Biology subjects

De Boer, R. j.

Publications and source records attributed to De Boer, R. j..

3 recordsLinked to original sources

bioRxiv2025

Modeling Phage Therapy

Patients infected with life-threatening multi-drug resistant (MDR) bacteria have been treated with cocktails of bacteriophages. This is a complicated form of personalized medicine as the phages given to a patient have to be selected beforehand on the basis of their lytic capacity of the infecting bacteria. Because bacteria rapidly become resistant, the evolution of resistance to a diverse cocktail of phages is a complicated dynamical process, during which competing bacterial strains replace one another by accumulating several resistance mechanisms, each of which may involve a fitness cost. As a consequence, it is typically not known why a particular phage therapy succeeded or failed, and how one can optimize the composition of the cocktails to maximize the rate of success. To improve upon this, we extend an existing in vivo-calibrated mouse model into a novel mathematical model for the human situation, and include multiple phages infecting multiple bacterial strains, differing in their resistance to each of the phages. We adjust several parameter estimates of the bacterial model to the human situation, and use the model to describe a successful case of phage therapy involving several cocktails, each containing several phages. In the model, treatment success crucially depended on pretreatment resistance levels, and on the diversity and the timing of the cocktails. Once an appropriate cocktail is found, it is less important to further optimize the infection rates of the phages. Resistant bacterial strains expand rapidly when sensitive strains decline, and the higher the infectivity of the phages, the faster resistant strains expand. Because resistance evolves rapidly, it is best to provide a diverse set of phages right from the start of therapy, i.e., to hit hard and early, and create a high genetic barrier to bacterial resistance.

microbiology↗

bioRxiv2021

Age-dependent normalisation functions for T-lymphocytes in healthy individuals

Lymphocyte numbers naturally change through age. Normalisation functions to account for this are sparse, and mostly disregard measurements from children in which these changes are most prominent. In this study, we analyse cross-sectional numbers of mainly T-lymphocytes (CD3+, CD3+CD4+ and CD3+CD8+) and their subpopulations (naive and memory) from 673 healthy Dutch individuals ranging from infancy to adulthood (0-62 years). We fitted the data by a delayed exponential function and received parameter estimates for each lymphocyte subset. Our modelling approach follows general laboratory measurement procedures in which absolute cell counts of T-lymphocyte subsets are calculated from observed percentages within a reference population that is truly counted (typically the total lymphocyte count). Consequently, we receive one set of parameter estimates per T-cell subset representing both the trajectories of their counts and percentages. We allow for an initial time delay of half a year before the total lymphocyte counts per {micro}l of blood start to change exponentially, and we find that T-lymphocyte trajectories tend to increase during the first half a year of life. Thus, our study provides functions describing the general trajectories of T-lymphocyte counts and percentages of the Dutch population. These functions provide important references to study T-lymphocyte dynamics in disease, and allow one to quantify losses and gains in longitudinal data, such as the CD4+ T-cell decline in HIV-infected children, and/or the rate of T-cell recovery after the onset of treatment.

immunology↗

bioRxiv2020

Modeling the immunological pre-adaptation of HIV-1

It is becoming increasingly evident that the evolution of HIV-1 is to a large extent determined by the immunological background of the host. On the population-level this results in associations between specific human leukocyte antigen (HLA) alleles and polymorphic loci of the virus. Furthermore, some HLA alleles that were previously associated with slow progression to AIDS have been shown to lose their protective effect, because HLA-specific immunological escape variants have spread through the population. This phenomenon is known as immunological pre-adaptation. Apart from adapting to human immune responses, the set-point virus load (SPVL) of HIV-1 is thought to have evolved to values that optimize the population-level fitness of the virus. This suggestion is supported by considerable heritability of the SPVL. Previous modeling studies show that whether or not SPVL optimization is expected to occur depends sensitively on the underlying assumptions with respect to the extent of within-versus between-host selection. Here we use a detailed and semi-realistic multi-level HIV-1 model in which immunological pre-adaptation and SPVL evolution can emerge from the underlying interactions of the virus with the immune system of the host. This enables us to study the effect of immunological escape on disease progression, and how disease progression may be molded by SPVL evolution. We find that the time to AIDS could decrease significantly (0.5-1.0 years) in a HLA-dependent manner by immunological pre-adaptation over the long-term course of the epidemic (> 100 years). We find that SPVL is not expected to evolve to optimize the population-level fitness of HIV-1, even though high heritability of the SPVL emerges from continual selection of immune-escape mutations.

evolutionary biology↗