Dataset Information

Membrane protein shaving with thermolysin can be used to evaluate topology predictors

ABSTRACT: Data from PASSEL: [[https://db.systemsbiology.net/sbeams/cgi/PeptideAtlas/PASS_View?datasetPassword=YV8455s&identifier=PASS00193 PASS00193]]. Data file: 110512_MB_LepB_65_10.mzXML. Published as part of Proteomics. 2013 Mar 20 . From the Abstract: {{i}}... Here, we examine the ability of some shaving enzymes to provide large-scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over-expressed proteins. Secondly, we analyzed the peptides from non over-expressed Escherichia coli membrane proteins with known structure to evaluate the shaving methods. Finally, the identified peptides were used to test the accuracy of a number of topology predictors ...{{/i}}

INSTRUMENT(S): Instrument

ORGANISM(S): Escherichia_coli_k_12_substr__mg1655, Enterobacteria_phage_13a, Enterobacteria_phage_933w, Enterobacteria_phage_alpha3, Enterobacteria_phage_ba14, Enterobacteria_phage_bp_4795, Enterobacteria_phage_bz13, Enterobacteria_phage_cdti, Enterobacteria_phage_ecods1, Enterobacteria_phage_eps7, Enterobacteria_phage_epsilon15, Enterobacteria_phage_es18, Enterobacteria_phage_felix_01, Enterobacteria_phage_fels_2, Enterobacteria_phage_fi_sensu_lato, Enterobacteria_phage_g4_sensu_lato, Enterobacteria_phage_hk022, Enterobacteria_phage_hk620, Enterobacteria_phage_hk97, Enterobacteria_phage_i2_2, Enterobacteria_phage_id18_sensu_lato, Enterobacteria_phage_id2, Enterobacteria_phage_if1, Enterobacteria_phage_ike, Enterobacteria_phage_jk06, Enterobacteria_phage_js10, Enterobacteria_phage_js98, Enterobacteria_phage_jse, Enterobacteria_phage_k1e, Enterobacteria_phage_k1f, Enterobacteria_phage_k1_5, Enterobacteria_phage_lambda, Enterobacteria_phage_m13, Enterobacteria_phage_min27, Enterobacteria_phage_ms2, Enterobacteria_phage_mu, Enterobacteria_phage_n15, Enterobacteria_phage_n4, Enterobacteria_phage_p1, Enterobacteria_phage_p2, Enterobacteria_phage_p22, Enterobacteria_phage_p4, Enterobacteria_phage_phi1, Enterobacteria_phage_phieco32, Enterobacteria_phage_phiecom_gj1, Enterobacteria_phage_phip27, Enterobacteria_phage_phiv10, Enterobacteria_phage_phix174_sensu_lato, Enterobacteria_phage_prd1, Enterobacteria_phage_psp3, Enterobacteria_phage_rb14, Enterobacteria_phage_rb32, Enterobacteria_phage_rb43, Enterobacteria_phage_rb49, Enterobacteria_phage_rb51, Enterobacteria_phage_rb69, Enterobacteria_phage_rtp, Enterobacteria_phage_sf6, Enterobacteria_phage_sfv, Enterobacteria_phage_sp6, Enterobacteria_phage_ssl_2009a, Enterobacteria_phage_st104, Enterobacteria_phage_st64t, Enterobacteria_phage_st_1, Enterobacteria_phage_t1, Enterobacteria_phage_t3, Enterobacteria_phage_t4, Enterobacteria_phage_t5, Enterobacteria_phage_t7, Enterobacteria_phage_tls, Enterobacteria_phage_vt2_sakai, Enterobacteria_phage_wa13_sensu_lato, Enterobacteria_phage_wv8, Enterobacteria_phage_yyz_2008, Enterobacteriophage_qbeta

DISEASE(S): Not Available

SUBMITTER: Bendz M, et al.

PROVIDER: GPM11210015438 | GPMDB |

REPOSITORIES: GPMDB

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Publications

Membrane protein shaving with thermolysin can be used to evaluate topology predictors.

Bendz Maria M Skwark Marcin M Nilsson Daniel D Granholm Viktor V Cristobal Susana S Käll Lukas L Elofsson Arne A

Proteomics 20130501 9

Topology analysis of membrane proteins can be obtained by enzymatic shaving in combination with MS identification of peptides. Ideally, such analysis could provide quite detailed information about the membrane spanning regions. Here, we examine the ability of some shaving enzymes to provide large-scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over-expressed proteins. Second, we analyzed the peptides from non- ...[more]

PMID: 23512833

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Project description:Spatial organization of the transcriptome has emerged as a powerful means for regulating the post-transcriptional fate of RNA in eukaryotes; however, whether prokaryotes use RNA spatial organization as a mechanism for post-transcriptional regulation remains unclear. Here we used super-resolution microscopy to image the E. coli transcriptome and observed a genome-wide spatial organization of RNA: mRNAs encoding inner-membrane proteins are enriched at the membrane, whereas mRNAs encoding outer-membrane, cytoplasmic and periplasmic proteins are distributed throughout the cytoplasm. Membrane enrichment is caused by co-translational insertion of signal peptides recognized by the signal-recognition particle. Our time-resolved RNA-sequencing and live-cell super-resolution imaging experiments revealed a physiological consequence of this spatial organization and the underlying mechanism: membrane localization enhances degradation rates of inner-membrane-protein mRNAs by placing them in proximity to membrane-bound RNA degradation enzymes. Together, these results demonstrate that the bacterial transcriptome is spatially organized and that this organization shapes the posttranscriptional Spatial organization of the transcriptome has emerged as a powerful means for regulating the post-transcriptional fate of RNA in eukaryotes; however, whether prokaryotes use RNA spatial organization as a mechanism for post-transcriptional regulation remains unclear. Here we used super-resolution microscopy to image the E. coli transcriptome and observed a genome-wide spatial organization of RNA: mRNAs encoding inner-membrane proteins are enriched at the membrane, whereas mRNAs encoding outer-membrane, cytoplasmic and periplasmic proteins are distributed throughout the cytoplasm. Membrane enrichment is caused by co-translational insertion of signal peptides recognized by the signal-recognition particle. Our time-resolved RNA-sequencing and live-cell super-resolution imaging experiments revealed a physiological consequence of this spatial organization and the underlying mechanism: membrane localization enhances degradation rates of inner-membrane-protein mRNAs by placing them in proximity to membrane-bound RNA degradation enzymes. Together, these results demonstrate that the bacterial transcriptome is spatially organized and that this organization shapes the post-transcriptional dynamics of mRNAs.

Dataset Information

Membrane protein shaving with thermolysin can be used to evaluate topology predictors

Publications

Membrane protein shaving with thermolysin can be used to evaluate topology predictors.

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