Lauren M. Childs - Research

Research

I am interested in the use of mathematical models with a focus on dynamical systems on biologically-motivated questions. My current and past research include mathematical and computational models with the following applications: the immune system, infectious disease, bacteriophage- host interactions, fish schools, and coupled oscillators.

Evolution of antibody repertoires
During an infection pathogens display a range of antigens to the host immune system. Despite the diversity and importance of antigens presented little is known about the adaptation of the host immune system to control multiple antigens simultaneously. In collaboration with Dr. Sarah Cobey at the University of Chicago, we model affinity maturation of receptors sequences of B-cells, which ultimately create protective antibodies, during an infection and explore how variation in the number and breadth of exposed pathogen immunogenic alters the host’s antibody repertoire.

Dynamics of Pathogens within host
My research generates and investigates models describing the dynamics of pathogen populations within hosts and incorporates these models and their output into population-wide measures. These models are used to examine variation in infectiousness across a pathogen lifecycle to determine the impact at a population level. The primary application of these models has been Plasmodium falciparum malaria where I have modeled the interactions between the parasite and the human immune system (with Dr. Caroline Buckee at the Harvard School of Public Health), the development of the parasite within the mosquito (with Dr. Olivia Prosper at Dartmouth College), the impact of mosquito dynamics on malaria spread (with Dr. Buckee and Dr. Flaminia Caterrucia at the Harvard School of Public Health), and development of sexual malaria parasites (with Dr. Buckee and Dr. Matthias Marti at the Harvard School of Public Health).

CRISPR: Understanding how much bacteria can understand about viruses that infect them
A novel bacterial defense system against invading viruses, known as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), has recently been described. Unlike other bacterial defense systems, CRISPRs are virus-specific and heritable, producing a form of adaptive immune memory. Specific bacterial DNA regions, CRISPR loci, incorporate on average 20 copies of unique short (~30 base pair) regions of viral DNA which then allow the bacteria to detect, degrade and have immunity to viruses with matching sub-sequences. I studied the coevolutionary dynamics between the bacteria and viruses as well as the dynamics of insertion and deletion of the unique viral DNA sequences.

Macrophage Activation
I studied a substrate-enzyme chemical reaction within macrophage cells, important effector cells of the immune system. We considered macrophages as they became activated under two distinct environmental conditions: appearance of pathogen in the body and presence of wounded cellular material. We collaborated with the lab of Dr. Matthias Hesse formerly at Cornell University using both mathematics, through analysis and simulation of a system of coupled ODEs, and experiments. We demonstrated that an individual macrophage, rather than a population as a whole, is able, under particular conditions, to convert between pathogen-killing and wound-healing functional pathways.

Coupled Oscillators
I worked with Dr. Steven Strogatz at Cornell University to analyze the periodically forced Kuramoto model, consisting of an infinite population of phase oscillators with random intrinsic frequencies, global sinusoidal coupling, and external sinusoidal forcing. It represents an idealization of many phenomena in physics, chemistry, and biology in which mutual synchronization competes with forced synchronization. In other words, the oscillators in the population try to synchronize with one another while also trying to lock onto an external drive. We extended previous work by completing a full bifurcation analysis of the model for a case in which the infinite-dimensional dynamics collapsed to a two-dimensional system as described by Antonsen et. al. (2008).

Publications

* denotes equal contribution
  1. W. R. Shaw, P. Marcenac, L. M. Childs, C. O. Buckee, F. Baldini, S. P. Sawadogo, R. K. Dabire, A. Diabate, F. Catteruccia, (2016) Wolbachia infection in natural Anopheles populations affect egg laying and negatively correlate with Plasmodium development. Nature Communications, 7:11772. doi:10.1038/ncomms11772
  2. J.C. Blackwood* and L. M. Childs*, (2016) The role of interconnectivity in control of an Ebola epidemic. Scientific Reports, 6:29262. doi:10.1038/srep29262
  3. H. H. Chang, L. M. Childs, and C. O. Buckee, (2016) Variation in infection length and superinfection enhance selection efficiency in the human malaria parasite. Scientific Reports, 6:26370. doi:10.1038/srep26370
  4. N. Obaldia III, G. S. Dow, L. Gerena, D. Kyle, W. Otero, P. Y. Mantel, N. Baro, R. Daniels, A. Mukherjee, L. M. Childs, C. O. Buckee, M. T. Duraisingh, S. K. Volkman, D. F. Wirth, and M. Marti, (2016) Altered drug susceptibility during host adaptation of a Plasmodium falciparum strain in a non-human primate model. Scientific Reports. doi:10.1038/srep21216
  5. L. M. Childs, E. B. Baskerville, and S. Cobey, (2015) Trade-offs in antibody repertoires to complex antigens. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 370(1676). doi:10.1098/rstb.2014.0245
  6. S. K. Nilsson*, L. M. Childs*, C. O. Buckee, and M. Marti, (2015) Targeting human transmission biology for malaria elimination. PLoS Pathogens, 11(6):e1004871. doi:10.1371/journal.ppat.1004871
  7. L. M. Childs and C. O. Buckee, (2015) Dissecting the determinants of malaria chronicity: why within-host models struggle to reproduce infection dynamics. Journal of the Royal Society Interface, 12(104):20142379. doi:10.1098/rsif.2014.1379
  8. L. M. Childs, N. N. Abuelezam, C. Dye, S. Gupta, M. B. Murray, B. Williams, and C. O. Buckee, (2015) Modelling challenges in context: Lessons from malaria, HIV and tuberculosis. Epidemics, 10:102-107. doi:10.1016/j.epidem.2015.02.002
  9. B. I. Coleman, K. M. Skillman, R. H. Y. Jiang, L. M. Childs, L. M. Altenhofen, M. Ganter, Y. Leung, I. Goldowitz, B. F. C. Kafsack, M. Marti, M. Llinas, C. O. Buckee, and M. T. Duraisingh, (2014) A Plasmodium falciparum histone deacetylase links parasite persistence and sexual conversion. Cell Host Microbe, 16(2):177-86. doi:10.1016/j.chom.2014.06.014
  10. L. M. Childs*, W. E. England*, M. J. Young, J. S. Weitz, and R. J. Whitaker, (2014) CRISPR-induced distributed immunity in microbial populations. PLoS ONE, 9(7):e0101710. doi:10.1371/journal.pone.0101710
  11. N. L. Held, L. M. Childs, M. Davison, J. S. Weitz, R. J. Whitaker, and D. Bhaya, (2013) CRISPR-Cas systems to probe ecological diversity and host-viral interactions. CRISPR-Cas Systems. Springer-Verlag Berlin Heidelberg. doi:10.1007/978-3-642-34657-6-9
  12. L. M. Childs, N. Held, M. Young, R. Whittaker, and J. Weitz, (2012) Multi-scale Model of CRISPR-induced Coevolutionary dynamics: Diversification at the interface of Lamarck and Darwin. Evolution, 66(7):2015--2029. doi:10.1111/j.1558-5646.2012.01595.x
  13. L. M. Childs, M. Paskow, S. Morris, M. Hesse and S. Strogatz, (2011) From inflammation to wound healing: using a simple model to understand the functional versatility of murine macrophages. Bulletin of Mathematical Biology. doi:10.1007/s11538-011-9637-5
  14. L. M. Childs and S. Strogatz, (2008) Stability diagram for the Forced Kuramoto model. CHAOS, 18: 043128. doi 10.1063/1.3049136