Dr Sara Jabbari BA PhD

Dr Sara Jabbari

School of Mathematics
Reader in Mathematical Biology

Contact details

Telephone
+44 (0) 121 414 6196
Email
s.jabbari@bham.ac.uk
View my research portal
Address
School of Mathematics
Watson Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Sara Jabbari is a Reader in Mathematical Biology, School lead for Equality, Diversity and Inclusion, and a BEaMS Staff Contact for students in the College of Engineering and Physical Sciences. She also sits on the Institute of Microbiology and Infection's Steering Group.

Her research group uses an interdisciplinary approach to understand microbial behaviour, with a particular focus on using mathematical modelling to develop or improve novel treatments for bacterial infections. By combining models with relevant experimental data, they study bacteria from the intra-cellular level up to host-pathogen interactions to identify and refine relevant experimental work with a view to accelerating drug development. Mathematical techniques used include numerical and asymptotic analyses combined with reliable model parameterisation.

Sara has received funding for her research from diverse sources, including BBSRC, MRC and the Leverhulme Trust.

Qualifications

  • PhD Mathematical Biology, University of Nottingham, 2007
  • BA Mathematics, Durham University, 2003

Biography

Sara Jabbari graduated from Durham University in 2003, incorporating a year of study at the Université Louis Pasteur in Strasbourg, France. She went on to complete a PhD in mathematical modelling of cell-cell bacterial communication under the supervision of Prof. John R. King at the University of Nottingham.

Following a post-doc position on an international interdisciplinary systems biology project examining biofuel production by bacteria, in 2011 Sara was awarded a Biomedical Informatics Fellowship from the MRC. This has provided her with invaluable laboratory experience for carrying out and designing interdisciplinary projects. Sara was appointed a Birmingham Fellow in 2012 to explore mathematical modelling of medically significant microorganisms. In addition to her role in the School of Mathematics, she is a member of the Institute of Microbiology and Infection, the Healthcare Technologies Research Institute and the Centre for Computational Biology at Birmingham.

Teaching

Semester 2

LI/LH Differential Equations

Research

Research themes

  • Mathematical modelling, particularly applied to biological systems, e.g. gene regulation networks.
  • The use of asymptotic methods to analyse and simplify mathematical models.
  • Integration of experimental data into mathematical models.

Research activity

 Mathematical modelling of:

  • Novel treatments for bacterial infections
  • The emergence of antimicrobial resistance
  • Gene regulation networks
  • Biological signalling pathways (e.g. quorum sensing)

While most of her group’s work centres on bacteria, they also study fungal and viral dynamics, in addition to host responses to disease and inflammation. Fully funded research projects led by Sara include "A systems biology approach to understanding and combating Clostridium difficile infection" (MRC) and "Maths-AIM: A mathematical and experimental approach for the rational assessment of bacterial Adhesion Inhibitor Materials in vivo" (BBSRC). Past and present members of her group include:

  • Dr Paul Roberts (BBSRC funded mathematics PDRA)
  • Chloe Spalding (EPSRC funded mathematics PhD student)
  • Will Thomson (EPSRC funded mathematics PhD student)
  • George Youlden (EPSRC funded mathematics PhD student, joint programme with University of Nottingham)
  • Emma Keen (BBSRC funded wet-lab technician)
  • Ryan Kerr (Wellcome Trust funded PhD student, Antimicrobials and Antimicrobial Resistance)
  • Vicky Hagel (Wellcome Trust funded PhD student, Mechanisms of Inflammatory Disease (MIDAS))
  • Aliya Alsaleh (PhD student)
  • Cameron Wilcox (Leverhulme Trust funded PhD student)
  • Sandeep Shirgill (MIBTP PhD student)

Publications

Recent publications

Article

Kerr, R, Jabbari, S, Blair, J & Johnston, IG 2022, 'Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression', Journal of The Royal Society Interface, vol. 19, no. 186, 20210771. https://doi.org/10.1098/rsif.2021.0771

Mostefaoui, IM, Moussaoui, A & Jabbari, S 2022, 'Large time behavior of nonautonomous differential systems modeling antibiotic-resistant bacteria in rivers', Mathematical Methods in the Applied Sciences . https://doi.org/10.1002/mma.8854

Youlden, G, McNeil, HE, Blair, JMA, Jabbari, S & King, JR 2022, 'Mathematical modelling highlights the potential for genetic manipulation as an adjuvant to counter efflux-mediated MDR in salmonella', Bulletin of Mathematical Biology, vol. 84, no. 5, 56. https://doi.org/10.1007/s11538-022-01011-9

Spalding, C, Shirgill, S, Keen, E, Krachler, AM & Jabbari, S 2022, 'Mathematical modelling of Pseudomonas aeruginosa L-forms reveals complex interplay between host defence mechanisms and putative treatments', Frontiers in Systems Biology, vol. 2, no. 2, 899990. https://doi.org/10.3389/fsysb.2022.899990

Mountcastle, S, Vyas, N, Villapun, VM, Cox, S, Jabbari, S, Sammons, R, Shelton, R, Walmsley, D & Kuehne, S 2021, 'Biofilm viability checker: an open-source tool for automated biofilm viability analysis from confocal microscopy images', npj Biofilms and Microbiomes, vol. 7, no. 1, 44. https://doi.org/10.1038/s41522-021-00214-7

Youlden, G, Ricci, V, Wang Kan, X, Piddock, L, Jabbari, S & King, JR 2021, 'Time dependent asymptotic analysis of the gene regulatory network of the AcrAB-TolC efflux pump system in gram-negative bacteria', Journal of Mathematical Biology, vol. 82, no. 4, 31. https://doi.org/10.1007/s00285-021-01576-4

Mountcastle, S, Cox, S, Sammons, R, Jabbari, S, Shelton, R & Kuehne, S 2020, 'A review of co-culture models to study the oral microenvironment and disease', Journal of Oral Microbiology, vol. 12, no. 1, 1773122. https://doi.org/10.1080/20002297.2020.1773122

Beentjes, CHL, Taylor-King, JP, Bayani, A, Davis, CN, Dunster, JL, Jabbari, S, Mirams, GR, Jenkinson, C, Kilby, M, Hewison, M & Tamblyn, JA 2019, 'Defining vitamin D status using multi-metabolite mathematical modelling: a pregnancy perspective', The Journal of Steroid Biochemistry and Molecular Biology, vol. 190, pp. 152-160. https://doi.org/10.1016/j.jsbmb.2019.03.024

Kerr, R, Jabbari, S & Johnston, I 2019, 'Intracellular energy variability modulates cellular decision-making capacity', Scientific Reports, vol. 9, 20196. https://doi.org/10.1038/s41598-019-56587-5

Roberts, P, Huebinger, RM, Keen, E, Krachler, AM & Jabbari, S 2019, 'Mathematical model predicts anti-adhesion–antibiotic–debridement combination therapies can clear an antibiotic resistant infection', PLoS Computational Biology, vol. 15, no. 7, e1007211. https://doi.org/10.1371/journal.pcbi.1007211

Thomson, W, Jabbari, S, Taylor, AE, Arlt, W & Smith, D 2019, 'Simultaneous parameter estimation and variable selection via the logit-normal continuous analogue of the spike-and-slab prior', Journal of The Royal Society Interface, vol. 16, no. 150, 20180572, pp. 20180572. https://doi.org/10.1098/rsif.2018.0572

Bushell, F, Tonner, P, Jabbari, S, Schmid, A & Lund, P 2019, 'Synergistic impacts of organic acids and pH on growth of Pseudomonas aeruginosa: a comparison of parametric and Bayesian non-parametric methods to model growth', Frontiers in Microbiology, vol. 09, 3196. https://doi.org/10.3389/fmicb.2018.03196

Spalding, C, Keen, E, Smith, DJ, Krachler, A-M & Jabbari, S 2018, 'Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa', PLoS Computational Biology, vol. 14, no. 2, e1006012. https://doi.org/10.1371/journal.pcbi.1006012

Roberts, PA, Huebinger, RM, Keen, E, Krachler, A & Jabbari, S 2018, 'Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds', PLoS Computational Biology, vol. 14, no. 5, e1006071. https://doi.org/10.1371/journal.pcbi.1006071

Review article

Jabbari, S 2022, 'Unravelling microbial efflux through mathematical modelling', Microbiology, vol. 168, no. 11, 001264. https://doi.org/10.1099/mic.0.001264

View all publications in research portal