Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

LOPIT-DC subcellular map of U-2 OS cells

ABSTRACT: Generation of a high-resolution subcellular localisation map for the proteome of the human cancer cell line U-2 OS, using the newly developed LOPIT-DC method. Comparison of the results generated using LOPIT-DC with data generated using the well-established hyperLOPIT method and data mining regarding multi-localising proteins, signalling pathways, isoforms and large protein complexes. Integration of the two methods using transfer learning.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Kathryn Lilley

PROVIDER: MSV000088434 | MassIVE | Tue Nov 23 07:54:00 GMT 2021

SECONDARY ACCESSION(S): PXD011254

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics.

Geladaki Aikaterini A Kočevar Britovšek Nina N Breckels Lisa M LM Smith Tom S TS Vennard Owen L OL Mulvey Claire M CM Crook Oliver M OM Gatto Laurent L Lilley Kathryn S KS

Nature communications 20190118 1

The study of protein localisation has greatly benefited from high-throughput methods utilising cellular fractionation and proteomic profiling. Hyperplexed Localisation of Organelle Proteins by Isotope Tagging (hyperLOPIT) is a well-established method in this area. It achieves high-resolution separation of organelles and subcellular compartments but is relatively time- and resource-intensive. As a simpler alternative, we here develop Localisation of Organelle Proteins by Isotope Tagging after Dif ...[more]

PMID: 30659192

Similar Datasets

LOPIT-DC subcellular map of U-2 OS cells

Project description:Generation of a high-resolution subcellular localisation map for the proteome of the human cancer cell line U-2 OS, using the newly developed LOPIT-DC method. Comparison of the results generated using LOPIT-DC with data generated using the well-established hyperLOPIT method and data mining regarding multi-localising proteins, signalling pathways, isoforms and large protein complexes. Integration of the two methods using transfer learning.

2019-01-23 | PXD011254 | Pride

Simultaneous characterisation of RNA and protein subcellular dynamics

Project description:Existing methods to analyse RNA localisation are constrained to specific RNAs or subcellular niches, precluding the cell-wide mapping of RNA. We present Localisation of RNA (LoRNA), which maps, at once, RNAs to membranous (nucleus, ER and mitochondria) and membraneless compartments (cytosol, nucleolus and phase-separated granules). Simultaneous interrogation of all RNA locations allows the system-wide quantification of RNA proportional distribution and the comprehensive analysis of RNA subcellular dynamics. Moreover, we have re-engineered the LOPIT (Localisation Of Proteins by Isotope Tagging) method, enabling integration with LoRNA, to jointly map RNA and protein subcellular localisation. Applying this framework, we obtain a global re-localisation map for 31839 transcripts and 5314 proteins during the unfolded protein response, uncovering that ER-localised transcripts are more efficiently recruited to stress granules than cytosolic RNAs, and revealing eIF3d is key to sustain cytoskeletal function. Overall, we provide the most exhaustive map to date of RNA and protein subcellular dynamics.

2022-01-25 | PXD030456 | Pride

A subcellular map of the human kinome.

Project description:The human kinome comprises 538 kinases playing essential functions by catalyzing protein phosphorylation. Annotation of subcellular distribution of the kinome greatly facilitates investigation of normal and disease mechanisms. Here, we present Kinome Atlas (KA), an image-based map of the kinome annotated to 10 cellular compartments. 456 epitope-tagged kinases, representing 85% of the human kinome, were expressed in HeLa cells and imaged by immunofluorescent microscopy under a similar condition. KA revealed kinase family-enriched subcellular localizations and discovered a collection of new kinase localizations at mitochondria, plasma membrane, extracellular space, and other structures. Furthermore, KA demonstrated the role of liquid-liquid phase separation in formation of kinase condensates. Identification of MOK as a mitochondrial kinase revealed its function in cristae dynamics, respiration, and oxidative stress response. Although limited by possible mislocalization due to overexpression or epitope tagging, this subcellular map of the kinome can be used to refine regulatory mechanisms involving protein phosphorylation.

| S-EPMC8175086 | biostudies-literature

Differential Peak Calling of ChIP-Seq Signals with Replicates with THOR

Project description:Dendritic cells (DC) are professional antigen presenting cells that develop from hematopoietic stem cells in bone marrow by successive steps of lineage commitment and differentiation. Different DC subsets were identified based on phenotype, localisation and function: (i) classical DC (cDC) and plasmacytoid DC (pDC) are found in lymphoid organs and (ii) migratory tissue DC are spread throughout peripheral organs, including Langerhans cells, the cutaneous contingent of DC. We have developed a two-step culture system that recapitulates DC development in vitro (Felker et al., J. Immunol. 185, 5326-5335, 2010). In this system multipotent hematopoietic progenitors (MPP) progress into DC-restricted common DC progenitors (CDP) and further into the two major DC subsets cDC and pDC. We employed chromatin immunoprecipitation (ChIP) with deep sequencing (ChIP-seq) to determine the dynamics of H3K27ac occupancy in MPP, CMP, cDC and pDC. Histone modification H3K27ac and RNA-Seq in MPP, CDP, cDC and pDC

2016-08-03 | E-GEOD-73143 | biostudies-arrayexpress

Differential Peak Calling of ChIP-Seq Signals with Replicates with THOR

Project description:Dendritic cells (DC) are professional antigen presenting cells that develop from hematopoietic stem cells in bone marrow by successive steps of lineage commitment and differentiation. Different DC subsets were identified based on phenotype, localisation and function: (i) classical DC (cDC) and plasmacytoid DC (pDC) are found in lymphoid organs and (ii) migratory tissue DC are spread throughout peripheral organs, including Langerhans cells, the cutaneous contingent of DC. We have developed a two-step culture system that recapitulates DC development in vitro (Felker et al., J. Immunol. 185, 5326-5335, 2010). In this system multipotent hematopoietic progenitors (MPP) progress into DC-restricted common DC progenitors (CDP) and further into the two major DC subsets cDC and pDC. We employed chromatin immunoprecipitation (ChIP) with deep sequencing (ChIP-seq) to determine the dynamics of H3K27ac occupancy in MPP, CDP, cDC and pDC. Additionally, we monitored changes in gene expression in MPP, CDP, cDC and pDC by RNA-seq.

2016-08-03 | GSE73143 | GEO

Application of text mining to build AOP-based mucus hypersecretion genesets and validation with in vitro and clinical samples

Project description:Purpose: Build genesets using text mining and validate the geneset with data from public repository and a dataset generated in house using in vitro models and RNA-seq Methods: Mucus hypersecretion and mucociliary dysfucntion adverse outcome pathways (AOPs) genesets were build using the text mining method described by Rani et al., 2015. Validation was performed using RNA expression data from cigarette and e-cigarette aerosol treated cells, IL-13 treated airway cells, and COPD-lung biopsies. The cigarette and e-cigarette aerosol RNA-samples from airway cells were generated and sequenced in house. The other dataset were publically available. Results: Using unsupervised clustering, the mucus hypersecretion and mucociliary dysfunction genesets were able to discriminate the cigartte treated cells from the e-cigarettes and the air control. The e-cigarette and the air control clustered together. Clustering was also observed with IL-13 treated cells. IL-13 is an induced of mucus hypersecretion. Clustering was not observed when COPD RNA-seq samples were used. PCA analysis revealed some degree of grouping based on disease status, but this was also heavily confounded by other parameters. Conclusions: Our study described the first application of text mining to build genesets relevant to AOPs. In vitro validation confirmed the genesets could discriminates between treatment that induce mucus hypersecretion phenotypes, however this could not be confirmed with COPD biopsy samples. This could be due to a series of technical confouding factors and the heterogeneity of the COPD disease.

2020-04-30 | GSE142100 | GEO

DC-SIGN initiates an immature dendritic cell phenotype triggering Rho activation that is utilised by HIV-1

Project description:DC-SIGN is a C-type lectin expressed by dendritic cells (DCs) that binds HIV-1, sequestering it within multivesicular bodies to facilitate transmission to CD4+ T cells. Here we characterize the molecular basis of signalling through DC-SIGN by large-scale gene expression profiling and phosphoproteome analysis. Solitary DC-SIGN activation leads to a phenotypically disparate transcriptional program from Toll-like receptor (TLR) triggering with downregulation of MHC II, CD86, and interferon response genes and with induction of the TLR negative regulator ATF3. Phosphoproteome analysis reveals DC-SIGN signals through the leukemia-associated Rho guanine nucleotide exchange factor (LARG) to induce Rho activity. This LARG activation also occurs on DC HIV exposure and is required for effective HIV viral synapse formation. Taken together HIV mediated DC-SIGN signalling provides a mechanism by which HIV evades the immune response yet induces viral spread. Keywords: Activation state, signalling, Toll-like Receptor (TLR)

2007-04-24 | GSE6090 | GEO

SFPQ-ABL1 and BCR-ABL1 utilise different signalling networks to drive B-cell acute lymphoblastic leukaemia

Project description:Purpose: We identified a rare instance of the SFPQ-ABL1 in a child with Ph-like ALL. The overall purpose of this study was to compare the structure and function of the SFPQ-ABL1 fusion to the well characterised BCR-ABL1 fusion. We used phosphoproteomics, transcriptomics and functional assays to determine the transforming capacity, subcellular localisation, and signalling networks of these two fusions. Given the known function of SFPQ in mRNA splicing, transcriptomic analysis was performed to analyse the effect of BCR-ABL1 or SFPQ-ABL1 expression on gene splicing. Methods: mRNA profiles of Ba/F3 cells expressing BCR-ABL1, SFPQ-ABL1, and empty vector control (MSCV) were generated by deep sequencing, in four biologically independent cell lines, using Illumina GAIIx. The sequences were aligned by subread and quantified by featureCounts. Results: In contrast to BCR-ABL1, SFPQ-ABL1 localised to the nuclear compartment and was a weaker driver of cellular proliferation. Phosphoproteomics analysis showed upregulation of cell cycle, DNA replication and spliceosome pathways, and downregulation of signal transduction pathways, including ErbB, NF-kappa B, VEGF, and MAPK signalling in SFPQ-ABL1-, compared to BCR-ABL1-expressing cells. SFPQ-ABL1 expression did not activate PI3K/AKT signalling and was associated with phosphorylation of G2/M cell cycle proteins. We identified no difference in overall splicing between cells expressing BCR-ABL1 and SFPQ-ABL1. Conclusions: SFPQ-ABL1 has functionally distinct mechanisms by which it drives ALL, including subcellular localisation, proliferative capacity, and activation of cellular pathways, highlighting the role that fusion partners have in mediating the function of ABL1 fusions.

2021-10-15 | GSE185860 | GEO

Transcription profiling of human monocyte derived dendritic cells treated with DC-SIGN initiates an immature dendritic cell phenotype triggering Rho activation that is utilised by HIV-1

Project description:DC-SIGN is a C-type lectin expressed by dendritic cells (DCs) that binds HIV-1, sequestering it within multivesicular bodies to facilitate transmission to CD4+ T cells. Here we characterize the molecular basis of signalling through DC-SIGN by large-scale gene expression profiling and phosphoproteome analysis. Solitary DC-SIGN activation leads to a phenotypically disparate transcriptional program from Toll-like receptor (TLR) triggering with downregulation of MHC II, CD86, and interferon response genes and with induction of the TLR negative regulator ATF3. Phosphoproteome analysis reveals DC-SIGN signals through the leukemia-associated Rho guanine nucleotide exchange factor (LARG) to induce Rho activity. This LARG activation also occurs on DC HIV exposure and is required for effective HIV viral synapse formation. Taken together HIV mediated DC-SIGN signalling provides a mechanism by which HIV evades the immune response yet induces viral spread. Experiment Overall Design: Circulating monocyte derived DCs were isolated from buffy coats by adherence and culture in IL-4 and granulocyte-macrophage colony-stimulating factor (GM-CSF). DC preparations analyzed were more than 98% pure. At day four 10 million immature DCs were either left unstimulated or stimulated using plate bound anti-DC-SIGN antibody for 2 hr. Three replicates of non-stimulated or stimulated cells were taken and used to extract total RNA.

2008-06-14 | E-GEOD-6090 | biostudies-arrayexpress

Genome-wide subcellular protein map for the flagellate parasite Trypanosoma brucei.

Project description:Trypanosoma brucei is a model trypanosomatid, an important group of human, animal and plant unicellular parasites. Understanding their complex cell architecture and life cycle is challenging because, as with most eukaryotic microbes, ~50% of genome-encoded proteins have completely unknown functions. Here, using fluorescence microscopy and cell lines expressing endogenously tagged proteins, we mapped the subcellular localization of 89% of the T. brucei proteome, a resource we call TrypTag. We provide clues to function and define lineage-specific organelle adaptations for parasitism, mapping the ultraconserved cellular architecture of eukaryotes, including the first comprehensive 'cartographic' analysis of the eukaryotic flagellum, which is vital for morphogenesis and pathology. To demonstrate the power of this resource, we identify novel organelle subdomains and changes in molecular composition through the cell cycle. TrypTag is a transformative resource, important for hypothesis generation for both eukaryotic evolutionary molecular cell biology and fundamental parasite cell biology.

| S-EPMC9981465 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data