Download PDF
Original Article  |  Open Access  |  2 Sep 2024

Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database

Views: 239 |  Downloads: 20 |  Cited:  0
Microbiome Res Rep 2024;3:45.
10.20517/mrr.2024.11 |  © The Author(s) 2024.
Author Information
Article Notes
Cite This Article

Abstract

Background: Members of the Bifidobacterium genus and lactobacilli are the most commonly used probiotics to promote human health. In this context, genome-based in silico analyses have been demonstrated as a fast and reliable tool for identifying and characterizing health-promoting activities imputed to probiotics.

Methods: This study is an extension of the Integrated Probiotic Database (IPDB) previously created on probiotics of the genus Bifidobacterium, facilitating a comprehensive understanding of the genetic characteristics that contribute to the diverse spectrum of beneficial effects of probiotics. The strains integrated into this new version of the IPDB, such as various lactobacilli and strains belonging to the species Streptococcus thermophilus(S. thermophilus) and Heyndrickxia coagulans (H. coagulans) (formerly Bacillus coagulans), were selected based on the labels of probiotic formulations currently on the market and using the bacterial strains whose genome had already been sequenced. On these bacterial strains, comparative genome analyses were performed, mainly focusing on genetic factors that confer structural, functional, and chemical characteristics predicted to be involved in microbe-host and microbe-microbe interactions.

Results: Our investigations revealed marked inter- and intra-species variations in the genetic makeup associated with the biosynthesis of external structures and bioactive metabolites putatively associated with microbe- and host-microbe interactions.

Conclusion: Although genetic differences need to be confirmed as functional or phenotypic differences before any probiotic intervention, we believe that considering these divergences will aid in improving effective and personalized probiotic-based interventions.

Keywords

Lactobacillus, Streptococcus thermophilus, Heyndrickxia coagulans, Bacillus, genomics, probiotics

INTRODUCTION

According to the Food and Agricultural Organization of the United Nations (FAO) and the World Health Organization (WHO), probiotics are “live microorganisms which, when administered in adequate amounts, confer a health benefit on the host”[1]. The probiotic efficacy of specific bacteria mainly resides in their ability to enhance immune responses, metabolize nutrients generating beneficial metabolites such as short-chain fatty acids (SCFAs) and vitamins, and exert antagonistic interactions with pathogenic and opportunistic bacteria[2-7]. This is achieved by producing diverse organic acids, leading to a decrease in pH and the generation of hydrogen peroxide, lysozyme, and bacteriocins[6]. However, each strain used within dietary supplements must adhere to some basic minimum criteria, including safety for the intended use, the ability to interact with intestinal epithelial surfaces and mucous membranes, and an adequate tolerance to gastric and bile acids to survive in the human gastrointestinal tract[8,9].

Generally, probiotic products may contain one or more microbial strains and are often developed with members of Bifidobacterium, Bacillus, and Streptococcus genera or with lactobacilli[10,11]. In particular, lactobacilli have been reported as the most prominent probiotic from the lactic acid bacteria (LAB) group, being widely used industrially due to their possible use in the production of dairy products such as cheese, yogurt, and other fermented milk-based foods[12]. The existing body of research links several lactobacilli, such as Lactobacillus acidophilus (L. acidophilus), Lactobacillus bulgaricus (L. bulgaricus), Lacticaseibacillus casei (L. casei), Lacticaseibacillus rhamnosus (L. rhamnosus), and Limosilactobacillus reuteri (L. reuteri), to the restoration of homeostasis in human intestinal disorders, inhibition of pathogen adhesion and growth, and a protective role against inflammatory diseases[13-15].To date, despite the presence in the literature of comparative genomic studies on bacteria in relation to their probiotic qualities, which have led to the identification of genes involved in key metabolic pathways and potential probiotic characteristics[16], a gap persists in analyses of the individual genetic factors underlying the specific claimed probiotic characteristics. For this reason, in this study, we investigated and compared the genetic content of 18 microbial strains commonly utilized in probiotic formulations, focusing on the species mentioned above. The goal was to expand the information cataloged in the Integrated Probiotic DataBase (IPDB) established in a previous study[17], creating a comprehensive public repository that connects strain-specific genetic traits with potential health-promoting activities on the host.

MATERIALS AND METHODS

Genome sequences of strains employed in commercial probiotic products

Through extensive scrutiny of the scientific literature, several microbial species used in the production of commercial dietary probiotic products were initially identified. Moreover, we collected information regarding commercially available probiotic products worldwide, and an initial selection was subsequently made based on the bacterial species for which specific strains are specified on the label of the probiotic products. Finally, we screened for the bacterial strains whose genomes were deposited online in the National Center for Biotechnology Information (NCBI) Genomes database. In detail, a total of 15 lactobacilli, two strains of Streptococcus thermophilus (S. thermophilus), and a single strain of the Heyndrickxia coagulans(H. coagulans) species were retrieved and submitted to genomics and comparative genomics analysis [Table 1]. In addition, as an extension of the previously built genome database, this work integrates data from genome comparative analysis of 34 Bifidobacterium strains generated in the context of a previous study[18]. Data integration was performed while maintaining methodological consistency with the original research to ensure comparability and robustness of the results.

Table 1

List and general characteristics of the bacterial genomes analyzed in this study

Organism nameStrain nameAccession numberGenome statusGenome size (Mb)GC content (%)CDS
Lactobacillus acidophilusBIO6307GCA_008868625.1Contig1.9734.61,850
Lactobacillus acidophilusLA1GCA_002286215.1Complete1.9934.71,860
Lactobacillus acidophilusLa-14GCA_000389675.2Complete1.9934.71,867
Lactobacillus acidophilusLa-5GCA_024665555.1Complete1.9934.71,859
Lactobacillus acidophilusNCFMGCA_000011985.1Complete1.9934.71,875
Lacticaseibacillus caseiBIO5773GCA_008868595.1Contig3.0847.92,848
Lactobacillus gasseriBIO6369GCA_008868535.1Contig1.8735.11,807
Lacticaseibacillus paracaseiLpc-37GCA_002762235.1Contig3.1646.33,010
Limosilactobacillus reuteriRC-14GCA_002762415.1Contig2.0138.61,966
Lacticaseibacillus rhamnosusATCC53103GCA_000026505.1Complete3.0146.72,817
Lacticaseibacillus rhamnosusBIO6870GCA_008831425.1Complete3.0146.72,815
Lacticaseibacillus rhamnosusGGGCA_003353455.1Complete3.0146.72,819
Lacticaseibacillus rhamnosusGR-1GCA_900604925.1Contig2.8946.52,682
Lacticaseibacillus rhamnosusHN001GCA_0001732155.2Contig2.9146.742,689
Ligilactobacillus salivariusBIO6313GCA_013249205.1Contig232.61,931
Streptococcus thermophilusTH-4GCA_024665315.1Complete1.8639.091,954
Streptococcus thermophilusSt-6GCA_002796655.1Contig1.9238.72,030
Heyndrickxia coagulansUnique IS-2GCA_01578455.1Contig3.4546.43,332

Genome annotation

To ensure consistent genomic analyses, open reading frames (ORFs) from the bacterial strains considered in this study were predicted and annotated using the most recent release of the MEGAnnotator pipeline[19]. In detail, contigs greater than 1000 bp were used to predict protein-encoding ORFs through Prodigal v2.0[20]. Functional annotation of the predicted ORFs was achieved using RAPSearch2[21] (cutoff e-value of 1 × 10-5 and minimum alignment length 20) employing the NCBI reference sequences (RefSeq) database together with hidden Markov model profile (HMM) searches (http://hmmer.org/) against the manually curated Pfam-A database (cutoff e-value of 1 × 10-10). Subsequently, tRNA genes were detected through tRNAscan-SE v1.4[22], and rRNA genes were identified using RNAmmer v1.2[23].

Comparative genome analyses

A pan-genomic analysis was performed using the Pangenome Analysis Pipeline (PGAP)[22] on the 34 strains of the genus Bifidobacterium already present in the IPDB from a previous study[18] and the 15 lactobacilli, the two strains of S. thermophilus, and the single strain of H. coagulans integrated into this new version of the IPDB [Supplementary Table 1]. Specifically, the proteome associated with each of these strains was classified through the gene family (GF) method into functional gene clusters by performing a pairwise protein similarity search using the software BLAST v2.2.28+ software (value and cutoff of 1 × 10-10 and exhibiting at least 50% identity on at least 80% of both protein sequences). Thus, the obtained protein data were used to assign the proteins to clusters of orthologous groups (COGs) using the Markov clustering algorithm based on graph theory (MCL)[24]. In this way, and with the use of a presence/absence matrix comprising the set of COGs identified at the level of the analyzed genomes (Linux command line “./PGAP.pl--strains [input_strain_list]--input input_path/--output output_path/--thread 20--identity 0.5--coverage 0.8--grappolo--method GF--evolution--pangenome”), the pan-genomic profile was reconstructed. The protein families shared among all the genomes were identified as part of the core genome, while protein families present in singleton were identified as Truly Unique Genes (TUGs).

Average pairwise nucleotide identity was calculated using the fastANI software[25].

Phylogenomic analysis

To study the phylogenetic relationships within the lactobacilli and the Streptococcus and the Heyndrickxia genera, the protein sequences shared among the members of the same genus were aligned using MAFFT software[26]. With ClustalW v2.1, using the neighbor-joining method, and with iTOL v6.8.1 (interactive Tree Of Life), an online tool for viewing, annotating, and managing phylogenetic trees, it was possible to obtain a graphic representation of the phylogenetic trees.

Glycobiome prediction and identification of genes potentially involved in probiotic traits

The collected genomic sequences of the 15 lactobacilli and of two strains of S. thermophilus, as well as that corresponding to H. coagulans UNIQUE IS-2, were analyzed to evaluate the possible presence of genes involved in persistence and survival in the gastrointestinal tract and microbial metabolic activity with potential roles in promoting the host’s health. Specifically, screening of genetic traits involved in the production of pili, S-layers, adhesins, and teichoic acids was performed through BLASTp sequence similarity searches[27] (cutoff e-value of 1 × 10-10) exploiting ad hoc databases built with well-known protein sequences retrieved from NCBI database, as previously performed[17]. The designation “hypothetical protein” refers to genes whose specific function has not yet been fully characterized. However, using screening approaches based on homology searches with known functional databases, it was possible to identify structural domains within these hypothetical proteins that suggest their potential function. The location of gene clusters encoding exopolysaccharides (EPS) structure was predicted based on homology with known sequences encoding EPS. The glycosyltransferase priming gene, crucial for forming such structures, was manually verified to distinguish these clusters from other glycan clusters. In addition, the absence of genes characteristic of other glycan clusters was assessed. BAGEL 4.0[28] and AntiSMASH 5.0[29] were used to predict antimicrobial compounds, while the Cazy database (December 2023 update) was exploited to identify glycosyl hydrolase families[30]. Genes encoding the enzymes responsible for the last step in the SCFA, and vitamin biosynthetic pathways were retrieved from the MetaCyc database[31], and their presence in the collected probiotic genomes was evaluated through local BLASTp searches. All the results were then manually validated to eliminate possible false positives.

RESULTS AND DISCUSSION

Retrieval of genomic sequences corresponding with probiotics

In a previous study[17], a genome database named the IPDB was built, including the genome sequences of Bifidobacterium genus members used in commercial probiotic products. As an extension of the IPDB, we have enriched the database with the chromosome sequences of several lactobacilli as well as those of strains belonging to the genus Heyndrickxia (previously belonging to the Bacillus genus) and Streptococcus members currently used in bacteria-based supplements available in the global probiotic market.

Specifically, we performed exhaustive research on probiotic product labels to identify those strains used in bacteria-based products currently available worldwide, obtaining 70 different strain IDs belonging to the species listed above [Supplementary Table 2]. However, out of these, only the different lactobacilli selected for the study, the two strains of S. thermophilus species, and one strain of H. coagulans [formerly known as Bacillus coagulans or Weizmannia coagulans][32-35] were suitable for the subsequent analyses as their associated genomes (complete or drafts) were available in public repositories such as the NCBI genome database [Supplementary Table 2]. Accordingly, although numerous studies have analyzed the genetic makeup of different probiotics to identify genetic factors related to their probiotic characteristics, there is still a need for more detailed and integrated analyses that can comprehensively elucidate the genetic basis underlying the health benefits these bacteria can confer. Indeed, access to essential genetic information is vital for capturing the mechanisms underlying the interactions between probiotics and the human host and identifying potential risks associated with specific strains.

The 18 genome sequences included in the study were de novo annotated and integrated into the IPDB. The complete list of the bacterial strains and their general genomic features are reported in Table 1. This updated version of the IPDB, encompassing genome sequences as well as manually curated information of strain-specific functional particulars, is freely accessible at http://probiogenomics.unipr.it/cmu/ (direct download at http://probiogenomics.unipr.it/files/IPDB_latest.zip).

Phylogenomic and comparative genomic analyses of bacterial chromosomes included in the IPDB

The genomes of 18 commercially distributed probiotic strains were employed to perform comparative genomic analyses to identify intra- and inter-species genetic peculiarities. The Average Nucleotide Identity (ANI) analysis performed upon alignment of lactobacilli genomes used in probiotic supplements highlighted a higher degree of genome identity among the five strains of L. acidophilus (average of 99.98%) as well as among three (ATCC53103, GG, and BIO6870) of the five strains belonging to the L. rhamnosus species (mean of 99.99%) [Supplementary Table 3]. These results suggest that not only L. acidophilus strains, known for their genome identity among commercial isolates[36], but also identical strains of L. rhamnosus could have been deposited and commercialized as probiotics with different labels. This observation may limit comparisons between strains and necessitates a detailed taxonomic review to clarify strain identities.

To provide a comprehensive perspective on the genetic diversity of various lactobacilli and of the 34 strains of Bifidobacterium already included in the previous version of the IPDB, the two strains of S. thermophilus and the strain of H. coagulans included in this new version of the IPDB compared to others, we performed species-level pangenome and phylogenomic analyses incorporating additional complete genome sequences available in public databases and pertaining to the same probiotic species selected for this study [Supplementary Table 1]. This approach enabled us to compare many conspecific genome sequences to identify actual genetic variations between these.

The pangenomic analysis highlighted a variable number of TUGs, ranging from 12 to 403, corresponding to Bifidobacterium animalis subsp. lactis SD5219 and B. longum subsp. infantis EVC001, respectively [Supplementary Table 4]. However, within the lactobacilli, Ligilactobacillus salivarius (L. salivarius) BIO6313 and L. reuteri RC-14 were the bacterial strains with the largest TUGs (175 and 186, respectively). In contrast, L. acidophilus is similar to what was previously reported for Bifidobacterium animalis subsp. lactis[36] is confirmed to be an isogenic species characterized by extremely low diversity and a high degree of genomic conservation.

In accordance with the relatively low number of identified strain-specific genetic traits, our phylogenomic analysis based on the core genome revealed that the genomes of lactobacilli and the H. coagulans strain used in probiotic supplements are uniformly placed within their respective species-specific phylogenetic clusters [Figure 1A and B]. Conversely, the genome of S. thermophilus St-6, harboring 316 TUGs [Supplementary Table 4], is placed on a distinct branch within the phylogenomic tree of its species [Figure 1C]. Although some caution is needed when interpreting phylogenomic trees reconstructed with both completed and draft bacterial chromosomes, from our analysis, it seems plausible that the probiotic strain S. thermophilus St-6, unlike S. thermophilus TH-4, may harbor genetic traits that distinguish it from other conspecific genomes [Figure 1C]. The detailed analysis of the specific differences between the strains is an excellent starting point for future studies, as it may provide new insights into the unique characteristics of the various probiotic strains and their application potential.

Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database

Figure 1. Phylogenomic trees of the bacterial genera added in this study to the IPDB. Panels (A-C) show the phylogenomic tree of the lactobacilli and of Heyndrickxia coagulans and Streptococcus thermophilus genus, respectively. All trees were constructed based on species-specific core genomes derived from a comparison of strains used in commercial probiotic formulations (highlighted in colored text) along with additional publicly available complete genome sequences of the same species. IPDB: Integrated Probiotic Database.

Genes involved in persistence in the gastrointestinal tract

The distribution of various genetic traits related to the ability to persist in the gastrointestinal tract and to induce beneficial effects in the host was investigated among the selected probiotic strains of lactobacilli and the S. thermophilus and H. coagulans genus, as well as among members of Bifidobacterium genus already included in the IPDB.

Specifically, the ability to adhere, at least temporarily, to the host’s gastrointestinal mucosa is a highly desired feature for probiotic strains, allowing for optimal adaptation to and persistence in the new niches encountered in the host[37]. Specific bacterial extracellular structures are recognized for their pivotal role in gut colonization, biofilm formation, and modulation of host immune system responses[38]. For these reasons, in this study, we explored the arsenal of genes encoding pili, S-layer proteins, mucus-binding adhesins, teichoic acids, and exopolysaccharides within the genome sequences of the selected probiotic strains.

Variability in pili-encoding gene sequences

Bacterial pili are filamentous appendages extending from the cell surface, exerting pivotal functions in interaction and adhesion to host cells, other bacteria, or environmental surfaces[39,40]. Since previous in vitro studies have led to the identification of pili in bacterial strains[41], we analyzed the genomes of the 18 probiotic strains included in this study to assess the presence of gene sequences encoding for pili. Our genome-wide explorations revealed that all the bacterial genomes considered possibly produced external adhesion proteins. In particular, lactobacilli generally encode cell wall anchoring proteins that harbor LPXTG motifs, which are already known among LAB as motifs that can enhance the properties and duration of bacterial colonization in the gastrointestinal tract and their probiotic effects on the host[42][ Supplementary Table 5]. At the same time, only closely related members of the L. casei and Lacticaseibacillus paracasei (L. paracasei) species, along with L. rhamnosus GG and BIO6870 strains, demonstrated the presence of two distinct pili sortase-dependent encoding islands known as SpaFED and SpaCBA pilus operons known for their involvement in intestinal mucus adhesion[43][ Supplementary Table 5]. In contrast, other examined L. rhamnosus strains (GR1 and HN001) appeared to possess only the SpaFED locus [Supplementary Table 5]. In accordance with previous observations[44,45], transposon genes are flanking the SpaCBA cluster in L. rhamnosus GG but are absent in the L. casei BIO5773 genome, suggesting that SpaCBA in L. rhamnosus GG might be acquired through horizontal gene transfer (HGT) events.

It is worth mentioning that strain-dependent differences in the pili-encoding gene clusters were also observed within members of the Bifidobacterium genus previously included in the IPDB[17], showing a noticeable divergence of genetic potential for sortase-dependent (SD) pili and a high level of genetic conservation of the Tight Adherence pili encoding locus (Tad locus).

Genetic potential for mucus-binding adhesins and S-layer proteins

Similar to the pili structures described above, adhesins and S-layer proteins on the bacterium’s outer surface facilitate interactions between the bacteria and the external environment. They probably play a role in adhesion to various substrates, mucins, and host cells and in processes involving intimate interaction with other bacteria[46,47]. Based on our in-silico investigation, the lactobacilli analyzed were predicted to encode a wide range of host-specific adhesion proteins, from one to 11, depending on the species [Supplementary Table 6]. Specifically, most lactobacilli appeared to express multiple adhesin types interacting with mucin (Mub domain), fibronectin (Fbp domain), or fibrinogen protein, with L. acidophilus and L. gasseri showing the greatest genetic potential to produce proteinaceous host-specific adhesion factors [Supplementary Table 6]. The specific binding abilities of these extracellular proteins, particularly Mub proteins, and FbpA-B from L. acidophilus, have been proposed to play crucial roles in facilitating effective colonization and competitively displacing gut pathogens[48]. In contrast, among the screened bacterial genomes, S-layer-associated proteins (SLPs and SLAPs) were precisely identified only in those from L. acidophilus species, underlying differences in possible mucus- and microbe-microbe interactions which could significantly affect the probiotic potential of different lactobacilli [Supplementary Table 7]. Indeed, previous studies have shown that S-layer proteins are essential for the probiotic effect of certain lactobacilli, as they enable colonization of the intestine and are responsible for their immunomodulatory properties[45], as also confirmed in vitro studies[49]. Furthermore, through homology analysis between these sequences, we could rule out that the sequences belonged to the same strain, given the low percentage of identity found (average homology of 42%).

In parallel, the same analysis performed on the two strains of S. thermophilus included in the extended version of the IPDB database showed that they lacked coding sequences for both S-layer and pili proteins as well as genetic determinants for adhesion on mucin, thus casting doubts on their ability to competitively colonize and persist in the human gut [Supplementary Tables 5-7], as previously demonstrated[50].

Repertoire of lipoteichoic acids and exopolysaccharide biosynthesis gene clusters

In Gram-positive bacteria, the cell wall is decorated with additional surface components, including lipoteichoic acids (LTAs) and EPS, exerting crucial roles in bacteria-host crosstalk by mediating immune response and anti-inflammatory functions[51-53]. Therefore, information at the genome level concerning such capsular polysaccharides derived from probiotics is important. These investigations showed that all probiotic strains included in the IPDB possessed putative LTAs-related genes coding for LTA synthase, LTA-transporters, and D- alanylation protein [Figure 2 and Supplementary Table 8].

Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database

Figure 2. Investigation of the microbial genetic traits involved in LTA, EPS, and BSH biosynthesis. The heat map illustrates the genome-level presence (colored box) or absence (black box) of genes involved in the biosynthesis of LTA (green), EPS (blue), and BSH (pink). The color scale reflects the number of significant sequences found for each function analyzed: black indicates a complete absence of gene function in the probiotic under investigation, darker colors indicate a small number of significant sequences identified (with a value of 1 indicating minimal presence), and lighter colors indicate a larger number of significant sequences identified for the gene function analyzed. LTA: Lipoteichoic acid; EPS: exopolysaccharides; BSH: bile salt hydrolase.

The increased number of putative LTA gene islands in L. acidophilus members, particularly in LA1, La-14, La-5, and NCFM strains, could contribute to their anti-inflammatory effects and immunomodulatory benefits[54,55]. However, although the contribution of lactobacilli LTAs in modulating the intestinal innate immune response has been demonstrated[56,57], more in-depth genomic examination of these genetic determinants is needed to better understand their interaction with the immune system.

In contrast, the S. thermophilus strains and the H. coagulans strain showed fewer gene sequences coding for LTA genome-wide. This result might suggest that these bacteria might have a different ability to interact with the host immune system than L. acidophilus strains.

The genome-wide analysis was then extended by evaluating the possible presence of sequences coding for EPS [Figure 2, Supplementary Table 9], the presence of which in LAB has already been evidenced by in vitro studies[58,59]. Beyond being present in all bifidobacterial strains previously investigated[17], putative gene clusters encoding EPS were found in all analyzed lactobacilli genomes, as well as S. thermophilus and H. coagulans species, confirming the extensive history of knowledge regarding the high EPS production by these bacteria commonly employed in probiotic formulations[60-62]. Notably, previous studies[55] have established that EPSs are present in LAB and highlighted their significant impact on immune cells. They can activate macrophages and stimulate lymphocyte proliferation. Therefore, the presence of EPS in bacterial cells is a crucial factor to consider when analyzing these microorganisms’ probiotic potential. However, a marked variation in the organization of the genes in the EPS clusters was observed among the considered bacterial chromosomes. This result is consistent with previous studies reporting high variability of EPS clusters between different lactobacilli genomes and different Streptococcus genomes[63,64]. Previous studies showed the existence of six different EPS genotypes in S. thermophilus strains[65] and a highly variable genetic composition in EPS-encoding gene clusters depending on the habitat of origin of the lactobacilli strains considered[63,64]. In particular, a high degree of conservation emerged for gene sequences directly involved in EPS biosynthesis, such as epsA, epsB, epsC, epsD, and epsE, while the products genes supporting this process by encoding enzymes that transfer I sugar monomers, ensuring passage through the membrane and polymerization, showed high variability in the number and composition of protein families.

Bile salt hydrolase encoding genes

Another essential bacterial trait needed to survive across the host gastrointestinal tract is the ability to detoxify bile salts through specific chemical modifications[66]. This function is entrusted to the gene product of bile salt hydrolase (BSH), the presence of which has been verified in several bacterial genera used as probiotics, including in the genomes of lactobacilli[67] and has long been recognized as a selection criterion for defining potential probiotics. The BSH enzyme plays a pivotal role in bile acid metabolism and enables bacteria expressing it to benefit host health by positively influencing the intestinal metabolome, improving fat digestion, increasing the bioavailability of fat-soluble nutrients, and providing benefits on lipid metabolism[67]. Screening for BSH genes within the bacterial chromosomes included in the IPDB showed that 100% of lactobacilli and bifidobacteria possessed such coding sequences, which, on the contrary, was absent in S. thermophilus and H. coagulans genomes [Figure 2, Supplementary Table 10]. Nevertheless, it is noteworthy to mention that the unique composition of spores morphology can provide H. coagulans members with high tolerance to acidic conditions in the stomach upon ingestion[68].

Overall, results from our genome-based investigations highlighted a high inter-strains variability in the genetic potential for microbe- and host-microbe interactions and, consequently, in their expected performance to adhere and persist in the host’s gastrointestinal tract as well as in the stimulation of the immune system. Accordingly, these results highlighted the need for genomic-based approaches to understand and predict the functionality of probiotics at the strain level.

Genes involved in microbial functionalities with health-promoting roles

Along external structures involved in mechanical interactions with the surrounding environment, bacteria are capable of producing various primary and secondary metabolites, including glycosidic hydrolases (GHs) and bacteriocins, that can greatly influence the host metabolism as well as microbe-microbe relationships[69-72].

Genetic potential for bacteriocins production

Lactic acid bacteria can produce protein compounds known as bacteriocins, which have been shown to have bactericidal or bacteriostatic effects on closely related bacteria or others, including pathogenic bacteria. In particular, previous studies have shown that bacteriocins can inhibit the adhesion of pathogenic microorganisms in the host due to their antimicrobial action. In detail, they can induce pore formation in the cell wall of the target organism or inhibit cell wall biosynthesis, causing its death[73]. For this reason, bacteriocin production is generally regarded as a desirable probiotic trait, and numerous bacteriocins have been isolated over time, mainly from lactobacilli[74-76]. Based on our screening, bacteriocin and bacteriocin-related coding sequences were present in the genome of all microbial strains analyzed in this study, with a putative higher bacteriocinogenic potential in lactobacilli, particularly those from L. acidophilus and L. rhamnosus species [Supplementary Table 11]. These divergences across probiotics suggested an unequal distribution of bacteriocin production potential, likely leading to varied abilities to compete and establish within a complex community, such as the human gut microbiota.

Differences in carbohydrate metabolism

To establish and proliferate in the host gut environment, bacteria exploit a great variety of GHs to metabolize complex carbohydrates and derive nutrients necessary for their growth, exerting simultaneously beneficial effects on gastrointestinal homeostasis[77]. In this regard, understanding the repertoire of genes involved in carbohydrate metabolism, i.e., the glycobiome, within probiotic strains is of paramount importance to gain insights into the metabolic pathways that contribute to the health-promoting activities of bacteria, enabling targeted and strategic employment of the therapeutic potential of these microorganisms[77].

Compared with the probiotic Bifidobacterium strains previously included in the IPDB, which were enriched in gene sequences encoding GHs responsible for the degradation of breastmilk polysaccharides and intestinal mucins, lactobacilli, and S. thermophilus, and H. coagulans species have exhibited a preferential commitment to complex plant-derived polysaccharides. Specifically, among the analyzed genomes, the most widely distributed glycoside hydrolases were GH13 and GH73 [Figure 3, Supplementary Tables 12 and 13], while the highest number of sequences were recorded for GH13 and GH1 (114 and 88, respectively) [Figure 3,Supplementary Tables 12 and 13], whose members, as noted on the public CAZy database[78], are mainly active on substrates containing α-glucoside linkages, such as starch, and involved in converting cellulose into glucose, respectively[79,80].

Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database

Figure 3. Glycobiome analysis of the genome sequences newly included in the IPDB. The bubble chart reports the number of gene sequences corresponding to various GHs identified within the genome sequences examined in this study. For each investigated genomes, the size of the circles is proportional to the number of genes corresponding to a given GH. IPDB: Integrated Probiotic Database; GHs: glycosidic hydrolases.

However, glycobiome analysis also showed marked interspecies differences with species-associated peculiarities [Figure 3, Supplementary Tables 12 and 13]. For example, L. acidophilus strains were characterized by family GH42 coding sequences, whose members are primarily beta-galactosidases metabolizing lactose to galactose and glucose[3].

Genes involved in organic acids production

As a result of bacterial carbohydrate metabolism, lactobacilli and bifidobacteria produce organic acids, mainly acetate and lactate[81,82]. These metabolites have been associated with positive effects on intestinal homeostasis, immune response, and inhibition of potential pathogens due to the decrease in pH[83-85]. Moreover, it has been proposed that acetate could activate lactobacilli bacteriocin biosynthesis[86]. According to the well-characterized key synthesis genes, all lactobacilli and Bifidobacterium genera members, as well as S. thermophilus and H. coagulans UNIQUE IS-2 strains, appeared able to produce acetate and L-lactate, with evident inter and intra-species variability [Figure 4, Supplementary Table 13]. Only lactobacilli and S. thermophilus strains showed coding sequences for D-lactate [Figure 4, Supplementary Table 14]. Interestingly, gut commensal-derived D-lactate recently showed stronger immune regulation effects than L-lactate[87,88], allowing us to suggest different abilities among probiotics to ameliorate gut dysbiosis and protect the host from enteropathogenic infections.

Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database

Figure 4. Investigation of the microbial genetic traits involved in SCFAs and vitamin biosynthesis. The heat map illustrates the genome-level presence (colored box) or absence (black box) of genes involved in the biosynthesis of organic acids (violet) and B-group vitamins (light blue). These investigations are based on the search for the gene encoding the final enzyme in the pathway, which is specified through the EC number reported on the first row. SCFAs: Short-chain fatty acids; EC: Enzyme Commission.

In-silico prediction of vitamin biosynthesis

Certain bacteria synthesize water-soluble vitamins during their microbial metabolism, such as those of the B group[89,90]. Accordingly, we assessed the presence of genes encoding enzymes involved in the final step of group B vitamin pathways in the genomes of lactobacilli, S. thermophilus, and H. coagulans UNIQUE IS-2, extending the analysis to the Bifidobacterium strains already included in the IPDB[17]. Our results showed marked intraspecies differences, with the H. coagulans UNIQUE IS-2 strain appearing as the strain with the most extensive genetic potential for vitamin biosynthesis [Figure 4, Supplementary Table 14]. In contrast, although certain strains of L. acidophilus have been reported as being able to increase folate in fermented milk[89], the genomes of L. acidophilus strains collected in the IPDB lack the genes involved in folate biosynthesis [Figure 4, Supplementary Table 14], while the genome sequences of Bifidobacterium species contained the coding sequences for vitamin B1, B3, B6, and B9 [Figure 4, Supplementary Table 14].

Accordingly, the differences that emerged in bacterial vitamin biosynthetic potential may reflect strain-dependent metabolism that, thus, should be considered when designing multi-species probiotic formulations to optimize their beneficial impact on host health.

Probiotic strains: analysis of antibiotic resistance and virulence factors for safety

When using a bacterial strain as a probiotic, it is paramount to assess its safety and risk/benefit ratio[90]. To date, three main factors are considered in selecting a strain as a probiotic, including the general aspects of the strain, including origin, identity, safety, non-pathogenicity, and resistance; technical elements, such as growth properties in vitro and during processing, ability to survive and remain viable during transport and storage; and functional aspects and its advantageous characteristics[91]. In particular, the safety and non-pathogenicity of a bacterial strain intended for probiotic use are considered factors of primary importance[91]. Consequently, assessing the presence of genes that confer antibiotic resistance could support in vivo and in vitro investigations. In addition, such assessment is crucial to ensure consumer safety and prevent the spread of antibiotic resistance, which seriously threatens public health.

In this context, the 18 probiotic strains integrated into this new version of the IPDB were examined for possible determinants of antibiotic resistance and virulence factors [Supplementary Tables 15 and 16]. Although our in silico analyses are for predictive purposes only, this approach may provide a starting point for future in vitro validations. The results showed that the St-6 and TH-4 strains of S. thermophilus possessed genes presumably involved in resistance against several classes of antibiotics [Supplementary Table 15], including rifampin, aminocoumarin antibiotics, as well as penicillin and other beta-lactam antibiotics. In addition, only strain St-6 had a 23S rRNA methyltransferase, which acts on the dimethylation of 23S rRNA, conferring resistance to macrolides, lincosamides, and streptogramins B[92,93] [Supplementary Table 15]. Performing the same analysis within lactobacilli, only strain RC-14 of L. reuteri was predicted to have a gene encoding for a Lincosamide nucleotidyltransferase (LNUA), which adenylates the hydroxyl group of lincosamides, modifying their structure and preventing their binding to their target [Supplementary Table 15].

Concerning virulence-associated factors, we identified two key genes that deserve attention for their potential role in modulating the host immune system. Specifically, strain BIO6313 of L. salivarius was predicted to have specific sequences (lgtC) belonging to the LOS system (VF0044), which is involved in the immune modulation of the host, in which it can activate strong inflammatory responses[94]. In addition, the two S. thermophilus strains were shown to possess a UTP-glucose-1-phosphate uridyl-transferase, which can catalyze UDP-glucose pyrophosphorylase production. Previous studies have emphasized this enzyme’s importance in hyaluronic acid capsule synthesis[89], which protects bacteria from phagocytosis and promotes the evasion mechanisms of the host immune system.

These results suggest that L. salivarius BIO6313 and S. thermophilus strains (St-6 and TH-4) may possess virulence factors capable of modulating the host immune response [Supplementary Table 16]. Although these observations are based on in silico analyses and need further experimental validation, they may suggest that the probiotics tested are generally free of virulence and antibiotic-resistance genes.

Analysis of genes associated with prebiotics and sugars of interest

The interaction between the gut microbiota and food components directly affects the health and well-being of host organisms[95]. Prebiotics and specific sugars are known to play a crucial role in modulating the composition and activity of the gut microbiota[96,97]. Some prebiotics such as fructo-oligosaccharides (FOS), xylo-oligosaccharides (XOS), manno-oligosaccharides (MOS), and raffinose are known for their ability to stimulate the growth of beneficial bacteria. In contrast, although not classified as prebiotics, lactose and glycogen still significantly impact host well-being. Lactose can be utilized by lactic acid bacteria as a source of energy and carbon via lactic fermentation, offering potential benefits for lactose-intolerant individuals who cannot independently metabolize this sugar due to deficiency of the enzyme β-galactosidase[98]. At the same time, precedent studies[99] have shown that the ability of bacteria to metabolize glycogen contributes to their retention and probiotic activities in the gastrointestinal tract.

Genomic analysis of genes involved in metabolizing prebiotics and sugars is essential for understanding the functionality of gut bacteria. In the new IPDB, we evaluated the presence of these sequences in 15 strains of lactobacilli, two strains of Streptococcus, and the Heyndrickxia strain. Our findings showed that L. gasseri strain Lpc-37 contains specific gene sequences for a fructan beta-fructosidase [Supplementary Table 17]. This enzyme breaks down fructans into simpler fructose units, facilitating their absorption or fermentation by other intestinal bacteria, providing significant benefits in reducing symptoms associated with gastrointestinal disorders. In addition, strains BIO6870, GG, HN001, GR-1 of L. rhamnosus, strain ATCC53103 of L. reuteri, and strain BIO5773 of L. acidophilus have genes for xylanase. This enzyme degrades xylan to XOS, a potential prebiotic that stimulates microbial growth [Supplementary Table 18]. The H. coagulans Unique IS-2 strain possesses genes coding for enzymes that remove acetyl groups from polysaccharides, suggesting a mechanism for influencing the structure of complex dietary polysaccharides and modulating gut microbial ecology [Supplementary Table 17]. This enzymatic activity results in the release, in the gastrointestinal tract (GIT), of simpler substrates that could be used by other members of the gut microbial community as nutrient sources, thus promoting the growth of beneficial bacteria that are not directly capable of metabolizing complex polysaccharides and contributing to the development of a more balanced and diverse gut environment, promoting host health. It is, moreover, relevant to note that all strains of L. rhamnosus, Unique IS-2 strain of H. coagulans, BIO6369 strain of L. casei, RC-14 strain of L. paracasei, ATCC53103 strain of L. reuteri, Lpc-32 strain of L. gasseri, and BIO6307 and BIO5773 strains of L. acidophilus have genes for alpha-galactosidase [Supplementary Table 19]. This enzyme degrades raffinose, a complex sugar found in various foods, potentially improving the digestion of this sugar in the gut and reducing gastrointestinal disorders associated with its fermentation.

A detailed analysis of the metabolic capacity of the included probiotic strains revealed that all strains of L. acidophilus, strain St-6 of S. thermophilus, and strain TH-4 of L. salivarius possess gene sequences for enzymes that degrade lactose and glycogen [Supplementary Tables 20 and 21], complex sugars widely present in the human diet. In contrast, L. rhamnosus strains, L. reuteri strain ATCC53103, L. gasseri strain Lpc-37, and H. coagulans strain have genes for enzymes capable of degrading glycogen but not lactose [Supplementary Table 21].

Conclusion

In this study, we retrieved 18 publicly available genome sequences of lactobacilli and S. thermophilus, and H. coagulans (formerly Bacillus coagulans) species currently used in many probiotic supplements that were used for genomics investigations to expand the IPDB previously build[17]. However, it is important to note that the number of sequences used is limited by the availability of data in public databases for probiotics used in commercial products, recognizing this as a significant constraint. As the genomes of bacterial species not yet included in the IPDB become available, they can be used for further studies, further expanding our understanding of the genomic properties of probiotics. By examining and comparing these strains, we recognized noteworthy differences in their genetic makeup with possible consequences on their health-promoting activities and mechanisms of action. Specifically, strain-dependent genetic potentials were observed for external adhesive proteins such as pili and S-layer components and metabolic activities, including carbohydrate metabolism and vitamin biosynthesis. Remarkably, such differences could impact the ability of bacteria to adhere to host surfaces and modulate metabolic processes, ultimately affecting their overall functional outcomes in promoting health.

Considering the rapid advances in research on the human gut microbiome and probiotic fields[83,84], we believe that it is essential to account for genetic variations related to probiotic properties in the formulation of multi-species probiotics to amplify and optimize their positive effects on host health. To achieve this goal, extensive whole-genome sequencing is needed to improve our understanding of the genetic content of the strains used in probiotic products[85]. Indeed, through detailed knowledge of the different metabolic capabilities of bacterial strains, we can strategically tailor probiotic treatments and adapt probiotic formulations to meet specific host health needs more effectively. However, it is essential to emphasize that using a specific bacterial strain as a probiotic cannot be based solely on its genome content but on its impact on health, which must be demonstrated in well-designed and controlled interventional studies. Consequently, it is paramount to associate in silico studies with functional and phenotypic investigations before any probiotic intervention.

DECLARATIONS

Acknowledgments

We thank GenProbio Srl for the financial support of the Laboratory of Probiogenomics.

Part of this research was conducted using the High-Performance Computing (HPC) facility at the University of Parma.

Authors’ contributions

Data analysis and manuscript writing: Tarracchini C

Data acquisition and data analysis: Petraro S

Data curation: Lugli GA, Mancabelli L, Fontana F

Conceptualization, supervision and manuscript editing: Turroni F, Milani C, Ventura M

Availability of data and materials

The IPDB can be accessed at http://probiogenomics.unipr.it/cmu/ (direct download at http://probiogenomics.unipr.it/files/IPDB_latest.zip).

Financial support and sponsorship

Fontana F was funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3 - Call for tender No. 341 of 15 March 2022 of Italian Ministry of University and Research funded by the European Union - NextGenerationEU; Award Number: Project code PE00000003, Concession Decree No. 1550 of 11 October 2022 adopted by the Italian Ministry of University and Research, CUP D93C22000890001, Project title “ON Foods - Research and innovation network on food and nutrition Sustainability, Safety and Security - Working ON Foods”. Postdoctoral research fellowship of Fontana F was funded by the “Fund for the National Research Programme and Projects of Significant National Interest (PRIN)”, Ministry of Research and University (20229LEB99). Ventura M was funded by the “Fund for the National Research Programme and Projects of Significant National Interest (PRIN) ”, Ministry of Research and Universities (20229LEB99).

Conflicts of interest

Lugli GA, Mancabelli L, Turroni F, Ventura M, and Milani C are Editorial Board members of the journal Microbiome Research Reports. Ventura M is the contact person at GenProbio Srl; Financial support by GenProbio Srl is independent from the results of this article. The results and conclusions presented in the article were not influenced in any way by the financial support received. Other authors have declared that there are no conflicts of interest.

Ethical approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Copyright

© The Author(s) 2024.

Supplementary Materials

REFERENCES

1. Hill C, Guarner F, Reid G, et al. Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nat Rev Gastroenterol Hepatol 2014;11:506-14.

2. Mazziotta C, Tognon M, Martini F, Torreggiani E, Rotondo JC. Probiotics mechanism of action on immune cells and beneficial effects on human health. Cells 2023;12:184.

3. Markowiak-Kopeć P, Śliżewska K. The effect of probiotics on the production of short-chain fatty acids by human intestinal microbiome. Nutrients 2020;12:1107.

4. Chávarri M, Diez-gutiérrez L, Marañón I, del Carmen Villarán M, Barrón LJR. Chapter 27 - The role of probiotics in nutritional health: probiotics as nutribiotics. In: Probiotics in the prevention and management of human diseases. Elsevier; 2022. pp. 397-415.

5. Barkhidarian B, Roldos L, Iskandar MM, Saedisomeolia A, Kubow S. Probiotic supplementation and micronutrient status in healthy subjects: a systematic review of clinical trials. Nutrients 2021;13:3001.

6. van Zyl WF, Deane SM, Dicks LMT. Molecular insights into probiotic mechanisms of action employed against intestinal pathogenic bacteria. Gut Microbes 2020;12:1831339.

7. Sanozky-Dawes R, Barrangou R. Lactobacillus, glycans and drivers of health in the vaginal microbiome. Microbiome Res Rep 2022;1:18.

8. Ruiz L, Margolles A, Sánchez B. Bile resistance mechanisms in Lactobacillus and Bifidobacterium. Front Microbiol 2013;4:396.

9. Bezkorovainy A. Probiotics: determinants of survival and growth in the gut. Am J Clin Nutr 2001;73:399S-405S.

10. Holzapfel WH, Haberer P, Geisen R, Björkroth J, Schillinger U. Taxonomy and important features of probiotic microorganisms in food and nutrition. Am J Clin Nutr 2001;73:365s-73s.

11. Fijan S. Microorganisms with claimed probiotic properties: an overview of recent literature. Int J Environ Res Public Health 2014;11:4745-67.

12. Goktepe I, Juneja VK, Ahmedna M. Probiotics in food safety and human health. 1st ed. CRC Press; 2005.

13. Chen L, Zou Y, Peng J, et al. Lactobacillus acidophilus suppresses colitis-associated activation of the IL-23/Th17 axis. J Immunol Res 2015;2015:909514.

14. Cortes-Perez NG, Lozano-Ojalvo D, Maiga MA, Hazebrouck S, Adel-Patient K. Intragastric administration of Lactobacillus casei BL23 induces regulatory FoxP3+RORγt+ T cells subset in mice. Benef Microbes 2017;8:433-8.

15. Karczewski J, Troost FJ, Konings I, et al. Regulation of human epithelial tight junction proteins by Lactobacillus plantarum in vivo and protective effects on the epithelial barrier. Am J Physiol Gastrointest Liver Physiol 2010;298:G851-9.

16. Garcia-Gonzalez N, Bottacini F, van Sinderen D, Gahan CGM, Corsetti A. Comparative genomics of Lactiplantibacillus plantarum: insights into probiotic markers in strains isolated from the human gastrointestinal tract and fermented foods. Front Microbiol 2022;13:854266.

17. Tarracchini C, Viglioli M, Lugli GA, et al. The Integrated Probiotic Database: a genomic compendium of bifidobacterial health-promoting strains. Microbiome Res Rep 2022;1:9.

18. Lugli GA, Fontana F, Tarracchini C, et al. MEGAnnotator2: a pipeline for the assembly and annotation of microbial genomes. Microbiome Res Rep 2023;2:15.

19. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010;11:119.

20. Zhao Y, Tang H, Ye Y. RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data. Bioinformatics 2012;28:125-6.

21. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 1997;25:955-64.

22. Lagesen K, Hallin P, Rødland EA, Staerfeldt HH, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res 2007;35:3100-8.

23. Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 2002;30:1575-84.

24. Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018;9:5114.

25. Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res 2002;30:3059-66.

26. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990;215:403-10.

27. Heel AJ, de Jong A, Song C, Viel JH, Kok J, Kuipers OP. BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins. Nucleic Acids Res 2018;46:W278-81.

28. Blin K, Shaw S, Augustijn HE, et al. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation. Nucleic Acids Res 2023;51:W46-50.

29. Drula E, Garron ML, Dogan S, Lombard V, Henrissat B, Terrapon N. The carbohydrate-active enzyme database: functions and literature. Nucleic Acids Res 2022;50:D571-7.

30. Caspi R, Billington R, Keseler IM, et al. The MetaCyc database of metabolic pathways and enzymes - a 2019 update. Nucleic Acids Res 2020;48:D445-53.

31. Zhang S, Li P, Lee S, Wang Y, Tan C, Shang N. Weizmannia coagulans: an ideal probiotic for gut health. Food Sci Hum Wellness 2024;13:16-226.

32. Zhu M, Zhu J, Fang S, Zhao B. Complete genome sequence of Heyndrickxia (Bacillus) coagulans BC99 isolated from a fecal sample of a healthy infant. Microbiol Resour Announc 2024;13:e0044923.

33. Zheng Z, Jiang T, Zou L, et al. Simultaneous consumption of cellobiose and xylose by Bacillus coagulans to circumvent glucose repression and identification of its cellobiose-assimilating operons. Biotechnol Biofuels 2018;11:320.

34. Juturu V, Wu JC. Production of high concentration of l-lactic acid from oil palm empty fruit bunch by thermophilic Bacillus coagulans JI12. Biotechnol Appl Biochem 2018;65:145-9.

35. Loquasto JR, Barrangou R, Dudley EG, Stahl B, Chen C, Roberts RF. Bifidobacterium animalis subsp. lactis ATCC 27673 is a genomically unique strain within its conserved subspecies. Appl Environ Microbiol 2013;79:6903-10.

36. Han S, Lu Y, Xie J, et al. Probiotic gastrointestinal transit and colonization after oral administration: a long journey. Front Cell Infect Microbiol 2021;11:609722.

37. Mandlik A, Swierczynski A, Das A, Ton-That H. Pili in Gram-positive bacteria: assembly, involvement in colonization and biofilm development. Trends Microbiol 2008;16:33-40.

38. Lukaszczyk M, Pradhan B, Remaut H. The biosynthesis and structures of bacterial pili. Subcell Biochem 2019;92:369-413.

39. Scott JR, Zähner D. Pili with strong attachments: gram-positive bacteria do it differently. Mol Microbiol 2006;62:320-30.

40. Dempsey E, Corr SC. Lactobacillus spp. for gastrointestinal health: current and future perspectives. Front Immunol 2022;13:840245.

41. Ye Q, Lao L, Zhang A, et al. Multifunctional properties of the transmembrane LPxTG-motif protein derived from Limosilactobacillus reuteri SH-23. J Dairy Sci 2023;106:8207-20.

42. von Ossowski I, Reunanen J, Satokari R, et al. Mucosal adhesion properties of the probiotic Lactobacillus rhamnosus GG SpaCBA and SpaFED pilin subunits. Appl Environ Microbiol 2010;76:2049-57.

43. Kant R, Rintahaka J, Yu X, et al. A comparative pan-genome perspective of niche-adaptable cell-surface protein phenotypes in Lactobacillus rhamnosus. PLoS One 2014;9:e102762.

44. Douillard FP, Ribbera A, Järvinen HM, et al. Comparative genomic and functional analysis of Lactobacillus casei and Lactobacillus rhamnosus strains marketed as probiotics. Appl Environ Microbiol 2013;79:1923-33.

45. Klotz C, Goh YJ, O’Flaherty S, Barrangou R. S-layer associated proteins contribute to the adhesive and immunomodulatory properties of Lactobacillus acidophilus NCFM. BMC Microbiol 2020;20:248.

46. Banić M, Uroić K, Leboš Pavunc A, et al. Characterization of S-layer proteins of potential probiotic starter culture Lactobacillus brevis SF9B isolated from sauerkraut. LWT 2018;93:257-67.

47. Kaushik JK, Kumar A, Duary RK, Mohanty AK, Grover S, Batish VK. Functional and probiotic attributes of an indigenous isolate of Lactobacillus plantarum. PLoS One 2009;4:e8099.

48. Sagmeister T, Gubensäk N, Buhlheller C, et al. The molecular architecture of Lactobacillus S-layer: assembly and attachment to teichoic acids. Proc Natl Acad Sci U S A 2024;121:e2401686121.

49. Martinović A, Cocuzzi R, Arioli S, Mora D. Streptococcus thermophilus: to survive, or not to survive the gastrointestinal tract, that is the question! Nutrients 2020;12:2175.

50. Zhang L, Yi H. Potential antitumor and anti-inflammatory activities of an extracellular polymeric substance (EPS) from Bacillus subtilis isolated from a housefly. Sci Rep 2022;12:1383.

51. Zhang J, Xiao Y, Wang H, Zhang H, Chen W, Lu W. Lactic acid bacteria-derived exopolysaccharide: formation, immunomodulatory ability, health effects, and structure-function relationship. Microbiol Res 2023;274:127432.

52. Ciszek-Lenda M, Nowak B, Sróttek M, Gamian A, Marcinkiewicz J. Immunoregulatory potential of exopolysaccharide from Lactobacillus rhamnosus KL37: effects on the production of inflammatory mediators by mouse macrophages. Int J Exp Pathol 2011;92:382-91.

53. Lu Q, Guo Y, Yang G, et al. Structure and anti-inflammation potential of lipoteichoic acids isolated from Lactobacillus strains. Foods 2022;11:1610.

54. Mizuno H, Arce L, Tomotsune K, et al. Lipoteichoic acid is involved in the ability of the immunobiotic strain Lactobacillus plantarum CRL1506 to modulate the intestinal antiviral innate immunity triggered by TLR3 activation. Front Immunol 2020;11:571.

55. Lightfoot YL, Mohamadzadeh M. Tailoring gut immune responses with lipoteichoic acid-deficient Lactobacillus acidophilus. Front Immunol 2013;4:25.

56. Li W, Ji J, Rui X, et al. Production of exopolysaccharides by Lactobacillus helveticus MB2-1 and its functional characteristics in vitro. LWT Food Sci Technol 2014;59:732-9.

57. Liu Z, Zhang Z, Qiu L, et al. Characterization and bioactivities of the exopolysaccharide from a probiotic strain of Lactobacillus plantarum WLPL04. J Dairy Sci 2017;100:6895-905.

58. Mizuno H, Tomotsune K, Islam MA, et al. Exopolysaccharides from Streptococcus thermophilus ST538 modulate the antiviral innate immune response in porcine intestinal epitheliocytes. Front Microbiol 2020;11:894.

59. Laiño J, Villena J, Kanmani P, Kitazawa H. Immunoregulatory effects triggered by lactic acid bacteria exopolysaccharides: new insights into molecular interactions with host cells. Microorganisms 2016;4:27.

60. Malick A, Khodaei N, Benkerroum N, Karboune S. Production of exopolysaccharides by selected Bacillus strains: optimization of media composition to maximize the yield and structural characterization. Int J Biol Macromol 2017;102:539-49.

61. Martino ME, Bayjanov JR, Caffrey BE, et al. Nomadic lifestyle of Lactobacillus plantarum revealed by comparative genomics of 54 strains isolated from different habitats. Environ Microbiol 2016;18:4974-89.

62. Deo D, Davray D, Kulkarni R. A diverse repertoire of exopolysaccharide biosynthesis gene clusters in Lactobacillus revealed by comparative analysis in 106 sequenced genomes. Microorganisms 2019;7:444.

63. Parlindungan E, McDonnell B, Lugli GA, Ventura M, van Sinderen D, Mahony J. Dairy streptococcal cell wall and exopolysaccharide genome diversity. Microb Genom 2022;8:000803.

64. Prete R, Long SL, Gallardo AL, Gahan CG, Corsetti A, Joyce SA. Beneficial bile acid metabolism from Lactobacillus plantarum of food origin. Sci Rep 2020;10:1165.

65. Song Z, Feng S, Zhou X, Song Z, Li J, Li P. Taxonomic identification of bile salt hydrolase-encoding lactobacilli: modulation of the enterohepatic bile acid profile. Imeta 2023;2:e128.

66. Bernardeau M, Lehtinen MJ, Forssten SD, Nurminen P. Importance of the gastrointestinal life cycle of Bacillus for probiotic functionality. J Food Sci Technol 2017;54:2570-84.

67. Heilbronner S, Krismer B, Brötz-Oesterhelt H, Peschel A. The microbiome-shaping roles of bacteriocins. Nat Rev Microbiol 2021;19:726-39.

68. Aminov R, Aminova L. The role of the glycome in symbiotic host-microbe interactions. Glycobiology 2023;33:1106-16.

69. Turroni F, Milani C, Duranti S, Mahony J, van Sinderen D, Ventura M. Glycan utilization and cross-feeding activities by bifidobacteria. Trends Microbiol 2018;26:339-50.

70. Seth ES, Taga ME. Nutrient cross-feeding in the microbial world. Front Microbiol 2014;5:350.

71. Singh JK, Devi PB, Reddy GB, Jaiswal AK, Kavitake D, Shetty PH. Biosynthesis, classification, properties, and applications of Weissella bacteriocins. Front Microbiol 2024;15:1406904.

72. O’Shea EF, O’Connor PM, O’Sullivan O, Cotter PD, Ross RP, Hill C. Bactofencin A, a new type of cationic bacteriocin with unusual immunity. mBio 2013;4:e00498-13.

73. Ryan MP, Rea MC, Hill C, Ross RP. An application in cheddar cheese manufacture for a strain of Lactococcus lactis producing a novel broad-spectrum bacteriocin, lacticin 3147. Appl Environ Microbiol 1996;62:612-9.

74. Holo H, Jeknic Z, Daeschel M, Stevanovic S, Nes IF. Plantaricin W from Lactobacillus plantarum belongs to a new family of two-peptide lantibiotics. The GenBank accession number for the sequence reported in this paper is AY007251. Microbiology 2001;147:643-51.

75. Latif A, Shehzad A, Niazi S, et al. Probiotics: mechanism of action, health benefits and their application in food industries. Front Microbiol 2023;14:1216674.

76. Lebeer S, Vanderleyden J, De Keersmaecker SC. Host interactions of probiotic bacterial surface molecules: comparison with commensals and pathogens. Nat Rev Microbiol 2010;8:171-84.

77. Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res 2014;42:D490-5.

78. Domingues SZ, Timmers LFSM, Granada CE. Cellulase production by bacteria is a strain-specific characteristic with a high biotechnological potential. A review of cellulosome of highly studied strains. Cellulose 2022;29:8065-83.

79. Saqib S, Akram A, Halim SA, Tassaduq R. Sources of β-galactosidase and its applications in food industry. 3 Biotech 2017;7:79.

80. Cheng Y, Liu J, Ling Z. Short-chain fatty acids-producing probiotics: a novel source of psychobiotics. Crit Rev Food Sci Nutr 2022;62:7929-59.

81. Puertollano E, Kolida S, Yaqoob P. Biological significance of short-chain fatty acid metabolism by the intestinal microbiome. Curr Opin Clin Nutr Metab Care 2014;17:139-44.

82. Makras L, De Vuyst L. The in vitro inhibition of Gram-negative pathogenic bacteria by bifidobacteria is caused by the production of organic acids. Int Dairy J 2006;16:1049-57.

83. Makras L, Triantafyllou V, Fayol-Messaoudi D, et al. Kinetic analysis of the antibacterial activity of probiotic lactobacilli towards Salmonella enterica serovar Typhimurium reveals a role for lactic acid and other inhibitory compounds. Res Microbiol 2006;157:241-7.

84. Meng F, Zhao H, Nie T, et al. Acetate activates Lactobacillus bacteriocin synthesis by controlling quorum sensing. Appl Environ Microbiol 2021;87:e0072021.

85. Yan Y, Xu R, Li X, et al. Unexpected immunoregulation effects of D-lactate, different from L-lactate. Food Agr Immunol 2022;33:286-301.

86. McDonald B, Zucoloto AZ, Yu IL, et al. Programing of an intravascular immune firewall by the gut microbiota protects against pathogen dissemination during infection. Cell Host Microbe 2020;28:660-8.e4.

87. LeBlanc JG, Laiño JE, del Valle MJ, et al. B-group vitamin production by lactic acid bacteria - current knowledge and potential applications. J Appl Microbiol 2011;111:1297-309.

88. LeBlanc JG, Milani C, de Giori GS, Sesma F, van Sinderen D, Ventura M. Bacteria as vitamin suppliers to their host: a gut microbiota perspective. Curr Opin Biotechnol 2013;24:160-8.

89. Lin MY, Young CM. Folate levels in cultures of lactic acid bacteria. Int Dairy J 2000;10:409-13.

90. Salminen S, von Wright A, Morelli L, et al. Demonstration of safety of probiotics - a review. Int J Food Microbiol 1998;44:93-106.

91. Holzapfel WH, Schillinger U. Introduction to pre- and probiotics. Food Res Int 2002;35:109-16.

92. Smith LK, Mankin AS. Transcriptional and translational control of the mlr operon, which confers resistance to seven classes of protein synthesis inhibitors. Antimicrob Agents Chemother 2008;52:1703-12.

93. Toh SM, Xiong L, Arias CA, et al. Acquisition of a natural resistance gene renders a clinical strain of methicillin-resistant Staphylococcus aureus resistant to the synthetic antibiotic linezolid. Mol Microbiol 2007;64:1506-14.

94. Plant L, Sundqvist J, Zughaier S, Lövkvist L, Stephens DS, Jonsson AB. Lipooligosaccharide structure contributes to multiple steps in the virulence of Neisseria meningitidis. Infect Immun 2006;74:1360-7.

95. Vernocchi P, Del Chierico F, Putignani L. Gut microbiota metabolism and interaction with food components. Int J Mol Sci 2020;21:3688.

96. Hitch TCA, Hall LJ, Walsh SK, et al. Microbiome-based interventions to modulate gut ecology and the immune system. Mucosal Immunol 2022;15:1095-113.

97. Romero-Velarde E, Delgado-Franco D, García-Gutiérrez M, et al. The importance of lactose in the human diet: outcomes of a mexican consensus meeting. Nutrients 2019;11:2737.

98. Gökmen GG, Sarıyıldız S, Cholakov R, et al. A novel Lactiplantibacillus plantarum strain: probiotic properties and optimization of the growth conditions by response surface methodology. World J Microbiol Biotechnol 2024;40:66.

99. Goh YJ, Klaenhammer TR. Insights into glycogen metabolism in Lactobacillus acidophilus: impact on carbohydrate metabolism, stress tolerance and gut retention. Microb Cell Fact 2014;13:94.

Cite This Article

Original Article
Open Access
Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database
Silvia Petraro, ... Christian MilaniChristian Milani

How to Cite

Petraro, S.; Tarracchini C.; Lugli G. A.; Mancabelli L.; Fontana F.; Turroni F.; Ventura M.; Milani C. Comparative genome analysis of microbial strains marketed for probiotic interventions: an extension of the Integrated Probiotic Database. Microbiome. Res. Rep. 2024, 3, 45. http://dx.doi.org/10.20517/mrr.2024.11

Download Citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click on download.

Export Citation File:

Type of Import

Tips on Downloading Citation

This feature enables you to download the bibliographic information (also called citation data, header data, or metadata) for the articles on our site.

Citation Manager File Format

Use the radio buttons to choose how to format the bibliographic data you're harvesting. Several citation manager formats are available, including EndNote and BibTex.

Type of Import

If you have citation management software installed on your computer your Web browser should be able to import metadata directly into your reference database.

Direct Import: When the Direct Import option is selected (the default state), a dialogue box will give you the option to Save or Open the downloaded citation data. Choosing Open will either launch your citation manager or give you a choice of applications with which to use the metadata. The Save option saves the file locally for later use.

Indirect Import: When the Indirect Import option is selected, the metadata is displayed and may be copied and pasted as needed.

About This Article

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Data & Comments

Data

Views
239
Downloads
20
Citations
0
Comments
0
0

Comments

Comments must be written in English. Spam, offensive content, impersonation, and private information will not be permitted. If any comment is reported and identified as inappropriate content by OAE staff, the comment will be removed without notice. If you have any queries or need any help, please contact us at support@oaepublish.com.

0
Download PDF
Share This Article
Scan the QR code for reading!
See Updates
Contents
Figures
Related
Microbiome Research Reports
ISSN 2771-5965 (Online)

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/