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. 2024 Nov 6;14(11):jkae209.
doi: 10.1093/g3journal/jkae209.

Linear poly-ubiquitin remodels the proteome and influences hundreds of regulators in Drosophila

Affiliations

Linear poly-ubiquitin remodels the proteome and influences hundreds of regulators in Drosophila

Oluwademilade Nuga et al. G3 (Bethesda). .

Abstract

Ubiquitin controls many cellular processes via its posttranslational conjugation onto substrates. Its use is highly variable due to its ability to form poly-ubiquitin chains with various topologies. Among them, linear chains have emerged as important regulators of immune responses and protein degradation. Previous studies in Drosophila melanogaster found that expression of linear poly-ubiquitin that cannot be dismantled into single moieties leads to their ubiquitination and degradation or, alternatively, to their conjugation onto proteins. However, it remains largely unknown which proteins are sensitive to linear poly-ubiquitin. To address this question, here we expanded the toolkit to modulate linear chains and conducted ultra-deep coverage proteomics from flies that express noncleavable, linear chains comprising 2, 4, or 6 moieties. We found that these chains regulate shared and distinct cellular processes in Drosophila by impacting hundreds of proteins, such as the circadian factor Cryptochrome. Our results provide key insight into the proteome subsets and cellular pathways that are influenced by linear poly-ubiquitin chains with distinct lengths and suggest that the ubiquitin system is exceedingly pliable.

Keywords: autophagy; catabolism; genetics; immune system; proteasome; proteomics.

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Conflict of interest statement

Conflicts of interest The author(s) declare no conflicts of interest.

Figures

Fig. 1.
Fig. 1.
a) Graphical summary of the UB conjugation and deconjugation system. b) Tabulation of the different linear UB chains that were over-expressed in flies and their properties. Legend and graphics on the right portion of this panel indicate types of conjugation that may occur with these transgenic linear UB species. c) Nucleotide and amino acid sequence of the UB2_GG construct. The other lines generated for this project were designed similarly. The underlined portions show the terminal “GG” motif and the nucleotide sequence encoding it. The HA epitope tag is shown in magenta, and methionine residues corresponding to the first methionine of the construct and the first methionine residues of UB are in green. d) Western blots from the expression of the linear UB chains used in the study. The lysates were from male flies of the same crosses used for proteomics. Immunoprecipitation procedures are explained in the Materials and Methods section. “Ctrl” line was the sqh-Gal4 driver in trans with the host line used to generate the UBX transgenics. As noted in the main text, while UB2 and UB6 are not able to be conjugated onto other proteins, owing to the lack of their own terminal “GG” motifs, they can have endogenous UB conjugated onto them, leading to the signal above UB2 and UB6 in this panel. e) Isolation of unanchored UB using recombinant GST-tagged ZnF domain from USP5, processed as outlined in the Materials and Methods section. In Western blots from flies, the vast majority of unanchored UB was mono-UB. Cutting the membrane to remove this species (dotted box) and exposing it longer revealed other unanchored UB species. For blots from the mouse brain, mono-UB was cut off from the membrane to reveal the other chains. Mouse brain sample was leftover lysate from mice used in our prior publication (Todi et al. 2009). The input and IP lanes from the mouse brain lysate blots are from the same membrane and exposure, cropped and rearranged to ease visualization. f) Western blots from male flies expressing the noted UB chain. g) Immunoprecipitation and Western blots from flies expressing UB2_GG everywhere. h) Summary of the groups used for proteomics. In Western blots throughout this figure asterisks denote nonspecific bands. For full blots, please see Supplementary Fig. 1.
Fig. 2.
Fig. 2.
Principal component analysis (a), venn diagrams (b-d), and protein overlap with odds-ratio analyses (e) of the differentially abundant proteins relative to the control group observed between and among the different UBX groups, collectively indicating shared and distinct proteins among the groups.
Fig. 3.
Fig. 3.
Gene ontology pathway enrichment analyses of differentially abundant proteins (DAPs) showing over-represented molecular functions (a), biological processes (b), and KEGG pathways (c) changed by the expression of specific linear UB species in flies. Key differences arise among the different groups expressing specific types of linear poly-UB, especially when comparing chains with a “GG” vs. not.
Fig. 4.
Fig. 4.
a) Heatmap of hierarchically clustered, TMT-quantified protein expression changes in curated UB-mediated catabolic processes in the presence of specific linear UB species with log2FC expression changes relative to the control group. b) Heatmap of proteins changes in the autophagy pathway in the presence of specific linear UB species. The levels of various proteasome-, UB-related enzymes and proteins, and autophagy-related components are impacted across the different genotypes.
Fig. 5.
Fig. 5.
a) Heatmap of hierarchically clustered, TMT-quantified protein expression changes in curated immune pathway in the presence of specific linear UB chains. Similarities and differences among the groups fall roughly into 4 areas, highlighted as “quartiles”. b) Heatmap of hierarchically clustered, TMT-quantified protein expression changes in curated neurodegeneration pathway in the presence of specific linear UB species. Similarities and differences are evident when comparing linear UB without or with a terminal “GG”.
Fig. 6.
Fig. 6.
Boxplot of log2 differentially abundant protein expression changes (a; mean ± SEM) and their known orthologues and functions (b) whose levels were consistently lower in the presence of UBX_GG. Gene name symbol, reported function, and potential human orthologues were sourced from flybase.org (Gramates et al. 2022). When suitable, based on “Best Score” outputs, multiple potential orthologues are shown. For panel (a), the individual data points shown represent biological replicates from N = 3.

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