Biology subjects

Szappanos, B.

Publications and source records attributed to Szappanos, B..

3 recordsLinked to original sources

bioRxiv2023

Metabolic complexity increases adaptability

Bacteria show a striking ability to adapt to new environments through horizontal gene transfer. Anecdotal evidence suggests that some bacteria are more adaptable than others: e.g., intestinal E. coli frequently spin off pathogenic strains adapted to other human tissues, while gastric Helicobacter pylori do not. However, it is unclear what determines the ability of individual strains or species to adapt to new environments. Here, we use pan-genome scale modeling to explore the ability of 102 different unicellular organisms to adapt to each of 5000+ diverse nutritional environments. While the small metabolic systems of specialized endosymbionts typically require 50+ additional metabolic reactions to adapt to new environments, different strains of the generalist E. coli require on average less than 5 new reactions. Thus, there is a positive feedback between metabolic complexity and adaptability, contrary to speculations that complex systems are generally less adaptable.

evolutionary biology↗

bioRxiv2022

Principles of metabolome conservation in animals

Metabolite concentrations shape cellular physiology and disease susceptibility, yet the general principles governing metabolome evolution are largely unknown. Here we introduce a measure of conservation of individual metabolite concentrations among related species. By analysing multispecies metabolome datasets in mammals and fruit flies, we show that conservation varies extensively across metabolites. Three major functional properties, metabolite abundance, essentiality and association with human diseases predict conservation, highlighting a striking parallel between the evolutionary forces driving metabolome and protein sequence conservation. Metabolic network simulations recapitulated these general patterns, and revealed that abundant metabolites are highly conserved due to their strong coupling to key metabolic fluxes in the network. This study uncovers simple rules governing metabolic evolution in animals and implies that most metabolome differences between species are permitted, rather than favored by selection. More broadly, our work paves the way towards using evolutionary information to discover biomarkers, as well as to detect pathogenic metabolome alterations in individual patients.

systems biology↗

bioRxiv2021

Proteome-wide landscape of solubility limits in a bacterial cell

Proteins are prone to aggregate when they are expressed above their solubility limits, a phenomenon termed supersaturation. Aggregation may occur as proteins emerge from the ribosome or after they fold and accumulate in the cell, but the relative importance of these two routes remain poorly known. Here, we systematically probed the solubility limits of each Escherichia coli protein upon overexpression using an image-based screen coupled with machine learning. The analysis suggests that competition between folding and aggregation from the unfolded state governs the two aggregation routes. Remarkably, the majority (70%) of insoluble proteins have low supersaturation risks in their unfolded states and rather aggregate after folding. Furthermore, a substantial fraction ([~]35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our proteome-wide study provides empirical insights into the molecular determinants of protein aggregation routes in a bacterial cell.

molecular biology↗