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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

Visual illustration of BADGE results of the P. damnosus beer spoilage example.(a) Illustration of BADGE comparison of the group of beer spoiling strains with the group of non-spoiling strains. The number of genes, shared by all five strains is also shown. All calculations were done with BADGE using default settings. (b) Percentage of SB-DMGs regarding their function based on RAST annotation. (c) BLAST ring image for whole genomes of all five strains. All rings are described from the inside to the outside: ring 1 (black) shows the whole genome of TMW 2.1535-SB as reference with bp coordinates; ring 2 (black) shows the GC content of TMW 2.1535-SB; ring 3 consists of arcs with different lengths and alternating coloration (grey / blue) representing the contigs (chromosome and plasmids) of TMW 2.1535-SB; ring 4 (red) shows all blast hits of TMW 2.1536-SB ORFs versus its own genome illustrating the coding density; ring 5 (orange) shows all blast hits of TMW 2.1533-SB ORFs versus the reference; rings 6–8 (blue shades) show all blast hits of the NB strains ORFs versus the reference, ring 9 contains all DMGs predicted by BADGE mapped to the reference, located in the gaps of the rings 6–8. Note that a particular DMG may occur more than once in a genome. Therefore the number of DMG labels does not correspond to the number of DMGs calculated by BADGE. (d) BLAST ring image for plasmids only. Most DMGs are located within clusters, e.g. in a cluster containing genes for fatty acid synthesis (FAS). For descriptions of the rings see (c).
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pone.0152747.g003: Visual illustration of BADGE results of the P. damnosus beer spoilage example.(a) Illustration of BADGE comparison of the group of beer spoiling strains with the group of non-spoiling strains. The number of genes, shared by all five strains is also shown. All calculations were done with BADGE using default settings. (b) Percentage of SB-DMGs regarding their function based on RAST annotation. (c) BLAST ring image for whole genomes of all five strains. All rings are described from the inside to the outside: ring 1 (black) shows the whole genome of TMW 2.1535-SB as reference with bp coordinates; ring 2 (black) shows the GC content of TMW 2.1535-SB; ring 3 consists of arcs with different lengths and alternating coloration (grey / blue) representing the contigs (chromosome and plasmids) of TMW 2.1535-SB; ring 4 (red) shows all blast hits of TMW 2.1536-SB ORFs versus its own genome illustrating the coding density; ring 5 (orange) shows all blast hits of TMW 2.1533-SB ORFs versus the reference; rings 6–8 (blue shades) show all blast hits of the NB strains ORFs versus the reference, ring 9 contains all DMGs predicted by BADGE mapped to the reference, located in the gaps of the rings 6–8. Note that a particular DMG may occur more than once in a genome. Therefore the number of DMG labels does not correspond to the number of DMGs calculated by BADGE. (d) BLAST ring image for plasmids only. Most DMGs are located within clusters, e.g. in a cluster containing genes for fatty acid synthesis (FAS). For descriptions of the rings see (c).

Mentions: More important, BADGE predicted 66 potential DMGs, which were present only in both strong spoilage strains (target group) and absent in all non-spoiling strains (background group). As already described, BADGE output can be affected by gene calling and the consistency of annotation. Thus the same comparison was also conducted with genes predicted by glimmer [43–45]. A comparison of both outputs revealed a 7.6% difference in DMG prediction, which could be reduced to 3.8% by applying the annotation_equalizer. Mainly very small and hypothetical proteins were found to be different. Using a spreadsheet application with the final tabular output file (S4 Table), functional and spatial gene clusters could be identified. Fig 3C and 3D show the localization of all DMGs using BRIG, illustrating that more than 95% of all potential DMGs are located on plasmids. Most DMGs are potentially encoding for hypothetical proteins, are part of a fatty acid synthesis cluster or mobile genetic elements (Fig 3B). Based on function, quality and localization of the predicted DMGs, 10 candidates were selected for primer design. For designation and predicted function see Table 3.


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)

Visual illustration of BADGE results of the P. damnosus beer spoilage example.(a) Illustration of BADGE comparison of the group of beer spoiling strains with the group of non-spoiling strains. The number of genes, shared by all five strains is also shown. All calculations were done with BADGE using default settings. (b) Percentage of SB-DMGs regarding their function based on RAST annotation. (c) BLAST ring image for whole genomes of all five strains. All rings are described from the inside to the outside: ring 1 (black) shows the whole genome of TMW 2.1535-SB as reference with bp coordinates; ring 2 (black) shows the GC content of TMW 2.1535-SB; ring 3 consists of arcs with different lengths and alternating coloration (grey / blue) representing the contigs (chromosome and plasmids) of TMW 2.1535-SB; ring 4 (red) shows all blast hits of TMW 2.1536-SB ORFs versus its own genome illustrating the coding density; ring 5 (orange) shows all blast hits of TMW 2.1533-SB ORFs versus the reference; rings 6–8 (blue shades) show all blast hits of the NB strains ORFs versus the reference, ring 9 contains all DMGs predicted by BADGE mapped to the reference, located in the gaps of the rings 6–8. Note that a particular DMG may occur more than once in a genome. Therefore the number of DMG labels does not correspond to the number of DMGs calculated by BADGE. (d) BLAST ring image for plasmids only. Most DMGs are located within clusters, e.g. in a cluster containing genes for fatty acid synthesis (FAS). For descriptions of the rings see (c).
© Copyright Policy
Related In: Results  -  Collection

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

pone.0152747.g003: Visual illustration of BADGE results of the P. damnosus beer spoilage example.(a) Illustration of BADGE comparison of the group of beer spoiling strains with the group of non-spoiling strains. The number of genes, shared by all five strains is also shown. All calculations were done with BADGE using default settings. (b) Percentage of SB-DMGs regarding their function based on RAST annotation. (c) BLAST ring image for whole genomes of all five strains. All rings are described from the inside to the outside: ring 1 (black) shows the whole genome of TMW 2.1535-SB as reference with bp coordinates; ring 2 (black) shows the GC content of TMW 2.1535-SB; ring 3 consists of arcs with different lengths and alternating coloration (grey / blue) representing the contigs (chromosome and plasmids) of TMW 2.1535-SB; ring 4 (red) shows all blast hits of TMW 2.1536-SB ORFs versus its own genome illustrating the coding density; ring 5 (orange) shows all blast hits of TMW 2.1533-SB ORFs versus the reference; rings 6–8 (blue shades) show all blast hits of the NB strains ORFs versus the reference, ring 9 contains all DMGs predicted by BADGE mapped to the reference, located in the gaps of the rings 6–8. Note that a particular DMG may occur more than once in a genome. Therefore the number of DMG labels does not correspond to the number of DMGs calculated by BADGE. (d) BLAST ring image for plasmids only. Most DMGs are located within clusters, e.g. in a cluster containing genes for fatty acid synthesis (FAS). For descriptions of the rings see (c).
Mentions: More important, BADGE predicted 66 potential DMGs, which were present only in both strong spoilage strains (target group) and absent in all non-spoiling strains (background group). As already described, BADGE output can be affected by gene calling and the consistency of annotation. Thus the same comparison was also conducted with genes predicted by glimmer [43–45]. A comparison of both outputs revealed a 7.6% difference in DMG prediction, which could be reduced to 3.8% by applying the annotation_equalizer. Mainly very small and hypothetical proteins were found to be different. Using a spreadsheet application with the final tabular output file (S4 Table), functional and spatial gene clusters could be identified. Fig 3C and 3D show the localization of all DMGs using BRIG, illustrating that more than 95% of all potential DMGs are located on plasmids. Most DMGs are potentially encoding for hypothetical proteins, are part of a fatty acid synthesis cluster or mobile genetic elements (Fig 3B). Based on function, quality and localization of the predicted DMGs, 10 candidates were selected for primer design. For designation and predicted function see Table 3.

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