The social and structural architecture of the yeast protein interactome
Open accessPublished version of a preprint
Abstract
Cellular functions are mediated by protein–protein interactions, and mapping the interactome provides fundamental insights into biological systems. Affinity purification coupled to mass spectrometry is an ideal tool for such mapping, but it has been difficult to identify low copy number complexes, membrane complexes and complexes that are disrupted by protein tagging. As a result, our current knowledge of the interactome is far from complete, and assessing the reliability of reported interactions is challenging. Here we develop a sensitive high-throughput method using highly reproducible affinity enrichment coupled to mass spectrometry combined with a quantitative two-dimensional analysis strategy to comprehensively map the interactome of Saccharomyces cerevisiae . Thousand-fold reduced volumes in 96-well format enabled replicate analysis of the endogenous GFP-tagged library covering the entire expressed yeast proteome 1 . The 4,159 pull-downs generated a highly structured network of 3,927 proteins connected by 31,004 interactions, doubling the number of proteins and tripling the number of reliable interactions compared with existing interactome maps 2 . This includes very-low-abundance epigenetic complexes, organellar membrane complexes and non-taggable complexes inferred by abundance correlation. This nearly saturated interactome reveals that the vast majority of yeast proteins are highly connected, with an average of 16 interactors. Similar to social networks between humans, the average shortest distance between proteins is 4.2 interactions. AlphaFold-Multimer provided novel insights into the functional roles of previously uncharacterized proteins in complexes. Our web portal ( www.yeast-interactome.org ) enables extensive exploration of the interactome dataset.
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“This compares with a 69% repeatability of assigned interactions in the previous large-scale screens 11 .”
ResultFrom E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions
Ulitsky, I., Shlomi, T., Kupiec, M., & Shamir, R. (2008) · Molecular Systems Biology · doi:10.1038/msb.2008.42 · Cited by 80 · cited 1× · see citing works
“A total of 11 evidences connect the uncharacterized protein YDL176Wp with the conserved glucose-induced degradation (GID) complex, only a few of which had been indicated by previous pull-down or genetic interaction data 5,30 (Fig.”
BackgroundPappenberger, G., Mccormack, E. A., & Willison, K. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2006.05.003 · Cited by 75 · cited 1× · see citing works
“For some proteins—for example, the members of the chaperonin containing t-complex (CCT)—tagging is not possible because it interferes with protein stability or function 20 .”
BackgroundKorber, P., & Barbarić, S. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku784 · Cited by 61 · cited 1× · see citing works
“This raises the possibility of a novel cytoplasmatic sensing and retention mechanism of this key transcriptional regulator, which is known to be necessary for a phosphate starvation response 38,39 .”
BackgroundPhan, V. T., Ding, V. W., Li, F., Chalkley, R. J., Burlingame, A. L., & McCormick, F. P. (2010) · Molecular and Cellular Biology · doi:10.1128/mcb.01450-08 · Cited by 56 · cited 1× · see citing works
“…we expand the known interaction of the GTPase-activating proteins Ira1 and Ira2 (neurofibromin (NF1) in humans), and Gpb1 and Gpb2 (ETEA in humans) 41 by Trx2 a thioredoxin isoenzyme (human homologue, TXN) and Gpx1 (human homologues, GPX3–6), an antioxidant enzyme whose glutathione peroxidase…”
BackgroundUses and misuses of the fudge factor in quantitative discovery proteomics
Gianetto, Q. G., Couté, Y., Bruley, C., & Burger, T. (2016) · Proteomics · doi:10.1002/pmic.201600132 · Cited by 21 · see citing works
le Mercier, P., Bolleman, J. T., de Castro, E., Gasteiger, E., Bansal, P., Auchincloss, A., Boutet, E., Breuza, L., Casals-Casas, C., Estreicher, A., et al. (2022) · Database J. Biol. Databases Curation · doi:10.1093/database/baac026 · Cited by 19 · cited 1× · see citing works
“4, the Cytoscape session and the web application is an adopted version from SwissBioPics by the Swiss-Prot group of the SIB Swiss Institute of Bioinformatics 65 .”
MethodProtein Kinase CK2 Cellular Function in Normal and Disease States
Ahmed, K., Issinger, O., & Szyszka, R. (2015) · Advances in Biochemistry in Health and Disease · doi:10.1007/978-3-319-14544-0 · Cited by 15
Discovery–Versus Hypothesis–Driven Detection of Protein–Protein Interactions and Complexes
Bludau, I. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094450 · Cited by 14 · cited 1× · see citing works
“The comprehensive yeast interactome data can be further used as prior knowledge for hypothesis-driven analysis of protein complexes—for example, for native protein complex co-fractionation coupled to mass spectrometry 55 .”
MethodSelf-citationQiao, S., Lee, C., Sherpa, D., Chrustowicz, J., Cheng, J., Duennebacke, M., Steigenberger, B. A., Karayel, Ö., Vu, D. T., von Gronau, S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30803-9 · Cited by 13 · cited 1× · see citing works
“These types of high-confidence associations assist in prioritizing interactions and form the basis for a detailed mechanism and structure discovery of a novel GID modulator 31 .”
BackgroundSelf-citation
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Mass-spectrometry-based proteomics: from single cells to clinical applications
Guo, T., Steen, J. A. J., & Mann, M. (2025) · Nature · doi:10.1038/s41586-025-08584-0 · Cited by 351 · see citing works
“A prime example is the recent elucidation of an essentially complete yeast interactome, providing an unprecedented view of the protein interaction landscape in a eukaryotic organism 63 .”
Self-citationIntegrated biotechnological and AI innovations for crop improvement
Li, G., An, L., Yang, W., Yang, L., Wei, T., Shi, J., Wang, J., Doonan, J. H., Xie, K., Fernie, A. R., et al. (2025) · Nature · doi:10.1038/s41586-025-09122-8 · Cited by 145 · see citing works
Skowronek, P., Wallmann, G., Wahle, M., Willems, S., & Mann, M. (2025) · Nature Protocols · doi:10.1038/s41596-024-01104-w · Cited by 35 · see citing works
Self-citationRecent Advances in Mass Spectrometry-Based Protein Interactome Studies
Wu, S.-W., Zhang, S., Liu, C., Fernie, A., & Yan, S.-J. (2024) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2024.100887 · Cited by 37 · see citing works
In situ analysis reveals the TRiC duty cycle and PDCD5 as an open-state cofactor
Xing, H., Rosenkranz, R. R. E., Rodriguez-Aliaga, P., Lee, T.-T., Majtner, T., Böhm, S., Turoňová, B., Frydman, J., & Beck, M. (2024) · Nature · doi:10.1038/s41586-024-08321-z · Cited by 29 · see citing works
“Notably, the yeast homologue of PDCD5, SDD2, also interacts with yeast TRiC in co-immunoprecipitation (co-IP) experiments 27 .”
µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics
Oliinyk, D., Will, A., Schneidmadel, F. R., Böhme, M., Rinke, J., Hochhaus, A., Ernst, T., Hahn, N., Geis, C., Lubeck, M., et al. (2024) · Molecular Systems Biology · doi:10.1038/s44320-024-00050-9 · Cited by 37 · see citing works
“…time as needed and complementing the protocol with ultra-sonication or mechanical cell lysis in plate format, e.g. similar to (Müller et al, 2020; Michaelis et al, 2023), should be straightforward, as we found that the low working volumes are compatible with different lysis buffers and 96-well…”
Self-citationla Herrán, H. C. D.-D., Reane, D. V., Cheng, Y., Katona, M., Hosp, F., Greotti, E., Wettmarshausen, J., Patrón, M., Mohr, H., de Mello, N. P., et al. (2024) · The EMBO Journal · doi:10.1038/s44318-024-00219-w · Cited by 25 · see citing works
“In protein – protein interaction studies, true positive interacting proteins often exhibit a good correlation of their intensity pro fi les across different samples, as demonstrated in our previous studies (Hein et al, 2015; Michaelis et al, 2023).”
Self-citationXia, S., Li, D.-K., Deng, X.-M., Liu, Z., Zhu, H., Liu, Y., & Li, D. (2024) · Briefings Bioinform. · doi:10.1093/bib/bbae274 · Cited by 21 · see citing works
“Remark-ably, five of our predicted complexes, have recently been experimentally validated and reported in independent studies [28–32], with three of them exhibiting high-confidence structures using AlphaFold-Multimer (AFM).”
MethodResultInfluentialMultimeric protein interaction and complex prediction: Structure, dynamics and function
Lu, D., Yu, S., Huang, Y., & Gong, X. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.05.009 · Cited by 20 · see citing works
“Researchers have successfully mapped the PPI network of Saccharomyces cerevisiae by combining affinity enrichment with mass spectrometry analysis [235].”
Jiao, F., Yu, C., Wheat, A. J., Chen, L., Lih, T. M., Zhang, H., & Huang, L. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00832 · Cited by 17 · see citing works
Serrano, L. R., Pelin, A., Arrey, T. N., Damoc, N. E., Richards, A., Zhou, Y. M., Lancaster, N. M., Peters-Clarke, T. M., Pashkova, A., Jang, G. Μ., et al. (2025) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c01040 · Cited by 14 · see citing works
Skribbe, M., Soneson, C., Stadler, M. B., Schwaiger, M., Sreechakram, V. N. S., Iešmantavičius, V., Heß, D., Moreno, E. P. F., Braun, S. J., Seebacher, J., et al. (2025) · Molecular Cell · doi:10.1016/j.molcel.2025.01.032 · Cited by 15 · see citing works
Spatiotemporal constrained RNA–protein heterogeneous network for protein complex identification
Li, Z., Wang, S.-L., Cui, H., Liu, X., & Zhang, Y.-J. (2024) · Briefings Bioinform. · doi:10.1093/bib/bbae280 · Cited by 9
“There have been in total 11 indications of the association of this redundant node with the GID complex [45], some of which are confirmed by pull-down or genetic interaction experiments, and these pieces of evidence indicate that YDL176W is strongly linked to the GID complex.”
BackgroundTowards the construction of a virtual yeast
Qian, L., Zhou, Z., Zhou, P., Dong, Z., Zhang, X., Dai, Z., Gao, Z., Sun, S., Roy, K. R., Wang, S., et al. (2026) · Nature · doi:10.1038/s41586-026-10574-9 · Cited by 10 · see citing works
“…by curated multiscale databases such as genomics (SGD and ScRAPdb) 30,134 , metabolomics (YMDB) 31 , proteomics and interactomics (Yeast interactome 38 , 5k Yeast Proteome 44 and Yeast PeptideAtlas 135 ), knowledge-based functional network (YEASTNET) 32 and imaging (LoQAtE and CYCLoPs) 33,34 .”
Cheng, Z., Wu, W., Zhou, X., Xu, T., Zhang, G.-B., & Chen, H.-W. (2025) · ACS Synthetic Biology · doi:10.1021/acssynbio.5c00025 · Cited by 8 · see citing works
Lazarewicz, N., Dez, G. L., Cerjani, R., Runeshaw, L., Meurer, M., Knop, M., Wysocki, R., & Rabut, G. E. E. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100880 · Cited by 5 · see citing works
“Importantly, the sensitivity obtained for high-confidence interactors was as good as or better than that in previous interactome studies 5,6,24–26 (Figure 2D; Table S2).”
InfluentialSingh, D., Liu, Y., Zhu, Y.-H., Zhang, S., Naegele, S. M., & Wu, J.-Q. (2025) · eLife · doi:10.7554/elife.101113 · Cited by 8 · see citing works
“However, no physical interactions between septins and the exocyst have been reported, even in the genome-wide interactome studies ( Michaelis et al., 2023 ).”
Biochemical Insights Into the Conserved Interactions of NMD Factors From Budding Yeast to Humans
Ruiz-Gutierrez, N., Graille, M., Hir, H. L., & Saveanu, C. (2026) · Journal of Molecular Biology · doi:10.1016/j.jmb.2026.169751 · Cited by 5 · see citing works
SND3 is the membrane insertase within a distinct SEC61 translocon complex
Yang, T., Mukherjee, S., Langer, J. D., Hummer, G., & McDowell, M. A. (2025) · Nature Communications · doi:10.1038/s41467-025-65357-z · Cited by 9 · see citing works
“Similarly, in a recent analysis of the yeast interactome, SND3 was predominantly found to cluster with multipass IMPs 35 (Supplementary Fig.”
Multiple interactions recruit BLTP2 to ER-PM contacts to control plasma membrane dynamics
Dai, A.-B., Xu, P., Amos, C., Fujise, K., Wu, Y.-M., Yang, H., Eisen, J. N., Guillén-Samander, A., & Camilli, P. D. (2025) · Journal of Cell Biology · doi:10.1083/jcb.202504027 · Cited by 6 · see citing works
“A recently posted database of the yeast interactome (Michaelis et al., 2023) (http://yeast-interactome.biochem.mpg.de:3838/ interactome/) revealed that the two yeast orthologs of BLTP2, Fmp27 and Ypr117w, are interactors of Ybl086c, with Fmp27 being the strongest interactor (Fig.”
Inferring protein from transcript abundances using convolutional neural networks
Schwehn, P., & Falter-Braun, P. (2025) · BioData Mining · doi:10.1186/s13040-025-00434-z · Cited by 6 · see citing works
Evaluating sequence and structural similarity metrics for predicting shared paralog functions
Dennler, O., & Ryan, C. J. (2025) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaf051 · Cited by 6 · see citing works
“Paralog pairs for which all AlphaFold and PLM features could not be computed were subsequently filtered out, resulting in a final total of 107 103 paralog pairs for humans and 5673 for yeast.”
Membrane contact sites regulate vacuolar fission via sphingolipid metabolism
Hanaoka, K., Nishikawa, K., Ikeda, A., Schlarmann, P., Sasaki, S., Fujii, S., Yamashita, S., Nakaji, A., & Funato, K. (2024) · eLife · doi:10.7554/elife.89938 · Cited by 6 · see citing works
Dbi1 is an oxidoreductase and an assembly chaperone for mitochondrial inner membrane proteins
Badrie, S., Hell, K., & Mokranjac, D. (2025) · EMBO Reports · doi:10.1038/s44319-024-00349-6 · Cited by 5 · see citing works
“The vast majority of cellular proteins need to be translocated across at least one cellular membrane and subsequently assembled into multimeric protein complexes before they can ful fi ll their biological functions (Alberts, 1998; Michaelis et al, 2023; Wickner and Schekman, 2005).”
Fiala, J., Schuster, D., Ollivier, S., Pengelley, S., Lubeck, M., Busch, F., Jankevics, A., Raether, O., Greisch, J.-F., & Heck, A. J. (2024) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.4c00076 · Cited by 5 · see citing works
Protein-protein interactions are a major source of epistasis in genetic interaction networks
Castellanos-Girouard, X., Serohijos, A. W. R., & Michnick, S. W. (2026) · Nature Communications · doi:10.1038/s41467-026-69152-2 · Cited by 4 · see citing works
Bykov, Y., Zuttion, S., Edilbi, D., Polozova, M., Arnold, J., Malitsky, S., Itkin, M., Senger, B., Klein, O., Asraf, Y., et al. (2025) · bioRxiv · doi:10.7554/elife.98889 · Cited by 4
“Of all eukaryotic organisms, Saccharomyces cerevisiae , or budding yeast, comes closest to having such an understanding thanks to its simple organization and compact genome allowing for versatile manipulations ( Michaelis et al., 2023 ).”
Mapping the architecture of protein complexes in Arabidopsis using cross-linking mass spectrometry
Trinh, C. S., Shrestha, R., Mao, P.-Z., Conner, W. C., Reyes, A. V., Karunadasa, S. S., Yu, A.-N., Liu, G., Hu, K., & Xu, S.-L. (2025) · bioRxiv · doi:10.1073/pnas.2519615123 · Cited by 4 · see citing works
“Unlike afnity purifcation MS (AP - MS) and proximity labeling MS (PL - MS) (3–5), XL - MS does not require antibodies or genetically tagged transgenes.”
Williams, S. A., Riley, D. M., Rockwood, T. P., Crosby, D. A., Call, K. D., LeCuyer, J. J., & Santangelo, T. (2025) · Applied and Environmental Microbiology · doi:10.1128/aem.00293-25 · Cited by 4 · see citing works
Preserve or destroy: Orphan protein proteostasis and the heat shock response
Ali, A., Paracha, S., & Pincus, D. (2024) · Journal of Cell Biology · doi:10.1083/jcb.202407123 · Cited by 4 · see citing works
Saccharomyces cerevisiae as a model for mammalian diseases
Sattlegger, E., & Schiemann, A. H. (2026) · FEMS Yeast Research · doi:10.1093/femsyr/foag013 · Cited by 3 · see citing works
“One unbiased approach is for example large scale screens of yeast libraries, to uncover genetic or physical interactions with the protein of interest (Uetz and Grigoriev 2005 , Michaelis et al. 2023 ).”
A global protein interaction network of Leishmania donovani.
Azimi, A., & Salavati, R. (2025) · International Journal of Parasitology · doi:10.1016/j.ijpara.2025.10.001 · Cited by 3 · see citing works
Robles, N. V., Moran, B. M., Rodríguez-Barrera, M. J., Jofre, G. I., Gunn, T. R., Iverson, E. N. K., Beskid, S., Baczenas, J., Sedghifar, A., Andolfatto, P., et al. (2025) · bioRxiv · doi:10.1101/2025.01.30.635158 · Cited by 3
(2026) · doi:10.1093/nar/gkaf1390 · Cited by 3 · see citing works
“In line with a prior high-throughput analysis involving Pim1–GFP [ 16 ], immunoprecipitation of Pim1–Spot from mitochondrial lysates with anti-Spot-tag nanobody followed by immunoblots revealed the co-purification of Mrx6 and Mam33, irrespective of bead type or protease inhibitor used (Fig.”
Complete end-to-end learning from protein feature representation to protein interactome inference
Chen, Y.-H., Liu, C., Leu, J.-Y., & Tsai, H.-K. (2025) · GigaScience · doi:10.1093/gigascience/giaf122 · Cited by 3 · see citing works
“Similarly, in the Y4 dataset, FREEPII predicted a cluster including FAF1, IBD2, LOC1, MRM1, and RCM1, among which the interaction between LOC1 and RCM1 was recently validated by an independent study [ 29 ].”
Defelipe, L., Veith, K., Burastero, O., Kupriianova, T., Bento, I., Skruzny, M., Kölbel, K., Uetrecht, C., Thuenauer, R., & García-Alai, M. (2024) · bioRxiv · doi:10.1038/s41467-024-54037-z · Cited by 3 · see citing works
“Interestingly, the majority of proteins containing the proposed CBM were not identi fi ed as clathrin binders in the comprehensive proteome interactome study conducted by Michaelis et al. in 2023 48 .”
I’m Walking into Spiderwebs: Making Sense of Protein–Protein Interaction Data
Skawinski, C. L. S., & Shah, P. S. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00892 · Cited by 3 · see citing works
Urquiza, J., Cuesta-Geijo, M. A., García-Dorival, I., Fernández, O., del Puerto, A., Díaz, J. F., & Alonso, C. (2024) · Viruses · doi:10.3390/v16030349 · Cited by 3 · see citing works
“These analyses have become increasingly important for understanding protein interactions and competitive binding models that provide highly accurate results [50,51].”
BackgroundRolfes, R. J. (2026) · FEBS Letters · doi:10.1002/1873-3468.70394 · Cited by 2
Avl9 defines a family of GTPase-activating proteins that regulate diverse cell biological functions
Vignogna, R. C., & Fromme, J. (2026) · bioRxiv · doi:10.64898/2026.01.05.697756 · Cited by 2
Nwaora, H., Yu, Y., & Zhuang, Z. (2025) · PROTEOMICS · doi:10.1002/pmic.70089
Global Protein Interaction Network for Trypanosoma cruzi.
Azimi, A., Gaudreault, F., Sulea, T., & Salavati, R. (2025) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5c00649 · Cited by 2 · see citing works
A comprehensive overview of yeast libraries and their role in advancing cell biology
Baruch, D., Schuldiner, M., & Klein, O. (2025) · The FEBS Journal · doi:10.1111/febs.70325 · Cited by 2 · see citing works
“For example, the original C 0 -GFP library, initially developed for fluorescence-based localization, was recently used to map the yeast protein interactome using high-throughput affinity enrichment MS [101].”
SND3 is the membrane insertase within a fungal multipass transloconPreprint
Yang, T.-J., Mukherjee, S., Langer, J. D., Hummer, G., & McDowell, M. A. (2025) · bioRxiv · doi:10.1101/2025.07.08.663624 · Cited by 2 · see citing works
What Have Data Standards Ever Done for Us?
Orchard, S. (2025) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2025.100933 · Cited by 2 · see citing works
Geist, J. L., Lee, C. Y., Strom, J. M., Naveja, J. J., & Luck, K. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae482 · Cited by 4 · see citing works
“While the systematic mapping of protein interactomes is well advanced for many model organisms, including human, experimental methods lack in throughput to provide a structural resolution of protein interactomes (Aloy et al. 2004, Luck et al. 2020, Huttlin et al. 2021, Michaelis et al. 2023).”
BackgroundChen, Q., & Fan, X. (2024) · Chinese Journal of Natural Medicines · doi:10.1016/s1875-5364(24)60635-7 · Cited by 2 · see citing works
ANYI: The ANnotated Yeast Interactome
Nissley, D., Goel, M., Castellanos-Girouard, X., Kuntz, C. P., Wang, Y.-Q., Mukhtar, M., Serohijos, A., & Schlebach, J. (2026) · bioRxiv · doi:10.64898/2026.04.30.721908 · Cited by 1
“Starting from the Mann Lab’s PPI network (Figure 1A), we computed network centrality features ( e.g. , degree and betweenness centrality) and incorporated primary sequence information from the SGD and sequence-derived predictions (Hallgren et al. 2022, Teufel et al. 2022) alongside curated UniProt annotations (Bateman…”
InfluentialDreute, J., & Schmitz, M. (2026) · Plasmid · doi:10.1016/j.plasmid.2026.102772 · Cited by 1 · see citing works
Zhang, C., Feng, Y., Calderin, J. D., Failla, V., Balutowski, A., Ahmed, R., Knapp, C. T., Shah, V., Grudzień, D., Karat, J. M., et al. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1805164 · Cited by 1 · see citing works
“Proteomic studies have shown that Vcx1 physically interacts with the V O subunits Vma6 and Vph1, as well as the V 1 subunits Vma1, Vma2, Vma4, Vma10 and Vma13 (Khan et al., 2022; Michaelis et al., 2023).”
AI for plant protein–protein interactions prediction
Deng, R., Zhang, C., Fernie, A. R., & Zhang, Y. (2026) · The Plant Journal · doi:10.1111/tpj.70867 · Cited by 2 · see citing works
RISK: a next-generation tool for biological network annotation and visualization
Horecka, I., & Röst, H. (2025) · Bioinform. · doi:10.1093/bioinformatics/btaf669 · Cited by 1 · see citing works
“To evaluate RISK’s performance, we compared it with SAFE on Saccharomyces cerevisiae protein–protein interaction (PPI; Michaelis et al. 2023) and genetic interaction (GI; Costanzo et al. 2016) networks.”
Street, L., Majumdar, M., Rothamel, K., Gogus, E., Brar, G., Yeo, G. W., Rube, T., & Jovanovic, M. (2025) · bioRxiv · doi:10.1101/2025.11.21.689547 · Cited by 1
Yang, S., Christensen, A. H., Coradini, A. L. V., Hull, C. B., Lusk, D. T., & Ehrenreich, I. M. (2026) · Genetics · doi:10.1101/2025.09.29.679105
“Future work should examine how a protein's number of interaction partners affects its likelihood of being involved in incompatibilities, given the significant variability in the extent to which proteins interact 48 .”
A diverse interactome of the molecular chaperone CCT/TRiC monomers
Córdoba-Beldad, C. M., & Grantham, J. (2025) · European Journal of Cell Biology · doi:10.1016/j.ejcb.2025.151506 · Cited by 1 · see citing works
Šupljika, N., Paić, A., Novačić, A., Martinić-Cezar, T., Vallée, B., Teparić, R., Stuparević, I., & Žunar, B. (2025) · The FEBS Journal · doi:10.1111/febs.70091 · Cited by 1
“However, neither we nor others find evidence for S. cerevisiae Mub1 – Rrp6 interaction [32 – 34].”
Zhang, C., Feng, Y., Calderin, J. D., Balutowski, A., Ahmed, R., Knapp, C. T., Shah, V., Grudzień, D., Williamson, E. F., Karat, J. M., et al. (2024) · bioRxiv · doi:10.1101/2024.09.27.615487 · Cited by 1 · see citing works
“Proteomic studies have shown that Vcx1 physically interacts with the V O subunits Vma6 and Vph1, as well as the V 1 subunits Vma1, Vma2, Vma4, Vma10 and Vma13 (Khan et al., 2022; Michaelis et al., 2023).”
Topological communities in complex networks
Seoane, L. F. (2024) · doi:10.48550/arxiv.2409.02317 · Cited by 1
“• Yeast protein-protein interaction network, G Y : We used the most recently published data on protein-protein interaction in yeast Saccharomyces cerevisiae [50].”
BackgroundMethodInfluentialMcNeil, B. A., Khalifa, C., Krishnan, A., & Stuart, D. (2020) · PLoS ONE · doi:10.1371/journal.pone.0333299 · Cited by 1
“Physical interactions have been demonstrated between Pyc1 - Pyc2, Pyc1 - Mdh1 and Pyc2 - Mdh1 as well as between Mdh1 - Mdh2 and Mdh1 - Mdh3 [58,59].”
Understanding Aging Genes and Pathways: Insight from Yeast
Taormina, G., & Mirisola, M. (2026) · Current Issues in Molecular Biology · doi:10.3390/cimb48101045
“The availability of whole-genome sequences also enabled genome-wide transcription analysis [7], protein– protein interaction atlases [8], protein localization maps [9], and genome-scale metabolic models [10].”
Li, Y., Shao, S., Lei, Q., Li, C., Yu, Q., Li, Y., Wang, S., Li, L., Chen, H., Huang, R., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117742
Huang, Y.-X., Yang, L., Wang, J.-D., & Gong, X.-Q. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1014698
“We further leveraged AlphaFold3 to model the structures of the predicted TRAPPII-like complex (Fig 10a) and the Ctf–Rfc complex (Fig 10b), and assessed their structural plausibility using the IPTM+PTM confidence metric [35,36].”
AASIA: A comprehensive protein structural interactome database for agricultural animals
Li, J., Yuan, M., Jiang, L., Li, D., Yin, Z., Zhu, F., Shi, W., Hou, Z., & Zhang, Z. (2026) · Journal of Advanced Research · doi:10.1016/j.jare.2026.09.015
Litsios, A., Lo, D. S., Fischbach, A., Friesen, H., Daiejavad, A., Sahin, N., Masinas, M. P., Nguyen, T., Pons, C., Hou, J., et al. (2026) · bioRxiv · doi:10.64898/2026.08.25.746993
“To test whether the structures in each pair are physically or functionally related, we determined for each pair of structures whether the genes associated with defects in a structure were enriched for protein-protein interactions 26 (PPIs) with the genes associated with the other structure.”
Sharma, P., Yadav, D., Faustino, A. M., Manriquez-Sandoval, E., Wagner, M., Carell, T., & Fried, S. D. (2026) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6c00388
Characterization of Vlf1 as a regulator of lipophagyPreprint
Fakih, Z., Cavarischia-Rega, C., Glück, B. R., Reichert, S., Dutta, P., Beresh, O., Schuldiner, M., Macek, B., Rapaport, D., & Dimmer, K. (2026) · bioRxiv · doi:10.64898/2026.08.11.744108
“Of note, this interaction was also reported in a high throughput mass spectrometry-based approach aimed at analyzing the complete interactome of S. cerevisiae proteins (Michaelis et al., 2023).”
Grantham, J. (2026) · Cell stress & chaperones (Print) · doi:10.1016/j.cstres.2026.100207
“41 Cryo-electron tomography was utilized to assess conformations and occupancy of the CCT oligomer in cultured human cells.”
Drugging the proteome via large-scale chemoproteomics.
Li, Y., Wang, J., Wang, T., Ke, X., & Qu, Y. (2026) · TIBS -Trends in Biochemical Sciences. Regular ed · doi:10.1016/j.tibs.2026.06.005
Chan, K., Yamaguchi, T., Izumiya, Y., Chu, Y.-W., & Watanabe, T. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27114750
“…in AdaPPI [125] were used as positive training references, an independent Complex Portal dataset [126] was used for testing, PPINs from DIP [127], BioGRID [12], and Mann-PPI [128] provided the interaction backbone, and UniProt [129] protein sequences were encoded using the conjoint triad method.”
Goel, M., Nissley, D., Castellanos-Girouard, X., Kuntz, C. P., Wang, Y.-Q., Mukhtar, M., Serohijos, A., & Schlebach, J. (2026) · bioRxiv · doi:10.64898/2026.05.11.724303
“15 By comparison, we observe very few signals within an analogous collection of Y2H measurements.”
Jessulat, M., Phanse, S., Aoki, H., Broderick, K., Zhang, Q., Castro, I., Novales, N. A., Hossain, S., Saccon, T., Moutaoufik, M., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-72525-2
“4a and Supplementary Data 9).”
InfluentialMechanistic dissection of BLTP2 targeting to ER-PM contact sitesPreprint
Neuman, S. D., Cavanagh, A., Sheffels, N., Conibear, E., & Bashirullah, A. (2026) · bioRxiv · doi:10.64898/2026.04.12.718032
“A recent study used a novel affinity purification approach to map nearly the entire S. cerevisiae interactome (Michaelis et al., 2023).”
WITHDRAWN: The Lsm1-7 complex marginally affects unstable mRNA degradation in yeast
Decourty, L., Namane, A., Janbon, G., & Saveanu, C. (2026) · bioRxiv · doi:10.64898/2025.12.17.694855
“This association with the mitoribosome was reported for Pat1 and other Lsm proteins, such as Lsm2, Lsm3, Lsm4, Lsm7, but not for nuclear Lsm8 (Michaelis et al. 2023).”
Emw1/TTC27 is a chaperone required for folding of the eukaryotic elongation factor 2
Yang, M., Li, R.-X., Mikolajczak, A., Wright, V. A., Hassan, M., Vaughan, C., Prescott, T. A., Heritz, J. A., Mollapour, M., & Panaretou, B. (2026) · Cellular and Molecular Life Sciences (CMLS) · doi:10.1007/s00018-026-06154-9
“In contrast, five separate studies have detected an interaction between eEF2 and Hgh1 [3, 4, 10, 33, 34].”
A Modular Toolkit for Nanoscale Interrogation of Multiprotein Assemblies Inside Living Cells.
Felker, A., Philippi, M., Holtmannspötter, M., Drees, C., Schäfer, E., Steinhart, M., Kurre, R., You, C., & Piehler, J. (2026) · ACS Nano · doi:10.1021/acsnano.5c14657
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“44–47 At 25°C, the level of Tpk3 was significantly reduced in cells expressing Cdc37-S14A and levels of Dun1 were reduced in cells expressing Hsc82-G309S.”
Mateusiak, C., Jia, E., Plaggenberg, J. N., Erdenebaatar, Z., Wang, Y. A., Shively, C. A., Liao, G., Mitra, R. D., & Brent, M. R. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.19.700460 · Cited by 1 · see citing works
There and back again: a cell biologist’s journey from organelles to molecules
Fenech, E. J., & Bykov, Y. S. (2025) · Biological Chemistry · doi:10.1515/hsz-2025-0185
“AE-MS, on the other hand, was employed for the global interactome analysis of baker ’ s yeast (Michaelis et al. 2023).”
Stausberg, D., Moshkovskii, S., Arlt, F. A., Fledrich, R., Stassart, R., Nave, K., Urlaub, H., Ewers, D., & Sereda, M. (2025) · bioRxiv · doi:10.1101/2025.09.03.673966
“Protein-protein interactions (PPIs) are essential for the cellular function of most proteins (Stumpf et al , 2008; Venkatesan et al , 2009; Michaelis et al , 2023).”
Rivera-Rivas, L. A., Hernández-Zamarripa, A. R., Florencio-Martínez, L., Manning-Cela, R., Carrero, J. C., Nepomuceno-Mejía, T., & Martínez-Calvillo, S. (2025) · Acta Tropica · doi:10.1016/j.actatropica.2025.107882
Huang, S., Liu, Y.-Q., Lv, L., & Wang, X. (2025) · Physics Letters · doi:10.1016/j.physleta.2025.131078
Zare, S. (2025) · bioRxiv · doi:10.1101/2025.04.11.647919
“While the current framework shows promising results, several avenues remain for further improvement: • Scalability and Efficiency: Future work could explore distributed computing techniques or more efficient algorithms to better handle growing biological datasets.”
Zhao, J., Mao, P.-Z., Wang, K.-F., Li, Y., Peng, Y.-P., Chen, R., Lu, S., Ji, X.-H., Ding, J.-X., Zhang, X., et al. (2025) · arXiv.org · doi:10.48550/arxiv.2507.00087
A Versatile Toolbox for Nanoscale Interrogation of Multiprotein Assemblies inside Living CellsPreprint
Felker, A., Philippi, M., Holtmannspötter, M., Drees, C., Schäfer, E., Steinhart, M., Kurre, R., You, C., & Piehler, J. (2025) · bioRxiv · doi:10.1101/2025.04.30.651189
“5 Despite tremendous progress in the structural prediction of protein complexes, quantitative interrogation of protein assemblies in the native cellular context remains a fundamental challenge in bioanalytics.”
Simmons, S. L., Graham, J., Cobb, D. W., Sudakar, S., Teng, E., Lee, E., Do, E. T., Scott, L., Price, A., Kezh, P., et al. (2025) · G3 · doi:10.1093/g3journal/jkaf074
“CK2 phosphorylates Atg32p in its regulation of Yeast genes required in limited sulfur and nitrogen | 13 mitophagy, particularly under nitrogen starvation conditions (Kanki et al .”
InfluentialThe receptor binding mechanism of mouse sPLA2 group IIE.
Hou, S.-L., He, H., Yang, H., Chen, C.-R., Wang, Q., Wu, Z.-F., Li, S.-J., & Xie, J. (2024) · Biochemical and Biophysical Research Communications - BBRC · doi:10.1016/j.bbrc.2024.151103
A nanobody-based microfluidic chip for fast and automated purification of protein complexes.
Keyser, P. D., de Waard, M. T. J., Jimidar, I. S. M., Verloy, S., Janvier, S., Kalichuk, V., Zögg, T., Wohlkonig, A., Pardon, E., Steyaert, J., et al. (2024) · Lab on a Chip · doi:10.1039/d4lc00728j
- Authors
- Michaelis, A. C., Brunner, A.-D., Zwiebel, M., Meier, F., Strauss, M. T., Bludau, I., & Mann, M.
- Affiliations
- Max Planck Institute of Biochemistry (DE)
- Boehringer Ingelheim (Germany) (DE)
- Jena University Hospital (DE)
- University of Copenhagen (DK)
- Corresponding author
- Mann, Matthias
- ORCID
- Venue
- Nature
- Published
- 2023-11-15
- Volume
- 624
- Issue
- 7990
- Pages
- 192-200
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC10700138
- OpenAlex
- W4388694323
- Cited by
- 119
- References
- 71
- Citations by year
- 2026: 34 · 2025: 44 · 2024: 38 · 2023: 2 · 2022: 1
- FWCI
- 10.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (191046)
- Max-Planck-Gesellschaft
- Novo Nordisk (NNF14CC0001)
- Novo Nordisk Fonden (NNF 14CC0001)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
- Keywords
- protein-protein interaction, interactome mapping, Saccharomyces cerevisiae, affinity purification mass spectrometry, membrane protein complexes, AlphaFold-Multimer, protein complex structure prediction
- MeSH terms
- Fungal Proteins, Humans, Saccharomyces cerevisiae, Mass Spectrometry, Reproducibility of Results, Databases, Factual, Proteome, Protein Interaction Mapping, Saccharomyces cerevisiae Proteins, Epigenesis, Genetic, Protein Interaction Maps
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