Selective footprinting of 40S and 80S ribosome subpopulations (Sel-TCP-seq) to study translation and its control.

Multiple aspects of mRNA translation are subject to regulation. Here we present a ribosome footprinting protocol to determine the location and composition of 40S and 80S ribosome complexes on endogenous mRNAs transcriptome-wide in vivo in yeast and mammalian cells. We present an extension of the translation complex profiling (TCP-seq) protocol, originally developed in yeast, by including an immunoprecipitation step to assay the location of both 40S and 80S ribosome complexes containing proteins of interest. This yields information on where along mRNAs the ribosome-bound protein of interest joins the ribosome to act, and where it leaves again, thereby monitoring the sequential steps of translation and the roles of various translation factors therein. Rapid fixation of live cells ensures the integrity of all translation complexes bound to mRNA at native positions. Two procedures are described, differing mainly in the fixation conditions and the library preparation. Depending on the research question, either procedure offers advantages. Execution of a Sel-TCP-seq experiment takes 5-10 working days, and initial data analysis can be completed within 2 days.

LinX: A Software Tool for Uncommon Cross-Linking Chemistry.

Chemical cross-linking mass spectrometry has become a popular tool in structural biology. Although several algorithms exist that efficiently analyze data-dependent mass spectrometric data, the algorithm to identify and quantify intermolecular cross-links located at the interaction interface of homodimer molecules was missing. The algorithm in LinX utilizes high mass accuracy for ion identification. In contrast with standard data-dependent analysis, LinX enables the elucidation of cross-linked peptides originating from the interaction interface of homodimers labeled by 14N/15N, including their ratio or cross-links from protein-nucleic acid complexes. The software is written in Java language, and its source code and a detailed user's guide are freely available at https://github.com/KukackaZ/LinX or https://ms-utils.org/LinX. Data are accessible via the ProteomeXchange server with the data set identifier PXD023522.

rPredictorDB: a predictive database of individual secondary structures of RNAs and their formatted plots.

Secondary data structure of RNA molecules provides insights into the identity and function of RNAs. With RNAs readily sequenced, the question of their structural characterization is increasingly important. However, RNA structure is difficult to acquire. Its experimental identification is extremely technically demanding, while computational prediction is not accurate enough, especially for large structures of long sequences. We address this difficult situation with rPredictorDB, a predictive database of RNA secondary structures that aims to form a middle ground between experimentally identified structures in PDB and predicted consensus secondary structures in Rfam. The database contains individual secondary structures predicted using a tool for template-based prediction of RNA secondary structure for the homologs of the RNA families with at least one homolog with experimentally solved structure. Experimentally identified structures are used as the structural templates and thus the prediction has higher reliability than de novo predictions in Rfam. The sequences are downloaded from public resources. So far rPredictorDB covers 7365 RNAs with their secondary structures. Plots of the secondary structures use the Traveler package for readable display of RNAs with long sequences and complex structures, such as ribosomal RNAs. The RNAs in the output of rPredictorDB are extensively annotated and can be viewed, browsed, searched and downloaded according to taxonomic, sequence and structure data. Additionally, structure of user-provided sequences can be predicted using the templates stored in rPredictorDB.

cpPredictor: a web server for template-based prediction of RNA secondary structure.

SUMMARY: We present the cpPredictor webserver that implements a novel template-based method for prediction of secondary structure of RNA. The method outperforms available prediction methods as it uses RNA structures of related molecules, either predicted or experimentally identified, as structural templates. The server aims at three major tasks: i) prediction of RNA secondary structures that are difficult to predict by available methods, ii) characterization of uncharacterized RNAs as compatible or incompatible with a chosen template structure and iii) an identification of the most relevant structure among different candidate structures of a single RNA ambiguously predicted by available methods. The web server is accompanied with a comprehensive documentation. AVAILABILITY AND IMPLEMENTATION: The web server is freely available at http://cppredictor.elixir-czech.cz/. The source code of the cpPredictor algorithm is freely available from the webserver under the Apache License, Version 2.0.

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

BACKGROUND: Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. RESULTS: We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. CONCLUSION: In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

Epidemiology of osteoarthritis and enthesopathies in a European population dating back 7700 years.

OBJECTIVES: To investigate the epidemiology of bone changes related to degenerative joint disease and enthesopathies in the earliest Neolithic population identified in Europe (dated back 7700 years), to compare the findings with those in medieval and contemporary populations, and to draw etiological inferences. METHODS: Examination of the skeletal remains of 119 individuals older than 20 years of age at death and buried in two Central European cemeteries dated as far back as 7700 years (5700 BC). RESULTS: The propensity for developing degenerative disease seemed to vary among individuals, as it does today. The hands, shoulder, and hip were common targets of osteoarthritis, as they are today, and the elbow was more likely to be affected in the Neolithic and medieval populations than in contemporary populations. When age of the individuals is taken into account, the prevalence of knee osteoarthritis does not seem to have changed substantially overtime. CONCLUSIONS: These results attest to the major role of microtrauma in osteoarthritis of the upper limb joints. At the other joints, after correction for age, the prevalence of degenerative disease and the combinations of joint involvements have remained remarkably constant over time, suggesting a major role for genetic factors (bone formers) already present in European populations in the early Neolithic period.