Biology subjects

Beck, R.

Publications and source records attributed to Beck, R..

6 recordsLinked to original sources

bioRxiv2023

Interactions between ploidy and resource availability shape clonal interference at initiation and recurrence of glioblastoma

Glioblastoma (GBM) is the most aggressive form of primary brain tumor. Complete surgical resection of GBM is almost impossible due to the infiltrative nature of the cancer. While no evidence for recent selection events have been found after diagnosis, the selective forces that govern gliomagenesis are strong, shaping the tumors cell composition during the initial progression to malignancy with late consequences for invasiveness and therapy response. We present a mathematical model that simulates the growth and invasion of a glioma, given its ploidy level and the nature of its brain tissue micro-environment (TME), and use it to make inferences about GBM initiation and response to standard-of-care treatment. We approximate the spatial distribution of resource access in the TME through integration of in-silico modelling, multi-omics data and image analysis of primary and recurrent GBM. In the pre-malignant setting, our in-silico results suggest that low ploidy cancer cells are more resistant to starvation-induced cell death. In the malignant setting, between first and second surgery, simulated tumors with different ploidy compositions progressed at different rates. Whether higher ploidy predicted fast recurrence, however, depended on the TME. Historical data supports this dependence on TME resources, as shown by a significant correlation between the median glucose uptake rates in human tissues and the median ploidy of cancer types that arise in the respective tissues (Spearman r = -0.70; P = 0.026). Taken together our findings suggest that availability of metabolic substrates in the TME drives different cell fate decisions for cancer cells with different ploidy and shapes GBM disease initiation and relapse characteristics.

cancer biology↗

bioRxiv2023

Large-scale phylogenomics uncovers a complex evolutionary history and extensive ancestral gene flow in an African primate radiation

Understanding the drivers of speciation is fundamental in evolutionary biology, and recent studies highlight hybridization as a potential facilitator of adaptive radiations. Using whole-genome sequencing data from 22 species of guenons (tribe Cercopithecini), one of the worlds largest primate radiations, we show that rampant gene flow characterizes their evolutionary history, and identify ancient hybridization across deeply divergent lineages differing in ecology, morphology and karyotypes. Lineages experiencing gene flow tend to be more species-rich than non-admixed lineages. Mitochondrial transfers between distant lineages were likely facilitated by co-introgression of co-adapted nuclear variants. Although the genomic landscapes of introgression were largely lineage specific, we found that genes with immune functions were overrepresented in introgressing regions, in line with adaptive introgression, whereas genes involved in pigmentation and morphology may contribute to reproductive isolation. This study provides important insights into the prevalence, role and outcomes of ancestral hybridization in a large mammalian radiation.

evolutionary biology↗

bioRxiv2023

Mathematical modeling of clonal interference by density-dependent selection in heterogeneous cancer cell lines

Many cancer cell lines are aneuploid and heterogeneous, with multiple karyotypes co-existing within the same cell line. Karyotype heterogeneity has been shown to manifest phenotypically, affecting how cells respond to drugs or to minor differences in culture media. Knowing how to interpret karyotype heterogeneity phenotypically, would give insights into cellular phenotypes before they unfold temporally. Here we reanalyze single cell RNA (scRNA)- and scDNA sequencing data from eight stomach cancer cell lines by placing gene expression programs into a phenotypic context. We quantify differences in growth rate and contact inhibition between the eight cell lines using live-cell imaging, and use these differences to prioritize transcriptomic biomarkers of growth rate and carrying capacity. Using these biomarkers, we find significant differences in the predicted growth rate or carrying capacity between multiple karyotypes detected within the same cell line. We use these predictions to simulate how the clonal composition of a cell line will change depending on the timing of splitting cells. Once validated, these models can aid the design of experiments that steer evolution with density dependent selection.

systems biology↗

bioRxiv2022

Self-Assembly of Tunable Intrinsically DisorderedPeptide Amphiphiles

Intrinsically disordered peptide amphiphiles (IDPAs) present a novel class of synthetic conjugates that consist of short hydrophilic polypeptides anchored to hydrocarbon chains. These hybrid polymer-lipid block constructs spontaneously self-assemble into dispersed nanoscopic aggregates or ordered mesophases in aqueous solution due to hydrophobic interactions. Yet, the possible sequence variations and their influence on the self-assembly structures is vast and have hardly been explored. Here, we measure the nanoscopic self-assembled structures of four IDPA systems that differ by their amino acid sequence. We show that permutations in the charge pattern along the sequence remarkably alter the headgroup conformation and consequently alters the pH-triggered phase transitions between spherical, cylindrical micelles and hexagonal condensed phases. We demonstrate that even a single amino acid mutation is sufficient to tune structural transitions in the condensed IDPA mesophases, while peptide conformations remain unfolded and disordered. Furthermore, alteration of the peptide sequence can render IDPAs to become susceptible to enzymatic cleavage and induces enzymatically activated phase transitions. These results hold great potential for embedding multiple functionalities into lipid nanoparticle delivery systems by incorporating IDPAs with desired properties.

biophysics↗

bioRxiv2021

Consistent predictors of microbial community composition across scales in grasslands reveal low context-dependency

Environmental circumstances shaping soil microbial communities have been studied extensively, but due to disparate study designs it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 sampled across regional plant productivity gradients) to examine i) if the same abiotic or biotic factors predict both large- and regional-scale patterns in bacterial and fungal community composition, and ii) if microbial community composition differs consistently with regional plant productivity (low vs high) across different sites. We found that there is high congruence between predictors of microbial community composition across spatial scales; bacteria were predominantly associated with soil properties and fungi with plant community composition. Moreover, there was a microbial community signal that clearly distinguished high and low productivity soils that was shared across worldwide distributed grasslands suggesting that microbial assemblages vary predictably depending on grassland productivity.

ecology↗

bioRxiv2020

CD137-stimulated cytotoxic T lymphocytes exert superior tumour control due to an enhanced antimitotic effect on tumour cells

Several immunotherapeutic strategies for the treatment of cancer are under development. Two prominent strategies are adoptive cell transfer (ACT) of cytotoxic T lymphocytes (CTLs) and modulation of CTL function with immune checkpoint inhibitors or with costimulatory antibodies. Despite some success with these approaches, there remains a lack of detailed and quantitative descriptions of the events following CTL transfer and the impact of immunomodulation. Here, we have applied ordinary differential equation models to two photon imaging data derived from a B16F10 murine melanoma. Models were parameterised with data from two different treatment conditions: either ACT-only, or ACT with intratumoural costimulation using a CD137 targeted antibody. Model dynamics and best fitting parameters were compared, in order to assess the mode of action of the CTLs and examine how the CD137 antibody influenced their activities. We found that the cytolytic activity of the transferred CTLs was minimal without CD137 costimulation, and that the CD137 targeted antibody did not enhance the per-capita killing ability of the transferred CTLs. Instead, the results of our modelling study suggest that an antiproliferative effect of CTLs exerted upon the tumour likely accounted for the majority of the reduction in tumour growth after CTL transfer. We found that CD137 most likely improved tumour control via enhancement of this antiproliferative effect, as well as prolonging the period in which CTLs were inside the tumour, leading to a sustained duration of their antitumour effects following CD137 stimulation. SignificanceCTLs play an important role in controlling tumours, and improved understanding of how they accomplish this will benefit immunotherapeutic cancer treatment strategies. Stimulation of CTLs by targeting their CD137 receptor is a strategy currently under investigation for enhancing responses against tumours, yet so far only limited quantitative knowledge regarding the effects of such stimulation upon CTLs has been obtained. Here, we develop mathematical models to describe dynamic in vivo two-photon imaging of tumour infiltrating CTLs, to characterise differences in their function either in the presence or absence of a CD137 agonist antibody. We showed that an increased antiproliferative effect and a more sustained presence of CTLs within the tumour were the most significant effects associated with anti-CD137 treatment.

cancer biology↗