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Article

The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media

by
Núria Ferrer-Bustins
1,†,
Jean Carlos Correia Peres Costa
2,†,
Fernando Pérez-Rodríguez
2,
Belén Martín
1,
Sara Bover-Cid
1 and
Anna Jofré
1,*
1
Food Safety and Functionality Program, Institute of Agrifood Research and Technology (IRTA), Finca Camps i Armet, 17121 Monells, Spain
2
Department of Food Science and Technology, UIC Zoonosis y Enfermedades Emergentes ENZOEM, ceiaA3, University of Cordoba, 14014 Córdoba, Spain
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Fermentation 2024, 10(6), 326; https://doi.org/10.3390/fermentation10060326
Submission received: 25 April 2024 / Revised: 4 June 2024 / Accepted: 18 June 2024 / Published: 20 June 2024
(This article belongs to the Section Microbial Metabolism, Physiology & Genetics)
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Abstract

:
Listeria monocytogenes, the causative agent of listeriosis, is a relevant pathogen in dry fermented sausages (DFSs), and the application of antilisterial starter cultures is an effective intervention strategy to control the pathogen during DFS production. The effect of factors in relation to DFS formulation and production, NaCl (0–40 g/L), Mn (0.08–0.32 g/L), glucose (0–40 g/L) and temperature (3–37 °C), on the behaviour of L. monocytogenes when cocultured with Latilactobacillus sakei 23K (non-bacteriocinogenic) and CTC494 (bacteriocinogenic) strains was studied through a central composite design in meat simulation media. L. sakei and L. monocytogenes counts, pH, lactic acid production and bacteriocin activity were determined in mono and coculture. The pH decrease and lactic acid production were highly influenced by glucose, while production of sakacin K by L. sakei CTC494 was observed at moderate (10 and 20 °C), but not at the lowest (3 °C) and highest (37 °C), temperatures. Coculture growth had no effect on the acidification and bacteriocin production but inhibited and inactivated L. monocytogenes when L. sakei 23K entered the early stationary phase and when L. sakei CTC494 produced sakacin K. Optimal conditions for achieving a 5-log units reduction of L. monocytogenes were at 20 °C, 20 g/L of NaCl, 0.20 g/L of Mn and 40 g/L of glucose, those highlighting the importance of considering product formulation and fermentation conditions for bioprotective starter cultures application.

1. Introduction

Listeria monocytogenes is a facultative anaerobe foodborne pathogen found in a wide range of environments, including water, soil, faeces, food processing environments, and food [1]. This pathogen, when ingested, is the causative agent for listeriosis, a very severe foodborne illness with high mortality rate between 20 and 30%, making L. monocytogenes one of the most significant pathogens encountered in food [1,2]. Ready-to-eat (RTE) products (e.g., deli meats, soft cheeses, and seafood) are the main source of listeriosis outbreaks. Dry fermented sausages (DFSs) are not generally linked to food poisoning [1,3], due to the low probability of growth of the pathogen in these foods thanks to the effect of hurdles combination, with pH and water activity (aw) reductions achieved during fermentation and drying processes [4]. However, DFSs (especially low-acid type) are occasionally involved in withdrawals and recalls if the raw meat is contaminated with L. monocytogenes and the lethality of the fermentation process is not able to decrease to compliance levels (i.e., <2 log CFU/g) [5]. In the last 4 years, the European Rapid Alert System for Food and Feed portal (RASFF) [6] has recorded 13 notifications of L. monocytogenes in DFSs. The ubiquitous nature of L. monocytogenes allows it to be found at all stages of the pork processing chain, including raw pork. Specifically, pork can be contaminated in industrial environments when in contact with equipment and surfaces, where the pathogen can adapt and persist for extended periods, for instance in biofilm formations (i.e., aggregation ability of microorganisms on wet surfaces and grow in microcolonies, persisting in the environment) [7,8,9]. This increases the risk of cross-contamination during post-processing stages, which can pose a listeriosis risk to vulnerable consumer groups such as pregnant woman and individuals with weakened immune systems. Chilling temperatures during pork storage before DFS manufacturing can support L. monocytogenes growth [10], since it can multiply under relatively broad range of conditions of temperature (−1.5–45 °C), pH (4.5–9.0), aw (0.92–0.99) and salt concentrations (<16%) [10,11,12]. Despite European Regulation (EC) 2073/2005 establishing a maximum of 100 CFU/g in ready-to-eat (RTE) foods like DFSs, which are unable to support the growth of L. monocytogenes, 1.24% of fermented sausage units tested positive, and 0.11% exceeded the maximum limit according to enumeration tests for the pathogen in EU official samplings conducted during the 2018–2022 period [3,13,14]. As shown by several authors [8,15], L. monocytogenes is highly present in the equipment, industrial surfaces, the meat batter used for DFS, and final products, which is of concern.
Mediterranean-style DFSs are produced with a mixture of lean pork and fat with ingredients and additives including salt, dextrose, black pepper or paprika, sodium ascorbate and nitrifying agents. The production process of DFSs consists of fermentation and drying steps that reduce the meat batter pH and aw, turning DFSs into self-stable meat products not supporting bacterial growth [16]. Acidification and decrease in water activity transform nutritious fresh meat environments to harsh conditions for microorganism growth and development [10]. In the framework of the hurdle technology, both the formulation and production processes (i.e., decrease in pH and aw) provide antimicrobial barriers that contribute to the food safety of the final product. In industrial production, lactic acid bacteria (LAB) are frequently used as starter cultures to promote the product acidification through fermentation. Some LAB strains (the so-called bioprotective LAB) produce small antimicrobial peptides (i.e., bacteriocins such as sakacin and enterocin) with strong antimicrobial activity against L. monocytogenes [17] that can be used as a strategy to control the pathogen [18,19]. In fermented meat products, the bioprotective culture Latilactobacillus sakei CTC494 (formerly Lactobacillus sakei CTC494), a producer of sakacin K, has been used as starter culture in different types of DFSs, enhancing food safety due to its antilisterial effect [20,21]. The sakacin K antilisterial effect of L. sakei CTC494 has been previously tested with Listeria innocua coculture in meat simulation media [22], but it is the first time that it is experimented in coculture with the pathogenic L. monocytogenes. Sakacin K is a class IIa bacteriocin composed of 40 amino acid residues and a molecular weight of 3802 Da. Its structural gene is located on a 60 Kbp plasmid harboured by the L. sakei CTC494 strain. The sakacin K mode of action is similar to other bacteriocins such as sakacin A and curvacin A. These bacteriocins specifically attach and form pores in the membrane of Listeria, disrupting the cell homeostasis and thereby reducing cell viability [21,23]. Among the DFS ingredients influencing the behaviour of LAB, glucose and black pepper have shown to promote the growth, while NaCl can reduce their growth. For instance, increasing the amount of salt, from 2 to 3.5% or up to 6%, was reported to interfere with the LAB growth, bacteriocin production or the binding of the bacteriocins to the target microbiota cell membrane receptors [24,25]. In contrast, glucose, as carbon source, assists bacteriocin biosynthesis and bacterial growth [26]. Similarly, black pepper, with a high manganese content (76 ppm), promotes the LAB growth and fermentation of the meat batter [27,28]. Environmental conditions during fermentation, including temperature and sausage ingredients and additives (e.g., salt, nitrite, magnesium, manganese, oxygen, and fat), were reported to influence the growth of L. sakei CTC494 and sakacin K production [29,30]. Accordingly, in the DFS production process, ingredients, additives, temperature, and initial microbial communities have cross-related effects on the fermentation; hence [31], that can have an impact on the bacterial growth and metabolism.
Response Surface Methodology (RSM) is a robust and cost-effective approach [32] that allows to study the influence of several factors on bacterial growth response and metabolite production behaviour through a multifactorial experiment [33]. Previous RSM studies have shown reliable inferences when testing the influence of ingredients and additives used in RTE food on the growth and inhibition of Listeria spp. [2,33,34]. The optimal application of factors promoting the production of antimicrobials (e.g., bacteriocins and organic acids) and inhibition of pathogens can be used as a tool to improve food safety.
The objective of the present study was to evaluate the effect of factors related with the DFS formulation and production (glucose, manganese, salt, and temperature) on the behaviour of a non-bacteriocinogenic and bacteriocinogenic L. sakei strains growing in mono and coculture with L. monocytogenes. An RSM approach was applied to identify those combinations enhancing the antilisterial potential of L. sakei used as starter culture in DFSs.

2. Materials and Methods

2.1. Experimental Design

The effect of NaCl, manganese (Mn) and glucose (Gluc) concentration and temperature (T) on the behaviour of L. sakei and L. monocytogenes in monoculture and coculture was evaluated through two complete factorial designs (α = 23/4), using a circumscribed Central Composite Design (CCD) [35], with three independent factors each (Table 1). The central levels of the independent factors were selected regarding the typical concentrations and fermentation temperatures employed on industrial DFS production [20,31]. A total of 40 experimental runs were designed, of which 30 were conducted. Overlapping combinations between CCD1 and CCD2 (10 experiments) were performed only once (Table 2, in italics). For three factors, a second-degree polynomial equation was modelled for each CCD.

2.2. Bacterial Strains and Inoculum Preparation

The bacteriocinogenic strain L. sakei CTC494, known for antilisterial activity [21] and sourced from the Institute of Agrifood Research and Technology (IRTA) Food Safety and Functionality Programme culture collection, and the non-bacteriocinogenic strain L. sakei 23K [37] were selected for this study. L. monocytogenes CTC1034 (serotype 4b), sourced from IRTA’s collection, was used as the target pathogen. L. sakei and L. monocytogenes strains were isolated from DFS and stored at −80 °C in De Man Rogosa and Sharpe broth (MRS, Oxoid, UK) and Brain Heart Infusion broth (BHI, Beckon Dickinson, Sparks, MD, USA), respectively, both supplemented with 20% glycerol as a cryoprotectant.
Before the experiments, L. sakei and L. monocytogenes strains were cultured in MRS at 30 °C and BHI at 37 °C, respectively, for 8 h. Subsequently, the strains were pre-adapted in Meat Simulation Media (see Section 2.3), supplemented with NaCl (20.18 g/L), Mn (0.20 g/L), and glucose (20.18 g/L) (i.e., to concentrations at the central conditions of the CCD), and then incubated for 16 h at 20 °C.

2.3. Experiments with L. sakei Strains and L. monocytogens in Mono and Coculture in Meat Simulation Media

The experiments with L. sakei strains and L. monocytogenes, both in mono and coculture, were carried out in Meat Simulation Media (MSM) based on the formulation by Sánchez Mainar et al. [38]. The basic composition per litter included 11.0 g of Bacto proteose peptone No. 3 (Gibco™, Thermo Fisher Scientific, San Diego, CA, USA), 8.8 g of Beef extract (Difco™, Thermo Fisher Scientific, San Diego, CA, USA), 2.2 g of Yeast Extract (Liofilchem, Roseto degli Abruzzi, Italy), 0.038 g of MnSO4:4H2O (Merck KGaA, Darmstadt, Germany), and 1 mL of Tween 80 (Merck KGaA, Darmstadt, Germany). The pH was adjusted to 5.80, simulating the pH of a DFS meat batter.
Following pre-adaptation, the strains were inoculated into tubes containing 10 mL of MSM with different initial concentration of ca. 5 log CFU/mL for L. sakei (Ls) strains, within the typical range of concentrations of L. sakei starter cultures [20,31], and ca. 3 log CFU/mL for L. monocytogenes (Lm), a level expected in pork [5], under mono and coculture conditions. For the coculture experiments, the inoculation of L. sakei (CTC494 or 23K): L. monocytogenes resulted in an inoculation ratio of 5:3, corresponding to a logarithmic scale. The set of experiments in both mono and coculture were stored at 20 °C for CCD1 and at 3, 10, 20, 30 and 37 °C for CCD2 (Table 2) during a period from 2 to 28 days.
Samples for microbiological, pH, lactic acid and bacteriocin activity analysis were taken periodically (one tube per sampling time) with a temperature-dependent frequency: every hour for 30–37 °C cultures, every 3 h for 10–20 °C and every 24 h for 3 °C.

2.4. Microbiological Analyses

Microbiological determinations were performed by 10-fold serially diluting the cultures in physiological saline solution (1 g/L of peptone and 8.5 g/L of NaCl). L. sakei strains were enumerated in MRS agar plates (de Man, Rogosa and Sharpe; Merck, Darmstadt, Germany) and incubated at 30 °C for 72 h under anaerobic conditions using sealed jars with AnaeroGen sachets (Oxoid Ltd., Altrincham, UK). L. monocytogenes was enumerated in CHROMagar™ Listeria plates (CHROMagar, Paris, France) incubated at 37 °C for 48 h.

2.5. Physicochemical and Metabolite Determinations

pH values were measured using a puncture electrode model 5232 connected to a portable pHmeter PH25 (Crison Instruments S.A., Alella, Spain). The minimum pH (pHmin) was recorded, while the pH reduction was calculated as the difference between the initial pH (5.80) and the pHmin.
The determination of lactic acid concentration (LA; [g/L]) was indirectly measured by spectrophotometry directly from the culture supernatant, as by Borshchevskaya (2016) [39]. The coloured product resulting from the reaction of lactate ions with iron (III) chloride was measured at a wavelength of 390 nm.
Sakacin K activity of L. sakei CTC494 cultures was analysed through the spot-on lawn test [34,35]. In brief, culture supernatant was pasteurized (10 min at 80 °C), and proteins were precipitated with ammonium sulphate (0.3 g/mL) and stored overnight at 4 °C. The pelleted proteins were then resuspended in phosphate buffer and 2-fold serially diluted. Subsequently, 10 µL drops were placed onto the surface of a semisolid TSAYE overlay (Tryptone Soya agar with 0.6% yeast extract and 7.5 g/L of agar) inoculated with an overnight culture of L. monocytogenes CTC1034 in TSBYE (Tryptone Soya broth with 0.6% yeast extract). Plates were incubated overnight at 30 °C for 24 h. The results of sakacin K activity were expressed in arbitrary units (AU/mL), defined as the highest dilution causing a clear inhibition zone on the lawn of the target strain.
The maximum values of lactic acid concentration (LAmax) and bacteriocin activity (BACmax) were determined. Yield of lactic acid (YLA; mg/log CFU·h) and bacteriocin (YBAC; AU/log CFU·h), expressing the metabolite production as a function of bacterial biomass, were estimated by fitting the modified Luedeking and Piret model [40].

2.6. Assessment of Growth and Inactivation Parameters

Plate counts for L. sakei CTC494 and 23 K, as well as L. monocytogenes in mono and coculture, were transformed into decimal logarithmic values. The Logistic growth model without delay (λ = 0) [41] was fitted to the growth curves obtained from the experimental datasets generated by CCD1 and 2, using the MS Excel 2016 Solver add-in (Microsoft, Redmond, WA, USA). This model was used to obtain the kinetic parameters of growth, including the maximum specific growth rate (µmax; h−1) and maximum population density (Nmax; log CFU/mL). The goodness of fit of the Logistic model was assessed by root-mean-square error (RMSE) and coefficient of determination (R2), respectively.
The growth potential (i.e., log increase) of L. sakei (CTC494 and 23K) and L. monocytogenes strains was calculated as the difference between the maximum and the initial bacterial concentrations (log CFU/mL) using concentrations estimated by the Logistic model. For coculture experiments, pathogen inactivation (i.e., log reduction) was calculated as the difference between the maximum and the minimum concentrations (log CFU/mL).
The inactivation rate constant (kd; h−1) of L. monocytogenes in coculture with bacteriocinogenic L. sakei CTC494 was estimated as the slope of the first-order equation fitted to the log counts of the pathogen between 12 and 36 h, the interval of time in which L. monocytogenes showed a linear decrease.

2.7. Response Surface Methodology and Data Analysis

The effects of the independent factors (i.e., NaCl, Mn, glucose, and temperature) on the dependent physicochemical (i.e., pHmin, LAmax, YLA, BACmax and YBAC) and microbiological factors (i.e., µmax, Nmax, growth potential, log reduction and kd) were assessed by the Response Surface Methodology. The JMP v16.0.0 software (SAS Institute Inc., Cary, NC, USA) was used to fit a polynomial model for each response applying a stepwise regression approach, with forward direction and combined rules of the Bayesian Information Criteria (BIC) to achieve a parsimonious model with only statistically significant factors (p-value < 0.05). This methodology allowed the evaluation of linear, quadratic, and interactive effects of independent factors on microbial behaviour (dependent factors). Statistic tests of lack of fit, summary of fit, and Analysis of Variance (ANOVA) were used to evaluate the goodness of fit of polynomial equations and test significant differences (p-value < 0.05). The significance of the regression model and estimated parameters were evaluated by the lack-of-fit test. Two- and three-dimensional surface plots were drawn to illustrate the effect of the independent factors on significant models with insignificant lack of fit. Differences between the mono and cocultures responses were calculated using the t-test within the replicates of the central level of CCD.

3. Results and Discussion

The present study evaluated the effect of NaCl (0, 8.18, 20.18, 32.18 and 46.36 g/L), Mn (0.08, 0.13, 0.20, 0.27 and 0.32 g/L), glucose (0, 8.18, 20.18, 32.18 and 40.36 g/L) and temperature (3, 9.9, 20, 30 and 37 °C) (Table 1) on the physicochemical parameters (pHmin, LAmax, BACmax, YLA and YBAC) and microbiological parameters (µmax, Nmax, growth potential, log reduction and kd) associated with the behaviour in mono and coculture of L. sakei (CTC494 and 23K) and/or L. monocytogenes. The factor’s impact main results on mono and coculture are described in the following sections, while detailed results are reported in Supplementary Table S1. All polynomial equations and the results of statistic tests (i.e., lack of fit, summary of fit and ANOVA) for L. sakei and L. monocytogenes strains are described in Supplementary Table S2.

3.1. Assessment of the Effect of NaCl, Mn, Glucose, Temperature and Coculture in the Acidification and Bacteriocin Production in Meat Simulation Media

3.1.1. pH Decrease and Lactic Acid Formation

The decrease in pH values and the production of lactic acid depended on the bacterial species and were clearly influenced by the NaCl and glucose concentrations in the medium and the incubation temperature. Sodium chloride has been described to interfere with bacterial growth due to its role as an aw-lowering agent [25], and glucose is the main ATP-energy source for LAB fermentation and is fully converted to lactate by homofermentative L. sakei. Temperature modulates cell growth and, consequently, the use of the nutrient resources available in the media [42].
The strongest acidification, representing a decrease of 2.0 pH units from an initial pH of 5.80, was observed for both L. sakei strains (CTC494 and 23K) in mono and coculture with L. monocytogenes, reducing the pH of the medium to pHmin values of ca. 3.80 at glucose concentrations ≥ 8 g/L (i.e., all experiments except for experiment 10) (Figure 1A). Specifically, the lowest pHmin was achieved when the glucose concentration was the highest (40 g/L) by the strains L. sakei 23K and CTC494 both in mono and coculture, with pHmin ranging from 3.6 to 4.0 (reduction of ca. 2.0 pH units). When glucose was not added (i.e., experiment 10), the highest pHmin was achieved by L. sakei 23K (pH of 5.1) and L. sakei CTC494 (pH of 5.4), showing significant differences with the lowest values (p < 0.05). The same results were observed in coculture experiments (pHmin ca. 5.1), resulting in a reduction of only ca. 0.7 pH units and the lowest LAmax concentrations (ca. 0.55 g/L), as detailed in Supplementary Table S1. Conversely, in L. sakei monoculture experiments with higher NaCl concentration (32.18 g/L) at 20 °C (experiments 5, 6, 7 and 8), the pHmin values were slightly higher, ca. 4.00, representing a reduction of 1.8 pH units (Figure 1A). Barbieri et al. (2022) [43] showed that in fermentations of L. sakei in defined liquid medium (initial pH of 6.50), when glucose was not a limiting factor, the pH was reduced by 2.6 units, whereas when glucose was limiting, the reduction of pH was only 0.5 units.
In contrast, L. monocytogenes reached pHmin values in MSM of ca. 4.4, with the exception of experiment 10, where glucose was not added and the pHmin, with a value of 5.1, was the highest, corresponding to a reduction of 0.7 pH units (Figure 1A). Different pH reductions were due to the different availability of glucose, and when it was limiting (i.e., not added to the MSM), there was a lower production of lactic acid and, therefore, a less pronounced reduction in pH. On the contrary, when glucose was not a limiting factor (i.e., present in sufficient quantity, such as 40 g/L), the metabolic activity of LAB and the pathogen strains was accelerated, and a more significant reduction in the pH of the MSM was observed. Glucose is a fermentable sugar used by bacteria to generate lactic acid as a fermentation metabolite that promotes a pH drop. Specifically, for homofermentative bacteria (e.g., L. sakei), lactic acid is obtained as the sole product of glucose metabolization (i.e., 1 mole of glucose yields 2 moles of lactic acid and 2 moles of ATP, or 1 g of lactic acid per 1 g of substrate) [44].
As expected, higher LAmax values were registered when higher pH reductions occurred and lower pHmin were observed (Supplementary Table S1), as previously shown for L. sakei CTC494 [42]. On the contrary, and similar to the pHmin results, the lowest values of LAmax were achieved when glucose was not added (0.5, 0.7 and 0.6 g/L of LAmax for L. sakei 23K, CTC494 and L. monocytogenes, respectively). L. sakei strains produced more LA (>3 g/L) than L. monocytogenes (ca. 1.5 g/L) (p < 0.001) (Figure 1A). This fact could be related to metabolic differences between L. sakei and L. monocytogenes. L. sakei strains are homofermentative, performing glycolysis as the most efficient way to produce energy (i.e., ATP), and LA is the main fermentation product. In contrast, L. monocytogenes also produces ethanol and formate as products of its metabolism [45]. In the coculture experiments, the same observation (i.e., higher reductions in LAmax and pH in L. sakei monocultures) was made due to the acid produced by L. sakei strains with no acidification differences regarding the L. sakei strain in coculture (p > 0.05). However, coculture of the 23K strain and L. monocytogenes often showed higher values (e.g., 5.86 g/L of LAmax concentration in experiment 4) than the CTC494 coculture (e.g., 5.09 g/L of LAmax concentration in experiment 4) [45].
Overall, the highest LAmax and pH reductions registered by both coculture experiments were similar to those observed by monoculture (>3 g/L and a decrease of 2 pH units) and slightly higher than those of L. monocytogenes monoculture (ca. 1.5 g/L and 1.5 pH units) (p < 0.01) (Figure 1A). In the central point experiment runs, no coculture effect was observed, and similar pHmin (i.e., 3.72 ± 0.01 and 3.75 ± 0.03, for the 23Kco and CTC494co, respectively) and LAmax (i.e., 4.47 ± 0.12 g/L and 4.12 ± 0.32 g/L) were similar to those obtained in monoculture experiments for L. sakei strains (p > 0.05) (Figure 1A). These results indicated that simultaneous growth of L. sakei with L. monocytogenes had no relevant effect on acidification.
The RSM showed in experiments with L. sakei strains that glucose and NaCl had quadratic and linear effects, respectively, on LAmax values, whereas in coculture with L. monocytogenes, only glucose had a quadratic effect (p < 0.05) on the pHmin and LAmax concentrations (see polynomial equations coefficients in Supplementary Table S2). LA yield (YLA) was influenced by glucose with linear or quadratic effects for all strains. However, the polynomial models obtained showed poor goodness of fit to observed YLA data (Supplementary Table S2). In food fermentations, high LA production is desirable from a food safety perspective, and, in DFS, the antilisterial effect of LAB has been linked to the antimicrobial effect of LA (i.e., pH drop) [20].

3.1.2. Sakacin K Activity

The main factors affecting bacteriocin production by L. sakei CTC494, measured as maximum activity recorded during the experiment (i.e., BACmax), were temperature and Mn concentration (g/L). Leroy and de Vuyst [30] studied the effect of Mn limitation, which resulted in a considerable decrease in cell growth and lactic acid and bacteriocin production. The most favourable temperatures for bacteriocin activity in monoculture experiments were moderate (i.e., 10 and 20 °C), reaching a maximum activity of 6400 AU/mL in experiments 6, 7, 12, 25 and 26, whereas in coculture the higher BACmax values were observed in experiments 1, 6 and 22 (Figure 1B), indicating that there were no consistently higher values in coculture. Consequently, sakacin K production by L. sakei CTC494 was not stimulated by the presence of the pathogen, although induction of bacteriocin production has been reported in Lactiplantibacillus plantarum strains. This trait may be associated with a quorum sensing-related mechanism involving cell-to-cell contact and is therefore specific to the strain and determined by the bacteriocin production regulatory operon [46].
BAC activity was detected at the late exponential phase (t = 15 h) and in general increased to reach its maximum (BACmax of 3200 AU/mL) at the early stationary phase (see Figure 2 as an example). However, when experiments were conducted at higher temperatures (i.e., 30 and 37 °C), sakacin K activity was ≤800 AU/mL for experiments 23, 24, 27, 28 and 29, while at low temperature (i.e., 3 °C; experiment 30), no BAC activity was detected (Figure 1B). Previous studies with the CTC494 strain showed that at pH 6.5, the optimal temperature for BAC production was between 20 and 25 °C and was undetectable at 34 °C [29]. Furthermore, it was observed that at NaCl concentrations of 2%, L. sakei bacteriocin activity was decreased [25], and above 8% of NaCl, the sakacin K activity was not detected [29]. For another L. sakei strain, CCUG 42687, the maximum sakacin P production was also reported at 20 °C, with a concentration seven times higher than at 30 °C [47]. Temperatures for some fast-fermented European-style DFS fermentation coincide with the highest values of bacteriocin activity, maximising the antilisterial effect of the bioprotective starter culture. At temperatures higher than 25 °C, although cells grow faster, bacteriocin activity drops significantly due to the combined effect of a lower specific productivity and a higher bacteriocin degradation rate, and cell yield decreases as the energy needed for maintenance becomes more important [42].
The concentrations of Mn and NaCl (CCD1) showed a significant effect (p < 0.05) on BACmax and YBAC, which was also influenced by temperature (CCD2) (Supplementary Table S2). YBAC in coculture also showed similar yields to those obtained in monoculture, with values <300 AU/log CFU·h at extreme temperatures (3 °C ≤ and ≥ 30 °C), while at tested star concentrations of Mn (i.e., experiments 11 and 12), YBAC was >2000 AU/log CFU·h (Supplementary Table S1). Polynomial models for YBAC highlight temperature and Mn as the main factors influencing sakacin K production with quadratic effects (Supplementary Table S2). Leroy and De Vuyst [42] observed that the production of sakacin K by L. sakei CTC494 was highly influenced by pH and that the optimal temperature and pH for growth were different from those maximising bacteriocin production. Specifically, the optimum temperatures and pH values for L. sakei CTC494 growth were reported to be 33.5 °C and 6.15, while a pH of 5.0 and 23 °C were the most favourable conditions for bacteriocin production [30,42]. Enhancing the production of lactic acid and sakacin K can be used not only to maximise the antilisterial properties of L. sakei CTC494 when applied as a bioprotective culture in foods but also to increase the antimicrobial activity of the strain prepared as a postbiotic (i.e., microbial cells inactivated with/without metabolites) [48].

3.2. Impact of NaCl, Mn, Glucose, Temperature and Coculture in the Behaviour of L. sakei and L. monocytogenes

3.2.1. Bacterial Growth under DFS Fermentation Conditions in MSM

Microbiological parameters (µmax, Nmax and growth potential) of the strains were highly influenced by temperature. In both mono- and coculture, the highest and the lowest µmax values were observed at 37 °C and at 3 °C for the two L. sakei and L. monocytogenes (around 1.0 h−1 at 37 °C and 0.025 h−1 at 3 °C) (Figure 3A in monoculture; Figure 3D,G,H in coculture; Supplementary Table S1), which is in agreement with previous studies evaluating the effect of temperature on the growth of L. sakei CTC494 [42].
In monoculture experiments, the Nmax ranged between 7.5 and 8.7 log CFU/mL for L. sakei strains and were slightly higher (8.4–9.1 log CFU/mL) for L. monocytogenes (Supplementary Table S1). Previous studies in cooked ham also showed higher Nmax values for L. monocytogenes CTC1034 than L. sakei CTC494 [19]. NaCl, Mn, glucose and temperature had a microbiologically and statistically relevant effect on Nmax, although they were only significant for the CTC494 CCD1 model (Figure 3B).
Overall, the growth potential of the strains was affected by the independent factors NaCl and glucose, with temperature having the most remarkable effect. In monoculture experiments with L. sakei strains, growth potential ranged from 2.4 to 5.1 for 23K and 2.3 to 3.8 for CTC494, with the highest values observed in experiments with low salt concentrations and intermediate temperatures (5.1 log for 23K in experiment 3 and 3.8 log for CTC494 strains in experiment 23). In contrast, in monoculture, L. monocytogenes exhibited higher growth potential, ranging from 4.8 to 6.0 log, attributed to its lower initial concentration and higher Nmax compared to L. sakei (Figure 4). Coculture did not affect L. sakei Nmax, as shown for CTC494 strain in Figure 3B,E. This is in agreement with other experiments with this strain in cooked ham [19] and the strain L. sakei 706 (sakacin A producer) in MRS broth [49].
However, it is remarkable that coculture with L. sakei strains considerably reduced Nmax of L. monocytogenes (p < 0.001), especially the bacteriocinogenic CTC494 strain (Figure 4). Specifically, L. monocytogenes reached Nmax values ranging from 4 to 7 log CFU/mL in coculture with L. sakei strains, while in monoculture experiments, the pathogen always exhibited Nmax > 8.4 log CFU/mL (Supplementary Table S1).
Multiple factors may be involved in interactions between bacterial populations in the same ecosystem, including competition for nutrients, production of metabolites (e.g., organic acids and bacteriocins), signalling molecules and cell-to-cell contact mechanisms [50]. The results in coculture experiments showed that inhibition of L. monocytogenes growth occurred when the dominant population, i.e., L. sakei 23 K, reached its Nmax, leading to an early entry of the pathogen into the stationary phase. This phenomenon is known as the Jameson effect [51], which has been observed by several authors studying non-bacteriocinogenic competition between L. sakei and L. monocytogenes in broth media simulating DFS fermentation conditions [52,53,54]. On the other hand, the bacteriocinogenic strain CTC494 not only inhibited the growth of L. monocytogenes but also promoted its inactivation by more than 5 log units. Similar results were observed for the non-pathogenic Listeria innocua by Leroy et al. [47] in broth. The different behaviour of L. monocytogenes in coculture with 23K and CTC494 strains is shown in Figure 2B, which provides a representative example of the microbial kinetics together with the corresponding pH, LA and BAC production profiles (Figure 2A).
Considering the impact of the evaluated factors on the coculture experiments between L. sakei CTC494 and L. monocytogenes, the highest Nmax (5.5 log CFU/mL) for the pathogen was observed at extreme temperatures of 3 and 37 °C, and at 30 °C with high NaCl concentration of 32.18 g/L (Supplementary Table S1). These conditions correspond to those combinations of factors that did not favour bacteriocin production (i.e., experiments 23, 24, 27, 28, 29 and 30) (Figure 1B). Accordingly, the growth potential of L. sakei and L. monocytogenes in coculture was also influenced by temperature and NaCl (p < 0.05), and in the case of L. monocytogenes, it was significantly reduced (p < 0.001) by the presence of the dominant population, i.e., L. sakei, especially in experiments where the CTC494 strain produced bacteriocin (Figure 3C,F). More specifically, L. monocytogenes growth potential in monoculture was above 5 log and decreased, depending on the experimental conditions, to 1.4–3.5 log in coculture with L. sakei 23K and to 0.9–3.9 log in coculture with L. sakei CTC494 (Figure 4). In contrast, for both L. sakei strains, experiments at the lowest temperature (3 °C), at the highest temperature (37 °C), and at high temperature and high NaCl (30 °C and 32 g/L), the lowest reductions in the growth potential of L. monocytogenes (<1 log) were observed (Figure 4).

3.2.2. L. monocytogenes Inactivation by the Sakacin K Producer L. sakei CTC494

L. monocytogenes inactivation was only observed in the presence of L. sakei CTC494, with reductions ranging from −0.6 to −5.7 log. The lowest reductions correlated with experiments with lower BAC (i.e., experiments 23, 24, 27 and 28) (Figure 4 and Figure 1B, respectively). The promotion of L. sakei CTC494 by glucose or Mn at 20 or 10 °C (e.g., experiments 9 and 11) enhanced inactivation of the pathogen and reduced Nmax the most (i.e., >5.2 log). The mechanism explaining this phenomenon would be related with the model of action of sakacin-type bacteriocins, which specifically targets Listeria spp. by interacting with bacterial cell surface and cell membrane and forming pores, leading to cell permeabilization and ultimately to cell death [17,55]. Specifically for experiment 9, the highest reduction was observed with the maximum glucose concentration, which increased LA and sakacin K production. Similarly, high inactivation of L. monocytogenes was also observed by Pleasants et al. [49] in coculture experiments with L. sakei 706, a sakacin A producer, under conditions of 20 °C and pH 7 in MRS broth.
The highest pathogen inactivation rate (kd; h−1) in coculture with CTC494 was −0.20 h−1, at 20 °C, with 8 g/L of NaCl and glucose and 0.27 g/L of Mn (experiment 3). Under these conditions, the kd coincided with the highest reductions in pH, high LA production (ca. 5 g/L) (Figure 1A) and a reduction in the growth potential of L. monocytogenes by approximately 1 log compared to the pathogen in monoculture (e.g., 5 log) (Figure 4).
Experiments 9 and 3 reinforce that the combination of mild temperature (20 °C) and high glucose (≥32 g/L) determines the best strategy to inactivate the pathogen. As shown in Figure 5, the combined concentrations of NaCl (i.e., 10 to 20 g/L), glucose (i.e., 20 to 30 g/L) and temperature (i.e., 10 to 20 °C) had a statistically significant effect on pathogen inactivation in terms of inactivation rate and log reduction. Usual formulation of DFSs (g per kg of meat) consists of NaCl (20), maltodextrin (20), pepper (3) (i.e., Mn (0.228)) and ripening temperature of 13 °C [31], coinciding with central values of the studied factors. The obtained results show that low NaCl (i.e., 0.8% [w/v]) and abundant glucose and Mn availability in the media at mild temperature (i.e., 20 °C) enhance bacteriocin activity, therefore L. monocytogenes inactivation.
The polynomial equation indicated that the highest predicted pathogen reduction (−5.5 log) and kd (−0.13 h−1) would be achieved at the optimal combinations of 40.36 and 20.18 g/L of glucose, respectively, together with 20.18 g/L of NaCl at 20 °C (Table 2). The analysis also showed two and three quadratic two-way interactions for NaCl (p < 0.05) and temperature (p < 0.01) for L. monocytogenes reduction and for all independent factors (p < 0.01) for kd (Supplementary Table S2).
The optimal conditions to increase pathogen inactivation mainly depended on glucose concentration, as shown by the growth potential. In this regard, Figure 4 shows that the lowest pathogen growth also resulted in higher inactivation rates, such as in experiment 9 (with a maximum glucose concentration of 40 g/L). However, the combination of NaCl and glucose have also shown an effect on sakacin K production and, consequently, on the pathogen inactivation. In agreement, Leroy and De Vuyst [30] showed that when high glucose was combined with 10–20 g/L of NaCl, increased L. innocua inactivation rates were observed. Additionally, as temperature also determined the inactivation rate, sakacin K amounts have been reported to be enhanced at 20 °C in comparison to higher temperatures of 30 °C. Temperatures ≤ 20 °C are recommended to promote the antilisterial potential of bacteriocinogenic strains in DFSs [30].

4. Conclusions

The inhibition of L. monocytogenes through the application of L. sakei represents a control measure to enhance the food safety of dry fermented sausages as this species reduces the growth potential of the pathogen through the reduction of Nmax. However, only the application of the bacteriocinogenic L. sakei CTC494 has an antilisterial effect, providing an additional level of control by the reduction in the pathogen population. At mild temperatures around 20 °C and formulations promoting L. sakei growth (such as high glucose concentrations and Mn), together with lactic acid and sakacin K production, the inactivation of L. monocytogenes was enhanced, resulting in a reduction of more than 5-log units.
The safety of DFSs must be achieved through reduction of the levels of L. monocytogenes during the production process. The findings of this study underscore the critical role of starter cultures within the framework of the hurdle technology. Furthermore, their efficacy can be enhanced by application under optimal conditions for L. sakei growth and/or bacteriocin production.
The response surface methodology was a useful approach to identify the most appropriate temperature, NaCl and glucose conditions, taking into account the complex interactions between multiple variables to increase the inactivation of L. monocytogenes in meat simulation media in coculture with L. sakei CTC494. Further research needs to be performed on a real DFS food matrix to confirm the optimal conditions of application as a useful strategy for DFS manufacturers.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/fermentation10060326/s1, Table S1: Experimental and predicted data for each experiment run of CCDs 1 and 2; Table S2: Polynomial equations and Response Surface statistical parameters.

Author Contributions

Conceptualization, A.J., F.P.-R., S.B.-C. and B.M.; investigation: J.C.C.P.C. and N.F.-B.; methodology, J.C.C.P.C. and N.F.-B.; formal analysis, J.C.C.P.C. and N.F.-B.; writing—original draft preparation, N.F.-B. and A.J.; writing—review and editing, A.J., J.C.C.P.C., N.F.-B., F.P.-R., S.B.-C. and B.M.; supervision, A.J.; project administration, A.J., F.P.-R. and S.B.-C.; funding acquisition, A.J., F.P.-R. and S.B.-C. All authors have read and agreed to the published version of the manuscript.

Funding

This work has been framed within the NG-sausaging project (Grant RTI2018-099195-R-I00) funded by the Spanish Ministry of Science, Innovation and Universities (MCIN/AEI/10.13039/501100011033) and ERDF A way of making Europe, the Consolidated Research Group (2021 SGR 00468) funded by the Agency for Management of University and Research Grants (AGAUR) and the CERCA Programme from Generalitat de Catalunya. N. Ferrer-Bustins was the recipient of a doctoral contract grant (PRE2019-087847), and J. Costa was the recipient of the “Margarita Salas” post-doctoral fellowship (UCOR01MS) from the University of Córdoba, both financed by the Ministry of Science, Innovation and Universities (MCIN/AEI/10.13039/501100011033) of the Spanish Government.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to acknowledge the Micalis institute, INRAE, Université Paris Saclay, for providing L. sakei 23K strain and to thank M. Viella and A. Figueras for technical assistance.

Conflicts of Interest

The authors declare no conflicts of interest.

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Fermentation 10 00326 g001
Figure 1. Maximum concentration of lactic acid (LAmax) and pH reduction of L. sakei 23K, CTC494 and L. monocytogenes CTC1034 in monoculture and in coculture with L. sakei 23K (23Kco) and L. sakei CTC494 (CTC494co) (A), and maximum bacteriocin activity (BACmax) registered by L. sakei CTC494 (B). Central points (experiments 15–20) are expressed as mean and standard deviation of 6 replicates, and statistical significance is indicated: p-value p < 0.01 (**), p < 0.001 (***), p > 0.05 (non-significant, n.s.).
Figure 1. Maximum concentration of lactic acid (LAmax) and pH reduction of L. sakei 23K, CTC494 and L. monocytogenes CTC1034 in monoculture and in coculture with L. sakei 23K (23Kco) and L. sakei CTC494 (CTC494co) (A), and maximum bacteriocin activity (BACmax) registered by L. sakei CTC494 (B). Central points (experiments 15–20) are expressed as mean and standard deviation of 6 replicates, and statistical significance is indicated: p-value p < 0.01 (**), p < 0.001 (***), p > 0.05 (non-significant, n.s.).
Fermentation 10 00326 g001
Fermentation 10 00326 g002
Figure 2. Physicochemical parameters (pH, lactic acid (LA) and bacteriocin activity (BAC)) (A) and microbial counts (B) of strains in mono- and coculture of experiment run 9 (star point of glucose, 20 g/L of NaCl, 0.20 g/L of Mn, 40 g/L of glucose at 20 °C). Ls: L. sakei, Lm: L. monocytogenes, co: coculture.
Figure 2. Physicochemical parameters (pH, lactic acid (LA) and bacteriocin activity (BAC)) (A) and microbial counts (B) of strains in mono- and coculture of experiment run 9 (star point of glucose, 20 g/L of NaCl, 0.20 g/L of Mn, 40 g/L of glucose at 20 °C). Ls: L. sakei, Lm: L. monocytogenes, co: coculture.
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Figure 3. Microbiological parameters with significant effects response to independent factors. In monoculture, µmax of L. sakei 23K (A) and Nmax of L. sakei CTC494 (B). In coculture, growth potential of L. monocytogenes CTC1034 in coculture with L. sakei 23K (Lm-23Kco) (C), µmax of L. sakei 23K in coculture (Ls-23Kco) (D), Nmax of L. sakei CTC494 in coculture (Ls-CTC494co) (E), growth potential of L. monocytogenes CTC1034 in coculture with L. sakei CTC494 (Lm-CTC494co) (F), µmax of Ls-CTC494co (G) and of Lm-CTC494co (H).
Figure 3. Microbiological parameters with significant effects response to independent factors. In monoculture, µmax of L. sakei 23K (A) and Nmax of L. sakei CTC494 (B). In coculture, growth potential of L. monocytogenes CTC1034 in coculture with L. sakei 23K (Lm-23Kco) (C), µmax of L. sakei 23K in coculture (Ls-23Kco) (D), Nmax of L. sakei CTC494 in coculture (Ls-CTC494co) (E), growth potential of L. monocytogenes CTC1034 in coculture with L. sakei CTC494 (Lm-CTC494co) (F), µmax of Ls-CTC494co (G) and of Lm-CTC494co (H).
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Figure 4. Growth potential of L. monocytogenes CTC1034 in monoculture and coculture with L. sakei 23K (Lm-23Kco) and CTC494 (Lm-CTC494co) and log reduction of L. monocytogenes in coculture with L. sakei CTC494 (Lm-CTC494co). Growth potential statistical significance (p < 0.001; ***) in central points (experiments 15–20) is indicated.
Figure 4. Growth potential of L. monocytogenes CTC1034 in monoculture and coculture with L. sakei 23K (Lm-23Kco) and CTC494 (Lm-CTC494co) and log reduction of L. monocytogenes in coculture with L. sakei CTC494 (Lm-CTC494co). Growth potential statistical significance (p < 0.001; ***) in central points (experiments 15–20) is indicated.
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Fermentation 10 00326 g005
Figure 5. Inactivation parameters of L. monocytogenes in coculture with the bacteriocinogenic L. sakei CTC494 showing significant effects in response to independent factors. (A) Inactivation rate (kd; h−1). (B) log reduction.
Figure 5. Inactivation parameters of L. monocytogenes in coculture with the bacteriocinogenic L. sakei CTC494 showing significant effects in response to independent factors. (A) Inactivation rate (kd; h−1). (B) log reduction.
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Table 1. Independent factors of the circumscribed Central Composite Designs (CCDs) 1 and 2, operating at five levels for each factor, used to evaluate the effect of ingredients and temperature of DFS on L. sakei and L. monocytogenes behaviour.
Table 1. Independent factors of the circumscribed Central Composite Designs (CCDs) 1 and 2, operating at five levels for each factor, used to evaluate the effect of ingredients and temperature of DFS on L. sakei and L. monocytogenes behaviour.
Levels aCCD1 FactorsCCD2 Factors
x1 bx2 cx3 dx2 c
−1.68180.000.080.003.01
−1.00008.180.138.189.90
0.000020.180.2020.1820.00
+1.000032.180.2732.1830.11
+1.681840.360.3240.3637.00
a To maintain rotatability and orthogonality, the scaled value for α relative to the coded values ± 1 was 1.68 (23/4). b Factor 1 represents the concentration of NaCl (g/L) for CCD1. The corresponding aw theoretical values regarding NaCl concentration were 1.00 (0.00 g/L), 1.00 (8.18 g/L), 0.99 (20.18 g/L), 0.98 (32.18 g/L) and 0.98 (40.36 g/L) [36]. c Factor 2 represents the concentration of Mn (g/L) and temperature (°C) for CCD1 and CCD2, respectively. d Factor 3 represents the concentration of glucose (g/L) for CCD1.
Table 2. Concentrations of the evaluated factors according to the CCD1 and CCD2 and observed and predicted values of L. monocytogenes reduction (log) and inactivation rate constant (kd; h−1) when in coculture with the bacteriocinogenic L. sakei CTC494.
Table 2. Concentrations of the evaluated factors according to the CCD1 and CCD2 and observed and predicted values of L. monocytogenes reduction (log) and inactivation rate constant (kd; h−1) when in coculture with the bacteriocinogenic L. sakei CTC494.
Experimentx1x2x3NaCl (g/L)Mn (g/L)T (°C)Gluc (g/L)Observed
Reduction (log) 1		Predicted
Reduction (log) 1		Observed
kd (h−1) 1		Predicted
kd (h−1) 1
1−1.00−1.00−1.008.180.13NE 28.18−3.24−2.81−0.12−0.06
2−1.00−1.001.008.180.13NE32.18−4.14−4.29−0.17−0.09
3−1.001.00−1.008.180.27NE8.18−4.56−2.81−0.20−0.06
4−1.001.001.008.180.27NE32.18−4.59−4.29−0.15−0.09
51.00−1.00−1.0032.180.13NE8.18−2.59−2.39−0.07−0.06
61.00−1.001.0032.180.13NE32.18−2.37−3.87−0.06−0.09
71.001.00−1.0032.180.27NE8.18−3.34−2.39−0.08−0.06
81.001.001.0032.180.27NE32.18−2.64−3.87−0.07−0.09
90.000.001.6820.180.20NE40.36−5.59−5.46−0.13−0.09
100.000.00−1.6820.180.20NE0.000.35−2.96−0.01−0.03
110.001.680.0020.180.32NE20.18−5.62−4.21−0.12−0.13
120.00−1.680.0020.180.08NE20.18−5.16−4.21−0.19−0.13
131.680.000.0040.360.20NE20.18−1.75−1.40−0.06−0.04
14−1.680.000.000.000.20NE20.18−2.07−2.11−0.04−0.04
150.000.000.0020.180.20NE20.18−5.69−4.21−0.14−0.13
160.000.000.0020.180.20NE20.18−5.56−4.21−0.10−0.13
170.000.000.0020.180.20NE20.18−5.61−4.21−0.13−0.13
180.000.000.0020.180.20NE20.18−3.72−4.21−0.16−0.13
190.000.000.0020.180.20NE20.18−3.10−4.21−0.14−0.13
200.000.000.0020.180.20NE20.18−4.15−4.21−0.10−0.13
210.00−1.000.0020.18NE9.9020.18−3.26−2.48−0.02−0.01
220.00−1.000.0020.18NE9.9020.18−5.29−3.97−0.04−0.04
230.001.000.0020.18NE30.1120.18−0.52−0.89−0.03−0.02
240.001.000.0020.18NE30.1120.18−0.53−2.37−0.03−0.05
250.00−1.000.0020.18NE9.9020.18−3.26−2.06−0.02−0.01
260.00−1.000.0020.18NE9.9020.18−2.81−3.55−0.02−0.04
270.001.000.0020.18NE30.1120.18−0.60−0.47−0.02−0.02
280.001.000.0020.18NE30.1120.18−0.60−1.95−0.02−0.05
290.001.680.0020.18NE37.0020.18−1.620.31−0.05−0.02
300.00−1.680.0020.18NE3.0120.18−0.02−2.370.000.00
1 L. monocytogenes in coculture with the bacteriocinogenic L. sakei CTC494. 2 NE: Factor Not Evaluated in this experiment. In italics: Overlapped combinations between CCD1 and CCD2.
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Ferrer-Bustins, N.; Costa, J.C.C.P.; Pérez-Rodríguez, F.; Martín, B.; Bover-Cid, S.; Jofré, A. The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media. Fermentation 2024, 10, 326. https://doi.org/10.3390/fermentation10060326

AMA Style

Ferrer-Bustins N, Costa JCCP, Pérez-Rodríguez F, Martín B, Bover-Cid S, Jofré A. The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media. Fermentation. 2024; 10(6):326. https://doi.org/10.3390/fermentation10060326

Chicago/Turabian Style

Ferrer-Bustins, Núria, Jean Carlos Correia Peres Costa, Fernando Pérez-Rodríguez, Belén Martín, Sara Bover-Cid, and Anna Jofré. 2024. "The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media" Fermentation 10, no. 6: 326. https://doi.org/10.3390/fermentation10060326

APA Style

Ferrer-Bustins, N., Costa, J. C. C. P., Pérez-Rodríguez, F., Martín, B., Bover-Cid, S., & Jofré, A. (2024). The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media. Fermentation, 10(6), 326. https://doi.org/10.3390/fermentation10060326

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