The proteomic landscape of genome-wide genetic perturbations

Messner, Christoph B.; Demichev, Vadim; Muenzner, Julia; Aulakh, Simran Kaur; Barthel, Natalie; Röhl, Annika; Herrera-Dominguez, Lucía; Egger, Anna-Sophia; Kamrad, Stephan; Hou, Jing; Tan, Guihong; Lemke, Oliver; Calvani, Enrica; Szyrwiel, Łukasz; Mülleder, Michael; Lilley, Kathryn S.; Boone, Charles; Kustatscher, Georg; Ralser, Markus

doi:10.1016/j.cell.2023.03.026

Cited by 30 publications

(48 citation statements)

References 108 publications

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“…We next conducted a quantitative proteomics experiment to capture molecular responses in the cells grown in the 91 conditions with altered metal concentrations, in triplicates. We employed a high-throughput proteomic pipeline that combines cell cultivation in multi-well plates, semi-automated sample preparation, microflow liquid chromatography, data-independent mass spectrometry data acquisition, and data processing using DIA-NN 24,40,41 . After extensive filtering and quality control of the raw proteomics data (Methods), we obtained precise quantitative data for 2330 unique proteins.…”

Section: Resultsmentioning

confidence: 99%

“…Previous work , including our own studies on the yeast metabolome (Mülleder et al 2016) and proteome (Messner et al 2023) have revealed that clustering of 'omic' profiles can be an efficient strategy for protein functional annotation. To identify groups of proteins that respond in a similar manner along the metal concentration series, we employed an ensemble clustering approach 49 .…”

Section: Metal Responsiveness Clusters Proteins According To Functionmentioning

confidence: 99%

“…Groups of clusters are annotated with names that summarise groups of gene set nodes as determined and visualised using the aPEAR R library. c) Summary of the Gene Ontology Slim a) Data integration: Summary of a new genetic interaction dataset, two metallomic datasets of gene deletions and gene overexpression, respectively 25,111 , and a genome-wide proteomic dataset 24 that integrated with the metallome and proteomic data, to create a comprehensive resource about metalloprotein function. b) Number of Open Reading Frames (ORFs) identified as significantly affected across the five datasets as summarised in a).…”

Section: Figures Figure 1 Metal Ion Homeostasis and Concentration-int...mentioning

confidence: 99%

“…We measured growth responses to the altered metal availability and employed a series of -omics technologies to monitor the biological responses: metallomics to quantify metal buffering and correlations between cellular metal concentrations, proteomics to measure the molecular response of cells, and growth screen of a genome-wide deletion library for identifying genetic interactions using metal depletion media. In parallel, we incorporated a dataset that captures the proteomic response to the deletion of each non-essential metal-related protein 24 , and two metallomic datasets that quantify metal quantities in all strains from the S. cerevisiae knockout deletion and overexpression mutant collections [25][26][27] . Our comprehensive resource of metal biology unveils an extensive impact of metal ion concentrations across cellular biochemical networks and their regulatory landscape.…”

Section: Introductionmentioning

confidence: 99%

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The molecular landscape of cellular metal ion biology

Aulakh,

Lemke,

Szyrwiel

et al. 2024

Preprint

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Metal ions play crucial roles in cells, yet the broader impact of metal availability on biological networks remains underexplored. We generated genome-wide resources, systematically quantifying yeast cell growth, metallomic, proteomic, and genetic responses upon varying each of its essential metal ions (Ca, Cu, Fe, K, Mg, Mn, Mo, Na, Zn), over several orders of magnitude. We find that metal ions deeply impact cellular networks, with 57.6% of the proteome, including most signalling pathways, responding. While the biological response to each metal is distinct, our data reveals common properties of metal responsiveness, such as concentration interdependencies and metal homeostasis. We describe a compendium of metal-dependent cellular processes and reveal that several understudied genes can be functionally annotated based on their metal responses. Furthermore, we report that metalloenzymes occupy central nodes in the metabolic network and are more likely to be encoded by isozymes, resulting in system-wide responsiveness to metal availability.

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Section: Resultsmentioning

confidence: 99%

Section: Metal Responsiveness Clusters Proteins According To Functionmentioning

confidence: 99%

Section: Figures Figure 1 Metal Ion Homeostasis and Concentration-int...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The molecular landscape of cellular metal ion biology

Aulakh,

Lemke,

Szyrwiel

et al. 2024

Preprint

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“…Proteins were extracted from exponentially growing cells and subjected to reduction, alkylation, and tryptic digestions, as described previously [43]. Proteomic data was acquired using micro ow chromatography and SWATH-MS on a 7600 instrument (Sciex) [44].…”

Section: Proteomicsmentioning

confidence: 99%

Uridylation regulates mRNA decay directionality in fission yeast.

Malecki,

Grochowski,

Lipińska-Zubrycka

et al. 2023

Preprint

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Cytoplasmic mRNA decay is effected by exonucleolytic degradation in in either the 5' to 3' or 3' to 5' direction. Pervasive terminal uridylation is implicated in mRNA degradation, however, despite its conservation throughout eucaryotes, its functional relevance for bulk mRNA turnover remains poorly understood. In this study, we employed genome-wide 3'-RACE technique to elucidate the role of uridylation in governing mRNA decay directionality. The observed widespread uridylation of shortened poly(A) tails promotes efficient 5' to 3' mRNA decay, ensuring timely and controlled mRNA degradation. Conversely, the inhibition of this uridylation process disrupts the delicate balance, leading to excessive deadenylation and enhanced 3' to 5' mRNA decay accompanied by oligouridylation of de-adenylated mRNAs. Strikingly we found that in fission yeast uridylation of poly(A) tails and oligouridylation of non-polyadenylated substrates are catalysed by different terminal uridyltransferases. Our study sheds new light on the intricate regulatory mechanisms underlying bulk mRNA turnover, emphasizing the role of uridylation in modulating mRNA decay pathways.

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Cellular control of protein levels: A systems biology perspective

Munro,

Kelly,

Messner

et al. 2023

Proteomics

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How cells regulate protein levels is a central question of biology. Over the past decades, molecular biology research has provided profound insights into the mechanisms and the molecular machinery governing each step of the gene expression process, from transcription to protein degradation. Recent advances in transcriptomics and proteomics have complemented our understanding of these fundamental cellular processes with a quantitative, systems‐level perspective. Multi‐omic studies revealed significant quantitative, kinetic and functional differences between the genome, transcriptome and proteome. While protein levels often correlate with mRNA levels, quantitative investigations have demonstrated a substantial impact of translation and protein degradation on protein expression control. In addition, protein‐level regulation appears to play a crucial role in buffering protein abundances against undesirable mRNA expression variation. These findings have practical implications for many fields, including gene function prediction and precision medicine.

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The proteomic landscape of genome-wide genetic perturbations

Cited by 30 publications

References 108 publications

The molecular landscape of cellular metal ion biology

The molecular landscape of cellular metal ion biology

Uridylation regulates mRNA decay directionality in fission yeast.

Cellular control of protein levels: A systems biology perspective

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