Cell cycle-dependent protein dynamics in budding yeast resolved by deconvolution of bulk proteomics

Abstract The cell division cycle is characterised by oscillatory dynamics in regulatory mechanisms and biosynthesis, coordinated with genome replication and segregation. To understand these dynamics, quantitative cell cycle-dependent protein concentration data are essential. Unfortunately, accurately resolving cell cycle-dependent protein dynamics is challenging because single-cell proteomics is currently infeasible and bulk proteomics requires – inherently imperfect – cell synchronisation. Here, we developed a computational method to deconvolve cell cycle-dependent protein concentration dynamics and applied it to new budding yeast bulk proteome data. Key to this method was a yeast population model, parameterised with experimental cell cycle progression and volume growth data, for quantifying the desynchronisation in sampled populations. We performed deconvolution on 3272 proteins, using cross-validation to determine regularisation parameters, and identified 539 proteins with cell cycle-dependent dynamics. Many of these dynamics were consistent with known yeast biology and dynamic proteins were enriched for several metabolic process, extending previous observations and supporting the emerging picture of metabolic activity as varying substantially over cell cycle phases. We consider the generated cell cycle-resolved budding yeast proteome data a key resource.

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Publication Details

Journal
Molecular Systems Biology
Published
2026-09-14
DOI
https://doi.org/10.1038/s44320-026-00241-6
Primary Topic
Bioinformatics and Genomic Networks
Type
article
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Cell cycle-dependent protein dynamics in budding yeast resolved by deconvolution of bulk proteomics

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Cell cycle-dependent protein dynamics in budding yeast resolved by deconvolution of bulk proteomics

Yulan B. van Oppen, Andreas Milias‐Argeitis, Andre Zylstra, Hugo P. Markus, Mattia Rovetta, Kerlen T. Korbeld, Matthias Heinemann, Julius A. Fülleborn, Silke R. Vedelaar, Alexander Schmidt, Katarzyna Buczak, Christian Bleischwitz, Enrico Calzati
article en

Abstract

Abstract The cell division cycle is characterised by oscillatory dynamics in regulatory mechanisms and biosynthesis, coordinated with genome replication and segregation. To understand these dynamics, quantitative cell cycle-dependent protein concentration data are essential. Unfortunately, accurately resolving cell cycle-dependent protein dynamics is challenging because single-cell proteomics is currently infeasible and bulk proteomics requires – inherently imperfect – cell synchronisation. Here, we developed a computational method to deconvolve cell cycle-dependent protein concentration dynamics and applied it to new budding yeast bulk proteome data. Key to this method was a yeast population model, parameterised with experimental cell cycle progression and volume growth data, for quantifying the desynchronisation in sampled populations. We performed deconvolution on 3272 proteins, using cross-validation to determine regularisation parameters, and identified 539 proteins with cell cycle-dependent dynamics. Many of these dynamics were consistent with known yeast biology and dynamic proteins were enriched for several metabolic process, extending previous observations and supporting the emerging picture of metabolic activity as varying substantially over cell cycle phases. We consider the generated cell cycle-resolved budding yeast proteome data a key resource.

Molecular Systems Biology
University of Groningen (NL), University of Basel (CH), University Hospital of Basel (CH)
Openalex Percentile: Top 18%
Bioinformatics and Genomic Networks
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