A genomic search approach to identify esterases in Propionibacterium freudenreichii involved in the formation of flavour in Emmental cheese

<p>Abstract</p> <p>Background</p> <p>Lipolysis is an important process of cheese ripening that contributes to the formation of flavour.<it> Propionibacterium freudenreichii </it>is the main agent of lipolysis in Emmental cheese; however, the enzymes involved produced by this species have not yet been identified. Lipolysis is performed by esterases (carboxylic ester hydrolases, EC 3.1.1.-) which are able to hydrolyse acylglycerols bearing short, medium and long chain fatty acids. The genome sequence of <it>P. freudenreichii </it>type strain CIP103027^Twas recently obtained in our laboratory.</p> <p>The aim of this study was to identify as exhaustively as possible the potential esterases in <it>P. freudenreichii </it>that could be involved in the hydrolysis of acylglycerols in Emmental cheese. The proteins identified were produced in a soluble and active form by heterologous expression in <it>Escherichia coli </it>for further study of their activity and specificity of hydrolysed substrates.</p> <p>Results</p> <p>The approach chosen was a genomic search approach that combined and compared four methods based on automatic and manual searches of homology and motifs among <it>P. freudenreichii </it>CIP103027^Tpredicted proteins. Twenty-three putative esterases were identified in this step. Then a selection step permitted to focus the study on the 12 most probable esterases, according to the presence of the GXSXG motif of the α/β hydrolase fold family. The 12 corresponding coding sequences were cloned in expression vectors, containing soluble N-terminal fusion proteins. The best conditions to express each protein in a soluble form were found thanks to an expression screening, using an incomplete factorial experimental design. Eleven out of the 12 proteins were expressed in a soluble form in <it>E. coli </it>and six showed esterase activity on 1-naphthyl acetate and/or propionate, as demonstrated by a zymographic method.</p> <p>Conclusion</p> <p>We were able to demonstrate that our genomic search approach was efficient to identify esterases from the genome of a <it>P. freudenreichii </it>strain, more exhaustively than classical approaches. This study highlights the interest in using the automatic search of motifs, with the manual search of homology to previously characterised enzymes as a complementary method. Only further characterisations would permit the identification of the esterases of <it>P. freudenreichii </it>involved in the lipolysis in Emmental cheese.</p

Genomic rearrangements in the aspA-dcuA locus of Propionibacterium freudenreichii are associated with aspartase activity.

Propionibacterium freudenreichii is crucial in Swiss-type cheese manufacture. Classic propionic acid fermentation yields the nutty flavor and the typical eyes. Co-metabolism of aspartate pronounces the flavor of the cheese; however, it also increases the size of the eyes, which can induce splitting and reduce the cheese quality. Aspartase (EC 4.3.1.1) catalyzes the deamination of aspartate, yielding fumarate and ammonia. The aspartase activity varies considerably among P. freudenreichii strains. Here, the correlation between aspartase activity and the locus of aspartase-encoding genes (aspA ) and dcuA encoding the C4-dicarboxylate transporter was investigated in 46 strains to facilitate strain selection for cheese culture. Low aspartase activity was correlated with a particular genomic rearrangement: low in vitro aspartase activity always occurred in strains with gene clusters aspA - dcuA where the dcuA was frameshifted, producing a stop codon or was disrupted by an ISL3-like element. The low aspartase activity could be due to the protein sequence of the aspartase or a dysfunctional DcuA. The highest values of aspartase activity were detected in strains with aspA1 - aspA2-dcuA with a DcuA sequence sharing 99.07 - 100% identity with the DcuA sequence of strain DSM 20271 T and an additional C4-dicarboxylate transporter belonging to the DcuAB family

Modelling metabolic network dynamics in a cheese bacterial community

International audienc

Metabolic modelling deciphers interactions in a cheese bacterial community

National audienc

The Complete Genome of Propionibacterium freudenreichii CIRM-BIA1T, a Hardy Actinobacterium with Food and Probiotic Applications

Background: Propionibacterium freudenreichii is essential as a ripening culture in Swiss-type cheeses and is also considered for its probiotic use [1]. This species exhibits slow growth, low nutritional requirements, and hardiness in many habitats. It belongs to the taxonomic group of dairy propionibacteria, in contrast to the cutaneous species P. acnes. The genome of the type strain, P. freudenreichii subsp. shermanii CIRM-BIA1 (CIP 103027T), was sequenced with an 11-fold coverage. Methodology/Principal Findings: The circular chromosome of 2.7 Mb of the CIRM-BIA1 strain has a GC-content of 67% and contains 22 different insertion sequences (3.5% of the genome in base pairs). Using a proteomic approach, 490 of the 2439 predicted proteins were confirmed. The annotation revealed the genetic basis for the hardiness of P. freudenreichii, as the bacterium possesses a complete enzymatic arsenal for de novo biosynthesis of aminoacids and vitamins (except panthotenate and biotin) as well as sequences involved in metabolism of various carbon sources, immunity against phages, duplicated chaperone genes and, interestingly, genes involved in the management of polyphosphate, glycogen and trehalose storage. The complete biosynthesis pathway for a bifidogenic compound is described, as well as a high number of surface proteins involved in interactions with the host and present in other probiotic bacteria. By comparative genomics, no pathogenicity factors found in P. acnes or in other pathogenic microbial species were identified in P. freudenreichii, which is consistent with the Generally Recognized As Safe and Qualified Presumption of Safety status of P. freudenreichii. Various pathways for formation of cheese flavor compounds were identified: the Wood-Werkman cycle for propionic acid formation, amino acid degradation pathways resulting in the formation of volatile branched chain fatty acids, and esterases involved in the formation of free fatty acids and esters. Conclusions/Significance: With the exception of its ability to degrade lactose, P. freudenreichii seems poorly adapted to dairy niches. This genome annotation opens up new prospects for the understanding of the P. freudenreichii probiotic activity

Bioinformatics tools as a way to select microbial strains for fermented food products

1. IntroductionFermented foods are complex biological ecosystems, harbouring diverse microbial communities which contribute to the quality of these food products. In most industrial processes, these communities are advisedly chosen as starter culture for their adaptation to: (i) the substrates to be fermented (milk, vegetable) (ii) the process (°C, O2, NaCl) and (iii) the desired overall quality of the food product in terms of texture, flavour, nutrition and health benefits. For this purpose, technological properties have been mainly assessed by a time-consuming in vitro screening. We hypothesis that the huge amount of bibliographic and microbial genomic data available in public databases would enable an in silico preselection of the strains of interest before wet laboratory screening experiments.2. ObjectivesOur aim was to provide (i) adapted bioinformatic tools to mine the diversity of microbial technological properties and metabolisms (ii) a strategy to preselect strains based on their phenotypes and on their genetic potential (sugar utilization, aroma production).3. Material and MethodsWe used a bioanalysis approach to provide insight into the presence of enzyme-encoding genes responsible for targeted technological properties. KEGG, Metacyc, NCBI and CAZY databases were queried by a search on enzyme numbers, names and sequence alignments. We developed Florilege (http://migale.jouy.inra.fr/Florilege/), a database of microbial phenotypes based on text-mining to gather microbial growth conditions.4. ResultsCombining both approaches, we set up a bioinformatic preselection of lactic acid bacteria able to degrade sugar from milk, cereal or legume based juice to develop yogurt-like products. Database queries provided a list of microbial species with genes encoding key targeted enzymes. A set of preselected anaerobic, mesophilic and thermophilic strains has been successfully screened on different milk and juice in our wet laboratory providing potential new starter strains.5. ConclusionThe developed tools and the strategy can be usefully applied to other domains like bioremediation and white biotechnology

Bioinformatics tools as a way to select microbial strains for fermented food products

1. IntroductionFermented foods are complex biological ecosystems, harbouring diverse microbial communities which contribute to the quality of these food products. In most industrial processes, these communities are advisedly chosen as starter culture for their adaptation to: (i) the substrates to be fermented (milk, vegetable) (ii) the process (°C, O2, NaCl) and (iii) the desired overall quality of the food product in terms of texture, flavour, nutrition and health benefits. For this purpose, technological properties have been mainly assessed by a time-consuming in vitro screening. We hypothesis that the huge amount of bibliographic and microbial genomic data available in public databases would enable an in silico preselection of the strains of interest before wet laboratory screening experiments.2. ObjectivesOur aim was to provide (i) adapted bioinformatic tools to mine the diversity of microbial technological properties and metabolisms (ii) a strategy to preselect strains based on their phenotypes and on their genetic potential (sugar utilization, aroma production).3. Material and MethodsWe used a bioanalysis approach to provide insight into the presence of enzyme-encoding genes responsible for targeted technological properties. KEGG, Metacyc, NCBI and CAZY databases were queried by a search on enzyme numbers, names and sequence alignments. We developed Florilege (http://migale.jouy.inra.fr/Florilege/), a database of microbial phenotypes based on text-mining to gather microbial growth conditions.4. ResultsCombining both approaches, we set up a bioinformatic preselection of lactic acid bacteria able to degrade sugar from milk, cereal or legume based juice to develop yogurt-like products. Database queries provided a list of microbial species with genes encoding key targeted enzymes. A set of preselected anaerobic, mesophilic and thermophilic strains has been successfully screened on different milk and juice in our wet laboratory providing potential new starter strains.5. ConclusionThe developed tools and the strategy can be usefully applied to other domains like bioremediation and white biotechnology

Bioinformatics tools as a way to select microbial strains for fermented food products

1. IntroductionFermented foods are complex biological ecosystems, harbouring diverse microbial communities which contribute to the quality of these food products. In most industrial processes, these communities are advisedly chosen as starter culture for their adaptation to: (i) the substrates to be fermented (milk, vegetable) (ii) the process (°C, O2, NaCl) and (iii) the desired overall quality of the food product in terms of texture, flavour, nutrition and health benefits. For this purpose, technological properties have been mainly assessed by a time-consuming in vitro screening. We hypothesis that the huge amount of bibliographic and microbial genomic data available in public databases would enable an in silico preselection of the strains of interest before wet laboratory screening experiments.2. ObjectivesOur aim was to provide (i) adapted bioinformatic tools to mine the diversity of microbial technological properties and metabolisms (ii) a strategy to preselect strains based on their phenotypes and on their genetic potential (sugar utilization, aroma production).3. Material and MethodsWe used a bioanalysis approach to provide insight into the presence of enzyme-encoding genes responsible for targeted technological properties. KEGG, Metacyc, NCBI and CAZY databases were queried by a search on enzyme numbers, names and sequence alignments. We developed Florilege (http://migale.jouy.inra.fr/Florilege/), a database of microbial phenotypes based on text-mining to gather microbial growth conditions.4. ResultsCombining both approaches, we set up a bioinformatic preselection of lactic acid bacteria able to degrade sugar from milk, cereal or legume based juice to develop yogurt-like products. Database queries provided a list of microbial species with genes encoding key targeted enzymes. A set of preselected anaerobic, mesophilic and thermophilic strains has been successfully screened on different milk and juice in our wet laboratory providing potential new starter strains.5. ConclusionThe developed tools and the strategy can be usefully applied to other domains like bioremediation and white biotechnology