Biology subjects

de Boer, R. J.

Publications and source records attributed to de Boer, R. J..

9 recordsLinked to original sources

bioRxiv2026

High-dimensional HIV-1 quasispecies modeling guides escape-proof antibody design

Rapidly evolving viruses form diverse quasispecies that enable escape from immune responses and treatments. For example, HIV-1 can rebound within weeks of broadly neutralizing antibody (bNAb) treatment through the outgrowth of high-fitness escape mutants in the quasispecies or the evolution of new escape variants. Most existing models of viral dynamics consider only a small number of viral variants and either assume arbitrary mutant fitness distributions or require extensive fitting to sparse clinical data. Here, we develop a high-dimensional HIV-1 quasispecies model that captures the dynamics of millions of viral strains and parameterize this using in silico binding affinity predictions. Without fitting to experimental data, the model qualitatively reproduces viral rebound following bNAb treatment. Lower-dimensional model projections recover these dynamics only when informed by features derived from the high-dimensional model. Finally, we use the model to develop a quasispecies-based framework for antibody optimization and identify antibodies predicted to effectively suppress viremia. Together, our results demonstrate that integrating mechanistic genotype-phenotype maps with high-dimensional quasispecies models provides unprecedented insights into viral evolution.

systems biology↗

bioRxiv2023

Towards a robust comparison of diversity between sampled TCR repertoires

T-cell receptor (TCR) repertoire sequencing data provides quantitative insight into the distribution of T-cell clones. The diversity of the TCR repertoire in humans tends do decrease with age, which may be a key determinant explaining immune senescence in older individuals. To address this, we first analyze how the diversity of a potential T-cell response against an unseen pathogen changes with age. Next, we discuss the complications with interpreting the outcomes of such an analysis. Specifically, the changes in T-cell subset sizes confound analyses of TCR diversity, and typical sample sizes do not easily allow for a robust quantification of this diversity. Thus, explaining immune senescence as a result of decreasing TCR diversity is far from straightforward and requires a detailed, robust, and quantitative analysis.

immunology↗

bioRxiv2021

Turnover of MCMV-expanded CD8+ T-cells is similar to that of memory phenotype T-cells and independent of the magnitude of the response

The potential of memory T-cells to provide protection against re-infection is beyond question. Yet, it remains debated whether long-term T-cell memory is due to long-lived memory cells. There is ample evidence that blood-derived memory phenotype CD8+ T-cells maintain themselves through cell division, rather than through longevity of individual cells. It has recently been proposed, however, that there may be heterogeneity in the lifespans of memory T-cells, depending on factors such as exposure to cognate antigen. Cytomegalovirus (CMV) infection induces not only conventional, contracting T-cell responses, but also inflationary CD8+ T-cell responses, which are maintained at unusually high numbers, and are even thought to continue to expand over time. It has been proposed that such inflating T-cell responses result from the accumulation of relatively long-lived CMV-specific memory CD8+ T-cells. Using in vivo deuterium labelling and mathematical modelling, we found that the average production rates and expected lifespans of mouse CMV-specific CD8+ T-cells are very similar to those of bulk memory-phenotype CD8+ T-cells. Even CMV-specific inflationary CD8+ T-cell responses that differ three-fold in size, were found to turn over at similar rates.

immunology↗

bioRxiv2021

TCRβ rearrangements without D-segment are common, abundant and public

T cells play an important role in adaptive immunity. An enormous clonal diversity of T-cells with a different specificity, encoded by the T-cell receptor (TCR), protect the body against infection. Most TCR{beta} chains are generated from a V-, D-, and J-segment during recombination in the thymus. Although complete absence of the D-segment is not easily detectable from sequencing data, we find convincing evidence for a substantial proportion of TCR{beta} rearrangements lacking a D-segment. Additionally, sequences without a D-segment are more likely to be abundant within individuals and/or shared between individuals. We find that such sequences are preferentially generated during fetal development and persist within the elderly. Summarizing, TCR{beta} rearrangements without a D-segment are not uncommon, and tend to allow for TCR{beta} chains with a high abundance in the naive repertoire.

immunology↗

bioRxiv2020

Cancer cell elimination by cytotoxic T cell cooperation and additive damage

Cytotoxic T lymphocytes (CTL) eliminate tumor target cells in an antigen and cell-contact dependent manner. Lethal hit delivery occurs as a rapid and binary, "yes/no" process when immunogenicity is very high1-3, however in vivo CTL often fail to kill solid tumor cells during 1:1 conjugations4-6. Using long-term time-lapse microscopy in three distinct tumor cytotoxicity models and statistical modeling, we here show that migrating CTL transit between target cells and initiate apoptosis by a series of sublethal interactions ( additive cytotoxicity), while individual conjugations rarely induced apoptosis. Sublethal damage included perforin-dependent membrane pore formation, nuclear lamina rupture and DNA damage, and these events resolved within minutes to hours. In immunogenic B16F10 melanoma tumors in vivo, frequent serial engagements and sublethal hit delivery of CTL was largely confined to interstitial niches in the invasion front, resulting in eradication of invading tumor cells. Thus, additive cytotoxicity is a probabilistic process achieved by a series of CTL-target cell engagements and sublethal events. The need for additive "hits" has implications for the topographic mechanisms of elimination or immune evasion of tumor cells and microenvironmental regulation of CTL accumulation and cooperation by targeted therapy.

immunology↗

bioRxiv2020

Testing structural identifiability by a simple scaling method

Successful mathematical modeling of biological processes relies on the expertise of the modeler to capture the essential mechanisms in the process at hand and on the ability to extract useful information from empirical data. The very structure of the model limits the ability to infer numerical values for the parameters, a concept referred to as structural identifiability. Most of the available methods to test the structural identifiability of a model are either too complex mathematically for the general practitioner to be applied, or require involved calculations or numerical computation for complex non-linear models. In this work, we present a new analytical method to test structural identifiability of models based on ordinary differential equations, based on the invariance of the equations under the scaling transformation of its parameters. The method is based on rigorous mathematical results but it is easy and quick to apply, even to test the identifiability of sophisticated highly non-linear models. We illustrate our method by example and compare its performance with other existing methods in the literature. Author summaryTheoretical Biology is a useful approach to explain, generate hypotheses, or discriminate among competing theories. A well-formulated model has to be complex enough to capture the relevant mechanisms of the problem, and simple enough to be fitted to data. Structural identifiability tests aim to recognize, in advance, if the structure of the model allows parameter fitting even with unlimited high-quality data. Available methods require advanced mathematical skills, or are too costly for high-dimensional non-linear models. We propose an analytical method based on scale invariance of the equations. It provides definite answers to the structural identifiability problem while being simple enough to be performed in a few lines of calculations without any computational aid. It favorably compares with other existing methods.

systems biology↗

bioRxiv2019

CXCL4 links inflammation and fibrosis through transcriptional and epigenetic reprogramming of monocyte-derived cells

Fibrosis is a condition shared by numerous inflammatory diseases. Our incomplete understanding of the molecular mechanisms underlying fibrosis has severely hampered effective drug development. CXCL4 is associated with the onset and extent of fibrosis development in systemic sclerosis, a prototypic inflammatory and fibrotic disease. Here, we integrated 65 paired longitudinal transcriptional and methylation profiles from monocyte-derived cells with/without CXCL4 exposure. Using data-driven gene regulatory network analyses, we demonstrate that CXCL4 dramatically alters the trajectory of monocyte differentiation, inducing a novel pro-inflammatory and pro-fibrotic phenotype mediated via key transcriptional regulators including CIITA. CXCL4 exposed monocyte-derived cells directly trigger a fibrotic cascade by producing ECM molecules and inducing myofibroblast differentiation. Inhibition of CIITA mimicked CXCL4 in inducing a pro-inflammatory and pro-fibrotic phenotype, validating the relevance of the gene regulatory network. Our study unveils CXCL4 as a key secreted factor driving innate immune training and forming the long-sought link between inflammation and fibrosis.

bioinformatics↗

bioRxiv2019

The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes

The human naive T-cell receptor (TCR) repertoire is extremely diverse and accurately estimating its distribution is challenging. We address this challenge by combining a quantitative sequencing protocol of TCRA and TCRB sequences with computational modelling. We observed the vast majority of TCR chains only once in our samples, confirming the enormous diversity of the naive repertoire. However, a substantial number of sequences were observed multiple times within samples, and we demonstrated that this is due to expression by many cells in the naive pool. We reason that and {beta} chains are frequently observed due to a combination of selective processes and summation over multiple clones expressing these chains. We test the contribution of both mechanisms by predicting samples from phenomenological and mechanistically modelled repertoire distributions. By comparing these with sequencing data, we show that frequently observed chains are likely to be derived from multiple clones. Still, a neutral model of T-cell homeostasis cannot account for the observed distributions. We conclude that the data are only compatible with distributions of many small clones in combination with a sufficient number of very large naive T-cell clones, the latter most likely as a result of peripheral selection.

immunology↗

bioRxiv2018

Both cell-intrinsic and environmental factors constrain speed and persistence in T cell migration

Cell migration is astoundingly diverse. Molecular signatures, cell-cell and cell-matrix interactions, and environmental structures each play their part in shaping cell motion, yielding numerous different cell morphologies and migration modes. Nevertheless, in recent years, a simple unifying law was found to describe cell migration across many different cell types and contexts: faster cells turn less frequently. Given this universal coupling between speed and persistence (UCSP), from a modelling perspective it is important to know whether computational models of cell migration capture this speed-persistence link. Here, we present an in-depth characterisation of an existing Cellular Potts Model (CPM). We first show that this model robustly reproduces the UCSP without having been designed for this task. Instead, we show that this fundamental law of migration emerges spontaneously through a crosstalk of intracellular mechanisms, cell shape, and environmental constraints, resembling the dynamic nature of cell migration in vivo. Our model also reveals how cell shape dynamics can further constrain cell motility by limiting both the speed and persistence a cell can reach, and how a rigid environment such as the skin can restrict cell motility even further. Our results further validate the CPM as a model of cell migration, and shed new light on the speed-persistence coupling that has emerged as a fundamental property of migrating cells. SIGNIFICANCEThe universal coupling between speed and persistence (UCSP) is the first general quantitative law describing motility patterns across the versatile spectrum of migrating cells. Here, we show - for the first time - that this migration law emerges spontaneously in an existing, highly popular computational model of cell migration. Studying the UCSP in entirely different model frameworks, not explicitly built with this law in mind, can help uncover how intracellular dynamics, cell shape, and environment interact to produce the diverse motility patterns observed in migrating cells.

immunology↗