scholarly journals Understanding the killing mechanism of action by virus-infected yeasts

2018 ◽  
Author(s):  
Sean Sheppard ◽  
Duygu Dikicioglu
Keyword(s):  
Large Scale ◽  
Deterministic Model ◽  
Mechanistic Model ◽  
Starter Cultures ◽  
Apoptotic Pathway ◽  
Toxic Activity ◽  
Killer Activity ◽  
Killer Yeasts ◽  
Death Kinetics ◽  
Kinetics Of

AbstractKiller yeasts are microorganisms, which can produce and secrete proteinaceous toxins, a characteristic gainedviainfection by a virus. These toxins are able to kill sensitive cells of the same or a related species. From a biotechnological perspective, killer yeasts have been considered as beneficial due to their antifungal/antimicrobial activity, but also regarded as problematic for large-scale fermentation processes, whereby those yeasts would kill species off starter cultures and lead to stuck fermentations. Here, we propose a mechanistic model of the toxin-binding kinetics pertaining to the killer population coupled with the toxin-induced death kinetics of the sensitive population to study toxic actionin silico. Our deterministic model explains how killerSaccharomyces cerevisiaecells distress and consequently kill the sensitive members of the species, accounting for the K1, K2 and K28 toxin mode of action at high or low concentrations. The dynamic model captured the transient toxic activity starting from the introduction of killer cells into the culture at the time of inoculation through to induced cell death, and allowed us to gain novel insight on these mechanisms. The kinetics of K1/K2 activityviaits primary pathway of toxicity was 5.5 times faster than its activity at low concentration inducing the apoptotic pathway in sensitive cells. Conversely, we showed that the primary pathway for K28 was approximately 3 times slower than its equivalent apoptotic pathway, indicating the particular relevance of K28 in biotechnological applications where the toxin concentration is rarely above those limits to trigger the primary pathway of killer activity.

scholarly journals Dynamic modelling of the killing mechanism of action by virus-infected yeasts

2019 ◽  
Vol 16 (152) ◽  
pp. 20190064
Author(s):  
Sean Sheppard ◽  
Duygu Dikicioglu
Keyword(s):  
Large Scale ◽  
Mechanistic Model ◽  
Dynamic Modelling ◽  
Starter Cultures ◽  
Apoptotic Pathway ◽  
Toxic Activity ◽  
Killer Activity ◽  
Killer Yeasts ◽  
Death Kinetics ◽  
Kinetics Of

Killer yeasts are microorganisms, which can produce and secrete proteinaceous toxins, a characteristic gained via infection by a virus. These toxins are able to kill sensitive cells of the same or a related species. From a biotechnological perspective, killer yeasts are beneficial due to their antifungal/antimicrobial activity, but also regarded as problematic for large-scale fermentation processes, whereby those yeasts would kill starter cultures species and lead to stuck fermentations. Here, we propose a mechanistic model of the toxin-binding kinetics pertaining to the killer population coupled with the toxin-induced death kinetics of the sensitive population to study toxic action. The dynamic model captured the transient toxic activity starting from the introduction of killer cells into the culture at the time of inoculation through to induced cell death. The kinetics of K1/K2 activity via its primary pathway of toxicity was 5.5 times faster than its activity at low concentration inducing the apoptotic pathway in sensitive cells. Conversely, we showed that the primary pathway for K28 was approximately three times slower than its equivalent apoptotic pathway, indicating the particular relevance of K28 in biotechnological applications where the toxin concentration is rarely above those limits to trigger the primary pathway of killer activity.

KNP89: Kinetics of nonhomogeneous processes (KNP) and nonlinear dynamics

1990 ◽  
Vol 68 (9) ◽  
pp. 655-659 ◽  
Author(s):  
Gordon R. Freeman
Keyword(s):  
Nonlinear Dynamics ◽  
Scientific Literacy ◽  
Large Scale ◽  
Deterministic Model ◽  
Essential Elements ◽  
Deterministic Models ◽  
Group Of Seven ◽  
Internal Motions ◽  
Probable Reaction ◽  
Kinetics Of

Most systems in nature are nonhomogeneous: at least one component is not distributed homogeneously. A nonhomogeneous process is one that occurs in a nonhomogeneous system. The new subject Kinetics of Nonhomogeneous Processes (KNP) deals with processes in all aspects of nature. Examples range from quantum mechanics to membranes and to the evolution of the large scale structure of the universe. Models dealing with molecules and galaxies have common features: each has translational and rotational motions as an entity, and it has internal motions that are governed by the internal masses, fields and energies. To make progress towards understanding behaviour of a complex system, simplifications are needed. The formulation of a model requires identification of essential features of the behaviour, finding correlations between the features, and then representing them by equations. There is interplay between the structure of a system and the kinetics of processes that occur in it. To identify essential elements of any process we visualize it. Visualization is a powerful tool, especially the visualization of behaviour represented by equations. Models of KNP are of two general kinds: deterministic and stochastic. Deterministic models involve an assumption that events are the inevitable result of preceding conditions. The mathematical description of KNP involves nonlinear equations. Part of the physics community has therefore come to speak of nonlinear dynamics, which is a subdivision of KNP. An example of a deterministic model is the time dependent Landau–Ginzberg equation and modifications of it, which apply to pattern formation, self-localization, instabilities, and chaos. A stochastic model involves a step-by-step process and considers the probability of events as a function of time. In a system that contains many zones and each zone contains a relatively small number of entities, for example two ion–electron pairs or a group of seven galaxies, the probable reaction or deflection of any given entity is strongly affected by the actual number of entities initially in the zone, by their relative motions and separation distances, and by the forces that act between and within them. Scientific literacy in the future will require an understanding of both deterministic and stochastic models.

scholarly journals Quantifying the Significance of Phage Attack on Starter Cultures: a Mechanistic Model for Population Dynamics of Phage and Their Hosts Isolated from Fermenting Sauerkraut

2006 ◽  
Vol 72 (6) ◽  
pp. 3908-3915 ◽  
Author(s):  
P. Mudgal ◽  
F. Breidt ◽  
S. R. Lubkin ◽  
K. P. Sandeep
Keyword(s):  
Leuconostoc Mesenteroides ◽  
Model Simulation ◽  
Mechanistic Model ◽  
Resistant Cell ◽  
Starter Cultures ◽  
Multiplicity Of Infection ◽  
Model Simulations ◽  
Host Interaction ◽  
Waste Salt ◽  
Kinetics Of

ABSTRACT We investigated the possibility of using starter cultures in sauerkraut fermentation and thereby reducing the quantity of salt used in the process. This, in turn, would reduce the amount of waste salt that would enter in our water resources. Phage, naturally present in sauerkraut fermentation, could potentially affect the starter cultures introduced. Thus, a mechanistic mathematical model was developed to quantify the growth kinetics of the phage and starter cultures. The model was validated by independent experiments with two Leuconostoc mesenteroides strains isolated from sauerkraut and their corresponding phage. Model simulations and experimental evidence showed the presence of phage-resistant cell populations in starter cultures which replaced phage-sensitive cells, even when the initial phage density (P 0) and multiplicity of infection (MOI) were low (P 0 < 1 � 103 PFU/ml; MOI < 10−4) in the MRS media. Based on the results of model simulation and parameter optimization, it was suggested that the kinetic parameters of phage-host interaction, especially the adsorption rate, vary with the initial phage and host densities and with time. The model was validated in MRS broth. Therefore, the effects of heterogeneity and other environmental factors, such as temperature and pH, should be considered to make the model applicable to commercial fermentations.

scholarly journals Effects of Different Winemaking Yeasts on the Composition of Aroma-Active Compounds and Flavor of the Fermented Jujube Wine

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 970
Author(s):  
Yan Zhao ◽  
Xiaobin Yu ◽  
Fengtao Zhu ◽  
Guangpeng Liu ◽  
Le Chu ◽  
...  
Keyword(s):  
Large Scale ◽  
Starter Cultures ◽  
Flavor Quality ◽  
Wine Quality ◽  
Active Compounds ◽  
Ethyl Hexanoate ◽  
Optimal Starter ◽  
Phenethyl Acetate ◽  
Ethyl Decanoate

For the winemaking bioprocess of jujube wine, the selection of optimal starter cultures is one of the major concerns before fermentation. In this study, we investigated the effects of different winemaking yeasts on the composition of aroma-active compounds in the fermented jujube wine and identified the principal components that determine the flavor quality. It showed that the starter winemaking yeasts produced a total of 43 aroma-active compounds, of which esters (e.g., ethyl caprylate, ethyl decanoate, ethyl hexanoate, and phenethyl acetate) contribute more to the wine quality attributes, especially for the improvement of the aroma. Moreover, the composition of aroma-active compounds, for example, the ratio of the content of esters and alcohols, exerts a great impact on the flavor quality of jujube wine. Different starter winemaking yeasts resulted in significant differences in the composition (both species and content) of aroma-active compounds, and thus formed different flavors in the jujube wine. Thus, we propose that screening of a desirable starter winemaking yeast is essential before the fermentation of jujube wine at a large scale, and more considerations should be taken into the resulting composition of aroma-active compounds.

scholarly journals Role of antigen, CD8, and cytotoxic T lymphocyte (CTL) avidity in high dose antigen induction of apoptosis of effector CTL.

1996 ◽  
Vol 184 (2) ◽  
pp. 485-492 ◽  
Author(s):  
M A Alexander-Miller ◽  
G R Leggatt ◽  
A Sarin ◽  
J A Berzofsky
Keyword(s):  
T Lymphocytes ◽  
Cytotoxic T Lymphocyte ◽  
Target Cells ◽  
High Dose ◽  
High Avidity ◽  
Apoptotic Pathway ◽  
Peptide Antigen ◽  
Kinetics Of ◽  
Selection Of

Experimental data suggest that negative selection of thymocytes can occur as a result of supraoptimal antigenic stimulation. It is unknown, however, whether such mechanisms are at work in mature CD8+ T lymphocytes. Here, we show that CD8+ effector cytotoxic T lymphocytes (CTL) are susceptible to proliferative inhibition by high dose peptide antigen, leading to apoptotic death mediated by TNF-alpha release. Such inhibition is not reflected in the cytolytic potential of the CTL, since concentrations of antigen that are inhibitory for proliferation promote efficient lysis of target cells. Thus, although CTL have committed to the apoptotic pathway, the kinetics of this process are such that CTL function can occur before death of the CTL. The concentration of antigen required for inhibition is a function of the CTL avidity, in that concentrations of antigen capable of completely inhibiting high avidity CTL maximally stimulate low avidity CTL. Importantly, the inhibition can be detected in both activated and resting CTL. Blocking studies demonstrate that the CD8 molecule contributes significantly to the inhibitory signal as the addition of anti-CD8 antibody restores the proliferative response. Thus, our data support the model that mature CD8+ CTL can accommodate an activation signal of restricted intensity, which, if surpassed, results in deletion of that cell.

scholarly journals Kinetics of in vitro natural killer activity against K562 cells as detected by flow cytometry

Cytometry ◽  
1998 ◽  
Vol 32 (4) ◽  
pp. 280-285 ◽  
Author(s):  
Loris Zamai ◽  
Adriana R. Mariani ◽  
Giorgio Zauli ◽  
Luigi Rodella ◽  
Rita Rezzani ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Natural Killer ◽  
Natural Killer Activity ◽  
K562 Cells ◽  
Killer Activity ◽  
Kinetics Of

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

Polymerization Kinetics of Wheat Gluten upon Thermosetting. A Mechanistic Model

2002 ◽  
Vol 50 (21) ◽  
pp. 5947-5954 ◽  
Author(s):  
Sandra Domenek ◽  
Marie-Hélène Morel ◽  
Joëlle Bonicel ◽  
Stéphane Guilbert
Keyword(s):  
Mechanistic Model ◽  
Wheat Gluten ◽  
Polymerization Kinetics ◽  
Kinetics Of

scholarly journals A new mechanistic framework to predict OCS fluxes from soils

2016 ◽  
Vol 13 (8) ◽  
pp. 2221-2240 ◽  
Author(s):  
Jérôme Ogée ◽  
Joana Sauze ◽  
Jürgen Kesselmeier ◽  
Bernard Genty ◽  
Heidi Van Diest ◽  
...  
Keyword(s):  
Large Scale ◽  
Soil Microorganisms ◽  
Soil Moisture Content ◽  
Mechanistic Model ◽  
Carbonyl Sulfide ◽  
Reaction Diffusion ◽  
Global Scale ◽  
First Order ◽  
Uptake Rates ◽  
Hydrolysis Of

Abstract. Estimates of photosynthetic and respiratory fluxes at large scales are needed to improve our predictions of the current and future global CO2 cycle. Carbonyl sulfide (OCS) is the most abundant sulfur gas in the atmosphere and has been proposed as a new tracer of photosynthetic gross primary productivity (GPP), as the uptake of OCS from the atmosphere is dominated by the activity of carbonic anhydrase (CA), an enzyme abundant in leaves that also catalyses CO2 hydration during photosynthesis. However soils also exchange OCS with the atmosphere, which complicates the retrieval of GPP from atmospheric budgets. Indeed soils can take up large amounts of OCS from the atmosphere as soil microorganisms also contain CA, and OCS emissions from soils have been reported in agricultural fields or anoxic soils. To date no mechanistic framework exists to describe this exchange of OCS between soils and the atmosphere, but empirical results, once upscaled to the global scale, indicate that OCS consumption by soils dominates OCS emission and its contribution to the atmospheric budget is large, at about one third of the OCS uptake by vegetation, also with a large uncertainty. Here, we propose a new mechanistic model of the exchange of OCS between soils and the atmosphere that builds on our knowledge of soil CA activity from CO2 oxygen isotopes. In this model the OCS soil budget is described by a first-order reaction–diffusion–production equation, assuming that the hydrolysis of OCS by CA is total and irreversible. Using this model we are able to explain the observed presence of an optimum temperature for soil OCS uptake and show how this optimum can shift to cooler temperatures in the presence of soil OCS emission. Our model can also explain the observed optimum with soil moisture content previously described in the literature as a result of diffusional constraints on OCS hydrolysis. These diffusional constraints are also responsible for the response of OCS uptake to soil weight and depth observed previously. In order to simulate the exact OCS uptake rates and patterns observed on several soils collected from a range of biomes, different CA activities had to be invoked in each soil type, coherent with expected physiological levels of CA in soil microbes and with CA activities derived from CO2 isotope exchange measurements, given the differences in affinity of CA for both trace gases. Our model can be used to help upscale laboratory measurements to the plot or the region. Several suggestions are given for future experiments in order to test the model further and allow a better constraint on the large-scale OCS fluxes from both oxic and anoxic soils.

Sign in / Sign up

Export Citation Format

Share Document