Thursday 30 September 2021

Regenerative medicine- Direct and indirect cell reprogramming

Regenerative medicine-Direct and indirect cell reprogramming
My last three blog posts commented on direct cell reprogramming. You may be wondering if there is a technology called indirect cell reprogramming. The answer is yes. It is formally called induced pluripotent stem cell (iPSC, cells that have the ability to become any cell in the body)-mediated reprogramming, and it was developed earlier than direct cell reprogramming. In this blog post, I give a brief introduction of the two technologies and the challenges faced by both technologies.

Both reprogramming technologies involve the conversion of one cell type into another, target, cell type, intended for therapeutic use. Usually, the conversion starts by using the most abundant cells in the body, such as human fibroblast cells, a type of cell found in connective tissue.

Indirect cell reprogramming
Indirect cell reprogramming is a technology that converts somatic cells to another type of cell via first transitioning through an intermediate state, induced pluripotent stem cells (iPSCs).1 Therefore it is also called induced pluripotent stem cell (iPSC)-mediated reprogramming. The iPSCs have similar properties as embryonic stem cells in having unlimited differentiation capacity, while avoiding the ethical issues related to embryonic stem cells.2 Moreover, as iPSCs are generated from patients, this eliminates the problem of tissue rejection following transplantation in patients. Once iPSCs are generated, the cells can then be directed for development and differentiation, to form desired cells.

Four main transcription factors (Oct3/4, Sox2, Klf4, c-Myc), called Yamanaka factors, that induce somatic cells into pluripotent states, were first identified by Japanese scientists, and the finding was published in 2006.1 These transcription factors are highly expressed in embryonic stem cells, and are able to induce pluripotency in both mouse and human somatic cells.1

Since the generation of the first induced pluripotent cells, some progress has been made to improve the quality of the iPSCs generated and the efficiency of the technology. Methods include:
1) replacing of c-Myc, which is oncogenic and may cause tumour formation, in many protocols of pluripotent cell induction;3-6
2) using of viral delivery systems, such as an adenovirus, which does not integrate into the recipient’s DNA.7,8 This choice of virus is because a retrovirus, which is used for delivery of the four factors in the original protocol, would integrate into host’s DNA and cause insertional mutagenesis, which increases the risk of tumorigenicity;
3) replacing the original Yamanaka factors by small molecules and chemical compounds. This could also avoid the use of retrovirus;9
4) expressing Yamanaka factors for a shorter time for induction. This saves the time required to generate, expand and differentiate pluripotent cells, and avoids the creation of teratomas, a rare type of tumor that can contain fully-developed tissues and organs.10-12

Direct cell reprogramming
Direct cell reprogramming, also called transdifferentiation, is the conversion of a fully functional cell type into cell type of other lineage. The process bypasses a state of pluripotency. Transdifferentiation between some cell types can occur naturally in response to injury, and can be induced experimentally. I have made a brief introduction to transdifferentiation technology in a previous blog post.

A major limitation of direct cell reprogramming is the identification of reprogramming factors that promote conversion to a specific target cell type. The conventional strategy, which screens through a list of transcription factors that are important for the development of the target cells, is a time-consuming and laborious process. There are a few predictive software applications developed to facilitate the process. These include MOGRIFY13 and epiMOGRIFY14 which we mentioned in the last three blog posts, CellNet,15,16 and the one developed by Massachusetts Institute of Technology (MIT).17

Challenges faced by the two technologies
As you can see from the general description of the two technologies, direct cell reprogramming is faster, cost-effective and more accessible than iPSC-based protocols. Direct cell reprogramming protocols do not use Yamanaka factors, which are licensed, to induce pluripotency. The technology does not involve ex vivo cell expansion and transplantation, as in iPSC-mediated reprogramming.

However, both technologies face the same problem of scalability, which could impede their therapeutic applications. For the direct cell conversion approach, most converted cells could either experience cell cycle arrest that limit the expansion of the cell populations, or they tend to revert back to what they were. This lowers the number of cells available for further use. Similarly, for the indirect cell reprogramming, forced differentiation of induced pluripotent stem cells to distinct lineages also leads to the problem of cell cycle arrest and inability to expand. Moreover, the efficiency of inducing mature cells into pluripotency is less than 4%, which is very low.18

Quality of induced pluripotent stem cells generated from the indirect cell reprogramming is also a concern. The iPSCs generated are highly tumorigenic.1 This maybe due to the fact that the iPSCs are mostly derived from somatic cells of aged individuals. The risk that comes with this source of cells is the incidence of spontaneously occurring tumours, which commonly increases exponentially with aging. Concerns related to tumorigenicity and teratoma formation by these cells hamper their direct applicability.

Both direct and indirect cell reprogramming have been developed for more than a decade, and the technologies provide a feasible method to generate cells for biological studies, tissue engineering or transplantation. Diseases such as diabetes, heart failure, arthritis, and many more, which affect a high proportion of the world population, are hopefully to be treatable from the cell reprogramming technologies. Although no cell-based therapy has yet been officially approved in any country in the world, once the challenges mentioned above are overcome, the clinical application of this technology may not be far away.

1. K. Takahashi, and S. Yamanaka. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 2006, 126 (4): 663–76.
2. B. Lo, and L.Parham. Ethical issues in stem cell research. Endocrine Reviews, Volume 30, Issue 3, 1 May 2009, Pages 204–213.
3. J. Han, P. Yuan, H. Yang, et al. Tbx3 improves the germ-line competency of induced pluripotent stem cells. Nature, 2010;463:1096–100.
4. J. Chen, J. Liu, J. Yang, et al. BMPs functionally replace Klf4 and support efficient reprogramming of mouse fibroblasts by Oct4 alone. Cell Res., 2011;21:205–12.
5. H.Y. Li, Y. Chien, Y.J. Chen, et al. Reprogramming induced pluripotent stem cells in the absence of c-Myc for differentiation into hepatocyte-like cells. Biomaterials. 2011;32:5994–6005.
6. M. Maekawa, K. Yamaguchi, T. Nakamura, et al. Direct reprogramming of somatic cells is promoted by maternal transcription factor Glis1. Nature, 2011;474:225–9.
7. N, Fusaki, H. Ban, A. Nishiyama, et al. Efficient induction of transgene-free human pluripotent stem cells using a vector based on Sendai virus, an RNA virus that does not integrate into the host genome. Proc. Jpn. Acad. Ser.B., 2009;85:348–62.
8. W. Zhou, and C.R. Freed. Adenoviral gene delivery can reprogram human fibroblasts to induced pluripotent stem cells. Stem Cells, 2009;27(11): 2667–74.
9.X. Li, J. Xu, and H. Deng. Small molecule-induced cellular fate reprogramming: promising road leading to Rome. Curr. Opin. Genet. Dev., 2018, 52, 29–35.
10. L. Kurian, I. Sancho-Martinez, E. Nivet, et al. Conversion of human fibroblasts to angioblast-like progenitor cells. Nat. Methods, 2013; 10:77–83.
11. M. Thier, P. Wörsdörfer, Y.B. Lakes, et al. Direct conversion of fibroblasts into stably expandable neural stem cells. Cell Stem Cell. 2012; 10:473–479.
12. A. Ocampo, P. Reddy, P. Martinez-Redondo, et al. In vivo amelioration of age-associated hallmarks by partial reprogramming. Cell, 2016 December 15; 167(7): 1719–1733.e12.
13.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.
14. 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, 2020, 11, 509–522, November 18.
15. S.A. Morris, P. Cahan, H. Li, et al. Dissecting engineered cell types and enhancing cell fate conversion via CellNet. Cell, 2014, 158, 889–902.
16. P. Cahan, H.Li, S.A. Morris. et al. CellNet: network biology applied to stem cell engineering.Cell, 2014, 158, 903–915.
17. A.C. D’Alessio, Z.P. Fan, K.J. Wert, et al. A systematic approach to identify candidate transcription factors that control cell identity. Stem Cell Reports, 2015 Nov 10;5(5):763-775.
18. Rao MS, Malik N. Assessing iPSC reprogramming methods for their suitability in translational medicine. J Cell Biochem. 2012;113:3061–8.

Friday 24 September 2021

Predictive bioinformatic platforms for direct cellular reprogramming-Mogrify Ltd (final part)

Predictive bioinformatic platforms for direct cellular reprogramming: Mogrify Ltd (final part)
Since its launch, Mogrify Ltd has started several projects on different therapeutic areas of regenerative medicine, which have made use of the prediction results from its computation platform Mogrify. In this blog post, I am going to present to you what I have found from the company’s website. (I am not sponsored by them, just looking.)

Application of the prediction from MOGRIFY
Through its wholly-owned subsidiary, Chondrogenix, Mogrify Ltd has stepped into the therapeutic area of musculoskeletal diseases such as osteoarthritis. The algorithm platform MOGRIFY identified a cocktail of transcription factors for the company, Chondrogenix, to convert, in a culture dish, different starting cell types from diseased patients, into functional chondrocytes that are capable of forming cartilage. Musculoskeletal diseases are usually caused by bone or cartilage defects. This technology paved the way for them to write an application request to the regulators to enhance the FDA-approved Autologous Chondrocyte Implantation (ACI) therapy, and to create additional reprogramming therapies using cells from donors (allogenic reprogramming therapy) or by direct cell conversion in living organisms (in vivo reprogramming therapy). Chondrogenix received two phases of funding from SBRI Healthcare for this project.1,2

Mogrify Ltd is also using its computational platform to predict combinations of transcription factors to induce conversion of one cell type to another in order to produce proteins which are not produced sufficiently well by existing production systems. The resulting target cell types could provide researchers with improved access to important proteins found in human cell types that are difficult to obtain, and allow for more efficient antibody production methods for biologic drugs. This exploratory research is done with the collaboration of the MRC’s Laboratory of Molecular Biology (MRC-LMB) in Cambridge.3

In fact, Mogrify Ltd also collaborates with MRC-LMB to improve the MOGRIFY cell reprogramming platform itself. The enhanced version, MOGRIFY V2, incorporates data from next-generation sequencing and single-cell RNA sequencing into the algorithm to enhance the quality and accuracy of transcription factor predictions and cell conversion efficacy.4

Furthermore, Mogrify Ltd is also involved in allogeneic (using cells from a donor who is not the patient) T-cell immunotherapy for inflammatory and autoimmune diseases, by collaborating with Sangamo Therapeutics, a genomic medicine company in the US. Mogrify is responsible for the discovery and optimisation of the cell conversion technology from induced pluripotent stem cells (iPSCs) or embryonic stem cells (ESCs) to regulatory T cells (Tregs). Sangamo expects to then use its technology and therapeutic development capabilities to transform these Tregs cells into ready to use allogeneic therapy candidates for the treatment of inflammatory and autoimmune diseases. The resulting collaboration will hopefully accelerate the development of scalable and accessible CAR-Treg cell therapies so that the treatments can be delivered more rapidly, in a more cost-effective way to a larger patient population.5

Financial Support
Since its launch in February 2019, Mogrify Ltd has attracted investments from strategic corporate investors to strengthen its business. According to a press release of the company in May this year, Mogrify Ltd has raised a total of US$33 million from seed funding and two rounds of Series A financing. The investors include Ahren Innovation Capital, 24Haymarket, Dr. Darrin M. Disley, OBE (CEO of Mogrify Ltd), Parkwalk Advisors, Astellas Venture Management, Dr Jonathan Milner (co-founder of Abcam PLC), and the University of Bristol Enterprise Fund III.6

In March 2019, Mogrify Ltd was awarded $555,000 (£420,000) from Innovate UK, a UK innovation agency, on a data-driven cell conversions project to produce cell therapies with potential applications in wound healing and oncology immunotherapy.7

Moreover, Chondrogenix (the subsidiary of Mogrify Ltd) received two rounds of funding from SBRI Healthcare, an NHS England initiative, championed by the Academic Health Science Networks (AHSNs). These funds were awarded for the purpose of generating a safe, efficient and scalable source of cartilage cells for the treatment of cartilage defects, osteoarthritis and other musculoskeletal conditions.1,2

From the above information, it is obvious that Mogrify Ltd has ambition to develop and scale up reprogramming of cells for many autologous and allogeneic cell therapies, as well as to create in vivo reprogramming therapies (direct cell conversion in living organisms).1-3,5 The two software platforms developed by the company no doubt speed up the process of direct cellular reprogramming, by using algorithms based on the big data already available in public repositories instead of performing trial and error experimentally. With the financial support it has got so far, I have no doubt that the company, in the near future, can meet its target of producing stable reprogrammed cells at scale for some areas of cell therapies. However, the company needs to overcome some challenges when it comes to clinically applying its reprogrammed cells.

The hurdles include the safety issues regarding the components suggested by the software platforms for cell conversion. There is a possibility that some biological factors such as cMYC, when overexpressed, can cause tumour growth.10,11 The method to deliver biological factors safely is also a concern. Engineered viruses constructed to deliver transcription factors may integrate into a DNA region of target cells and cause a tumour later. In addition, the recipient’s immunity against the reprogrammed cells also needs to be addressed. These challenges, though, are also faced by other biotech companies focusing on regenerative medicine.

Besides the above-mentioned issues, I am eager to see the reports on the experiments, which apply the prediction from MOGRIFY8 and epiMOGRIFY9, to be published soon. I am also expecting Mogrify Ltd will merge the two software platforms into a single platform with synergistic power.

1. Mogrify subsidiary Chondrogenix secures funding from SBRI Healthcare to advance regenerative cartilage therapy to the clinic. Mogrify Ltd press release, 1st April, 2019.
2. Mogrify awarded $1.1M additional funding from SBRI Healthcare. Mogrify Ltd press release, 28th January, 2020.
3. Mogrify enters research collaboration with the MRC Laboratory of Molecular Biology. Mogrify Ltd press release, 11th January, 2021.
4. Mogrify solidifies IP position surrounding core technology and expands platform algorithm to enhance cell conversion. Mogrify Ltd press release, 17th December, 2020.
5. Mogrify and Sangamo announce collaboration and exclusive license agreement for Mogrify’s iPSC- and ESC-derived regulatory T cells. Mogrify Ltd press release, 21st April, 2020.
6. Mogrify completes Series A financing totalling $33 million USD. Mogrify Ltd press release, 4th May, 2021.
7. Mogrify awarded $555,000 USD (£420,000 GBP) Innovate UK funding to accelerate regenerative cell therapies. Mogrify Ltd press release, 18th March, 2019.
8. 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.
9. U.S. Kamaraj, J. Chen, and K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 2020, 11, 509–522, November 18.
10. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 2006;126:663–676.
11. Meyer N, Penn LZ. Reflecting on 25 years with MYC. Nat Rev Cancer. 2008;8:976–990

Friday 17 September 2021

Predictive bioinformatic platforms for direct cellular reprogramming- Mogrify Ltd (cont'd)

Predictive bioinformatic platforms for direct cellular reprogramming: Mogrify Ltd (cont’d)
My previous blog post presented a brief understanding of recent progress in direct cellular reprogramming and the reason for the development of two software platforms by Mogrify Ltd. This blog post is about further details of the two platforms, MOGRIFY and epiMOGRIFY.

MOGRIFY was first co-developed by two scientists, Julian Gough (Professor of Computer Science in the University of Bristol) and Owen Rackham (PhD student of Julian Gough in the University of Bristol), in 2011. They began the development of the platform by using the data from the FANTOM 5 consortium, an international consortium launched to provide gene expression data in virtually all cell types across the human body.1 In 2014, they collaborated with Jose Polo from Monash University in Australia to test cell conversions in order to validate the prediction power of MOGRIFY. In 2015, based on the prediction results from MOGRIFY, the co-founders filed a patent application for the algorithm used by the computation platform, with over 30 direct cell conversions listed as example proof of what the algorithm can achieve.2 The predictions and cell conversion results were then published in 2016.3

According to the paper, predictions from MOGRIFY have been applied on 173 human cell types and 134 tissues. In order to assess the predictive power of MOGRIFY, the performance of the algorithm was first compared against well-known, previously-published human cell conversions. MOGRIFY correctly predicted the transcription factors (enzyme proteins that bind to a particular DNA sequence and regulate the expression of genes) used in previously-published direct cell conversions from human fibroblasts (the most common type of cell found in connective tissue) into induced pluripotent stem cells,4,5,6 and from B cells/ fibroblasts into macrophage-like cells.7,8 In addition, MOGRIFY’s prediction list included four of the five transcription factors (or similar factors) used in the conversion of human dermal fibroblasts into cardiomyocytes (cells responsible for generating contractile force in the intact heart).9

The predictive capabilities of MOGRIFY® were also experimentally examined using human cells. Two cell conversions, human fibroblasts to keratinocyte cells (cell within the epidermis) and adult human keratinocyte cells to micro-vascular endothelial cells (cells isolated from small vessels within skin tissue), were performed using prediction results from MOGRIFY. By examining the morphological and molecular characterization of the reprogrammed cells, the conversions were found to be successful.3

The results showed that MOGRIFY provides a practical and efficient mechanism to facilitate the reprogramming of human cells.

However, since the publication of the results in 2016, no further reports of cell conversions using predictions from MOGRIFY, have been published, or at least I was not able to find any after extensive searches.

Once the cells are converted from other cell types, it is important to maintain the reprogrammed cells’ identity, as the converted cells tend to revert back to what they were before. Difficulty maintaining the differentiated cells makes a large-scale production of these differentiated cells hard to achieve. This can be a hurdle for the development of cell therapies.

EpiMOGRIFY was developed with the aim of identifying optimal culture conditions (with suggested small molecules and chemical compounds) required to maintain cell identity or induce cell conversion in chemically-defined media. The computation algorithm incorporated gene-regulatory information data and cell epigenetic landscapes for more than 100 human cells and tissues, from the ENCODE and Epigenome Roadmap consortia, to define culture conditions that can maintain the phenotype and function of the converted cell, or that can be used to induce cell conversion.10

The EpiMOGRIFY platform was co-developed by Duke-NUS Medical School (Professors Enrico Pettreto and Owen Rackham), Monash University (Professor Jose Polo) and Mogrify Ltd. Owen Rackham and Jose Polo were the co-developers of MOGRIFY.11

Experiments validating the computational prediction in cell culture conditions for cell maintenance and differentiation have recently been published.12 Using the suggestion factors predicted from EpiMOGRIFY, astrocytes (cells commonly found in the brain) and cardiomyocytes (cells that make up heart muscle) were able to grow as effectively, in terms of cell numbers and proliferation rate, as they are in the culture conditions that have long been used. Moreover, these cells appeared to better maintain their morphology, in terms of the biological structure and the presence of key markers for the cell types, when growing in the culture conditions with biological factors suggested from EpiMOGRIFY. These results provide a fundamental proof for EpiMOGRIFY’s predictive power to suggest culture conditions that are able to maintain a stable phenotype.12

Furthermore, using the cell conversion conditions predicted from EpiMOGRIFY, neural progenitors and embryonic stem cells were able to differentiate to astrocyte cells and cardiomyocyte cells, respectively. The differentiation efficiency was as good as that of existing differentiation protocols.12 These results indicate that EpiMOGRIFY is highly accurate in identifying biological factors for cell conversion as well.

To be continued.

1. Our history. Mogrify Ltd website.
3. 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.
4. K. Takahashi, K. Tanabe, M. Ohnuki, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell, 2007, 131, 861–872.
5. J. Yu, M.A. Vodyanik, K. Smuga-Otto. et al. Induced pluripotent stem cell lines derived from human somatic cells. Science, 2007, 318, 1917–1920. 6. D. Huangfu, K. Osafune, R. Maehr, et al. Induction of pluripotent stem cells from primary human fibroblasts with only Oct4 and Sox2. Nat. Biotechnol., 2008, 26, 1269–1275.
7. H. Xie, M. Ye, R. Feng, & T. Graf. Stepwise reprogramming of B cells into macrophages. Cell, 2004, 117, 663–676.
8. F. Rapino, E.F. Robles, J.A. Richter-Larrea, et al. C/EBPα induces highly efficient macrophage transdifferentiation of B lymphoma and leukemia cell lines and impairs their tumorigenicity. Cell Reports, 2013, 3, 1153–1163.
9. J. D. Fu, N.R. Stone, L. Liu, et al. Direct reprogramming of human fibroblasts toward a cardiomyocyte-like state. Stem Cell Reports, 2013, 1, 235–247.
10. epiMOGRIFY PLATFORM. Systematically identify the epigenetically-predicted factors required to drive and maintain cell identity. Mogrify website.
11. Our history. Mogrify Ltd website.
12. 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.

Sunday 12 September 2021

Predictive bioinformatic platforms for direct cellular reprogramming- Mogrify Ltd

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.

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.
2. MOGRIFY® PLATFORM. Systematically predict the transcriptomic switches required to produce any target cell type from any source cell type. Mogrify website.
3. EpiMOGRIFY PLATFORM. Systematically identify the epigenetically-predicted factors required to drive and maintain cell identity. Mogrify website.
4. Our history. Mogrify Ltd website.
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.

Tuesday 7 September 2021

A story of false data

A story of false data
In fiction, cancer research is about trying to find a cure for cancer. A single cure, that fixes everybody's cancer. While this certainly makes for good stories, and would indeed be wonderful if anyone ever managed to come up with it, most real-life cancer researchers settle for a lesser goal that is still an achievement: find drugs that will slow down (or, in some cases, remove) a particular type of cancer in a particular type of person. For example, they might come up with research that only works on nose cancer in Asians, and then only works some of the time. Nevertheless this can still add years of life to some people and is therefore worth checking.

In 2013-2014 I was involved in therapeutic aspects of cancer research, in further investigation of the interplay between the PRDM1 gene and the NF-κB protein that leads to different susceptibility rates of NK/T cell lymphoma (NKTCL) cancer patients towards chemotherapeutic agents. The research team of my supervisor had a leading study using a 26S proteasome inhibitor drug, bortezomib (Velcade), to act against NK/T cell lymphoma.1 With the assumption that IL2 is an important factor in sustaining NK/T cell lymphoma, we investigated the combination treatment that can reduce bortezomib dosage by using either of the two fusion anti-IL2 receptor antibodies, basiliximab (Simulect®) and denileukin diftitox (ONTAK®). We found that IC50 (median inhibitory concentration) of NKTCL cells being treated by bortezomib can be decreased by ~53% to ~90% when combined with a low level of basiliximab. This was a promising result, but it still needed testing "in vivo" (in a live setting). As the lab I was in did not have enough live sample (and my supervisor was retiring and the grants were running out), we came up the idea of asking another lab (one in mainland China with whom we had long been in collaboration) to run the live tests for us.

I visited China, trained the people there to perform a couple of in vivo tests, and finished the job. Several months later I married and moved to the UK, and the lab in China kept informing us about the progress of their study by sending us results in pictures. Those results were coherent with the in vitro test results we had previously found in our lab. Maybe we really did have a new, more effective chemotherapy drug on our hands for people with that particular cancer type? I had to fly back to Hong Kong and check things out (we tried working remotely but the lab really wanted me there). Things seemed to be playing out like a film script, aeroplanes and all.

But sadly, our further analysis showed that the data from the China lab was very likely to be fake. I found two pictures sent at two different times, supposedly representing different samples, were actually identical. By reflecting and rotating one of the pictures later sent to me, I could not see any difference with the one that had been sent earlier. We decided not to publish it after all.

So, does our combination work? It has not been disproven. But science does not work on not disproving things, it works on positive proof. It might still be possible for other labs to re-check our combination, and we hope they will do so from our partial publications, but we were not able to show it ourselves. And we ended up being a little annoyed with that lab for faking their data (perhaps because they couldn't be bothered to run the real tests?) and causing all that excitement for nothing. But these things happen.

The quest to improve the lives of people with cancer continues, one small uncertain arduous step at a time.

1. L. Shen, W.Y. Au, T. Guo, et al. Proteasome inhibitor bortezomib-induced apoptosis in natural killer (NK)-cell leukemia and lymphoma: an in vitro and in vivo preclinical evaluation. Blood, 2007 Jul 1;110(1):469-70.

Tuesday 31 August 2021

Cambridge Open Exascale Lab

Cambridge Open Exascale Lab
Recently I have been occupyed writing coronavirus-related blog posts, but with the first round of the COVID-19 vaccination programme almost at its final stage in the UK, and the recovery of business activities, I plan to start writing more about spin-offs and other initiatives from Cambridge University that involve with latest innovative technologies.

In this blog post, I would like to introduce you a world-class supercomputer laboratory, Cambridge Open Exascale Lab, the University of Cambridge. It is dedicated to designing fast supercomputers to bring the UK’s science, health and industry into the levels of complexity and performance that previously were out of reach.

Cambridge Open Exascale Lab is part of the Cambridge Research Computing Services (RCS), formerly called the High Performance Computing (HPC) Facility when it was founded in 1996. Cambridge Research Computing Services was established with the aim of providing high performance computing services to leading scientists, medics and engineers across the whole of the UK.

Cambridge Research Computing Services currently runs two supercomputers, called Peta4 and Wilkes (named after Cambridge computing pioneer Sir Maurice Wilkes, 1913-2010). These are running at rates of peta (1015) floating-point operations per second (FLOPS, a measure of supercomputer performance when totalled across thousands of CPU cores, useful when handling scientific tasks that are highly parallelisable between many CPUs). The newly established Cambridge Open Exascale Lab aims to develop supercomputing systems running at the speed of exascale (1018) FLOPS, some 1,000 times the scale of the current systems.

What exascale supercomputing systems could bring
Countries from the United States to Europe to Japan are in the race to produce the world’s first exascale computing system. The United States Department of Energy and Intel announced that the first exaFLOPS supercomputer, Aurora, would be operational at Argonne National Laboratory in Lemont, Ilinois, by the end of 2021. The European Union has a range of exascale programmes in the works under its European High-Performance Computing Joint Undertaking. Japan is aiming for the exascale version of its Fugaku supercomputer to be available to users within a couple of years.1 You may wonder why exascale computing systems are so urgently being developed. Let’s explore.

Take the example of my field of expertise, biomedical science. In the last 10 years, a huge amount of biological data, such as genomic and proteomic data, has been generated, mainly due to the fall in price of sequencing. Combining this biological data with clinical data could help develop personalized medicine (also called precision medicine). Analysing an amalgamation of all this data tends to require computing systems with high processing capacity (and also high storage space, although this tends to be only a secondary consideration for supercomputers, because managing the processor interconnects is the most difficult task, whereas adding more storage is easy by comparison). With the invention of the exascale computing system, analysis of data from different data sources, which currently takes weeks or even months, could be shortened to hours or days, and thus allow more calculations to be explored within a research project’s time-frame. Personalized medicine could therefore be developed in a much faster pace.

In addition, exascale supercomputers will enable simulations that are more complex and of higher resolution. This allows researchers to explore the molecular interactions of viruses and their hosts, which aids in the design of vaccines.1 Imagine how it might have helped if we could have had a vaccine against SARS-CoV-2 with more than 95% efficacy designed in a few days, or even in a few hours, during the initial stages of the COVID-19 pandemic.

The exascale power will allow climate forecasters to swiftly run thousands of simulations, introducing tiny variations in the initial conditions, to provide better insight into the potentially disastrous effects of climate change.1

Besides life sciences, exascale computing is expected to benefit chemical design, pattern modelling, high-energy physics, materials science, oil exploration, and transportation.1

In view of the benefits of exascale computing systems, the opening of Cambridge Open Exascale Lab could help the UK remain at the forefront of different fields of science.

Goals of Cambridge Open Exascale Lab
An exascale supercomputer will contain some 135,000 GPUs and 50,000 CPUs, each one being a multi-core chip with many individual processing units. This immediately creates the problems of huge power consumption, and a potentially difficult method of programming to enable almost a billion instructions being executed simultaneously. Furthermore, if the system is upgraded, researchers may need to re-examine millions of lines of code and optimize them to make use of the extra hardware, so that the programs can reach as close to the theoretical maximum processing power as possible. In addition, the ability to access memory (RAM or long-term storage) and retrieve data quickly is an issue in highly interconnected supercomputers, as evidenced by Cambridge startup Ellexus (recently sold to Altair), which focused on profiling the bottlenecks of I/O (input and output) to the storage devices in supercomputers, and found this was frequently more of an issue than the software designers had realised.

The Cambridge Open Exascale Lab’s plans include: analyse supercomputer power consumption with a view to how to reduce it; provide a method of giving supercomputer time more quickly to scientists that need it for urgent work (such as those responding to pandemics and other disasters); apply an Intel-made programming framework that allows loads to be shared across heterogeneous computers (those involving more than one type of processor, which should make upgrades easier because any new processors do not have to be exactly matched to the existing ones); install faster storage systems (based on solid-state memory chips); improve fast communication between the parts of the computer; and work on new types of graphics to visualise the data produced by the supercomputer.

Cambridge Open Exascale Lab works with a broad range of industry, government, University and other partners. Its industry partners include Dell and Intel Corporation. With its aim to recruit 20 more staff in 2021, hopefully the lab will have sufficient support from talented people to achieve its goal in developing an exascale computing system very shortly.

Cambridge Open Exascale Lab is situated in the West Cambridge Data Centre (WCDC) built by the University of Cambridge at a cost of £20m. This centre is designed to accommodate the rapid growth in demand for high performance computing, and is one of UK’s most energy-efficient high performance computer data centres. It has a high level of security and provides research computing services at a national level.

Most information written in this blog post is mainly from the website of Cambridge Open Exascale Lab.

1. Adam Mann. Core Concept: Nascent exascale supercomputers offer promise, present challenges. PNAS, September 15, 2020 117 (37) 22623-22625).

Wednesday 30 June 2021

Coronavirus (46) NHS website on vitamins and minerals

Coronavirus (46) NHS website on vitamins and minerals
After reading the last two blog posts, you might be eager to start a balanced diet in order to strengthen your immune system. The NHS website on vitamins and minerals provides examples of food that can be easily found in UK supermarkets.1 Here in this blog post, I would like to tabulate the information from the website to make it easier for you to have a look. The harmful effects if we have too much of the vitamins/minerals and the suggested maximum daily intake amount for an adult in the website are also included in the table.

As the daily intake requirement for the vitamins/minerals between adults and children, male and female are different, you might have an interest to have a look at the report from the Public Health of England on dietary recommendations for both children and adults before you plan for your diet.2

Table 1. Sources of vitamins and minerals

Sources of Vitamin Can it be stored in the body? Effects if having too much
Vitamin A cheese, eggs, oily fish such as trout, salmon, sardines, pilchards, fortified low-fat spreads milk and yoghurt, liver and liver products such as liver pâté Yes Having more than an average of 1.5 mg a day of vitamin A over many years may affect your bones, making them more likely to fracture when you're older..Having large amounts of vitamin A can harm your unborn baby.
Beta-carotene (Precursor of vitamin A) Yellow, red and green (leafy) vegetables, such as spinach, carrots, sweet potatoes and red peppers, yellow fruit, such as mango, papaya and apricots Yes If you eat more beta-carotene, less is converted, and the rest is stored in fat reserves in the body. So too much beta-carotene can make you turn yellow, but will not kill you with hypervitaminosis.
Vitamin B1 (Thiamine) Peas, some fresh fruits (such as bananas and oranges), nuts, wholegrain breads, some fortified breakfast cereals, liver No There's not enough evidence to know what the effects might be of taking high doses of thiamin supplements each day. Taking 100mg or less a day of thiamin supplements is unlikely to cause any harm.
Vitamin B2 (Riboflavin) Milk, eggs, fortified breakfast cereals, mushrooms, plain yoghurt No There's not enough evidence to know what the effects might be of taking high doses of riboflavin supplements each day. Taking 40mg or less a day of riboflavin supplements is unlikely to cause any harm.
Vitamin B3 (Niacin: nicotinic acid and nicotinamide. ) Meat, fish, wheat flour, eggs No Taking high doses of nicotinic acid supplements can cause skin flushes. Taking high doses for a long time could lead to liver damage. Taking 17mg or less of nicotinic acid supplements a day, or 500mg or less of nicotinamide supplements a day, is unlikely to cause any harm.
Vitamin B5 (Pantothenic acid) Chicken, beef, liver and kidney, eggs, mushrooms, avocado No If you take supplements, do not take too much as this might be harmful. Taking 200mg or less a day of pantothenic acid in supplements is unlikely to cause any harm.
Vitamin B6 (Pyridoxine) Pork, poultry, such as chicken or turkey, some fish, peanuts, soya beans, wheatgerm, oats, bananas, milk, some fortified breakfast cereals. The bacteria that live naturally in your bowel are also able to make vitamin B6. No Taking 200mg or more a day of vitamin B6 can lead to a loss of feeling in the arms and legs known as peripheral neuropathy. This will usually improve once you stop taking the supplements. But in a few cases when people have taken large amounts of vitamin B6, particularly for more than a few months, the effect can be permanent.
Vitamin B7 (Biotin) Biotin is also found in a wide range of foods, but only at very low levels. The bacteria that live naturally in your bowel are able to make biotin, so it's not clear if you need any additional biotin from the diet. No If you take biotin supplements, do not take too much as this might be harmful. Taking 0.9mg or less a day of biotin in supplements is unlikely to cause any harm.
Vitamin B9 (Folate or folic acid) Broccoli, brussels sprouts, leafy green vegetables such as cabbage, kale, spring greens and spinach, peas, chickpeas and kidney beans, liver (but avoid this during pregnancy), breakfast cereals fortified with folic acid No Taking doses of folic acid higher than 1mg can mask the symptoms of vitamin B12 deficiency, which can eventually damage the nervous system Taking 1mg or less a day of folic acid supplements is unlikely to cause any harm.
Vitamin B12 Meat, fish, milk, cheese, eggs, some fortified breakfast cereals No There's not enough evidence to show what the effects may be of taking high doses of vitamin B12 supplements each day. Taking 2mg or less a day of vitamin B12 in supplements is unlikely to cause any harm.
Vitamin C (Ascorbic acid) Citrus fruit, such as oranges and orange juice, peppers, strawberries, blackcurrants, broccoli, brussels sprouts, potatoes No Taking large amounts (more than 1,000mg per day) of vitamin C can cause stomach pain, diarrhoea, flatulence. These symptoms should disappear once you stop taking vitamin C supplements.
Vitamin D The body creates vitamin D from direct sunlight on the skin when outdoors. Vitamin D is also found in a small number of foods. Sources include oily fish – such as salmon, sardines, herring and mackerel, red meat, liver, egg yolks, fortified foods – such as some fat spreads and breakfast cereals Yes Taking too many vitamin D supplements over a long period of time can cause too much calcium to build up in the body (hypercalcaemia). This can weaken the bones and damage the kidneys and the heart. If you choose to take vitamin D supplements, 10 micrograms a day will be enough for most adults.
Vitamin E Plant oils – such as rapeseed (vegetable oil), sunflower, soya, corn and olive oil; nuts and seeds; wheatgerm-found in cereals and cereal product Yes There is not enough evidence to know what the effects might be of taking high doses of vitamin E supplements each day. Taking 540mg (800 IU) or less a day of vitamin E supplements is unlikely to cause any harm.
Vitamin K Green leafy vegetables such as broccoli and spinach, vegetable oils, cereal grains. Small amounts can also be found in meat and dairy foods. n.a There's not enough evidence to know what the effects might be of taking high doses of vitamin K supplements each day. Adults need approximately 1 microgram a day of vitamin K for each kilogram of their body weight.
Calcium Milk, cheese and other dairy foods, green leafy vegetables such as curly kale, okra but not spinach (spinach does contain high levels of calcium but the body cannot digest it all), soya drinks with added calcium, bread and anything made with fortified flour, fish where you eat the bones such as sardines and pilchards n.a. Taking high doses of calcium (more than 1,500mg a day) could lead to stomach pain and diarrhoea. Adults aged 19 to 64 need 700mg of calcium a day.
Chromium Meat, nuts, cereal grains n.a. There's not enough evidence to know what the effects might be of taking high doses of chromium each day. Having 10mg or less a day of chromium from food and supplements is unlikely to cause any harm.
Copper Nuts, shellfish, offal n.a. Taking high doses of copper could cause stomach pain, sickness, diarrhoea, damage to the liver and kidneys (if taken for a long time). Having 10mg or less a day of copper supplements is unlikely to cause any harm.
Iodine Sea fish, shellfish, plant foods such as cereals and grains (the levels vary depending on the amount of iodine in the soil where the plants are grown) n.a. Taking high doses of iodine for long periods of time could change the way your thyroid gland works. This can lead to a wide range of different symptoms, such as weight gain. However, taking 0.5mg or less a day of iodine supplements is unlikely to cause any harm.
Iron Liver (but avoid this during pregnancy); red meat; beans such as red kidney beans, edamame beans and chickpeas; nuts; dried fruit such as dried apricots; fortified breakfast cereals; soy bean flour n.a. Side effects of taking high doses (over 20mg) of iron include: constipation, feeling sick, being sick, stomach pain. Very high doses of iron can be fatal, particularly if taken by children. Taking 17mg or less a day of iron supplements is unlikely to cause any harm. But continue taking a higher dose if advised to by a GP.
Manganese Bread, nuts, breakfast cereals (especially wholegrain), green vegetables such as peas n.a. Taking high doses of manganese for long periods of time might cause muscle pain, nerve damage and other symptoms, such as fatigue and depression. For most people, taking 4mg or less of manganese supplements a day is unlikely to cause any harm. For older people, who may be more sensitive to manganese, taking 0.5mg or less of manganese supplements a day is unlikely to cause any harm.
Molybdenum Molybdenum is found in a wide variety of foods. Foods that grow above ground tend to be higher in molybdenum than foods that grow below the ground, such as potatoes or carrots. n.a. There's some evidence to suggest taking molybdenum supplements might cause joint pain.
Phosphorus Red meat, dairy foods, fish, poultry, bread, brown rice, oats n.a. Taking high doses of phosphorus supplements for a short time can cause diarrhoea or stomach pain. Taking high doses for a long time can reduce the amount of calcium in the body, which means bones are more likely to fracture. Taking 250mg or less a day of phosphorus supplements on top of the phosphorous you get from your diet is unlikely to cause any harm.
Potassium Bananas, some vegetables such as broccoli, parsnips and brussels sprouts, beans and pulses, nuts and seeds, fish, beef, chicken, turkey n.a. Taking too much potassium can cause stomach pain, feeling sick and diarrhoea. Taking 3,700mg or less of potassium supplements a day is unlikely to have obvious harmful effects. But older people may be more at risk of harm from potassium because their kidneys may be less able to remove potassium from the blood.
Selenium Brazil nuts, fish, meat, eggs n.a. Too much selenium causes selenosis, a condition that, in its mildest form, can lead to loss of hair and nails. Taking 350μg or less a day of selenium supplements is unlikely to cause any harm.
Sodium chloride (salt) Ready meals, meat products such as bacon, some breakfast cereals, cheese, tinned vegetables with added salt, some bread, savoury snacks n.a. Having too much salt is linked to high blood pressure, which raises your risk of serious problems like strokes and heart attacks. You should have no more than 6g of salt (around 1 teaspoon) a day.
Zinc Meat, shellfish, dairy foods such as cheese, bread, cereal products such as wheatgerm n.a. Taking high doses of zinc reduces the amount of copper the body can absorb. This can lead to anaemia and weakening of the bones. Do not take more than 25mg of zinc supplements a day unless advised to by a doctor.

By now, you might have an idea what you would like to have in your meals. However, before you start the next meal, you can think about preparing it by yourself: buy fresh and unprocessed foods, add less salt and sugar, and use moderate amounts of oil for cooking. This way, you can get the most value of vitamins/minerals from the meal. Last but not least, don’t forget to drink enough water and exercise regularly.3

1. Vitamins and minerals. NHS.
2. Government dietary recommendations. Government recommendations for energy and nutrients for males and females aged 1 – 18 years and 19+ years.
3. Nutrition advice for adults during the COVID-19 outbreak. WHO.