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Repertoire of morphable proteins in an organism.

ABSTRACT: All living organisms have evolved to contain a set of proteins with variable physical and chemical properties. Efforts in the field of structural biology have contributed to uncovering the shape and the variability of each component. However, quantification of the variability has been performed mostly by multiple pair-wise comparisons. A set of experimental coordinates for a given protein can be used to define the "morphness/unmorphness". To understand the evolved repertoire in an organism, here we show the results of global analysis of more than a thousand Escherichia coli proteins, by the recently introduced method, distance scoring analysis (DSA). By collecting a new index "UnMorphness Factor" (UMF), proposed in this study and determined from DSA for each of the proteins, the lowest and the highest boundaries of the experimentally observable structural variation are comprehensibly defined. The distribution plot of UMFs obtained for E. coli represents the first view of a substantial fraction of non-redundant proteome set of an organism, demonstrating how rigid and flexible components are balanced. The present analysis extends to evaluate the growing data from single particle cryo-electron microscopy, providing valuable information on effective interpretation to structural changes of proteins and the supramolecular complexes.

SUBMITTER: Izumi K

PROVIDER: S-EPMC7020816 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Repertoire of morphable proteins in an organism.

Izumi Keisuke K Saho Eitaro E Kutomi Ayuka A Tomoike Fumiaki F Okada Tetsuji T

PeerJ 20200211

All living organisms have evolved to contain a set of proteins with variable physical and chemical properties. Efforts in the field of structural biology have contributed to uncovering the shape and the variability of each component. However, quantification of the variability has been performed mostly by multiple pair-wise comparisons. A set of experimental coordinates for a given protein can be used to define the "morphness/unmorphness". To understand the evolved repertoire in an organism, here ...[more]

PMID: 32095378

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Project description:BackgroundThe annotation of biomolecular functions is an essential step in the analysis of newly sequenced organisms. Usually, the functions are inferred from predicted genes on the genome using homology search techniques. A high quality genomic sequence is an important prerequisite which, however, is difficult to achieve for certain organisms, such as hybrids or organisms with a large genome. For functional analysis it is also possible to use a de novo transcriptome assembly but the computational requirements can be demanding. Up to now, it is unclear how much of the functional repertoire of an organism can be reliably predicted from unassembled RNA-seq short reads alone.ResultsWe have conducted a study to investigate to what degree it is possible to reconstruct the functional profile of an organism from unassembled transcriptome data. We simulated the de novo prediction of biomolecular functions for Arabidopsis thaliana using a comprehensive RNA-seq data set. We evaluated the prediction performance using several homology search methods in combination with different evidence measures. For the decision on the presence or absence of a particular function under noisy conditions we propose a statistical mixture model enabling unsupervised estimation of a detection threshold. Our results indicate that the prediction of the biomolecular functions from the KEGG database is possible with a high sensitivity up to 94 percent. In this setting, the application of the mixture model for automatic threshold calibration allowed the reduction of the falsely predicted functions down to 4 percent. Furthermore, we found that our statistical approach even outperforms the prediction from a de novo transcriptome assembly.ConclusionThe analysis of an organism's transcriptome can provide a solid basis for the prediction of biomolecular functions. Using RNA-seq short reads directly, the functional profile of an organism can be reconstructed in a computationally efficient way to provide a draft annotation in cases where the classical genome-based approaches cannot be applied.

Dataset Information

Repertoire of morphable proteins in an organism.

Publications

Repertoire of morphable proteins in an organism.

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