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Prediction of microbial phenotypes based on comparative genomics.

ABSTRACT: The accessibility of almost complete genome sequences of uncultivable microbial species from metagenomes necessitates computational methods predicting microbial phenotypes solely based on genomic data. Here we investigate how comparative genomics can be utilized for the prediction of microbial phenotypes. The PICA framework facilitates application and comparison of different machine learning techniques for phenotypic trait prediction. We have improved and extended PICA's support vector machine plug-in and suggest its applicability to large-scale genome databases and incomplete genome sequences. We have demonstrated the stability of the predictive power for phenotypic traits, not perturbed by the rapid growth of genome databases. A new software tool facilitates the in-depth analysis of phenotype models, which associate expected and unexpected protein functions with particular traits. Most of the traits can be reliably predicted in only 60-70% complete genomes. We have established a new phenotypic model that predicts intracellular microorganisms. Thereby we could demonstrate that also independently evolved phenotypic traits, characterized by genome reduction, can be reliably predicted based on comparative genomics. Our results suggest that the extended PICA framework can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomics studies.

SUBMITTER: Feldbauer R

PROVIDER: S-EPMC4603748 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Prediction of microbial phenotypes based on comparative genomics.

Feldbauer Roman R Schulz Frederik F Horn Matthias M Rattei Thomas T

BMC bioinformatics 20151002

The accessibility of almost complete genome sequences of uncultivable microbial species from metagenomes necessitates computational methods predicting microbial phenotypes solely based on genomic data. Here we investigate how comparative genomics can be utilized for the prediction of microbial phenotypes. The PICA framework facilitates application and comparison of different machine learning techniques for phenotypic trait prediction. We have improved and extended PICA's support vector machine p ...[more]

PMID: 26451672

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Project description:BACKGROUND: We studied four extremely halophilic archaea by low-pass shotgun sequencing: (1) the metabolically versatile Haloarcula marismortui; (2) the non-pigmented Natrialba asiatica; (3) the psychrophile Halorubrum lacusprofundi and (4) the Dead Sea isolate Halobaculum gomorrense. Approximately one thousand single pass genomic sequences per genome were obtained. The data were analyzed by comparative genomic analyses using the completed Halobacterium sp. NRC-1 genome as a reference. Low-pass shotgun sequencing is a simple, inexpensive, and rapid approach that can readily be performed on any cultured microbe. RESULTS: As expected, the four archaeal halophiles analyzed exhibit both bacterial and eukaryotic characteristics as well as uniquely archaeal traits. All five halophiles exhibit greater than sixty percent GC content and low isoelectric points (pI) for their predicted proteins. Multiple insertion sequence (IS) elements, often involved in genome rearrangements, were identified in H. lacusprofundi and H. marismortui. The core biological functions that govern cellular and genetic mechanisms of H. sp. NRC-1 appear to be conserved in these four other halophiles. Multiple TATA box binding protein (TBP) and transcription factor IIB (TFB) homologs were identified from most of the four shotgunned halophiles. The reconstructed molecular tree of all five halophiles shows a large divergence between these species, but with the closest relationship being between H. sp. NRC-1 and H. lacusprofundi. CONCLUSION: Despite the diverse habitats of these species, all five halophiles share (1) high GC content and (2) low protein isoelectric points, which are characteristics associated with environmental exposure to UV radiation and hypersalinity, respectively. Identification of multiple IS elements in the genome of H. lacusprofundi and H. marismortui suggest that genome structure and dynamic genome reorganization might be similar to that previously observed in the IS-element rich genome of H. sp. NRC-1. Identification of multiple TBP and TFB homologs in these four halophiles are consistent with the hypothesis that different types of complex transcriptional regulation may occur through multiple TBP-TFB combinations in response to rapidly changing environmental conditions. Low-pass shotgun sequence analyses of genomes permit extensive and diverse analyses, and should be generally useful for comparative microbial genomics.

Project description:The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone.Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc.

Dataset Information

Prediction of microbial phenotypes based on comparative genomics.

Publications

Prediction of microbial phenotypes based on comparative genomics.

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