quantitative biology + synthetic biology + systems biology

Mutational processes

Microbiome engineering

Biological computation

Mutational processes

We focus on the mechanistic modelling of genetic and sequence data to try to infer the biological processes that shape genomes. We have developed evolutionary models that can be fit to cancer patient sequencing data to infer important parameters such as mutation rates and selection coefficients. We are currently working on modelling structural variation and chromosome instability to try to understand how these important processes contribute to intra-tumour heterogeneity.

Microbiome engineering

The human intestine and the wide range of prokaryotic and eukaryotic organisms it supports form a mutualistic host-microbe symbiotic system crucial for many processes including the breakdown of plant polysaccharides and microbial fermentation. Variation and disruption of this natural ecosystem is linked to a diverse array of disorders including infectious disease, autoimmunity, obesity and cancer. We are engineering probiotic strains for therapeutic and sensing applications, plus understanding how to engineer microbial consortia.

Gene regulatory networks

Using model space exploration from Bayesian statistics we have developed and parameterised a number of models of morphogenesis in collaboration with developmental biologists. We have also used the same methods to examine the robustness of simple gene networks in the context of synthetic biology, including the dynamics of multi-functional networks.

Biological computation

Biological organisms comprise complex information processing systems and computation is present at every level, from protein and DNA nanomachines, through cellular gene and signalling networks to tissues, brains and ecosystems. Thus, computation can be seen to be a fundamental and unifying theme of biology. This computation is performed in a highly parallel and robust fashion, using concurrent, multi-scale hybrid digital and analogue processing, often utilising components that are unreliable and noisy, and at orders of magnitude lower power requirements than traditional, “silicon” computing. Understanding how biological computing is performed thus has enormous potential for driving forward biology and engineering, enabling a more sustainable future in an increasingly computation-dependent world.

Interdisciplinary and collaborative

We have backgrounds ranging across physics, computer science, microbiology, synthetic biology and genetics.


Group retreat, Stratford 2022
Coal Drops yard, 2021
Regents park, 2020
Rockefeller Building xmas party, 2019

Group retreat, Bath 2018

Current group members

Prof. Chris P Barnes
Dr Linda Dekker
Dr Jack Rutter
Dr Pedro Fontanarrosa
Dr Soutrick Das
Dr Jurgen Riedel
Kimberley Owen
Chania Clare
Kathleen Zhang
Qing Ong

Prof. Chris Barnes
christopher.barnes@ucl.ac.uk

I'm a Professor in the Division of Biosciences within the Faculty of Life Sciences at University College London. My career has spanned multiple fields including particle physics, genetics, statistics, computational systems biology and synthetic biology (Google Scholar). In addition to my research, I'm also actively engaged in training the next generation of researchers; I developed the BBSRC funded e-learning resource SysMIC to train life scientists in computational and mathematical skills. I'm also involved in running the EPSRC funded Centre for Doctoral Training in BioDesign Engineering and the LIDo Doctoral Training Partnership.

Dr Linda Dekker
linda.dekker.09@ucl.ac.uk

I am currently working on a project constructing, characterising and optimising whole-cell bacterial biosensors that detect metabolites important in gut microbiota disorders. I completed my BSc and MSc in Microbiology at the University of Otago (New Zealand) and did a PhD in Microbiology in Prof Joanne Santini's group at UCL. I previously worked as a PDRA at Imperial College London on various synthetic biology projects ranging from natural product biosynthesis in Clostridia, to changing the material properties of bacterial cellulose. I'm passionate about Microbiology and am a Microbiology Society Champion and try to promote the awesome opportunities the Microbiology Society has to offer. I founded the Barnes Lab cake club 🧁.

Dr Jack Rutter
jack.rutter.16@ucl.ac.uk

I am currently a Post Doctoral Research Associate, at University College London in the CSSB lab. I previously completed my PhD, supervised by Prof. Chris Barnes and Prof. Geraint Thomas, where I developed a range of novel whole-cell biosensors. I now work on microbiome engineering. My current project is looking at how we can engineer probiotic E. coli to target and remove pathogenic species of bacteria in the body.

Dr Pedro Fontanarrosa
pfontanarrosa@gmail.com

I am a Postdoctoral Research Associate in the CSSB lab, where my primary focus is on the intersection of artificial intelligence and microbiology. My academic path began at the University of Buenos Aires (UBA), Argentina, where I earned both my Bachelor's and Master's degrees in Evolutionary Biology. I furthered my studies in the United States, obtaining a Master's in Bioengineering and a Ph.D. in Biomedical Engineering from the University of Utah. My doctoral research laid the foundation for my postdoctoral fellowship at the University of Boulder, Colorado, where I delved into the intricacies of genetic circuitry. Currently, at UCL, my work revolves around leveraging AI and machine learning techniques to model and engineer resilient microbial communities.

Dr Soutrick Das
soutrick.das@ucl.ac.uk

I am a post-doctoral research associate in the CSSB lab, Division of Biosciences at University College London. My current research focuses on spatial computation in the context of synthetically engineered microbial populations, incorporating artificial neural networks, machine learning and mathematical modeling techniques. Previously, I completed my Ph.D. under the guidance of Prof. Debashis Barik at the School of Chemistry, University of Hyderabad, India. Here, I employed mathematical modeling tools to investigate the roles of diverse functional motifs and chemical noise in biological reaction networks. Notably, we developed a novel protocol to automate the modeling of canonical and noncanonical biological switches.

Kimberley Owen
k.owen20@imperial.ac.uk

I am a PhD student on the CDT for Biodesign Engineering. I am new to synthetic biology and looking forward to expanding my skill set. I spent the summer of 2020 working at the Milton Keynes Lighthouse Lab (UKBiocentre) testing covid-19 samples. I completed my Bachelor’s in Biochemistry at the University of Bath (2020) and conducted a year in research (2018/19) at the University of Arizona (Herbst-Kralovetz group) where I was introduced to the complex interplay between host and microbiota in the female reproductive tract. My PhD project will involve developing new bacterial therapeutics for targeting and manipulating the cancer microbiome.

Jurgen Riedel
jurgen.riedel@gmail.com

I am a PhD student at University College London in the Department of Cell and Developmental Biology. I've had a career as a Data Analyst and Scientist in many industries, including private banking, energy and biotechnology. I hold a PhD in Theoretical Physics from the University of Oldenburg, Germany, where my research focused on black holes, quantum gravity and dark matter. I'm also deeply interested in complexity theory and its application to large universe masses, including nature at the cellular level. My current research focuses on reaction-diffusion systems in the continuous domain via PDEs and the discrete domain via cellular automata. My goal is to study complex systems at the edge of chaos and observe the emergence of complex behaviour.

Chania Clare
chania.clare.21@ucl.ac.uk

I’m a PhD student on the London Interdisciplinary Doctoral Programme (LIDo), where my work looks into the role of bacterial microcompartments in community dynamics though computational and wetlab techniques. I completed my Bachelor’s and Master’s degrees at Imperial College London, where I investigated electrotropism in plants, engineering cyanobacteria to support crop growth, and circadian-dependent immunity in the malaria parasite. As part of my PhD I completed a rotation project with the London School of Hygiene and Tropical Medicine and the Francis Crick Institute to identify novel drug targets for malaria parasite invasion.

Kathleen Zhang
kathleen.zhang@ucl.ac.uk

I am a PhD student on the EPSRC Centre for Doctoral Training in BioDesign Engineering program. My research focuses on applying analogue computing to biologics by using artificial neural network and spatial patterning of engineered bacteria. Previously, I worked as a Platform Scientist for 2 years at LabGenius, a London based biotech start-up in drug discovery at the interface of ML and Synbio. I have a Master of Science in Cell and Systems Biology from the University of Toronto, Canada, in the McMillen Synthetic Biology and Cellular Control lab where I worked on developing stress responsive biosensors in probiotic bacteria for detection of inflammation in IBD; and a Bachelor of Science in Honours Biology from the University of Waterloo.

Qing Ong
qing.ong.19@ucl.ac.uk

I am a research assistant in the Computational Systems and Synthetic Biology lab at UCL. I am currently working on the biological spatial computing project. Before joining the lab, I completed my undergraduate degree in Biomedical Sciences: Cells and Molecules, also at UCL. I found my passion for doing lab work during my undergraduate study, and now I am interested in learning more about synthetic biology, also the application of computational approaches in biology.

Past group members

Dr Mohamed Ali al-Badri. PDRA 2020-2024. Now a Senior ML Engineer at Nucleome Therapeutics
Dr Bingxin Lu. PDRA 2019-2023. Now a Surrey Future Fellow at University of Surrey
Dr Will Cross. Visiting Fellow 2021-2023. Now a Lecturer (Assistant Prof.) at University of Westminster
Dr Alex Fedorec. PhD/PDRA 2014-2022. Now a Lecturer (Assistant Prof.) at UCL
Dr Neythen Treloar. PhD/PDRA 2018-2023. Now a Senior Data Scientist at Bactobio
Dr Ke Yan Wen. PDRA 2019-2022. Now a Senior Scientist at BactoBio
Dr Behzad Karkaria. PhD/PDRA 2017-2021. Now a AI/ML Engineer at GSK
Dr Luca Rosa. PhD student 2017-2021. Now a Synthetic Biology Engineer at Micrographia Bio
Ms Clare Robinson. Research Assistant 2019-2020. Now doing a PhD with David Riglar, Imperial College
Dr Josh Russell-Buckland. PhD student 2016-2020. Now a software engineer at Guardian News and Media
Dr Marc Williams. PhD student 2014-2018. Now a Research Fellow with Sohrab Shah, Memorial Sloan Kettering
Dr Tanel Ozdemir. PhD student 2013-2017. Now an Investment Associate at AlbionVC
Dr Lourdes Sriraja. PhD student 2013-2017. Now a PDRA with Tariq Enver, UCL Cancer Institute
Dr Mae Woods. PDRA 2013-2018. Now at Baylor College of Medicine
Dr Miriam Leon. PhD student 2012-2016. Now a Senior Data Scientist at Lyft

Mutational processes

Fig: Modelling chromosomal gain and loss within a stochastic branching process

MA al-Badri, WCH Cross, CP Barnes (2024). Explainable deep learning on 7500 whole genomes elucidates cancer-specific patterns of chromosomal instability. bioRxiv, 2024.03.08.584160

B Lu, S Winnall, W Cross, CP Barnes (2024). Cell-cycle dependent DNA repair and replication unifies patterns of chromosome instability. bioRxiv, 2024.01.03.574048

Lu, B., Curtius, K., Graham, T.A., Yang, Z., Barnes, C.P. (2023). CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples. Genome biology, 24 doi:10.1186/s13059-023-02983-0

Gabbutt, C., Schenck, R.O., Weisenberger, D.J., Kimberley, C., Berner, A., Househam, J., ...Patel, R. (2022). Fluctuating methylation clocks for cell lineage tracing at high temporal resolution in human tissues. Nature Biotechnology, doi:10.1038/s41587-021-01109-w

Bollen, Y., Stelloo, E., van Leenen, P., van den Bos, M., Ponsioen, B., Lu, B., ...Snippert H.J.G. (2021). Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns. Nature Genetics, doi:10.1038/s41588-021-00891-2

Williams, M.J., Zapata, L., Werner, B., Barnes, C.P., Sottoriva, A., Graham, T.A. (2020). Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios. eLife, 9 doi:10.7554/eLife.48714

Williams, M.J., Werner, B., Heide, T., Curtis, C., Barnes, C.P., Sottoriva, A., Graham, T.A. (2018). Quantification of subclonal selection in cancer from bulk sequencing data. Nature Genetics 2018 Jun;50(6):895-903. doi:10.1038/s41588-018-0128-6
Article in The Times

Woods M.L., Barnes C.P. (2016). Mechanistic Modelling and Bayesian Inference Elucidates the Variable Dynamics of Double-Strand Break Repair. PLoS Comput Biol. 2016 Oct 14;12(10):e1005131. doi:10.1371/journal.pcbi.1005131

Williams, M.J., Werner, B, Barnes, C.P., Graham, T.A., & Sottoriva, A. (2016). Identification of neutral tumor evolution across cancer types. Nature Genetics, 2016 Jan 18. doi:10.1038/ng.3489

Chaidos, A, Barnes, C.P. et. al. (2013). Clinical drug resistance linked to interconvertible phenotypic and functional states of tumor-propagating cells in multiple myeloma. Blood. 2013 Jan 10;121(2):318-28. doi:10.1182/blood-2012-06-436220

Microbiome engineering

Fig: (Left) Fluorescent bacteria colonising the gut of a C. elegans nematode worm. (Right) An engineered GRN in E. coli enabling bacteriocin production control through quorum sensing (SPoCK system)

C Clare, JW Rutter, AJH Fedorec, S Frank, CP Barnes (2024). Bacterial microcompartment utilisation in the human commensal Escherichia coli Nissle 1917. bioRxiv, 2024.05. 13.593892

JW Rutter, L Dekker, C Clare, ZF Slendebroek, KA Owen, JAK McDonald, AJH Fedorec, CP Barnes (2024). A bacteriocin expression platform for targeting pathogenic bacterial species. Nature Communications 15 (1), 6332, doi: 10.1038/s41467-024-50591-8

Karkaria, B.D., Manhart, A., Fedorec, A.J.H., Barnes, C.P. (2022). Chaos in synthetic microbial communities. PLoS Computational Biology, 18 (10), doi:10.1371/journal.pcbi.1010548

Rutter, J.W., Dekker, L., Owen, K.A., Barnes, C.P. (2022). Microbiome engineering: engineered live biotherapeutic products for treating human disease. Frontiers in Bioengineering and Biotechnology, 10 doi:10.3389/fbioe.2022.1000873

Rutter, J.W., Dekker, L., Fedorec, A.J.H., Gonzales, D.T., Wen, K.Y., Tanner, L.E.S., ...Barnes, C.P. (2021). Engineered acetoacetate-inducible whole-cell biosensors based on the AtoSC two-component system. Biotechnology and Bioengineering, doi:10.1002/bit.27897
Download the data here

Fedorec, A.J.H., Karkaria, B.D., Sulu, M., Barnes, C.P. (2021). Single strain control of microbial consortia. Nat Commun, 12, 1977. doi:10.1038/s41467-021-22240-x
Download the data here

Karkaria, B.D., Fedorec, A.J.H., Barnes, C.P. (2021). Automated design of synthetic microbial communities. Nat Commun, 12, 672. doi:10.1038/s41467-020-20756-2
Download the data here
Code available on GitHub

Fedorec, A.J.H., Robinson, C.M., Wen, K.Y., Barnes, C.P. (2020). FlopR: An Open Source Software Package for Calibration and Normalization of Plate Reader and FlowCytometry Data. ACS Synth Biol, doi:10.1021/acssynbio.0c00296
Download the data here
Code available on GitHub

Treloar, N.J., Fedorec, A.J.H., Ingalls, B., Barnes, C.P. (2020). Deep reinforcement learning for the control of microbial co-cultures in bioreactors. PLoS Comput Biol, 16 (4), e1007783. doi:10.1371/journal.pcbi.1007783
Download the data here
Code available on GitHub

Wen, K.Y., Rutter, J.W., Barnes, C.P., Dekker, L. (2019). Fundamental Building Blocks of Whole-Cell Biosensor Design. In Thouand, G. (Ed.), Handbook of Cell Biosensors. (pp. 1-23). Springer International Publishing.

Rutter, J.W., Ozdemir, T., Galimov, E.R., Quintaneiro, L.M., Rosa, L., Thomas, G.M., Cabreiro, F., Barnes, C.P. (2019). Detecting Changes in the Caenorhabditis elegans Intestinal Environment Using an Engineered Bacterial Biosensor. ACS Synth Biol, doi:10.1021/acssynbio.9b00166
Download the data and code here

Shaw, L., Bassam, H., Barnes, C.P., Walker, A., Klein, N., Balloux, F. (2019). Modelling microbiome recovery after antibiotics using a stability landscape framework. ISME Journal, doi:10.1038/s41396-019-0392-1
Article in The Telegraph

Fedorec, A.J.H., Ozdemir, T., Doshi, A., Ho, Y.-.K., Rosa, L., Rutter, J., ...Barnes, C.P. (2019). Two New Plasmid Post-segregational Killing Mechanisms for the Implementation of Synthetic Gene Networks in Escherichia coli. iScience, doi:10.1016/j.isci.2019.03.019
Download the data and code here
Plasmids available on addgene

Barnes, C.P., Fedorec, A.J.H. (2018). Five amazing ways redesigning biological cells could help us fight cancer. The Conversation

Ozdemir, T., Fedorec, A.J.H., Danino, T., Barnes, C.P. (2018). Synthetic Biology and Engineered Live Biotherapeutics: Toward Increasing System Complexity. Cell Systems, 7 (1), 5-16. doi:10.1016/j.cels.2018.06.008

Biological computation

Fig: Patterning as a spatial computation. Each panel represents a different interpretation of a morphogen gradient produced from two sources A and B

AJH Fedorec, NJ Treloar, KY Wen, L Dekker, QH Ong, G Jurkeviciute, E Lyu, JW Rutter, KJY Zhang, L Rosa, A Zaikin, CP Barnes (2024). Emergent digital bio-computation through spatial diffusion and engineered bacteria Nature Communications 15 (1), 4896, doi: 10.1038/s41467-024-49264-3

Otero-Muras, I., Perez-Carrasco, R., Banga, J.R., Barnes, C.P. (2023). Automated design of gene circuits with optimal mushroom-bifurcation behavior. iScience, 26 (6), doi:10.1016/j.isci.2023.106836

Treloar, N.J., Braniff, N., Ingalls, B., Barnes, C.P. (2022). Deep reinforcement learning for optimal experimental design in biology. PLoS Computational Biology, 18 (11), doi:10.1371/journal.pcbi.1010695

Treloar, N., Wen, K.Y., Fedorec, A., Barnes, C. (2021). SynBioBrain: building biological computers from bacterial populations. The Project Repository Journal, doi:doi.org/10.54050/PRJ1117751

Karkaria, B.D., Treloar, N.J., Barnes, C.P., Fedorec, A.J.H. (2020). From microbial communities to distributed computing systems Frontiers in Bioengineering and Biotechnology 8, 834, doi:doi.org/10.3389/fbioe.2020.00834

Dalchau, N., Szép, G., Hernansaiz-Ballesteros, R., Barnes, C.P., Cardelli, L., Phillips, A., Csikász-Nagy, A. (2018). Computing with biological switches and clocks. Natural Computing, 1-19. doi:10.1007/s11047-018-9686-x

Perez-Carrasco, R., Barnes, C.P., Schaerli, Y., Isalan, M., Briscoe, J., Page, K.M. (2018). Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors. Cell Systems. doi:10.1016/j.cels.2018.02.008

Boeing, P., Leon, M., Nesbeth, D.N., Finkelstein, A., Barnes, C. (2018). Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology. Processes, 6 (9), doi:10.3390/pr6090167

Leon, M., Woods, M.L., Fedorec, A.J.H., & Barnes, C.P. (2016) A computational method for the investigation of multistable systems and its application to genetic switches. BMC Systems Biology 2016 Dec 7;10(1):130. doi:10.1186/s12918-016-0375-z

Woods, M., Leon, M., Perez-Carrasco, R. & Barnes, C.P. (2016) A statistical approach reveals designs for the most robust stochastic gene oscillators. ACS Synthetic Biology 5 (6), pp 459–470. doi:10.1021/acssynbio.5b00179

Cohen, M., Kicheva, A., Ribeiro, A., Blassberg, R., Page, K. M., Barnes, C. P. & Briscoe, J. (2015). Ptch1 and Gli regulate Shh signalling dynamics via multiple mechanisms. Nature Communications, 6. doi:10.1038/ncomms7709

Cohen, M., Page, K. M., Perez-Carrasco, R., Barnes, C. P., & Briscoe, J. (2014). A theoretical framework for the regulation of Shh morphogen-controlled gene expression. Development, 141(20), 3868-3878. doi:10.1242/dev.112573

Liepe, J., Kirk, P., Filippi, S., Toni, T., Barnes, C. P., & Stumpf, M. P. H. (2014). A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation. Nature Protocols, 9(2), 439-456. doi:10.1038/nprot.2014.025