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During industrial handling, Lactococcus lactis needs to adapt to different culture conditions by regulating its metabolic pathways. Modifying culture conditions may be an important way to control the biomass and functional metabolites of lactic acid bacteria. In this study, we identified the differentially expressed genes and proteins of L. lactis under different culture conditions by integrating transcriptomics and proteomics. We also analyzed the data using a bioinformatic approach to reveal the regulatory mechanisms affected by culture conditions. The transcriptome and proteome studies indicated that different culture conditions (fructose, calcium ion, palmitic acid, low pH) affected gene and protein expressions. The levels of differentially expressed proteins did not significantly correlate with the expression levels of their corresponding genes. Our results highlight the importance of comparative transcriptomics and proteomics analyses. In this study, fructose and pH significantly affected sugar metabolism of L. lactis. When lactose was replaced by fructose, fructokinase expression was promoted, and fructose metabolism was accelerated, whereas starch and sucrose metabolism and galactose metabolism system were inhibited. Low pH may be beneficial to homofermentation of L. lactis, which may also metabolize galactose through the tagatose pathway and the Leloir pathway. Fatty acid metabolism and fatty acid biosynthesis were significantly downregulated under calcium ion and palmitic acid. The purine metabolism was upregulated under fructose treatment and downregulated under palmitic acid treatment.
Characterisation of Lactococcus lactis isolates from herbs, fruits and vegetables for use as biopreservatives against Listeria monocytogenes in cheese.
) because lactic acid is a major end product of its fermentation's metabolism. It was also selected as a new probiotic organism because of its safety and technological ability (
During the fermentation process, L. lactis needs to survive under variable environmental conditions, including different sugars as energy sources, pH, and other media components (
In vitro evaluation of resistance to environmental stress by planktonic and biofilm form of lactic acid bacteria isolated from traditionally made cheese from Serbia.
). It is important to note that different media components might cause variations in L. lactis metabolic characteristics, leading to the production of diverse bioactive compounds. The specific growth rate of bacteria directly depends on the concentration of limiting substrates (
). The ability to produce γ-aminobutyric acid in lactic acid bacteria depends on the type of carbon and nitrogen sources, as well as other components (
Statistical study on fermentation conditions in the optimization of exopolysaccharide production by Lactobacillus rhamnosus 519 in skimmed milk base media.
). Lactococcus lactis has been the subject of numerous studies aiming to determine the most relevant characteristics to select the best strains for dairy production.
Omic technologies provide valuable data about compound biosynthesis and the complex relationships between nutrition and metabolism (
Comparative proteomic analyses for elucidating metabolic changes during EPS production under different fermentation temperatures by Lactobacillus plantarum Q823.
Int. J. Food Microbiol.2016; 238 (27611800): 96-102
). Previous proteomic studies of the Lactobacillus genus revealed that several proteins were differentially expressed after exposure to bile and in cheese-like conditions (
Transcriptomic studies provide a better comprehension of bacterial physiology and new insights into gene expression in response to environmental variations (
The genomic and transcriptomic basis of the potential of Lactobacillus plantarum A6 to improve the nutritional quality of a cereal based fermented food.
Int. J. Food Microbiol.2018; 266 (29037836): 346-354
Providing more information about the regulatory mechanisms that allow L. lactis to tolerate different culture conditions are of great importance to improve its productivity. In the previous study, we found that specific conditions (fructose, calcium, palmitic acid, low pH) had a great influence on the growth and metabolism of Lactobacillus, especially the metabolism of fatty acids. In this study, we aimed to identify key pathways, genes, and proteins that might improve tolerance to different culture conditions in lactic acid bacteria. We combined transcriptomic and proteomic techniques to identify differentially expressed genes and proteins and used comparative omics technologies and a bioinformatic approach to reveal the regulatory mechanisms that are altered when L. lactis is cultured under different conditions.
MATERIALS AND METHODS
Bacterial Samples
Lactococcus lactis was preserved in the laboratory of the College of Food Science (Northeast Agricultural University, Harbin, China). Lactococcus lactis was incubated at 37°C and collected at the exponential phase (OD600 0.6–0.8) by centrifugation (5,000 × g for 10 min at 4°C). The precipitate was washed 2 times with PBS (4°C) and once with RNA protection solution, then the samples were stored at −80°C. Each sample was extracted in triplicate.
Culture Conditions
The basic M17 broth (medium B1) contained 5 g/L soybean peptone, 2.5 g/L peptone, 2.5 g/L casein peptone, 2.5 g/L yeast powder, 5 g/L beef powder, 0.5 g/L sodium ascorbate, 19 g/L sodium β-glycerophosphate, 0.25 g/L magnesium sulfate, and 5 g/L lactose, with pH 7.2. The media for different culture conditions had the following modifications: medium F2 (5 g/L fructose instead of lactose, pH 7.2); medium C3 (addition of 2 mmol/L calcium chloride, pH 7.2); medium Z4 (addition of 1 mmol/L palmitic acid, pH 7.2); and medium P5 (pH 5.0).
Transcriptomics Analysis
RNA Extraction and Quantification
The samples were suspended in 100 μL TE buffer containing lysozyme (3 mg/mL) and incubated 5 min at room temperature. Trizol reagent (1.5 mL) was added, and the samples were shaken for 3 min and incubated for 5 min at room temperature. The mixture was centrifuged for 5 min (10,397 × g, 4°C). The supernatant (2.0 mL) and chloroform/isoamyl alcohol (400 μL) were added to an Eppendorf tube. The samples were mixed and centrifuged for 10 min (10,397 × g, 4°C). Supernatant (1.5 mL) and isopropanol (1.5 mL) were mixed and incubated at −20°C for 1 h to allow precipitation. After centrifugation (19,231 × g 4°C, 20 min), the supernatant was removed, and 1 mL of 75% ethanol was added to wash the precipitate. After centrifugation (10,397 × g 4°C, 3 min), the residual liquid was removed, and the sample was dried for 3 to 5 min. The sediment was dissolved with 30 to 100 μL diethyl pyrocarbonate or RNase-free water (Thermo Fisher Scientific Co. Ltd., Shanghai, China). We used Agilent 2100 Bioanalyzer (Agilent RNA 6000 Nano Kit, Beijing, China) to quantify and NanoDrop 2000 Ultra Trace Ultraviolet/Visible Spectrophotometer (Thermo Fisher Scientific Co. Ltd.) to measure the purity of the RNA samples.
Differentially Expressed Gene Detection and Analysis
RNA-Seq libraries were prepared as described recently (
). The library was sequenced using Illumina HiSeq X TEN (Illumina Trading Co. Ltd., Shanghai, China). After raw reads were processed through in-house perl scripts, clean reads were aligned to the genome using HISTAT2 software (
) as follows (fold change ≥ 1.2 and adjusted P-value ≤ 0.05). Gene ontology (GO) analysis was conducted for the functional classification of DEG, and pathway analysis was performed using Kyoto Encyclopedia of Genes and Genomes (KEGG;
Four volumes of lysis buffer (8 M urea, 1% protease inhibitor cocktail) was added to the bacteria samples, followed by sonication on ice using a high-intensity ultrasonic processor (Scientz, Shanghai, China). The precipitate was removed by centrifugation (20,000 × g, 4°C, 10 min). Finally, the protein was precipitated by incubation with 20% trichloroacetic acid for 2 h at 4°C. After centrifugation (12,000 × g, 4°C, 3 min), the supernatant was discarded. The remaining precipitate was washed with cold acetone 3 times. The protein was resuspended in 8 M urea, and the protein concentration was determined with a BCA kit (Beyotime Institute of Biotechnology, Jiangsu, China) according to the manufacturer's instructions.
LC-MS/MS Analysis
After trypsin digestion, the peptides were desalted with a Strata-X C18 SPE column (Phenomenex, Tianjin, China) and vacuum-dried. The tryptic peptides were fractionated by high pH reverse-phase HPLC using Agilent 300Extend C18 column (5-μm particles, 4.6-mm inner diameter, 250-mm length). The tryptic peptides were dissolved in 0.1% formic acid and separated by EASY-nLC 1000 ultrahigh-performance liquid phase system. The peptides were subjected to an NSI ion source for ionization and then analyzed by Q Exactive Plus (Thermo Fisher Scientific) mass spectrometry. The ion source voltage applied was 2.0 kV. The m/z scan range was 350 to 1,800 for a full scan, and intact peptides were detected in the Orbitrap (Thermo Fisher Scientific) at a resolution of 70,000. Peptides were then selected for MS/MS, and the fragments were detected in the Orbitrap at a resolution of 17,500, the fixed first mass was set as 100 m/z. The resulting MS/MS data were processed using Maxquant search engine (v.1.5.2.8; https://www.maxquant.org/).
Bioinformatics
The GO annotation was derived from the UniProt-GOA database. First, converting identified protein ID to UniProt ID and then mapping to GO ID by protein ID. If some identified proteins were not annotated by UniProt-GOA database, the InterProScan soft would be used to annotated protein's GO functional based on protein sequence alignment method (
iTRAQ-based proteomic analysis of the viable but nonculturable state of Vibrio parahaemolyticus ATCC 17802 induced by food preservative and low temperature.
). The protein domain functional descriptions were annotated using the InterProtein domain database (https://www.ebi.ac.uk/interpro/). The KEGG database was used to annotate the protein pathways. CELLO, a subcellular localization prediction software, was used to predict subcellular localization (
). A 2-tailed Fisher's exact test was employed to test the enrichment of the differentially expressed proteins. The GO pathway and protein domains with a corrected P-value < 0.05 were considered significant.
Statistical Analysis
All experiments were performed in triplicate. Data were analyzed using SPSS (ver. 20.0, IBM Software, Chicago, IL). Differences among group means were considered significant if P < 0.05.
RESULTS
Transcriptomics Analysis
DEG Detection
We found 143 DEG when we replaced lactose by fructose in the culture system; 76 were significantly upregulated, and 67 were significantly downregulated. Adding calcium ions to the culture system led to the differential expressions of 108 genes; 65 were significantly upregulated, and 43 were significantly downregulated. We found 38 DEG when we added palmitic acid to the culture system; 29 were significantly upregulated, and 9 were significantly downregulated. After reducing the pH of the culture system, we observed 227 DEG; 172 were significantly upregulated, and 55 were significantly downregulated (P < 0.05). These results indicated that different culture conditions cause significant changes in the transcriptome profiles of L. lactis.
Bioinformatic Analysis of DEG
The GO has 3 categories: biological process, cellular component, and molecular function. The GO classifications and functional enrichment of the DEG were shown in Figure 1A. The genes were divided into cellular processes, genetic information processing, metabolism, and organismal systems, according to the KEGG metabolic pathways. Along with pathway database information and the relationship between genes in the pathway map, we analyzed the effects of different culture conditions on the pathways. The pathway classification results were shown in Figure 1B.
The bioinformatic analysis showed that the main biological process of DEG were mainly involved in cell and metabolic process. Their main molecular functions were binding and catalysis, and they were mainly present in the cell, cell part, membrane, and membrane part (Figure 1A). The DEG mainly participated in metabolism and genetic information processing. The most represented metabolic pathways were amino acid metabolism, carbohydrate metabolism, fat metabolism, and energy metabolism. The most represented genetic information processing were translation, folding, sorting, and degradation (Figure 1B).
The up- and downregulated DEG in the enrichment pathway were shown in Supplemental Figure S1 (https://doi.org/10.3168/jds.2020-18895). The DEG of enrichment pathway under fructose treatment were mainly involved in metabolic pathways, biosynthesis of secondary metabolites, biosynthesis of antibiotics, and alanine, aspartate, and glutamate metabolism (Supplemental Figure S1a).
The DEG of enrichment pathway under calcium ions treatment were mainly involved in metabolic pathways, aminoacyl-tRNA biosynthesis, biosynthesis of secondary metabolites, and alanine, aspartate, and glutamate metabolism (Supplemental Figure S1b, https://doi.org/10.3168/jds.2020-18895). The DEG of enrichment pathway under palmitic acid treatment were mainly involved in metabolic pathways, biosynthesis of secondary metabolites, biosynthesis of amino acids, and aminoacyl-tRNA biosynthesis (Supplemental Figure S1c). The DEG of enrichment pathway in the low pH were mainly involved in ribosome, carbon metabolism, glycolysis/gluconeogenesis, and pyruvate metabolism (Supplemental Figure S1d). Hierarchical clustering for DEG were shown as Figure 2a. According to the statistical analysis, 241 genes were characterized as specific to P5 group (Figure 2b).
Figure 2Number and distribution of differentially expressed genes; heatmap of hierarchical clustering of differentially expressed genes (left) and the distribution of differentially expressed genes in different samples (right). B1 = basic M17 group; F2 = fructose group; C3 = calcium ions group; Z4 = palmitic acid group; P5 = low pH group.
Proteomics plays a vital role in understanding the biological functions and role of probiotics. Our results showed 300 differentially expressed proteins (DEP) when fructose was added to the medium, 128 significantly upregulated and 172 significantly downregulated (Figure 3). There were 84 DEP when calcium ions were added to the culture system; 43 were significantly upregulated, and 41 were significantly downregulated. We found 322 DEP when palmitic acid was added; 164 were significantly upregulated, and 158 were significantly downregulated. After reducing the pH of the culture system (from 7.2 to 5), we observed 596 DEP; 294 were significantly upregulated, and 302 were significantly downregulated. The results indicated that the different culture conditions cause significant changes in the proteomic profiles of L. lactis.
Gene ontology is an important bioinformatic analysis method to explain the biological function of proteins and is carried out by investigating the functional enrichment in the altered proteome (
). We statistically analyzed the distribution of DEP in the secondary annotation of GO. In the fructose group, metabolic process was the largest category among biological processes, including 146 (33%) all, 72 (33%) upregulated, and 74 (33%) downregulated proteins, respectively. The second category among biological processes was cellular process (112, 25%, all protein), cellular process (61, 28%, upregulated), and single-organism process (53, 23%, downregulated), respectively. The DEP were mainly located in the cell and membrane. Catalytic activity and binding accounted for the largest molecular functions (88%). In the calcium ions, palmitic acid, and low pH groups (Supplemental Figures S2–S5, https://doi.org/10.3168/jds.2020-18895), metabolic process also was the largest category among biological processes; the next categories among biological processes were cellular process and single-organism process. The DEP were mainly located in the cell, membrane, and macromolecular complex. Catalytic activity and binding were the most represented molecular functions.
Most proteins must be localized in the appropriate subcellular compartments to perform their functions (
). We predicted the subcellular localization of DEP involved in the different pathways (Supplemental Figure S6, https://doi.org/10.3168/jds.2020-18895). The subcellular localization analysis indicated that cytoplasmic and extracellular proteins were mainly DEP in the calcium ions group, and DEP in other groups were mainly located in the cytoplasm and membrane. However, cytoplasm had the highest number of proteins in all samples. We used functional classification information to identify the specific functions and other relevant information of the DEP in L. lactis.
Functional Enrichment Cluster
We performed a hierarchical clustering based on the protein functional classification (GO, pathway). The GO enrichment-based clusters were analyzed under different culture conditions (Supplemental Figure S7). The dominant biological process enrichment-based clusters were carbohydrate transport, phosphoenolpyruvate-dependent sugar phosphotransferase system, peptide transport, and cellular carbohydrate catabolic process. The enriched cellular components were cell periphery and plasma membrane. The enriched molecular functions were phosphotransferase activity, kinase activity, and carbohydrate transport activity.
The significantly enriched cellular components were the same as those of fructose when calcium ions were added to the culture. The enriched molecular functions were related to exopeptidase activity, coenzyme binding, and cofactor binding.
In the culture with palmitic acid, the enriched biological processes were cellular protein metabolic process. The enriched cellular components were small ribosomal subunit and intracellular ribonucleoprotein complex. The enriched molecular functions were transferase activity, DNA N-glycosylase activity, and hydrolase activity.
The significantly enriched biological processes under low pH were glycosyl compound biosynthetic process and ketone biosynthetic process. The enriched cellular components were membrane protein complex and protein complex. The enriched molecular functions were related to ligase activity, magnesium ion binding, and acid-amino acid ligase activity.
As observed in the KEGG analyses (Supplemental Figure S8), the DEP with altered abundance in the medium with fructose were largely involved in amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism, nitrogen metabolism, purine metabolism, and galactose metabolism. The DEP in culture with calcium ions were involved in ABC transporters and other glycan degradation. The DEP with altered levels in the presence of palmitic acid were involved in fatty acid metabolism, fatty acid biosynthesis, ribosome, biotin metabolism, pyruvate metabolism, and propanoate metabolism. The DEP with altered abundance under low pH were involved in ubiquinone and other terpenoid-quinone biosynthesis, butanoate metabolism, glycolysis/gluconeogenesis, and propanoate metabolism.
Transcriptomics and Proteomics Correlation Analysis
Proteomics and transcriptomics are effective tools for studying biological mechanisms, but single omics technology could not completely reveal the necessary regulatory mechanisms. By integrating proteomics and transcriptomics, the biological mechanisms can be understood at the protein and transcription levels, and the interactions or correlations between them can be revealed.
Quantification Relationship Between Proteomics and Transcriptomics
We studied the quantification relationship between proteomics and transcriptomics. The correlations between gene expression and their corresponding proteins were shown in Figure 4. The proteins levels did not significantly correlate with their corresponding gene expression levels in L. lactis. These results indicated the importance of comparative analysis of proteomics and transcriptomics.
The protein levels did not significantly correlate with their corresponding gene expression levels in L. lactis. Previous studies have shown mRNA abundance did not always correlate well with protein expression levels (
), because proteins were the effectors of gene expression, and the gene transcript level was not always well-correlated with the protein level (due to posttranslational modification and co-translation, along with environmental factors;
). However, irrelevant here refers to all data of the differentially expressed protein and genes, some of which are expressed in the same trend. A total of 84 DEP (21 upregulated and 63 downregulated were identified between fructose-treated and control) had a same trend with corresponding DEG; genes may share the same function at the transcriptomic and proteomic levels (
Comparison of Differentially Expressed Proteins or Genes
We divided the data into 9 groups according to the different expression patterns and counted the number on each type. The comparison analysis between transcriptomics and proteomics showed that 63, 5, 2, and 53 proteins and their corresponding genes were simultaneously downregulated, and 21, 13, 23, and 47 proteins and their corresponding genes were simultaneously upregulated in the fructose, calcium ions, palmitic acid, and low pH groups, respectively, showing that the expression of proteins and genes was mostly inconsistent.
Biological Information of Proteomics and Transcriptomics
We performed GO, KEGG pathway, and protein domain enrichment clustering analysis by combining proteomics and transcriptomics to find more biological information. The results directly displayed the overall changes between DEP and DEG.
Under fructose treatment (Supplemental Figures S9 and S10, https://doi.org/10.3168/jds.2020-18895), Up-Up (biological process) was mainly related to purine-containing compound biosynthesis process and nucleobase-containing compound biosynthesis process. Down-Down (biological process) was related to cellular polysaccharide metabolic process, cellular carbohydrate biosynthesis process, polysaccharide biosynthesis process, and hexose metabolic process (Figure 5). Down-Down (molecular function) was connected with sugar transmembrane transporter activity, galactose-6-phosphate isomerase activity, tagatose-6-phosphate kinase activity, and galactosidase activity. Up-Up (KEGG) was connected with purine metabolism. Down-Down (KEGG) was connected with galactose metabolism, amino sugar and nucleotide sugar metabolism, and starch and sucrose metabolism.
Figure 5Gene ontology enrichment-based cluster analysis (biological process; fructose group); yellow circle indicates unchanged, green down arrow indicates downregulated, red up arrow indicates upregulated.
In response to calcium ion treatment (Supplemental Figures S11 and S12, https://doi.org/10.3168/jds.2020-18895), Unchanged-Down, Unchanged-Up, and Down-Unchanged were the major enrichment groups according to the KEGG pathway and protein domain. Up-Up (KEGG) was connected with ABC transporters and other glycan degradation. Down-Down (KEGG) was connected with ABC transporters.
Under palmitic acid treatment (Supplemental Figures S13 and S14, https://doi.org/10.3168/jds.2020-18895), Unchanged-Up, Down-Unchanged, and Up-Unchanged were the major enrichment groups according to the KEGG pathway and protein domain. Up-Up (KEGG) was connected with glycine, serine, and threonine metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; histidine metabolism; and other glycan degradation. Down-Down (KEGG) was related to purine metabolism (Figure 6).
Figure 6Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment-based clustering analysis (palmitic acid group); yellow circle indicates unchanged, green down arrow indicates downregulated, red up arrow indicates upregulated.
In the low pH group (Supplemental Figures S15 and S16), Down-Down (biological process) was related to hexose metabolic process, monosaccharide metabolic process, and alditol metabolic process. Up-Up (molecular function) was connected with oxidoreductase activity. Down-Down (molecular function) was connected with glycerone kinase activity, carbohydrate kinase activity, and acetyltransferase activity (Figure 7). Up-Up (KEGG) was connected with thiamine metabolism, cationic antimicrobial peptide resistance, and RNA degradation. Down-Down (KEGG) was related to butanoate metabolism, galactose metabolism, ABC transporters, amino sugar, nucleotide sugar metabolism, and fructose and mannose metabolism.
Figure 7Gene ontology enrichment-based cluster analysis (molecular function, low pH group); yellow circle indicates unchanged, green down arrow indicates downregulated, red up arrow indicates upregulated.
Lactic acid bacteria produce lactic acid and derive metabolic energy mainly from carbohydrates. Therefore, carbohydrate metabolism is very important and could be regulated under different culture conditions (
). In this study, fructose and low pH had significant effects on the sugar metabolism of L. lactis. When lactose was replaced by fructose, fructokinase expression was promoted, and fructose metabolism was accelerated, but starch and sucrose metabolism (Supplemental Figure S17, https://doi.org/10.3168/jds.2020-18895) and galactose metabolism system were inhibited (Figure 8, galactokinase, 6-phospho-β-glucosidase, tagatose 1,6-diphosphate aldolase, and tagatose-6-phosphate kinase were significantly downregulated). When lactose was replaced by fructose, l-lactate dehydrogenase, alpha-acetolactate decarboxylase, and pyruvate formate lyase were significantly downregulated, the results indicated that pyruvate metabolism was inhibited in the fructose group. Because l-lactate dehydrogenase converts pyruvate into lactic acid (
Figure 8Galactose metabolism pathway obtained from Kyoto Encyclopedia of Genes and Genomes pathway analysis (fructose group). The proteins in green are downregulated.
Glyceraldehyde-3-phosphate dehydrogenase was significantly upregulated at low pH, which was inconsistent with previous results showing that the same protein was strongly inhibited by decreased pH (from 7.8 to 5.6); this difference may be related to the lower pH (pH 5) in this study (
). Fructose and mannose metabolism, galactose metabolism, and glycolysis /gluconeogenesis were significantly downregulated at low pH, especially pyruvate metabolism. Low pH may be beneficial to homofermentation in L. lactis because glyceraldehyde-3-phosphate dehydrogenase was significantly upregulated and alcohol dehydrogenase was significantly downregulated. Galactokinase is crucial in the conversion of exogenous galactose to uridine diphosphate-galactose through the Leloir pathway (
). Lactococcus lactis contains genes encoding for galactokinase, tagatose-6-phosphate kinase, and tagatose 1,6-diphosphate aldolase, which might allow L. lactis to metabolize galactose through the tagatose pathway or the Leloir pathway. The results were consistent with (
), which showed that L. lactis S0 can metabolize galactose through the tagatose pathway or Leloir pathway.
Fatty Acid Metabolism
Fatty acid degradation is a major flavor-formation pathway, and fatty acid changes in the bacterial membrane provide the first line of defense against any stress (
Transcription profiling of interactions between Lactococcus lactis subsp. cremoris SK11 and Lactobacillus paracasei ATCC 334 during cheddar cheese simulation.
Int. J. Food Microbiol.2014; 178 (24674930): 76-86
Diverse physiological and metabolic adaptations by Lactobacillus plantarum and Oenococcus oeni in response to the phenolic stress during wine fermentation.
suggested that altering fatty acid composition by changing growth conditions may be useful to enhance bile resistance in lactococci. The cell envelope of Lactobacillus salivarius was modified by increasing the ratio of hydrophobic lipids and unsaturated fatty acids with key roles in tolerance to bile salt (
We detected a few DEG and DEP involved in fatty acid metabolism with consistent regulatory trends in the proteomics and transcriptomics analysis. Fatty acid metabolism and fatty acid biosynthesis were significantly downregulated under calcium ions in the transcriptome analysis, whereas fatty acid metabolism and fatty acid biosynthesis were significantly downregulated under palmitic acid (Supplemental Figure S18, https://doi.org/10.3168/jds.2020-18895) and low pH in the proteomics analysis (Supplemental Figure S19). These results were consistent with previous studies.
showed that the fatty acids biosynthesis in Lactobacillus plantarum decreased under adverse conditions. However, fatty acid biosynthesis in Lactobacillus rhamnosus GG was upregulated at pH 4.8, which may be the rerouting of the pyruvate metabolism which is conducive to fatty acid biosynthesis, thereby, affecting membrane fluidity in response to acid stress (
Amino acid and nucleotide metabolism are generally regulated under different culture conditions. The DEP related to amino acid metabolism and nucleic acid metabolism were significantly increased with increasing nitrite concentration (
). The transcriptional levels of key genes revealed that the acid resistance of Streptococcus thermophilus was achieved by regulating the arginine decarboxylase-urease pathway (
Influence of arginine on the growth, arginine metabolism and amino acid consumption profiles of Streptococcus thermophilus TLC2 in controlled pH batch fermentations.
). In this study, amino acid metabolism was significantly regulated under palmitic acid (Supplemental Figure S20, https://doi.org/10.3168/jds.2020-18895), glycine, serine, and threonine metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, and histidine metabolism were upregulated. These results indicated that L. lactis can make the necessary adjustments (promoting amino acid metabolism) to adapt to palmitic acid.
The transcriptional regulation of purine metabolism had important implications for stress tolerance in L. lactis (
Lactic acid bacteria (LAB) encounter various stress conditions during industrial processes, which are able to produce adaptive responses, and there are multiple self-regulatory mechanisms (
Effects of environmental stresses on the physiological characteristics, adhesion ability and pathogen adhesion inhibition of Lactobacillus plantarum KLDS 1.0328.
). Fructose consumption in foods and beverages has dramatically increased, fructose metabolism by Lactobacillus reuteri alters the metabolic flux in the cells (
). Therefore, in the present study, fructose was selected to replaced lactose in M17. Results showed that fructose metabolism was accelerated, but pyruvate metabolism was inhibited, besides, alpha-acetolactate decarboxylase were significantly downregulated, physiological role of decarboxylation was related to the production of metabolic energy (
Putrescine production via the ornithine decarboxylation pathway improves the acid stress survival of Lactobacillus brevis and is part of a horizontally transferred acid resistance locus.
Int. J. Food Microbiol.2014; 175 (24495587): 14-19
). The LAB gradually acidify their environment through the conversion of pyruvate to lactate, an essential process to regenerate NAD (+) used during glycolysis and conversion of pyruvate to acetic acid, which in turn benefits catabolic activities of the cell (
Effect of incubation conditions and possible intestinal nutrients on cis-9, trans-11 conjugated linoleic acid production by Lactobacillus acidophilus F0221.
). Optimal growth of some Lactobacillus requires supplementation with a source of fatty acids incorporated into the membrane and likely stimulate growth by significantly reducing the energy needed for fatty acids biosynthesis (
Diverse physiological and metabolic adaptations by Lactobacillus plantarum and Oenococcus oeni in response to the phenolic stress during wine fermentation.
Effects of environmental stresses on the physiological characteristics, adhesion ability and pathogen adhesion inhibition of Lactobacillus plantarum KLDS 1.0328.
), but long-chain fatty acids (palmitic acid) had no such effect in this study. In earlier studies, palmitic acid was closely related to the β-oxidation system of L. lactis (
Effect of incubation conditions and possible intestinal nutrients on cis-9, trans-11 conjugated linoleic acid production by Lactobacillus acidophilus F0221.
), so we detected DEG and DEP involved in fatty acid metabolisms by omics-analysis; fatty acid metabolism and fatty acid biosynthesis were significantly downregulated under palmitic acid. The amino acid metabolism and purine metabolism were significantly regulated under palmitic acid, as reported in previous study that the intracellular metabolites (proline, aspartate, glycerol, and mannitol) would be significantly accumulated in the cells under stress (
Exploring cellular fatty acid composition and intracellular metabolites of osmotic-tolerant mutant Lactobacillus paracasei NCBIO-M2 for highly efficient lactic acid production with high initial glucose concentration.
). Fatty acid metabolism and biosynthesis were significantly regulated under calcium ions in this study; this was consistent with the results in past studies: Ca2+ ions significantly affected the β-oxidation system of L. lactis (
), and acid stress not only induces changes on the components of the bacterial membrane, lipids and proteins but also disturbs the DNA and peptidoglycan components (
). By analyzing proteome under acid stress, proteins of Lactobacillus delbrueckii ssp. bulgaricus were changed in energy metabolism, nucleotide, and protein synthesis and stress response (
Acid adaptation of Lactobacillus delbrueckii subsp. bulgaricus induces physiological responses at membrane and cytosolic levels that improves cryotolerance.
J. Appl. Microbiol.2008; 105 (18498349): 1071-1080
); the intrinsic resistance of Lactobacillus pentoses was associated with metabolic pathways of proteins and carbohydrates, energy production, and stress responses (
Proteomic analysis of Lactobacillus pentosus for the identification of potential markers involved in acid resistance and their influence on other probiotic features.
). Similar results were obtained in this work; carbohydrates metabolic pathways (fructose and mannose metabolism, galactose metabolism, and glycolysis/gluconeogenesis) were significantly regulated at low pH, especially pyruvate metabolism. Other studies had shown that main functional categories of the proteins in Lactobacillus reuteri were metabolism of nucleotides and glycerolipids, transcription and translation, pH homeostasis, and stress responses (
). In addition, transcription analysis in acid-adapted cells indicated that several genes of Lactobacillus plantarum were differently regulated, including those related to amino acid metabolism, sugar metabolism and stress response pathways, and genes in fatty acid synthesis were significantly upregulated (
Study on the effect of citric acid adaptation toward the subsequent survival of Lactobacillus plantarum NCIMB 8826 in low pH fruit juices during refrigerated storage.
); however, in this study, fatty acid metabolism and fatty acid biosynthesis were significantly downregulated under low pH. The regulation of genes involved in the biogenesis of the cell wall and lipid metabolism was the reason of persistence (
). It can be seen from the literature that Lactobacillus adapts to acid stress by adjusting fatty acid metabolism, sugar metabolism, and amino acid metabolism; the conclusion is true in this study, but amino acid metabolism is not significant.
CONCLUSIONS
We analyzed the effects of different culture conditions on the transcriptome and proteome profiles of L. lactis and the changes in its biological regulatory mechanisms. Our results showed that different culture conditions caused significant changes in the proteomic and transcriptomic profiles of L. lactis. The protein levels did not significantly correlate with their corresponding gene expression levels. Fructose and pH significantly affected sugar metabolism in L. lactis. Fatty acid metabolism and fatty acid biosynthesis were significantly downregulated when calcium and palmitic acid were added to the culture. The amino acid metabolism was significantly regulated under palmitic acid. Our results provide theoretical support to explain the metabolic regulation of L. lactis under different culture conditions.
ACKNOWLEDGMENTS
This study was supported by the National Natural Science Foundation of China (Beijing; Grant No. 31401513) and the Excellent Youth Project of Natural Science Foundation of Heilongjiang Province (No. YQ2019C010; Heilongjiang, China). The authors declare no competing financial interest.
Transcription profiling of interactions between Lactococcus lactis subsp. cremoris SK11 and Lactobacillus paracasei ATCC 334 during cheddar cheese simulation.
Int. J. Food Microbiol.2014; 178 (24674930): 76-86
Diverse physiological and metabolic adaptations by Lactobacillus plantarum and Oenococcus oeni in response to the phenolic stress during wine fermentation.
Statistical study on fermentation conditions in the optimization of exopolysaccharide production by Lactobacillus rhamnosus 519 in skimmed milk base media.
Characterisation of Lactococcus lactis isolates from herbs, fruits and vegetables for use as biopreservatives against Listeria monocytogenes in cheese.
Influence of arginine on the growth, arginine metabolism and amino acid consumption profiles of Streptococcus thermophilus TLC2 in controlled pH batch fermentations.
Effect of incubation conditions and possible intestinal nutrients on cis-9, trans-11 conjugated linoleic acid production by Lactobacillus acidophilus F0221.
Effects of environmental stresses on the physiological characteristics, adhesion ability and pathogen adhesion inhibition of Lactobacillus plantarum KLDS 1.0328.
In vitro evaluation of resistance to environmental stress by planktonic and biofilm form of lactic acid bacteria isolated from traditionally made cheese from Serbia.
Proteomic analysis of Lactobacillus pentosus for the identification of potential markers involved in acid resistance and their influence on other probiotic features.
Putrescine production via the ornithine decarboxylation pathway improves the acid stress survival of Lactobacillus brevis and is part of a horizontally transferred acid resistance locus.
Int. J. Food Microbiol.2014; 175 (24495587): 14-19
Study on the effect of citric acid adaptation toward the subsequent survival of Lactobacillus plantarum NCIMB 8826 in low pH fruit juices during refrigerated storage.
Acid adaptation of Lactobacillus delbrueckii subsp. bulgaricus induces physiological responses at membrane and cytosolic levels that improves cryotolerance.
J. Appl. Microbiol.2008; 105 (18498349): 1071-1080
Exploring cellular fatty acid composition and intracellular metabolites of osmotic-tolerant mutant Lactobacillus paracasei NCBIO-M2 for highly efficient lactic acid production with high initial glucose concentration.
The genomic and transcriptomic basis of the potential of Lactobacillus plantarum A6 to improve the nutritional quality of a cereal based fermented food.
Int. J. Food Microbiol.2018; 266 (29037836): 346-354
Comparative proteomic analyses for elucidating metabolic changes during EPS production under different fermentation temperatures by Lactobacillus plantarum Q823.
Int. J. Food Microbiol.2016; 238 (27611800): 96-102
iTRAQ-based proteomic analysis of the viable but nonculturable state of Vibrio parahaemolyticus ATCC 17802 induced by food preservative and low temperature.
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