• Open Access

Lactic acid bacteria: life after genomics

Authors

  • Michiel Kleerebezem,

    1. Laboratory of Microbiology, Wageningen University, Wageningen, the Netherlands
    2. NIZO food research, Ede, the Netherlands
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  • Willem M. de Vos

    1. Laboratory of Microbiology, Wageningen University, Wageningen, the Netherlands
    2. Department of Veterinary Biosciences and Department of Bacteriology & Immunology, Helsinki University, Helsinki, Finland
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As powerhouses for the food industry, lactic acid bacteria continue to be the focus of considerable interest. While traditionally applied in industrial dairy and other food fermentations, lactic acid bacteria are now used in a great variety of drinks, yoghurts or other products that are marketed with specific health benefits. This has been the largest growth segment in the functional foods market with an annual sales value of over a billion Euro. The lactic acid bacteria in these products include notably species of Lactobacillus and Bifidobacterium that are marketed as probiotics (Saxelin et al., 2005). Hence it is no surprise that these species are actively studied and often considered together as will be detailed below. The attention for these groups of lactic acid bacteria represents a marked shift in the attention from the traditional focus on strains of notably Lactococcus and Streptococcus spp. that are used as starters in important milk fermentations, resulting in commodity products, such as cheese and yoghurt. However, Lactococcus lactis can still be seen as a model for lactic acid bacteria as will be discussed below. All these genera belong to the Gram-positive bacteria and produce lactic acid from sugars. Bifidobacteria belong to the Actinobacteria and contain genomic DNA with a high G+C content, while the other lactic acid bacteria are phylogenetically closely related and belong to the Firmicutes that are characterized by genomes with a low G + C content. It is of more than anecdotal importance to note here that the bacteria belonging to the Actinobacteria and Firmicutes make up the vast majority of microbial taxa present in our intestinal tract (Zoetendal et al., 2008). Both Lactobacillus and Bifidobacterium spp. are early colonizers and belong to our microbes inside where – in adult life – they are notably present in the upper and lower intestinal tract respectively (Kleerebezem and Vaughan, 2009). This explains why the growing interest in these different groups of lactic acid bacteria and their application in health-promoting products is paralleled by attention for their activity and diversity in the human body. The impact of consumed lactobacilli has recently been established in pioneering studies addressing the human response in the upper intestinal tract (van Baarlen et al., 2009; 2011). The results show specific and strain-dependent transcriptional host responses that are dependent on the physiological state of the consumed cells. In this way, the provide support for the functionality of probiotics, which are often defined as microbial cultures providing when consumed in adequate amounts a health benefit to the host (Saxelin et al., 2005).

In line with the industrial importance and scientific interest, this issue of Microbial Biotechnology addresses various aspects of Lactobacillus and Bifidobacterium spp. and the genetic model L. lactis. All contributions capitalize in different forms on the post-genomic progress that set off a revolution in the understanding of the lactic acid bacteria (De Vos, 2001). A decade ago, the 2 Mb genome was characterized of a plasmid-free L. lactis strain (Bolotin et al., 2001) and the first complete genome sequence of a Lactobacillus strain was reported with the 3.3-Mb-large genome of Lactobacillus plantarum (Kleerebezem et al., 2003). Subsequently, a great number of industrial and model strains have been characterized at the genome level. These include representatives of the over 100 Lactobacillus spp., as well as different strains belonging to the same species. However, many genomes have only been partially sequenced and have some gaps as the genomes are notably highly repetitive because of the presence of IS elements, repeated domains or other unusual sequences. These include several intestinal isolates that recently have been reported as part of the Human Microbiome Jumpstart Initiative (Nelson et al., 2010). In a review article, Ravi Kant and colleagues focus on the 20 completely genomes of Lactobacillus spp. and describe their comparative bioinformatic analysis (Kant et al., 2011). These genomes varied in size between 1.8 and 3.3 Mb, reflecting the large variation of niches occupied by these lactic acid bacteria. The deduced Lactobacillus pangenome of over 14 000 protein-encoding genes was predicted together with the Lactobacillus Core Genome that includes several hundreds of orthologous genes. This detailed analysis provides a platform for functional and comparative genomics of presently known lactobacilli as well as future analysis of new Lactobacillus genomes.

Knowledge of a genome sequence does not directly provide insight in the activity or behaviour of an organism. The relations between the genomic blueprint and the apparent functional properties can be unravelled using functional genomic approaches that target different molecular levels, i.e. transcriptomics, proteomics and metabolomics. Transcriptome platforms have been developed for several lactic acid bacteria and bifidobacteria and have accelerated gene-function annotation and enabled holistic approaches towards adaptive behaviour under different environmental conditions. Transcriptome analyses under multiple conditions allow for data driven reconstruction of regulatory networks as is illustrated by Michiel Wels and co-workers, who reconstructed the gene regulatory networks and cognate cis acting elements that control gene expression in L. plantarum (Wels et al., 2011). Use was made of a large amount of transcriptional data sets that were collected under different growth conditions. Over 40 sets of co-regulated genes were discovered enhancing the insight in the metabolic response of L. plantarum that has developed into one of probiotic paradigms. Validation of these and other gene-regulation networks by mutation analysis of the regulator involved is often required to further specify their regulons and mode of control. This approach is taken by Ida Rudd and colleagues who targeted the cggR gene encoding the central glycolytic gene regulator that is conserved in lactobacilli and several other Gram-positive bacteria (Rud et al., 2011). The impact of this mutation on the transcriptome was studied in two strains of L. plantarum (WCFS1 and NC8), showing that the role of CggR in glycolysis control is rather strain-specific. This notion underpins earlier findings in L. lactis that identified an impressive degree of diversity in the environmental control of gene expression among individual strains (Bachmann et al., 2009).

For the lactic acid bacteria that exert their relevant health-promoting function in the intestine of the consumer, functional genomics approaches are faced with the relative inaccessibility and physicochemical complexity of this niche. Nevertheless, recent in situ transcriptome studies succeeded to elucidate the convergence of metabolic and cell-wall architecture adaptations elicited in L. plantarum when it resides in the mouse and human gastrointestinal tract (Marco et al., 2010). The observed adaptations of the cell-wall architecture of this microbe during its transit through the intestine may have a profound impact on host responses since the extracellular properties of bacteria are commonly considered to be of great importance in molecular communication with specific host cells (Kleerebezem et al., 2010). This is clearly illustrated by the differential responses measured in human immature dendritic cells (iDC) upon their interaction with wild-type and mutant lactobacilli that harbour mutations in genes encoding specific cell surface molecules or their biosynthetic pathway (Grangette et al., 2005; Konstantinov et al., 2008; Meijerink et al., 2010). Inversely, cell-surface properties and architecture may influence the impact of host-derived antimicrobial factors on bacterial physiology. Many lactic acid bacteria produce extracellular polysaccharides and these have been studied extensively in lactic acid bacteria, notably with attention for their biosynthesis, structure and function, and engineering (Van Kranenburg et al., 1999). The importance of these molecules in host–microbe interactions is evidenced by the work presented by Sarah Lebeer and colleagues, showing that the extracellular polysaccharides provide a surface layer that protects Lactobacillus rhamnosus against the inactivating capacities of human innate immunity activity (Lebeer et al., 2011). This explains the observation that a mutant defective in the production of extracellular polysaccharides shows much less survival than the wild-type L. rhamnosus GG. Moreover, it was observed that the production of extracellular polysaccharides is induced by innate defence molecules. Lactobacillus rhamnosus GG is among the most widely used probiotic strains (Saxelin et al., 2005) and known to carry a genomic island coding for the production of extracellular polysaccharides (Kankainen et al., 2009). The now reported observations provide a molecular basis for understanding the dynamic role of extracellular polysaccharides produced by an important probiotic strain in the human host that at the one hand provides protection and at the other hand prevents other surface molecules to be exposed.

A variety of effective genetic engineering systems for lactic acid bacteria have been developed during the past decades (De Vos, 1999; 2001). However, this toolbox is constantly expanded by novel cloning and expression vectors with specific and attractive features as is exemplified by the novel gene expression tools for lactobacilli presented by Duong and colleagues (2011). They used a transcriptome-based approach to identify strongly regulated promoters and control elements in L. acidophilus and developed these into versatile inducible and strong constitutive expression vectors by using the broad-host-range pWV01 replicon (De Vos, 1987). Their functionality and further application potential was exemplified by the controlled overproduction of the oxalate degradation pathway into various intestinal lactobacilli. This is of great interest as lactic acid bacteria that degrade oxalate have potential as candidate biotherapeutics for the treatment of human oxalate-related disorders. Another relevant group of biotherapeutics is formed by several of the lantibiotics produced by lactic acid bacteria. Its paradigm is nisin A, a 34-residue peptide produced by L. lactis that is both an antimicrobial targeting a wide range of Gram-positive bacteria and an auto-inducing signal molecule (Kleerebezem et al., 1997). Hence it is produced in a density-dependent way by some strains of L. lactis. There are wide applications in the food industry both for nisin A and for nisin Z, a naturally occurring variant differing from nisin A in a single residue that affects greatly its solubility and activity (De Vos et al., 1993). Moreover, a variety of engineered nisin derivatives have been generated following the first protein-engineering study addressing its structure–function relation (Kuipers et al., 1992). However, there is a need for improved derivatives, notably those that have an increased level and spectrum of bioactivity. This has been addressed in the study by Claire Piper and co-workers, who generated isogenic L. lactis strains producing the naturally occurring nisin A, Z, Q and F (Piper et al., 2011). This was realized by using as a host the L. lactis strain NZ9800 carrying a deletion in the structural gene for nisin A (Kuipers et al., 1993). Both producing strains and the purified peptides were tested – the latter as to eliminate any confounding effect of the auto-inducing capacity of the nisin derivatives that is known to vary (Kleerebezem et al., 1997). Following analysis of a wide range of clinically relevant indicator bacteria, it was found that nisin F was the most active antimicrobial against multidrug-resistant Staphylococcus aureus strains. Nisin F showed minimal inhibitory concentrations of some staphylococci of as low as 1.3 µg ml−1. It differs from nisin A in the substitution His27Asn (like in nisin Z) and Ile30Val; hence, the antistaphylococcal activity resides in the C-terminal part of the molecule and this knowledge may form the basis for new biotherapeutic use of nisin derivatives.

As is evident from the work summarized above, L. lactis is still used as a model for lactic acid bacteria. While its genome was the first of the lactic acid bacteria to be characterized (Bolotin et al., 2001) its comparative genomics lags behind that of lactobacilli that are much more diverse. In fact, only three subspecies of L. lactis are known (ssp. lactis, cremoris and hordniae) and in the study by Roland Siezen and co-workers, a series of 39 strains from dairy and plant origin was compared using comparative genome hybridization (CGH) and extensive functional analysis (Siezen et al., 2011). The use of CGH in differentiating L. plantarum strains has been described more than 5 years ago (Molenaar et al., 2005) and has shown considerable power in gene–trait matching searches for probiotic properties as discussed above (Pretzer et al., 2005; Meijerink et al., 2010). While it is known that lactococci have a multitude of plasmids that code for industrially relevant properties, the CGH analysis of L. lactis strains extends this now to its genomic traits and illustrates the flexibility of the lactococcal genomes. A considerable variation was observed in the degradation of plant-derived polysaccharides, such as various α-galactosides, arabinose and xylan, and galacturonate. Moreover, the production of extracellular polysaccharides, defence systems (including nisin production) and stress response systems were found to be variable in the studied strains. This is of practical relevance as transfer of those properties to industrial strains by known and efficient genomic conjugation systems may extend their substrate use. Transfer of the 70 kb sucrose-nisin conjugative transposons has allowed new starters to be developed that are industrially used as non-genetic modification is involved (Rauch et al., 1994). Similarly, a 51 kb conjugal transposon that codes for the use of α-galactosides has recently been discovered in a specific plant isolate (Machielsen et al., 2011). The presented CGH shows the presence of α-galactosides transposon-like structures in various other strains, allowing an extended range of potentially donor strains.

Bifidobacteria are among the first intestinal colonizers in human life, explaining the great interest in their function, diagnostics and development as probiotic bacteria. The latter relates to the potential health-promoting effects that can be ascribed to Bifidobacteria (Boesten and De Vos, 2008). Moreover, the activity of Bifidobacteria can be modulated by the consumption of specific oligo- and polysaccharides. This reflects the natural function of Bifidobacteria that predominantly reside in the colon where they are involved in the degradation of plant or host-derived sugars. Hence, analysis of the sugar degradation capacity is a recurrent theme in Bifidobacteria research that has been facilitated by genomic characterization of some species that all have small genomes with a size of around 2 Mb (Ventura et al., 2009). The genome of Bifidobacterium breve UCC2003 has recently been completed and served as a basis for molecular studies on the metabolism of the plant-derived galactan, a galactose-containing polysaccharide, as reported by O'Connell Motherway and colleagues (2011). They focused on the B. breve gal locus and showed this to encode the complete galactan degradation pathway and included genes for an extracellular endogalactanase, an ABC transporter and a β-galactosidase. Moreover, the control of gene expression by the galactan was studied and found to involve the LacI-like repressor GalR. As galactan is an important component of potato tubers, the information on its degradation provides opportunities to develop dedicated and improved prebiotics, defined as selectively fermented food ingredients that allow specific changes, both in the composition and/or in the activity in the gastrointestinal microbiota that confer benefits upon the host' well-being and health. A variety of prebiotics have been developed for all stages of life and many include plant-derived oligosaccharides that promote the growth of specific groups of Bifidobacteria. These and other oligosaccharides are increasingly used in infant formulas as it has been noted that their content is much higher in human than in bovine milk. The effect of the consumption of such prebiotics on the development of the microbiota in infants was determined in the study described by Boesten and colleagues (2011). They used a specific bifidobacterial mixed-species microarray capable of detecting the relevant species in intestinal Bifidobacteria. This was used to address the composition and development of bifidobacteria in a period of 2 years since birth. The developed approach did not rely on any PCR amplification and hence has advantages over other presently used methods, including next-generation sequencing technology. It was observed that prebiotic intervention indeed affected the number and species diversity of Bifidobacteria opening avenues for further optimizing infant formulas.

All present studies on lactic acid bacteria are strongly genome-driven. This allows to address global effects as well as permits the detailed analysis of basic mechanisms underlying the industrial properties of the used strains. The future developments in this area will be strongly influenced by the increasing number of sequenced genomes of strains within a species, which will expand rapidly through the application of next-generation sequencing technologies. It is expected that this may enable the sequence-based and strain-specific reconstruction of gene-regulation networks as an integral part of a systems biology approach to mathematically describe microbial behaviour at a molecular level and extending the currently available genome-based metabolic models (Teusink et al., 2006).

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