Ryazanova, L. | Search bioRxiv

bioRxiv2021

Glycogen-dependent demixing of frog egg cytoplasm at increased crowding

Crowding increases the tendency of macromolecules to aggregate and phase separate, and high crowding can induce glass-like states of cytoplasm. To explore the effect of crowding in a well-characterized model cytoplasm we developed methods to selectively concentrate components larger than 25 kDa from Xenopus egg extracts. When crowding was increased 1.4x, the egg cytoplasm demixed into two liquid phases of approximately equal volume. One of the phases was highly enriched in glycogen while the other had a higher protein concentration. Glycogen hydrolysis blocked or reversed demixing. Quantitative proteomics showed that the glycogen phase was enriched in proteins that bind glycogen, participate in carbohydrate metabolism, or are in complexes with especially high native molecular weight. The glycogen phase was depleted of ribosomes, ER and mitochondria. These results inform on the physical nature of a glycogen-rich cytoplasm and suggest a role of demixing in the localization of glycogen particles in tissue cells.

cell biology↗

bioRxiv2017

Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-Statistics with Peptide Quantification Concordance

Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signal generated by isobaric tags, which encode the samples origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the proteins peptides and the signal level of these measurements. However, typically only the most likely results are reported without providing confidence for these measurements. Here we present a mathematically rigorous approach that integrates peptide MS-signal and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ). The main advantages of BACIQ are: 1) it removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment; 2) confidence can be assigned without replicates; 3) for repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; 4) for repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement. To demonstrate the power of BACIQ we reanalyzed previously published data on subcellular protein movement upon treatment with an Exportin 1 inhibiting drug. We detect ~2x more highly significant movers, down to subcellular localization changes of ~1%. Thus, our method drastically increases the value obtainable from quantitative proteomics experiments helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.

systems biology↗