduce bias and build confidence by documenting the rationale, hypotheses, methods and intended analyses before the study begins. General registries such as OSF and AsPredicted can be used. Registered Reports may also be appropriate where a journal offers this format

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During your study:

Test for contamination 

Mycoplasma testing should be routine practice. Many laboratories recommend testing every one to two months. Methods include PCR, enzymatic approaches and easy-to-use kits that require only a sample of used media, so cells do not need to be sacrificed. 

Avoid routine antibiotic use 

New lab members should be trained in proper sterile technique in the absence of antibiotics or antimycotics. Routine antibiotic use can mask poor technique and allow mycoplasma contamination to spread. Antibiotics and antimycotics should generally be reserved for specific circumstances, such as thawing a precious newly purchased cell line or performing clonal selection before precious lines have been frozen down. 

Use correct controls 

Controls should match the experimental manipulation. Examples include vehicle controls when treating cells, equivalent empty vectors during transfections or infections, negative or scrambled controls in knock-down experiments, and untreated cells to assess whether the control condition itself affects the cells. 

Manage data throughout the study 

In vitro studies can generate complex and heterogeneous data. A clear data management plan should specify naming conventions, storage locations, metadata, raw data retention, versioning and responsibility for maintaining records. Electronic lab notebooks can support consistency across the lab and improve continuity when staff change. 

After data collection:

Share data and materials where possible 

Sharing data, protocols, code and materials can strengthen transparency and help others evaluate or reuse the work. This is most useful when shared outputs are well documented, linked to the publication and deposited in a stable repository. Sensitive data, proprietary materials and ethical constraints should be considered early and explained clearly. 

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References and links 
  • Open Science Framework: https://osf.io/ 
  • AsPredicted: https://aspredicted.org/ 
  • European Bank for induced pluripotent Stem Cells: https://ebisc.org/ 
  • UK Stem Cell Bank: https://www.nibsc.org/science_and_research/advanced_therapies/uk_stem_cell_bank.aspx 
  • Lancaster Lab protocols and regional marker resources: [Review] check current URL before publication. 

 

This toolkit was produced with guidance from Credibility Advisory Board member Dr Madeline Lancaster originally in 2020, and updated with content from BNA webinars and other sources in 2023.