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      From Wild Strain to Domesticated Strain: The Philosophy of Microbial Diversity in Foods

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      Frontiers in Microbiology
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          Abstract

          In context with “the different and contrasting roles of microorganisms in food quality, shelf life, and safety” (Guerzoni, 2010), the knowledge on how wild strains become domesticated represents a common research priority for food microbiologists. The diversity of microbial communities and their ecological and metabolic functions have the potential for remarkable scientific, social, and economic impact. However, microbiological diversity remains largely undiscovered and the knowledge of its global distribution and temporal variability remain elusive. The biosphere is estimated to contain between 1030 and 1031 different microbial genomes; however, we likely only know a minority of them at present (Whitman et al., 1998). Sequencing surveys of amplified regions of small subunit ribosomal RNA (SSU rRNA) genes have revealed that microbial diversity is much greater than the 5,000 microbial species described using phenotypic features in Bergey's taxonomic outline (Staley, 2006), and that microbial communities are far more complex than initially thought. Hence the application of molecular phylogenetic methods to study natural microbial ecosystems has resulted in the unexpected discovery of many evolutionary lineages. In addition, the recent surge of research in molecular microbial ecology produced compelling evidence for the existence of many novel types of microorganisms in the environment – both regarding abundance and diversity – that dwarf those of the comparatively few microorganisms amenable to laboratory cultivation. Collectively, the genomes of the total microbiota found in nature, termed the metagenome (Sebat et al., 2003; Handelsman, 2004), contain vastly more genetic information than is contained in the culturable subset. Comparative genomics, gaining a better understanding of how species have evolved, has shown the power to determine the function of genes and non-coding regions of the genome. The comparative genomics of the lactic acid bacteria reported by Makarova et al.  (2006), for instance, demonstrated the phylogenetic and functional diversity of these bacteria. The reconstruction of ancestral gene sets revealed a combination of gene loss and gain during coevolution of lactic acid bacteria with animals and the foods they consumed. The study proposed that the origin of Lactobacillales involved extensive loss of ancestral genes (600–1200 genes) during their transition to life in a nutritionally rich medium, which allowed a reduction in catabolic capacity and an increased stress resistance. A powerful approach for studying microbial diversity in a complex environment such as food is the direct cloning of DNA from environmental samples. Genomic fragments that are >100-kb long can be obtained, and they provide functional and taxonomic information about the organisms, which they were derived from. Such metagenomic libraries have been used to identify microorganisms or enzymes that are responsible for significant processes. Functional analysis has identified novel antibiotics, degradative enzymes, bioactive compounds, etc. (Henne et al., 2000). Metabolomics that focuses on high-throughput characterization of small molecule metabolites in biological matrices has also great relevance to food science and technology as it is suitable to identify and highlight the microbial biodiversity in food systems not only at the level of different species but also among strains. The analysis of a microorganism in different environments and the quantification of metabolic fluxes can help to better understand its role in food and also optimize starter strain performance. In fact the evaluation of strain diversity provides a great chance to increase the knowledge of metabolic functions and regulation and to speed up the process of targeted strain improvement. Phenotypic investigations enable us to compare the different strains with similar overall metabolic behaviors and to select a certain strain as most promising for further targeted optimization (Wittmann and Heinzle, 2002). Moreover, the microbial activity impacts on the composition and nutritional status, which can be valorized by the introduction of specific health beneficial attributes. Despite the profound differences in the microbial consortia involved in the fermentation of different foods there is a striking similarity in the health attributes that can be delivered along the chain from fermented food to gut microbiota through three encompassing phases: microbial ecosystem, health impacting molecules, and the possibility to modulate the gut ecosystem (Van Hylckama Vlieg et al., 2011). In contrast to other habitats, foods are generally characterized by a not relevant number of microbial species. The factors affecting this peculiar characteristic are multiple and depend on the origin of raw materials and the processes used to stabilize the foods and to improve their sensorial and heath quality. Microorganisms living in foods are constantly exposed to fluctuating environmental conditions and many of these conditions are potentially detrimental and negatively affect the physiological state and growth rate of resident microorganisms. Nevertheless, their multiple regulatory networks of stress response systems allow them to withstand harsh conditions and sudden changes in environmental conditions (Van de Guchte et al., 2002). Hence the complex network of such responses, involving several metabolic activities, can reflect upon the composition and organoleptic properties of the growth medium. Even if autochthonous bacteria are adapted and competitive, the food system must be considered as a stressful environment for them. Moreover, mutations may favor generation of strain variants that are better adapted to survive under these stress conditions. In addition, DNA instability might result in a so-called mutator phenotype, where sharply elevated spontaneous mutation rates (transiently) enhance a strain's ability to adapt to radical changes in the environment (Machielsen et al., 2010). So the species present in a food are always intrinsically differentiated into many populations of strains belonging to the same species. Among these strains and species environment and stress parameters highlight their biodiversity, from strain to strain. Many microorganisms involved in food processing are considered “domesticated”; the best known case is that of Saccharomyces cerevisiae, which is predominantly found in association with anthropogenic processes, particularly the production of bread, beer, and fermented beverages. To date, S. cerevisiae includes both wild and domesticated forma species, where the domestication event that resulted in grape wine yeasts likely occurred approximately 2,700 years ago (Mortimer and Polsinelli, 1999; Fay and Benavides, 2005). The wine strains of S. cerevisiae are highly diverse; populations fermenting grape are usually polyclonic and the clones can differ significantly in enological performance and genotype. The extent of genetic differences ranges from single-nucleotide substitutions to whole-genome duplication (Sipiczki, 2011). Similar genotypic diversity can be expected in other microorganisms associated with food habitats. For instance, phylogenetic analyses, comparisons of gene content across groups, and reconstruction of ancestral gene sets indicate a combination of extensive gene loss and key gene acquisition events via horizontal gene transfer during the coevolution of lactic acid bacteria and their habitats (Makarova et al., 2006). This coevolution is particularly evident in Oenococcus oeni and Lactobacillus sanfranciscensis, both of which can be considered highly specialized microorganisms because they uniquely occupy very narrow ecological niches: wine and sourdough, respectively. O. oeni plays an important role in the elaboration of wine, where it is often added as a starter culture to carry out the malolactic conversion. While the taxonomic structure of this species was believed to be quite homogeneous, recently, however, multilocus sequence typing (MLST) of strains revealed a high level of allelic diversity in O. oeni resulting in a panmictic population structure where lines of clonal descent are difficult to define (de Las Rivas et al., 2004). Panmictic populations are often characterized by high levels of horizontal transfer and recombination among strains. The hypermutable status in the genus, due to the absence of the mismatch repair genes mutS and mutL results in the accumulation of spontaneous errors in DNA replication and in facilitating the generation of isolates with beneficial mutations, resulting in increased fitness for the environment (Prunier and Leclercq, 2005; Bon et al., 2009). It is likely that this factor contributed to the unique adaptation of O. oeni to acidic and alcoholic environments that made it an ideal organism for the malolactic fermentation during the production of wine. Lactobacillus sanfranciscensis represents a good example of specialized adaptation to dough environment, since it preferentially ferments the maltose (the main sugar of the dough) as an energy source and uses fructose (present in the flour, too) as an additional electron acceptor in order to gain an extra mole of ATP via acetate kinase thereby improving its growth rate and competition. A new pathway proposed by Ganesan et al. (2006) and Serrazanetti et al. (2011) to convert leucine to 2-metylbutanoic acid, maybe useful in the production and use of intermediates and cofactors resulting in energy (3 mol ATP) and reducing equivalents. This novel pathway may contribute to the microorganisms’ survival during cellular stress and limitation of carbon source. Taken together, it appears that selective pressure from many environmental parameters and processing conditions during time rather than the geographical area have driven the domestication process leading to specialized strains in species with a high genetic diversity. It appears therefore, that genetic engineering, directed evolution or even the creation of entirely synthetic genomes could serve to overcome and fast-forward the series of mutagenic events that is usually driven by the environment to create biodiversity. This approach of reaching “maximum utility based on a minimum of knowledge” appears to be the new paradigm of applied sciences reaffirming Jacques Monod's statement that “the first scientific postulate is the objectivity of nature. Nature does not have any intention or goal.”

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          Most cited references17

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          Metagenomics: application of genomics to uncultured microorganisms.

          Metagenomics (also referred to as environmental and community genomics) is the genomic analysis of microorganisms by direct extraction and cloning of DNA from an assemblage of microorganisms. The development of metagenomics stemmed from the ineluctable evidence that as-yet-uncultured microorganisms represent the vast majority of organisms in most environments on earth. This evidence was derived from analyses of 16S rRNA gene sequences amplified directly from the environment, an approach that avoided the bias imposed by culturing and led to the discovery of vast new lineages of microbial life. Although the portrait of the microbial world was revolutionized by analysis of 16S rRNA genes, such studies yielded only a phylogenetic description of community membership, providing little insight into the genetics, physiology, and biochemistry of the members. Metagenomics provides a second tier of technical innovation that facilitates study of the physiology and ecology of environmental microorganisms. Novel genes and gene products discovered through metagenomics include the first bacteriorhodopsin of bacterial origin; novel small molecules with antimicrobial activity; and new members of families of known proteins, such as an Na(+)(Li(+))/H(+) antiporter, RecA, DNA polymerase, and antibiotic resistance determinants. Reassembly of multiple genomes has provided insight into energy and nutrient cycling within the community, genome structure, gene function, population genetics and microheterogeneity, and lateral gene transfer among members of an uncultured community. The application of metagenomic sequence information will facilitate the design of better culturing strategies to link genomic analysis with pure culture studies.
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            Evidence for Domesticated and Wild Populations of Saccharomyces cerevisiae

            Introduction Sensu strictu species of the genus Saccharomyces, as their scientific name implies, are yeast specialized for growth on sugar. In comparison to other yeasts, Saccharomyces favor aerobic fermentation over respiration in the presence of high concentrations of sugar [1]. Fermentation results in the production of ethanol and a competitive advantage, as these yeasts are tolerant to high concentrations of ethanol [2]. One of these species, S. cerevisiae, has served as one of the best model systems for understanding the eukaryotic cell and has served as the dominant species for the production of beer, bread, and wine [3]. However, it is worth noting that strains of S. bayanus are sometimes used for wine production and strains of S. pastorianus, hybrids between S. cerevisiae and S. bayanus, are used to brew lagers [4]. Since the discovery of yeast as the cause of fermentation [5], numerous strains of S. cerevisiae have been isolated, the majority of which have been found associated with the production of alcoholic beverages [6–9]. In many instances, the strains are clearly specialized for use in the lab [10] and the production of wine [11], beer [12], and bread [13]. This has lead to the common view that S. cerevisiae is a domesticated species that has continuously evolved in association with the production of alcoholic beverages [3,6,14]. Under this model, the occasional strains of S. cerevisiae found in nature are thought to be migrants from human-associated fermentations. The first use of S. cerevisiae is likely to have been for the production of wine, rather then bread or beer [3,15]. S. cerevisiae has been associated with winemaking since 3150 BC, based on extraction of DNA from ancient wine containers [16], and the earliest evidence for winemaking is to 7000 BC from the molecular analysis of pottery jars found in China [17]. The idea that S. cerevisiae was first used to produce wine rather than beer or bread is further supported by the fact that the production of wine requires no inoculum of yeast [7]. In addition, strains associated with whisky, ale, and bakeries show amplified fragment length polymorphism (AFLP) profiles similar to various wine strains [18]. To examine the relationship between vineyard and non-vineyard strains of S. cerevisiae and to understand their evolutionary origin, we have surveyed DNA sequence variation in 81 strains isolated from geographically and ecologically diverse sources (Table 1). These include 60 strains associated with human fermentations, predominantly from vineyards, and 19 strains not associated with human fermentations, predominantly from immunocompromised patients and tree exudates. Table 1 Strains Studied and Their Source NA, not available; seg., segregant. Table 1 Continued Results/ Discussion DNA sequence variation was examined in 81 yeast strains at five unlinked loci (see Materials and Methods). A total of 184 polymorphic sites were found. Figure 1 shows all of the variable sites along with a neighbor-joining tree constructed from these sites. There are two immediately striking features of the data. First, there are high levels of linkage disequilibrium between sites found in unlinked genes. This linkage disequilibrium cannot be explained by a lack of recombination because the four gamete test [19] shows evidence of recombination both within and between loci. The high level of linkage disequilibrium is most likely caused by population subdivision and suggests that the data from these five genes provide a genomic view of population differentiation among these strains. Second, there are significant levels of population differentiation based on the source from which the samples were isolated (see Materials and Methods). A number of strains are worth noting. Y9 is very closely related to the saké strains and was obtained from Indonesian ragi, or yeast cake, which like saké is made by fermenting koji, a mixture of rice and the mold Aspergillus oryzae [20]. Y3 and Y12 were isolated from African palm wine, made from fermenting sap of the oil palm, Elaeis guineensis. Y5 was isolated from African bili wine. Figure 1 A Neighbor-Joining Tree Shows Differentiation among Yeast Strains Isolated from Different Sources The tree was constructed from polymorphic sites found at five unlinked loci and was rooted using S. paradoxus. Strains are colored according to the substrates from which they were isolated. The right side shows color-coded polymorphism data with minor alleles shown in black, major alleles shown in white, missing data shown in light gray, and heterozygous sites shown in orange. If strains of S. cerevisiae that are not associated with human fermentations have escaped their manmade environments, their progenitors should be closely related to strains isolated from human fermentations. Two aspects of the data indicate this is not the case. First, the oldest lineages at the root of the tree, that are most similar to S. paradoxus, were isolated from tree exudates in North America and Africa, or from immunocompromised patients. Although one of the clinical samples is most closely related to vineyard strains, the majority of clinical isolates are not closely related to strains obtained from human-associated fermentations. Second, strains from grape wine and saké wine production contain significantly less variation, as measured by the average number of pairwise differences between strains [21], than is found in natural and clinical isolates, which contain just as much variation as is found in the total sample (Table 2). However, diversity in strains associated with human fermentations other than grape and saké wine production is not reduced compared to the clinical and natural isolates. The four strains associated with fermentations, three of which were isolated from traditional African wines, show the greatest diversity and represent some of the oldest lineages. This raises the possibility that S. cerevisiae was domesticated in Africa and that most vineyard and saké strains were derived from a domesticated African strain. If so, one would expect clinical and natural isolates to be more closely related to strains isolated from vineyards, which have a cosmopolitan distribution compared to strains from traditional African wine. Clinical and natural isolates, however, show no obvious relationship to strains associated with manmade fermentations. Table 2 Diversity among Strains aOnly strains without missing data are used. bπ is the average number of pairwise differences between strains, per basepair. The standard deviation is shown in parentheses. Although the genealogical relationships among strains of S. cerevisiae show that the species as a whole is not domesticated, the data do support the hypothesis that some strains are domesticated. Based on the low levels of diversity within vineyard and saké strains and the clear separation of these two groups, we propose two domestication events, one for yeast used to produce grape wine and one for yeast used to produce rice wine. When might these events have occurred? Domestication would have occurred after the divergence between the vineyard and saké strains but before differentiation among the vineyard and among the saké strains. These two time points can be roughly estimated by the average number of differences per synonymous site between the saké and vineyard strains, 1.28 × 10−2, and the average number of differences among the vineyard, 2.92 × 10−3, and among the saké strains, 4.06 × 10−3, respectively (see Materials and Methods). Assuming a point mutation rate of 1.84 × 10−10 per base pair (bp) per generation and 2,920 generations per year, the estimate for the divergence time between the two groups is approximately 11,900 years ago, and within the vineyard group and saké group is approximately 2,700 and approximately 3,800 years ago, respectively (see Materials and Methods). These dates could easily be an order of magnitude older if the number of generations per year is one tenth that obtained assuming an exponential growth rate. Interestingly, the time period is consistent with the earliest archeological evidence for winemaking, approximately 9,000 years ago [17]. It should be noted that proof that these strains are domesticated requires evidence that they have acquired characteristics advantageous to humans through human activity, whether intentional or not. The alternative hypothesis to domestication is that initial fermentations selected those natural isolates most amenable to alcoholic beverage production and that these initial isolates have been used by humans ever since. The source population for both the saké and grape wine strains is not clear, but is likely similar to the source population for the clinical strains. Insects, particularly fruit flies, present one possibility [22,23]. Numerous strains of S. cerevisiae and S. paradoxus have been isolated from oak tree exudates in North America [24], and tree exudates are often visited by insects [22]. Three of these oak tree isolates were included in our study and are among the most diverse of the strains (Figure 1). Given that S. paradoxus is most often found in association with tree exudates from both Europe [25,26] and North America [24], strains of S. cerevisiae isolated from tree exudates may be truly “wild” yeast. Whether the yeast isolated from African palm wine is domesticated remains an open question, although it is worth noting that African palm wine is made by collecting sap tapped from oil palm trees and fermentation occurs naturally without the addition of yeast. Materials and Methods Strains were obtained from a number of individuals and stock centers. B1–B6 were obtained from B. Dunn; I14 from J. Fay; CDB and PR from Red Star, Berkeley, California, United States; K1–K15 from N. Goto-Yamamoto and the NODAI culture collection; M1–M34 from R. Mortimer; SB from Whole Foods, Berkeley, California, United States; UC1–UC10 from the University of California, Davis stock center; Y1–Y12 from C. Kurtzman and the ARS culture collection; YJM145–YJM1129 from J. McCusker; and YPS163–YPS1009 were from the collection of P. Sniegowski. Five genes, CCA1, CYT1, MLS1, PDR10, and ZDS2, and their promoters were sequenced in 81 strains (see Table 1). These genes were randomly chosen from all divergently transcribed intergenic sequences upstream of functionally annotated genes with clear orthologs in S. paradoxus. The sequenced regions include 3,671 bp of coding sequence and 3,561 bp of noncoding sequence. For each gene, both strands of purified PCR products were sequenced using Big Dye (Perkin Elmer, Boston, Massachusetts, United States) termination reactions. Sequence variation was identified using phred, phrap, and consed [27]. For construction of the neighbor-joining tree, a single allele was used from strains with heterozygous sites. The allele was randomly chosen from the two haplotypes inferred by PHASE [28]. Sequence data were analyzed using DNASP [29]. Population subdivision was tested by a permutations test according to the source categories from which each strain was obtained (Table 1). The average time since divergence of two strains was obtained by k = 2μt, where k is the substitution rate, μ is the mutation rate per bp and t is the time in generations. The mutation rate has been estimated at CAN1 and SUP3 at 2.25 × 10−10 per base pair per generation [30]. Given that 82% of spontaneous mutations are single base substitutions [31], we estimate the point mutation rate is 1.84 × 10−10 per bp per generation. S. cerevisiae can reproduce in 90 min, or 16 generations per day. However, even under optimal laboratory conditions the number of generations over a 24-h period is typically much less. To obtain divergence time in years rather than generations, we assumed S. cerevisiae can go through a maximum of eight generations per day or 2,920 generations per year. Supporting Information Accession Numbers The sequences of the genes CCA1, CYT1, MLS1, PDR10, and ZDS2 that are discussed in this paper have been deposited into GenBank (http://www.ncbi.nlm.nih.gov/Genbank/) as accession numbers AY942206–AY942556.
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              Stress responses in lactic acid bacteria.

              Lactic acid bacteria (LAB) constitute a heterogeneous group of bacteria that are traditionally used to produce fermented foods. The industrialization of food bio-transformations increased the economical importance of LAB, as they play a crucial role in the development of the organoleptique and hygienic quality of fermented products. Therefore, the reliability of starter strains in terms of quality and functional properties (important for the development of aroma and texture), but also in terms of growth performance and robustness has become essential. These strains should resist to adverse conditions encountered in industrial processes, for example during starter handling and storage (freeze-drying, freezing or spray-drying). The development of new applications such as life vaccines and probiotic foods reinforces the need for robust LAB since they may have to survive in the digestive tract, resist the intestinal flora, maybe colonize the digestive or uro-genital mucosa and express specific functions under conditions that are unfavorable to growth (for example, during stationary phase or storage). Also in nature, the ability to quickly respond to stress is essential for survival and it is now well established that LAB, like other bacteria, evolved defense mechanisms against stress that allow them to withstand harsh conditions and sudden environmental changes. While genes implicated in stress responses are numerous, in LAB the levels of characterization of their actual role and regulation differ widely between species. The functional conservation of several stress proteins (for example, HS proteins, Csp, etc) and of some of their regulators (for example, HrcA, CtsR) renders even more striking the differences that exist between LAB and the classical model micro-organisms. Among the differences observed between LAB species and B. subtilis, one of the most striking is the absence of a sigma B orthologue in L. lactis ssp. lactis as well as in at least two streptococci and probably E. faecalis. The overview of LAB stress responses also reveals common aspects of stress responses. As in other bacteria, adaptive responses appear to be a usual mode of stress protection in LAB. However, the cross-protection to other stress often induced by the expression of a given adaptive response, appears to vary between species. This observation suggests that the molecular bases of adaptive responses are, at least in part, species (or even subspecies) specific. A better understanding of the mechanisms of stress resistance should allow to understand the bases of the adaptive responses and cross protection, and to rationalize their exploitation to prepare LAB to industrial processes. Moreover, the identification of crucial stress related genes will reveal targets i) for specific manipulation (to promote or limit growth), ii) to develop tools to screen for tolerant or sensitive strains and iii) to evaluate the fitness and level of adaptation of a culture. In this context, future genome and transcriptome analyses will undoubtedly complement the proteome and genetic information available today, and shed a new light on the perception of, and the response to, stress by lactic acid bacteria.
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                Author and article information

                Journal
                Front Microbiol
                Front. Microbio.
                Frontiers in Microbiology
                Frontiers Research Foundation
                1664-302X
                17 August 2011
                2011
                : 2
                : 169
                Affiliations
                [1] 1simpleFood Science Department, University of Teramo Teramo, Italy
                Author notes
                *Correspondence: gsuzzi@ 123456unite.it

                This article was submitted to Frontiers in Food Microbiology, a specialty of Frontiers in Microbiology.

                Article
                10.3389/fmicb.2011.00169
                3157009
                21887153
                fcac1598-9c1d-43fa-a6b7-8e581e61064d
                Copyright © 2011 Suzzi.

                This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.

                History
                : 07 June 2011
                : 26 July 2011
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 19, Pages: 3, Words: 2243
                Categories
                Microbiology
                Specialty Grand Challenge

                Microbiology & Virology
                Microbiology & Virology

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