Listeria monocytogenes (LM) is an ubiquitous pathogen responsible for several outbreaks/foodborne diseases. The mortality rate is close to 24% mainly in immunocompromised persons (Farber and Peterkin, 1991). In the spreading of this pathology, milk and dairy products are a key reservoir for this pathogen (Greenwood et al., 1991). This represents a serious burden if considering the possibility of human infection and the financial losses due to the strict rules for food export. Food processing is one of the major steps that could be linked to LM contamination (Northolt et al., 1988) that is probably due to the presence of LM after the first post-pasteurization process of milk (Kozak et al., 1996). Inhibition of LM growth through the competition of other bacteria could represent a solution to this problem. In particular the production of bacteriocins by some species of Lactococcus could play a key role in pathogens growth inhibition (Stecchini et al., 1995). As well as, the study of the putative production of short genes coding peptides of LM could represent an important point, especially if considering their putative role in bacterial gene regulation. The objectives of this work are the bioinformatic study of the genomes of Listeria monocytogenes strains, in order to predict putative short genes coding peptides, potentially involved in gene regulation and the evaluation of extracellular peptidome analysis of separated lactoccoccus and listeria cultures and of these bacteria growing in competition conditions. Materials and Methods Bacterial strains Two strains of Lactococcus lactis (ATCC 11454, IL1403) and two strains of Listeria monocytogens (ATCC 19115, EDGe) have been used in the present study. They were stored at -80°C in M17 broth containing glycerol. Culture conditions Strains of both bacteria were precultured at 30°C in CDM (chemically-defined medium) (Letort and Juillard, 2001) and incubated overnight. 1% of Lactococcus lactis preculture was inoculated in 50 ml of MCD for Lactococcus lactis monoculture. 1% of Listeria monocytogenes preculture was inoculated in 50 ml of MCD for Listeria monoculture. 0.5% of Lactococcus preculture and 0.5% Listeria preculture were inoculated in 50 ml of CDM for coculture. Three described cultures were incubated at 30°C. Bacterial growth was estimated by measuring optical density at 600 nm (OD600) to the end of the exponential phase of growth. Supernatant preparation Cultures were centrifuged (5000 rpm, 10 min, 4°C) and supernatants were recovered. Supernatant was filtered using PDVF membrane 0,22 µm. Samples concentration has been performed using SPE (Strata X, 200mg, 0,3ml/min) and ultrafiltration using 3 kDa cut-off membranes (Amicon). HPLC injection in neutre condition 200 µl of each sample was separated by HPLC system equipped with an Acclaim column C18, 3µm, 2.1x150mm, 300 A°. Mobile phase A was ammonium formate 20 mM and mobile phase B was ammonium formate 20 mM in 80 % acetonitrile. Peptides were separated with a gradient of 5–35% mobile phase B over 20 min, followed by a plateau of 35% mobile phase B. Fractions were collected from 0 to 35 min. Fractions were dried by evaopartion (Speed Vac) then resuspended in 30 µl of TFA 0.08%/ACN 2% LC MS/MS Analysis LC-MS/MS analysis was performed on the PAPPSO platform (INRA, Jouy-en-Josas, France). An Ultimate 3000 LC system (Dionex) was connected to to a linear ion trap mass spectrometer (LTQ, Thermo Fisher) by a nanoelectrospray interface to conduct the separation, ionization and fragmentation of peptides, respectively. 5 microliters of each sample were loaded at a flow rate of 20 µL/min onto a precolumn (Pepmap C18; 0.3 × 5 mm, 100 Å, 5 µm; Dionex). After 4 min, the precolumn was connected with the separating nanocolumn Pepmap C18 (0.075 by 15 cm, 100Å, 3 μm), and the linear gradient was started from 2 to 36% of buffer B (0.1% formic acid, 80% ACN) in buffer A (0.1% formic acid, 2% ACN) at 300 nl min−1 over 50 min. Ionization was performed on liquid junction with a spray voltage of 1.3 kV applied to an uncoated capillary probe (PicoTip EMITER 10-μm tip inner diameter; New Objective). Peptides ions were automatically analyzed by the data-dependent method as follows: full MS scan (m/z 300 to 1,600) on Orbitrap analyzer and MS/MS on the four most abundant precursor on the LTQ linear ion trap. Data obtained in the instrument-specific data format (.RAW) were converted to mzxml files for further data analysis using a conversion software program (MSConvertGUI). Peptidomic data were analyzed by X!Tandem Pipeline software. Bioinformatic analysis The genomic sequence of strains has been analyzed for the presence of short genes at he MIGALE plateform (INRA, Jouy-en-Josas, France) using the BactGeneShow program. A gene containing from 48 to 183 bases (peptide from 15 to 60 amino acids) is considered as a short gene (artificial cut off), genes containing more than 183 bases are considered as "normal" genes. The threshold that has been used is mainly based on removal of predictions related to genes shorter than 48 bases. Three steps are fundamental for the construction of the database used for the peptides identification: 1. Extraction of the regions corresponding to coding sequences 2. Reversion of the nucleotidic sequences that are located on the reverse DNA strand 3. Conversion from nucleotides to amino acids. All these steps are done using bio-informatic scripts that are enclosed in the EMBOSS package. Results In Figure 1, growth curves of monoculture and coculture of Listeria monocytogenes and Lactococcus lactis with different strains are shown. Database searching, performed by X! Tandem Pipeline, allowed the identification of peptides that accumulates in the medium during the growth of the strains. About 957 peptides were identified for the LM ATCC 19115 monoculture, 2350 for Lactococcus lactis ATCC 11454 and 1440 for the mixed culture. 957 petides derive from 115 proteins for the monoculture of Listeria monocytogenes ATCC 19115; 2350 peptides from 110 proteins for the monoculture of Lactococcus lactis ATCC 11454 and 1440 peptides derive from 115 proteins identified in mixed culture (Figure 2A). Figure 2B shows a representative distribution of proteins identified in monoculture of Listeria monocytogenes EGDe, in monoculture of Lactococcus lactis IL 1403 and in co-culture (Listeria-lactococcus). 984 came from the degradation (by the bacteria) of 100 proteins for the monoculture of Listeria monocytogenes EDGE, among these 30 were present also in co-culture. Moreover, 4 proteins were expressed only in co-culture condition. 1741 peptides derive from 122 proteins identified in monoculture of Lactococcus lactis IL1403 and also in co-culture. 9 other proteins were expressed only in co-culture condition. 2587 peptides came from 165 proteins identified in coculture condition. This work has shown that specific proteins are degradated during the co-culture and we are currently investigating to elucidate the mechanism involved. Acknowledgements This work was performed during a COST ACTION FA1002 FAP Short Term Scientific Mission at INRA, UMR1319 MICALIS, Jouy-en-Josas(FR). This project was supported by Ministry of Health CCM Project : Milano EXPO 2015 (LB)

Bacterial competition for food safety in dairy products

C. Piras;P. Roncada
2014-01-01

Abstract

Listeria monocytogenes (LM) is an ubiquitous pathogen responsible for several outbreaks/foodborne diseases. The mortality rate is close to 24% mainly in immunocompromised persons (Farber and Peterkin, 1991). In the spreading of this pathology, milk and dairy products are a key reservoir for this pathogen (Greenwood et al., 1991). This represents a serious burden if considering the possibility of human infection and the financial losses due to the strict rules for food export. Food processing is one of the major steps that could be linked to LM contamination (Northolt et al., 1988) that is probably due to the presence of LM after the first post-pasteurization process of milk (Kozak et al., 1996). Inhibition of LM growth through the competition of other bacteria could represent a solution to this problem. In particular the production of bacteriocins by some species of Lactococcus could play a key role in pathogens growth inhibition (Stecchini et al., 1995). As well as, the study of the putative production of short genes coding peptides of LM could represent an important point, especially if considering their putative role in bacterial gene regulation. The objectives of this work are the bioinformatic study of the genomes of Listeria monocytogenes strains, in order to predict putative short genes coding peptides, potentially involved in gene regulation and the evaluation of extracellular peptidome analysis of separated lactoccoccus and listeria cultures and of these bacteria growing in competition conditions. Materials and Methods Bacterial strains Two strains of Lactococcus lactis (ATCC 11454, IL1403) and two strains of Listeria monocytogens (ATCC 19115, EDGe) have been used in the present study. They were stored at -80°C in M17 broth containing glycerol. Culture conditions Strains of both bacteria were precultured at 30°C in CDM (chemically-defined medium) (Letort and Juillard, 2001) and incubated overnight. 1% of Lactococcus lactis preculture was inoculated in 50 ml of MCD for Lactococcus lactis monoculture. 1% of Listeria monocytogenes preculture was inoculated in 50 ml of MCD for Listeria monoculture. 0.5% of Lactococcus preculture and 0.5% Listeria preculture were inoculated in 50 ml of CDM for coculture. Three described cultures were incubated at 30°C. Bacterial growth was estimated by measuring optical density at 600 nm (OD600) to the end of the exponential phase of growth. Supernatant preparation Cultures were centrifuged (5000 rpm, 10 min, 4°C) and supernatants were recovered. Supernatant was filtered using PDVF membrane 0,22 µm. Samples concentration has been performed using SPE (Strata X, 200mg, 0,3ml/min) and ultrafiltration using 3 kDa cut-off membranes (Amicon). HPLC injection in neutre condition 200 µl of each sample was separated by HPLC system equipped with an Acclaim column C18, 3µm, 2.1x150mm, 300 A°. Mobile phase A was ammonium formate 20 mM and mobile phase B was ammonium formate 20 mM in 80 % acetonitrile. Peptides were separated with a gradient of 5–35% mobile phase B over 20 min, followed by a plateau of 35% mobile phase B. Fractions were collected from 0 to 35 min. Fractions were dried by evaopartion (Speed Vac) then resuspended in 30 µl of TFA 0.08%/ACN 2% LC MS/MS Analysis LC-MS/MS analysis was performed on the PAPPSO platform (INRA, Jouy-en-Josas, France). An Ultimate 3000 LC system (Dionex) was connected to to a linear ion trap mass spectrometer (LTQ, Thermo Fisher) by a nanoelectrospray interface to conduct the separation, ionization and fragmentation of peptides, respectively. 5 microliters of each sample were loaded at a flow rate of 20 µL/min onto a precolumn (Pepmap C18; 0.3 × 5 mm, 100 Å, 5 µm; Dionex). After 4 min, the precolumn was connected with the separating nanocolumn Pepmap C18 (0.075 by 15 cm, 100Å, 3 μm), and the linear gradient was started from 2 to 36% of buffer B (0.1% formic acid, 80% ACN) in buffer A (0.1% formic acid, 2% ACN) at 300 nl min−1 over 50 min. Ionization was performed on liquid junction with a spray voltage of 1.3 kV applied to an uncoated capillary probe (PicoTip EMITER 10-μm tip inner diameter; New Objective). Peptides ions were automatically analyzed by the data-dependent method as follows: full MS scan (m/z 300 to 1,600) on Orbitrap analyzer and MS/MS on the four most abundant precursor on the LTQ linear ion trap. Data obtained in the instrument-specific data format (.RAW) were converted to mzxml files for further data analysis using a conversion software program (MSConvertGUI). Peptidomic data were analyzed by X!Tandem Pipeline software. Bioinformatic analysis The genomic sequence of strains has been analyzed for the presence of short genes at he MIGALE plateform (INRA, Jouy-en-Josas, France) using the BactGeneShow program. A gene containing from 48 to 183 bases (peptide from 15 to 60 amino acids) is considered as a short gene (artificial cut off), genes containing more than 183 bases are considered as "normal" genes. The threshold that has been used is mainly based on removal of predictions related to genes shorter than 48 bases. Three steps are fundamental for the construction of the database used for the peptides identification: 1. Extraction of the regions corresponding to coding sequences 2. Reversion of the nucleotidic sequences that are located on the reverse DNA strand 3. Conversion from nucleotides to amino acids. All these steps are done using bio-informatic scripts that are enclosed in the EMBOSS package. Results In Figure 1, growth curves of monoculture and coculture of Listeria monocytogenes and Lactococcus lactis with different strains are shown. Database searching, performed by X! Tandem Pipeline, allowed the identification of peptides that accumulates in the medium during the growth of the strains. About 957 peptides were identified for the LM ATCC 19115 monoculture, 2350 for Lactococcus lactis ATCC 11454 and 1440 for the mixed culture. 957 petides derive from 115 proteins for the monoculture of Listeria monocytogenes ATCC 19115; 2350 peptides from 110 proteins for the monoculture of Lactococcus lactis ATCC 11454 and 1440 peptides derive from 115 proteins identified in mixed culture (Figure 2A). Figure 2B shows a representative distribution of proteins identified in monoculture of Listeria monocytogenes EGDe, in monoculture of Lactococcus lactis IL 1403 and in co-culture (Listeria-lactococcus). 984 came from the degradation (by the bacteria) of 100 proteins for the monoculture of Listeria monocytogenes EDGE, among these 30 were present also in co-culture. Moreover, 4 proteins were expressed only in co-culture condition. 1741 peptides derive from 122 proteins identified in monoculture of Lactococcus lactis IL1403 and also in co-culture. 9 other proteins were expressed only in co-culture condition. 2587 peptides came from 165 proteins identified in coculture condition. This work has shown that specific proteins are degradated during the co-culture and we are currently investigating to elucidate the mechanism involved. Acknowledgements This work was performed during a COST ACTION FA1002 FAP Short Term Scientific Mission at INRA, UMR1319 MICALIS, Jouy-en-Josas(FR). This project was supported by Ministry of Health CCM Project : Milano EXPO 2015 (LB)
2014
9789086862627
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12317/19230
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