Ykt6 membrane-to-cytosol cycling regulates exosomal Wnt secretion

Linnemannstöns, Karen; M, Pradhipa Karuna; Witte, Leonie; Kittel, Jeanette Clarissa; Danieli, Adi; Madeddu, Denise; Nitsch, Lena; Honemann‐Capito, Mona; Grawe, Ferdi; Wodarz, Andreas; Gross, Julia Christina

doi:10.1101/485565

Cited by 3 publications

(5 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ykt6 (O15498) is a SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein that regulates a wide variety of intracellular trafficking and membrane tethering and fusion processes. The membrane-associated form of Ykt6 has been detected at the PM, ER, Golgi apparatus, endosomes, lysosomes, vacuoles (in yeast), and autophagosomes as part of various SNARE complexes [71][72][73][74][75][76][77][78]. In line with this, our results show a mixed sub-cellular distribution for Ykt6 with potential localisation to the endosome and cytosol ( Fig 6D).…”

Section: Improved Annotation Allows Exploration Of Endosomal Processessupporting

confidence: 85%

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

et al. 2020

View full text Add to dashboard Cite

The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a protein’s sub-cellular localisation to one or more of these compartments can therefore be a first step in determining its function. High-throughput and high-accuracy mass spectrometry-based sub-cellular proteomic methods can now shed light on the localisation of thousands of proteins at once. Machine learning algorithms are then typically employed to make protein-organelle assignments. However, these algorithms are limited by insufficient and incomplete annotation. We propose a semi-supervised Bayesian approach to novelty detection, allowing the discovery of additional, previously unannotated sub-cellular niches. Inference in our model is performed in a Bayesian framework, allowing us to quantify uncertainty in the allocation of proteins to new sub-cellular niches, as well as in the number of newly discovered compartments. We apply our approach across 10 mass spectrometry based spatial proteomic datasets, representing a diverse range of experimental protocols. Application of our approach to hyperLOPIT datasets validates its utility by recovering enrichment with chromatin-associated proteins without annotation and uncovers sub-nuclear compartmentalisation which was not identified in the original analysis. Moreover, using sub-cellular proteomics data from Saccharomyces cerevisiae, we uncover a novel group of proteins trafficking from the ER to the early Golgi apparatus. Overall, we demonstrate the potential for novelty detection to yield biologically relevant niches that are missed by current approaches.

show abstract

Section: Improved Annotation Allows Exploration Of Endosomal Processessupporting

confidence: 85%

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

et al. 2020

View full text Add to dashboard Cite

show abstract

“…These proteins all have roles in intracellular vesicle transport in yeast [85][86][87], particularly the v-SNARE Ykt6 which is involved in vesicle fusion to the ER, Golgi and vacuole [88,89]. In Drosophila and human cells, Ykt6 is required for sorting of Wnt proteins into exosomes for secretion [90,91]. Interestingly, another SNARE protein similar to human syntaxin-2 was enriched in all the EV proteomes (Supplementary Data S2).…”

Section: Discussionmentioning

confidence: 99%

Protein markers forCandida albicansEVs include claudin‐like Sur7 family proteins

Dawson

Garcia-Ceron

Rajapaksha

et al. 2020

J of Extracellular Vesicle

View full text Add to dashboard Cite

Background: Fungal extracellular vesicles (EVs) have been implicated in host-pathogen and pathogen-pathogen communication in some fungal diseases. In depth research into fungal EVs has been hindered by the lack of specific protein markers such as those found in mammalian EVs that have enabled sophisticated isolation and analysis techniques. Despite their role in fungal EV biogenesis, ESCRT proteins such as Vps23 (Tsg101) and Bro1 (ALIX) are not present as fungal EV cargo. Furthermore, tetraspanin homologs are yet to be identified in many fungi including the model yeast S. cerevisiae. Objective: We performed de novo identification of EV protein markers for the major human fungal pathogen Candida albicans with adherence to MISEV2018 guidelines. Materials and methods: EVs were isolated by differential ultracentrifugation from DAY286, ATCC90028 and ATCC10231 yeast cells, as well as DAY286 biofilms. Whole cell lysates (WCL) were also obtained from the EV-releasing cells. Label-free quantitative proteomics was performed to determine the set of proteins consistently enriched in EVs compared to WCL. Results: 47 proteins were consistently enriched in C. albicans EVs. We refined these to 22 putative C. albicans EV protein markers including the claudin-like Sur7 family (Pfam: PF06687) proteins Sur7 and Evp1 (orf19.6741). A complementary set of 62 EV depleted proteins was selected as potential negative markers. Conclusions: The marker proteins for C. albicans EVs identified in this study will be useful tools for studies on EV biogenesis and cargo loading in C. albicans and potentially other fungal species and will also assist in elucidating the role of EVs in C. albicans pathogenesis. Many of the proteins identified as putative markers are fungal specific proteins indicating that the pathways of EV biogenesis and cargo loading may be specific to fungi, and that assumptions made based on studies in mammalian cells could be misleading. Abbreviations: A1-ATCC10231; A9-ATCC90028; DAY B-DAY286 biofilm; DAY Y-DAY286 yeast; EVextracellular vesicle; Evp1extracellular vesicle protein 1 (orf19.6741); GOgene ontology; Log 2 (FC)log 2 (fold change); MCCmembrane compartment of Can1; MDSmultidimensional scaling; MISEVminimal information for studies of EVs; sEVssmall EVs; SPsignal peptide; TEMstetraspanin enriched microdomains; TMtransmembrane; VDMvesicle-depleted medium; WCLwhole cell lysate ARTICLE HISTORY

show abstract

“…The membrane-associated form of Ykt6 has been detected at the PM, ER, Golgi apparatus, endosomes, lysosomes, vacuoles (in yeast), and autophagosomes as part of various SNARE complexes (Dilcher et al, 2001;Tai et al, 2004;Fukasawa et al, 2004;Meiringer et al, 2008;Takáts et al, 2018;Matsui et al, 2018;Linnemannstöns et al, 2018;Yong and Tang, 2019).…”

Section: Improved Annotation Allows Exploration Of Endosomal Processesmentioning

confidence: 99%

“…Fifth, O15498 (Ykt6) is a SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein which is conserved from yeast to humans. This protein regulates a wide variety of intracellular tracking and membrane tethering and fusion processes including ER-to-Golgi vesicular transport, intra-Golgi trac, retrograde Golgi-to-ER transport, retrograde endosome-to-TGN (trans-Golgi network) tracking, homotypic fusion of ER membranes, Golgi-to-PM transport and exosome/secretory vesicle-PM fusion, Golgi-tovacuole trac (in yeast), homotypic vacuole fusion (in yeast), autophagosome formation and autophagosome-lysosome fusion (Dilcher et al, 2001;Tai et al, 2004;Takáts et al, 2018;Matsui et al, 2018;Linnemannstöns et al, 2018;Yong and Tang, 2019). Ykt6 lacks a transmembrane domain and is able to cycle between intracellular membranes and the cytosol in a palmitoylation-and farnesylation-dependent manner (Fukasawa et al, 2004;Meiringer et al, 2008).…”

Section: Details Of Mcmcmentioning

confidence: 99%

“…Ykt6 lacks a transmembrane domain and is able to cycle between intracellular membranes and the cytosol in a palmitoylation-and farnesylation-dependent manner (Fukasawa et al, 2004;Meiringer et al, 2008). The membrane-associated form of Ykt6 has been detected on the PM, ER, Golgi apparatus, endosomes, lysosomes, vacuoles (in yeast), and autophagosomes as part of various SNARE complexes (Dilcher et al, 2001;Tai et al, 2004;Fukasawa et al, 2004;Meiringer et al, 2008;Takáts et al, 2018;Matsui et al, 2018;Linnemannstöns et al, 2018;Yong and Tang, 2019). In line with this information, our results show a mixed sub-cellular distribution for Ykt6 with potential localisation to the endosome and cytosol (gure 6, panel d).…”

Section: Details Of Mcmcmentioning

confidence: 99%

See 1 more Smart Citation

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

Crook

Geladaki

Nightingale

et al. 2020

Preprint

View full text Add to dashboard Cite

The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a protein's sub-cellular localisation to one or more of these compartments can therefore be a rst step in determining its function. High-throughput and high-accuracy mass spectrometry-based sub-cellular proteomic methods can now shed light on the localisation of thousands of proteins at once. Machine learning algorithms are then typically employed to make protein-organelle assignments. However, these algorithms are limited by insucient and incomplete annotation. We propose a semi-supervised Bayesian approach to novelty detection, allowing the discovery of additional, previously unannotated sub-cellular niches. Inference in our model is performed in a Bayesian framework, allowing us to quantify uncertainty in the allocation of proteins to new sub-cellular niches, as well as in the number of newly discovered compartments. We apply our approach across 10 mass spectrometry based spatial proteomic datasets, representing a diverse range of experimental protocols. Application of our approach to hyperLOPIT datasets validates its utility by recovering enrichment with chromatin-associated proteins without annotation and uncovers sub-nuclear compartmentalisation which was not identied in the original analysis. Moreover, using sub-cellular proteomics data from Saccharomyces cerevisiae, we uncover a novel group of proteins tracking from the ER to the early Golgi apparatus. Overall, we demonstrate the potential for novelty detection to yield biologically relevant niches that are missed by current approaches. * ksl23@cam.ac.uk

show abstract

Ykt6 membrane-to-cytosol cycling regulates exosomal Wnt secretion

Cited by 3 publications

References 83 publications

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

Protein markers forCandida albicansEVs include claudin‐like Sur7 family proteins

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

Contact Info

Product

Resources

About