Find research datasets worth reusing

opencc-by-4.0May 2024View details →

Distance Tuneable Integral Membrane Protein Containing Floating Bilayers via In Situ Directed Self-Assembly : Data and Analysis Scripts

<p>Neutron Reflectometry data and analysis scripts (for RasCal software) and Quartz Crystal Microbalance data and plotting script for data shown in Figures 1, 3, 4 and 5 of the Article: Distance Tuneable Integral Membrane Protein Containing Floating Bilayers via In Situ Directed Self-Assembly.</p>

opencc-by-4.0Apr 2019View details →

Simulations of membrane proteins in a mixture of lipids with varying levels of chain unsaturation

<p>Four structurally distinct membrane proteins were simulated in a mixture of phospholipids. The membranes contained one copy of one of the protein types with equimolar concentrations of DPPC, DOPC, DLiPC, SDPC, and cholesterol. The CHARMM36 force field [1] was employed, and the systems were built using the CHARMM-GUI web portal [2]. The 4-microsecond long simulations were performed using GROMACS [3]. Further details on the setup of the systems as well as on the simulation protocol can be found in the related paper at DOI: 10.1371/journal.pcbi.1007033.</p> <p>The files are named based on the PDB codes of the proteins (1AFO, 2M0B, 3EML, and 3EMN). For each system, the original simulation run input file (tpr) and the corresponding outputs (xtc, edr) are provided. Additionally, the simulations can be extended using the continue point (cpt) file. For each system the files required to generate the run input file are also provided: the topology file (top), index file (ndx), and a common run parameter file (mdp). The CHARMM36 force field can be downloaded from http://mackerell.umaryland.edu/charmm_ff.shtml</p> <p>Notably, the protein definition files (itp) were re-generated. After performing these simulations, the atom ordering of cholesterol in the CHARMM36 force field was changed. The provided gro files, as well as the lipid definition files (itp) correspond to this new atom order. While they can be used to generate a run input file, yet this run input file will not be identical to the one provided. Therefore: 1) for analysis, the provided xtc+tpr files are fine; 2) for extending the simulation, the tpr+cpt files are fine; 3) for new simulations, the tpr file can be generated based on the provided files, yet it cannot be used together with the provided xtc file.</p> <p>[1] <strong>DOI: </strong>10.1021/jp101759q</p> <p>[2] <strong>DOI: </strong>10.1021/acs.jctc.5b00935</p> <p>[3] <strong>DOI: </strong>10.1016/j.softx.2015.06.001</p>

opencc-by-4.0Sep 2019View details →

Coarse-grained simulation of a dilute lipid membranes with 7 protein types

<pre>A simulation of a DPPC lipid membrane with one copy of seven protein types. This is an extension to the dataset [1] with an even more dilute membrane. Topologies and mdp files can be obtained from [1], and all the simulation parameters are equal to those described in [1] and in the related publication [2]. The trajectory does not contain the solvent and is stored every 10 ns. [1] https://doi.org/10.5281/zenodo.846428</pre> <p>[2] M. Javanainen, H. Martinez-Seara, R. Metzler, and I. Vattulainen; Diffusion of Integral Membrane Proteins in Protein-Rich Membranes. J. Phys. Chem. Lett., 2017, 8 (17), pp 4308–4313, DOI: 10.1021/acs.jpclett.7b01758<br>  </p>

opencc-by-4.0Nov 2024View details →

Disorder predictions for all reviewed UniProt proteins with "membrane" subcellular localization

<h1>IDRs in membrane proteins</h1> <h3>About</h3> <p>The writeup below walks through how to answer the question "what fraction of membrane proteins have IDRs".</p> <p>The tl/dr: on average <strong>55% of membrane proteins [as defined here] have IDRs</strong>.</p> <h3>Data</h3> <p>This directory (WITH the associated sequences), which are not included on GitHub, are deposited on Zenodo.</p> <h2>Steps</h2> <h4>Install software</h4> <p>Install metapredict</p> <div> <pre><code>pip install metapredict</code></pre> </div> <p>Done.</p> <h4>Find the data</h4> <p>Using the "Advanced Search", I downloaded all reviewed proteins on <a href="https://uniprot.org/">UniProt</a> tagged as having a "membrane" subcellular localization.</p> <p>There are, of course, much more detailed ways one could get these data (e.g., requiring transmembrane helices, integral membrane protein filtering etc, etc), but I figured for purposes here, I'd just do this...</p> <h4>Download the data</h4> <p>From this, I downloaded all the FASTA sequences. This triggers the following file to be downloaded:</p> <div> <pre><code>uniprotkb_cc_scl_term_SL_0162_AND_revie_2024_11_09.fasta</code></pre> </div> <h4>Preprocessing the data</h4> <p>Next I wanted to fix any sequences with non-standard amino acids by converting those residues to "standard" amino acids. I did this using <code>pfasta</code>, a commandline tool that's part of <a href="https://protfasta.readthedocs.io/en/latest/">protfasta</a> which comes with metapredict.</p> <p>Did this simply with</p> <div> <pre><code>pfasta --invalid-sequence convert-all -o membrane_proteins.fasta uniprotkb_cc_scl_term_SL_0162_AND_revie_2024_11_08.fasta</code></pre> </div> <ul> <li>The <code>--invalid-sequence</code> flag tells pfasta what to with an invalid sequence, and <code>-o</code> tells it what the ouput file should be called.</li> </ul> <p>Running this (~5 seconds) generates the following output:</p> <div> <pre><code>........................ pfasta version 0.1.13+0.gc1786bd.dirty Please report bugs to: https://github.com/holehouse-lab/protfasta ........................ [INFO]: Reading in the file uniprotkb_cc_scl_term_SL_0162_AND_revie_2024_11_08.fasta [INFO]: Read in file with 1004330 lines [INFO]: Parsed file to recover 117691 sequences [INFO]: Converted 697 sequences to valid sequences [INFO]: Writing new sequence file [membrane_proteins.fasta]...</code></pre> </div> <h4>Predicting all IDRs</h4> <p>Run one of metapredict's command-line utilities to predict all IDRs in these proteins.</p> <div> <pre><code>metapredict-predict-idrs membrane_proteins.fasta -o membrane_protein_idrs.fasta</code></pre> </div> <p>This takes ~20 seconds on my desktop with an A4500 GPU or ~5 min with my Macbook Pro. We're then left with a file called <code>membrane_protein_idrs.fasta</code>. This is a FASTA file that the header format:</p> <div> <pre><code>><HEADER FOR ORIGINAL PROTEIN> IDR_START=<start position> IDR_END=<end_position></code></pre> </div> <p>e.g.</p> <div> <pre><code>>sp|B4R1D8|HH_DROSI Protein hedgehog OS=Drosophila simulans OX=7240 GN=hh PE=3 SV=1 IDR_START=0 IDR_END=94 MDNHSSVPWASAASVTCLSLDAKCHSSSSSCSSKSTASSISASPETQTMRHIAHTQRCLS RLTSLVALLLIVLPMMFSPAHSCGPGRGLGRHRA</code></pre> </div> <h3>Hacky way to get number of proteins with IDRs</h3> <p>Get the number of unique proteins in the main file:</p> <div> <pre><code>cat membrane_proteins.fasta | grep ">" | awk -F "|" {' print $2 '} | sort | uniq |wc</code></pre> </div> <p>Which returns</p> <div> <pre><code>117691 117691 829609</code></pre> </div> <p>So we have 117,691 unique proteins (NB: we could also just have gotten this without the <code>awk -F "|" {' print $2 '} | sort | uniq</code> part BUT we do need that for the number of unique proteins with IDRs so good to be consistent.</p> <div> <pre><code>cat membrane_protein_idrs.fasta | grep ">" | awk -F "|" {' print $2 '} | sort | uniq |wc</code></pre> </div> <p>Which returns</p> <div> <pre><code>64971 64971 458829 </code></pre> </div> <p>So on average <strong>55% of membrane proteins [as defined here] have IDRs</strong>.</p> <h3>Bonus!</h3> <p>In addition we can predict all disorder scores rather than discrete IDRs using</p> <div> <pre><code>metapredict-predict-disorder membrane_proteins.fasta -o membrane_protein_disorder_scores.csv</code></pre> </div> <p>This takes ~5 min on my Macbook Pro. The data for these are included here for completeness/convenience.</p>

Fig. 4 in Identification and Expression Patterns of Sensory Neuron Membrane Protein Genes from Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae)

Fig. 4. Relative expression levels of SzeaSNMP in various tissues of Sitophilus zeamais. mAn = male antennae; fAn = female antennae; H = heads without antennae; T = thoraces without legs and wings; Abd = abdomens; W = wings; L = legs. Error bars represent the standard error, and the different letters above each bar indicate significant differences in relative levels of expression at P <0.05 (Tukey's HSD test).

Fig. 2 in Identification and Expression Patterns of Sensory Neuron Membrane Protein Genes from Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae)

Fig. 2. Sequence alignments of Sitophilus zeamais sensory neuron membrane protein with SNMPs from other Coleoptera species. Black triangles represent six conserved cysteine residues that could form three pairs of disulphide bridges in the SNMPs (Rasmussen et al. 1998). Abbreviated species names and GenBank accession numbers of amino acid sequences are described in Fig. 3.

Fig. 3 in Identification and Expression Patterns of Sensory Neuron Membrane Protein Genes from Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae)

Fig. 3. Phylogenetic analysis of insect SNMPs. A tree of SNMPs from Sitophilus zeamais and other insects was made by MEGA7 through the Neighbor-joining method with 1,000 bootstrap replications. The insect species and GenBank accession numbers for all the sequences of SNMPs are as follows: Aethina tumida (AtumSNMP2a/XP_019867287.1, AtumSNMP2b/ XP_019867285.1); Anoplophora chinensis (AchiSNMP1a/AUF73093.1, AchiSNMP1b/AUF73091.1); Anoplophora glabripennis (AglaSNMP2a/XP_018566912.1, AglaSNMP2b/XP_018566911.1); Colaphellus bowringi (CbowSNMP1a/ ALR72542.1, CbowSNMP1b/ALR72543.1, CbowSNMP2/ALR72544.1); Dendroctonus ponderosae (DponSNMP1a/ AGI05171.1, DponSNMP1b/XP_019756753.1, DponSNMP2a/XP_019770615.1, DponSNMP2b/AGI05184.1); Holotrichia parallela (HparSNMP1/AVM18969.1); Leptinotarsa decemlineata (LdecSNMP2/XP_023025981.1); Onthophagus taurus (OtauSNMP1/XP_022906339.1); Phyllotreta striolata (PstrSNMP1/ANQ46504.1, PstrSNMP2/ANQ46505.1); Tenebrio molitor (TmolSMMP1/AJO62245.1); Tribolium castaneum (TcasSNMP1/KYB28032.1, TcasSNMP2a/XP_008198962.1, TcasSMMP2b/ XP_970008.1).

Fig. 1 in Identification and Expression Patterns of Sensory Neuron Membrane Protein Genes from Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae)

Fig. 1. Nucleotide and deduced amino acid sequences of SzeaSNMPs from Sitophilus zeamais. The stop codons are marked with "-", and the black lines below the amino acid sequences indicate the two transmembrane domains. A) SzeaSNMP1a, B) SzeaSNMP1b, C) SzeaSNMP2a, D) SzeaSNMP2b.

opencc-by-4.0Oct 2021View details →

Membrane Protein Channels Equipped With a Cleavable Linker for Inducing Catalysis Inside Nanocompartments

<p>Data underlying the figures in the publication “Membrane protein channels equipped with a cleavable linker for inducing catalysis inside nanocompartments”, published in <em>J. Mater. Chem. B, </em><em><strong>2021</strong></em><em>.</em></p> <p><em><a href="https://pubs.rsc.org/en/content/articlelanding/2021/TB/D1TB01463C">https://pubs.rsc.org/en/content/articlelanding/2021/TB/D1TB01463C</a></em></p> <p>Table of contents:</p> <p><strong>1. Figure 1</strong>: Experimental data for <em>Figure 1</em>. OmpF structure and linker design. <em>(A)</em> PyMol ribbon representation of OmpF-M secondary structure reveals a distance of about 30 Å between the side groups of the two amino acids replaced by Cys in OmpF-M. <em>(B)</em> The linker length corresponds to the distance between the two opposing Cys of OmpF-M, as estimated by PyMol modeling. <em>(C)</em> Chemical structure of the designed linker terminal maleimide groups, fluorophore side chains (pink) and the diol unit (blue).</p> <p><strong>2. Figure 2</strong>: Experimental data for <em>Figure 2</em>. Ultrastructural morphology of <em>(A)</em> CNCs without OmpF, <em>(B)</em> CNCs with linker-OmpF-M inserted in the membrane, <em>(C)</em> CNCs with OmpF-M, and <em>(D)</em> OmpF wild-type. Scale bars: 200 nm. <em>(E)</em> FCS autocorrelation curves (solid line) and raw data (dots) of PBS solutions of the linker (black), standalone linker-OmpF-M in 1% OG (blue), and CNCs with linker-OmpF-M inserted in the membrane (red).</p> <p><strong>3. Figure 3</strong>: Experimental data for <em>Figure 3</em>. Linker-based control of laccase activity in CNCs in response to NaIO4. <em>(A)</em> Schematic representation of periodate-induced linker cleavage, activating in situ catalysis. Addition of NaIO<sub>4</sub> cleaves the linker and thereby unblocks the pore. In the open state, substrate enters the compartment where it is oxidized to a detectable product by the confined laccase. <em>(B)</em> An increase in absorbance at 470 nm reflects laccase-catalyzed DMP conversion in NaIO<sub>4</sub>-treated CNC-linker-OmpF-M. Laccase activity was minimal in CNCs lacking OmpF or in CNC-linker OmpF-M in the absence of NaIO<sub>4</sub> (closed pores). Measurements were carried out at pH 7.4 for 9 hours at RT.</p> <p><strong>4. Figure 4</strong>: Experimental data for <em>Figure 4</em>. Absorbance intensity of the laccase product was measured at 470 nm. Measurements were carried out in triplicate (SD) at pH 7.4 and RT. <em>(A)</em> Activity of free laccase in PBS compared to laccase encapsulated in CNC-linker-OmpF in the presence of NaIO<sub>4</sub> over 20 h. <em>(B)</em> Activity measured for one week of free laccase in PBS compared to CNCs with and without periodate-cleaved pores or CNCs lacking pores. Periodate treatment had no effect on the ultrastructural morphology of (C) CNClinker-OmpF-M compared to (D) CNC-no OmpF after 1 week nor after 3 weeks (<em>E</em> and <em>F</em>, respectively). Scale bars: 200 nm.</p> <p><strong>5. Figure 5</strong>: Experimental data for <em>Figure 5</em>. Longevity of CNC morphology. TEM micrographs of CNCs encapsulating laccase with <em>(A)</em> unmodified OmpF-M inserted in the compartment membrane, and <em>(B)</em> linker-OmpF-M reveal an intact morphology after 11 months at 4 1C. Scale bars: 500 nm.</p> <p><strong>6. Figure S5</strong>: Experimental data for <em>Figure S5</em>.</p> <p><strong>7. Figure S8</strong>: Experimental data for <em>Figure S8</em>.</p> <p><strong>8. Figure S9</strong>: Experimental data for <em>Figure S9</em>.</p> <p><strong>9. Figure S10</strong>: Experimental data for <em>Figure S10</em>.</p> <p><strong>10. Figure S12</strong>: Experimental data for <em>Figure S12</em>.</p> <p> </p>

opencc-by-4.0Sep 2023View details →

The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini

<p>The deposited data set contains data for the main figure 3 of the manuscript "The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini" by Blaimschein et al. published in Structure (2023).</p>

opencc-by-4.0Sep 2023View details →

The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini

<p>The deposited data set contains data for the main figure 2 of the manuscript "The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini" by Blaimschein et al. published in Structure (2023).</p>

opencc-by-4.0Sep 2023View details →

The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini

<p>The deposited data set contains data for the main figure 6 of the manuscript "The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini" by Blaimschein et al. published in Structure (2023).</p>

Fig. 4 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

Fig. 4. DEG functional enrichment during different growth stages. Pathway functional enrichment of differential expressed genes (DEGs) by using Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Pathways are at the yaxis plot, while rich factor values are at the x-axis. Size of the dots reflect gene number; small dot means 500 genes, big dot means 1000 genes. Darker the color of the dot means the highest the significant value of enrichment (Q-value). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 6 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

Fig. 6. Summary differential expressed genes (DEGs) in photosynthesis – antenna proteins pathway (second most enriched pathway) using Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation analysis. The genes at early stationary growth phase were normalized against genes at early exponential growth phase. Green color means down-regulated DEGs; red color means up-regulated DEGs; black color means no DEGs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

Fig. 1. Functional annotation of unigenes. Ratio of different species maps on transcripts annotation analysis based on non-redundant (NR) protein databases. Blue color means Monoraphidium neglectum; green color means other species; orange means Porphyra umbilicalis; grey color means Aureococcus anophagefferens; yellow color means Guillardia theta CCMP2712; purple color means Chlamydomonas reinhardtii. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

Fig. 5. Top DEG pathway enrichment involved during different growth stages. Summary of differential expressed genes (DEGs) identified in photosynthesis pathway (most enriched pathway) of M. gracile SE-MC4 according to Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation analysis. The genes at early stationary growth phase were normalized against genes at early exponential growth phase. Green color means down-regulated DEGs; red color means up-regulated DEGs; black color means no DEGs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

Fig. 3. Differential expressed gene analysis (DEG) of transcriptome. DEG in Volcano plot (log transform of early exponential growth and early stationary growth phases versus inverse log Padj – corrected P-value). Up-regulated DEGs are in red color dots, down-regulated DEGs are in blue dots, while grey dots represent no significant DEGs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

Fig. 2. Transcriptome expression analysis during different growth stages. (a) Venn diagram for specific treatment genes. Venn diagram constructed based on subset between gene pools in the early exponential and early stationary growth phases of M. gracile SEMC4 cultures. The total number of early exponential growth-specific (EEG-specific) genes (blue subset); early stationary growth-specific (ESG-specific) genes (pink sub set) and regulatory genes (purple sub set) are as indicated. (b) Soft clustering based on time series analysis on expression changes between early exponential growth and early stationary growth phases of M. gracile SE-MC4 cultures. R1, R2 and R3 are the biological replicates of each early exponential (day 1) and early stationary (day 12) growth phase of M. gracile SE-MC4 cultures. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)