Metatranscriptome analysis for insight into whole-ecosystem gene expression during spontaneous wheat and spelt sourdough fermentations

MetaPro: a scalable and reproducible data processing and analysis pipeline for metatranscriptomic investigation of microbial communities

BACKGROUND

Whole microbiome RNASeq (metatranscriptomics) has emerged as a powerful technology to functionally interrogate microbial communities. A key challenge is how best to process, analyze, and interpret these complex datasets. In a typical application, a single metatranscriptomic dataset may comprise from tens to hundreds of millions of sequence reads. These reads must first be processed and filtered for low quality and potential contaminants, before being annotated with taxonomic and functional labels and subsequently collated to generate global bacterial gene expression profiles.

RESULTS

Here, we present MetaPro, a flexible, massively scalable metatranscriptomic data analysis pipeline that is cross-platform compatible through its implementation within a Docker framework. MetaPro starts with raw sequence read input (single-end or paired-end reads) and processes them through a tiered series of filtering, assembly, and annotation steps. In addition to yielding a final list of bacterial genes and their relative expression, MetaPro delivers a taxonomic breakdown based on the consensus of complementary prediction algorithms, together with a focused breakdown of enzymes, readily visualized through the Cytoscape network visualization tool. We benchmark the performance of MetaPro against two current state-of-the-art pipelines and demonstrate improved performance and functionality.

CONCLUSIONS

MetaPro represents an effective integrated solution for the processing and analysis of metatranscriptomic datasets. Its modular architecture allows new algorithms to be deployed as they are developed, ensuring its longevity. To aid user uptake of the pipeline, MetaPro, together with an established tutorial that has been developed for educational purposes, is made freely available at https://github.com/ParkinsonLab/MetaPro . The software is freely available under the GNU general public license v3. Video Abstract.

Mechanistic Insight into Yeast Bloom in a Lactic Acid Bacteria Relaying-Community in the Start of Sourdough Microbiota Evolution

The spontaneous microbiota of wheat sourdough, often comprising one yeast species and several lactic acid bacteria (LAB) species, evolves over repeated fermentation cycles, which bakers call backslopping. The final product quality largely depends on the microbiota functions, but these fluctuate sometimes during the initial months of fermentation cycles due to microbiota evolution in which three phases of LAB relay occur. In this study, the understanding of yeast-LAB interactions in the start of the evolution of the microbiota was deepened by exploring the timing and trigger interactions when sourdough yeast entered a preestablished LAB-relaying community. Monitoring of 32 cycles of evolution of 6 batches of spontaneous microbiota in wheat sourdoughs revealed that sourdough yeasts affected the LAB community when the 2nd- or 3rd-relaying types of LAB genera emerged. In in vitro pairwise cocultures, all 12 LAB strains containing the 3 LAB-relaying types arrested the growth of a Saccharomyces cerevisiae strain, a frequently found species in sourdoughs, to various extents by sugar-related interactions. These findings suggest competition due to different affinities of each LAB and a S. cerevisiae strain for each sugar. In particular, maltose was the driver of S. cerevisiae growth in all pairwise cocultures. The functional prediction of sugar metabolism in sourdough LAB communities showed a positive correlation between maltose degradation and the yeast population. Our results suggest that maltose-related interactions are key factors that enable yeasts to enter and then settle in the LAB-relaying community during the initial part of evolution of spontaneous sourdough microbiota.

IMPORTANCE Unpredictable evolution of spontaneous sourdough microbiota sometimes prevents bakers from making special-quality products because the unstable microbiota causes the product quality to fluctuate. Elucidation of the evolutionary mechanisms of the sourdough community, comprising yeast and lactic acid bacteria (LAB), is fundamental to control fermentation performance. This study investigated the mechanisms by which sourdough yeasts entered and settled in a bacterial community in which a three-phase relay of LAB occurred. Our results showed that all three layers of LAB restricted the cohabiting yeast population by competing for the sugar sources, particularly maltose. During the initial evolution of spontaneous sourdough microbiota, yeasts tended to grow synchronously with the progression of the lactic acid bacterial relay, which was predictably associated with changes in the maltose degradation functions in the bacterial community. Further study of ≥3 species’ interactions while considering yeast diversity can uncover additional interaction mechanisms driving the initial evolution of sourdough microbiota.

Sourdough production: fermentation strategies, microbial ecology, and use of non-flour ingredients

Sourdough production is an ancient method to ferment flour from cereals for the manufacturing of baked goods. This review deals with the state-of-the-art of current fermentation strategies for sourdough production and the microbial ecology of mature sourdoughs, with a particular focus on the use of non-flour ingredients. Flour fermentation processes for sourdough production are typically carried out by heterogeneous communities of lactic acid bacteria and yeasts. Acetic acid bacteria may also occur, although their presence and role in sourdough production can be criticized. Based on the inoculum used, sourdough productions can be distinguished in fermentation processes using backslopping procedures, originating from a spontaneously fermented flour-water mixture (Type 1), starter culture-initiated fermentation processes (Type 2), and starter culture-initiated fermentation processes that are followed by backslopping (Type 3). In traditional recipes for the initiation and/or propagation of Type 1 sourdough productions, non-flour ingredients are often added to the flour-water mixture. These ingredients may be the source of an additional microbial inoculum and/or serve as (co-)substrates for fermentation. An example of the former is the addition of yoghurt; an example of the latter is the use of fruit juices. The survival of microorganisms transferred from the ingredients to the fermenting flour-water mixture depends on the competitiveness toward particular strains of the microbial species present under the harsh conditions of the sourdough ecosystem. Their survival and growth is also determined by the presence of the appropriate substrates, whether or not carried over by the ingredients added.

Deciphering the succession patterns of bacterial community and their correlations with environmental factors and flavor compounds during the fermentation of Zhejiang rosy vinegar

Zhejiang Rosy Vinegar (ZRV) is a traditional condiment in Southeast China, produced using semi-solid-state fermentation techniques under an open environment, yet little is known about the functional microbiota involved in the flavor formation of ZRV. In this study, 43 kinds of volatile flavor substances were identified by HS-SPME/GC-MS, mainly including ethyl acetate (relative content at the end of fermentation: 1104.1 mg/L), phenylethyl alcohol (417.6 mg/L) and acetoin (605.2 mg/L). The most abundant organic acid was acetic acid (59.6 g/L), which kept rising during the fermentation, followed by lactic acid (7.0 g/L), which showed a continuously downward trend. Amplicon sequencing analysis revealed that the richness and diversity of bacterial community were the highest at the beginning and then maintained decreasing during the fermentation. The predominant bacteria were scattered in Acetobacter (average relative abundance: 63.7%) and Lactobacillus (19.8%). Both sequencing and culture-dependent analysis showed Lactobacillus dominated the early stage (day 10 to 30), and Acetobacter kept highly abundant from day 40 to the end. Spearman correlation analysis displayed that the potential major groups involved in the formation of flavor compounds were Acetobacter and Lactobacillus, which were also showed strong relationships with other bacteria through co-occurrence network analysis (edges attached to Acetobacter: 61.7%; Lactobacillus: 14.0%). Moreover, structural equation model showed that the contents of ethanol, titratable acid and reducing sugar were the major environmental factors playing essential roles in influencing the succession of bacterial community and their metabolism during the fermentation. Overall, these findings illuminated the dynamic profiles of bacterial community and flavor compounds and the potential functional microbes, which were expected to help us understand the formation of flavor substances in ZRV.

Comparative Peptidomic and Metatranscriptomic Analyses Reveal Improved Gamma-Amino Butyric Acid Production Machinery in Levilactobacillus brevis Strain NPS-QW 145 Cocultured with Streptococcus thermophilus Strain ASCC1275 during Milk Fermentation

The high-gamma-amino butyric acid (GABA)-producing bacterium Levilactobacillus brevis strain NPS-QW 145, along with Streptococcus thermophilus (one of the two starter bacteria used to make yogurt for its proteolytic activity), enhances GABA production in milk. However, a mechanistic understanding of how Levilactobacillus brevis cooperates with S. thermophilus to stimulate GABA production has been lacking. Comparative peptidomic and metatranscriptomic analyses were carried out to unravel the casein and lactose utilization patterns during milk fermentation with the coculture. We found that particular peptides hydrolyzed by S. thermophilus ASCC1275 were transported and biodegraded with peptidase in Lb. brevis 145 to meet the growth needs of the latter. In addition, amino acid synthesis and metabolism in Lb. brevis 145 were activated to further support its growth. Glucose, as a result of lactose hydrolysis by S. thermophilus 1275, but not available lactose in milk, was metabolized as the main carbon source by Lb. brevis 145 for ATP production. In the stationary phase, under acidic conditions due to the accumulation of lactic acid produced by S. thermophilus 1275, the expression of genes involved in pyridoxal phosphate (coenzyme of glutamic acid decarboxylase) metabolism and glutamic acid decarboxylase (Gad) in Lb. brevis 145 was induced for GABA production.SIGNIFICANCE A huge market for GABA-rich milk as a dietary therapy for the management of hypertension is anticipated. The novelty of this work lies in applying peptide profiles supported by metatranscriptomics to elucidate (i) the pattern of casein hydrolysis by S. thermophilus 1275, (ii) the supply of peptides and glucose by S. thermophilus 1275 to Lb. brevis 145, (iii) the transportation of peptides in Lb. brevis and the degradation of peptides by this organism, which was reported to be nonproteolytic, and (iv) GABA production by Lb. brevis 145 under acidic conditions. Based on the widely reported contribution of lactic acid bacteria (LAB) and GABA to human health, the elucidation of interactions between the two groups of bacterial communities in the production of GABA-rich milk is important for promoting the development of functional dairy food and may provide new insight into the development of industrial GABA production.

Metagenomics analysis of cocoa bean fermentation microbiome identifying species diversity and putative functional capabilities

Fermentation of Theobroma cacao L. beans is the most critical stage in the production of cocoa products such as chocolates and its derivatives. There is a limited understanding of the complex response of microbial diversity during cocoa bean fermentation. The aim of the present study was to investigate microbial communities in the cocoa bean fermentation heap using a culture-independent approach to elucidate microbial diversity, structure, functional annotation and mapping unto metabolic pathways. Genomic DNA was extracted and purified from a sample of cocoa beans fermentation heap and was followed by library preparations. Sequence data was generated on Illumina Hiseq 2000 paired-end technology (Macrogen Inc). Taxonomic analysis based on genes predicted from the metagenome identified a high percentage of Bacteria (90.0%), Yeast (9%), and bacteriophages (1%) from the cocoa microbiome. Lactobacillus (20%), Gluconacetobacter (9%), Acetobacter (7%) and Gluconobacter (6%) dominated this study. The mean species diversity, measured by Shannon alpha-diversity index, was estimated at 142.81. Assignment of metagenomic sequences to SEED database categories at 97% sequence similarity identified a genetic profile characteristic of heterotrophic lactic acid fermentation of carbohydrates and aromatic amino acids. Metabolism of aromatic compounds, amino acids and their derivatives and carbohydrates occupied 0.6%, 8% and 13% respectively. Overall, these results provide insights into the cocoa microbiome, identifying fermentation processes carried out broadly by complex microbial communities and metabolic pathways encoding aromatic compounds such as phenylacetaldehyde, butanediol, acetoin, and theobromine that are required for flavour and aroma production. The results obtained will help develop targeted inoculations to produce desired chocolate flavour or targeted metabolic pathways for the selection of microbes for good aroma and flavour compounds formation.

Impact of process conditions on the microbial community dynamics and metabolite production kinetics of teff sourdough fermentations under bakery and laboratory conditions

Teff and teff sourdoughs are promising ingredients for bread production. Therefore, this study aimed at the characterization of spontaneous and flour-native starter culture-initiated teff sourdough productions under bakery and laboratory conditions. Backslopped laboratory and bakery teff sourdough productions were characterized by different lactic acid bacteria (LAB) and yeast species, but were both characterized by a pH below 4.0 after five backslopping steps. The sourdough-associated Lactobacillus sanfranciscensis was isolated for the first time from backslopped spontaneous teff sourdoughs. The autochthonous strain L. sanfranciscensis IMDO 150101 was tested as starter culture during laboratory teff sourdough fermentations. Its prevalence could be related to the process conditions applied, in particular the ambient temperature (below 30°C). Breads made with 20% teff sourdough (on flour basis) displayed interesting features compared with all-wheat-based reference breads. Teff sourdoughs were characterized as to their pH evolution, microbial community dynamics, and microbial species composition. Representative strains of the LAB species isolated from these sourdoughs, in particular L. sanfranciscensis, may be selected as starter cultures for the production of stable teff sourdoughs and flavorful breads, provided they are adapted to the environmental conditions applied.

Insights into the microbial diversity and community dynamics of Chinese traditional fermented foods from using high-throughput sequencing approaches

Chinese traditional fermented foods have a very long history dating back thousands of years and have become an indispensable part of Chinese dietary culture. A plethora of research has been conducted to unravel the composition and dynamics of microbial consortia associated with Chinese traditional fermented foods using culture-dependent as well as culture-independent methods, like different high-throughput sequencing (HTS) techniques. These HTS techniques enable us to understand the relationship between a food product and its microbes to a greater extent than ever before. Considering the importance of Chinese traditional fermented products, the objective of this paper is to review the diversity and dynamics of microbiota in Chinese traditional fermented foods revealed by HTS approaches.

Divergent functional isoforms drive niche specialisation for nutrient acquisition and use in rumen microbiome

Many microbes in complex competitive environments share genes for acquiring and utilising nutrients, questioning whether niche specialisation exists and if so, how it is maintained. We investigated the genomic signatures of niche specialisation in the rumen microbiome, a highly competitive, anaerobic environment, with limited nutrient availability determined by the biomass consumed by the host. We generated individual metagenomic libraries from 14 cows fed an ad libitum diet of grass silage and calculated functional isoform diversity for each microbial gene identified. The animal replicates were used to calculate confidence intervals to test for differences in diversity of functional isoforms between microbes that may drive niche specialisation. We identified 153 genes with significant differences in functional isoform diversity between the two most abundant bacterial genera in the rumen (Prevotella and Clostridium). We found Prevotella possesses a more diverse range of isoforms capable of degrading hemicellulose, whereas Clostridium for cellulose. Furthermore, significant differences were observed in key metabolic processes indicating that isoform diversity plays an important role in maintaining their niche specialisation. The methods presented represent a novel approach for untangling complex interactions between microorganisms in natural environments and have resulted in an expanded catalogue of gene targets central to rumen cellulosic biomass degradation.

Microbial Ecology and Process Technology of Sourdough Fermentation

From a microbiological perspective, sourdough is to be considered as a specific and stressful ecosystem, harboring yeasts and lactic acid bacteria (LAB), that is used for the production of baked goods. With respect to the metabolic impact of the sourdough microbiota, acidification (LAB), flavor formation (LAB and yeasts), and leavening (yeasts and heterofermentative LAB species) are most noticeable. Three distinct types of sourdough fermentation processes can be discerned based on the inocula applied, namely backslopped ones (type 1), those initiated with starter cultures (type 2), and those initiated with a starter culture followed by backslopping (type 3). A sourdough-characteristic LAB species is Lactobacillus sanfranciscensis. A sourdough-characteristic yeast species is Candida humilis. Although it has been suggested that the microbiota of a specific sourdough may be influenced by its geographical origin, region specificity often seems to be an artefact resulting from interpretation of the research data, as those are dependent on sampling, isolation, and identification procedures. It is however clear that sourdough-adapted microorganisms are able to withstand stress conditions encountered during their growth. Based on the technological setup, type 0 (predoughs), type I (artisan bakery firm sourdoughs), type II (industrial liquid sourdoughs), and type III sourdoughs (industrial dried sourdoughs) can be distinguished. The production of all sourdoughs, independent of their classification, depends on several intrinsic and extrinsic factors. Both the flour (type, quality status, etc.) and the process parameters (fermentation temperature, pH and pH evolution, dough yield, water activity, oxygen tension, backslopping procedure and fermentation duration, etc.) determine the dynamics and outcome of (backslopped) sourdough fermentation processes.

Exploring flavour-producing core microbiota in multispecies solid-state fermentation of traditional Chinese vinegar

Multispecies solid-state fermentation (MSSF), a natural fermentation process driven by reproducible microbiota, is an important technique to produce traditional fermented foods. Flavours, skeleton of fermented foods, was mostly produced by microbiota in food ecosystem. However, the association between microbiota and flavours and flavour-producing core microbiota are still poorly understood. Here, acetic acid fermentation (AAF) of Zhenjiang aromatic vinegar was taken as a typical case of MSSF. The structural and functional dynamics of microbiota during AAF process was determined by metagenomics and favour analyses. The dominant bacteria and fungi were identified as Acetobacter, Lactobacillus, Aspergillus, and Alternaria, respectively. Total 88 flavours including 2 sugars, 9 organic acids, 18 amino acids, and 59 volatile flavours were detected during AAF process. O2PLS-based correlation analysis between microbiota succession and flavours dynamics showed bacteria made more contribution to flavour formation than fungi. Seven genera including Acetobacter, Lactobacillus, Enhydrobacter, Lactococcus, Gluconacetobacer, Bacillus and Staphylococcus were determined as functional core microbiota for production of flavours in Zhenjiang aromatic vinegar, based on their dominance and functionality in microbial community. This study provides a perspective for bridging the gap between the phenotype and genotype of ecological system, and advances our understanding of MSSF mechanisms in Zhenjiang aromatic vinegar.

Determination of expression and activity of genes involved in starch metabolism in Lactobacillus plantarum A6 during fermentation of a cereal-based gruel

Traditional fermented gruels prepared from cereals are widely used for complementary feeding of young children in Africa and usually have a low energy density. The amylase activity of some lactic acid bacteria (LAB) helps increase the energy content of gruels through partial hydrolysis of starch, thus enabling the incorporation of more starchy material while conserving the desired semi-liquid consistency for young children. Even if this ability is mainly related to the production of alpha-amylase (E.C. 3.2.1.1), in a recent molecular screening, genes coding for enzymes involved in starch metabolism were detected in the efficient amylolytic LAB Lactobacillus plantarum A6: alpha-glucosidase (E.C. 3.2.1.20), neopullulanase (E.C. 3.2.1.135), amylopectin phosphorylase (E.C. 2.4.1.1) and maltose phosphorylase (E.C. 2.4.1.8). The objective of this study was to investigate the expression of these genes in a model of starchy fermented food made from pearl millet (Pennisetum glaucum). Transcriptional and enzymatic analyses were performed during the 18-h fermentation period. Liquefaction was mainly caused by an extracellular alpha amylase encoded by the amyA gene specific to the A6 strain among L. plantarum species and found in both Lactobacillus amylovorus and Lactobacillus manihotivorans. The second most active enzyme was neopullulanase. Other starch metabolizing enzymes were less often detected. The dynamic detection of transcripts of gene during starch fermentation in pearl millet porridge suggests that the set of genes we investigated was not expressed continuously but transiently.

Comparison of assembly algorithms for improving rate of metatranscriptomic functional annotation

BACKGROUND

Microbiome-wide gene expression profiling through high-throughput RNA sequencing ('metatranscriptomics') offers a powerful means to functionally interrogate complex microbial communities. Key to successful exploitation of these datasets is the ability to confidently match relatively short sequence reads to known bacterial transcripts. In the absence of reference genomes, such annotation efforts may be enhanced by assembling reads into longer contiguous sequences ('contigs'), prior to database search strategies. Since reads from homologous transcripts may derive from several species, represented at different abundance levels, it is not clear how well current assembly pipelines perform for metatranscriptomic datasets. Here we evaluate the performance of four currently employed assemblers including de novo transcriptome assemblers - Trinity and Oases; the metagenomic assembler - Metavelvet; and the recently developed metatranscriptomic assembler IDBA-MT.

RESULTS

We evaluated the performance of the assemblers on a previously published dataset of single-end RNA sequence reads derived from the large intestine of an inbred non-obese diabetic mouse model of type 1 diabetes. We found that Trinity performed best as judged by contigs assembled, reads assigned to contigs, and number of reads that could be annotated to a known bacterial transcript. Only 15.5% of RNA sequence reads could be annotated to a known transcript in contrast to 50.3% with Trinity assembly. Paired-end reads generated from the same mouse samples resulted in modest performance gains. A database search estimated that the assemblies are unlikely to erroneously merge multiple unrelated genes sharing a region of similarity (<2% of contigs). A simulated dataset based on ten species confirmed these findings. A more complex simulated dataset based on 72 species found that greater assembly errors were introduced than is expected by sequencing quality. Through the detailed evaluation of assembly performance, the insights provided by this study will help drive the design of future metatranscriptomic analyses.

CONCLUSION

Assembly of metatranscriptome datasets greatly improved read annotation. Of the four assemblers evaluated, Trinity provided the best performance. For more complex datasets, reads generated from transcripts sharing considerable sequence similarity can be a source of significant assembly error, suggesting a need to collate reads on the basis of common taxonomic origin prior to assembly.

Microbial ecology of sourdough fermentations: diverse or uniform?

Sourdough is a specific and stressful ecosystem inhabited by yeasts and lactic acid bacteria (LAB), mainly heterofermentative lactobacilli. On the basis of their inocula, three types of sourdough fermentation processes can be distinguished, namely backslopped ones, those initiated with starter cultures, and those initiated with a starter culture followed by backslopping. Typical sourdough LAB species are Lactobacillus fermentum, Lactobacillus paralimentarius, Lactobacillus plantarum, and Lactobacillus sanfranciscensis. Typical sourdough yeast species are Candida humilis, Kazachstania exigua, and Saccharomyces cerevisiae. Whereas region specificity is claimed in the case of artisan backslopped sourdoughs, no clear-cut relationship between a typical sourdough and its associated microbiota can be found, as this is dependent on the sampling, isolation, and identification procedures. Both simple and very complex consortia may occur. Moreover, a series of intrinsic and extrinsic factors may influence the composition of the sourdough microbiota. For instance, an influence of the flour (type, quality status, etc.) and the process parameters (temperature, pH, dough yield, backslopping practices, etc.) occurs. In this way, the presence of Lb. sanfranciscensis during sourdough fermentation depends on specific environmental and technological factors. Also, Triticum durum seems to select for obligately heterofermentative LAB species. Finally, there are indications that the sourdough LAB are of intestinal origin.

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.

Systems solutions by lactic acid bacteria: from paradigms to practice

Lactic acid bacteria are among the powerhouses of the food industry, colonize the surfaces of plants and animals, and contribute to our health and well-being. The genomic characterization of LAB has rocketed and presently over 100 complete or nearly complete genomes are available, many of which serve as scientific paradigms. Moreover, functional and comparative metagenomic studies are taking off and provide a wealth of insight in the activity of lactic acid bacteria used in a variety of applications, ranging from starters in complex fermentations to their marketing as probiotics. In this new era of high throughput analysis, biology has become big science. Hence, there is a need to systematically store the generated information, apply this in an intelligent way, and provide modalities for constructing self-learning systems that can be used for future improvements. This review addresses these systems solutions with a state of the art overview of the present paradigms that relate to the use of lactic acid bacteria in industrial applications. Moreover, an outlook is presented of the future developments that include the transition into practice as well as the use of lactic acid bacteria in synthetic biology and other next generation applications.

Genomic diversity and versatility of Lactobacillus plantarum, a natural metabolic engineer

In the past decade it has become clear that the lactic acid bacterium Lactobacillus plantarum occupies a diverse range of environmental niches and has an enormous diversity in phenotypic properties, metabolic capacity and industrial applications. In this review, we describe how genome sequencing, comparative genome hybridization and comparative genomics has provided insight into the underlying genomic diversity and versatility of L. plantarum. One of the main features appears to be genomic life-style islands consisting of numerous functional gene cassettes, in particular for carbohydrates utilization, which can be acquired, shuffled, substituted or deleted in response to niche requirements. In this sense, L. plantarum can be considered a "natural metabolic engineer".