Decoding the network logic for resetting pluripotency

Lead Research Organisation: University of Cambridge
Department Name: Wellcome Trust - MRC Cam Stem Cell Inst

Abstract

Embryonic stem cells (ESC) have the unique capacity to become all cell types of the body, a process termed differentiation. Mature cells, such as skin, blood and nerve cells, can revert back to this versatile stem cell state in a process termed reprogramming. These remarkable cellular conversions from and to the ESC state form the basis of an innovative new form of medicine, which aims to transplant the diseased cell type with the patient's own healthy cells that have been reset to the stem cell state and subsequently differentiated to the affected cell type. Therefore, an in-depth understanding of the molecular mechanisms underlying these remarkable cellular processes is not only important in revealing basic scientific principles; it also has crucial practical implications in making regenerative medicine a reality. However, the fundamental details of reprogramming remain elusive and this presents significant challenges for effective generation of stem cells that are suitable for clinical applications.

This research will provide a deep understanding into the molecular controls of reprogramming on a systems level. The ESC state is governed by a network of factors, termed transcription factors, which can control the activity of many genes within a cell. This network of transcription factors works together in a synergistic fashion and the activation of the network is required during reprogramming in order for cells to gain ESC identity. However, the details of how this network is launched and becomes fully connected remain elusive and the full network activation is a potent barrier to reprogramming. Therefore, understanding and overcoming this barrier is crucial to efficient and successful reprogramming.

This research seeks to address this important aspect of reprogramming through integrating experimental measurements with computational and mathematical modelling to produce a systems level insight into reprogramming. We will capture the molecular characteristics of individual cells during reprogramming progression. These molecular "snapshots" collected experimentally will be used as data input for developing computational models which connect individual components of the TF network using mathematical logic. Using experimental tests as benchmarks, these models will be verified by their capabilities of generating correct predictions on how cells behave in reprogramming. The models will be further refined in an iterative process of prediction/validation/improvement in order to obtain the best models. By analysing such models, we will reveal molecular and mechanistic insights into how cells make fate decisions in reprogramming. This top-down approach will not only integrate our existing knowledge of individual network components, it will also decode molecular network rules and programs governing cell fate decision making and the principles of which could be generally applicable to other biological systems and behaviours.

The development of computational and mathematical modelling techniques from this research will be of great help in the study of other types of cellular decisions. By advancing our understanding of such information processing in cells, ultimately we will be able to program and design living systems, and to realistically predict cellular behaviours digitally. This will bring significant benefit to many sectors of science, technology and medicine.

Technical Summary

Reprogramming is a process which resets cells from established cellular identities to the pluripotent embryonic stem cell (ES) state. This cellular process requires the activation and full connections of the core transcription factor (TF) network which governs the naïve stem cell state, as well as the prohibition of alternative cell fates and their associated TF networks. These dynamics network choices make reprogramming an exciting paradigm for investigating the molecular information-processing underlying cell fate transitions.

Here we propose to use an interdisciplinary approach to systematically address the molecular basis of cell fate transitions in reprogramming at a network level. Using post-implantation epiblast-derived stem cells (EpiSC) as a minimal resetting experimental model, we will examine the dynamics of naïve TF network activation and evolution in the induced pluripotent stem (iPS) cell trajectory as well as the network switches in commitment to alternative cell fates at a single cell resolution. We will use a data-constrained automated formal reasoning approach for the synthesis and analysis of interaction networks and all possible trajectories of network configurations over resetting timeline. We can formulate predictions of system behaviours in perturbed conditions which can be tested experimentally. This approach will overcome the challenges originating from the multi-step, heterogeneous and asynchronous nature of reprogramming to achieve high resolution molecular delineation of network trajectories.

Our original research will illuminate molecular principles in how cells transit between identities and is applicable for the investigation of a wide range of cellular transitions. The insights gained will facilitate the improvement of authenticity, efficiency and reproducibility of cellular reprogramming for regenerative medicine. Advancing network understanding in cellular decisions will also facilitate digital designs of living systems.

Planned Impact

Stem cell biology is a priority area for UK science investment. This proposed research takes an interdisciplinary approach to systematically address the molecular network logic underlying cell fate decisions in induced pluripotency. The insight gained from this research could be applied to optimise cellular reprogramming for biomedical goals in drug discovery and regenerative medicine. Advancing such network understanding in cellular decisions will facilitate the future program and design of living systems. This will bring significant benefit to many sectors of science, technology and medicine.

Users of research and stakeholders
Academic researchers - this research will contribute to maintaining the world-leading position of the UK for innovation and discovery in pluripotent stem cell research and cognate areas, as detailed in the Academic Beneficiaries section.
Industry -insight into protocols for efficiently produce induced pluripotent stem cells will be of considerable interest to commercial activities in research tool provision, drug discovery and regenerative medicine. Relevant industry includes reagent companies in the stem cell sector, biotechnology service companies, and Pharma, all of whom are represented in the Cambridge cluster. In addition, the computational approach developed here to understand biological information processing in cells is part of the effort towards programming and designing digital living systems. This will bring significant benefit to many sectors of biotechnology industry. Overall the project will support retention and growth of the Life Sciences industry around Cambridge and in the UK and thereby contribute to economic activity and competitiveness.

Clinicians and patients - in the long term this research is expected to feed through to improved medical care and treatment by enabling more effective exploitation of pluripotent stem cells. This will include both applications in regenerative medicine and use of reprogrammed cells derived from patients for applications in disease modelling and drug discovery.

General public - the project aims to meet expectations for publicly funded research; (i) to increase understanding of the natural world, and (ii) to lead to improved quality of life. In the first domain the research addresses fundamental issues in induced pluripotency. For the second, a long-term perspective is that increased understanding in effective and efficient production of induced pluripotent stem cells will provide a strong basis for regenerative medicine in treating debilitating diseases which are not currently druggable with small molecules or antibody based therapies.

Outcomes of the project will be disseminated through a range of communication routes. Seminars, workshops, conference presentations and open access publications will reach relevant academics. The Cambridge Stem Cell Club provides frequent opportunity for informal dialogue and networking with the local scientific community including clinical and industry researchers. Cambridge Enterprise and the University Office for Translation provide more formal avenues for identifying and engaging with commercial partners. Austin Smith has personal contacts within management at companies such as StemCell Technologies UK, Plasticell and AstraZeneca, and is a member of the Cell and Gene Therapy Catapult Scientific Advisory Board.

The Smith laboratory has a track record in public engagement, speaking at schools and science festivals, meeting patient groups, contributing to EuroStemCell, (Europe's Stem Cell Hub http://www.eurostemcell.org/), and hosting work experience projects for sixth form pupils. In 2015 we worked with the Institute Public Engagement Officer to organise a competition for computer game developers on the theme of stem cell fate. The winning game is being taken forward for development into an outreach tool. For the present proposal we aim to host an equivalent activity.

Publications

10 25 50
 
Description In this work we combined experimental findings with computational analysis. The results showed that a common small network of signals and transcription factors controls both the maintenance of pluripotent stem cells and the induction of pluripotency by molecular reprogramming of somatic cells.
Exploitation Route The methodology we demonstrate can be extended to decipher cell fate decisions in any biological system in which suitable molecular information is available.
Sectors Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology

URL https://www.microsoft.com/en-us/research/project/stem/
 
Description Cambridge Doctoral Training Partnership
Amount £96,736 (GBP)
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 10/2017 
End 09/2021
 
Description Plasticity of the Pluripotency Network
Amount € 2,499,970 (EUR)
Organisation European Research Council (ERC) 
Sector Public
Country Belgium
Start 01/2020 
End 12/2024
 
Title RE:IN tool 
Description Public access is provided to the RE:IN tool via an html5 web application, which is freely hosted by Microsoft and provides the necessary cloud-based compute via Azure services. The computation auto-scales to the size of the job that is being performed, and the tool employs web sockets to stream results that are visualised with Microsoft graphing technology. There is an online tutorial and FAQ. 
Type Of Material Computer model/algorithm 
Year Produced 2014 
Provided To Others? Yes  
Impact To add 
URL http://www.research.microsoft.com/rein
 
Description Computational Modelling 
Organisation Microsoft Research
Department Microsoft Research Cambridge
Country United Kingdom 
Sector Private 
PI Contribution Computational Modelling
Collaborator Contribution Computational Modelling
Impact n/a
Start Year 2010
 
Description BBC Science & Technology 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Media (as a channel to the public)
Results and Impact Commentary for BBC Science & Technology, Jan 2018
Year(s) Of Engagement Activity 2018