Biology subjects

Samuel Marguerat

Publications and source records attributed to Samuel Marguerat.

4 recordsLinked to original sources

bioRxiv2016

Size-Dependent Accumulation of the Mitotic Activator Cdc25 as a Mechanism of Size Control in Fission Yeast

Proper cell size is essential for cellular function (Hall et al., 2004). Nonetheless, despite more than 100 years of work on the subject, the mechanisms that maintain cell size homeostasis are largely mysterious (Marshall et al., 2012). Cells in growing populations maintain cell size within a narrow range by coordinating growth and division. Bacterial and eukaryotic cells both demonstrate homeostatic size control, which maintains population-level variation in cell size within a certain range, and returns the population average to that range if it is perturbed (Marshall et al., 2012; Turner et al., 2012; Amodeo and Skotheim, 2015). Recent work has proposed two different strategies for size control: budding yeast has been proposed to use an inhibitor-dilution strategy to regulate size at the G1/S transition (Schmoller et al., 2015), while bacteria appear to use an adder strategy, in which a fixed amount of growth each generation causes cell size to converge on a stable average, a mechanism also suggested for budding yeast (Campos et al., 2014; Jun and Taheri-Araghi, 2015; Taheri-Araghi et al., 2015; Tanouchi et al., 2015; Soifer et al., 2016). Here we present evidence that cell size in the fission yeast Schizosaccharomyces pombe is regulated by a third strategy: the size dependent expression of the mitotic activator Cdc25. The cdc25 transcript levels are regulated such that smaller cells express less Cdc25 and larger cells express more Cdc25, creating an increasing concentration of Cdc25 as cell grow and providing a mechanism for cell to trigger cell division when they reach a threshold concentration of Cdc25. Since regulation of mitotic entry by Cdc25 is well conserved, this mechanism may provide a wide spread solution to the problem of size control in eukaryotes.

Cell Biology↗

bioRxiv2016

A unified coarse-grained theory of bacterial physiology explains the relationship between cell size, growth rate and proteome composition under various growth limitations

Universal observations in Biology are sometimes described as "laws". In E. coli, experimental studies performed over the past six decades have revealed major growth laws relating ribosomal mass fraction and cell size to the growth rate. Because they formalize complex emerging principles in biology, growth laws have been instrumental in shaping our understanding of bacterial physiology. Here, we discovered a novel size law that connects cell size to the inverse of the metabolic proteome mass fraction and the active fraction of ribosomes. We used a simple whole-cell coarse-grained model of cell physiology that combines the proteome allocation theory and the structural model of cell division. The model captures all available experimental data connecting the cell proteome composition, ribosome activity, division size and growth rate in response to nutrient quality, antibiotic treatment and increased protein burden. Finally, a stochastic extension of the model explains non-trivial correlations observed in single cell experiments including the adder principle. This work provides a simple and robust theoretical framework for studying the fundamental principles of cell size determination in unicellular organisms.

Biophysics↗

bioRxiv2014

Skip and bin: pervasive alternative splicing triggers degradation by nuclear RNA surveillance in fission yeast

Exon-skipping is considered a principal mechanism by which eukaryotic cells expand their transcriptome and proteome repertoires, creating different slice varaiants with distinct cellular functions. Here we analyze RNA-seq data from 116 transcriptomes in fission yeast (Schizosaccharomyces pombe), covering multiple physiological conditions as well as transcriptional and RNA processing mutants. We applied brute-force algorithms to detect all possible exon-skipping events, which were ubiquitous but rare compared to canonical splicing events. Exon-skipping events increased in cells deficient for the nuclear exosome or the 5-3 exonuclease Dhp1, and also at late stages of meiotic differentiation when nuclear-exosome transcripts were down-regulated. The pervasive exon-skipping transcripts were stochastic, did not increase in specific physiological conditions, and were mostly present at below 1 copy per cell, even in the absence of nuclear RNA surveillance and late during meiosis. These exon-skipping transcripts are therefore unlikely to be functional and may reflect splicing errors that are actively removed by nuclear RNA surveillance. The average splicing error-rate was [~]0.24% in wild-type and [~]1.75% in nuclear exonuclease mutants. Using an exhaustive search algorithm, we also uncovered thousands of previously unknown splice sites, indicating pervasive splicing, yet most of these novel splicing events were rare and targeted for nuclear degradation. Analysis of human transcriptomes revealed similar, albeit much weaker trends for pervasive exon-skipping transcripts, some of which being degraded by the nuclear exosome. This study highlights widespread, but low frequency alternative splicing which is targeted by nuclear RNA surveillance.

Genomics↗

bioRxiv2014

Proportionality: a valid alternative to correlation for relative data

In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative---or compositional---data, differential expression needs careful interpretation, and correlation---a statistical workhorse for analyzing pairwise relationships---is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic {varphi} which can be used instead of correlation as the basis of familiar analyses and visualization methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes.

Bioinformatics↗