Shotgun Metagenomics of a Water Kefir Fermentation Ecosystem Reveals a Novel Oenococcus Species

Water kefir is a fruity, sour, slightly alcoholic and carbonated beverage, which is made by fermentation of an aqueous sucrose solution in the presence of dried figs and water kefir grains. These polysaccharide grains contain lactic acid bacteria (LAB), yeasts, and sometimes bifidobacteria and/or acetic acid bacteria, which consume sucrose to produce exopolysaccharides, lactic acid, acetic acid, ethanol, and carbon dioxide. Shotgun metagenomic sequencing was used to examine the microbial species diversity present at two time points during water kefir fermentation in detail, both in the water kefir liquor and on the water kefir grains, hence representing four samples. Lactobacillus harbinensis, Lactobacillus hilgardii, Lactobacillus nagelii, Lactobacillus paracasei, and a Lactobacillus species similar to Lactobacillus hordei/mali were present in the water kefir examined, along with Bifidobacterium aquikefiri and two yeast species, namely Saccharomyces cerevisiae and Dekkera bruxellensis. In addition, evidence for a novel Oenococcus species related to Oenococcus oeni and Oenococcus kitaharae was found. Its genome was derived from the metagenome and made available under the name of Candidatus Oenococcus aquikefiri. Through functional analysis of the four metagenomic data sets, it was possible to link the production of lactic acid, acetic acid, ethanol, and carbon dioxide to subgroups of the microbial species found. In particular, the production of mannitol from fructose was linked to L. hilgardii, Candidatus O. aquikefiri, and B. aquikefiri, whereas glycerol production was associated with S. cerevisiae. Also, there were indications of cross-feeding, for instance in the case of amino acid supply. Few bacterial species could synthesize a limited number of cofactors, making them reliant on the figs or S. cerevisiae. The LAB species in turn were found to be capable of contributing to water kefir grain growth, as dextransucrase-encoding genes were attributed to L. hilgardii, L. hordei/mali, and Candidatus O. aquikefiri

Phylogenetic Analysis of a Spontaneous Cocoa Bean Fermentation Metagenome Reveals New Insights into Its Bacterial and Fungal Community Diversity

This is the first report on the phylogenetic analysis of the community diversity of a single spontaneous cocoa bean box fermentation sample through a metagenomic approach involving 454 pyrosequencing. Several sequence-based and composition-based taxonomic profiling tools were used and evaluated to avoid software-dependent results and their outcome was validated by comparison with previously obtained culture-dependent and culture-independent data. Overall, this approach revealed a wider bacterial (mainly γ-Proteobacteria) and fungal diversity than previously found. Further, the use of a combination of different classification methods, in a software-independent way, helped to understand the actual composition of the microbial ecosystem under study. In addition, bacteriophage-related sequences were found. The bacterial diversity depended partially on the methods used, as composition-based methods predicted a wider diversity than sequence-based methods, and as classification methods based solely on phylogenetic marker genes predicted a more restricted diversity compared with methods that took all reads into account. The metagenomic sequencing analysis identified Hanseniaspora uvarum, Hanseniaspora opuntiae, Saccharomyces cerevisiae, Lactobacillus fermentum, and Acetobacter pasteurianus as the prevailing species. Also, the presence of occasional members of the cocoa bean fermentation process was revealed (such as Erwinia tasmaniensis, Lactobacillus brevis, Lactobacillus casei, Lactobacillus rhamnosus, Lactococcus lactis, Leuconostoc mesenteroides, and Oenococcus oeni). Furthermore, the sequence reads associated with viral communities were of a restricted diversity, dominated by Myoviridae and Siphoviridae, and reflecting Lactobacillus as the dominant host. To conclude, an accurate overview of all members of a cocoa bean fermentation process sample was revealed, indicating the superiority of metagenomic sequencing over previously used techniques

Genome-scale metabolic modeling of Acetobacter pasteurianus 386B reveals its metabolic adaptation to cocoa fermentation conditions

Acetobacter pasteurianus 386B has been selected as a candidate functional starter culture to better control the cocoa fermentation process. Previously, its genome has been sequenced and a genome-scale metabolic model (GEM) has been reconstructed. To understand its metabolic adaptation to cocoa fermentation conditions, different flux balance analysis (FBA) simulations were performed and compared with experimental data. In particular, metabolic flux distributions were simulated for two phases that characterize the growth of A. pasteurianus 386B under cocoa fermentation conditions, predicting a switch in respiratory chain usage in between these phases. The possible influence on the resulting energy production was shown using a reduced version of the GEM. FBA simulations revealed the importance of the compartmentalization of the ethanol oxidation reactions, namely in the periplasm or in the cytoplasm, and highlighted the potential role of ethanol as a source of carbon, energy, and NADPH. Regarding the latter, the physiological function of a proton-translocating NAD(P)+ transhydrogenase was further investigated in silico. This study revealed the potential of using a GEM to simulate the metabolism of A. pasteurianus 386B, and may provide a general framework toward a better physiological understanding of functional starter cultures in food fermentation processes.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Application of comparative genomics of Acetobacter species facilitates genome-scale metabolic reconstruction of the Acetobacter ghanensis LMG 23848T and Acetobacter senegalensis 108B cocoa strains.

Acetobacter species play an import role during cocoa fermentation. However, Acetobacter ghanensis and Acetobacter senegalensis are outcompeted during fermentation of the cocoa pulp-bean mass, whereas Acetobacter pasteurianus prevails. In this paper, an in silico approach aimed at delivering some insights into the possible metabolic adaptations of A. ghanensis LMG 23848T and A. senegalensis 108B, two candidate starter culture strains for cocoa fermentation processes, by reconstructing genome-scale metabolic models (GEMs). Therefore, genome sequence data of a selection of strains of Acetobacter species were used to perform a comparative genomic analysis. Combining the predicted orthologous groups of protein-encoding genes from the Acetobacter genomes with gene-reaction rules of GEMs from two reference bacteria, namely a previously manually curated model of A. pasteurianus 386B (iAp386B454) and two manually curated models of Escherichia coli (EcoCyc and iJO1366), allowed to predict the set of reactions present in A. ghanensis LMG 23848T and A. senegalensis 108B. The predicted metabolic network was manually curated using genome re-annotation data, followed by the reconstruction of species-specific GEMs. This approach additionally revealed possible differences concerning the carbon core metabolism and redox metabolism among Acetobacter species, pointing to a hitherto unexplored metabolic diversity. More specifically, the presence or absence of reactions related to citrate catabolism and the glyoxylate cycle for assimilation of C2 compounds provided not only new insights into cocoa fermentation but also interesting guidelines for future research. In general, the A. ghanensis LMG 23848T and A. senegalensis 108B GEMs, reconstructed in a semi-automated way, provided a proof-of-concept toward accelerated formation of GEMs of candidate functional starter cultures for food fermentation processes.info:eu-repo/semantics/publishe

Amplicon-Based High-Throughput Sequencing Method Capable of Species-Level Identification of Coagulase-Negative Staphylococci in Diverse Communities

Coagulase-negative staphylococci (CNS) make up a diverse bacterial group, appearing in a myriad of ecosystems. To unravel the composition of staphylococcal communities in these microbial ecosystems, a reliable species-level identification is crucial. The present study aimed to design a primer set for high-throughput amplicon sequencing, amplifying a region of the tuf gene with enough discriminatory power to distinguish different CNS species. Based on 2566 tuf gene sequences present in the public European Nucleotide Archive database and saved as a custom tuf gene database in-house, three different primer sets were designed, which were able to amplify a specific region of the tuf gene for 36 strains of 18 different CNS species. In silico analysis revealed that species-level identification of closely related species was only reliable if a 100% identity cut-off was applied for matches between the amplicon sequence variants and the custom tuf gene database. From the three primer sets designed, one set (Tuf387/765) outperformed the two other primer sets for studying Staphylococcus-rich microbial communities using amplicon sequencing, as it resulted in no false positives and precise species-level identification. The method developed offers interesting potential for a rapid and robust analysis of complex staphylococcal communities in a variety of microbial ecosystems

SNPbox: Web-based high-throughput primer design from gene to genome. Nucleic Acids Res

SNPbox is a modular software package that automates the design of PCR primers for large-scale amplification and sequencing projects in a standardized manner resulting in high-quality PCR amplicons with a low failure rate. Here, we present the SNPbox web server a

Genome-Scale Metabolic Reconstruction of Acetobacter pasteurianus 386B, a Candidate Functional Starter Culture for Cocoa Bean Fermentation.

Acetobacter pasteurianus 386B is a candidate functional starter culture for the cocoa bean fermentation process. To allow in silico simulations of its related metabolism in response to different environmental conditions, a genome-scale metabolic model for A. pasteurianus 386B was reconstructed. This is the first genome-scale metabolic model reconstruction for a member of the genus Acetobacter. The metabolic network reconstruction process was based on extensive genome re-annotation and comparative genomics analyses. The information content related to the functional annotation of metabolic enzymes and transporters was placed in a metabolic context by exploring and curating a Pathway/Genome Database of A. pasteurianus 386B using the Pathway Tools software. Metabolic reactions and curated gene-protein-reaction associations were bundled into a genome-scale metabolic model of A. pasteurianus 386B, named iAp386B454, containing 454 genes, 322 reactions, and 296 metabolites embedded in two cellular compartments. The reconstructed model was validated by performing growth experiments in a defined medium, which revealed that lactic acid as the sole carbon source could sustain growth of this strain. Further, the reconstruction of the A. pasteurianus 386B genome-scale metabolic model revealed knowledge gaps concerning the metabolism of this strain, especially related to the biosynthesis of its cell envelope and the presence or absence of metabolite transporters.info:eu-repo/semantics/publishe