Identification of Quorum Sensing Signal Molecule of Lactobacillus

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Identification of quorum sensing signal molecule of Lactobacillus delbrueckii subsp. bulgaricus Xiaoyang Pang, Cuiping Liu, Pengcheng Lv, Shuwen Zhang, Lu Liu, Jing Lu, Changlu Ma, and Jiaping Lv J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b04016 • Publication Date (Web): 25 Nov 2016 Downloaded from http://pubs.acs.org on November 27, 2016

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Journal of Agricultural and Food Chemistry

Identification of quorum sensing signal molecule of Lactobacillus delbrueckii subsp. bulgaricus Xiaoyang Pang,†,‡,ǁ Cuiping Liu,†, ǁ Pengcheng Lv, ∆ Shuwen Zhang, ‡ Lu Liu, ‡ Jing Lu, ‡

†

Changlu Ma, # and Jiaping Lv‡,*

State Key Laboratory of Dairy Biotechnology, Shanghai Engineering Research

Center of Dairy Biotechnology, Dairy Research Institute, Bright Dairy Co. Ltd., Shanghai 200436, P.R. China. ‡Key Laboratory of Agro-Food Processing and Quality Control, Institute of Agro-Food Science and Technology, Chinese Academy of Agricultural Science, Beijing 100193, P.R. China.

∆

College of life science and

Bioengineering, Beijing University of Technology, Beijing 100124, P.R. China. #

Beijing Vocational College of Agriculture, Beijing 102442, P.R. China.

ACS Paragon Plus Environment


Abstract: Many bacteria in nature use Quorum sensing (QS) to regulate gene expression. The quorum sensing system plays critical roles in the adaptation of bacteria to the surrounding environment. Previous studies have shown that during the high-density fermentation, the autolysis of lactic acid bacteria was regulated by the QS system, and the two-component system (TCS, LBUL_RS00115/LBUL_RS00110) is involved in the autolysis of Lactobacillus delbrueckii subsp. bulgaricus. However, the QS signal molecule which regulate this pathway have not been identified. In this study, we compared the genome of Lactobacillus bulgaricus ATCC BAA-365 with the locus of seven lactobacillus QS system, the position of QS signal molecule of Lactobacillus bulgaricus ATCC BAA-365 was predicted by bioinformatics tool. Its function was identified by in vitro experiments. Construction of TCS mutant by gene knockout of LBUL_RS00115 confirmed that the signal molecule regulates the density of the flora by the TCS (LBUL_RS00115/LBUL_RS00110). This study indicated that quorum quenching and inhibition based on the signal molecule might serve as an approach to reduce the rate of autolysis of LAB and increase the number of live bacteria in fermentation. Key words: Autolysis; quorum sensing; signal molecule; two-component system.

Introduction The lactic acid bacteria (LAB) is a kind of important food industry microorganism, which is widely used in the production of fermented food products such as dairy, meat, and vegetable products 1. Among the LAB, many Lactobacillus strains are considered


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to have excellent prebiotic effects in human 2. The genome sequences of a number of Lactobacillus species have been sequenced by Next Generation Sequencing（NGS） technology3, 4. This provides a basis for the analysis of the specific physiological characteristics of Lactobacillus using comparative genomics techniques

5-7

. During

the fermentation of dairy products, when the density of LAB exceeds a certain threshold, the phenomenon of cell lysis occurs in LAB, which is similar to the quorum sensing (QS) mechanism. In bacteria, the QS system is commonly composed of a two-component system (TCS) and a signal molecule

8, 9

. TCSs consist of a

membrane-located histidine protein kinase (HPK), which monitors one or more signal molecules, and a response regulator (RR), which modulates the expression of specific genes 10. Previous studies have shown that the autolysis rate of LAB is correlated with the

QS system

11

, and

one

of the

two-component regulatory systems

LBUL_RS00115/LBUL_RS00110 is involved in the autolysis of Lactobacillus delbrueckii subsp. bulgaricus ATCC BAA-365. However, the QS signaling molecule (Autoinducing Peptide, AIP) of L. bulgaricus has not been reported. In this study, the QS signal molecule of L. bulgaricus ATCC BAA-365 was found by bioinformatics analysis, and its function was identified by in vitro experiments. The aim of the present study was to increase the number of live LAB in fermentation by quorum quenching and inhibition based on the signal molecule. Materials and methods Bacterial culture and growth. L. bulgaricus ATCC BAA-365 was routinely grown at 37ºC in the Man–Rogosa–Sharpe (MRS) medium (Beijing Land Bridge



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Technology Co., Ltd. CM187) under static conditions. The polypeptides were synthesized by GL Biochem (Shanghai) Ltd. Genome sequence source and sequence analysis tools. The genome sequences of Lactobacillus acidophilus NCFM, Lactobacillus salivarius UCC118, Lactobacillus sakei subsp. sakei 23K, Lactobacillus plantarum WCFS1, Lactobacillus johnsonii NCC533 and Lactobacillus bulgaricus ATCC BAA-365 were downloaded from NCBI (http://www.ncbi.nlm.nih.gov/genome/). The Simple Modular Architecture Research Tool (SMART, http://smart.embl.de/) was used to analyze the main domain. The TMHMM Server (http://www.cbs.dtu.dk/services/TMHMM/) was used to analyze the transmembrane domain of proteins. Candidate QS-AIPs were examined according to their amino acid composition, residue position, motifs, and physicochemical properties using prediction algorithm “QSPpred”

12

. The Artemis

tool (http://www.sanger.ac.uk/science/tools/artemis) was used to browse and annotate the genomes. Functional verification of candidate QS-AIPs. The liquid (1 mL) containing bacteria in the logarithmic growth phase was added to a 1.5-mL centrifuge tube and centrifuged at room temperature at 5000 rpm for 5 mins. The supernatant was discarded, and the bacterial cells were collected. The cells were washed three times with 50 mL of sterile MRS culture media. After washing, the bacterial cells were inoculated into 50 mL of MRS culture medium. Candidate QS-AIP (2µM) was added to the bacterial suspension, and the change in the bacterial autolysis rate was detected. The autolysis rates were determined using the propidium iodide (PI)-flow cytometry


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method, as previously described 11. Briefly, about 1 × 107cells were stained with PI– phosphate-buffered saline away from light (30 min, 4ºC). Flow cytometry was used for analysis, with 100,000 cells collected per specimen, using the CellQuest software. The cells stained with PI were considered autolyzed. The groups were compared using one-way analysis of variance and least significant difference test. Construction of TCS Mutant. In order to verify the relationship between the two-component system (LBUL_RS00115/LBUL_RS00110) and the signal molecule, the LBUL_RS00115 mutant strain was constructed. A 819bp fragment intermediate region of the LBUL_RS00115 gene was first amplified by PCR with the HPK0115-SphI-F (5’- ACGCGCATGCCGCGGGCAGGCAAAAAG -3’) [SphI site underlined]

and

HPK0115-EcoRI-R

(5’-ACATGAATTCAACGCAGCGGATGATGCTTA-3’) [EcoR I site underlined] primers, and inserted into pUC19 to generate pUC19-HPK0115. The erythromycin resistance gene was amplified by PCR from pMG76e with the EryB-BstEII-F (5’CGGGTAACCATGACCACCGACGCCGCGACG -3’) and EryB-BstYI-R (5’CGAGATCCTCACTGCAACCAGGCTTCCGG -3’) primers, and inserted into pUC19-HPK0115

to

create

the

pUC19-HPK0115::EryBII

plasmid.

The

pUC19-HPK0115::EryBII plasmids was transformed into L. bulgaricus ATCC BAA-365 with minor modifications described in a previous study

13, 14

. The

transformed bacteria were transferred on solid MRS medium with 0.5M sucrose and erythromycin (200 µg/mL) for selection. Statistical Analysis. Statistical analysis was performed with one way ANOVA in



Origin 6.5 software. Results were accepted as statistically significant at a 0.05 significance level. Results Analysis of QS-TCS of Lactobacillus. Based on the published literature15-19 and the Quorumpeps database (http://quorumpeps.ugent.be), eight QS-TCS from six bacteria (L. acidophilus NCFM, L. johnsonii NCC533, L. sakei subsp. sakei 23K, L. salivarius UCC118, L. plantarum WCFS1, and L. bulgaricus ATCC BAA-365) were collected (Table 1) and analyzed. The results are shown in Figure 1. The eight QS-TCSs had similar domains of HPK and RR. Seven QS-HPKs have a typical transmembrane domain and histidine kinase-like ATPase domain (HATPase_c), but the HPK from L. sakei 23K lacked the transmembrane region. It might sense the intracellular signal (such as changes in the redox potential) through the unique signal transduction protein to obtain external environmental signals. The HPK generally has a conserved C-terminal ATP-binding domain in which a phosphoryl-accepted histidine residue is located and have highly conserved clusters of residues called homology boxes

20, 21

. Grebe & Stock classifies HPK proteins

according to the variable structure of homology boxes

22

. According to this

classification system, quorum sensing-related HPKs belonging to the subfamily called HPK10. In this study, a multiple comparison of different sources of HPK was conducted, and the phylogenetic tree was built using MEGA 6.0. The results are shown in Figure 2. WP_011677872.1 (which is encoded by LBUL_RS00115) from L. bulgaricus ATCC BAA-365 belongs to the HPK10 subfamily. All the eight QS-RR


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have LytTr DNA-binding domain (LytTR) and cheY-homologous receiver domain. The LytTR domain is extensively distributed in the low GC content of Gram-positive bacteria and involved in virulence

23, 24

, synthesis of bacteriocin

26

and extracellular

polysaccharides 25, and metabolic regulation. Sturme

26

summarized the characteristics of different kinds of QS-related proteins.

These characteristics included the following: (1) The HPK protein has an HPK10 subfamily domain and 5-7 N-terminal transmembrane segments and (2) The HPK protein have LytTr DNA-binding domains or RD/ComE subfamily domains. For L. bulgaricus ATCC BAA-365, one of the TCS (LBUL_RS00115/LBUL_RS00110) was in accordance with the aforementioned (1) and (2), but its QS-AIP has not been reported. Prediction QS-AIP of L. bulgaricus ATCC BAA-365. In many cases, the genes encoding the QS-AIP precursor, the histidine kinase receptor, and the RR form an operon, and its expression is auto-induced by QS 27. Figure 1 shows that the location of QS gene locus in Lactobacillus is AIP-HPK-RR, which gives a direction to analyze and predict the QS signal molecule (QS-AIP) of L. bulgaricus ATCC BAA-365. The whole genome of L. bulgaricus ATCC BAA-365 was analyzed, and it was found that a 372bp region (gene position 25031–25403) located upstream of the gene LBUL_RS00115 (HPK) was not annotated. All the possible coding peptides in this region were analyzed according to the three different reading frames, and 13 candidate QS-AIP precursor sequences were obtained (Table 2). The “QSPepPred” tool (http://crdd.osdd.net/servers/qsppred/) was used to predict and



analyze the QS-AIP from the 13 candidate peptides. QSPepPred is the first web server for predicting and designing QS peptides (QSPs). The tool can examine peptides whether they are QSPs according to their amino acid composition, residue position, motifs, and physicochemical properties. The QSPepPred tool was used in this study to predict QSPs from 13 candidate precursor sequences. The results are shown in Supplementary Table 1. Eleven candidate mature AIP sequences were selected according to the scores (Table 3). The length of the 11 AIP sequences ranged from 7 aa to 14 aa, and they were mainly distributed in three regions. Candidate AIPs in the same region had a very high degree of sequence overlap, and were considered as different fragments of the same polypeptide. One polypeptide was selected from each region, and the three peptides (I: LLSFFFY; II: MLDYFLFEN; III: FNINNNYS) were synthesized by GL Biochem (Shanghai) Ltd. Functional verification of candidate QS-AIPs. Previous studies have shown that during high-density fermentation, the autolysis rate of LAB is correlated with the QS system11, and the TCS (LBUL_RS00115/LBUL_RS00110) is involved in the autolysis of L. bulgaricus ATCC BAA-365. To verify the function of the candidate QS-AIPs predicted by the present study, three candidate QS-AIPs were added to the suspension of L. bulgaricus ATCC BAA-365. The change in autolysis rate was detected after adding QS-AIPs. Flow cytometry revealed no significant differences between BAA-365 with 2µM peptide I and BAA-365 with no peptide, indicating that peptide I was not associated with cell autolysis. Peptides I and III had similar experimental results. However, the autolysis rate of BAA-365 with 2µM peptide II


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sharply increased compared with the rate for BAA-365 with no peptide at the early cultivation. In addition, a markedly reduced maximum optical density value was obtained in BAA-365 with 2µM peptide II compared with BAA-365 with no peptide indicating that the density of L. bulgaricus population significantly decreased when peptide II was added (Fig3 a-d). The relationship of the TCS and the peptide II. In order to verify the relationship of

the

TCS

(LBUL_RS00115/LBUL_RS00110)

and

the

peptide

II,

the

LBUL_RS00115 mutant strain was constructed. The peptide II was added to the suspension of LBUL_RS00115 mutant according to the above method, and the growth curve of the mutant was observed and compared with the wild-type bacteria (Fig3 e-f). From the figure, it can be seen that the mutant with the peptide II reached its maximum growth density at 22 h, and the OD600 value at this time was significantly higher than that of wild-type BAA-365, the mutant without peptide II showed no significant difference in growth curve and autolysis rate with the mutant with 2 uM peptide II. By comparing Figures 3a, 3c and 3e, it can be seen that the peptide II has a function of regulating the growth density of Lactobacillus bulgaricus, and this regulatory process is involved by LBUL_RS00115. These findings indicated a significant role of peptide II in L. bulgaricus QS. Discussion Bacteria use the cell density–dependent quorum sensing system to regulate the expression of related genes to make themselves more adaptable to the surrounding environment

28

. In food industry, quorum sensing is related to many cases, for



example (foodborne) pathogenicity29, food spoilage30, and biofilm formation31, 32. The bacterial QS system consists of a two-component system (TCS) and a signal molecule33. TCSs consist of a membrane-located histidine protein kinase and a cytoplasmic response regulator, the former is responsible for sensing signal molecules, the latter is responsible for regulating specific genes expression34. Previous studies have shown that during the high-density fermentation, the autolysis rate of LAB is correlated with the QS system, and the TCS (LBUL_RS00115/LBUL_RS00110) is involved in the autolysis of Lactobacillus delbrueckii subsp. bulgaricus. However, the QS signaling molecule of L. bulgaricus has not been reported. The signal molecule play an important role in QS system of lactic acid bacteria, fermented milk producer can increase the number of live bacteria in fermentation by quorum quenching and inhibition based on the signal molecule. Acyl-homoserine lactones (AHLs) are a major QS signal molecules used by Gram-negative bacteria35. At present, many methods are used to detect AHL signal molecules, for example, high-performance liquid chromatography mass spectrometry, lysogeny broth plate method, agar strip method, beta-gal assay, and so on. But for Gram-positive bacteria, it primarily use autoinducing peptide as the signal molecule in the QS system to control gene expression. At present, there are few studies on the detection methods of autoinducing peptide. In this study, the QS intraspecies signal molecule of the L. bulgaricus ATCC BAA-365 was identified by bioinformatics analysis, and its function was identified by in vitro experiments. Construction of TCS mutant by gene knockout of


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LBUL_RS00115 confirmed that the signal molecule regulates the density of the flora by the TCS (LBUL_RS00115/LBUL_RS00110). This study indicated that quorum quenching and inhibition based the signal molecule might serve as an approach to reduce the rate of autolysis of LAB and promote the number of live bacteria in fermentation.

ASSOCIATED CONTENT Supporting Information Signal peptide prediction results by the “QSPepPred” tool. (Supplementary Table 1) AUTHOR INFORMATION Corresponding Author *

(J.L.) Mail: Institute of Agro-Food Science and Technology, Chinese Academy of

Agricultural Science, No. 1 Nongda South Rd., Xi Beiwang, Haidian District, Beijing 100193, China. Phone: (86) 10-62815542. E-mail: [email protected]. Author Contributions ǁ

Xiaoyang Pang and Cuiping Liu contributed equally to this work.

Funding This work was financially supported by National Natural Science Foundation of China (No.31471603), National Science-technology Support Plan Projects of China (No.2013BAD18B01),

Science

and

Technology

Commission

Municipality, China (No.16DZ2280600). Notes The authors declare no competing financial interest.


of

Shanghai


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Figure 1. Analysis results of six species of the Lactobacillus quorum sensing system. a, Lactobacillus salivarius UCC118; b, Lactobacillus johnsonii NCC533; c, Lactobacillus sakei subsp. sakei 23K; d, Lactobacillus acidophilus NCFM; e–g, Lactobacillus plantarum WCFS1; h,Lacbobacillus bulgaricus BAA-365. Figure 2. Evolutionary relationships of different histidine protein kinases. The evolutionary history was inferred using the Neighbor-Joining method36. The optimal tree with the sum of branch length = 16.51471714 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and are in the units of the number of amino acid substitutions per site. The analysis involved 36 amino acid sequences. Evolutionary analyses were conducted in MEGA637. Figure 3. Change in autolysis rate and OD600 of L. bulgaricus BAA-365 with 2µM candidate peptide.

Table 1 General features of HPKs and RRs of candidate QS-TCSs in different lactobacilli Gene/

Size

HPK10 Gene/

Locus Accession No.

Size

LytTR

Gene/

(aa)

domains

Accession No.

Locus (aa)

subfamily Accession No.

Locus


Page 15 of 20


HPK

RR

AIP

L. salivarius UCC118: abpK

LSL_1913

429

+

abpR

LSL_1912

264

+

abpIP

LSL_1914

435

+

NP_964619

LJ0766

265

+

NP_964616

LJ0763b

183

+

sppR

LSA0563

248

+

sppIP

440

+

YP_194633

LBA1798

274

+

L. johnsonii NCC533: NP_964617

LJ0764

L. sakei subsp. sakei 23K: sppKC

LSA0562

LSA0560b

L. acidophilus NCFM: LBA1799

YP_194634

YP_194635 LBA1800

L. plantarum WCFS1: plnB

lp_0416

442

+

plnC

lp_0417

247

+

plnA

lp_0415

pltK

lp_1355

420

+

pltR

lp_1356

255

+

pltA

lp_1354a

lamC

lp_3581

419

+

lamA

lp_3580

247

+

lamD

lp_3581a

LBUL_RS00115 434

+

RR

LBUL_RS00110 260

+

Unknown

Unknown

L. bulgaricus BAA-365: HPK

Table 2 Candidate QS-AIP sequences No.

Candidate QS-AIP sequences

ORF

Position

Peptide 1

YCCCLLSFFFYAF

–3

25293–25331

Peptide 2

QFLVSSMLDYFLFENFEYLYS

–3

25212–25274

Peptide 3

LFPPLRSMLPVICLSSLPRKNNF

–3

25140–25208

Peptide 4

ALLALHFAGHCFNINNNYSVARVFSRK

–3

25035–25115

Peptide 5

EIASLKELAQNVKVDVIAQNADIAVAYSRFSSMLFSPETCSNSL

–2

25265–25396

Peptide 6

VRCWIIFCLKILSICIHSYFLP

–2

25196–25261

Peptide 7

DLCFLLYAFPASREKIIFER

–2

25133–25192

Peptide 8

ISGLERCWRCTLPGTALT

–2

25076–25129

Peptide 9

HVYFQGNKK

–2

25028–25054

Peptide 10

LHRMLILLLLTLVFLLCFLARRLVAIPCKFDAGLFSV

–1

25237–25347

Peptide 11

VSVFIVISSLKIYASCYMPFQPPAKK

–1

25147–25224

Peptide 12

FLNVEFLALSVAGVALCRALL

–1

25081–25143

Peptide 13

QLFCSTCIFKEIKK

-1

25027–25068

Table 3 QS PepMap protein scan and mapping of peptides on proteins Peptide

SVM

SVM

SVM

SVM

Sequence

Comp Binary Physico Hybrid

KNN

KNN

KNN

Binary

Physico Hybrid

RF

RF

RF

Region Comp Physico

Hybrid

I

LLSFFFY

0.97

0.72

0.85

0.99

1

1

1

0.7

1

0.5

I

LLSFFFYA

0.94

0.68

0.89

0.95

0.8

1

1

0.9

1

0.5

II

DYFLFEN

1.26

1

1.27

1.3

1

1

1

1

0.9

1

II

DYFLFENF

1.17

0.3

1.04

1.16

1

1

1

1

0.9

0.8

II

MLDYFLFEN

1.14

0.29

0.75

1.14

1

1

1

1

0.9

0.8



Page 16 of 20

II

SMLDYFLFEN

1.04

0.85

0.57

1.03

1

1

1

1

0.9

0.7

II

SSMLDYFLFEN

1

1.17

0.27

0.96

1

1

1

1

0.9

0.9

II

SSMLDYFLFENFEY 0.87

0.84

-0.41

0.9

1

1

1

0.9

0.8

0.9

III

FNINNNY

1.04

0.07

0.94

1

1

1

1

1

1

0.9

III

FNINNNYS

1.08

0.22

0.84

1.03

1

1

1

1

0.9

0.9

III

CFNINNNYS

0.93

0.11

0.8

0.84

1

1

1

0.8

1

0.8

TOC graphic:


Page 17 of 20


Figure 1. Analysis results of six species of the Lactobacillus quorum sensing system. a, Lactobacillus salivarius UCC118; b, Lactobacillus johnsonii NCC533; c, Lactobacillus sakei subsp. sakei 23K; d, Lactobacillus acidophilus NCFM; e–g, Lactobacillus plantarum WCFS1; h,Lacbobacillus bulgaricus BAA-365. 194x499mm (72 x 72 DPI)


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Journal of Agricultural and Food WP 003623839.1 Page 18 of 20 100Chemistry

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II

4

70

3.5

3

60

3

2.5

50

2

40

1.5

30

1

20

1

0.5

10

0.5

2

4

6

8

10

12

14

16

18

20

22

24

60 50

2.5

40

2 30

1.5

0

20 10

0

0

2

4

6

8

10

Time/h

0.4 0.2

10

12

14

16

18

20

22

24

80

60

2.5

50

2

40

1.5

30

20

1

20

10

0.5

10

0

0

0

2

4

6

8

10

autolysis rate

12

14

16

18

70

20

22

24

growth curve

d: BAA-365 + peptide III (2uM) 80

autolysis rate

6

70

5

growth curve

80

autolysis rate

70

5

60

40

3

30

2

4

OD600nm

50

60

Autolysis rate/%

OD600nm

4

50

3

40 30

2

20 1

10 0

2

4

6

8

10

12

0

Time/h

c: BAA-365 + peptide II (2uM)

0

0

3

growth curve

Time/h

6

24

60

30

8

22

3.5

40 0.6

6

20

70

50

0.8

4

18

4

OD600nm

OD600nm

1

2

16

80

Autolysis rate/%

autolysis rate

1.2

0

14

b: BAA-365 + peptide I (2uM)

growth curve

0

12

Time/h

a: BAA-365 1.4

70

autolysis rate

Autolysis rate/%

0

growth curve

14

16

Time/h

ΔH0115++peptide peptideIIII(2uM) (2uM) c:e:BAA-365

18

20

22

24

0

20 1 0

10 0


2

4

6

8

10

12

14

Time/h

f: ΔH0115

16

18

20

22

24

0

Autolysis rate/%

0

OD600nm

OD600nm

3.5


autolysis rate

Autolysis rate/%

growth curve

Autolysis rate/%

80

4

Page 19 of 20


TOC Graphic


Page 20 of 20

Identification of Quorum Sensing Signal Molecule of Lactobacillus

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