Dr Iain G. Johnston

Dr Iain G. Johnston

School of Biosciences
Birmingham Fellow

Contact details

Address
School of Biosciences
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Iain's research uses mathematical modelling, simulation, and tools from statistics and data science to build quantitative and predictive descriptions of the biological world, harnessing expanding volumes of (often noisy and heterogeneous) experimental data. He is particularly interested in biological systems where stochastic effects are important, including mitochondrial genetics, bioenergetics, and evolutionary processes in plants and animals.

Qualifications

MA, MSci Natural Sciences (Cambridge)

DPhil Theoretical Physics (Oxford)

Biography

Iain studied Natural Sciences at Downing College, Cambridge, working for a Masters' dissertation on the self-assembly of virus capsids. He completed a D. Phil. at Oxford, associated with Lincoln College, exploring the stochastic dynamics of biological evolution and self-assembly. His post-doctoral work at Oxford focussed on how mitochondria, important cellular energy sources, vary within and between cells, and the implications that this variability has for downstream processes including cell cycle progression, protein expression, and stem cell differentiation. He then moved to Imperial College London to take up an MRC research fellowship, during which he studied the role that physical and genetic variability in mitochondria play in human disease and plant bioenergetics. He is now a Birmingham Fellow.

Postgraduate supervision

I would be delighted to discuss projects with potential students. I am looking for people interested in developing their mathematical, statistical, and/or computational skills, and exploring questions about systems biology in plants, the evolution of mitochondria and chloroplasts, the "dynamic syncytium" of plant mtDNA, mtDNA damage and ageing, the power spectra of evolutionary processes, and other bioenergetic and evolutionary topics. Drop me an email!

Research

The biological cell is a tumultuous environment, in which proteins and organelles are constantly constructed, destroyed and buffeted. The processes that are responsible for life take place in this unpredictable setting, and require energy, which is produced (in eukaryotes -- the group which includes animals, plants and fungi) by organelles called mitochondria. My research focusses on how random influences affect these vital cellular processes, and how mitochondria behave and adapt to meet the cell's energy requirements, with a particular emphasis on how variability in mitochondrial genetics and biophysics may lead to disease, cell stress, and other physiological consequences.

I'm also very interested in biological evolution and how maths can be used to model, and even predict, its outcomes. This topic is naturally braided with the study of mitochondria, which have a fascinating evolutionary history and are still constantly evolving in our cells. We've found several ways in which we can "learn from evolution" in diverse fields from mitochondrial medicine to crop engineering.

Mathematical modelling and simulation studies, combined with tools from statistics, give us the ability to amalgamate, unify and harness the vast (and often heterogeneous) volumes of experimental data currently available, producing descriptive and predictive theories of the biological world. I am particularly interested in using physical and stochastic modelling with approaches from inference and model selection to build quantitative frameworks describing noisy systems of biological and medical relevance.

Many of my recent projects are briefly described in less technical detail in the publication list below, and also in articles like Nature's coverage of our "probability calculator"; the evolution of C4 photosynthesis; and an mtDNA study suggesting a way of improving gene therapies.

Some projects that I'm currently interested in:

  • Physical modelling of mitochondrial ultrastructure, motion, and chemical biophysics
  • Stochastic evolution of populations of mtDNA within cells
  • Plant mtDNA recombination and the "dynamic syncytium"
  • Predicting worldwide vaccine coverage and confidence using big socio-economic data
  • Master equation expansions beyond the linear noise approximation
  • The power spectra of evolutionary processes

ORCID ID: 0000-0001-8559-3519 

Publications

Peer-Reviewed Science

36. The essential genome of Escherichia coli K-12
E Goodall, A Robinson, IGJ, S Jabbari, K Turner, A Cunningham, P Lund, J Cole, I Henderson
mBio (accepted 2018)

35. Mitochondrial DNA density homeostasis accounts for a threshold effect in a cybrid model of a human mitochondrial disease
J Aryaman, IGJ, N Jones
Biochem J (online before print; BCJ20170651)

34. Temperature variability is integrated by a spatially-embedded decision-making center to break dormancy in Arabidopsis seeds
A Topham, R Taylor, D Yan, E Nambara, IGJ, G Bassel
Proc Natl Acad Sci USA 114 6629 (2017)
(International press coverage including Daily Mail, IFL Science; recommended by F1000)

33. Mitochondrial heterogeneity, metabolic scaling and cell death
J Aryaman, IGJ, N Jones
BioEssays 39 1700001 (2017)

32. Stochastic Models for Evolving Cellular Populations of Mitochondria: Disease, Development, and Ageing
H Hoitzing, IGJ, N Jones
in Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology, Springer, p287 (2017)

31. Toward Precision Healthcare: Context and Mathematical Challenges
C Colijn, N Jones, IGJ, S Yaliraki, M Barahona
Frontiers Physiol 8 136 (2017)

30. Evolution of cell-to-cell variability in stochastic, controlled, heteroplasmic mtDNA populations
IGJ, N Jones
Am J Hum Genet 99 1150 (2016)

29. mtDNA diversity in human populations highlights the merit of haplotype matching in gene therapies
E Røyrvik, J Burgstaller, IGJ
Mol Hum Reprod 22 809 (2016)
(Presented to and included in 2016 UK HFEA policy recommendations on mitochondrial gene therapies)

28. The state of vaccine confidence 2016: global insights through a 67-country survey
H Larson, A de Figueiredo, Z Xiahong, W Schulz, P Verger, IGJ, A Cook, N Jones
eBioMedicine 12 295 (2016)
(International press coverage including Daily Mail, The Mirror, Le Monde, New Scientist, Science, Scientific American; commentary in eBioMedicine)

27. Forecasted trends in vaccination coverage and correlations with socioeconomic factors: a global time-series analysis over 30 years
A de Figueiredo, IGJ, D Smith, S Agarwal, H Larson, N Jones
Lancet Global Health 4 e726 (2016)
(Commentary in Lancet Global Health)

26. Variability in seeds: biological, ecological, and agricultural implications
J Mitchell, IGJ, G Bassel
J Exp Bot 68 809 (2017)

25. Modulating mitochondrial quality in disease transmission: towards enabling mitochondrial DNA disease carriers to have healthy children
A Diot, E Dombi, T Lodge, C Liao, K Morten, J Carver, D Wells, T Child, IGJ, S Williams, J Poulton
Biochem Soc Trans 44 1091 (2016)

24. Evolutionary inference across eukaryotes identifies specific pressures favoring mitochondrial gene retention
IGJ, B Williams
Cell Systems 2 101 (2016)
(Science magazine’s #1 “favourite news story of 2016”; commentaries in Cell Systems and Science; substantial scientific press coverage and online attention (Facebook, The Scientist, La Recherche))

23. Endless love: On the termination of a playground number game
IGJ
Recreational Mathematics Magazine 2016 61 (2016)

22. Monitoring Intracellular Oxygen Concentration: Implications for Hypoxia Studies and Real-Time Oxygen Monitoring
M Potter, L Badder, Y Hoade, IGJ, K Morten
Adv Exp Med Biol (Oxygen Transport to Tissue XXXVII) 257 (2016)

21. A novel quantitative assay of mitophagy: Combining high content fluorescence microscopy and mitochondrial DNA load to quantify mitophagy and identify novel pharmacological tools against pathogenic heteroplasmic mtDNA
A Diot et al.
Pharm Res 100 24 (2015)

20. Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
IGJ, J Burgstaller, V Havlicek, T Kolbe, T Rlicke, G Brem, J Poulton, N Jones
eLife 4 e07464 (2015)

19. What is the function of mitochondrial networks? A theoretical assessment of hypotheses and proposal for future research
H Hoitzing, IGJ, N Jones
BioEssays 37 687 (2015)

18. Multiple hypothesis correction is vital and undermines reported mtDNA links to diseases including AIDS, cancer, and Huntingdon’s
IGJ
Mitochondrial DNA Part A 27 3423 (2016)

17. Closed-form stochastic solutions for non-equilibrium dynamics and inheritance of cellular components over many cell divisions
IGJ, N Jones
Proc Roy Soc A 471 20150050 (2015)

16. Mitochondrial DNA disease and developmental implications for reproductive strategies
(IGJ & J Burgstaller)‡, J Poulton
Mol Hum Reprod 21 11 (2015)

15. Explicit tracking of uncertainty increases the power of quantitative rule-of-thumb reasoning in cell biology
IGJ, B Rickett, N Jones
Biophys J 107 2612 (2014)
(Toolbox article in Nature; commentary in Biophys J)

14. The ’mitoflash’ probe cpYFP does not respond to superoxide
M Schwarzlander et al.
Nature 514 E12 (2014)
(International scientific press coverage)

13. FRIENDLY regulates mitochondrial distribution, fusion, and quality control in Arabidopsis
A El Zawily et al.
Plant Physiol 166 808 (2014)

12. mtDNA segregation in heteroplasmic tissues is common in vivo and modulated by haplotype differences and developmental stage
J Burgstaller, IGJ, et al.
Cell Reports 7 2031 (2014)
(International scientific press coverage; included in UK health policy via 2014 HFEA recommendations for gene therapies)

11. A tractable genotype-phenotype map modelling the self-assembly of protein quaternary structure
S Greenbury, IGJ, A Louis, S Ahnert
J Roy Soc Interf 11 20140249 (2014)
(One of Interface’s top-cited articles in 2014)

10. Efficient parametric inference for stochastic biological systems with measured variability
IGJ
Stat Appl Genet Mol Biol 13 379 (2014)

9. Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis
(IGJ & B Williams)‡, S Covshoff, J Hibberd
eLife 2 e00961 (2013)
(Editor’s choice and commentary in eLife; UK scientific press coverage)

8. Pulsing of membrane potential in individual mitochondria: a stress-induced mechanism to regulate respiratory bioenergetics in Arabidopsis
M Schwarzlander, D Logan, IGJ, N Jones, A Meyer, M Fricker, L Sweetlove
Plant Cell 24 1188 (2012)
(Recommended by F1000)

7. Epistasis can lead to fragmented neutral spaces and contingency in evolution
S Schaper, IGJ, A Louis
Proc Roy Soc B 279 1777 (2011)

6. Mitochondrial Variability as a Source of Extrinsic Cellular Noise
IGJ, B Gaal, R das Neves, T Enver, F Iborra, N Jones
PLoS Comput Biol 8 e1002416 (2011)

5. Evolutionary dynamics in a simple model of self-assembly
IGJ, S Ahnert, J Doye, A Louis
Phys Rev E 83 066105 (2011)

4. The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks
S Greenbury, IGJ, M Smith, J Doye, A Louis
J Theor Biol 267 48 (2010)

3. Self-assembly, modularity, and physical complexity
S Ahnert, IGJ, T Fink, J Doye, A Louis
Phys Rev E 82 026117 (2010)

2. Modelling the self-assembly of virus capsids
IGJ, A Louis, J Doye
J Phys: Condens Matt 22 104101 (2010)
(Journal front cover and 2010 highlight)

1. The self-assembly of DNA Holliday junctions studied with a minimal model
T Ouldridge, IGJ, A Louis, J Doye
J Chem Phys 130 065101 (2009)