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The Identification of Novel Diagnostic Marker Genes for the Detection of Beer Spoiling Pediococcus damnosus Strains Using the BlAst Diagnostic Gene findEr.

Behr J, Geissler AJ, Schmid J, Zehe A, Vogel RF - PLoS ONE (2016)

Bottom Line: DMG identification settings can be modified easily and installing and running BADGE does not require specific bioinformatics skills.On the basis of an example with relevance for beer brewing, being one of the oldest biotechnological processes known, we show a straightforward procedure, from phenotyping, genome sequencing, assembly and annotation, up to a discriminant marker gene PCR assay, making comparative genomics a means to an end.The value and the functionality of BADGE were thoroughly examined, resulting in the successful identification and validation of an outstanding novel DMG (fabZ) for the discrimination of harmless and harmful contaminations of Pediococcus damnosus, which can be applied for spoilage risk determination in breweries.

View Article: PubMed Central - PubMed

Affiliation: Lehrstuhl für Technische Mikrobiologie, Technische Universität München, Freising, Germany.

ABSTRACT
As the number of bacterial genomes increases dramatically, the demand for easy to use tools with transparent functionality and comprehensible output for applied comparative genomics grows as well. We present BlAst Diagnostic Gene findEr (BADGE), a tool for the rapid prediction of diagnostic marker genes (DMGs) for the differentiation of bacterial groups (e.g. pathogenic / nonpathogenic). DMG identification settings can be modified easily and installing and running BADGE does not require specific bioinformatics skills. During the BADGE run the user is informed step by step about the DMG finding process, thus making it easy to evaluate the impact of chosen settings and options. On the basis of an example with relevance for beer brewing, being one of the oldest biotechnological processes known, we show a straightforward procedure, from phenotyping, genome sequencing, assembly and annotation, up to a discriminant marker gene PCR assay, making comparative genomics a means to an end. The value and the functionality of BADGE were thoroughly examined, resulting in the successful identification and validation of an outstanding novel DMG (fabZ) for the discrimination of harmless and harmful contaminations of Pediococcus damnosus, which can be applied for spoilage risk determination in breweries. Concomitantly, we present and compare five complete P. damnosus genomes sequenced in this study, finding that the ability to produce the unwanted, spoilage associated off-flavor diacetyl is a plasmid encoded trait in this important beer spoiling species.

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Related in: MedlinePlus

The use-oriented prediction of diagnostic marker genes using BADGE.(a) Workflow illustrating the structure of a comparative genomics project with the aim to identify and validate diagnostic marker genes (DMGs). Each box corresponds to a single step within the straightforward procedure. (b) The prediction of group A specific DMGs is shown using a fictive example with two members of group A and two members of group B. A description of all steps can be found in the corresponding boxes. Genome = here: sequences of chromosome and all extrachromosomal elements (contigs); ORFs = open reading frames, here: sequences of all ORFs; DMG = diagnostic marker gene.
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pone.0152747.g001: The use-oriented prediction of diagnostic marker genes using BADGE.(a) Workflow illustrating the structure of a comparative genomics project with the aim to identify and validate diagnostic marker genes (DMGs). Each box corresponds to a single step within the straightforward procedure. (b) The prediction of group A specific DMGs is shown using a fictive example with two members of group A and two members of group B. A description of all steps can be found in the corresponding boxes. Genome = here: sequences of chromosome and all extrachromosomal elements (contigs); ORFs = open reading frames, here: sequences of all ORFs; DMG = diagnostic marker gene.

Mentions: As described above, some approaches and tools for the prediction of DMGs are available. However, these tools partially lack ease of use, require the installation of additional software packages or lack flexibility. This makes them difficult to install and handle for users without programming or IT background. In addition they do not focus on an application-oriented prediction of DMGs, relying on subsequent post-processing of data. With BADGE we provide users with a fast and applied tool for the prediction of DMGs. BADGE is based on the sh-compatible command language BASH (Bourne-again shell). BADGE requires as few commands as necessary and is simple to install on unix-based platforms, while being easy to use and highly flexible. Within a straightforward procedure (see Fig 1) we used BADGE as a central tool for the prediction of DMGs for a strain specific trait, starting with phenotyping up to the point of validation of the predicted DMGs using PCR. We sequenced five genomes of the important beer-spoiling species P. damnosus, comprising strains with varying beer spoilage ability. After assembly to complete genomes and consequent annotation, we used BADGE to identify new DMGs, allowing the differentiation of P. damnosus strains according to their ability to grow in and spoil beer.


The Identification of Novel Diagnostic Marker Genes for the Detection of Beer Spoiling Pediococcus damnosus Strains Using the BlAst Diagnostic Gene findEr.

Behr J, Geissler AJ, Schmid J, Zehe A, Vogel RF - PLoS ONE (2016)

The use-oriented prediction of diagnostic marker genes using BADGE.(a) Workflow illustrating the structure of a comparative genomics project with the aim to identify and validate diagnostic marker genes (DMGs). Each box corresponds to a single step within the straightforward procedure. (b) The prediction of group A specific DMGs is shown using a fictive example with two members of group A and two members of group B. A description of all steps can be found in the corresponding boxes. Genome = here: sequences of chromosome and all extrachromosomal elements (contigs); ORFs = open reading frames, here: sequences of all ORFs; DMG = diagnostic marker gene.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4814128&req=5

pone.0152747.g001: The use-oriented prediction of diagnostic marker genes using BADGE.(a) Workflow illustrating the structure of a comparative genomics project with the aim to identify and validate diagnostic marker genes (DMGs). Each box corresponds to a single step within the straightforward procedure. (b) The prediction of group A specific DMGs is shown using a fictive example with two members of group A and two members of group B. A description of all steps can be found in the corresponding boxes. Genome = here: sequences of chromosome and all extrachromosomal elements (contigs); ORFs = open reading frames, here: sequences of all ORFs; DMG = diagnostic marker gene.
Mentions: As described above, some approaches and tools for the prediction of DMGs are available. However, these tools partially lack ease of use, require the installation of additional software packages or lack flexibility. This makes them difficult to install and handle for users without programming or IT background. In addition they do not focus on an application-oriented prediction of DMGs, relying on subsequent post-processing of data. With BADGE we provide users with a fast and applied tool for the prediction of DMGs. BADGE is based on the sh-compatible command language BASH (Bourne-again shell). BADGE requires as few commands as necessary and is simple to install on unix-based platforms, while being easy to use and highly flexible. Within a straightforward procedure (see Fig 1) we used BADGE as a central tool for the prediction of DMGs for a strain specific trait, starting with phenotyping up to the point of validation of the predicted DMGs using PCR. We sequenced five genomes of the important beer-spoiling species P. damnosus, comprising strains with varying beer spoilage ability. After assembly to complete genomes and consequent annotation, we used BADGE to identify new DMGs, allowing the differentiation of P. damnosus strains according to their ability to grow in and spoil beer.

Bottom Line: DMG identification settings can be modified easily and installing and running BADGE does not require specific bioinformatics skills.On the basis of an example with relevance for beer brewing, being one of the oldest biotechnological processes known, we show a straightforward procedure, from phenotyping, genome sequencing, assembly and annotation, up to a discriminant marker gene PCR assay, making comparative genomics a means to an end.The value and the functionality of BADGE were thoroughly examined, resulting in the successful identification and validation of an outstanding novel DMG (fabZ) for the discrimination of harmless and harmful contaminations of Pediococcus damnosus, which can be applied for spoilage risk determination in breweries.

View Article: PubMed Central - PubMed

Affiliation: Lehrstuhl für Technische Mikrobiologie, Technische Universität München, Freising, Germany.

ABSTRACT
As the number of bacterial genomes increases dramatically, the demand for easy to use tools with transparent functionality and comprehensible output for applied comparative genomics grows as well. We present BlAst Diagnostic Gene findEr (BADGE), a tool for the rapid prediction of diagnostic marker genes (DMGs) for the differentiation of bacterial groups (e.g. pathogenic / nonpathogenic). DMG identification settings can be modified easily and installing and running BADGE does not require specific bioinformatics skills. During the BADGE run the user is informed step by step about the DMG finding process, thus making it easy to evaluate the impact of chosen settings and options. On the basis of an example with relevance for beer brewing, being one of the oldest biotechnological processes known, we show a straightforward procedure, from phenotyping, genome sequencing, assembly and annotation, up to a discriminant marker gene PCR assay, making comparative genomics a means to an end. The value and the functionality of BADGE were thoroughly examined, resulting in the successful identification and validation of an outstanding novel DMG (fabZ) for the discrimination of harmless and harmful contaminations of Pediococcus damnosus, which can be applied for spoilage risk determination in breweries. Concomitantly, we present and compare five complete P. damnosus genomes sequenced in this study, finding that the ability to produce the unwanted, spoilage associated off-flavor diacetyl is a plasmid encoded trait in this important beer spoiling species.

Show MeSH
Related in: MedlinePlus