Dr Mario Recker

Associate Professor in Applied Mathematics


Telephone: 01326 259329

Royal Society University Research Fellow


Research Interests

Many pathogens utilise antigenic and phenotypic diversity as a means to avoid detection and clearance by the host’s immune system. This enables them to remain within the host for prolonged periods of time, allows the pathogen to establish infections in previously exposed individuals and can lead to highly varied infection outcomes. My research focuses on the multifaceted epidemiology of antigenically and phenotypically diverse pathogens, such as Plasmodium falciparum, dengue or Staphylococcus aureus. With the help of mathematical models and in close collaboration with field and laboratory scientists I investigate the evolutionary epidemiology of these pathogens, focusing on host-pathogen interactions at multiple ecological scales that link within-host processes of gene expression and immune selection to between-host epidemiological patterns of infection and disease.



The causative agent of severe malaria in humans, Plasmodium falciparum, employs a sophisticated immune evasion startegy, called antigenic variation, to circumvent the host's immune pressure and maintain long lasting infections. Central to this process is the var multi-gene family, which encode the cell-surface antigens PfEMP1. Mutually exclusive switching between ~60 members of these highly polymorphic genes ensures that only a small fraction of the whole antigenic reperoire is exposed to the immune system at a time. PfEMP1 are also involved in malaria virulence. They mediate the attachement of parasitised red blood cells to host tissues, which can then lead to parasite sequestration and obstruction of blood flow in vital organs, such as the brain or placenta. Different PfEMP1 variants adhere to different host tissues, and antigenic switches between var genes can therefore also lead to a phenotypic change during the course of an infection. The involvement of var genes and var gene switching is therefore central for our understanding of the infection dynamics, pathology and epidemiology of P. falciparum malaria.

I am particularly interested in the underlying patterns of var gene switching, and how these relate to observed gene expression pattern in individuals growing up in malaria endemic regions. E.g. we have shown that antigenic switching is a highly non-random process in which different genes have different, hard-wired switch characteristics in terms of the rates at which they are activated or silenced [Noble et al. (2013), Recker et al. (2011)]. Furthermore, we could show the resulting switch hierarchy is inherently linked to gene recombination and therefore the generation of further antigenic diversity in these parasites. My work currently focuses on developing multi-scale, mathematical frameworks that integrate molecular genetic processes with the dynamics of within-host infections and between-host epidemiologies.

Selected Publications

  • Holding T, & Recker M (2015). Maintenance of phenotypic diversity within a set of virulence encoding genes of the malaria parasite Plasmodium falciparum. J R Soc Interface, 12(113)

  • Noble R, Christodoulou Z, Kyes S, Pinches R , Newbold CI, & Recker M (2013). The antigenic switching network of Plasmodium falciparum and its implications for the immuno-epidemiology of malaria. eLife 2013;2:e01074

  • Buckee CO, & Recker M (2012). Evolution of the multi-domain structures of virulence genes in the human malaria parasite Plasmodium falciparum. PLoS Comp Biol, 8(4): e1002451

  • Recker M, Buckee CO, Serazin A, Kyes S, Pinches R, Christodoulou Z, Springer AL, Gupta S, Newbold CI (2011). Antigenic variation in Plasmodium falciparum malaria involves a highly structured switching pattern. PLoS Pathog, 7(3):e1001306

  • Recker M, Nee S, Bull PC, Kinyanjui S, Marsh K, Newbold C, & Gupta S (2004). Transient cross-reactive immune responses can orchestrate anti­genic variation in malaria. Nature, 429(6991):555-8



In less than six decades dengue has emerged from South East Asia to become the most widespread arbovirus affecting human populations. A recent dramatic increase in epidemic dengue fever has mainly been attributed to factors such as vector expansion and ongoing ecological, climate and socio-demographic changes. The lack of antivirals or vaccines and the current failure to control the pathogen in endemic regions and to prevent globalized distribution of the vector-species and viral variants underlines the urgency for reassessment of previous research methods, hypothesis and empirical observations.

Previous modelling approaches have mostly focused on the impact of immunological competition between dengue’s four serotypes (DENV1-4), which can generate a frequency-dependent mechanism that partially explains dengue's temporal epidemiological patterns. We have developed a spatially explicit, individual-based model to investigate the effects of demographic and ecological stochasticities. Our model demostrated that amplification of natural stochastic differences in disease transmission can give rise to persistent oscillations comprising semi-regular epidemic outbreaks and sequential serotype dominance that are characteristic of dengue's epidemiolgical dynamics. Work is currently under way to address such questions as if and how host ecological and demographic heterogeneities are shaping the viral evolution of dengue, and how different population structures (small-world, lattice, scale-free, etc) can affect the spatial epidemiology of dengue, including persistence and synchrony?

Selected Publications

  • Flasche S, Jit M, Rodríguez-Barraquer I, Coudeville L, Recker M*, et al. (2016). The long term safety, public health impact, and cost effectiveness of routine vaccination with a recombinant, live-attenuated dengue vaccine (Dengvaxia): a model comparison study.  PLoS Medicine13(11):e1002181

  • Lourenço J, & Recker M (2016). Dengue serotype immune-interactions and their consequences for vaccine impact predictions. Epidemics, 16: 40-48

  • Lourenço J, & Recker M (2014). The 2012 Madeira dengue outbreak: epidemiological determinants and future epidemic potential. PLoS Negl Trop Dis, 8(8):e3083

  • Lourenço J, & Recker M (2013). Natural, persistent oscillations in a spatial multi-strain disease system with application to dengue. PLoS Comp Biol, 9(10): e1003308



Antimicrobial resistance (AMR) is a major global public health issue, making first-line treatments of many bacterial infections ineffective. One of the best known examples is the methicillin-resistant Staphylococcus aureus, or MRSA. It is the most common cause of hospital-acquired infections although community acquired MRSA (CA-MRSA) is also becoming of increasing concern. S. aureus is an opportunistic pathogen. It colonises around 30% of the human population, where its interactions with the human hosts are largely asymptomatic. Infections most commonly result from breaches in the host’s innate immunity and can result in both acute and chronic disease. The most severe form of infection occurs when S. aureus gains access to the blood stream, which is referred to as bacteraemia. This is often aided by breakages in the skin or mucosal membranes, for example due to surgery or the use of catheters, and can lead to very high fatality rate in the absence of antibiotic treatment.  

The genes expressed by S. aureus and their interaction with the human immune system facilitating such varied infections are not fully understood, and my work on MRSA focuses on understanding this bacterial virulence as a complex phenotype. In collaboration with researchers at Bath University and by using whole genome approaches, combined with functional genomics, mathematical and statistical modelling we have made important headway in seeking to map phenotype directly from genotype (Laabei et al. (2014)) and to understand how bacterial virulence evolved as a trade-off between maintaining fitness at the within-host level and at the between-host level (Laabei et al. (2015)). By analysing fully sequenced and phenotyped, clinical isolates we are currently investigating if and to what degree severe infection outcomes can be predicted using machine learning algorithms, which would be an important step towards personalised medicine and infectious disease management.

Selected Publications

  • Laabei M, Uhlemann AC, Lowy FD, Austin ED, Yokoyama M, Ouadi K, Feil E, Thorpe HA, Williams B, Perkins M, Peacock SJ, Clarke SR, Dordel J, Holden M, Votintseva AA, Bowden R, Crook DW, Young BC, Wilson DJ, Recker M*, Massey RC (2015) Evolutionary Trade-Offs Underlie the Multi-faceted Virulence of Staphylococcus aureus. PLoS Biol, 13(9):e1002229

  • Laabei M*, Recker M*, Rudkin J, Sloan T, Williams P, Lewis K, Scowen L, Peacock S, van den Elsen J, Priest N, Feil E, Josefsson E, & Massey RC (2014). Predicting the virulence of MRSA from its genome sequence. Genome Res, 24: 839-849

  • Priest NK, RudkinJ, Feil EJ, van den Elsen J, Cheung A, Peacock JP, Laabei M, Lucks DA, Recker M, & Massey RC (2012). From genotype to phenotype: can systems biology be used to predict Staphylococcus aureus virulence. Nat Rev Microbiol, 10(11):791-7

  • Collins J, Rudkin J, Recker M, Pozzi C, O'Gara JP, & Massey RC (2010). Offsetting virulence and antibiotic resistance costs by MRSA. ISME J, 4(4):577-84.