Predictive bioinformatic platforms for direct cellular reprogramming: Mogrify Ltd
Have you ever imagined one day we could have our liver, kidney or heart regenerated from our own skin cells, to replace our failed or damaged organs, without the need to wait for transplants from a suitable donor? Research studies in cellular reprogramming, targeting this prospect, have become a hot topic in recent decades. A new bioinformatic start-up, Mogrify Ltd, aiming to transform the development of cell therapies and to develop scalable off-the-shelf cell therapies, seems worth our attention.
Mogrify Ltd is situated in the Bio-Innovation Centre in Cambridge Science Park in the UK. According to the press release of the company on this March, the company has a headcount of over 60 scientific, operational, and commercial staff.1 The main technology products of the company are two computation prediction platforms, MOGRIFY and EpiMOGRIFY, which are useful to facilitate the development of cell therapies.2,3 The company was incorporated in 2016 and was launched in February 2019. However, the development of its first computational prediction platform, MOGRIFY version 1, was started in 8 years previously in 2011. The second platform, EpiMOGRIFY, was launched in 2020.4 Both platforms were validated and the results were published in peer reviewed journals.5,6
Why did Mogrify Ltd develop the two computational prediction platforms? Why are the two platforms developed by Mogrify Ltd useful tools to facilitate the development of cell therapies? Let us briefly explore the development of direct cellular reprogramming, an important area in regenerative medicine.
Background of direct cellular reprogramming
As early as 1958, an experimental finding suggested that terminally-differentiated cells have a certain degree of plasticity and can be reprogrammed to alter cell fate.7 Nearly 30 years later, a single transcription factor (an enzyme protein that binds to a particular DNA sequence and regulates the expression of genes), MyoD, was shown to convert fibroblasts (the most common type of cell found in connective tissue) directly to myoblasts (embryonic progenitor cells that differentiate to form muscle cells).8 However, later findings suggested that a single factor is not sufficient to drive cellular reprogramming for most tissues. Since then, different combinations of key transcription factors and microRNAs, which are developmental regulators of the target cell lineage, have been identified to convert fibroblasts to various cell types with therapeutic purposes.9,10,11
Traditionally, “minus-one” strategy is used to identify the combination of key transcription factors and microRNAs to convert mature cells to another mature cell type. In brief, scientists start with combinatorial screening using a pool of transcription factors and microRNAs, which are chosen according to the domain knowledge of the scientist on the biological networks controlling cell differentiation, to convert one cell type to another differentiated (mature, fully functional) cell type. Once the pool of the biological factors are experimentally proved to be efficient for the cell conversion, then a “minus-one” strategy is used to identify essential factors by removing one factor at a time from the pool, aiming at minimal combination required for cell conversion.
However, this method can be very time-consuming. Take for example an experiment which converted dermal or cardiac fibroblasts to induced cardiomyocyte (heart cells for contraction)-like cells: it was originally started with a pool of nearly 20 transcription factors and a similar number of miRNAs. “Minus-one” strategy was used to finally identify 3 key transcription factors for the cell conversion. You can imagine that it was a long, exhaustive task of trial and error.10 Moreover, the mechanism for direct reprogramming is cell type specific and still largely unknown for many cell types.
In addition, most of the converted cells cannot stay where they are after adding key biological factors for conversion. They either end up converted back to what they were, or rapidly exit the cell cycle and don’t proliferate. This is because cell fate is actually controlled by the epigenetic state, the regulation mechanism that happens on the DNA level, of each cell. Only the change in DNA level can bring permanent change in the fate of cells. Chemicals, microRNAs, and transcription factors with appropriate culture conditions which change the epigenetic state of cells could permanently change the cell fate. The addition of transcription factors and micro RNA which do not affect the change in DNA level can bring only a temporary conversion of the cells.
In general, traditional direct cell conversion method is not time efficient, and it is hard to produce stable, scalable converted cells for clinical applications. This presents a big challenge to the cell therapies which rely on converted cells using traditional direct cell conversion methods.
The two predictive computational platforms, MOGRIFY and epiMOGRIFY, were developed by Mogrify Ltd. to address the problems mentioned above. MOGRIFY® predicts transcription factors which promote any cell conversion from any source cell types.2 EpiMOGRIFY identifies culture conditions with optimal combinations of transcription factors or growth factors required to maintain cell identity and epigenetically support the reprogramming of cells in chemically-defined media. These two platforms could help speed up the direct cell conversion process, and help to develop stable and scalable resulting cells that can meet clinical needs.
Data sources such as FANTOM5 and ENCODE, which were being incorporated to develop MOGRIFY® and epiMOGRIFY, have emerged thanks to the advances in developmental biology research and discovery, over the last two decades, of gene networks that drive cell fate.
To be continued.
References
1. Mogrify wins Hewitsons Award for Innovation in Business and Price Bailey Award for Business of the Year at CambridgeshireLive Business Excellence Awards 2020. Mogrify press release, 26 March, 2021. https://mogrify.co.uk/mogrify-wins-hewitsons-award-for-innovation-in-business-and-price-bailey-award-for-business-of-the-year-at-cambridgeshirelive-business-excellence-awards-2020/
2. MOGRIFY® PLATFORM. Systematically predict the transcriptomic switches required to produce any target cell type from any source cell type. Mogrify website. https://mogrify.co.uk/science/mogrify/
3. EpiMOGRIFY PLATFORM. Systematically identify the epigenetically-predicted factors required to drive and maintain cell identity. Mogrify website. https://mogrify.co.uk/science/epimogrify/
4. Our history. Mogrify Ltd website. https://mogrify.co.uk/about-us/
5. O.J.L. Rackham, J. Firas, and H. Fang, et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, March 2016, Vol. 48, No. 3.
6. U.S. Kamaraj, J. Chen, K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 11, 509–522, November 18, 2020.
7. J.B. Gurdon, T.R. Elsdale, and M. Fischberg. Sexually mature individuals of Xenopus laevis from the transplantation of single somatic nuclei. Nature, 1958, 182, 64–65.
8. R.L. Davis, H. Weintraub, and A.B. Lassar. Expression of a single transfected cDNA converts fibroblasts to myoblasts. Cell, 1987, 51, 987–1000.
9. K. Batta, M. Florkowska, and V. Kouskoff, et al. Direct reprogramming of murine fibroblasts to hematopoietic progenitor cells. Cell Rep., 2014, 9:1871–1884.
10. M., Ieda, J.D. Fu, and P. Delgado-Olguin, et al. Direct reprogramming of fibroblasts into functional cardiomyocytes by defined factors. Cell, 2010, 142:375–386.
11. T. Vierbuchen, A. Ostermeier, and Z.P. Pang, et al. Direct conversion of fibroblasts to functional neurons by defined factors. Nature, 2010, 463:1035–1041.
Have you ever imagined one day we could have our liver, kidney or heart regenerated from our own skin cells, to replace our failed or damaged organs, without the need to wait for transplants from a suitable donor? Research studies in cellular reprogramming, targeting this prospect, have become a hot topic in recent decades. A new bioinformatic start-up, Mogrify Ltd, aiming to transform the development of cell therapies and to develop scalable off-the-shelf cell therapies, seems worth our attention.
Mogrify Ltd is situated in the Bio-Innovation Centre in Cambridge Science Park in the UK. According to the press release of the company on this March, the company has a headcount of over 60 scientific, operational, and commercial staff.1 The main technology products of the company are two computation prediction platforms, MOGRIFY and EpiMOGRIFY, which are useful to facilitate the development of cell therapies.2,3 The company was incorporated in 2016 and was launched in February 2019. However, the development of its first computational prediction platform, MOGRIFY version 1, was started in 8 years previously in 2011. The second platform, EpiMOGRIFY, was launched in 2020.4 Both platforms were validated and the results were published in peer reviewed journals.5,6
Why did Mogrify Ltd develop the two computational prediction platforms? Why are the two platforms developed by Mogrify Ltd useful tools to facilitate the development of cell therapies? Let us briefly explore the development of direct cellular reprogramming, an important area in regenerative medicine.
Background of direct cellular reprogramming
As early as 1958, an experimental finding suggested that terminally-differentiated cells have a certain degree of plasticity and can be reprogrammed to alter cell fate.7 Nearly 30 years later, a single transcription factor (an enzyme protein that binds to a particular DNA sequence and regulates the expression of genes), MyoD, was shown to convert fibroblasts (the most common type of cell found in connective tissue) directly to myoblasts (embryonic progenitor cells that differentiate to form muscle cells).8 However, later findings suggested that a single factor is not sufficient to drive cellular reprogramming for most tissues. Since then, different combinations of key transcription factors and microRNAs, which are developmental regulators of the target cell lineage, have been identified to convert fibroblasts to various cell types with therapeutic purposes.9,10,11
Traditionally, “minus-one” strategy is used to identify the combination of key transcription factors and microRNAs to convert mature cells to another mature cell type. In brief, scientists start with combinatorial screening using a pool of transcription factors and microRNAs, which are chosen according to the domain knowledge of the scientist on the biological networks controlling cell differentiation, to convert one cell type to another differentiated (mature, fully functional) cell type. Once the pool of the biological factors are experimentally proved to be efficient for the cell conversion, then a “minus-one” strategy is used to identify essential factors by removing one factor at a time from the pool, aiming at minimal combination required for cell conversion.
However, this method can be very time-consuming. Take for example an experiment which converted dermal or cardiac fibroblasts to induced cardiomyocyte (heart cells for contraction)-like cells: it was originally started with a pool of nearly 20 transcription factors and a similar number of miRNAs. “Minus-one” strategy was used to finally identify 3 key transcription factors for the cell conversion. You can imagine that it was a long, exhaustive task of trial and error.10 Moreover, the mechanism for direct reprogramming is cell type specific and still largely unknown for many cell types.
In addition, most of the converted cells cannot stay where they are after adding key biological factors for conversion. They either end up converted back to what they were, or rapidly exit the cell cycle and don’t proliferate. This is because cell fate is actually controlled by the epigenetic state, the regulation mechanism that happens on the DNA level, of each cell. Only the change in DNA level can bring permanent change in the fate of cells. Chemicals, microRNAs, and transcription factors with appropriate culture conditions which change the epigenetic state of cells could permanently change the cell fate. The addition of transcription factors and micro RNA which do not affect the change in DNA level can bring only a temporary conversion of the cells.
In general, traditional direct cell conversion method is not time efficient, and it is hard to produce stable, scalable converted cells for clinical applications. This presents a big challenge to the cell therapies which rely on converted cells using traditional direct cell conversion methods.
The two predictive computational platforms, MOGRIFY and epiMOGRIFY, were developed by Mogrify Ltd. to address the problems mentioned above. MOGRIFY® predicts transcription factors which promote any cell conversion from any source cell types.2 EpiMOGRIFY identifies culture conditions with optimal combinations of transcription factors or growth factors required to maintain cell identity and epigenetically support the reprogramming of cells in chemically-defined media. These two platforms could help speed up the direct cell conversion process, and help to develop stable and scalable resulting cells that can meet clinical needs.
Data sources such as FANTOM5 and ENCODE, which were being incorporated to develop MOGRIFY® and epiMOGRIFY, have emerged thanks to the advances in developmental biology research and discovery, over the last two decades, of gene networks that drive cell fate.
To be continued.
References
1. Mogrify wins Hewitsons Award for Innovation in Business and Price Bailey Award for Business of the Year at CambridgeshireLive Business Excellence Awards 2020. Mogrify press release, 26 March, 2021. https://mogrify.co.uk/mogrify-wins-hewitsons-award-for-innovation-in-business-and-price-bailey-award-for-business-of-the-year-at-cambridgeshirelive-business-excellence-awards-2020/
2. MOGRIFY® PLATFORM. Systematically predict the transcriptomic switches required to produce any target cell type from any source cell type. Mogrify website. https://mogrify.co.uk/science/mogrify/
3. EpiMOGRIFY PLATFORM. Systematically identify the epigenetically-predicted factors required to drive and maintain cell identity. Mogrify website. https://mogrify.co.uk/science/epimogrify/
4. Our history. Mogrify Ltd website. https://mogrify.co.uk/about-us/
5. O.J.L. Rackham, J. Firas, and H. Fang, et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, March 2016, Vol. 48, No. 3.
6. U.S. Kamaraj, J. Chen, K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 11, 509–522, November 18, 2020.
7. J.B. Gurdon, T.R. Elsdale, and M. Fischberg. Sexually mature individuals of Xenopus laevis from the transplantation of single somatic nuclei. Nature, 1958, 182, 64–65.
8. R.L. Davis, H. Weintraub, and A.B. Lassar. Expression of a single transfected cDNA converts fibroblasts to myoblasts. Cell, 1987, 51, 987–1000.
9. K. Batta, M. Florkowska, and V. Kouskoff, et al. Direct reprogramming of murine fibroblasts to hematopoietic progenitor cells. Cell Rep., 2014, 9:1871–1884.
10. M., Ieda, J.D. Fu, and P. Delgado-Olguin, et al. Direct reprogramming of fibroblasts into functional cardiomyocytes by defined factors. Cell, 2010, 142:375–386.
11. T. Vierbuchen, A. Ostermeier, and Z.P. Pang, et al. Direct conversion of fibroblasts to functional neurons by defined factors. Nature, 2010, 463:1035–1041.
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