Next Article in Journal
Not Just a Banana: The Extent of Fruit Cross-Reactivity and Reaction Severity in Adults with Banana Allergy
Next Article in Special Issue
Main Challenges Expected from the Impact of Climate Change on Microbial Biodiversity of Table Olives: Current Status and Trends
Previous Article in Journal
Multivariate Assessment and Risk Ranking of Pesticide Residues in Citrus Fruits
Previous Article in Special Issue
Microbial and Chemical Characterization of Natural-Style Green Table Olives from the Gordal, Hojiblanca and Manzanilla Cultivars
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Foods
Volume 12
Issue 13
10.3390/foods12132455
foods-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genome-Wide Comparative Analysis of Lactiplantibacillus pentosus Isolates Autochthonous to Cucumber Fermentation Reveals Subclades of Divergent Ancestry

by
Clinton A. Page
1,
Ilenys M. Pérez-Díaz
1,*,
Meichen Pan
2 and
Rodolphe Barrangou
2
1
United States Department of Agriculture, Agricultural Research Service, SEA Food Science and Market Quality and Handling Research Unit, 322 Schaub Hall, Box 7624, Raleigh, NC 27695-7624, USA
2
Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, 322 Schaub Hall, Box 7624, Raleigh, NC 27695-7624, USA
*
Author to whom correspondence should be addressed.
Foods 2023, 12(13), 2455; https://doi.org/10.3390/foods12132455
Submission received: 28 April 2023 / Revised: 7 June 2023 / Accepted: 13 June 2023 / Published: 23 June 2023
(This article belongs to the Special Issue New Insight in Microbial Diversity and Genomic in Foods)
Browse Figures
Review Reports Versions Notes

Abstract

:
Lactiplantibacillus pentosus, commonly isolated from commercial cucumber fermentation, is a promising candidate for starter culture formulation due to its ability to achieve complete sugar utilization to an end pH of 3.3. In this study, we conducted a comparative genomic analysis encompassing 24 L. pentosus and 3 Lactiplantibacillus plantarum isolates autochthonous to commercial cucumber fermentation and 47 lactobacillales reference genomes to determine species specificity and provide insights into niche adaptation. Results showed that metrics such as average nucleotide identity score, emulated Rep-PCR-(GTG)5, computed multi-locus sequence typing (MLST), and multiple open reading frame (ORF)-based phylogenetic trees can robustly and consistently distinguish the two closely related species. Phylogenetic trees based on the alignment of 587 common ORFs separated the L. pentosus autochthonous cucumber isolates from olive fermentation isolates into clade A and B, respectively. The L. pentosus autochthonous clade partitions into subclades A.I, A.II, and A.III, suggesting substantial intraspecies diversity in the cucumber fermentation habitat. The hypervariable sequences within CRISPR arrays revealed recent evolutionary history, which aligns with the L. pentosus subclades identified in the phylogenetic trees constructed. While L. plantarum autochthonous to cucumber fermentation only encode for Type II-A CRISPR arrays, autochthonous L. pentosus clade B codes for Type I-E and L. pentosus clade A hosts both types of arrays. L. pentosus 7.8.2, for which phylogeny could not be defined using the varied methods employed, was found to uniquely encode for four distinct Type I-E CRISPR arrays and a Type II-A array. Prophage sequences in varied isolates evidence the presence of adaptive immunity in the candidate starter cultures isolated from vegetable fermentation as observed in dairy counterparts. This study provides insight into the genomic features of industrial Lactiplantibacillus species, the level of species differentiation in a vegetable fermentation habitat, and diversity profile of relevance in the selection of functional starter cultures.

1. Introduction

Diverse lactobacilli and Leuconostoc species are frequently isolated from vegetable fermentations, including cabbage, cucumber, green tomato, green bean, okra, olive, and onion, making them relevant for the formulation of starter cultures [1,2,3,4,5,6,7,8,9,10,11]. Starter cultures encompassing Lactiplantibacillus plantarum and Lactiplantibacillus pentosus are often used in the fermentation of blanched garlic, carrot, cucumber, olives kimchi, and kale, as well as cereal grains [5,12,13,14,15,16,17,18]. Fermentative bacteria such as lactobacilli are implicated in the conversion of sugars to lactic acid and the production of ascorbic acid, glutathione, flavonoid aglycones, and distinguishable volatile compounds, as well as in enhancing total antioxidant activity [7,19]. Fermentative bacteria also reduce total amino acid concentration in fermented vegetables, leading to the production of esters, alcohols, and aldehydes presumably involved in flavor development [20]. The metabolic activity of fermentative bacteria confers complex chemical and biochemical characteristics to fermented vegetables of relevance for preservation and organoleptic attributes.
The growth of L. plantarum and L. pentosus in cucumber fermentation favors the preservation of pickle quality. Such lactobacilli convert sugars to lactic acid exclusively in cucumber fermentation, which favors the prevention of bloater defects from the accumulation of carbon dioxide inside the fruits [21]. L. plantarum and L. pentosus lead a rapid reduction in pH relative to competing microbes and tolerate pH as low as 3.1 [22]. Additionally, it is speculated that starter cultures autochthonous to vegetable fermentations could arrest the growth of spoilage-associated microbes through competitively excluding energy sources or producing bacteriocins [23]. This is relevant for the development of low-salt cucumber fermentation, in which spoilage-associated microbes can accumulate after the completion of sugar conversion, elevate pH, and jeopardize the microbial stability of the fermented product [24,25,26]. Thus, the informed design of lactobacilli starter culture for cucumber fermentation can function in enhancing the performance of fermentation as well as preventing spoilage.
L. pentosus and L. plantarum are closely related lactic acid bacteria (LAB) originally defined by the ability of the former to metabolize pentose sugars into lactic acid [27]. The species definition was later refined to specify metabolism of the pentose sugar D-xylose as well as glycerol as characteristic of L. pentosus [28]. Subsequent research confounded the usefulness of D-xylose and glycerol utilization as a phenotypic test, as strains belonging to both species were found capable of such metabolic activity [29]. While DNA–DNA hybridization can discriminate between L. plantarum and L. pentosus strains [29,30], the 16S rDNA sequence-based phylogeny construction is often insufficient to discriminate the species [31]. The construction of a phylogenetic tree based on a single housekeeping gene sequence, including recA, dnaK, and pheS, can discriminate between L. plantarum and L. pentosus but is limited in assessing intraspecies genetic diversity [32]. Random Amplified Polymorphic DNA (RAPD)-PCR combined with analysis of banding patterns, was sufficient to correctly group seven isolates (1.2.13, 3.8.24, 1.2.11, 1.8.6, 1.8.9, 3.2.37, and LA0445) with L. pentosus reference strains while discriminating among themselves [32]. The same analysis also grouped L. plantarum isolates with L. plantarum reference strains [32]. However, the availability of whole genome sequences enables comparative genomic analysis which is useful in discriminating among the two species and in identifying putative and divergent functions. Calculation of average nucleotide identity (ANI) for genome sequences against references can quickly identify the affiliation of the harboring organism to a given species [33,34]. The identification of divergent or unique putative functions informs the selection of strains to serve as starter cultures that can exert a function within the intrinsic microbiome.
This study analyzed genome sequences from L. plantarum and L. pentosus isolates autochthonous to commercial cucumber fermentations that were selected based on multiple criteria. Most of the bacteria were selected for whole genome sequence comparative analysis based on their ability to rapidly reduce pH in multiple cucumber juice treatments varying in starting pH, temperature, and salinity [32]. L. plantarum T1R2b and 3.2.8 were selected for their ability to produce an unusually slimy, exopolysaccharide (EPS)-like matrix in cucumber fermentation [35]. The primary goal of the study was to determine species-specific genomic content and assess diversity between and within species. The approach was to apply comparative genome sequence analysis focused on the metrics for structural genome features and phylogeny, determination of ANI scores, computed MLST, emulated Rep-PCR, prophage coding, and CRISPR arrays to define diversity as relevant for cucumber fermentation.

2. Materials and Methods

L. plantarum and L. pentosus isolates and genome sequences used in this study: Twenty-seven pure cultures were included in this study, of which twenty-two were isolated from a commercial cucumber fermentation tank filled with recycled cover brine in 2009 as described by Pérez-Díaz et al. [32]. The twenty-two cultures include L. plantarum 3.2.8 and 7.8.4, and twenty L. pentosus cultures. L. pentosus 7.8.2 and 7.2.20 were isolated from an independent commercial cucumber fermentation tank filled with fresh cover brine in 2010 [32]. L. pentosus LA0445 is of cucumber fermentation origin isolated in 1983 and MU045 is a mutant derivative of this strain [36,37]. L. plantarum T1R2b was isolated in 2020 from a low-salt cucumber fermentation that produced an irregular slimy cover brine [38].
The sequencing, assembly, and annotation, along with growth conditions, of the genomic sequences corresponding to the L. plantarum and L. pentosus cultures autochthonous to cucumber fermentation and included in this study are described by Page & Pérez-Díaz [39] and available from the National Center for Biotechnology Information (NCBI) database under BioProject Accession Number PRJNA674638. GenBank accession numbers corresponding to the genome sequences derived from the autochthonous and allochthonous lactic acid bacteria included in this study are listed in Table 1.
Categorical description of genome sequences: The descriptive data of the genome sequence features and coding gene type shown in Figure 1 were determined in the IMG system [40] (analysis was run in July 2022) using the genome browser function and modifying the output table configuration for the data shown. Significant difference between the L. pentosus and L. plantarum genome sequences was determined using a T-test performed in Microsoft Excel (2019) for each feature or gene coding type, individually.
ANI score calculation for the L. plantarum and L. pentosus genome sequences: Calculations of the ANI scores between an L. pentosus and an L. plantarum were carried out in the IMG system [40] (analysis was run in July 2022). Estimated ANI scores for pairwise comparisons of L. pentosus or L. plantarum homolog genomes were calculated in Kbase via the FastANI v0.13 automated pipeline [41] (analysis run in March 2022).
Construction of phylogenetic trees: Three distinct phylogenetic trees were constructed for definitive culture identification and comparison of species boundaries. A phylogenetic tree was constructed based on a computer emulated Rep-PCR using the (GTG)5 primer [42] for the genome sequences of several lactic acid bacteria whose genome sequences are described in Table 1. The metadata for the genome sequences described in Table 1 that are autochthonous to cucumber may be found in Page & Perez-Diaz [39]. Amplicons from a computed Rep-PCR-(GTG)5 were generated with Geneious software (v. 2021.1.1, www.geneious.com, analysed in June 2021, accessed on 1 June 2023) for each genome sequence of interest. The band patterns produced for each genome sequence were compared using Bionumerics software v. 7.6.3 (www.applied-maths.com, accessed on 1 June 2023). Similarity matrices of the densitometric curves from each sample were calculated using Pearson correlation coefficients and clustered via unweighted pair group method with arithmetic averages (UPGMA).
A second phylogenetic tree was produced using a computer-emulated MLST run in AutoMLST [43] (analysis run in December 2021) based on the 79 core genes described in Table S1, which were automatically selected by the software. This analysis was focused on the clustering of autochthonous and allochthonous L. plantarum and L. pentosus genomes, whose accession numbers are listed in Table 1. The genome sequence of Pediococcus damnosus DSM20331 was selected by AutoMLST as the tree root.
A phylogenetic tree was generated in PATRIC (analysis run in December 2021) [44] via the Codon Tree method, which employs RaxML to generate phylogenetic distances between sequences of L. pentosus genomes exclusively [45]. Accession numbers for the L. pentosus genomes used, from cucumber fermentation autochthonous and allochthonous isolates, are listed in Table 1. No duplications or deletions were allowed for the analysis. The 587 ORFs listed in Table S1 were used for the construction of the phylogenetic tree.
Tree diagrams were generated for the computed MLST and multiple ORFs phylogenetic analysis outputs with Interactive Tree of Life (iTOL) v.6.5.7 [46] in June 2022. Default parameters were used for the construction of trees.
CRISPR-Cas system identification and characterization: The CRISPRCasTyper pipeline was used to scrutinize the genome sequences of interest [47]. CRISPR spacers were extracted and visualized using the CRISPRViz pipeline [48]. The extracted spacer sequences were passed to BLASTn searches in the NCBI nucleotide database to identify potential protospacer sequences. The positive BLAST hits had an e-value smaller than 1 × 10−3 and an identity score greater than 85%. The flanking regions of the protospacer matches were extracted and aligned to identify putative protospacer adjacent motifs (PAM) (Supplementary Figure S1). The BLAST-webserver search was conducted against the nucleotide collection [49] in December 2021.
Identification of putative prophage sequences: A survey of putative prophage sequences was conducted among the genome sequences derived from the cucumber-autochthonous L. plantarum and L. pentosus using the Phage Search Tool enhanced release (PHASTER, analysis run in February 2022) [50,51]. The multiple contigs option was selected for the prophage sequence analysis and default parameters were applied for the other options in the service. Accession numbers for the lactobacilli genome sequences used are listed in Table 1.

3. Results and Discussion

Features of the L. pentosus and L. plantarum genome sequences: The genome sizes of most LAB are between 1.8 and 3.4 megabases [52], which ranges on the lower end of the bacterial genome spectrum spanning approximately 500 kilobases to 12 megabases [53]. LAB are thought to be highly specialized given their evolutionary path and historical association with select niches over the course of human association and use for fermentation processes in relatively nutrient-rich habitats [52]. Such bacteria are known for their ability to use horizontal gene transfer for adaptation [54]. Generally, bacteria exhibit mutational bias that deletes superfluous sequences, which produces smaller genomes with a greater degree of specialization [55].
The L. pentosus genomes studied here ranged in size from 3.59 to 3.83 Mbp with 46% GC content, while the L. plantarum genome sequences were found to be significantly smaller at 3.38 to 3.48 Mbp with 44% GC content (Figure 1). The range of such genome sizes and GC percentages are consistent with the ranges reported in the PATRIC database for each species [19]. The benefits derived by L. pentosus from the additional genes relative to L. plantarum and the metabolic versatility associated with such genes could confer a competitive advantage [56,57]. Figure 1 shows that the predicted signal peptides and proteins, specifically transmembrane proteins, are more abundant in the L. pentosus genome as compared to those in the L. plantarum counterpart. It is documented that L. pentosus is more commonly isolated from cucumber and olive fermentations than L. plantarum [2,10]. Such observations suggest that the larger L. pentosus genome may be advantageous in sensing its habitat, fermentation in this case.
ANI is widely used to determine whether multiple genomes belong to the same species [34,58]. As expected, the calculation of ANI values from a comparison of a L. pentosus and L. plantarum genome sequences was approximately 80%, significantly less than the 95% cut-off score for species membership (Figure 2A). The ANI calculations described here were generated through pairwise comparisons between an autochthonous L. plantarum or L. pentosus genome sequence and a homolog genome sequence or a reference genome (Figure 2A). Contrary to L. plantarum autochthonous to cucumber fermentation (Figure 2B), the calculation of varied ANI values above the 95% threshold among the L. pentosus counterparts suggested a degree of intraspecies variation worth studying for discerning adaptive diversity of value in the optimization of starter cultures for cucumber fermentations (Figure 2C).
The 27 isolates included in this study were previously identified through the alignment of the 16S rDNA partial sequence to those of reference strains and the recA amplicon size as described by Torriani et al. [10,31]. The identification of 26 out of the 27 isolates in the study was confirmed via the ANI scores calculated as well as via the whole genome sequence alignments to reference genomes in the NCBI and the IMG/M databases, the exception being L. pentosus 7.2.4, which was initially classified as L. plantarum [10].
L. pentosus and L. plantarum intraspecies genetic diversity as defined through the construction of phylogenetic trees:
The simulation of Rep-PCR-(GTG)5 through emulated banding patterns from whole genome sequences discriminated between the L. pentosus and L. plantarum autochthonous to cucumber fermentation (Figure 3) and replicated the separation previously observed by Pérez-Díaz et al. [32] for L. pentosus LA0445 from six commercial fermentation isolates of the same species (1.2.13, 3.8.24, 1.2.11, 1.8.6, 1.8.9, and 3.2.37) using benchtop Rep-PCR-(GTG)5. The L. pentosus strain separation identified using computer-emulated and benchtop Rep-PCR-(GTG)5 phylogenetic clustering was also detected in AutoMLST analysis including 79 common ORFs (Figure 4A) and using PATRIC-based clustering aligning 587 common ORFs (Figure 4B). The four analyses suggest at least two distinct L. pentosus clades, A and B, which include identical clusters of isolates. L. pentosus clade A includes isolates collected in North Carolina from fermentation day one to day thirty, while L. pentosus clade B includes three isolates collected from fermentation day seven or later. Among these are LA0445, which was derived from a commercial fermentation conducted in 1983, as well as MU045, a derivative of the former deficient in malic acid decarboxylation [59]. Two L. pentosus isolated from cucumber fermentation conducted in North Carolina (2009) also belong to clade B, 7.2.4 and 7.2.11. Two L. pentosus isolated from a cucumber fermentation conducted in Minnesota (7.2.20 and 7.8.2), as well as multiple isolates collected on days seven and 14 of the Carolinian counterparts (7.2.15, 7.8.11, 7.8.46, 14.2.3, 14.2.16, and 14.8.42) did not sort consistently into clade A or B (Figure 4A).
A subsequent phylogenetic construction including only L. pentosus strains employed 1000 core ORFs and expanded the L. pentosus clade A described in Figure 4 to include isolates that did not sort into clade A or B in the previous trees (Figure 5). Clade A can be further subdivided into three subclades, A.I, A.II, and A.III. Subclade A.I includes twelve isolates, ten of which were collected on day one or three of fermentation. Subclade A.II is a group of two isolates, one each from the cucumber fermentations conducted in North Carolina and Minnesota, both isolated on day seven. Subclade A.III includes five L. pentosus isolated on day seven or 14 of the cucumber fermentation conducted in North Carolina. L. pentosus 7.8.2 was isolated from the cucumber fermentation performed in Minnesota and did not sort with isolates from clade A or B but is consistently associated with L. pentosus reference genomes from multiple sources (Figure 5). This phylogenetic analysis also included multiple strains derived from olive fermentation, which, with the exception of a single isolate associated with subclade A.I, clustered in several distinct clades not associated with L. pentosus clades A or B.
The three autochthonous L. plantarum isolates were associated with counterparts from multiple habitats based in the three phylogenetic analyses employing emulated Rep-PCR-(GTG)5, computed MLST data (AutoMLST) involving 79 common ORFs, and 587 common ORFs via the PATRIC Codon Tree builder (Figure 4). L. plantarum 3.2.8 and 7.8.4 share a common ancestor with the L. plantarum strain ZJ316, which is a human fecal isolate with reported probiotic properties [60]. L. plantarum T1R2b clustered into a separate branch from 3.2.8 and 7.8.4, which has common ancestry with L. plantarum B21, a fermented sausage isolate able to produce a broad spectrum bacteriocin B21AG, which is also a circular plantacyclin [61]. The L. plantarum T1R2b draft genomic DNA sequence, however, lacks the putative genes encoding for such bacteriocin [62]. It is relevant to note that two of the three L. plantarum autochthonous to cucumber fermentation are capable of prevailing in the native habitat and consistently produce slimy brines. Thus, exploitation of such L. plantarum isolates in cucumber fermentation is limited.
Occurrence and diversity of CRISPR-Cas immune systems: The hypervariable nature of CRISPR loci has been used in the past for the genotyping of various genera and species, including starter cultures and food pathogens, notably, Streptococcus thermophilus for the former [63,64] and E. coli and Salmonella for the later [65,66]. Here, we sought to exploit the hypervariable CRISPR arrays in the L. pentosus and L. plantarum genomes to discern intraspecies diversity and ancestry. Both type I-E and type II-A CRISPR-Cas systems were identified in the L. pentosus genomes, with canonical cas operon structures and occurrence of variable spacers in CRISPR arrays (Table 2). Distinct type II-A arrays were detected in L. plantarum isolates, as well as in L. pentosus 7.8.2 and the L. pentosus subclades A.I, A.II, and A.III. The fact that no type II-A spacers were shared between the subclades confirms the significance of the isolates’ clustering observed in phylogenetic analyses (Figure 6). The identified CRISPR arrays in the L. plantarum isolates did not share similar spacer sequences despite the close association of these isolates in phylogenetic trees. No CRISPR-Cas system was detected in the L. plantarum isolate T1R2b.
L. pentosus isolates 7.8.46 and 7.2.20, which belong to subclade A.II, shared common type I-E CRISPR arrays with subclade A.III but not with subclade A.I, suggesting that A.II shares more recent ancestry with A.III than subclade A.I (Figure 7). L. pentosus 7.8.46 and 7.2.20 also shared a type II-A array that was not detected in other L. pentosus isolates, further supporting the separation of these isolates from subclades A.I and A.III. Type I-E CRISPR arrays detected in the L. pentosus isolate 7.8.2 were distinct from other L. pentosus CRISPR sequences, which reflected the separation of strain 7.8.2 from other L. pentosus isolates described in phylogenetic analysis (Figure 8).
Four type I-E spacers were found to match known phages previously isolated from the same fermentation tanks (Figure 9) [10,26]. Unexpectedly, three separate spacers in L. pentosus 7.2.11 matched to two different phages, ϕJL-1 and ϕSha, while a fourth spacer in L. pentosus 7.2.4 targeted ϕSha (Figure 9). All protospacers were flanked by putative protospacer adjacent motif (PAM) sequence 5′-AAA-3′ on the 5′ end, reflecting CRISPR-mediated immunity in L. pentosus against these phages during industrial fermentation. This is consistent with the role of CRISPR-Cas systems as providers of adaptive immunity as originally demonstrated in dairy starter cultures [67].
Putative prophage profiles detected in the L. pentosus and L. plantarum genome sequences: It is estimated that 10% of the bacterial community in commercial cucumber fermentations is susceptible to bacteriophage infection, of which a fifth is attributed to L. pentosus and L. plantarum [68]. Phages of the Myoviridae and Siphoviridae are commonly isolated from vegetable fermentations [68,69]. Five intact prophage sequences of the Siphoviridae sp. were detected in 7 of the 24 L. pentosus isolates (Table 3). Siphoviridae ctu0P1 was found in the genomic DNA sequences of six L. pentosus isolated on days one and three of commercial fermentations, within subclade A.I. The genome sequences of the L. pentosus 14.2.3 includes two different Siphoviridae, ctu0P1 and ctk5O4, as well as a third phage with homology to Siphoviridae ctk5O4. Phages with homology to Siphoviridae ctu0P1 were also detected in two L. plantarum isolates, 7.8.4 and T1R2b. Two additional phages were detected in the genome sequences of L. plantarum 7.8.4 and another was found in T1R2b, all of which have homology to Siphoviridae. Together, these observations suggest the presence of grounded Siphoviridae phages in L. plantarum and L. pentosus autochthonous to commercial cucumber fermentations, which may be conferring immunity and serving as drivers of evolution and biogenesis of genetic information [70].

4. Conclusions

Given the inability of classical phenotypic tests and 16S rDNA-based methods to differentiate between L. plantarum and L. pentosus, the verification of multiple genomic-based methods can assist researchers in properly identifying and discriminating such species. The phylogenetic distribution of L. pentosus isolates from commercial cucumber fermentation suggests the co-existence of multiple L. pentosus strains in this habitat. The presence of Type I-E CRISPRs arrays in L. pentosus isolates from clade B that are homologous to identified phages provides evidence of adaptive immunity in candidate starter cultures. Such findings underscore the need to decipher the genetic composition of strains to be used as commercial starter cultures and to design formulations that can exert specific functional features relevant for complex industrial fermentations.
Short version of the title: comparative genomics of L. pentosus
Mention of a trademark or proprietary product does not constitute a guarantee or warranty of the product by the US Department of Agriculture or North Carolina Agricultural Research Service, nor does it imply approval to the exclusion of other products that may be suitable. USDA is an equal opportunity provider and employer.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods12132455/s1. Table S1: Describes the 79 ORFs used for the computed MLST, 589 and 1000 core genes used for the construction of phylogenetic trees in Figure 4A,B and Figure 5, respectively. Figure S1: The putative protospacer adjacent motifs (PAMs) were predicted for Type II-A (A) and Type I-E (B) CRISPR-Cas systems present in L. plantarum and L. pentosus genomes, using protospacer flanking sequences and the consensus sequences illustrated at the top.

Author Contributions

Conceptualization, C.A.P., I.M.P.-D., R.B., and M.P.; methodology, C.A.P., I.M.P.-D., R.B., and M.P.; validation, C.A.P. and M.P.; formal analysis, C.A.P., I.M.P.-D., R.B., and M.P.; writing—original draft preparation, C.A.P.; writing—review and editing, C.A.P., I.M.P.-D., R.B., and M.P.; visualization, C.A.P. and M.P.; supervision, I.M.P.-D. and R.B.; project administration, I.M.P.-D. and R.B. All authors have read and agreed to the published version of the manuscript.

Funding

This project was conducted under the United State Department of Agriculture—Agricultural Research Service Project Plan No. 6070-41000-008-00D associated with National Project 306 and titled “Improved vegetable processing methods to reduce environmental impact, enhance product quality and reduce food waste”. M.P. was funded by the North Carolina Agricultural Foundation.

Data Availability Statement

The data used to support the findings of this study can be made available by the corresponding author upon request.

Acknowledgments

The authors thank Sandra Parker and Muquarrab Qureshi with the USDA-ARS, SEA, Food Science & Market Quality and Handling Research Unit located in Raleigh, NC for administrative and managerial assistance, respectively. The authors also thank Adam Rivers with the USDA-ARS, SEA, Genomics and Bioinformatics Research Unit located in Stoneville, MS, USA for reviewing the manuscript.

Conflicts of Interest

The authors declare no conflict of interest with the research performed.

References

  1. Al-Sahlany, S.T.; Niamah, A.K. Bacterial viability, antioxidant stability, antimutagenicity and sensory properties of onion types fermentation by using probiotic starter during storage. Nutr. Food Sci. 2022, 52, 901–916. [Google Scholar] [CrossRef]
  2. Benítez-Cabello, A.; Bautista-Gallego, J.; Garrido-Fernández, A.; Rantsiou, K.; Cocolin, L.; Jiménez-Díaz, R.; Arroyo-López, F.N. RT-PCR–DGGE Analysis to Elucidate the Dominant Bacterial Species of Industrial Spanish-Style Green Table Olive Fermentations. Front. Microbiol. 2016, 7, 1291. [Google Scholar] [CrossRef]
  3. Chen, K.-H.; McFEETERS, R.F.; Fleming, H.P. Stability of Mannitol to Lactobacillus plantarum Degradation in Green Beans Fermented with Lactobacillus cellobiosus. J. Food Sci. 1983, 48, 972–974. [Google Scholar] [CrossRef]
  4. Di Cagno, R.; Surico, R.F.; Siragusa, S.; De Angelis, M.; Paradiso, A.; Minervini, F.; De Gara, L.; Gobbetti, M. Selection and use of autochthonous mixed starter for lactic acid fermentation of carrots, French beans or marrows. Int. J. Food Microbiol. 2008, 127, 220–228. [Google Scholar] [CrossRef] [PubMed]
  5. Jung, J.Y.; Lee, S.H.; Kim, J.M.; Park, M.S.; Bae, J.W.; Hahn, Y.; Madsen, E.L.; Jeon, C.O. Metagenomic Analysis of Kimchi, a Traditional Korean Fermented Food. Appl. Environ. Microbiol. 2011, 77, 2264–2274. [Google Scholar] [CrossRef]
  6. Kotzekidou, P.; Roukas, T. Characterization and Distribution of Lactobacilli during Lactic Fermentation of Okra (Hibiscus esculentus). J. Food Sci. 1986, 51, 623–625. [Google Scholar] [CrossRef]
  7. Lee, Y.G.; Cho, J.-Y.; Kim, Y.-M.; Moon, J.-H. Change in Flavonoid Composition and Antioxidative Activity during Fermentation of Onion (Allium cepa L.) by Leuconostoc mesenteroides with Different Salt Concentrations. J. Food Sci. 2016, 81, C1385–C1393. [Google Scholar] [CrossRef]
  8. Paramithiotis, S.; Kouretas, K.; Drosinos, E.H. Effect of ripening stage on the development of the microbial community during spontaneous fermentation of green tomatoes. J. Sci. Food Agric. 2014, 94, 1600–1606. [Google Scholar] [CrossRef]
  9. Pérez-Díaz, I.M.; Dickey, A.; Fitria, R.; Ravishankar, N.; Hayes, J.S.; Campbell, K.; Arritt, F. Modulation of the bacterial population in commercial cucumber fermentations by brining salt type. J. Appl. Microbiol. 2020, 128, 1678–1693. [Google Scholar] [CrossRef]
  10. Pérez-Díaz, I.M.; Hayes, J.; Medina, E.; Anekella, K.; Daughtry, K.; Dieck, S.; Levi, M.; Price, R.; Butz, N.; Lu, Z.; et al. Reassessment of the succession of lactic acid bacteria in commercial cucumber fermentations and physiological and genomic features associated with their dominance. Food Microbiol. 2017, 63, 217–227. [Google Scholar] [CrossRef]
  11. Plengvidhya, V.; Breidt, F.; Lu, Z.; Fleming, H.P. DNA Fingerprinting of Lactic Acid Bacteria in Sauerkraut Fermentations. Appl. Environ. Microbiol. 2007, 73, 7697–7702. [Google Scholar] [CrossRef] [PubMed]
  12. Ashaolu, T.J.; Reale, A. A Holistic Review on Euro-Asian Lactic Acid Bacteria Fermented Cereals and Vegetables. Microorganisms 2020, 8, 1176. [Google Scholar] [CrossRef] [PubMed]
  13. De Castro, A.; Montaño, A.; Sánchez, A.H.; Rejano, L. Lactic acid fermentation and storage of blanched garlic. Int. J. Food Microbiol. 1998, 39, 205–211. [Google Scholar] [CrossRef] [PubMed]
  14. Jung, J.H.; Kim, S.J.; Lee, J.Y.; Yoon, S.R.; You, S.Y.; Kim, S.H. Multifunctional properties of Lactobacillus plantarum strains WiKim83 and WiKim87 as a starter culture for fermented food. Food Sci. Nutr. 2019, 7, 2505–2516. [Google Scholar] [CrossRef] [PubMed]
  15. Lorn, D.; Nguyen, T.-K.-C.; Ho, P.-H.; Tan, R.; Licandro, H.; Waché, Y. Screening of lactic acid bacteria for their potential use as aromatic starters in fermented vegetables. Int. J. Food Microbiol. 2021, 350, 109242. [Google Scholar] [CrossRef] [PubMed]
  16. Maoloni, A.; Ferrocino, I.; Milanović, V.; Cocolin, L.; Corvaglia, M.R.; Ottaviani, D.; Bartolini, C.; Talevi, G.; Belleggia, L.; Cardinali, F.; et al. The Microbial Diversity of Non-Korean Kimchi as Revealed by Viable Counting and Metataxonomic Sequencing. Foods 2020, 9, 1568. [Google Scholar] [CrossRef]
  17. Montaño, A.; Sánchez, A.H.; Rejano, L.; de Castro, A. Processing and storage of lye-treated carrots fermented by a mixed starter culture. Int. J. Food Microbiol. 1997, 35, 83–90. [Google Scholar] [CrossRef]
  18. Oguntoyinbo, F.A.; Cho, G.S.; Trierweiler, B.; Kabisch, J.; Rösch, N.; Neve, H.; Bockelmann, W.; Frommherz, L.; Nielsen, D.S.; Krych, L.; et al. Fermentation of African kale (Brassica carinata) using L. plantarum BFE 5092 and L. fermentum BFE 6620 starter strains. Int. J. Food Microbiol. 2016, 238, 103–112. [Google Scholar] [CrossRef]
  19. Di Cagno, R.; Surico, R.F.; Paradiso, A.; De Angelis, M.; Salmon, J.-C.; Buchin, S.; De Gara, L.; Gobbetti, M. Effect of autochthonous lactic acid bacteria starters on health-promoting and sensory properties of tomato juices. Int. J. Food Microbiol. 2009, 128, 473–483. [Google Scholar] [CrossRef]
  20. Cheng, L.; Luo, J.; Li, P.; Yu, H.; Huang, J.; Luo, L. Microbial diversity and flavor formation in onion fermentation. Food Funct. 2014, 5, 2338–2347. [Google Scholar] [CrossRef]
  21. Zhai, Y.; Pérez-Díaz, I.M. Identification of potential causative agents of the CO2-mediated bloater defect in low salt cucumber fermentation. Int. J. Food Microbiol. 2021, 344, 109115. [Google Scholar] [CrossRef] [PubMed]
  22. McDonald, L.C.; Fleming, H.P.; Hassan, H.M. Acid Tolerance of Leuconostoc mesenteroides and Lactobacillus plantarum. Appl. Environ. Microbiol. 1990, 56, 2120–2124. [Google Scholar] [CrossRef] [PubMed]
  23. Ucar, R.A.; Pérez-Díaz, I.M.; Dean, L.L. Content of xylose, trehalose and l-citrulline in cucumber fermentations and utilization of such compounds by certain lactic acid bacteria. Food Microbiol. 2020, 91, 103454. [Google Scholar] [CrossRef] [PubMed]
  24. Fleming, H.P.; Daeschel, M.A.; McFeeters, R.F.; Pierson, M.D. Butyric Acid Spoilage of Fermented Cucumbers. J. Food Sci. 1989, 54, 636–639. [Google Scholar] [CrossRef]
  25. Franco, W.; Pérez-Díaz, I.M.; Johanningsmeier, S.D.; McFeeters, R.F. Characteristics of Spoilage-Associated Secondary Cucumber Fermentation. Appl. Environ. Microbiol. 2012, 78, 1273–1284. [Google Scholar] [CrossRef]
  26. Pérez-Díaz, I.M.; Medina, E.; Page, C.A.; Johanningsmeier, S.D.; Daughtry, K.V.; Moeller, L. Prevention of microbes-induced spoilage in sodium chloride–free cucumber fermentations employing preservatives. J. Food Sci. 2022, 87, 5054–5069. [Google Scholar] [CrossRef]
  27. Fred, E.B.; Peterson, W.H.; Anderson, J.A. The characteristics of certain pentose-destroying bacteria, especially as it concerns their action on arabinose. J. Biol. Chem. 1921, 48, 385–412. [Google Scholar] [CrossRef]
  28. Zanoni, P.; Farrow, J.A.E.; Phillips, B.A.; Collins, M.D. Lactobacillus pentosus (Fred, Peterson, and Anderson) sp. nov., nom. rev. Int. J. Syst. Bacteriol. 1987, 37, 339–341. [Google Scholar] [CrossRef]
  29. Bringel, F.; Curk, M.-C.; Hubert, J.-C. Characterization of Lactobacilli by Southern-Type Hybridization with a Lactobacillus plantarum pyrDFE Probe. Int. J. Syst. Bacteriol. 1996, 46, 588–594. [Google Scholar] [CrossRef]
  30. Dellaglio, F.; Bottazzi, V.; Vescovo, M. Deoxyribonucleic Acid Homology Among Lactobacillus Species of the Subgenus Streptobacterium Orla-Jensen. Int. J. Syst. Bacteriol. 1975, 25, 160–172. [Google Scholar] [CrossRef]
  31. Torriani, S.; Felis, G.E.; Dellaglio, F. Differentiation of Lactobacillus plantarum, L. pentosus, and L. paraplantarum by recA Gene Sequence Analysis and Multiplex PCR Assay with recA Gene-Derived Primers. Appl. Environ. Microbiol. 2001, 67, 3450–3454. [Google Scholar] [CrossRef] [PubMed]
  32. Pérez-Díaz, I.M.; Johanningsmeier, S.D.; Anekella, K.; Pagán-Medina, C.G.; Méndez-Sandoval, L.; Arellano, C.; Price, R.; Daughtry, K.V.; Borges, M.; Bream, C.; et al. Genotypic and phenotypic diversity among Lactobacillus plantarum and Lactobacillus pentosus isolated from industrial scale cucumber fermentations. Food Microbiol. 2021, 94, 103652. [Google Scholar] [CrossRef] [PubMed]
  33. Figueras, M.J.; Beaz-Hidalgo, R.; Hossain, M.J.; Liles, M.R. Taxonomic Affiliation of New Genomes Should Be Verified Using Average Nucleotide Identity and Multilocus Phylogenetic Analysis. Genome Announc. 2014, 2, e00927-14. [Google Scholar] [CrossRef] [PubMed]
  34. Richter, M.; Rosselló-Móra, R. Shifting the genomic gold standard for the prokaryotic species definition. Proc. Natl. Acad. Sci. USA 2009, 106, 19126–19131. [Google Scholar] [CrossRef]
  35. Anekella, K.; Pérez-Díaz, I.M. Characterization of robust Lactobacillus plantarum and Lactobacillus pentosus starter cultures for environmentally friendly low-salt cucumber fermentations. J. Food Sci. 2020, 85, 3487–3497. [Google Scholar] [CrossRef]
  36. Fleming, H.P.; McFeeters, R.F.; Daeschel, M.A.; Humphries, E.G.; Thompson, R.L. Fermentation of Cucumbers in Anaerobic Tanks. J. Food Sci. 1988, 53, 127–133. [Google Scholar] [CrossRef]
  37. McDonald, L.C.; Shieh, D.-H.; Fleming, H.P.; McFeeters, R.F.; Thompson, R.L. Evaluation of malolactic-deficient strains of Lactobacillus plantarum for use in cucumber fermentations. Food Microbiol. 1993, 10, 489–499. [Google Scholar] [CrossRef]
  38. Fideler Moore, J. Generation of Bioactive Peptides and ɣ-Aminobutyric Acid (GABA) during Natural Lactic Acid Fermentation of Cucumber. Ph.D. Thesis, North Carolina State University, Raleigh, NC, USA, 2021. Available online: https://www.lib.ncsu.edu/resolver/1840.20/38713 (accessed on 1 June 2023).
  39. Page, C.A.; Pérez-Díaz, I.M. Whole-Genome Sequencing and Annotation of Selected Lactobacillales Isolated from Commercial Cucumber Fermentation. Microbiol. Resour. Announc. 2021, 10, e0062521. [Google Scholar] [CrossRef]
  40. Markowitz, V.M.; Chen, I.-M.A.; Palaniappan, K.; Chu, K.; Szeto, E.; Grechkin, Y.; Ratner, A.; Jacob, B.; Huang, J.; Williams, P.; et al. IMG: The integrated microbial genomes database and comparative analysis system. Nucleic Acids Res. 2012, 40, D115–D122. [Google Scholar] [CrossRef]
  41. Jain, C.; Rodriguez-R, L.M.; Phillippy, A.M.; Konstantinidis, K.T.; Aluru, S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat. Commun. 2017, 9, 5114. [Google Scholar] [CrossRef]
  42. Versalovic, J.; Schneider, M.; De Bruijn, F.J.; Lupski, J.R. Genomic fingerprinting of bacteria using repetitive sequence-based polymerase chain reaction. Meth. Mol. Cell. Biol. 1994, 5, 25–40. [Google Scholar]
  43. Alanjary, M.; Steinke, K.; Ziemert, N. AutoMLST: An automated web server for generating multi-locus species trees highlighting natural product potential. Nucleic Acids Res. 2019, 47, W276–W282. [Google Scholar] [CrossRef] [PubMed]
  44. Davis, J.J.; Wattam, A.R.; Aziz, R.K.; Brettin, T.; Butler, R.; Butler, R.M.; Chlenski, P.; Conrad, N.; Dickerman, A.; Dietrich, E.M.; et al. The PATRIC Bioinformatics Resource Center: Expanding data and analysis capabilities. Nucleic Acids Res. 2020, 48, D606–D612. [Google Scholar] [CrossRef] [PubMed]
  45. Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014, 30, 1312–1313. [Google Scholar] [CrossRef] [PubMed]
  46. Letunic, I.; Bork, P. Interactive Tree Of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021, 49, W293–W296. [Google Scholar] [CrossRef]
  47. Russel, J.; Pinilla-Redondo, R.; Mayo-Muñoz, D.; Shah, S.A.; Sørensen, S.J. CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci. CRISPR J. 2020, 3, 462–469. [Google Scholar] [CrossRef]
  48. Nethery, M.A.; Barrangou, R. Predicting and visualizing features of CRISPR–Cas systems. Methods Enzymol. 2019, 616, 323–362. [Google Scholar] [CrossRef]
  49. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
  50. Arndt, D.; Grant, J.R.; Marcu, A.; Sajed, T.; Pon, A.; Liang, Y.; Wishart, D.S. PHASTER: A better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016, 44, W16–W21. [Google Scholar] [CrossRef]
  51. Zhou, Y.; Liang, Y.; Lynch, K.H.; Dennis, J.J.; Wishart, D.S. PHAST: A Fast Phage Search Tool. Nucleic Acids Res. 2011, 39, W347–W352. [Google Scholar] [CrossRef]
  52. Davidson, B.E.; Kordias, N.; Dobos, M.; Hillier, A.J. Genomic organization of lactic acid bacteria. Antonie Leeuwenhoek 1996, 70, 161–183. [Google Scholar] [CrossRef] [PubMed]
  53. Yampolsky, L.Y. Mutation and genome evolution. In Encyclopedia of Evolutionary Biology; Kliman, E.D., Ed.; Academic Press: Cambridge, MA, USA, 2016; pp. 77–83. [Google Scholar] [CrossRef]
  54. Makarova, K.; Slesarev, A.; Wolf, Y.; Sorokin, A.; Mirkin, B.; Koonin, E.; Pavlov, A.; Pavlova, N.; Karamychev, V.; Polouchine, N.; et al. Comparative genomics of the lactic acid bacteria. Proc. Natl. Acad. Sci. USA 2006, 103, 15611–15616. [Google Scholar] [CrossRef] [PubMed]
  55. Bobay, L.-M.; Ochman, H. The Evolution of Bacterial Genome Architecture. Front. Genet. 2017, 8, 72. [Google Scholar] [CrossRef]
  56. Sela, I.; Wolf, Y.I.; Koonin, E.V. Theory of prokaryotic genome evolution. Proc. Natl. Acad. Sci. USA 2016, 113, 11399–11407. [Google Scholar] [CrossRef]
  57. Westoby, M.; Aagren, D.; Gillings, M.R.; Litchman, E.; Madin, J.S.; Paulsen, I.T.; Tetu, S.G. Cell size, genome size, and maximum growth rate are near-independent dimensions of ecological variation across bacteria and archaea. Ecol. Evol. 2021, 11, 3956–3976. [Google Scholar] [CrossRef] [PubMed]
  58. Goris, J.; Konstantinidis, K.T.; Klappenbach, J.A.; Coenye, T.; Vandamme, P.; Tiedje, J.M. DNA–DNA hybridization values and their relationship to whole-genome sequence similarities. Int. J. Syst. Evol. Microbiol. 2007, 57, 81–91. [Google Scholar] [CrossRef] [PubMed]
  59. Daeschel, M.A.; McFeeters, R.F.; Fleming, H.P. Modification of lactic acid bacteria for cucumber fermentations: Elimination of carbon dioxide production from malate. Devel. Ind. Microbiol. 1985, 26, 339–346. [Google Scholar]
  60. Suo, C.; Yin, Y.; Wang, X.; Lou, X.; Song, D.; Wang, X.; Gu, Q. Effects of Lactobacillus plantarum ZJ316 on pig growth and pork quality. BMC Vet. Res. 2012, 8, 89. [Google Scholar] [CrossRef]
  61. Parlindungan, E.; May, B.K.; Jones, O.A.H. Metabolic Insights into the Effects of Nutrient Stress on Lactobacillus plantarum B21. Front. Mol. Biosci. 2019, 6, 75. [Google Scholar] [CrossRef]
  62. Golneshin, A.; Gor, M.-C.; Williamson, N.; Vezina, B.; Van, T.T.H.; May, B.K.; Smith, A.T. Discovery and characterisation of circular bacteriocin plantacyclin B21AG from Lactiplantibacillus plantarum B21. Heliyon 2020, 6, e04715. [Google Scholar] [CrossRef]
  63. Barrangou, R.; Dudley, E.G. CRISPR-Based Typing and Next-Generation Tracking Technologies. Annu. Rev. Food Sci. Technol. 2016, 7, 395–411. [Google Scholar] [CrossRef]
  64. Horvath, P.; Romero, D.A.; Coûté-Monvoisin, A.C.; Richards, M.; Deveau, H.; Moineau, S.; Boyaval, P.; Fremaux, C.; Barrangou, R. Diversity, Activity, and Evolution of CRISPR Loci in Streptococcus thermophilus. J. Bacteriol. 2008, 190, 1401–1412. [Google Scholar] [CrossRef]
  65. Shariat, N.; DiMarzio, M.J.; Yin, S.; Dettinger, L.; Sandt, C.H.; Lute, J.R.; Barrangou, R.; Dudley, E.G. The combination of CRISPR-MVLST and PFGE provides increased discriminatory power for differentiating human clinical isolates of Salmonella enterica subsp. enterica serovar Enteritidis. Food Microbiol. 2013, 34, 164–173. [Google Scholar] [CrossRef] [PubMed]
  66. Toro, M.; Cao, G.; Ju, W.; Allard, M.; Barrangou, R.; Zhao, S.; Brown, E.; Meng, J. Association of Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) Elements with Specific Serotypes and Virulence Potential of Shiga Toxin-Producing Escherichia coli. Appl. Environ. Microbiol. 2014, 80, 1411–1420. [Google Scholar] [CrossRef] [PubMed]
  67. Barrangou, R.; Fremaux, C.; Deveau, H.; Richards, M.; Boyaval, P.; Moineau, S.; Romero, D.A.; Horvath, P. CRISPR Provides Acquired Resistance Against Viruses in Prokaryotes. Science 2007, 315, 1709–1712. [Google Scholar] [CrossRef] [PubMed]
  68. Lu, Z.; Pérez-Díaz, I.M.; Hayes, J.S.; Breidt, F. Bacteriophage Ecology in a Commercial Cucumber Fermentation. Appl. Environ. Microbiol. 2012, 78, 8571–8578. [Google Scholar] [CrossRef] [PubMed]
  69. Lu, Z.; Breidt, F.; Plengvidhya, V.; Fleming, H.P. Bacteriophage Ecology in Commercial Sauerkraut Fermentations. Appl. Environ. Microbiol. 2003, 69, 3192–3202. [Google Scholar] [CrossRef]
  70. Ramisetty, B.C.M.; Sudhakari, P.A. Bacterial “Grounded” Prophages: Hotspots for Genetic Renovation and Innovation. Front. Genet. 2019, 10, 65. [Google Scholar] [CrossRef]
Foods 12 02455 g001 550
Figure 1. Descriptive data of the Lactiplantibacillus plantarum (■) and Lactiplantibacillus pentosus (□) genome sequence features and coding gene type. A significant difference (p-value < 0.05) was calculated for panels identified with an asterisk (*).
Figure 1. Descriptive data of the Lactiplantibacillus plantarum (■) and Lactiplantibacillus pentosus (□) genome sequence features and coding gene type. A significant difference (p-value < 0.05) was calculated for panels identified with an asterisk (*).
Foods 12 02455 g001
Foods 12 02455 g002 550
Figure 2. Heat maps displaying average nucleotide identity (ANI) for L. pentosus versus L. plantarum (A) and within L. plantarum (B) and L. pentosus (C) isolates versus a selection of reference genomic DNA sequences. Darker shading indicates elevated relative ANI scores between two isolates or reference strains.
Figure 2. Heat maps displaying average nucleotide identity (ANI) for L. pentosus versus L. plantarum (A) and within L. plantarum (B) and L. pentosus (C) isolates versus a selection of reference genomic DNA sequences. Darker shading indicates elevated relative ANI scores between two isolates or reference strains.
Foods 12 02455 g002
Foods 12 02455 g003 550
Figure 3. Computer-emulated Rep-PCR-(GTG)5 and banding pattern clustering analysis based on 40 genome sequences from selected Lactobacillales. L. pentosus and L. plantarum isolates are labeled blue and orange, respectively.
Figure 3. Computer-emulated Rep-PCR-(GTG)5 and banding pattern clustering analysis based on 40 genome sequences from selected Lactobacillales. L. pentosus and L. plantarum isolates are labeled blue and orange, respectively.
Foods 12 02455 g003
Foods 12 02455 g004 550
Figure 4. Phylogenetic trees, including all L. plantarum and L. pentosus isolates as well as multiple reference strains for each species based on MLST of sequences from 79 common ORFs (A) and the alignment of 587 common ORFs (B). Colored bands indicate L. plantarum isolates and reference strains and L. pentosus phylogenetic subgroups clade A and clade B. Pediococcus damnosus DSM 20331 was selected as the root for both trees based on AutoMLST automatic selection. Trees without scale are included in order to more clearly indicate branching, with matched colored triangles representing groupings in the circular trees.
Figure 4. Phylogenetic trees, including all L. plantarum and L. pentosus isolates as well as multiple reference strains for each species based on MLST of sequences from 79 common ORFs (A) and the alignment of 587 common ORFs (B). Colored bands indicate L. plantarum isolates and reference strains and L. pentosus phylogenetic subgroups clade A and clade B. Pediococcus damnosus DSM 20331 was selected as the root for both trees based on AutoMLST automatic selection. Trees without scale are included in order to more clearly indicate branching, with matched colored triangles representing groupings in the circular trees.
Foods 12 02455 g004
Foods 12 02455 g005 550
Figure 5. A phylogenetic tree based on 1000 core genes in L. pentosus autochthonous to cucumber and olive fermentations and reference strains. Subclades A.I, A.II, and A.III and clade B are indicated with superimposed color bands. L. pentosus KCA1 is the root for this tree. The rectangular tree diagram with collapsed nodes representing matching-colored clades is included to more clearly show individual branches.
Figure 5. A phylogenetic tree based on 1000 core genes in L. pentosus autochthonous to cucumber and olive fermentations and reference strains. Subclades A.I, A.II, and A.III and clade B are indicated with superimposed color bands. L. pentosus KCA1 is the root for this tree. The rectangular tree diagram with collapsed nodes representing matching-colored clades is included to more clearly show individual branches.
Foods 12 02455 g005
Foods 12 02455 g006 550
Figure 6. The Type II-A CRISPR spacers were extracted and aligned from L. plantarum (■) and L. pentosus autochthonous to commercial cucumber fermentation belonging to subclade A.I (■), subclade A.II (■), subclade A.II (■), or 7.8.2 (■). Differently colored boxes represent individual spacer sequences in each CRISPR array. Identically colored boxes in two or more isolates indicate a shared spacer sequence between those isolates.
Figure 6. The Type II-A CRISPR spacers were extracted and aligned from L. plantarum (■) and L. pentosus autochthonous to commercial cucumber fermentation belonging to subclade A.I (■), subclade A.II (■), subclade A.II (■), or 7.8.2 (■). Differently colored boxes represent individual spacer sequences in each CRISPR array. Identically colored boxes in two or more isolates indicate a shared spacer sequence between those isolates.
Foods 12 02455 g006
Foods 12 02455 g007 550
Figure 7. The Type I-E CRISPR spacers were extracted and aligned from the L. pentosus clade A genomes, subclade A.I (■), subclade A.II (■), and subclade A.III (■). All L. pentosus strains were isolated from commercial cucumber fermentations. Differently colored boxes represent individual spacer sequences in each CRISPR array. Identically colored boxes in two or more isolates indicate a shared spacer sequence between those isolates. Asterisks indicate CRISPR spacer arrays detected in separate subclades.
Figure 7. The Type I-E CRISPR spacers were extracted and aligned from the L. pentosus clade A genomes, subclade A.I (■), subclade A.II (■), and subclade A.III (■). All L. pentosus strains were isolated from commercial cucumber fermentations. Differently colored boxes represent individual spacer sequences in each CRISPR array. Identically colored boxes in two or more isolates indicate a shared spacer sequence between those isolates. Asterisks indicate CRISPR spacer arrays detected in separate subclades.
Foods 12 02455 g007
Foods 12 02455 g008 550
Figure 8. Type I-E CRISPR spacers extracted and aligned from L. pentosus clade B genomes (■) and the L. pentosus 7.8.2 genome (■). All L. pentosus strains were isolated from commercial cucumber fermentations. Differently colored boxes represent individual spacer sequences in each CRISPR array. Identically colored boxes in two or more isolates indicate a shared spacer sequence between those isolates.
Figure 8. Type I-E CRISPR spacers extracted and aligned from L. pentosus clade B genomes (■) and the L. pentosus 7.8.2 genome (■). All L. pentosus strains were isolated from commercial cucumber fermentations. Differently colored boxes represent individual spacer sequences in each CRISPR array. Identically colored boxes in two or more isolates indicate a shared spacer sequence between those isolates.
Foods 12 02455 g008
Foods 12 02455 g009 550
Figure 9. Incidence of phages (%) in industrial cucumber fermentations as determined via metagenomic analysis conducted by Pérez-Díaz et al. (2020) (A), and spacer matches to Lactobacillus ɸ phiJL1 (B) and Lactobacillus ɸ Sha1(C).
Figure 9. Incidence of phages (%) in industrial cucumber fermentations as determined via metagenomic analysis conducted by Pérez-Díaz et al. (2020) (A), and spacer matches to Lactobacillus ɸ phiJL1 (B) and Lactobacillus ɸ Sha1(C).
Foods 12 02455 g009
Table
Table 1. GenBank accession numbers for the genome sequences used in this study.
Table 1. GenBank accession numbers for the genome sequences used in this study.
Strain Accession NumberStrain Accession Number
Lactiplantibacillus plantarum
CMPG5300GCA_000762955.1JDM1GCA_000023085.1
B21GCA_000931425.2DOMLaGCA_000604105.1
WCFS1GCA_000203855.16GCA_000412205.1
ZJ316GCA_000338115.2P-8GCA_000392485.2
ATCC14917GCA_000143745.17.8.4GCA_018993285.1
LPL-1GCA_002205775.23.2.8GCA_018991195.1
ST-IIIGCA_000148815.2T1R2bGCA_018993325.1
CGMCC1.557GCA_001272315.2
Lactiplantibacillus pentosus
BGM48GCA_002850015.11.8.6GCA_018991355.1
FL0421GCA_001188985.11.8.9GCA_018993945.1
ZFM222GCA_003627295.11.8.18GCA_018993635.1
MP-10GCA_900092635.13.2.37GCA_018993495.1
KCA1GCA_000271445.13.2.36GCA_018993725.1
RI-031GCA_002751855.13.8.24GCA_018993345.1
MS031GCA_016804305.13.8.45GCA_018991565.1
SLC13GCA_002211885.17.2.4GCA_018991185.1
IG2GCA_002993465.17.2.11GCA_018991375.1
IG3GCA_002993425.17.2.15GCA_018993445.1
IG4GCA_002993385.17.2.20GCA_018993665.1
IG5GCA_002993435.17.2.23GCA_018993485.1
IG6GCA_002993485.17.8.2GCA_018991535.1
IG7GCA_002993395.17.8.11GCA_018993275.1
IG8GCA_003702625.17.8.46GCA_018991465.1
IG9GCA_003702665.114.8.42GCA_018993525.1
IG10GCA_003702635.114.2.3GCA_018991425.1
IG11GCA_003702605.114.2.16GCA_018993625.1
IG12GCA_003702565.130.2.29GCA_018991255.1
1.2.7GCA_018991365.1LA0445GCA_018993965.1
1.2.11GCA_018991285.1MU045GCA_018993585.1
1.2.13GCA_018991345.1
Weissella spp.Leuconostoc spp.
W. paramesenteroides 3.2.24GCA_018991665.1Leu. citreum 3.8.12GCA_018991475.1
W. cibaria 7.8.34GCA_025770435.1Leu. lactis 1.2.50GCA_018993865.1
W. cibaria 3.8.44GCA_018993825.1Leu. fallax 1.2.22GCA_018993745.1
W. sagaensis 1.2.50GCA_018993865.1Leu. mesenteroides 1.2.47GCA_018991785.1
Pediococcus spp.Lactococcus spp.
P. ethanolidurans 90.8.30GCA_018993685.1Lc. lactis LA0312GCA_018991605.1
P. damnosus DSM 20331GCA_001437255.1Lc. lactis 1.8.12GCA_018991645.1
Levilactobacillus spp.
Lev. brevis 14.2.24GCA_018993885.1Lactiplantibacillus paraplantarum L-ZS9GCA_001443645.1
Lev. brevis 14.2.10GCA_018991505.1
Lev. brevis 3.2.41GCA_018991675.1
Table
Table 2. Incidence of CRISPR loci in the genomic DNA sequences of L. plantarum and L. pentosus autochthonous to cucumber fermentation and reference strains by type.
Table 2. Incidence of CRISPR loci in the genomic DNA sequences of L. plantarum and L. pentosus autochthonous to cucumber fermentation and reference strains by type.
Genomic DNA Sequence Identification
L. plantarumL. pentosus
3.2.87.8.4T1R2bSubclade A.ISubclade A.IISubclade A.IIIClade B7.8.2
CRISPR loci1104 ± 144 ± 12 ± 15
Type I-E0002 322 ± 14
Type II-A1102 ± 111 ± 101
Table
Table 3. Closest matches to the putative prophages found in the L. pentosus and L. plantarum genomic sequences in the NCBI database.
Table 3. Closest matches to the putative prophages found in the L. pentosus and L. plantarum genomic sequences in the NCBI database.
Closest Homolog Identity (>95%)L. plantarum Isolates Autochthonous to Cucumber Fermentation
3.2.87.8.4T1R2b
Siphoviridae sp. ctu0P1 X
Siphoviridae sp. ctyPQ2 X
Siphoviridae sp. ct97I3 X
Siphoviridae sp. ctk5O4
Siphoviridae sp. ctUZT2 X
Closest Homolog
Identity (>95%)		L. pentosus Isolates Autochthonous to Cucumber Fermentation
Subclade A.ISubclade A.IISubclade A.IIIClade B
1.2.7 1.2.13 3.8.24 1.8.6 1.2.11 3.2.37 30.2.29 1.8.9 7.2.23 3.2.36 3.8.45 1.8.18 7.8.46 7.2.20 14.2.3 7.2.15 14.2.16 14.8.42 7.8.11 7.2.11 7.2.4 LA0445 MU0045 7.8.2
Siphoviridae ctu0P1 XXXXX X
Siphoviridae ctyPQ2
Siphoviridae ct97I3
Siphoviridae ctk5O4 X
Siphoviridae ctUZT2
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Page, C.A.; Pérez-Díaz, I.M.; Pan, M.; Barrangou, R. Genome-Wide Comparative Analysis of Lactiplantibacillus pentosus Isolates Autochthonous to Cucumber Fermentation Reveals Subclades of Divergent Ancestry. Foods 2023, 12, 2455. https://doi.org/10.3390/foods12132455

AMA Style

Page CA, Pérez-Díaz IM, Pan M, Barrangou R. Genome-Wide Comparative Analysis of Lactiplantibacillus pentosus Isolates Autochthonous to Cucumber Fermentation Reveals Subclades of Divergent Ancestry. Foods. 2023; 12(13):2455. https://doi.org/10.3390/foods12132455

Chicago/Turabian Style

Page, Clinton A., Ilenys M. Pérez-Díaz, Meichen Pan, and Rodolphe Barrangou. 2023. "Genome-Wide Comparative Analysis of Lactiplantibacillus pentosus Isolates Autochthonous to Cucumber Fermentation Reveals Subclades of Divergent Ancestry" Foods 12, no. 13: 2455. https://doi.org/10.3390/foods12132455

APA Style

Page, C. A., Pérez-Díaz, I. M., Pan, M., & Barrangou, R. (2023). Genome-Wide Comparative Analysis of Lactiplantibacillus pentosus Isolates Autochthonous to Cucumber Fermentation Reveals Subclades of Divergent Ancestry. Foods, 12(13), 2455. https://doi.org/10.3390/foods12132455

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop