Analysis of M. pneumoniae ribosome and polysome distributions inside cells and ribosomal protein extensions
Supporting scripts to a publication by Liang Xue, Swantje Lenz, Maria Zimmermann-Kogadeeva, Dimitry Tegunov, Patrick Cramer, Peer Bork, Juri Rappsilber, and Julia Mahamid
This script analyses ribosome sequences in polysomes identified from M. pneumoniae tomograms and performs statistical analysis of ribosome pairs and comparison to randomly shuffled ribosomes. Each ribosome is classified based on its conformation according to the translation-elongation cycle.
Required file in the data_ribosomes folder:
- motl_annoted_addpolysome_allcombined.txt
File contains coordinates of all identified ribosomes across M. pneumoniae tomograms with class information. The format is described in the file motl_format.ppt.
- polysome_tomoNum_pid_riboclass_sequence
File contains polysome sequences encoded with ribosome classes. The file format and classifications are explained in the file info.ppt.
This script makes a figure with schematic representation of amino acid extensions in M. pneumoniae ribosomal proteins and their structural and functional information.
Required file in the data_rp_sequences folder:
- rp_extensions20_allCN.fasta
Fasta file with amino acid sequences for ribosomal proteins with extensions > 20 amino acids as compared to E. coli downloaded from NCBI (RefSeq)
- rp_extension_stats.csv
Extension table with information on extension lengths for the selected ribosomal proteins
- rp_xlink_information.csv
Information on cross links in ribosomal proteins from O'Reilly & Xue et al, Science 2020 (https://doi.org/10.1126/science.abb3758)
- rp_jpred_prediction.fasta
Fasta file with secondary structure predictions by JPRED (https://www.compbio.dundee.ac.uk/jpred/)
- rp_iupred_disorder_scores.csv
File with disorder scores for each amino acid in ribosomal proteins predicted by IUPRED (https://iupred2a.elte.hu/)
- rp_TNins_mapping.csv
Positions of transposon insertions in ribosomal proteins from Miravet-Verde et al., Nucleic Acids Research 2020 (https://doi.org/10.1093/nar/gkaa679)