Surface Properties of Parabacteroides distasonis and Impacts of Stress-Induced Molecules on Its Surface Adhesion and Biofilm Formation Capacities

The gut microbiota is a complex and dynamic ecosystem whose balance and homeostasis are essential to the host’s well-being and whose composition can be critically affected by various factors, including host stress. Parabacteroides distasonis causes well-known beneficial roles for its host, but is negatively impacted by stress. However, the mechanisms explaining its maintenance in the gut have not yet been explored, in particular its capacities to adhere onto (bio)surfaces, form biofilms and the way its physicochemical surface properties are affected by stressing conditions. In this paper, we reported adhesion and biofilm formation capacities of 14 unrelated strains of P. distasonis using a steam-based washing procedure, and the electrokinetic features of its surface. Results evidenced an important inter-strain variability for all experiments including the response to stress hormones. In fact, stress-induced molecules significantly impact P. distasonis adhesion and biofilm formation capacities in 35% and 23% of assays, respectively. This study not only provides basic data on the adhesion and biofilm formation capacities of P. distasonis to abiotic substrates but also paves the way for further research on how stress-molecules could be implicated in P. distasonis maintenance within the gut microbiota, which is a prerequisite for designing efficient solutions to optimize its survival within gut environment.

Strain variability in growth and thermal inactivation characteristics of Listeria monocytogenes strains after acid adaptation

Given the importance of strain variability to predictive microbiology and risk assessment, the present study aimed to quantify the magnitude of strain variability in growth and thermal inactivation kinetics behaviors after acid adaptation. Thirty-three Listeria monocytogenes strains were exposed to acid-adapted tryptic soy broth with yeast extract and nonacid-adapted TSB-YE (pH 7.0) for 20 hours. Then, the growth parameters of these adapted and non-adapted strains that grew in non-buffered TSB-YE at 25℃ were estimated. The tested strains were inactivated at 60°C in non-buffered broth to obtain the heat resistance parameters. The results revealed that strain variability was present in the growth and thermal inactivation characteristics. The maximum specific growth rate ( μ max ) ranged within 0.21-0.44 and 0.20-0.45 h -1 after acid and non-acid adaptation, respectively. The lag times ( λ ) were 0.69-2.56 and 0.24-3.36 hours for acid-adapted and non-acid adapted cells, respectively. The apparent D -values at 60°C ( D 60 -values) of the pathogen ranged within 0.56-3.93 and 0.52-3.63 minutes for the presence and absence of acid adaptation condition, respectively. Acid adaptation increased the magnitude of strain variability in the thermal inactivation characteristics of the organism ( P <0.05), with the coefficient of variation (CV) increasing to 0.17, while acid adaptation did not significantly influence the variabilities in the growth parameters of the tested strains ( P ≥0.05). Furthermore, the subsequent growth behaviors of all strains did not exhibit significant changes ( P >0.05) after exposure to acidic broth. However, the thermal resistance of most of the tested strains (25/33) increased ( P <0.05) after growing in acid-adapted broth. The relevant data generated in the present study can be used to describe the strain variability in predictive microbiology, and deeply understand the behavior responses of different strains to acid adaptation.

Evaluation of strain variability in inactivation of Campylobacter jejuni in simulated gastric fluid by using hierarchical Bayesian modeling

This study was conducted to quantitatively evaluate the variability of stress resistance in different strains of Campylobacter jejuni and the uncertainty of such strain variability. We developed Bayesian statistical models with multilevel analysis to quantify variability within a strain and variability between different strains and the uncertainty associated with these estimates. Furthermore, we measured the inactivation of 11 strains of C. jejuni in simulated gastric fluid with low pH, using the Weibullian survival model. The model was first developed for separate pH conditions, and then analyzed over a range of pH levels. We found that the model parameters developed under separate pH conditions exhibited clear dependence of survival on pH. In addition, the uncertainty of the variability between different strains could be described as the joint distribution of the model parameters. The latter model, including pH dependency, accurately predicted the number of surviving cells in individual as well as multiple strains. In conclusion, variabilities and uncertainties in inactivation could be simultaneously evaluated and interpreted via a probabilistic approach based on Bayesian theory. Such hierarchical Bayesian models could be useful for understanding individual strain variability in quantitative microbial risk assessment. Importance Since microbial strains vary in their growth and activation patterns in food materials, it is important to accurately predict these patterns for quantitative microbial risk assessment. However, most previous studies in this area have used highly resistant strains, which could lead to inaccurate predictions. Moreover, Variability including measurement errors and variability within a strain and between different strains, can contribute to predicted individual-level outcomes. Therefore, a multilevel framework is required to resolve these levels of variability and estimate their uncertainties. We developed a Bayesian predictive model for the survival of Campylobacter jejuni in simulated gastric conditions taking into account the variabilities and uncertainties. We demonstrated a high correspondence between predictions from the model and empirical measurements. The modeling procedure proposed in this study recommends a novel framework for predicting pathogen behavior, which can help improve quantitative microbial risk assessment during food production and distribution.

Genome Sequence of Staphylococcus epidermidis AUH4567, a Clinical Isolate from an Infected Central Venous Catheter

ABSTRACT Staphylococcus epidermidis is a common cause of implant-associated infections, and this is related to its ability to form biofilms. Strain-to-strain variability in biofilm formation is likely caused by genetic differences. Here, we present a draft genome of S. epidermidis AUH4567, which was isolated from a central venous catheter infection.

Secondary Aroma: Influence of Wine Microorganisms in Their Aroma Profile

Aroma profile is one of the main features for the acceptance of wine. Yeasts and bacteria are the responsible organisms to carry out both, alcoholic and malolactic fermentation. Alcoholic fermentation is in turn, responsible for transforming grape juice into wine and providing secondary aromas. Secondary aroma can be influenced by different factors; however, the influence of the microorganisms is one of the main agents affecting final wine aroma profile. Saccharomyces cerevisiae has historically been the most used yeast for winemaking process for its specific characteristics: high fermentative metabolism and kinetics, low acetic acid production, resistance to high levels of sugar, ethanol, sulfur dioxide and also, the production of pleasant aromatic compounds. Nevertheless, in the last years, the use of non-saccharomyces yeasts has been progressively growing according to their capacity to enhance aroma complexity and interact with S. cerevisiae, especially in mixed cultures. Hence, this review article is aimed at associating the main secondary aroma compounds present in wine with the microorganisms involved in the spontaneous and guided fermentations, as well as an approach to the strain variability of species, the genetic modifications that can occur and their relevance to wine aroma construction.