Biology subjects

Lahtvee, P.-J.

Publications and source records attributed to Lahtvee, P.-J..

3 recordsLinked to original sources

bioRxiv2020

Physical confinement impacts cellular phenotype within living materials

Additive manufacturing allows three-dimensional printing of polymeric materials together with cells, creating living materials for applications in biomedical research and biotechnology. However, understanding the cellular phenotype within living materials is lacking and a key limitation for their wider application. Herein, we present an approach to characterize the cellular phenotype within living materials. We immobilized the budding yeast Saccharomyces cerevisiae in three different photocross-linkable triblock polymeric hydrogels containing F127-bis-urethane methacrylate, F127-dimethacrylate, or poly(alkyl glycidyl ether)-dimethacrylate. Using optical and scanning electron microscopy, we showed that hydrogels based on these polymers were stable under physiological conditions, but yeast colonies showed differences in the interaction within the living materials. We found that the physical confinement, imparted by compositional and structural properties of the hydrogels, impacted the cellular phenotype by reducing the size of cells in living materials compared with suspension cells. These properties also contributed to the differences in immobilization patterns, growth of colonies, and colony coatings. We observed that a composition-dependent degradation of polymers was likely possible by cells residing in the living materials. In conclusion, our investigation highlights the need for a holistic understanding of the cellular response within hydrogels to facilitate the synthesis of application-specific polymers and the design of advanced living materials in the future.

bioengineering↗

bioRxiv2020

Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae

Protein quantification via label-free mass spectrometry (MS) has become an increasingly popular method for determining genome-wide absolute protein abundances. A known caveat of this approach is the poor technical reproducibility, i.e. how consistent the estimations are when the same sample is measured repeatedly. Here, we measured proteomics data for Saccharomyces cerevisiae with both biological and inter-batch technical triplicates, to analyze both accuracy and precision of protein quantification via MS. Moreover, we analyzed how these metrics vary when applying different methods for converting MS intensities to absolute protein abundances. We found that a simple normalization and rescaling approach performs as accurately yet more precisely than methods that rely on external standards. Additionally, we show that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods. These results subsequently serve as a benchmark for assessing MS data quality for protein quantification, whilst also underscoring current limitations in this approach.

bioinformatics↗

bioRxiv2020

Proteome overabundance enables respiration but limitation onsets carbon overflow

Central carbon metabolism produces energy and precursor metabolites for biomass in heterotrophs. Carbon overflow yields metabolic byproducts and, here, we examined its dependency on nutrient and growth using the unicellular eukaryotic model organism Saccharomyces cerevisiae. We performed quantitative proteomics analysis together with metabolic modeling and found that proteome overabundance enabled respiration, and variation in energy efficiency caused distinct composition of biomass at different carbon to nitrogen ratio and growth rate. Our results showed that ceullar resource allocation for ribosomes was determinative of growth rate, but energy constrains on protein synthesis incepted carbon overflow by prioritizing abundance of ribosomes and glycolysis over mitochondria. We proved that glycolytic efficiency affected energy metabolism by making a trade-off between low and high energy production pathways. Finally, we summarized cellular energy budget underlying nutrient-responsive and growth rate-dependent carbon overflow, and suggested implications of results for bioprocesses and pathways relevant in cancer metabolism in humans.

systems biology↗