Subcellular proteomics of the protist Paradiplonema papillatum reveals the digestive capacity of the cell membrane and the plasticity of peroxisomes across euglenozoans
Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection
Typ dokumentu časopisecké články
Grantová podpora
Wellcome Trust - United Kingdom
PubMed
41336180
PubMed Central
PMC12697944
DOI
10.1371/journal.pbio.3003319
PII: PBIOLOGY-D-25-02050
Knihovny.cz E-zdroje
- MeSH
- buněčná membrána * metabolismus MeSH
- Euglenozoa * metabolismus MeSH
- metabolismus sacharidů MeSH
- peroxizomy * metabolismus MeSH
- proteom metabolismus MeSH
- proteomika * metody MeSH
- protozoální proteiny metabolismus MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- proteom MeSH
- protozoální proteiny MeSH
Diplonemids are among the most diverse and abundant protists in the deep ocean, have extremely complex and ancient cellular systems, and exhibit unique metabolic capacities. Despite this, we know very little about this major group of eukaryotes. To establish a model organism for comprehensive investigation, we performed subcellular proteomics on Paradiplonema papillatum and localized 4,870 proteins to 22 cellular compartments. We additionally confirmed the predicted location of several proteins by epitope tagging and fluorescence microscopy. To probe the metabolic capacities of P. papillatum, we explored the proteins predicted to the cell membrane compartment in our subcellular proteomics dataset. Our data revealed an accumulation of many carbohydrate-degrading enzymes (CDZymes). Our predictions suggest that these CDZymes are exposed to the extracellular space, supporting proposals that diplonemids may specialize in breaking down carbohydrates in plant and algal cell walls. Further exploration of carbohydrate metabolism revealed an evolutionary divergence in the function of glycosomes (modified peroxisomes) in diplonemids versus kinetoplastids. Our subcellular proteome provides a resource for future investigations into the unique cell biology of diplonemids.
Faculty of Science University of South Bohemia České Budějovce Czech Republic
Institute of Parasitology Biology Centre Czech Academy of Sciences České Budějovce Czech Republic
Zobrazit více v PubMed
Flegontova O, Flegontov P, Malviya S, Audic S, Wincker P, de Vargas C, et al. Extreme diversity of diplonemid eukaryotes in the ocean. Curr Biol. 2016;26(22):3060–5. doi: 10.1016/j.cub.2016.09.031 PubMed DOI
Gawryluk RMR, Del Campo J, Okamoto N, Strassert JFH, Lukeš J, Richards TA, et al. Morphological identification and single-cell genomics of marine diplonemids. Curr Biol. 2016;26(22):3053–9. doi: 10.1016/j.cub.2016.09.013 PubMed DOI
Mukherjee I, Salcher MM, Andrei A-Ş, Kavagutti VS, Shabarova T, Grujčić V, et al. A freshwater radiation of diplonemids. Environ Microbiol. 2020;22(11):4658–68. doi: 10.1111/1462-2920.15209 PubMed DOI
Obiol A, Giner CR, Sánchez P, Duarte CM, Acinas SG, Massana R. A metagenomic assessment of microbial eukaryotic diversity in the global ocean. Mol Ecol Resour. 2020;20(3):10.1111/1755-0998.13147. doi: 10.1111/1755-0998.13147 PubMed DOI
Lax G, Okamoto N, Keeling PJ. Phylogenomic position of eupelagonemids, abundant, and diverse deep-ocean heterotrophs. ISME J. 2024;18(1):wrae040. doi: 10.1093/ismejo/wrae040 PubMed DOI PMC
Tashyreva D, Simpson AGB, Prokopchuk G, Škodová-Sveráková I, Butenko A, Hammond M, et al. Diplonemids—a review on “New” flagellates on the oceanic block. Protist. 2022;173(2):125868. doi: 10.1016/j.protis.2022.125868 PubMed DOI
Prokopchuk G, Korytář T, Juricová V, Majstorović J, Horák A, Šimek K, et al. Trophic flexibility of marine diplonemids—switching from osmotrophy to bacterivory. ISME J. 2022;16(5):1409–19. doi: 10.1038/s41396-022-01192-0 PubMed DOI PMC
Škodová-Sveráková I, Záhonová K, Juricová V, Danchenko M, Moos M, Baráth P, et al. Highly flexible metabolism of the marine euglenozoan protist PubMed DOI PMC
Valach M, Moreira S, Petitjean C, Benz C, Butenko A, Flegontova O, et al. Recent expansion of metabolic versatility in PubMed DOI PMC
Tashyreva D, Faktorová D, Stříbrná E, Horák A, Lukeš J, Archibald JM, Oatley G, Sinclair E, Aunin E, Gettle N, et al. The genome sequences of the diplonemid protist PubMed DOI PMC
Tashyreva D, Faktorová D, Horák A, Lukeš J, Archibald JM, Oatley G, et al. The genome sequences of the diplonemid protist PubMed DOI PMC
Faktorová D, Kaur B, Valach M, Graf L, Benz C, Burger G, et al. Targeted integration by homologous recombination enables in situ tagging and replacement of genes in the marine microeukaryote PubMed DOI
Akiyoshi B, Faktorová D, Lukeš J. Discovery of unique mitotic mechanisms in PubMed DOI PMC
Valach M, Benz C, Aguilar LC, Gahura O, Faktorová D, Zíková A, et al. Miniature RNAs are embedded in an exceptionally protein-rich mitoribosome via an elaborate assembly pathway. Nucleic Acids Res. 2023;51(12):6443–60. doi: 10.1093/nar/gkad422 PubMed DOI PMC
Valach M, Léveillé-Kunst A, Gray MW, Burger G. Respiratory chain Complex I of unparalleled divergence in diplonemids. J Biol Chem. 2018;293(41):16043–56. doi: 10.1074/jbc.RA118.005326 PubMed DOI PMC
Benz C, Raas MWD, Tripathi P, Faktorová D, Tromer EC, Akiyoshi B, et al. On the possibility of yet a third kinetochore system in the protist phylum Euglenozoa. mBio. 2024;15(12):e0293624. doi: 10.1128/mbio.02936-24 PubMed DOI PMC
Záhonová K, Lukeš J, Dacks JB. Diplonemid protists possess exotic endomembrane machinery, impacting models of membrane trafficking in modern and ancient eukaryotes. Curr Biol. 2025;35(7):1508-1520.e2. doi: 10.1016/j.cub.2025.02.032 PubMed DOI
Richards TA, Eme L, Archibald JM, Leonard G, Coelho SM, de Mendoza A, et al. Reconstructing the last common ancestor of all eukaryotes. PLoS Biol. 2024;22(11):e3002917. doi: 10.1371/journal.pbio.3002917 PubMed DOI PMC
Geladaki A, Kočevar Britovšek N, Breckels LM, Smith TS, Vennard OL, Mulvey CM, et al. Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics. Nat Commun. 2019;10(1):331. doi: 10.1038/s41467-018-08191-w PubMed DOI PMC
Opperdoes FR, Michels PA. The glycosomes of the Kinetoplastida. Biochimie. 1993;75(3–4):231–4. doi: 10.1016/0300-9084(93)90081-3 PubMed DOI
Šubrtová K, Panicucci B, Zíková A. ATPaseTb2, a unique membrane-bound FoF1-ATPase component, is essential in bloodstream and dyskinetoplastic trypanosomes. PLoS Pathog. 2015;11(2):e1004660. doi: 10.1371/journal.ppat.1004660 PubMed DOI PMC
Joseph A-M, Adhihetty PJ, Wawrzyniak NR, Wohlgemuth SE, Picca A, Kujoth GC, et al. Dysregulation of mitochondrial quality control processes contribute to sarcopenia in a mouse model of premature aging. PLoS One. 2013;8(7):e69327. doi: 10.1371/journal.pone.0069327 PubMed DOI PMC
Chou C-W, Yang R-Y, Chan L-C, Li C-F, Sun L, Lee H-H, et al. The stabilization of PD-L1 by the endoplasmic reticulum stress protein GRP78 in triple-negative breast cancer. Am J Cancer Res. 2020;10(8):2621–34. PubMed PMC
Orsburn BC. Proteome discoverer—a community enhanced data processing suite for protein informatics. Proteomes. 2021;9(1):15. doi: 10.3390/proteomes9010015 PubMed DOI PMC
Breckels LM, Holden SB, Wojnar D, Mulvey CM, Christoforou A, Groen A, et al. Learning from heterogeneous data sources: an application in spatial proteomics. PLoS Comput Biol. 2016;12(5):e1004920. doi: 10.1371/journal.pcbi.1004920 PubMed DOI PMC
Almagro Armenteros JJ, Salvatore M, Emanuelsson O, Winther O, von Heijne G, Elofsson A, et al. Detecting sequence signals in targeting peptides using deep learning. Life Sci Alliance. 2019;2(5):e201900429. doi: 10.26508/lsa.201900429 PubMed DOI PMC
Teufel F, Almagro Armenteros JJ, Johansen AR, Gíslason MH, Pihl SI, Tsirigos KD, et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat Biotechnol. 2022;40(7):1023–5. doi: 10.1038/s41587-021-01156-3 PubMed DOI PMC
Hallgren J, Tsirigos K, Pederson M, Armenteros J, Marcatili P, Nielsen H, et al. DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks. bioRxiv. 2022. doi: 10.1101/2022.04.08.487609 DOI
Billington K, Halliday C, Madden R, Dyer P, Barker AR, Moreira-Leite FF, et al. Genome-wide subcellular protein map for the flagellate parasite PubMed DOI PMC
Tashyreva D, Týč J, Horák A, Lukeš J. Ultrastructure and 3D reconstruction of a diplonemid protist (Diplonemea) and its novel membranous organelle. mBio. 2023;14(5):e0192123. doi: 10.1128/mbio.01921-23 PubMed DOI PMC
Porter D.
Newell SY. Fungi and bacteria in or on leaves of Eelgrass ( PubMed DOI PMC
George EE, Tashyreva D, Kwong WK, Okamoto N, Horák A, Husnik F, et al. Gene transfer agents in bacterial endosymbionts of microbial eukaryotes. Genome Biol Evol. 2022;14(7):evac099. doi: 10.1093/gbe/evac099 PubMed DOI PMC
Tashyreva D, Votýpka J, Yabuki A, Horák A, Lukeš J. Description of new diplonemids (Diplonemea, Euglenozoa) and their endosymbionts: charting the morphological diversity of these poorly known heterotrophic flagellates. Protist. 2025;177:126090. doi: 10.1016/j.protis.2025.126090 PubMed DOI
Michels PAM, Bringaud F, Herman M, Hannaert V. Metabolic functions of glycosomes in trypanosomatids. Biochim Biophys Acta. 2006;1763(12):1463–77. doi: 10.1016/j.bbamcr.2006.08.019 PubMed DOI
Makiuchi T, Annoura T, Hashimoto M, Hashimoto T, Aoki T, Nara T. Compartmentalization of a glycolytic enzyme in Diplonema, a non-kinetoplastid euglenozoan. Protist. 2011;162(3):482–9. doi: 10.1016/j.protis.2010.11.003 PubMed DOI
Morales J, Hashimoto M, Williams TA, Hirawake-Mogi H, Makiuchi T, Tsubouchi A, et al. Differential remodelling of peroxisome function underpins the environmental and metabolic adaptability of diplonemids and kinetoplastids. Proc Biol Sci. 2016;283(1830):20160520. doi: 10.1098/rspb.2016.0520 PubMed DOI PMC
Jirsová D, Licknack TJ, Poh Y-P, Qiu Y, Quan N, Chou T-F, et al. Subcellular proteomics of DOI
Freitag J, Stehlik T, Stiebler AC, Bölker M. The obvious and the hidden: prediction and function of fungal peroxisomal matrix proteins. Subcell Biochem. 2018;89:139–55. doi: 10.1007/978-981-13-2233-4_6 PubMed DOI
Río Bártulos C, Rogers MB, Williams TA, Gentekaki E, Brinkmann H, Cerff R, et al. Mitochondrial glycolysis in a major lineage of eukaryotes. Genome Biol Evol. 2018;10(9):2310–25. doi: 10.1093/gbe/evy164 PubMed DOI PMC
Kovářová J, Barrett MP. The pentose phosphate pathway in parasitic trypanosomatids. Trends Parasitol. 2016;32(8):622–34. doi: 10.1016/j.pt.2016.04.010 PubMed DOI
Güther MLS, Urbaniak MD, Tavendale A, Prescott A, Ferguson MAJ. High-confidence glycosome proteome for procyclic form PubMed DOI PMC
Moloney NM, Barylyuk K, Tromer E, Crook OM, Breckels LM, Lilley KS, et al. Mapping diversity in African trypanosomes using high resolution spatial proteomics. Nat Commun. 2023;14(1):4401. doi: 10.1038/s41467-023-40125-z PubMed DOI PMC
Gray MW, Valach M, Sarrasin M, Le Sieur FA, Lukeš J, Burger G. The mitochondrial proteome of diplonemids: from conventional pathway to eccentric RNA editing and transcript processing. BMC Genomics. 2025. PubMed PMC
Hammond MJ, Nenarokova A, Butenko A, Zoltner M, Dobáková EL, Field MC, et al. A uniquely complex mitochondrial proteome from PubMed DOI PMC
Faktorová D, Nisbet RER, Fernández Robledo JA, Casacuberta E, Sudek L, Allen AE, et al. Genetic tool development in marine protists: emerging model organisms for experimental cell biology. Nat Methods. 2020;17(5):481–94. doi: 10.1038/s41592-020-0796-x PubMed DOI PMC
Crook OM, Breckels LM, Lilley KS, Kirk PDW, Gatto L. A Bioconductor workflow for the Bayesian analysis of spatial proteomics. F1000Res. 2019;8:446. doi: 10.12688/f1000research.18636.1 PubMed DOI PMC
Ødum MT, Teufel F, Thumuluri V, Almagro Armenteros JJ, Johansen AR, Winther O, et al. DeepLoc 2.1: multi-label membrane protein type prediction using protein language models. Nucleic Acids Res. 2024;52(W1):W215–20. doi: 10.1093/nar/gkae237 PubMed DOI PMC
Gíslason M, Nielsen H, Armenteros J, Johansen A. Prediction of GPI-anchored proteins with pointer neural networks. Curr Res in Biotech. 2021;3:6–13.
Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG Tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428(4):726–31. doi: 10.1016/j.jmb.2015.11.006 PubMed DOI
Perez-Riverol Y, Bandla C, Kundu DJ, Kamatchinathan S, Bai J, Hewapathirana S, et al. The PRIDE database at 20 years: 2025 update. Nucleic Acids Res. 2025;53(D1):D543–53. doi: 10.1093/nar/gkae1011 PubMed DOI PMC
Faktorová D, Záhonová K, Benz C, Dacks JB, Field MC, Lukeš J. Functional differentiation of Sec13 paralogues in the euglenozoan protists. Open Biol. 2023;13(6):220364. doi: 10.1098/rsob.220364 PubMed DOI PMC
Kaur B, Valach M, Peña-Diaz P, Moreira S, Keeling PJ, Burger G, et al. Transformation of PubMed DOI