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Article

Dissecting of the AI-2/LuxS Mediated Growth Characteristics and Bacteriostatic Ability of Lactiplantibacillus plantarum SS-128 by Integration of Transcriptomics and Metabolomics

by
Yilin Qian
,
Yuan Li
,
Tengteng Xu
,
Huijuan Zhao
,
Mingyong Zeng
and
Zunying Liu
*
College of Food Science and Engineering, Ocean University of China, Qingdao 266003, China
*
Author to whom correspondence should be addressed.
Foods 2022, 11(5), 638; https://doi.org/10.3390/foods11050638
Submission received: 26 January 2022 / Revised: 17 February 2022 / Accepted: 19 February 2022 / Published: 22 February 2022
(This article belongs to the Special Issue Structure Identification and Functional Mechanism of Natural Active Components)
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Abstract

:
Lactiplantibacillus plantarum could regulate certain physiological functions through the AI-2/LuxS-mediated quorum sensing (QS) system. To explore the regulation mechanism on the growth characteristics and bacteriostatic ability of L. plantarum SS-128, a luxS mutant was constructed by a two-step homologous recombination. Compared with ΔluxS/SS-128, the metabolites of SS-128 had stronger bacteriostatic ability. The combined analysis of transcriptomics and metabolomics data showed that SS-128 exhibited higher pyruvate metabolic efficiency and energy input, followed by higher LDH level and metabolite overflow compared to ΔluxS/SS-128, resulting in stronger bacteriostatic ability. The absence of luxS induces a regulatory pathway that burdens the cysteine cycle by quantitatively drawing off central metabolic intermediaries. To accommodate this mutations, ΔluxS/SS-128 exhibited lower metabolite overflow and abnormal proliferation. These results demonstrate that the growth characteristic and metabolism of L. plantarum SS-128 are mediated by the AI-2/LuxS QS system, which is a positive regulator involved in food safety. It would be helpful to investigate more bio-preservation control potential of L. plantarum, especially when applied in food industrial biotechnology.

Graphical Abstract

1. Introduction

Lactic acid bacteria (LAB) comprise a huge group of safe and widespread microorganisms in nature, and they are primarily applied as starter cultures and probiotics [1,2]. LAB are apprehended as ideal candidates for commercial exploitation in food industry with their status recognized as Generally Regarded As Safe (GRAS) and Qualified Presumption of Safety (QPS) in the European Union [3,4]. Aside from the health-promoting and probiotic properties, certain LAB producing organic acids, including lactic acid and phenyllactic acid (PLA), are also associated with food industrial biotechnology, providing food preservation for biocatalysis [5,6,7,8,9]. Today’s food industry faces the tremendous problem in producing goods that are not only productive, but also wholesome for customers, as well as longer-lasting [4,5]. Consequently, the scientific research in the potential of LAB as bio-preservatives has attracted continuous interest. Strategies of enhancement on bio-preservation potential can be roughly classified into two major types: the strain development strategy and microbiological control strategy. The strain development strategy involves natural approaches or metabolic engineering, and it is used for strain transformation. The microbiological control strategy involves the regulation of LAB to microorganisms throughout the food system or environment. Both strategies are regulated by quorum sensing (QS), which provides new opportunities to enhance the safety and quality of foods by the “positive regulation” of QS.
QS, associated with some cellular activities, is a process in which cells socially coordinate gene expression, involving producing extracellular signaling molecules called autoinducers [10,11,12]. The QS mediated by autoinducer-2 (AI-2)/LuxS could be detected in various Gram-negative and -positive organisms [13,14]. The gene luxS converts S-ribosomal homocysteine (SRH) into homocysteine and 4,5-dihydroxy-2,3-pentanedione (DPD) that undergoes spontaneous rearrangements to form AI-2. The exogenous addition of AI-2 could show influences on the biofilm formation, bacteriostatic action, and stress tolerance by LAB have been reported [14,15,16,17,18]. However, to enhance the “positive regulation” of QS in LAB, focusing on the metabolic pathway regulated by luxS could be an effective way compared with the addition of expensive signaling molecules. Previous studies have shown that the inactivation of the luxS gene has shown greatly impacts on the Lactobacillus reuteri 100-23C behaviors, which are inhabited in mice intestinal tracts [19]. Lebeer et al. reported that the luxS mutation could show indirect impact on biofilm formation in Lactobacillus rhamnosus GG, while it was not impacted by exogenous AI-2 mediated QS [20]. The role of the luxS mediated molecular mechanisms from the proteomic analyses in bacteriocin production was reported by Jia et al. [21]. However, the growth characteristic of the wild strain and the luxS mutant in the above studies showed inconsistent trends. Meanwhile, the regulation of AI-2/LuxS on LAB growth characteristics and bacteriostatic ability has not been elucidated yet.
L. plantarum possesses the ability of rapid proliferation, due to the strong resistance against the environment of complex food matrix, indicating its high potential for industrial application [16,22]. Unlike other strains, L. plantarum can synthesize homocysteine from cysteine by direct sulfhydrylation involving the cysK enzyme, to ensure the regeneration of the methyl group of S-adenosyl methionine (SAM) [20]. Since the unique functions of the cysK enzyme carried out are pretty similar to the luxS, we hypothesized that it contributes to enhancing the growth ability and stress resistance of L. plantarum, and also helps to focus on the luxS.
Previously, we found that the cooperation of L. plantarum showed high biopreservative activity, which was related to the AI-2/LuxS system [23], but the role of the luxS system has not been clearly elucidated. In this study, we aimed to understand the regulation mechanism of the AI-2/LuxS-mediated QS system on the growth characteristics and bacteriostatic ability of LAB, to provide a basis for improving its bio-preservation function.

2. Materials and Methods

2.1. Construction of luxS-Mutant of SS-128

The luxS-mutant of SS-128, named ΔluxS/SS-128, was constructed using fusion PCR and a two-step homologous recombination. In brief, the luxS gene-flanked two fragments were amplified and fused by overlap extension PCR with a primer pair. The primers are shown in Table 1. The ligation products, transforming into competent Escherichia coli pFED760, generated the recombinant plasmids, which carried the homologous fragments for allelic exchange of flanking fragments of the luxS gene. The pFED760 was a temperature-sensitive plasmid and was a kind gift from Professor Yiyong Luo (Kunming University of Science and Technology, Kunming, China). Recombinant plasmids pFED760-luxS were extracted and transformed into SS-128 by electroporation. The ΔluxS/SS-128 was constructed through a two-step homologous recombination by changing the temperature to control the replication and suicide of pFED760.

2.2. AI-2 Assay

The AI-2 bioluminescence assay was operated according to the approach with some modifications [24]. The Vibrio harveyi strain BB170 was cultured in AB medium at 30 °C for 12 h and diluted with the AB medium at a ratio of 1:5000. The medium was added to the diluted V. harveyi culture at a final concentration of 10% (v/v). The white 96-well plates vibrated at 100 rpm at 30 °C (PBS was used as the negative control). Light production was recorded every 30 min using a Synergy H4 hybrid microplate reader (Bio-Tek, Winooski, VT, USA) in the bioluminescence mode. AI-2 activity was calculated as the difference compared with the bioluminescence level in the control group and presented as relative luminescence units (RLUs).
The total RNA was directly extracted from L. plantarum according to the approach described by Zhang et al. at incubation times of 6, 8, 10, 12, 14, 16, 20, 24, 36, 48 h, respectively [25]. The bacteria were collected after being washed twice with PBS. According to the protocol, the obtained precipitate was used for total RNA extraction with TRIzol Reagent (Invitrogen, Carlsbad, CA, USA). The quality of the RNA was detected through the agarose gel electrophoresis, and the concentration was measured through the NanoDrop spectrophotometer (Nano-200, Hangzhou Austrian Sheng Instrument Co., Ltd., Hangzhou, China). RT-qPCR amplifications were measured in three biological replicates using a Bio-Rad CFX Connect System (Bio-Rad Laboratories, Inc., California, USA). The housekeeping gene, 16S rRNA, was chosen to normalize RNA amounts (internal control). The sequences coding for the 16S rRNA, luxS of the wild type (WT) SS-128 and the mutant strain ΔluxS/SS-128, were designed based on the L. plantarum WCFS1 gene sequences (GenBank, no. NC_004567.2, from https://www.ncbi.nlm.nih.gov/nuccore/NC_004567.2/, accessed on 10 April 2021). qPCR was performed with ChamQ SYBR Color qPCR Master Mix on a CFX Connect Real-Time PCR Detection System (Bio-Rad Laboratories, Inc., Hercules, CA, USA). The primer sequence is demonstrated in Table 1. Each experiment was repeated three times and analyzed using the 2−∆ΔCT method.

2.3. Bacterial Growth Assay

SS-128 (wild type) and ΔluxS/SS-128 (luxS mutant type) were first propagated twice in MRS broth at 37 °C overnight. The 1% overnight cultures (18 h) were inoculated into a 5 mL fresh medium under aerobic conditions at 37 °C for 48 h. During the incubation, the bacterial density of the samples was determined every 2 h at 600 nm. Plate counting was used to determine the live cell number of the samples. The WT and mutant strains cultured for 14 h were collected by centrifugation and then were immediately frozen and stored at −80 °C.

2.4. Flow Cytometry Assay

The live/dead cells were determined by flow cytometry employing fluorescence after being stained with SYTO 9 and propidium iodide (PI). The counting method was constructed by Leonard and Bensch et al. [25,26], with some modifications. Cells (102–103 cells/μL) were incubated with SYTO 9 (5 μg/mL) and PI (5 μg/mL) for 3 min in dark. Flow cytometric analyses were carried out using a BD FACSVerse™ flow cytometry (BD Biosciences, San Jose, CA, USA). Data were analyzed by using FlowJo software 10.6.1 (Tree Star Inc., Ashland, OR, USA).

2.5. Determination of Bacteriostatic Ability

The agar diffusion assay was used to identify the bacteriostatic ability of cell-free supernatant (CFS) by Zhang and Li et al. [27,28]. A 15 mL aliquot of 0.4% soft agar with 2% bacterial culture medium was poured into a sterile Petri dish, and sterile Oxford cups (ϕ = 7.64 mm) were put on the surface of the medium. The Oxford cup was filled with the CFS of L. plantarum (200 μL). The inhibition zone could be measured after incubation at 28 °C for 24 h.

2.6. Transcriptome Analysis

RNA isolation and high-throughput RNA sequencing (RNA-Seq) were conducted by Oebiotech Corp. (Shanghai, China). Total RNA was extracted using a Total RNA Purification Kit (Sangon Biotech, Shanghai, China), followed by evaluating the RNA integrity on Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The libraries were sequenced on an Illumina sequencing platform (HiSeq 2500), and 150-bp/125-bp paired-end reads were generated. The gene expression profiles were analyzed based on reads per kilobase of transcript per million mapped read (RPKM) normalization. DESeq was used to standardize the counts of genes in each sample, and NB was used to test the difference significance of reads. Differential genes were screened according to the difference multiple and different significance test results. Finally, the GO and KEGG enrichment of differentially expressed genes were analyzed under the cutoff of p-value < 0.05 using the BLAST program.

2.7. Non-Targeted Metabolomic Analysis

2.7.1. Sample Preparation

A total of 20 μL of 2-chloro-l-phenylalanine (0.3 mg/mL) dissolved in methanol as internal standard and methanol-water (4:1 = v/v) were added to each sample. Trichloromethane was added to each aliquot. The mixture was extracted in the ice water bath with ultrasonication for 20 min and then centrifugation (13,000 rpm, for 10 min at 4 °C). A total of 1 mL of supernatant was dried in a freeze concentration centrifugal dryer, sequentially redissolved in 25% methanol, and incubated at 4 °C for 2 min. After that, the mixtures were centrifuged again, using the same step as before. The supernatant of each tube was filtered to LC–MS and GC–MS for analysis. QC samples were prepared by mixing aliquots of all samples to be a pooled sample.

2.7.2. Gas Chromatography/Mass Spectrometry (GC/MS) Analysis

The derivatized samples were analyzed on an Agilent 7890B gas chromatography system coupled to an Agilent 5977A MSD system (Agilent Technologies Inc., CA, USA). A DB-5MS fused-silica capillary column (30 m × 0.25 mm × 0.25 μm, Agilent J&W Scientific, Folsom, CA, USA) was utilized to separate the derivatives. Helium (>99.999%) was used as the carrier gas at a 1 mL/min constant flow rate through the column. The QCs were injected at regular intervals throughout the analytical run to provide a set of data from which repeatability could be assessed.

2.7.3. Ultrahigh Performance Liquid Chromatography/Mass Spectrometry (UPLC/MS) Analysis

ACQUITY UPLC I-Class system (Waters Corporation Milford, Milford, MA, USA) coupled with VION IMS QTOF Mass spectrometer (Waters Corporation Milford, Milford, MA, USA) was used to analyze the metabolic profiling in both ESI positive and ESI negative ion modes. An ACQUITY UPLC BEH C18 column (1.7 μm, 2.1 × 100 mm) was employed in both positive and negative modes. Water and Acetonitrile/Methanol 2/3 (v/v), both containing 0.1% formic acid were used as mobile phases A and B, respectively. The injection volume was 1 μL. Data were collected in full scan mode (m/z ranges from 50 to 1000) combined with MSE mode, including two independent scans with different collision energies (CE) that were alternatively acquired during the running process.

2.7.4. Data Preprocessing and Analysis

The acquired LC–MS raw data were analyzed by the progenesis QI software (Waters Corporation, Milford, CT, USA) to identify the metabolites. The raw data were converted to .abf format, followed by processing on the MD-DIAL software through LUG database (Untargeted database of GC–MS rom Lumingbio).
Principle component analysis (PCA) and (orthogonal) partial least-squares-discriminant analysis (O) PLS-DA were carried out to visualize the metabolic alterations among experimental groups after mean centering (Ctr) and Pareto variance (Par) scaling, respectively. Variable importance in the projection (VIP) ranks the overall contribution of each variable to the OPLS-DA model, and those variables with VIP > 1 are considered relevant for group discrimination. In this study, the default seven-round cross-validation was applied with one/seventh of the samples being excluded from the mathematical model in each round.
The differential metabolites were selected based on the combination of a statistically significant threshold of VIP values obtained from the OPLS-DA model and p values from a two-tailed Student’s t-test on the normalized peak areas, where metabolites with VIP values larger than 1.0 and p values less than 0.05 were considered as differential metabolites.

2.8. Statistical Analysis

All results were statistically analyzed with IBM SPSS Statistics version 19.0. Data were presented as means and standard deviations. One-way analysis of variance followed by Duncan’s post hoc test was used to compare the mean differences. A p-value < 0.05 was considered significant.

3. Results

3.1. Confirmation of luxS Gene Knockout

In order to confirm the function of luxS as a S-ribosylhomocysteine lyase, a knockout mutant of luxS was constructed. Gene luxS was successfully deleted by a temperature-sensitive plasmid pFED760 (Figure 1a). The PCR in the luxS-mutant generated a short 3224-bp DNA fragment (lane 1) as expected, while a normal 3701-bp DNA fragment (lane 2) was amplified in WT strain when using UD-f and UD-r primer pair in Table 1 (Figure 1b). From lane 3, it can be seen that the primers of luxS did not amplify the gene. The sequencing of PCR products also confirmed that the luxS-mutant was successfully achieved.
To determine the effect of luxS knockout on the AI-2 production ability of the strains, we monitored the AI-2 levels in the supernatants of L. plantarum SS-128 and ΔluxS/SS-128 by bioluminescence assay using the V. harveyi BB170 strain. Lack of the luxS gene, which encodes an enzyme involved in methionine metabolism, ultimately leads to the loss of AI-2. As shown in Figure 1c, the accumulation concentration of AI-2 of L. plantarum SS-128 was at its highest in the late exponential phase and diminished slowly in the stationary phase. It was agreed with the results of Amandeep et al. [29], which reported that AI-2 activity increased till the late exponential phase. Moreover, the results demonstrated that AI-2 activities of SS-128 were significantly increased at 14 h compared to those of ΔluxS/SS-128 combined with transcript-level expression analysis (Figure 1d). These data suggested that the deletion of the luxS contributed to a disability in synthesizing AI-2.

3.2. Growth Characteristics of L. plantarum SS-128 and ΔluxS/SS-128

The behaviors of L. plantarum exposed to 37 °C were summarized in Figure 2. Results in Figure 2a showed that the tested SS-128 started to grow exponentially earlier compared with ΔluxS/SS-128. The pH of SS-128 reached its lowest value (3.54) after 14 h of cultivation, then began to increase, and the time was 2 h earlier than that of defective strain. These properties differ from the growth rate of L. reuteri luxS mutant [19]. This might be account for the cysK enzyme in L. plantarum. Gu et al. reported that the exogenous synthetic AI-2 led to different growth feedback on physiological behaviors of Enterococcus faecium and Lactobacillus fermentum in vitro [15,16]. However, the live cell number of the ΔluxS/SS-128 was significantly higher than that of the SS-128 at the late exponential phase (12–18 h) (Figure 2b). It is speculated that the proportion of viable bacteria in ΔluxS/SS-128 was higher than that in the SS-128 within 12–18 h.
For determining the viable cell proportion (VCP) of L. plantarum, the SYTO 9 and PI staining was used to analyze the membrane integrity by flow cytometry. The results of double-staining on L. plantarum (Figure 2c) showed the live/dead cells, respectively. The VCP was 83.6% in SS-128 and 94.6% in ΔluxS/SS-128 at 14 h, and no apparent difference in the proportion of viable bacteria at 24 h was shown in Figure 2c (p < 0.05). The results demonstrated that the VCP in ΔluxS/SS-128 was higher than that in SS-128 during the late exponential phase. L. plantarum proliferates by binary fission, in which the cell must double its mass, replicate its DNA and divide equally to produce two daughter cells [30]. Based on this way of splitting and the adequate nutrition, the higher total number of living bacteria should exhibit an exponential increase with the normal proliferation rate of normal cells. However, the live cell number of the luxS mutant did not increase many times as much as that of the wild strain at the late exponential phase, contrary to the normal rate of the cell proliferation. Empirical evidence suggests that E. coli and Schizosaccharomyces pombe, all copied by binary division, avoid division by prolonging senescence when conditions are unfavorable [31,32]. Therefore, we hypothesized that the luxS gene might regulate cell proliferation, thereby affecting cell growth.

3.3. In Vitro Bacteriostatic Effect of L. plantarum SS-128 and ΔluxS/SS-128

LAB have great potential in hindering the activity of pathogenic and spoilage bacteria in food systems by producing bacteriostatic compounds mainly composed of organic acids [4,33]. Thus, we compared the bacteriostatic ability of cell-free supernatant against E. coli, Shewanella baltica, Staphylococcus aureus and Acinetobacter johnsonii of L. plantarum SS-128 and ΔluxS/SS-128 (Figure 2d). E. coli and S. aureus are common food spoilage and pathogenic microorganisms [34,35,36], while A. johnsonii and P. fluorescens are the main spoilage potential organism during the iced storage of aquatic products [37,38], which may pose considerable risks to the health of consumers. The activity was evaluated by Oxford cup tests with the sample from that of the CFS; the MRS broth without L. plantarum as the control. The inhibitory zone diameter of each sample was measured with calipers and summarized in Table S1. As shown in Figure 2d, the control group showed no bacteriostatic ring, indicating that MRS broth has no bacteriostatic ability against the food-borne spoilage and pathogenic bacteria. In contrast, SS-128 exhibited a clear antibacterial ring around the bacteria and was larger than that of ΔluxS/SS-128 after 14 h. In particular, the CFS of SS-128 collected at 24 h showed significant antibacterial activity against S. baltica (16.41 mm) compared with ΔluxS/SS-128 (15.18 mm) (p < 0.05). According to the above results, the metabolites of SS-128 had stronger bacteriostatic ability.

3.4. The Organic Acids Production of L. plantarum SS-128 and ΔluxS/SS-128

To further explore the regulation of the luxS gene on the main bacteriostatic metabolites (organic acids) produced by L. plantarum, the organic acids production in L. plantarum SS-128 and ΔluxS/SS-128 was measured. The data suggested that the organic acid production of L. plantarum SS-128 was significantly decreased upon knockout of the luxS gene (Figure 3a,b). The lactic acid production of L. plantarum SS-128 was 20.96% to 64.12% higher than that of the luxS mutant type in 12–16 h (p < 0.05) (Figure 3a). QS is widely believed to regulate the metabolism of bacteria (e.g., Pseudomonas aeruginosa and S. baltica) [39,40]. Similar results were observed for PLA production in 12–14 h. These results indicated that the production of lactic acid and PLA in L. plantarum might be related to the regulation of AI-2/LuxS system. In our study, a lower number of viable bacteria and stronger bacteriostatic ability persisted in SS-128 compared with ΔluxS/SS-128 after 14 h, which could further confirm the regulation of luxS on the growth characteristics and metabolism of L. plantarum.
Lactate dehydrogenase (LDH), widely distributed in diverse sources including LAB, catalyzes the reduction of pyruvate to lactic acid. It can also catalyze the conversion of phenylpyruvic acid (PPA) to PLA due to its broad substrate specificity [41]. Therefore, the determination of LDH activity could reflect the effect of luxS gene on the acid production capacity of L. plantarum. Figure 3c shows the LDH activity in L. plantarum evaluated after 8, 10, 12, 14, 16, and 24 h of cultivation. Compared with ΔluxS/SS-128 (2.32 mU/104 cell), LDH activity was significantly increased in SS-128 after 10 h (4.25 mU/104 cell) (p < 0.05). During the exponential growth period, the LDH activity of SS-128 remained stable and significantly higher than that of ΔluxS/SS-128 (p < 0.05).

3.5. Transcriptomics Analyses between L. plantarum SS-128 and the ΔluxS/SS-128

The luxS gene is involved in QS, which has been shown to regulate critical physiological traits and various adaptive processes in different bacteria [42,43]. Therefore, probing the relationship between AI-/LuxS-mediated QS and the cell transcriptional expression levels is the premise to influence bacterial metabolites accumulation. Based on this, the expression profile of L. plantarum without luxS gene was discerning, and transcriptome analysis was performed on wild type and mutant type. Overall, 22.92 and 22.83 million reads of SS-128 and ΔluxS/SS-128 were used for further analysis, respectively, and 94.06–94.48% of the total reads mapped to the reference genome, among which 66.10–76.02% were coding sequence (CDS) mapped reads (Table S2). There were significant differences between ΔluxS/SS-128 and SS-128 in PCA model (Figure 4a). The differences between the first and the second principal component were 77.93% and 11.78%, respectively. A total of 157 genes were identified in ΔluxS/SS-128 from uniquely matched reads data compared to SS-128 expressing at different levels (p < 0.05) (Figure 4b).
The 157 differentially expressed genes (DEGs) were subsequently applied to functional analysis in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional enrichment. As shown in Figure 4c, KEGG enrichment analysis found that some pathways were remarkably changed after the luxS gene knocked out in the histogram. These pathways included “Membrane transport”, “Carbohydrate metabolism”, and “Amino acid metabolism”. Our data indicated that, owing to the loss of the luxS gene, a series of transport-related pathways were adjusted, and the pathways involved in energy metabolism were also changed in the process of cell growth. The identified DEGs were combined with functional analysis results, such as KEGG annotations based on previous reports. These genes were considered the most critical genes related to cell growth and accumulation of metabolites, mainly involved in PTS, tricarboxylic acid (TCA), and methionine cycle (Table 2).

3.6. Metabolomics Analyses between L. plantarum SS-128 and the ΔluxS/SS-128

Except for transcriptome sequencing analysis, the untargeted GC–MS and LC–MS metabolomics analyses were used to further explore the adaptation of metabolic processes in L. plantarum SS-128 response to the luxS gene. The total number of metabolites detected in samples was 357, 2316, and 1330 for GC–MS, LC–MS positive ion mode, and negative ion mode, respectively. The tested samples were apparently separated from the wild type and mutant type in Figure 5a and Figure S1a. Furthermore, the first principal components (PC) were clearly separated by the OPLS-DA model, corresponding a variation between groups of 38.7% (GC–MS) and 54.7% (LC–MS). These data indicated that the cell metabolism was changed significantly owing to the knocked out of the luxS gene (Figure 5b and Figure S1b). The OPLS-DA model screened out differentially expressed metabolites in the two groups. The structure identities of 110 metabolites screened by GC–MS were assigned, among which 26 metabolites were significantly upregulated and 84 metabolites were significantly downregulated (p < 0.05) (Figure 5c). LC–MS identified a total of 464 differentially expressed metabolites. Meanwhile, there were 17 metabolites substantial decreased and 33 metabolites increased in the first 50 metabolites that exhibited significant differences (p < 0.05) (Figure S1c).
To investigate the metabolic pathways involved, KEGG pathway analysis was performed. Among the top-20 metabolic pathway enrichment map, the differentially expressed metabolites (DEMs) in mutant type compared with WT strains were mainly enriched on aminoacyl-rRNA biosynthesis, ABC transporters, amino acid metabolism, pyrimidine metabolism and purine metabolism (Figure 5d). Based on the above, the key differential metabolites involved in the enriched pathways were listed in Table 3.

4. Discussion

Since the above results showed that AI-2/LuxS positively regulated the bacteriostatic activity and growth of L. plantarum SS-128, to explore the correlation between two regulatory networks, the metabolome and transcriptome data were subjected to integrated analysis. The results suggest that the knockout of luxS gene resulted in the overall downregulation of methionine and cysteine cycling pathways. By comparing the ΔluxS/SS-128 with the SS-128, the metabolites (SAM, L-cystathionine, O-Acetyl-L-Serine, et al.) and genes (luxS and cysK) showed a lower expression in the mutant strain. Due to the disruption of the methionine cycle, L-homocysteine cannot be replenished-resulting in the consumption of a large SAM as methyl provider, and eventually, the dynamic cycle is disrupted. It is worth noting that it is converted to S-adenosine homocysteine (SAH) when methyl groups are transferred from SAM to nucleic acids, proteins, or other compounds via a SAM-dependent methyltransferase [44]. Therefore, SAM participated in DNA and protein methylation as a major methyl donor for methylation in living cells [45]. Thus, it can be inferred that luxS in the methionine cycle is involved in the regulation of methylation of DNA and other substances and cysteine metabolic pathways.
Bacteria, yeast, and mammalian cells are all dependent on an adequate supply of purines and pyrimidines to maintain proliferation. The proliferation of LAB requires a deoxyriboside bound to purine and pyrimidine bases [46]. As shown in Table 3, the DEMs, such as hypoxanthine, uracil, and riboflavin, were significantly increased by 5.61, 2.59, and 2.22 times, respectively. Therefore, the differential purine metabolites may be the response of the luxS mutant strain to changes in cellular metabolism, which is consistent with previous similar studies. It was reported that purine and purine precursors are related to cell growth under stress conditions [47,48,49]. Uracil dramatically affected L. plantarum growth incubated in ordinary air, and uracil sensitivity in aerobiosis was found in L. plantarum [50]. The accumulation of metabolites in the nucleotide synthesis pathway in cells reflects the delay of nucleotide metabolism in cell proliferation, further confirming the regulation of luxS on cell proliferation.
A significant increase in SRH was observed due to the interruption of activated methyl cycle (AMC) and store depletion of L-homocysteine. Intracellular L-cysteine levels have properly been regulated for proper cell growth [51]. As shown in Figure 6, L-cysteine was maintained only by the pyruvate, while the contents of metabolites in other related metabolic pathways were significantly decreased. The phenomenon is similar to the “anaplerotic sequences” described by Hans Kornberg in Biochemistry that some key intermediates are removed during the growth process, other related metabolites are used for the net production of the intermediate [52]. This is consistent with previous studies in which cysteine-deficient cells exhibited over 100-fold increased oxidative stress compared with the cysteine-added cells and was associated with protective mechanisms of cell growth [53]. Since pyruvate is a major metabolic junction linking carbohydrate or amino acid utilization to energy generation and biosynthetic pathways, the content of key intermediate metabolites requires timely replenishment through auxiliary reactions [54,55]. In response to the interruption of the methionine cycle, glycolysis and TCA cycle were upregulated to “maintain” the ATP for energy and NADPH for reducing power. DEGs related to pyruvate metabolism and TCA cycle, such as pckA, ME2, fumA, and frdA, were upregulated in ΔluxS/SS-128 compared to the control. Whereas operated by the “anaplerotic sequences”, L-lactic, PLA, malate and fumarate synthesis were downregulated to maintain the overall rate of pyruvate, oxaloacetate, and phosphoenolpyruvate synthesis.
The primary fermentation metabolite of LAB is lactic acid, which results in an environment of the lower pH which generally limits the growth of pathogenic and spoilage microbes [3]. The solubility of undissociated lactic acid within the cytoplasm membrane and the insolubility of dissociated lactic acid may affect the pH gradient across the membrane and reduce the available energy for cell growth [56]. As shown in Figure 6 and Table 3, while succinic acid was accumulated in the TCA cycle, the lactic acid and PLA produced by fermentation of the ΔluxS/SS-128 was significantly lower than that of the SS-128. This conclusion was consistent with the result of lactic acid and PLA production by extracellular accumulation of SS-128 and ΔluxS/SS-128. Yang et al. reported that exogenous DPD could promote the growth and the production of PLA of L. Plantarum AB-1 cells [57]. Similarly, our data suggest that the lactic acid and PLA production of L. plantarum SS-128 was regulated by the AI-2/LuxS system. The crucial enzyme in lactic acid fermentation is LDH, which is mainly responsible for catalyzing the reversible reduction of pyruvate to lactic acid [58]. Recently, LDH has also been shown to be the main enzyme catalyzing the PPA to PLA, which is a broad-spectrum antibacterial compound [59,60]. The significant reduction of ldh of defective strains in transcriptomics results was also consistent with our previous experimental results (p < 0.05) (Figure 3c). The results indicated that the pyruvate production was maintained by increasing the directly related anabolism of the ΔluxS/SS-128, followed by a reduction in directly related catabolism. Thus, downregulation of the ldh reduces the production of the organic acid.
In addition, our results showed that the yield of malic acid, fumaric acid and citric acid in ΔluxS/SS-128 were also significantly downregulated (p < 0.05). The production of organic acids is undoubtedly the decisive factor to prolong the shelf life and safety of products by LAB, which was an important indicator to reflect the biocontrol ability. The significant decrease of organic acid production confirmed the regulation effect of luxS on the bacteriostatic ability of LAB.
Unlike pyruvate metabolism to output energy in the form of ATP, PTS is an ATP-dependent mechanism for absorbing sugars. It is dominant among the three mechanisms (PTS, secondary carriers and ABC transporters) of LAB, accounting for about 52%. It provides an essential carbon source to support lipid production and the biosynthesis of nucleotides and non-essential amino acids (NEAAs). Due to the various carbohydrate sources supplemented in MRS medium, the result of combined omics analysis could reflect the difference in carbohydrate transport capacity of SS-128 compared with ΔluxS/SS-128. More than 200 unigenes were involved in carbohydrate metabolism during the growth of L. plantarum, and 36 of these unigenes were involved in membrane transporter. Twenty-seven of these unigenes were DEGs in the PTS, and 17 of them in KEGG enrich top 20 (Figure 4) were summarized in Table 2. The results suggested that most of the DEGs associated with PTS were significantly downregulated (p < 0.05). Genes celA, celB, and celC encoding cellobiose transport system permease are responsible for the carbohydrates utilization in ΔluxS/SS-128, and significantly downregulated 1.92-, 3.36-, and 3.19-fold compared to SS-128. The bglF was downregulated 5.93-fold change in response to stimulating growth. Normal cells often increase the uptake of glucose to provide the significant carbon source for the production of lipids, nucleotides, and non-essential amino acids [61,62]. Therefore, lower transcript levels of genes encoding specific carbohydrate PTS components indicate that ΔluxS/SS-128 may only be able to uptake and utilize the limited range of energy substances, as part of a defense mechanism against the genetic mutations, and this could explain their less efficient for growth and lower biocontrol ability.

5. Conclusions

In summary, the comparative multiomic analyses demonstrated that the higher pyruvate metabolic efficiency and energy input, followed by higher LDH level and metabolite overflow in SS-128, resulted in stronger bacteriostatic ability compared to that of ΔluxS/SS-128. These results suggest that the AI-2/LuxS could positively regulate the bacteriostatic activity and growth of L. plantarum SS-128. Our data indicated that L. plantarum as bio-preservatives was mediated by AI-2/luxS targeting to improve food safety, but further studies are needed to explore the strategies of enhancing positive regulation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods11050638/s1, Figure S1: Changes in the metabolite contents compared the luxS mutant group with the control by LC-MS; Table S1: The mean inhibition zone diameter (mm) of CFS of L. plantarum against the E. coli, S. baltica, S. aureus and A. johnsonii; Table S2: Comparison of statistical results and reference genome.

Author Contributions

Conceptualization, Y.Q.; data curation, Y.Q. and H.Z.; formal analysis, Y.L. and H.Z.; funding acquisition, Z.L.; investigation, Y.Q. and Y.L.; methodology, Y.Q.; software, T.X.; supervision, M.Z. and Z.L.; visualization, T.X.; writing—original draft, Y.Q.; writing—review & editing, Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (No. 31972141) and the National key research and development program (No. 2021YFD2100504).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This work was financially supported by the National Natural Science Foundation of China (no. 31972141) and the National key research and development program (No. 2021YFD2100504).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hatti-Kaul, R.; Chen, L.; Dishisha, T.; Enshasy, H.E. Lactic acid bacteria: From starter cultures to producers of chemicals. FEMS Microbiol. Lett. 2018, 365, fny213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Barcenilla, C.; Ducic, M.; López, M.; Prieto, M.; Álvarez-Ordóñez, A. Application of lactic acid bacteria for the biopreservation of meat products: A systematic review. Meat Sci. 2022, 183, 108661. [Google Scholar] [CrossRef] [PubMed]
  3. Crowley, S.; Mahony, J.; van Sinderen, D. Current perspectives on antifungal lactic acid bacteria as natural bio-preservatives. Trends Food Sci. Technol. 2013, 33, 93–109. [Google Scholar] [CrossRef]
  4. Nasrollahzadeh, A.; Mokhtari, S.; Khomeiri, M.; Saris, P.E. Antifungal Preservation of Food by Lactic Acid Bacteria. Foods 2022, 11, 395. [Google Scholar] [CrossRef] [PubMed]
  5. Michon, C.; Langella, P.; Eijsink, V.G.; Mathiesen, G.; Chatel, J.M. Display of recombinant proteins at the surface of lactic acid bacteria: Strategies and applications. Microb. Cell Fact. 2016, 15, 70. [Google Scholar] [CrossRef]
  6. Gao, C.; Ma, C.; Xu, P. Biotechnological routes based on lactic acid production from biomass. Biotechnol. Adv. 2011, 29, 930–939. [Google Scholar] [CrossRef]
  7. Gálvez, A.; Abriouel, H.; Benomar, N.; Lucas, R. Microbial antagonists to food-borne pathogens and biocontrol. Curr. Opin. Biotechnol. 2010, 21, 142–148. [Google Scholar] [CrossRef]
  8. Kos, B.; Šušković, J.; Beganović, J.; Gjuračić, K.; Frece, J.; Iannaccone, C.; Canganella, F. Characterization of the three selected probiotic strains for the application in food industry. World J. Microbiol. Biotechnol. 2008, 24, 699–707. [Google Scholar] [CrossRef]
  9. Lee, S.-J.; Jeon, H.-S.; Yoo, J.-Y.; Kim, J.-H. Some Important Metabolites Produced by Lactic Acid Bacteria Originated from Kimchi. Foods 2021, 10, 2148. [Google Scholar] [CrossRef]
  10. Whiteley, M.; Diggle, S.P.; Greenberg, E.P. Progress in and promise of bacterial quorum sensing research. Nature 2017, 551, 313–320. [Google Scholar] [CrossRef]
  11. Schauder, S.; Shokat, K.; Surette, M.G.; Bassler, B.L. The LuxS family of bacterial autoinducers: Biosynthesis of a novel quorum-sensing signal molecule. Mol. Microbiol. 2001, 41, 463–476. [Google Scholar] [CrossRef] [PubMed]
  12. Zhang, Y.; Yu, H.; Xie, Y.; Guo, Y.; Cheng, Y.; Yao, W. Quorum sensing inhibitory effect of hexanal on Autoinducer-2 (AI-2) and corresponding impacts on biofilm formation and enzyme activity in Erwinia carotovora and Pseudomonas fluorescens isolated from vegetables. J. Food Processing Preserv. 2022, 46, e16293. [Google Scholar] [CrossRef]
  13. Pereira, C.S.; Thompson, J.A.; Xavier, K.B. AI-2-mediated signalling in bacteria. FEMS Microbiol. Rev. 2013, 37, 156–181. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Gu, Y.; Li, B.; Tian, J.; Wu, R.; He, Y. The response of LuxS/AI-2 quorum sensing in Lactobacillus fermentum 2-1 to changes in environmental growth conditions. Ann. Microbiol. 2018, 68, 287–294. [Google Scholar] [CrossRef]
  15. Gu, Y.; Wu, J.; Tian, J.; Li, L.; Zhang, B.; Zhang, Y.; He, Y. Effects of Exogenous Synthetic Autoinducer-2 on Physiological Behaviors and Proteome of Lactic Acid Bacteria. ACS Omega 2020, 5, 1326–1335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Gu, Y.; Tian, J.; Zhang, Y.; Wu, R.; Li, L.; Zhang, B.; He, Y. Dissecting signal molecule AI-2 mediated biofilm formation and environmental tolerance in Lactobacillus plantarum. J. Biosci. Bioeng. 2021, 131, 153–160. [Google Scholar] [CrossRef]
  17. Yeo, S.; Park, H.; Ji, Y.; Park, S.; Yang, J.; Lee, J.; Mathara, J.M.; Shin, H.; Holzapfel, W. Influence of gastrointestinal stress on autoinducer-2 activity of two Lactobacillus species. FEMS Microbiol. Ecol. 2015, 91, fiv065. [Google Scholar] [CrossRef] [Green Version]
  18. Man, L.-L.; Meng, X.-C.; Zhao, R.-H.; Xiang, D.-J. The role of plNC8HK-plnD genes in bacteriocin production in Lactobacillus plantarum KLDS1.0391. Int. Dairy J. 2014, 34, 267–274. [Google Scholar] [CrossRef]
  19. Tannock, G.W.; Ghazally, S.; Walter, J.; Loach, D.; Brooks, H.; Cook, G.; Surette, M.; Simmers, C.; Bremer, P.; Dal Bello, F.; et al. Ecological behavior of Lactobacillus reuteri 100-23 is affected by mutation of the luxS gene. Appl. Environ. Microbiol. 2005, 71, 8419–8425. [Google Scholar] [CrossRef] [Green Version]
  20. Lebeer, S.; De Keersmaecker, S.C.; Verhoeven, T.L.; Fadda, A.A.; Marchal, K.; Vanderleyden, J. Functional analysis of luxS in the probiotic strain Lactobacillus rhamnosus GG reveals a central metabolic role important for growth and biofilm formation. J. Bacteriol. 2007, 189, 860–871. [Google Scholar] [CrossRef] [Green Version]
  21. Jia, F.F.; Pang, X.H.; Zhu, D.Q.; Zhu, Z.T.; Sun, S.R.; Meng, X.C. Role of the luxS gene in bacteriocin biosynthesis by Lactobacillus plantarum KLDS1.0391: A proteomic analysis. Sci. Rep. 2017, 7, 13871. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Sun, L.; Zhang, Y.; Guo, X.; Zhang, L.; Zhang, W.; Man, C.; Jiang, Y. Characterization and transcriptomic basis of biofilm formation by Lactobacillus plantarum J26 isolated from traditional fermented dairy products. LWT 2020, 125, 109333. [Google Scholar] [CrossRef]
  23. Li, J.; Yang, X.; Shi, G.; Chang, J.; Liu, Z.; Zeng, M. Cooperation of lactic acid bacteria regulated by the AI-2/LuxS system involve in the biopreservation of refrigerated shrimp. Food Res. Int. 2019, 120, 679–687. [Google Scholar] [CrossRef]
  24. Bassler, B.L.; Greenberg, E.P.; Stevens, A.M. Cross-species induction of luminescence in the quorum-sensing bacterium Vibrio harveyi. J. Bacteriol. 1997, 179, 4043–4045. [Google Scholar] [CrossRef] [Green Version]
  25. Léonard, L.; Beji, O.; Arnould, C.; Noirot, E.; Bonnotte, A.; Gharsallaoui, A.; Degraeve, P.; Lherminier, J.; Saurel, R.; Oulahal, N. Preservation of viability and anti-Listeria activity of lactic acid bacteria, Lactococcus lactis and Lactobacillus paracasei, entrapped in gelling matrices of alginate or alginate/caseinate. Food Control 2015, 47, 7–19. [Google Scholar] [CrossRef]
  26. Bensch, G.; Rüger, M.; Wassermann, M.; Weinholz, S.; Reichl, U.; Cordes, C. Flow cytometric viability assessment of lactic acid bacteria starter cultures produced by fluidized bed drying. Appl. Microbiol. Biotechnol. 2014, 98, 4897–4909. [Google Scholar] [CrossRef] [PubMed]
  27. Zhang, X.; Zhang, S.; Shi, Y.; Shen, F.; Wang, H. A new high phenyl lactic acid-yielding Lactobacillus plantarum IMAU10124 and a comparative analysis of lactate dehydrogenase gene. FEMS Microbiol. Lett. 2014, 356, 89–96. [Google Scholar] [CrossRef] [Green Version]
  28. Li, H.; Xie, X.; Li, Y.; Chen, M.; Xue, L.; Wang, J.; Zhang, J.; Wu, S.; Ye, Q.; Zhang, S.; et al. Pediococcus pentosaceus IM96 Exerts Protective Effects against Enterohemorrhagic Escherichia coli O157:H7 Infection. In Vivo Foods 2021, 10, 2945. [Google Scholar] [CrossRef]
  29. Kaur, A.; Capalash, N.; Sharma, P. Expression of Meiothermus ruber luxS in E. coli alters the antibiotic susceptibility and biofilm formation. Appl. Microbiol. Biotechnol. 2020, 104, 4457–4469. [Google Scholar] [CrossRef]
  30. Monahan, L.G.; Harry, E.J. You Are What You Eat: Metabolic Control of Bacterial Division. Trends Microbiol. 2016, 24, 181–189. [Google Scholar] [CrossRef]
  31. Rang, U.; Peng, A.; Poon, A.; Chao, L. Ageing in Escherichia coli requires damage by an extrinsic agent. Microbiology 2012, 158, 1553–1559. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Nakaoka, H.; Wakamoto, Y. Aging, mortality, and the fast growth trade-off of Schizosaccharomyces pombe. PLoS Biol. 2017, 15, e2001109. [Google Scholar] [CrossRef] [Green Version]
  33. Rathod, N.B.; Phadke, G.G.; Tabanelli, G.; Mane, A.; Ranveer, R.C.; Pagarkar, A.; Ozogul, F. Recent advances in bio-preservatives impacts of lactic acid bacteria and their metabolites on aquatic food products. Food Biosci. 2021, 44, 101440. [Google Scholar] [CrossRef]
  34. El-Saber Batiha, G.; Hussein, D.E.; Algammal, A.M.; George, T.T.; Jeandet, P.; Al-Snafi, A.E.; Tiwari, A.; Pagnossa, J.P.; Lima, C.M.; Thorat, N.D.; et al. Application of natural antimicrobials in food preservation: Recent views. Food Control 2021, 126, 108066. [Google Scholar] [CrossRef]
  35. Shekarforoush, S.S.; Basiri, S.; Ebrahimnejad, H.; Hosseinzadeh, S. Effect of chitosan on spoilage bacteria, Escherichia coli and Listeria monocytogenes in cured chicken meat. Int. J. Biol. Macromol. 2015, 76, 303–309. [Google Scholar] [CrossRef]
  36. Hong Tran, D.; Tran, T.; Pham, N.; Phung, H. Direct multiplex recombinase polymerase amplification for rapid detection of Staphylococcus aureus and Pseudomonas aeruginosa in food. bioRxiv 2021. [Google Scholar] [CrossRef]
  37. Ge, Y.; Zhu, J.; Ye, X.; Yang, Y. Spoilage potential characterization of Shewanella and Pseudomonas isolated from spoiled large yellow croaker (Pseudosciaena crocea). Lett. Appl. Microbiol. 2017, 64, 86–93. [Google Scholar] [CrossRef]
  38. Wang, X.-Y.; Xie, J. Quorum Sensing System-Regulated Proteins Affect the Spoilage Potential of Co-cultured Acinetobacter johnsonii and Pseudomonas fluorescens From Spoiled Bigeye Tuna (Thunnus obesus) as Determined by Proteomic Analysis. Front. Microbiol. 2020, 11, 940. [Google Scholar] [CrossRef]
  39. Flickinger, S.T.; Copeland, M.F.; Downes, E.M.; Braasch, A.T.; Tuson, H.H.; Eun, Y.-J.; Weibel, D.B. Quorum sensing between Pseudomonas aeruginosa biofilms accelerates cell growth. J. Am. Chem. Soc. 2011, 133, 5966–5975. [Google Scholar] [CrossRef] [Green Version]
  40. Jie, J.; Yu, H.; Han, Y.; Liu, Z.; Zeng, M. Acyl-homoserine-lactones receptor LuxR of Shewanella baltica involved in the development of microbiota and spoilage of refrigerated shrimp. J. Food Sci. Technol. 2018, 55, 2795–2800. [Google Scholar] [CrossRef]
  41. Li, X.; Jiang, B.; Pan, B.; Mu, W.; Zhang, T. Purification and partial characterization of Lactobacillus species SK007 lactate dehydrogenase (LDH) catalyzing phenylpyruvic acid (PPA) conversion into phenyllactic acid (PLA). J. Agric. Food Chem. 2008, 56, 2392–2399. [Google Scholar] [CrossRef]
  42. Lin, M.; Zhou, G.-H.; Wang, Z.-G.; Yun, B. Functional analysis of AI-2/LuxS from bacteria in Chinese fermented meat after high nitrate concentration shock. Eur. Food Res. Technol. 2015, 240, 119–127. [Google Scholar] [CrossRef] [Green Version]
  43. Moslehi-Jenabian, S.; Vogensen, F.K.; Jespersen, L. The quorum sensing luxS gene is induced in Lactobacillus acidophilus NCFM in response to Listeria monocytogenes. Int. J. Food Microbiol. 2011, 149, 269–273. [Google Scholar] [CrossRef] [PubMed]
  44. Fontecave, M.; Atta, M.; Mulliez, E. S-adenosylmethionine: Nothing goes to waste. Trends Biochem. Sci. 2004, 29, 243–249. [Google Scholar] [CrossRef]
  45. Chen, H.; Wang, Z.; Cai, H.; Zhou, C. Progress in the microbial production of S-adenosyl-L-methionine. World J. Microbiol. Biotechnol. 2016, 32, 153. [Google Scholar] [CrossRef] [PubMed]
  46. Kilstrup, M.; Hammer, K.; Ruhdal Jensen, P.; Martinussen, J. Nucleotide metabolism and its control in lactic acid bacteria. FEMS Microbiol. Rev. 2005, 29, 555–590. [Google Scholar] [CrossRef] [PubMed]
  47. Vilain, S.; Pretorius, J.M.; Theron, J.; Brözel, V.S. DNA as an adhesin: Bacillus cereus requires extracellular DNA to form biofilms. Appl. Environ. Microb 2009, 75, 2861–2868. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Duwat, P.; Ehrlich, S.D.; Gruss, A. Effects of metabolic flux on stress response pathways in Lactococcus lactis. Mol. Microbiol. 1999, 31, 845–858. [Google Scholar] [CrossRef]
  49. Rallu, F.; Gruss, A.; Ehrlich, S.D.; Maguin, E. Acid- and multistress-resistant mutants of Lactococcus lactis: Identification of intracellular stress signals. Mol. Microbiol. 2000, 35, 517–528. [Google Scholar] [CrossRef]
  50. Nicoloff, H.; Hubert, J.-C.; Bringel, F. In Lactobacillus plantarum, Carbamoyl Phosphate Is Synthesized by Two Carbamoyl-Phosphate Synthetases (CPS): Carbon Dioxide Differentiates the Arginine-Repressed from the Pyrimidine-Regulated CPS. J. Bacteriol. 2000, 182, 3416–3422. [Google Scholar] [CrossRef] [Green Version]
  51. Sperandio, B.; Polard, P.; Ehrlich, D.S.; Renault, P.; Guédon, E. Sulfur amino acid metabolism and its control in Lactococcus lactis IL1403. J. Bacteriol. 2005, 187, 3762–3778. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Owen, O.E.; Kalhan, S.C.; Hanson, R.W. The key role of anaplerosis and cataplerosis for citric acid cycle function. J. Biol. Chem. 2002, 277, 30409–30412. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Dijkstra, A.R.; Alkema, W.; Starrenburg, M.J.; Hugenholtz, J.; van Hijum, S.A.; Bron, P.A. Fermentation-induced variation in heat and oxidative stress phenotypes of Lactococcus lactis MG1363 reveals transcriptome signatures for robustness. Microb Cell Fact. 2014, 13, 148. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Kornberg, H.L. The role and control of the glyoxylate cycle in Escherichia coli. Biochem. J. 1966, 99, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Petersen, S.; de Graaf, A.A.; Eggeling, L.; Möllney, M.; Wiechert, W.; Sahm, H. In Vivo Quantification of Parallel and Bidirectional Fluxes in the Anaplerosis of Corynebacterium glutamicum. J. Biol. Chem. 2000, 275, 35932–35941. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Reis, J.A.; Paula, A.T.; Casarotti, S.N.; Penna, A.L.B. Lactic Acid Bacteria Antimicrobial Compounds: Characteristics and Applications. Food Eng. Rev. 2012, 4, 124–140. [Google Scholar] [CrossRef]
  57. Yang, X.; Li, J.; Shi, G.; Zeng, M.; Liu, Z. Improving 3-phenyllactic acid production of Lactobacillus plantarum AB-1 by enhancing its quorum-sensing capacity. J. Food Sci. Technol. 2019, 56, 2605–2610. [Google Scholar] [CrossRef]
  58. Feldman-Salit, A.; Hering, S.; Messiha, H.L.; Veith, N.; Cojocaru, V.; Sieg, A.; Westerhoff, H.V.; Kreikemeyer, B.; Wade, R.C.; Fiedler, T. Regulation of the activity of lactate dehydrogenases from four lactic acid bacteria. J. Biol. Chem. 2013, 288, 21295–21306. [Google Scholar] [CrossRef] [Green Version]
  59. Rajanikar, R.V.; Nataraj, B.H.; Naithani, H.; Ali, S.A.; Panjagari, N.R.; Behare, P.V. Phenyllactic acid: A green compound for food biopreservation. Food Control 2021, 128, 108184. [Google Scholar] [CrossRef]
  60. Jia, J.; Mu, W.; Zhang, T.; Jiang, B. Bioconversion of Phenylpyruvate to Phenyllactate: Gene Cloning, Expression, and Enzymatic Characterization of d-and l 1-Lactate Dehydrogenases from Lactobacillus plantarum SK002. Appl. Biochem. Biotechnol. 2010, 162, 242–251. [Google Scholar] [CrossRef]
  61. Stoll, R.; Goebel, W. The major PEP-phosphotransferase systems (PTSs) for glucose, mannose and cellobiose of Listeria monocytogenes, and their significance for extra- and intracellular growth. Microbiology 2010, 156, 1069–1083. [Google Scholar] [CrossRef] [PubMed]
  62. Zhu, J.; Thompson, C.B. Metabolic regulation of cell growth and proliferation. Nat. Rev. Mol. Cell Biol. 2019, 20, 436–450. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Two-step homologous recombination (a), PCR amplification (b), AI-2 activity (c), and transcription of the luxS gene (d) in SS-128 and ΔluxS/SS-128. All data points mean ± standard deviations (n = 3) with * denoting statistically significant differences (p < 0.05).
Figure 1. Two-step homologous recombination (a), PCR amplification (b), AI-2 activity (c), and transcription of the luxS gene (d) in SS-128 and ΔluxS/SS-128. All data points mean ± standard deviations (n = 3) with * denoting statistically significant differences (p < 0.05).
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Figure 2. Cell density (a), live cell number (b), VCP of L. plantarum by flow cytometry (c), and images of inhibition zone of SS-128 and ΔluxS/SS-128 against E. coli, S. baltica, S. aureus, and A. johnsonii (d). All data points mean ± standard deviations (n = 3).
Figure 2. Cell density (a), live cell number (b), VCP of L. plantarum by flow cytometry (c), and images of inhibition zone of SS-128 and ΔluxS/SS-128 against E. coli, S. baltica, S. aureus, and A. johnsonii (d). All data points mean ± standard deviations (n = 3).
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Figure 3. Extracellular concentrations of L-lactic acid (a) and PLA (b) detected by HPLC in SS-128 and ΔluxS/SS-128; LDH activity (c). All data points mean ± standard deviations (n = 3) with * denoting statistically significant differences (p < 0.05); n.s.: not significant.
Figure 3. Extracellular concentrations of L-lactic acid (a) and PLA (b) detected by HPLC in SS-128 and ΔluxS/SS-128; LDH activity (c). All data points mean ± standard deviations (n = 3) with * denoting statistically significant differences (p < 0.05); n.s.: not significant.
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Figure 4. PCA analysis (a), volcano plot (b), and KEGG pathway of DEGs at level 2, (c) (ΔluxS/SS-128 vs. SS-128).
Figure 4. PCA analysis (a), volcano plot (b), and KEGG pathway of DEGs at level 2, (c) (ΔluxS/SS-128 vs. SS-128).
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Figure 5. Changes in the metabolite contents compared the luxS mutant group with the control by GC–MS. The PCA (a), OPLS-DA (b), volcano plot (c), and metabolic pathway enrichment map-Top 20 (d) between ΔluxS/SS-128 and SS-128 under the cut off of p < 0.05 (ΔluxS/SS-128 vs. SS-128). The red line and blue line in (d) indicate p = 0.01 and 0.05, respectively.
Figure 5. Changes in the metabolite contents compared the luxS mutant group with the control by GC–MS. The PCA (a), OPLS-DA (b), volcano plot (c), and metabolic pathway enrichment map-Top 20 (d) between ΔluxS/SS-128 and SS-128 under the cut off of p < 0.05 (ΔluxS/SS-128 vs. SS-128). The red line and blue line in (d) indicate p = 0.01 and 0.05, respectively.
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Figure 6. Changes of the expression levels of genes and metabolisms involved in L. plantarum (ΔluxS/SS-128 vs. SS-128). Pathways were constructed based on information provided in the KEGG database and previous studies. Microcompartments are depicted by dotted green lines.
Figure 6. Changes of the expression levels of genes and metabolisms involved in L. plantarum (ΔluxS/SS-128 vs. SS-128). Pathways were constructed based on information provided in the KEGG database and previous studies. Microcompartments are depicted by dotted green lines.
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Table
Table 1. Primer sequences.
Table 1. Primer sequences.
Gene NameOligonucleotide Sequence (5′-3′)
UpForwardTATCCC ACTACCTGAA ACTCG
ReverseGCACCACCATTACTTTTTATATTGTAGCACATTGCCCGTTA
DownForwardTAACGGGCAATGTGCATACAATATAAAAAGTAATGGTGGTGC
ReverseGCTGGTGCTTCGTAAACTTCC
16S rRNAForwardCGTAGGTGGCAAGCGTTGTCC
ReverseCGCCTTCGCCACTGGTGTTC
LuxSForwardCGGATGGATGGCGTGATTGACTG
ReverseCTTAGCAACTTCAACGGTGTCATGTTC
UDForwardGTTCTGCACGGACGCTATCT
ReverseATTAACTTGCGTTGGTAGGC
Table
Table 2. DEGs involved in PTS, pyruvate metabolism and quorum sensing.
Table 2. DEGs involved in PTS, pyruvate metabolism and quorum sensing.
Locus TagEntryGene Name
(ID)		DefinitionFold Changep-Value
PTSK02793manXamannose PTS system EIIA component1.56 ↓1.12 × 104
K02768fruBfructose PTS system EIIA component1.68 ↓2.14 × 106
K02810scrA, ptsSsucrose PTS system EIIBCA component1.54 ↓8.15 × 103
K02761celB, chbCcellobiose PTS system EIIC component3.36 ↓ *2.21 × 104
K02760celA, chbBcellobiose PTS system EIIB component1.92 ↓6.99 × 104
K02759celC, chbAcellobiose PTS system EIIA component3.19 ↓*4.32 × 104
K02773gatA, sgcAgalactitol PTS system EIIA component1.88 ↓2.76 × 104
K02774gatB, sgcBgalactitol PTS system EIIB component1.71 ↓1.46 × 102
K02755bglFbeta-glucoside PTS system EIIA component5.93 ↓ *3.28 × 109
K02798cmtBmannitol PTS system EIIA component1.59 ↓1.49 × 105
LP_RS14755PTS system EIIC component1.74 ↓1.79 × 102
LP_RS12340PTS system EIIA component1.67 ↓3.06 × 102
LP_RS12650PTS system EIIB component1.52 ↓4.89 × 102
LP_RS12655PTS system EIIC component2.33 ↓ *9.25× 1010
LP_RS13505 beta-glucoside PTS system EIIBCA component1.54 ↓8.15× 103
LP_RS14845PTS system EIIB component1.71 ↓1.46 × 102
LP_RS14850PTS system EIIA component1.88 ↓2.76 × 104
Pyruvate metabolismK00927PGK, pgkphosphoglycerate kinase1.52 ↑1.85 × 105
K00016ldhL-lactate dehydrogenase2.58 ↓ *1.03 × 102
K01610pckA, PEPCKphosphoenolpyruvate carboxykinase (ATP)1.51 ↑3.95 × 102
K00027ME, maeAmalate dehydrogenase4.87 ↑ * 5.68 × 103
K01676fumA, fumBfumarate hydratase, class I3.39 ↑ *1.10 × 104
K00244frdAfumarate reductase flavoprotein subunit4.08 ↑ *3.14 × 102
K01744aspAaspartate ammonia-lyase1.70 ↑1.99 × 107
K01939purA, ADSSadenylosuccinate synthase1.55 ↑2.25 × 102
K01512acyPacylphosphatase1.70 ↑2.95 × 105
Methionine cycleK07173luxSS-ribosylhomocysteine lyase 2.53 × 104
K01738cysKcysteine synthase2.95 ↓5.85 × 1010
K01999livKbranched-chain amino acid transport system substrate-binding protein2.01 ↓ *2.75 × 102
Fold change was ΔluxS/SS-128 vs. SS-128. ↑ and ↓ represented up and down regulation, respectively. * fold change was significantly higher than 2 (p < 0.05).
Table
Table 3. Differential metabolites involving PTS, nucleotide synthesis, pyruvate metabolism, cysteine and methionine metabolism.
Table 3. Differential metabolites involving PTS, nucleotide synthesis, pyruvate metabolism, cysteine and methionine metabolism.
MetabolitesKEGGKEGG AnnotationDataclassFormulaVIPp-ValueFC
2′-Deoxyguanosine 5′-monophosphateC00362Purine metabolismLCC10H14N5O7P1.123.46 × 1081.53 ↑
DeoxyguanosineC00330Purine metabolismLCC10H13N5O41.262.38 × 1061.84 ↑
GuanineC00242Purine metabolismGCC5H5N5O1.386.32 × 1042.05 ↑ *
HypoxanthineC00262Purine metabolismGCC5H4N4O22.274.52 × 1055.61 ↑ *
XanthineC00385Purine metabolismLCC5H4N4O21.141.08 × 1072.21 ↑ *
CytosineC00380Pyrimidine metabolismGCC4H5N3O1.435.73 × 1042.15 ↑ *
dCMPC00239Pyrimidine metabolismLCC9H14N3O7P1.621.58 × 1041.62 ↑
dTMPC00364Pyrimidine metabolismLCC10H15N2O8P5.821.20 × 1071.73 ↑
Pseudouridine 5′-phosphateC01168Pyrimidine metabolismLCC9H13N2O9P4.186.41 × 1051.15 ↑
UracilC00106Pyrimidine metabolismGCC4H4N2O21.673.17 × 1052.59 ↑ *
UridineC00299Pyrimidine metabolismGCC9H12N2O61.293.43 × 1041.86 ↑
Uridine 5′-monophosphateC00105Pyrimidine metabolismLCC9H13N2O9P2.205.38 × 1041.42 ↑
OrotidineC01103Pyrimidine metabolismLCC10H12N2O81.427.33 × 1074.61 ↓ *
L-glutamineC00064Purine metabolism
pyrimidine metabolism		GCC5H10N2O33.133.58 × 10722.12 ↓ *
Flavin MononucleotideC00061Oxidative phosphorylation
Riboflavin metabolism		LCC17H21N4O9P1.044.29 × 1031.66 ↑
RiboflavinC00255ABC transporters
Riboflavin metabolism		LCC17H20N4O61.233.40 × 1032.22 ↑ *
Flavin adenine dinucleotideC00016Riboflavin metabolismLCC27H33N9O15P22.962.77 × 10101.64 ↑
D-Glycerate 2-phosphateC00631Glycolysis/GluconeogenesisLCC3H7O7P1.812.85 × 1071.84 ↑
D-Glycerate 3-phosphateC00197Glycolysis/GluconeogenesisLCC3H7O7P1.109.00 × 1081.79 ↑
Phosphoenolpyruvic acidC00074Glycolysis/Gluconeogenesis
Citrate cycle (TCA cycle)		LCC3H5O6P1.865.37 × 1081.91 ↑
Isocitric acidC00311Citrate cycle (TCA cycle)GCC6H8O71.222.09 × 1024.97 ↑ *
Succinic acidC00042Citrate cycle (TCA cycle)GCC4H6O41.471.91 × 1042.17 ↑ *
L-aspartateC00049Cysteine and methionine metabolismGCC4H7NO41.294.77 × 1032.02 ↑ *
L-glutamateC00025Alanine, aspartate and glutamate metabolismLCC5H9NO48.241.44 × 1051.52 ↑
N-acetyl-glutamateC01250Arginine biosynthesisGCC7H11NO41.842.72 × 1043.37 ↑ *
Glutathione (GSH)C00051Cysteine and methionine metabolism | ABC transportersGCC10H17N3O6S1.258.57 × 1041.82 ↑
L-gamma-glutamyl-L-valineC03740Glutathione metabolismLCC10H18N2O51.343.31 × 1061.34 ↑
Malic acidC00149Citrate cycle (TCA cycle)GCC4H6O51.132.28 × 1042.62 ↓
Fumaric acidC00122Citrate cycle (TCA cycle)GCC4H4O41.493.51 × 1031.52 ↓
L-lactic acidC00186Pyruvate metabolismGCC3H6O32.055.33 × 1044.56 ↓
L-PhenylalanineC00079Phenylalanine metabolismLCC9H11NO25.942.58 × 1043.24 ↓
Phenyllactic acidC05607Phenylalanine metabolismLCC9H10O31.158.02 × 1081.61 ↓
Aconitic acidC00417Citrate cycle (TCA cycle)GCC6H6O61.192.58 × 1041.54 ↑
Citric acidC00158Citrate cycle (TCA cycle)GCC6H8O72.623.81 × 1065.75 ↓ *
L-methionineC00073Cysteine and methionine metabolismGCC5H11NO2S1.171.14 × 1031.69 ↓
S-adenosyl-L-methionine (SAM)C00019Cysteine and methionine metabolismLCC15H22N6O5S1.811.49 × 101016.66 ↓ *
S-ribosyl-L-homocysteine (SRH)C03539Cysteine and methionine metabolismLCC9H17NO6S5.761.00 × 1084.71 ↑ *
L-cystathionineC02291Cysteine and methionine metabolismGCC7H14N2O4S2.409.01 × 1086.85 ↓ *
L-homocysteineC00155Cysteine and methionine metabolismGCC4H9NO2S2.031.44 × 1051.73 ↓
S-adenosyl-L-homocysteine (SAH)C00021Cysteine and methionine metabolismGCC14H20N6O5S2.922.72 × 1042.58 ↓
SerineC00065Cysteine and methionine metabolismGCC3H7NO31.586.93 × 1050.42 ↓
HomoserineC00263Cysteine and methionine metabolismGCC4H9NO31.761.39 × 1062.80 ↓ *
O-acetyl-L-serineC00979Cysteine and methionine metabolismGCC5H9NO41.511.02 × 1052.89 ↓ *
CreatineC00300Glycine, serine and threonine metabolismLCC4H9N3O22.011.23 × 1080.65 ↓
D-fructose 2,6-bisphosphateC00665Fructose and mannose metabolismGCC6H14O12P21.511.04 × 1032.27 ↓ *
D-fructoseC02336Phosphotransferase system (PTS)
Fructose and mannose metabolism		GCC6H12O61.742.06 × 1072.70 ↓ *
CellobioseC00185Phosphotransferase system (PTS)GCC12H22O111.731.40 × 1061.59 ↓
GalactoseC00984Galactose metabolism
Phosphotransferase system (PTS)		GCC6H12O61.485.98 × 1062.08 ↓ *
Glucose-6-phosphateC00092Phosphotransferase system (PTS)GCC6H13O9P1.351.41 × 1041.93 ↓
D-ribulose 5-phosphateC00199Pentose phosphate pathwayGCC5H11O8P1.093.31 × 1031.61 ↓
UDP-glucoseC00029Pyrimidine metabolism
Pentose and glucuronate		LCC15H24N2O17P21.533.97 × 1053.80 ↓ *
D-glucoseC00031Glycolysis/Gluconeogenesis
Phosphotransferase system (PTS)		LCC6H12O62.042.79 × 1052.33 ↓ *
Fold change was ΔluxS/SS-128 vs. SS-128. ↑ and ↓ represented up and down regulation, respectively. * fold change was significantly higher than 2 (p < 0.05).
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Qian, Y.; Li, Y.; Xu, T.; Zhao, H.; Zeng, M.; Liu, Z. Dissecting of the AI-2/LuxS Mediated Growth Characteristics and Bacteriostatic Ability of Lactiplantibacillus plantarum SS-128 by Integration of Transcriptomics and Metabolomics. Foods 2022, 11, 638. https://doi.org/10.3390/foods11050638

AMA Style

Qian Y, Li Y, Xu T, Zhao H, Zeng M, Liu Z. Dissecting of the AI-2/LuxS Mediated Growth Characteristics and Bacteriostatic Ability of Lactiplantibacillus plantarum SS-128 by Integration of Transcriptomics and Metabolomics. Foods. 2022; 11(5):638. https://doi.org/10.3390/foods11050638

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Qian, Yilin, Yuan Li, Tengteng Xu, Huijuan Zhao, Mingyong Zeng, and Zunying Liu. 2022. "Dissecting of the AI-2/LuxS Mediated Growth Characteristics and Bacteriostatic Ability of Lactiplantibacillus plantarum SS-128 by Integration of Transcriptomics and Metabolomics" Foods 11, no. 5: 638. https://doi.org/10.3390/foods11050638

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