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Coding cells for more accurate cell models in neurodegeneration

By Dr Farah Patell-Socha, VP of Research Products at bit.bio

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Although several drugs are available to control neurodegenerative disease symptoms, therapeutics that ‘cure’ such diseases have proved evasive.

Neurodegenerative diseases are a devastating group of conditions that include Huntington’s, Parkinson’s and Alzheimer’s disease, in addition to frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS).

Although several drugs are available to control neurodegenerative disease symptoms, therapeutics that ‘cure’ such diseases have proved evasive. This issue partly stems from the complex and poorly understood cellular pathologies that underlie neurodegenerative disease.

As scientists do not have access to reproducible cell models, the generation of translatable and reflective data has suffered from poor reproducibility, and our ability to assess the efficacy of candidate therapeutics has been limited.

Ultimately, a reliable supply of consistent and physiologically relevant human cell models will enable disease researchers to perform more relevant experiments with improved reliability, contributing to decreased development times and overall discovery costs for neurodegenerative disease therapeutics.

Achieving consistent cell models at scale

Induced Pluripotent Stem Cells (iPSCs) offer the industry translatable cell models that address the challenges of inconsistent experimental data.

Scientists have developed various methods to convert iPSCs into desired cell types.

The classical method, directed differentiation, utilises small molecules, cytokines, or cocktails of both to trigger a differentiation cascade similar to early fetal development. iPSCs treated in this way mimic development, with the ability to achieve a myriad of cell fates.

However, this approach can often take months and lead to mixed cell populations with low purity and poor yields. This is not ideal when scientists require large numbers of such cells throughout drug discovery and development.

Efforts to circumvent the challenges of directed differentiation have “reprogrammed” iPSCs into desired cell types by overexpressing transcription factors inserted into the genome using retroviruses.

In turn, the transcription factors activate the genes that define cell fate and so result in a more homogenous cell population in a shorter period of time.

Transcription factor-driven cell reprogramming can shorten the time to somatic cell production to weeks compared to months for equivalent directed differentiation-based workflows. It can also provide higher yields with more precise cell subtypes.

However, as explained previously, a homogeneous and defined population of cells is required to achieve reliable results for improved drug discovery efforts.

Gene silencing, a cell’s natural genetic “off switch”, can turn off the aberrant overexpression of genes leading to undesirable, inconsistent and unpredictable transcription factor expression, ultimately hindering consistent iPSC conversion.

bit.bio’s new precision cell reprogramming platform, opti-ox (optimised induced overexpression) overcomes gene silencing with an inducible transcription factor expression system placed into specific genomic sites that are not affected by gene silencing.

Such precision control over transcription factor expression means that bit.bio can produce consistent populations of billions of cells in 10-14 days.

Being able to address the issue of gene silencing and its undesirable consequences allows for the robust manufacturing of cells that are defined at their sub-cell identity, for example, microglia versus macrophage.

One crucial additional benefit provided by precision reprogramming is the consistency in genotype and phenotype across batches of cells.

This technology can significantly decrease the time and resources required in front-end validation when used at key stages of drug discovery and development, such as in target identification and high throughput screening.

Combining precision reprogramming with CRISPR for a generation of new disease models

Precision reprogramming can also be used in conjunction with advanced gene-editing techniques to create accurate human disease models.

For example, bit.bio has employed CRISPR/Cas9 gene editing to introduce an abnormal expansion of 50 CAG repeats into the first exon of the Huntingtin gene within iPSC-derived glutamatergic neurons.

An abnormal expansion of (greater than) ≥ 40 CAG repeats in the first exon of the Huntingtin gene leads to the development of Huntington’s Disease.

Precisely making only the disease-relevant mutation, then matching the resulting cell model with its wild-type human ioGlutamatergic Neurons has allowed bit.bio to create a disease model with a genetically matched control.

Scientists can directly compare data from the disease model and the control, enabling the study of novel potential treatments in a disease-relevant system.

These precision disease cell models and their corresponding genetically matched control offer the drug discovery and development community the opportunity to assess candidate drugs in a highly relevant human background, making it possible to understand candidate drug efficacy and toxicity as early as possible.

A consistent supply of relevant human disease and control cells enables scientists to perform, more relevant experiments with improved reliability.

The role of human cells in the future of medicine

At bit.bio, we believe that access to a consistent supply of required human cell types will help identify and define the next generation of medicine.

As it becomes possible to precision reprogram iPSCs into more and more human cell types, this approach will start to impact positively not only on the ability to study and accelerate potential therapeutics for neurodegenerative diseases but also on a wider range of disease areas, ultimately benefiting humans as well as our wider society.

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  1. Pingback: 'Silent' genes may be tapped for new antibiotics | Health Tech World

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