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Lactobacillus rossiae, a Vitamin B12 Producer, Represents a Metabolically Versatile Species within the Genus Lactobacillus

  • Maria De Angelis ,

    These authors are joint first authors on this work.

    Affiliation Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy

  • Francesca Bottacini ,

    These authors are joint first authors on this work.

    Affiliation Department of Microbiology, University College Cork, Cork, Ireland

  • Bruno Fosso,

    Affiliation Department of Bioscience, Biotechnology and Biopharmaceutical, University of Bari Aldo Moro, Bari, Italy

  • Philip Kelleher,

    Affiliation Department of Microbiology, University College Cork, Cork, Ireland

  • Maria Calasso,

    Affiliation Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy

  • Raffaella Di Cagno,

    Affiliation Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy

  • Marco Ventura,

    Affiliation Laboratory of Probiogenomics, Department of Life Sciences, University of Parma, Parma, Italy

  • Ernesto Picardi,

    Affiliations Department of Bioscience, Biotechnology and Biopharmaceutical, University of Bari Aldo Moro, Bari, Italy, Institute of Biomembranes and Bioenergetics (IBBE), CNR, Bari, Italy, National Institute of Biostructures and Biosystems (INBB), Rome, Italy

  • Douwe van Sinderen ,

    d.vansinderen@ucc.ie (DVS); marco.gobbetti@uniba.it (MG)

    ‡ These authors are joint senior authors on this work.

    Affiliations Department of Microbiology, University College Cork, Cork, Ireland, Alimentary Pharmabiotic Centre, University College Cork, Cork, Ireland

  • Marco Gobbetti

    d.vansinderen@ucc.ie (DVS); marco.gobbetti@uniba.it (MG)

    ‡ These authors are joint senior authors on this work.

    Affiliation Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy

Abstract

Lactobacillus rossiae is an obligately hetero-fermentative lactic acid bacterium, which can be isolated from a broad range of environments including sourdoughs, vegetables, fermented meat and flour, as well as the gastrointestinal tract of both humans and animals. In order to unravel distinctive genomic features of this particular species and investigate the phylogenetic positioning within the genus Lactobacillus, comparative genomics and phylogenomic approaches, followed by functional analyses were performed on L. rossiae DSM 15814T, showing how this type strain not only occupies an independent phylogenetic branch, but also possesses genomic features underscoring its biotechnological potential. This strain in fact represents one of a small number of bacteria known to encode a complete de novo biosynthetic pathway of vitamin B12 (in addition to other B vitamins such as folate and riboflavin). In addition, it possesses the capacity to utilize an extensive set of carbon sources, a characteristic that may contribute to environmental adaptation, perhaps enabling the strain's ability to populate different niches.

Introduction

Lactobacillus rossiae (formerly Lactobacillus rossii, designated a novel species in 2005 [1],) is an obligately hetero-fermentative lactic acid bacterium, exhibiting close phylogenetic relationship with Lactobacillus durianis, Lactobacillus malefermentans and Lactobacillus suebicus. L. rossiae strains have been isolated from the microbiota of sourdoughs [1], [2], [3], [4], wheat-legume sourdough [5], spelt flour [6], pineapples [7] and fermented meat [8], and from the gastrointestinal tract of humans [9] and animals [10]. The ability of Lactobacillus spp. to adapt to different environments is variable: some species are isolated from diverse habitats, while others appear to be restricted to specific niches [11]. The latter situation applies to Lactobacillus sanfranciscensis, which has so far only been found in sourdoughs. In contrast, Lactobacillus casei and Lactobacillus plantarum represent more versatile species, as they have been isolated from various fermented foods and are natural inhabitants of the human gastrointestinal tract [11].

Comparative genome analysis of Lactobacillus species has indicated that environmental adaptations cause a combination of gene gain and gene loss events [12], [13], [14]. Adaptation to the dairy niche appears to be associated with a tendency towards metabolic simplification. Loss of genes involved in carbohydrate metabolism and biosynthesis of amino acids and cofactors, and acquisition of genes required for peptide transport and hydrolysis have indeed been described in lactic acid bacteria [14], [15]. Species such as Lactobacillus gasseri and Lactobacillus johnsonii, which are commonly found in the gastrointestinal tract, carry genetic features that contribute to gut survival and promote interactions with intestinal mucosa. L. casei and L. plantarum possess the largest chromosome (2.9 and 3.3 Mb, respectively) among lactic acid bacteria, and contain a large number of regulatory and transport functions. Similar to L. plantarum, strains of L. rossiae exhibit remarkable ecological adaptability, genotypic and phenotypic diversity, and may be used to ferment a variety of foods [3], [16]. Some strains have been identified based on their antifungal activity [17], [18], and/or used for sourdough biotechnology, glutamate production [19] and fermentation of wheat germ [20].

The peculiarities of food fermentations mainly depend on the physiological and biochemical traits of the processing microbiota. Substantial progress has been achieved in genomic sequencing of lactic acid bacteria, especially for those species that are used for making dairy, sourdough, meat and vegetable foods, or those with promising probiotic traits [11]. To date (June, 2014), genomes of 78 lactobacilli have been completely sequenced or their genome sequencing is in progress (source http://www.ncbi.nlm.nih.gov/genome). Knowledge on the genomic features of lactobacilli will facilitate the identification of species and/or strain-specific traits, which may allow the rational design of strategies for improved fermentations or probiotic formulations for targeted food matrices or human applications [21].

For the above reasons, this study carried out the genomic annotation, comparative analyses, and metabolic pathway reconstruction of L. rossiae DSM 15814T, in addition to phenotypic analyses to confirm some of the predicted functional features.

Results and Discussion

General genome features

Whole-genome shotgun sequencing results of L. rossiae DSM 15814T [22] were retrieved from the NCBI public database; subsequent analyses focused on a selected subset of 57 contigs (size>400 bp) (Table S1). The combined DNA sequence of these 57 contigs represented 2,870,031 base pairs, which was thus presumed to be the minimum predicted genome size of this organism. The average G+C mol % content of the combined DNA sequences was determined to be 43%, consistent with the G+C mol % range of the Lactobacillus genus [21]. The sequences were subjected to ORF prediction, which resulted in the identification of 2,701 protein-encoding sequences (Table S2, general features). In silico annotation assigned a function to 74% of these deduced proteins, while the remaining 26% were deemed to represent hypothetical proteins. A Venn diagram, displaying core gene families, and the unique genes of L. rossiae DSM 15814T and other representatives of the Lactobacillus genus, is shown in Figure 1A. The Cluster of Orthologous Group (COG) classification assigned a COG category to 78% of the identified ORFs. This analysis established that the largest proportions of predicted genes are involved in carbohydrate and amino acid transport and metabolism (10% and 8%, respectively), and in general or unknown functions (10% and 8%, respectively) (Figure 1B). Regarding mobile elements, L. rossiae DSM 15814T appears to harbour a single plasmid (with a size of 57,494 bp), which contains genes predicted to encode a type I R/M system (LROS_2631-33), and proteins involved in conjugation (TraG/TraD/TraE), where the latter genes clustered together with genes specifying putative surface proteins (LROS_2616-25) and several hypothetical proteins (Figure S1). In addition, an apparently incomplete prophage (LROS_2487-2558), was identified that was integrated in the bacterial chromosome in the proximity of a predicted tRNAGln gene (data not shown).

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Figure 1. Classification of Lactobacillus rossiae DSM 15814T.

A) Venn diagram displaying core gene families obtained by MCL clustering, and unique genes of L. rossiae DSM 15814T and selected representatives of the Lactobacillus genus. B) Cluster of Orthologous Groups (COGs) classification of L. rossiae DSM 15814T based on the predicted ORFs. The occurrence of each COG family relative to the total of classified genes is indicated as a frequency percentage.

https://doi.org/10.1371/journal.pone.0107232.g001

Phylogeny and comparative analyses

To assess the phylogenetic positioning of L. rossiae within the Lactobacillus genus, a supertree based on the concatenation of 96 orthologous genes was built, using relevant sequences from the genomes of L. rossiae DSM 15814T, of 20 other fully sequenced Lactobacillus genus, and of Bifidobacterium breve UCC2003 as an outgroup (Figure 2A-C). This analysis revealed that the phylogenetic positioning of L. rossiae is close to that of the L. plantarum and L. brevis groups (Figure 2C), suggesting that these species may have followed similar strategies of environmental adaptation. BLASTP-based comparative analysis (Figure 3) showed that L. rossiae shares a high number of similar genes with L. plantarum, L. brevis and L. buchneri, thus confirming the higher degree of resolution using the 96 orthologous-based phylogenomic approach, compared to the one solely based on 16S rRNA gene sequence alignment (Figure 3A). The comparative genomics approach, coupled with hierarchical clustering analysis also allowed the definition of a set of 697 families (Figures 1A and 3A), which represent the predicted conserved core genome (gene families of L. rossiae DSM 15814T which are also present in all other examined lactobacilli), accounting for 33% of the total of genes (Figure 3A-B). The remaining 67% of L. rossiae ORF content appeared instead to be variable (only present in the genomes of some, but not all examined lactobacilli), confirming that this species appears to be quite different from the other members of this genus. It furthermore allowed the identification of a gene cluster (designated here as the pdu-cbi-cob-hem cluster) putatively involved in cobalamin (vitamin B12) de novo biosynthesis, as well as the ethanolamine utilization cluster and the presence of various mobile elements (e.g., prophage region and a putative plasmid described above) (Figure 3).

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Figure 2. Phylogenomics of Lactobacillus rossiae DSM 15814T.

A) 16S neighbor-joining (NJ) tree, resulting from the alignment of the 16S rRNA-encoding gene of L. rossiae DSM 15814T and that of 20 selected representatives of the Lactobacillus genus (L. amylovorus GRL 1112, L. acidophilus 30SC, L. kefiranofaciens ZW3, L. crispatus ST1, L. helveticus DPC 4571, L. gasseri ATCC 33323, L. johnsonii NCC 533, L. delbrueckii subsp. bulgaricus ATCC 11842, L. sakei subsp. sakei 23K, L. rhamnosus ATCC 8530, L. paracasei subsp. paracasei, L. casei ATCC334, L. ruminis ATCC 27782, L. salivarius UCC118, L. fermentum IFO 3956, L. reuteri DSM 20016, L. plantarum WCFS1, L. brevis ATCC 367, L. buchneri NRRL B-30929 and L. sanfranciscensis TMW 1.1304). The corresponding 16S rRNA-specifying sequence of Bifidobacterium breve UCC2003 was used as an outgroup. The positioning of L. rossiae DSM 15814T within the Lactobacillus genus is indicated in red. B) Multilocus supertree resulting from the alignment of the sequence of three housekeeping genes (groEL, dnaK and grpE) of L. rossiae DSM 15814T and 20 selected representatives of the Lactobacillus genus (see above for the species). The positioning of L. rossiae DSM 15814T within the Lactobacillus genus is indicated in red. C) Multilocus supertree resulting from the alignment of 96 selected orthologous genes of L. rossiae DSM 15814T and 20 selected representatives of the Lactobacillus genus (see above for the species). The positioning of L. rossiae DSM 15814T within the Lactobacillus genus is indicated in red.

https://doi.org/10.1371/journal.pone.0107232.g002

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Figure 3. Comparative genomics of L. rossiae DSM 15814T.

A) Hierarchical clustering analysis realized in Tmev and restricted to the sole variable genes of L. rossiae DSM 15814T with respect to representatives of the Lactobacillus genus used for the analysis in Figure 2. The positioning of the cobalamin biosynthesis and ethanolamine utilization cluster, and of prophage region and putative plasmid are indicated. B) Pie chart indicating the core, extended core and variable genome with respect to the total of gene families, resulting from the MCL clustering algorithm.

https://doi.org/10.1371/journal.pone.0107232.g003

De novo production of cofactor vitamin B12 and related ethanolamine utilization

The comparative analysis conducted on the here identified pdu-cbi-cob-hem cluster of L. rossiae DSM 15814T showed a high degree of homology with the previously characterized pdu-cbi-cob-hem cluster present in the genome of L. reuteri DSM 20026 [23], [24] and located upstream of a cobalamin-dependent ethanolamine utilization cluster.

Among lactobacilli evidence of a pdu-cbi-cob-hem cluster has been extensively described in L. reuteri DSM 20026, where cbi-cob-hem genes are involved in cobalamin production, while the pdu locus encodes propanediol and glycerol dehydratase activity which requires B12 as a cofactor [23]. In L. reuteri DSM 20026 the acquisition of this locus through horizontal transfer has been proposed because of the presence of IS elements in its flanking regions, even though the mechanism of acquisition is still unclear [23]. Comparison of the genetic organization of this locus in L. rossiae DSM 15814T with that of L. reuteri DSM 20026 and the pathogen Salmonella enterica var. Typhimurium LT2 showed that gene synteny of these gene clusters is conserved. The only apparent difference is the relative position of the transcriptional regulator pocR, which is located at the beginning of the pdu-cbi-cob-hem gene cluster in L. reuteri (Lreu_1750) [24], while it is located in the middle of the equivalent gene cluster in S. enterica and L. rossiae (Figure 4A), supporting the hypothesis proposed for L. reuteri DSM 20016 that the genetic transfer of the gene cluster occurred by means of two independent events [23]. It is also worth mentioning that the downstream located ethanolamine utilization cluster (eut) of DSM 15814T represents a so far unique feature within the genus Lactobacillus and that protein products of these genes exhibit 30–40% similarity to the corresponding proteins encoded by genes STM2452-70 of S. enterica var. Typhimurium LT2, supporting the notion that horizontal transfer of this region from a progenitor or close relative of S. enterica var. Typhimurium may have occurred in L. rossiae, and that the two species adopted a similar cobalamin-dependent ethanolamine-propanediol utilization strategy. Previous studies have indicated that ethanolamine utilization is a feature that is not uncommon among gut pathogens and gut commensals (e.g. Salmonella, Enterococcus, Pseudomonas, Corynebacterium, Clostridium, Escherichia) [25]. Phosphatidylethanolamine represents a major component of bacterial and epithelial membranes and may also be present in the gut as a result of the host's diet. For this reason the ability to metabolize this particular compound may confer a distinct advantage to a bacterium in a particular metabolic niche [25]. Cobalamin-dependent utilization of ethanolamine and 1,2-propanediol as a sole carbon source can occur in bacteria under both aerobic and anaerobic conditions [26], while the de novo biosynthesis of the cofactor vitamin B12 occurs under anaerobic conditions. A recent comparative study conducted on the ethanolamine utilization cluster (eut) in bacteria highlighted that the ethanolamine-ammonia lyase-encoding genes (eutB and eutC) are the most conserved among species (in our case LROS_0819-20), while the accessory genes (e.g., eutK, eutL, eutM, eutN, eutS), homologues of which appear to be absent from the L. rossiae DSM 15814T genome, are believed to be involved in the formation of a metabolosome, yet are not strictly required as they merely seem to increase the substrate utilization efficiency [27].

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Figure 4. Vitamin B12 production and related ethanolamine utilization.

A) Schematic representation of the pdu-cbi-cob-hem-eth cluster of L. rossiae DSM 15814T. Locus map displaying the organization of the pdu-cbi-cob-hem-eth of L. rossiae DSM 15814T and BLAST-based comparison with the relative cluster of S. enterica var Typhimurium LT2 and L. reuteri DSM 20016. Synteny map was reconstructed using a combination of reciprocal best BLASTP and CloneManager suite 5 (http://www.scied.com/). B) Growth of L. delbrueckii subsp. lactis ATCC 7830 in vitamin B12-free medium supplemented with increasing concentrations of vitamin B12 or CE of L. rossiae DSM 15814T or L. plantarum DC400 as negative control. Optical density (620 nm) and acidification (ΔpH) are also reported.

https://doi.org/10.1371/journal.pone.0107232.g004

In order to obtain a phenotypic confirmation of the biosynthetic capacity of B12 production in L. rossiae DSM 15814T a bioassay was performed using Lactobacillus delbrueckii ATCC 7830, a strain known as being unable to grow in the absence of vitamin B12 cofactor (see Methods section). During this experiment growth of L. delbrueckii ATCC 7830 was observed only following the addition of cytoplasmic extract (CE) obtained from L. rossiae or, alternatively, vitamin B12 to the medium, thus confirming that L. rossiae is capable of producing B12 and that this cofactor is present in its CE (Figure 4B). As a negative control we used CE from L. plantarum DC400, which as expected failed to support growth of L. delbrueckii ATCC 7830.

B-complex vitamins production in L. rossiae

In silico analyses of the genome of L. rossiae DSM 15814T indicated the potential for de novo synthesis of three B group or B-complex vitamins: cobalamin, riboflavin and folate. All these vitamins are important micronutrients, which are involved in a number of vital biochemical reactions of all living cells. Humans do not possess the capacity to synthesize folate, riboflavin, thiamine and cobalamin, and, consequently, they have to obtain such vitamins exogenously. Due to the relevant biotechnological applications, the biosynthetic pathways of B-complex vitamins have been described in detail for food- and gut-associated microorganisms [28]. As shown for members of the genus Lactobacillus and Lactococcus [24], [29], L. rossiae DSM 15814T is predicted to synthesize riboflavin from D-ribulose 5-phosphate and guanosine triphosphate (GTP) (Figure 5A). Indeed, being consistent with this genomic data, L. rossiae DSM 15814T was shown to be able to grow in and acidify riboflavin-free LDMIIIG broth (Figure 5C). L. rossiae DSM 15814T is also predicted to synthesize folate, but only in the presence of one of its precursors para-aminobenzoic acid (pABA) (Figure 5B). In fact, among the lactobacilli, L. plantarum is the only species predicted to be able to synthesize pABA [30]. In support of this in silico prediction, L. rossiae DSM 15814T growth was shown to occur in folate-free LDMIIIG medium to which pABA had been added (Figure 5C). Nine genes are present in the L. rossiae DSM 15814T genome with predicted functions related to thiamine biosynthesis, however, no growth or acidification were observed on thiamine-free LDMIIIG broth (data not shown), indicating that this biosynthetic pathway is incomplete or non-functional.

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Figure 5. Biosynthesis of riboflavin and folate.

Reconstruction of the biosynthesis of riboflavin (A) and folate (B) in L. rossiae DSM 15814T. Growth and acidification (ΔpH) of DSMZ 15184T at 30°C for 18 h (C). LDMIIIG, modified semi-defined medium LDMIIIG; vitamin-free, LDMIIIG without added vitamins; folate-free, LDMIIIG without folate; riboflavin-free, LDMIIIG without riboflavin. Data are the means of three separate experiments performed in triplicate.

https://doi.org/10.1371/journal.pone.0107232.g005

Carbohydrate utilization and pyruvate metabolism

In silico analyses also predicted that the L. rossiae DSM 15814T genome harbours a substantial number of genes involved in carbohydrate utilization. Based on previous studies, DSM 15814T is capable of metabolizing ribose, D-xylose, arabinose, galactose, glucose, fructose, mannose, N-acetyl glucosamine, maltose, turanose, D-gluconic acid, palatinose, α-hydroxy-butyric acid and D-L lactic acids, when grown in MRS medium [1], [16]. Bioinformatic analyses of the DSM 15814T genome sequence revealed 17 complete phosphoenolpyruvate phospho-transferase systems (PEP-PTS) belonging to different families (e.g., Glc, Lac and Man families), but also putative ABC transporters involved in the uptake of various carbohydrates (e.g maltose/maltodextrin, ribose, fucose, glucose, galactose, lactose, galactose and N-acetyl-D-glucosamine).

In addition, L. rossiae DSM 15814T is also predicted to produce a number of extracellular or cell wall-associated polysaccharide-degrading enzymes, represented by a cyclomaltodextrinase (E.C. 3.2.1.54; LROS_1707), an α-amylase (E.C. 3.2.1.10; LROS_1584), a β-glucosidase (E.C. 3.2.1.21; LROS_2047), a mannosyl-glycoprotein endo-beta-N-acetylglucosaminidase (E.C. 3.2.1.96; LROS_0612) and a neopullulanase (EC 3.2.1.135; LROS_1707). Furthermore, the L. rossiae DSM 15814T genome specifies putative enzymatic pathways predicted to degrade arabinose and xylose-containing poly- and/or oligosaccharides (Figure S2), both of which occur as major carbohydrate components in plant cells. In particular two genes (LROS_1251 and LROS_1108) are present which encode predicted extracellular glycosyl hydrolases responsible for the initial degradation of arabinose and xylose-containing polysaccharides into oligosaccharides prior to their internalization, after which they are further hydrolysed to xylose/arabinose.

Regarding pyruvate metabolism, both D- and L-lactate dehydrogenase-encoding genes (ldhD: LROS_0202, LROS_0465, LROS_2176, LROS_2251 and ldhL: LROS_1559, LROS_2223, LROS_2704) are present, which convert pyruvate into D- and L-lactate, respectively (Figure S3). The presence of multiple copies of ldh genes is not a peculiarity of L. rossiae as this has also been found in other lactobacilli, possessing both large (e.g., L. plantarum, L. casei) or small (e.g., L. sanfranciscensis) genomes [30], [31], [32]. The same can be said for genes whose encoded enzymes are predicted to lead to the synthesis of ethanol and acetic acid from pyruvate, or catabolize pyruvate to other compounds such as acetaldehyde and acetoin.

Furthermore, it has previously been demonstrated that growth of hetero-fermentative lactic acid bacteria is enhanced when certain organic carbon sources (for example citrate) are used as external electron acceptors [33], a notion enforced by the fact that L. rossiae DSM 15814T encompasses several genes with predicted functions in citrate metabolism (LROS_0055-LROS_0059).

Amino acid biosynthesis, catabolism and proteolytic system

The various biosynthetic pathways involved in amino acid synthesis are variably present or absent in the different members of the Lactobacillus genus [12], [32] and in this regard L. rossiae DSM 15814T is predicted to contain genes encoding the enzymes that make up biosynthetic pathways for certain amino acids (e.g. serine, glycine, L-asparagine, glutamine, L-cysteine and L-methionine).

Regarding the catabolism of free amino acids, the L. rossiae DSM 15814T genome is predicted to specify a complete arginine deaminase (ADI) pathway, glutamine synthase and glutamate decarboxylase enzymes (Table S3, Figure S4 and S5 and Text S1).

The ADI gene cluster, characterized in lactococci and lactobacilli, has been correlated with having a positive effect on the flavour of leavened baked goods [33], but is mainly used by the cell as an acid-stress response mechanism through the production of the alkaline compound NH3. In addition, the energy (ATP) produced via this pathway enables the extrusion of cytoplasmic protons through the F0F1 ATPase, thus supporting cell survival following sugar depletion [34]. Activity of the ADI pathway in L. rossiae DSM 15814T was detected at phenotypic level (Figure S5) by determining the kinetics of growth and acidification with and without arginine supplementation in the medium. Compared to the negative control (e.g. medium without arginine addition), cell density of L. rossiae DSM 15814T did not differ (P>0.05) in the arginine-supplemented medium. However, an increase of cell survival was found after 48 h in the growth medium containing arginine compared to the same medium without arginine. Due to the production of NH3 from arginine metabolism, different kinetics of acidification were found, which at 24 h showed a substantial difference of pH 6.79 (arginine-containing medium) versus 4.32 (medium without arginine). The activity of all three ADI pathway enzymes was also found in the cytoplasmic extract of DSM 15814T (80, 140, and 87 U/mg for ADI, OTC, and CK, respectively). Similar data was previously found for L. sanfranciscensis [34].

Glutamate is inter-convertible to glutamine through the activity of the glutamine synthase (GS, EC 6.3.1.2). The genome of L. rossiae contains a gene that is predicted to encode a glutamate decarboxylase (EC 4.1.1.15), which converts glutamate into γ-amino butyric acid (GABA). In addition, the production of GABA was also confirmed phenotypically. The capacity for synthesizing GABA of L. rossiae was assayed in SDB medium. After 24 h of fermentation at 30°C, the concentration of GABA was 1.75 mg/kg. GABA, a four-carbon non-protein amino acid, has been reported to act as the major inhibitory neurotransmitter of the central nervous system, to possess anti-hypertensive, diuretic and tranquilizer effects, and to prevent diabetes [35].

Except for two putative and uncharacterized zinc proteases (metalloproteases) (LROS_1355; LROS_2169), no predicted extracellular proteinase (prt) genes were found in the genome of L. rossiae, which is in agreement with the fact that L. rossiae was shown to be unable to grow in milk without the addition of peptides or free amino acids. In addition, only a weak protease activity was found on albumin and globulin (data no shown).

As shown for L. sanfranciscensis [32], [36], L. rossiae has more than 20 genes encoding putative intracellular peptidases with different specificities (e.g. aminopeptidase and oligo-/tri-/di-peptidase activities), which may confer this strain the ability of hydrolysing a broad range of peptides (Table S4). In support of this in silico prediction, L. rossiae DSM 15814T showed peptidase activities (general aminopeptidase type N, PepN; proline iminopeptidase, PepI; X-prolyl dipeptidyl aminopeptidase, PepX; endopeptidase, PepO; prolyl endopeptidyl peptidase, PEP; tripeptidase, PepT; dipeptidase, PepV; prolidase, PepQ; and prolinase, PepR (Figure S6). Peptidase activities improve the organoleptic characteristics of fermented foods (e.g., sourdough leavened baked goods) by increasing the concentration of free amino acids [33].

Regulation of L. rossiae

Regulatory proteins play an important role in the adaptation of bacteria to different environments and L. rossiae DSM 15814T encodes quite a high number of putative regulatory genes (117, representing 4.3% of the total identified protein complement), some of which are involved in stress response (Table S5). The number of transcriptional regulators of L. rossiae is markedly higher than that found for L. delbrueckii subsp. bulgaricus (ca. 53, representing 3.1% of total of gene content), L. helveticus (ca. 44, representing 2.7% of the total of gene content) or L. sanfranciscensis (ca. 40, representing 2.8% of the total of gene content), while it is similar to that found for the highly versatile species L. casei (ca. 140, representing 4.5% of the total of gene content), yet lower than L. plantarum (ca. 234, representing 7.7% of the total of genes). These findings are in agreement with the notion that large genomes specify a relative high number of regulatory proteins [37], [12].

Conclusions

Since its isolation, L. rossiae has been shown to be a highly versatile species capable of colonizing different environments, such as fermented cereals, legumes, fruits and meat, as well as being an inhabitant of the human and animal gut-intestinal tract. Analysis of L. rossiae DSM 15814T, a sourdough strain, revealed a minimum predicted genome size of 2,870,031 bp, encoding relatively high numbers of genes involved in carbohydrate and amino acid transport and metabolism, stress resistance, transcriptional regulation and signal transduction. Based on phylogeny, phylogenomic and comparative analyses, the L. rossiae taxon forms an independent phylogenetic branch, in close proximity to the L. reuteri, L. fermentum, L. plantarum and L. brevis groups, which suggests that these species all adopted a similar strategy for phylogenetic evolution and environmental adaptation. From a technological point of view, the genome of L. rossiae DSM 15814T shows some interesting features: (i) the de novo production of B12 cofactor and other B-complex vitamins (e.g. riboflavin and folate), which represents an important biotechnological potential for industrial applications; (ii) the synthesis of flavor-related compounds from the pyruvate metabolism, proteolysis and amino acid catabolism; and (iii) the capacity to use a substantial number of carbon sources, which provides metabolic flexibility in terms of nutrient availability. In addition, the high number of genes correlated to regulatory systems indicates that L. rossiae is a versatile species with a high potential for environmental colonization. The results of this study are expected to provide the foundation for further investigations to exploit the biotechnology potential of L. rossiae isolates.

Materials and Methods

Genome annotation

The genome sequence of L. rossiae DSM 15814T was obftained from the NCBI database (accession number: NZ_AKZK00000000) and the analysis focused on 57 large contigs (400 bp size cut-off). Open Reading Frame (ORF) prediction and functional assignment was automatically performed using the RAST webserver (http://rast.nmpdr.org/), and the generated information was integrated and assessed with the contribution of alternative databases as protein family (Pfam) (http://pfam.sanger.ac.uk), ENZYME database [38] and Clusters of Orthologous Groups (COGs). In particular, the annotation of the EC numbers of each ORF was carried out using the annotat8r tool [39]. COG classification was carried out using BLASTP alignment against the relative database (http://www.ncbi.nlm.nih.gov/Ftp/databases/COG), using a cut-off E-value of 0.0001 with at least 50% of identity across a minimum of 50% of a given protein length.

Comparative analyses

BLAST-based comparative analyses at protein level were performed on 20 representative Lactobacillus species, including L. rossiae DSM 15814T, through the bi-directional BLASTP alignment [40], and employing a cut-off E-value of 0.0001, with at least 50% of identity across a minimum of 50% of protein length.

Using Markov Cluster Algorithm (MCL) [41], all identified genes were grouped in orthologous families and the resulting output was used to build a binary matrix containing information on the presence/absence of such families in each Lactobacillus species.

Hierarchical clustering analysis was performed with the hclust package in R (http://www.r-project.org), using as input the binary matrix computed with the above method. A heatmap displaying the clustering of organisms and related families was generated through the Multiple Experiment Viewer (MeV) tool v.4.8.1 (http://mev-tm4.sourceforge.net).

Phylogenomics of L. rossiae DSM 15814T

First, phylogenetic analysis of L. rossiae DSM 15814T and 20 complete Lactobacillus genomes was inferred through 16S rDNA alignment in MUSCLE v6.0 [42] and single gene neighbour-joining tree in MEGA6 [43]. As an additional analysis, a multi-locus supertree was computed from the alignment of three concatenated housekeeping genes (groEL, dnaK and grpE) and 96 selected orthologues. The relative phylogenetic relations were inferred using the JTT model in Phyml v3.0 [44]. A consensus tree was computed using the Consense module in Phylip package v3.69 (http://evolution.genetics.washington.edu/phylip.html). In all cases, bootstrap assessment of the inferred relations was carried out by means of 1000 bootstrap iterations.

Reconstruction of metabolic pathways

Metabolic reconstruction may provide insights regarding the metabolic potential of L. rossiae DSM 15814T, which should guide experimental studies to investigate genotype–phenotype relationships. EC numbers were extracted from genome annotations. They were then automatically mapped onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways [45]. In cases where key enzymes were missing within an otherwise complete pathway, a further effort was made to identify homologous candidate enzymes through extensive manual searches with BLASTP and HMMER [46], [37].

Biosynthesis of riboflavin, folate, thiamine and cobalamin

Growth of L. rossiae DSM 15814T was assayed in modified semi-defined medium (LDMIIIG) (pH 5.6) [47], which was supplemented with 0.1% Tween 80 and 1% of peptone (see Text S2).

Cobalamin detection and quantitative bioassay

To demonstrate cobalamin production by L. rossiae DSM 15814T, a bioassay was performed using Lactobacillus leichmannii ATCC 7830 (formerly Lactobacillus delbrueckii subsp. lactis ATCC 7830), a strain that requires B12 for growth (see Text S2).

Protease and peptidase activities

Proteinase activity was measured using wheat albumins and globulins as substrates. The level of protein hydrolysis was estimated by Reversed-phase high-performance liquid chromatography (RP-HPLC) and amino acid analyses (see Text S2).

Arginine catabolism assay, cell survival and biosynthesis of GABA from glutamic acid

L. rossiae DSM 15814T was propagated for 24 h at 30°C in modified MRS broth (Oxoid, Basingstoke, Hampshire, England) with the addition of fresh yeast extract (5%, vol/vol) and 28 mM maltose to a final pH of approximately 5.6 [34]; see Text S2). The biosynthesis of GABA from glutamic acid was estimated as described by Siragusa et al. [48] using a Biochrom 30 series Amino Acid Analyzer (Biochrom Ltd., Cambridge Science Park, England).

Supporting Information

Figure S1.

Predicted plasmid of L. rossiae DSM 15814T. Genome atlas representing the organization of ORFs in the predicted plasmid pLR1 of L. rossiae DSM 15814T. Displayed are, from inner to outer circle: G+C skew, G+C content and ORFs organization. Each ORF is also classified based on the predicted function.

https://doi.org/10.1371/journal.pone.0107232.s001

(TIF)

Figure S2.

Utilization of arabinose and xylose-containing poly/oligosaccharides.

https://doi.org/10.1371/journal.pone.0107232.s002

(TIF)

Figure S3.

Pyruvate metabolic pathway of L. rossiae DSM 15814T.

https://doi.org/10.1371/journal.pone.0107232.s003

(TIF)

Figure S4.

Locus map showing the organization of the arginine deaminase (ADI) cluster. L. rossiae DSM 15814T, L. amylovorus GRL 1112, L. acidophilus 30SC, L. fermentum IFO 3956, L. sakei subsp. sakei 23K, L. brevis ATCC 367, L. buchneri NRRL B-30929, L. kefiranofaciens ZW3.

https://doi.org/10.1371/journal.pone.0107232.s004

(TIF)

Figure S5.

Kinetics of growth (Log CFU/ml) (A) and pH of growth medium (B). L. rossiae DSM 15814T cells were cultivated in MAM broth with (empty triangles) and without (filled triangles) 17 mM arginine.

https://doi.org/10.1371/journal.pone.0107232.s005

(TIF)

Figure S6.

Peptidase activities of L. rossiae DSM 15814T.

https://doi.org/10.1371/journal.pone.0107232.s006

(TIF)

Table S1.

Selected contig and accession number of the genome of Lactobacillus rossiae DSM 15814T.

https://doi.org/10.1371/journal.pone.0107232.s007

(XLSX)

Table S2.

General features of representatives of the genus Lactobacillus analysed in this study.

https://doi.org/10.1371/journal.pone.0107232.s008

(DOCX)

Table S3.

In silico search of the genome of Lactobacillus rossiae DSM 15814T for ORFs putatively involved in amino acid metabolism.

https://doi.org/10.1371/journal.pone.0107232.s009

(DOCX)

Table S4.

In silico analysis of the genome of Lactobacillus rossiae DSM 15814T for ORFs encoding proteases and peptidases, and their cleavage specificities, gene names and relative abundance in the genome.

https://doi.org/10.1371/journal.pone.0107232.s010

(DOCX)

Table S5.

Predicted transcriptional regulators encoded by the Lactobacillus rossiae DSM 15814T genome.

https://doi.org/10.1371/journal.pone.0107232.s011

(DOCX)

Text S1.

Results - Supporting Information.

https://doi.org/10.1371/journal.pone.0107232.s012

(DOCX)

Text S2.

Experimental Procedures - Supporting Information.

https://doi.org/10.1371/journal.pone.0107232.s013

(DOCX)

Acknowledgments

We thank Sonya Siragusa (Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy) for technical assistance.

Author Contributions

Conceived and designed the experiments: DVS MG MDA FB. Performed the experiments: FB MDA BF PK MC. Analyzed the data: FB MDA RDC EP. Contributed reagents/materials/analysis tools: MG DVS. Wrote the paper: MDA FB DVS. Revised the manuscript: DVS MG MV.

References

  1. 1. Corsetti A, Settanni L, van Sinderen D, Felis GE, Dellaglio F, et al. (2005) Lactobacillus rossi sp. nov. isolated from wheat sourdough. Int J Syst Evol Microbiol 55: 35–40.
  2. 2. Siragusa S, Di Cagno R, Ercolini D, Minervini F, Gobbetti M, et al. (2009) Taxonomic structure and monitoring of the dominant lactic acid bacteria population during wheat flour sourdough type I propagation by using Lactobacillus sanfranciscensis starters. Appl Environ Microbiol 75: 1099–1109.
  3. 3. Scheirlinck I, Van der Meulen R, Vrancken G, De Vuyst L, Settanni L, et al. (2009) Polyphasic taxonomic characterization of Lactobacillus rossiae isolates from Belgian and Italian sourdoughs reveals intraspecific heterogeneity. Syst Appl Microbiol 32: 151–156.
  4. 4. Minervini F, De Angelis M, Di Cagno R, Pinto D, Siragusa S, et al. (2010) Robustness of Lactobacillus plantarum starters during daily propagation of wheat flour sourdough type I. Food Microbiol 27: 897–908.
  5. 5. Rizzello CG, Calasso M, Campanella D, De Angelis M, Gobbetti M (2014) Sourdough fermentation of a mixture of wheat, chickpea, lentil and bean flours for making white bread. Int J Food Microbiol 180: 78–87.
  6. 6. Coda R, Nionelli L, Rizzello CG, De Angelis M, Tossut P, et al. (2010) Spelt and emmer flours: characterization of the lactic acid bacteria microbiota and selection of mixed starters for bread making. J Appl Microbiol 108: 925–935.
  7. 7. Di Cagno R, Cardinali G, Minervini G, Antonielli L, Rizzello CG, et al. (2009) Taxonomic structure of the yeasts and lactic acid bacteria microbiota of pineapple (Ananas comosus L. Merr.) and use of autochthonous starters for minimally processing. Food Microbiol 27: 381–389.
  8. 8. Nguien DTL, Van Hoorde K, Cnockaert M, De Brandt E, De Bruyne K, et al. (2013) A culture–dependent and –independent approach for the identification of lactic acid bacteria associated with the production of nemchua, a Vietnamese fermented meat product. Food Res Int 50: 232–240.
  9. 9. Di Cagno R, Rizzello CG, Gagliardi F, Ricciuti P, Ndagijimana M, et al. (2009) Different fecal microbiotas and volatile organic compounds in treated and untreated children with celiac disease. Appl Environ Microbiol 75: 3963–3971.
  10. 10. De Angelis M, Siragusa S, Berloco M, Caputo L, Settanni L, et al. (2006) Selection of potential probiotic lactobacilli from pig feces to be used as additives in pelleted feeding. Res Microbiol 157: 792–801.
  11. 11. De Angelis M, Gobbetti M (2012) Lactic Acid Bacteria | Lactobacillus spp.: General Characteristics. In Encyclopedia of Dairy Sciences. Fuquay, J.W., Fox, P.F., and McSweeney P.L.H. (eds.), San Diego: Academic Press, pp. 78–90.
  12. 12. Cai H, Thompson R, Budinich MF, Broadbent JR, Steele JL (2009) Genome sequence and comparative genome analysis of Lactobacillus casei: insights into their niche–associated evolution. Gen Biol Evol 9: 239–257.
  13. 13. Goh Y, Klaenhammer TR (2009) Genomic features of Lactobacillus species. Front Biosci 14: 1362–1386.
  14. 14. Makarova K, Slesarev A, Wolf Y, Sorokin A, Mirkin B, et al. (2006) Comparative genomics of the lactic acid bacteria. Proc Natl Acad Sci USA 103: 15611–15616.
  15. 15. Callanan M, Kaleta P, O′Callaghan J, O′Sullivan O, Jordan K, et al. (2008) Genome sequence of Lactobacillus helveticus, an organism distinguished by selective gene loss and insertion sequence element expansion. J Bacteriol 190: 727–735.
  16. 16. Di Cagno R, De Angelis M, Gallo G, Settanni L, Berloco MG, et al. (2007) Genotypic and phenotypic diversity of Lactobacillus rossiae strains isolated from sourdough. J Appl Microbiol 10: 821–835.
  17. 17. Valerio F, Favilla M, De Bellis P, Sisto A, De Candia S, et al. (2009) Antifungal activity of strains of lactic acid bacteria isolated from a semolina ecosystem against Penicillium roqueforti, Aspergillus niger and Endomyces fibuliger contaminating bakery products. Syst Appl Microbiol 32: 438–448.
  18. 18. Crowley S, Mahony J, van Sinderen D (2013) Current perspectives on antifungal lactic acid bacteria as natural bio–preservatives. Trends Food Sci Technol 33: 93–109.
  19. 19. Stromeck A, Hu Y, Chen L, Gänzle MG (2011) Proteolysis and bioconversion of cereal proteins to glutamate and γ–Aminobutyrate (GABA) in rye malt sourdoughs. J Agric Food Chem 59: 1392–1399.
  20. 20. Rizzello CG, Nionelli L, Coda R, De Angelis M, Gobbetti M (2010) Effect of sourdough fermentation on stabilisation, and chemical and nutritional characteristics of wheat germ. Food Chem 119: 1079–1089.
  21. 21. Claesson MJ, van Sinderen D, O′Toole PW (2007) The genus Lactobacillus–a genomic basis for understanding its diversity. FEMS Microbiol Lett 269: 22–28.
  22. 22. Di Cagno R, De Angelis M, Cattonaro F, Gobbetti M (2012) Draft Genome Sequence of Lactobacillus rossiae DSM 15814T. J Bacteriol 194: 5460–5461.
  23. 23. Morita H, Toh H, Fukuda S, Horikawa H, Oshima K, et al. (2008) Comparative genome analysis of Lactobacillus reuteri and Lactobacillus fermentum reveal a genomic island for reuterin and cobalamin production. DNA Res 15: 151–161.
  24. 24. Santos F, Spinler JK, Saulnier DM, Molenaar D, Teusink B, et al. (2011) Functional identification in Lactobacillus reuteri of a PocR–like transcription factor regulating glycerol utilization and vitamin B12 synthesis. Microb Cell Fact 10: 55.
  25. 25. Garsin DA (2010) Ethanolamine utilization in bacterial pathogens: roles and regulation. Nat Rev Microbiol 8: 290–295.
  26. 26. Kofoid E, Rappleye C, Stojiljkovic I, Roth J (1999) The 17–gene ethanolamine (eut) operon of Salmonella typhimurium encodes five homologues of carboxysome shell proteins. J Bacteriol 181: 5317–5329.
  27. 27. Brinsmade SR, Paldon T, Escalante–Semerena JC (2005) Minimal functions and physiological conditions required for growth of Salmonella enterica on ethanolamine in the absence of the metabolosome. J Bacteriol 187: 8039–8046.
  28. 28. LeBlanc JG, Milani C, De Giori GS, Sesma F, van Sinderen D, et al. (2013) Bacteria as vitamin suppliers to their host: a gut microbiota perspective. Curr Opin Biotechnol 24: 160–168.
  29. 29. Burgess C, O′Connell–Motherway M, Sybesma W, Hugenholtz J, van Sinderen D (2004) Riboflavin production in Lactococcus lactis: potential for in situ production of vitamin–enriched foods? Appl Environ Microbiol 70: 5769–5777.
  30. 30. Kleerebezem M, Boekhorst J, van Kranenburg R, Molenaar D, Kuipers OP, et al. (2003) Complete genome sequence of Lactobacillus plantarum WCFS1. Proc Natl Acad Sci USA 100: 1990–1995.
  31. 31. Rico J, Yebra MJ, Perez–Martinez G, Deutscher J, Monedero V (2008) Analysis of ldh genes in Lactobacillus casei BL23: role on lactic acid production. J Ind Microbiol Biotechnol 35: 579–586.
  32. 32. Vogel RF, Pavlovic M, Ehrmann MA, Wiezer A, Liesegang H, et al. (2011) Genomic analysis reveals Lactobacillus sanfranciscensis as stable element in traditional sourdoughs. Microb Cell Fact 10: S6.
  33. 33. Gobbetti M, De Angelis M, Corsetti A, Di Cagno R (2005) Biochemistry and physiology of sourdough lactic acid bacteria. Trends Food Sci Technol 16: 57–69.
  34. 34. De Angelis M, Mariotti L, Rossi J, Servili M, Fox P, et al. (2002) Arginine catabolism by sourdough lactic acid bacteria: purification and characterization of the arginine deiminase pathway enzymes from Lactobacillus sanfranciscensis CB1. Appl Environm Microbiol 68: 6193–6201.
  35. 35. Hagiwara H, Seki T, Ariga T (2004) The effect of pre-germinated brown rice intake on blood glucose and PAI-1 levels in streptozotocin-induced diabetic rats. Biosci Biotechnol Biochem 68: 444–447.
  36. 36. De Angelis M, Di Cagno R, Gallo G, Curci M, Siragusa S, et al. (2007) Molecular and functional characterization of Lactobacillus sanfranciscensis strains isolated from sourdoughs. Int J Food Microbiol 114: 69–82.
  37. 37. Boekhorst J, Siezen RJ, Zwahlen MC, Vilanova D, Pridmore RD, et al. (2004) The complete genomes of Lactobacillus plantarum and Lactobacillus johnsonii reveal extensive differences in chromosome organization and gene content. Microbiology 150: 3601–3611.
  38. 38. Bairoch A, Apweiler R, Wu CH, Barker WC, Boeckmann B, et al. (2005) The Universal Protein Resource (UniProt). Nucleic Acids Res 33: D154–D159.
  39. 39. Schmid R, Blaxter ML (2008) Annot8r: GO, EC and KEGG annotation of EST datasets. BMC Bioinformatics 9: 180.
  40. 40. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215: 403–410.
  41. 41. Enright AJ, Van Dongen S, Ouzounis CA (2002) An efficient algorithm for large–scale detection of protein families. Nucleic Acids Res 30: 1575–1584.
  42. 42. Edgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5: 113.
  43. 43. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol 30: 2725–2729.
  44. 44. Guindon S, Gascuel O (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 52: 696–704.
  45. 45. Kanehisa M, Goto MS, Kawashima S, Okuno Y, Hattori M (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32: D277–D280.
  46. 46. Eddy SR (1996) Hidden Markov models. Curr Opin Struct Biol 6: 361–365.
  47. 47. Jones SE, Versalovic J (2009) Probiotic Lactobacillus reuteri biofilms produce antimicrobial and anti–inflammatory factors. BMC Microbiol 9: 35.
  48. 48. Siragusa S, De Angelis M, Di Cagno R, Rizzello CG, Coda R, et al. (2007) Synthesis of γ–aminobutyric acid by lactic acid bacteria Isolated from a Variety of Italian Cheeses. Appl Environ Microbiol 73: 7283–7290.