Biology subjects

Bjorklund, M.

Publications and source records attributed to Bjorklund, M..

4 recordsLinked to original sources

bioRxiv2023

The difficulties of predicting evolutionary response to selection

There has been a long debate about the difficulties of predicting evolutionary change despite knowledge of selection and genetic variance. One reason might be the stochastic effects of sexual reproduction creating a variance of offspring genotypes and thus phenotypes. This was tested by means of an explicit genetic individual-based simulation with one trait determined by 50 loci. After 100 generations of weak fluctuating selection an experiment was performed where the optimum was displaced one standard deviation. The response and the predicted response were then compared for 100 populations. The simulation shows two things, first there is a considerable variation in response between populations. This was also found when the same population was replicated many times with the same selection. Second, using the individual-based estimates of genetic variance seriously overestimates the predicted response, while an approach using the variance of mean pair breeding values gave essentially unbiased predictions. However, in all cases there was a lack of precision. Hence, the "missing response" is, at least partly, due to an overestimation of predicted response and an inevitable variance around the predicted value.

evolutionary biology↗

bioRxiv2021

Size-scaling promotes senescence-like changes in proteome and organelle content

Senescent cells typically have an enlarged cell size but the reason for this has not been fully elucidated. As abnormal cell size may alter protein concentrations and cellular functionality, we used proteomic data from 59 unperturbed human cell lines to systematically characterize cell-size dependent changes in intracellular protein concentrations and organelle content. Increase in cell size leads to ubiquitous transcriptionally and post-transcriptionally regulated reorganization and dilution of the proteome. Many known senescence proteins display disproportionate size-scaling consistent with their altered expression in senescent cells, while lysosomes and the endoplasmic reticulum expand in larger cells contributing to the senescence phenotype. Analysis of organelle proteome expression identifies p53 and retinoblastoma pathways as mediators of size-scaling, consistent with their role in senescence. Taken together, cell size can alter cellular fitness and function through cumulative reorganization of the proteome and organelle content. An extreme consequence of this pervasive size-scaling appears to be senescence.

cell biology↗

bioRxiv2017

Thermal proteome profiling of breast cancer cells reveals proteasomal activation by CDK4/6 inhibitor palbociclib

Palbociclib is a CDK4/6 inhibitor approved for metastatic estrogen receptor positive breast cancer. In addition to G1 cell cycle arrest, palbociclib treatment results in cell senescence, a phenotype that are not readily explained by CDK4/6 inhibition. In order to identify a molecular mechanism responsible for palbociclib-induced senescence, we performed thermal proteome profiling of MCF7 breast cancer cells. In addition to affecting known CDK4/6 targets, palbociclib induces a thermal stabilization of the 20S proteasome, despite not directly binding to it. We further show that palbociclib treatment increases proteasome activity independently of the ubiquitin pathway. This leads to cellular senescence which can be counteracted by proteasome inhibitors. Palbociclib-induced proteasome activation and senescence is mediated by reduced proteasomal association of ECM29. Loss of ECM29 activates the proteasome, blocks cell proliferation and induces senescence. Finally, we find that ECM29 mRNA levels are predictive of relapse-free survival in breast cancer patients treated with endocrine therapy. In conclusion, thermal proteome profiling identifies the proteasome and ECM29 protein as mediators of palbociclib activity in breast cancer cells.

cancer biology↗

bioRxiv2017

Joint regulation of growth and division timing drives size homeostasis in proliferating animal cells

How organisms maintain cell size homeostasis is a long-standing problem that remains unresolved, especially in multicellular organisms. Recent experiments in diverse animal cell types demonstrate that within a cell population the extent of growth and cellular proliferation (i.e., fitness) is low for small and large cells, but high at intermediate sizes. Here we use mathematical models to explore size-control strategies that drive such a non-monotonic fitness profile resulting in an optimal cell size. Our analysis reveals that if cell size grows exponentially or linearly over time, then fitness always varies monotonically with size irrespective of how timing of division is regulated. Furthermore, if the cell divides upon attaining a critical size (as in the Sizer or size-checkpoint model), then fitness always increases with size irrespective of how growth rate is regulated. These results show that while several size control models can maintain cell size homeostasis, they fail to predict the optimal cell size, and hence unable to explain why cells prefer a certain size. Interestingly, fitness maximization at an optimal size requires two key ingredients: 1) The growth rate decreases with increasing size for large enough cells; and 2) The cell size at the time of division is a function of the newborn size. The latter condition is consistent with the Adder paradigm for division control (division is triggered upon adding a fixed size from birth), or a Sizer-Adder combination. Consistent with theory, Jurkat T cell growth rates, as measured via oxygen consumption or mitochondrial activity, increase with size for small cells, but decrease with size for large cells. In summary, regulation of both growth and cell division timing is critical for size control in animal cells, and this joint-regulation leads to an optimal size where cellular fitness is maximized. Address inquires to A. Singh, E-mail: absingh@udel.edu.

systems biology↗