Microbial Growth Kinetics Research Articles

Multivariable Robust Regulation of Alkalinities in Continuous Anaerobic Digestion Processes: Experimental Validation

A multivariable adaptive feedback control for highly uncertain continuous anaerobic digestion processes is proposed to regulate the volatile fatty acids (VFA) concentration, the strong ions concentrations, and the total and intermediate alkalinities. The multivariable control scheme includes a Luenberger observer to estimate both the unmeasured variables (i.e., VFA) and unknown microbial growth kinetics. The control approach is designed using an exponential Lyapunov function to resemble the typical exponential biological growth of the involved microbial consortia. Taking into account physicochemical equilibrium, alkalinities are represented as a function of the state variables. As a result, the control problem becomes a regulation problem on alkalinities, and in turn, a tracking control problem on the state variables, with two manipulated variables—the dilution rate and the feed rate of a strong alkali solution—while the state variables’ set-points are given as a function of pH. The implementation of this multivariable control scheme was experimentally tested and validated in a 0.982 m3 pilot plant treating agro-industrial wastewater and demonstrated to be robust in the face of unknown microbial growth kinetics. Results showed the potential for practical application and optimization of industrial digesters.

Producción de voltaje y tratamiento simultáneo de agua residual municipal en celdas de combustible microbianas operadas con cepas Clostridium

Clostridium strains are known due to their capability to produce hydrogen and free electrons during their metabolism; however, voltage production and electric current generation by Microbial Fuel Cell (MFC) have not been deeply explored yet employing these microorganisms. In this paper we evaluated both voltage generation and Chemical Oxygen Demand (COD) reduction in municipal wastewater by one chamber MFC performed with graphite cloth electrodes and inoculated with Clostridium bifermentans, Clostridium sordellii and native bacteria. Clostridium strains grew properly on both Ravot medium and municipal wastewater reaching the maximum develops at 96 and 120 hours for bifermentans and sordellii respectively. Microbial growth kinetics determined by Gompertz modified model showed low lag times for all tests. Clostridium sordellii showed not only the maximum voltages but also the highest potential to remove organic matter from wastewater since COD diminished around 60% at the end of MFC’s operation. The addition of phosphate salts solution increased the removal of organic matter but was not efficient to generate voltage, moreover, the microorganisms present in wastewater were able to produce voltage but  the amount of organic matter removed by them were low. The maximum generated voltage, Power Density (PD), Volumetric Power Density (VPD) and Current Density (CD) values were observed in MFC inoculated with Clostridium sordelli and performed with wastewater with no buffer solution, they were; 0.372 V, 153.43 mW m-2, 1.73 W m-3 and 0.413 A m-2 respectively. Clostridium strains showed a high potential to reduce COD in wastewater generating green energy as by-product.

Bio-Electrochemical System Depollution Capabilities and Monitoring Applications: Models, Applicability, Advanced Bio-Based Concept for Predicting Pollutant Degradation and Microbial Growth Kinetics via Gene Regulation Modelling

Microbial fuel cells (MFC) are an emerging technology for waste, wastewater and polluted soil treatment. In this manuscript, pollutants that can be treated using MFC systems producing energy are presented. Furthermore, the applicability of MFC in environmental monitoring is described. Common microbial species used, release of genome sequences, and gene regulation mechanisms, are discussed. However, although scaling-up is the key to improving MFC systems, it is still a difficult challenge. Mathematical models for MFCs are used for their design, control and optimization. Such models representing the system are presented here. In such comprehensive models, microbial growth kinetic approaches are essential to designing and predicting a biosystem. The empirical and unstructured Monod and Monod-type models, which are traditionally used, are also described here. Understanding and modelling of the gene regulatory network could be a solution for enhancing knowledge and designing more efficient MFC processes, useful for scaling it up. An advanced bio-based modelling concept connecting gene regulation modelling of specific metabolic pathways to microbial growth kinetic models is presented here; it enables a more accurate prediction and estimation of substrate biodegradation, microbial growth kinetics, and necessary gene and enzyme expression. The gene and enzyme expression prediction can also be used in synthetic and systems biology for process optimization. Moreover, various MFC applications as a bioreactor and bioremediator, and in soil pollutant removal and monitoring, are explored.

The microplastisphere: Biodegradable microplastics addition alters soil microbial community structure and function

Plastics accumulating in the environment, especially microplastics (defined as particles <5 mm), can lead to a range of problems and potential loss of ecosystem services. Polyhydroxyalkanoates (PHAs) are biodegradable plastics used in mulch films, and in packaging material to minimize plastic waste and to reduce soil pollution. Little is known, however, about the effect of microbioplastics on soil-plant interactions, especially soil microbial community structure and functioning in agroecosystems. For the first time, we combined zymography (to localize enzyme activity hotspots) with substrate-induced growth respiration to investigate the effect of PHAs addition on soil microbial community structure, growth, and exoenzyme kinetics in the microplastisphere (i.e. interface between soil and microplastic particles) compared to the rhizosphere and bulk soil. We used a common PHAs biopolymer, poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and showed that PHBV was readily used by the microbial community as a source of carbon (C) resulting in an increased specific microbial growth rate and a more active microbial biomass in the microplastisphere in comparison to the bulk soil. Higher β-glucosidase and leucine aminopeptidase activities (0.6–5.0 times higher Vmax) and lower enzyme affinities (1.5–2.0 times higher Km) were also detected in the microplastisphere relative to the rhizosphere. Furthermore, the PHBV addition changed the soil bacterial community at different taxonomical levels and increased the alpha diversity, as well as the relative abundance of Acidobacteria and Verrucomicrobia phyla, compared to the untreated soils. Overall, PHBV addition created soil hotspots where C and nutrient turnover is greatly enhanced, mainly driven by the accelerated microbial biomass and activity. In conclusion, microbioplastics have the potential to alter soil ecological functioning and biogeochemical cycling (e.g., SOM decomposition).

Comparison of the modified Monod and Droop function combined with Logistic function for describing algae growth

Microcystis aeruginosa (M. aeruginosa) are algae found in common freshwater blooms in China, and Dunaliella tertiolecta (D. tertiolecta) are economically important marine algae. Understanding of the microbial growth kinetics plays a significant role in the management of M. aeruginosa’s blooms and biodiesel production by D. tertiolecta. This study has shown that the combination of mechanistic models (Logistic and Monod) proved to be efficient in describing relationship between M. aeruginosa growth rates and specific concentrations of total dissolved phosphorus (TDP), orthophosphate (PO4 3--P), total dissolved nitrogen (TDN) and ammonia (NH4 +-N) reasonably with R2=0.28-0.93. Meanwhile, results also show that both PO43--P and NH4 +-N are important forms of TDP and TDN in influencing M. aeruginosa growth. It was also noted that the combination of modified Monod and Logistic functions is suitable for describing specific growth rates of D. tertiolecta versus extracellular nitrate concentrations (R2=0.24-0.72). In terms of the combination of Droop and Logistic functions, it was analysed to better explain the relationships between M. aeruginosa specific growth rates and cellular P and N concentrations (R2=0.41-0.86) as compared to the application of Droop function alone. It is also observed that the relationship between D. tertiolecta specific growth rates and intracellular nitrate concentrations also can be well described by the combination of Logistic and Droop functions. In addition, M. aeruginosa growth was affected by less intracellular P concentrations than intracellular N concentrations. In sum, the combination of modified Monod and Logistic functions and the combination of Droop and Logistic functions all can predict algae growth reasonably well, while the combination of Droop and Logistic functions is slightly better. Meanwhile, it is through these two combinations that two sets of better parameters in modified Monod and Droop functions can be respectively obtained to characterize algal population kinetics with changing nutrient concentrations.

Mathematical modeling for the design of evolution experiments to study the genetic instability of metabolically engineered photosynthetic microorganisms

Engineering the metabolism of photosynthetic microorganisms with the aim of converting CO2 and water, by exploiting solar energy, into end-products of commercial value is a rising interest in the biotechnology field. The producing host that carries a genetic modification not associated with competitive fitness advantage usually experiences a production burden (i.e., a metabolic burden related to product synthesis), leading to genetic instability and abortive production phenotype. The genetic instability of these engineered strains is a major hindrance to the spreading of large-scale photosynthetic cell factory processes. This genetic instability can be studied by means of evolution experiments, which are often time-consuming. In these experiments, the cell population is subjected to a long-term culturing during which the possible variation of the number of producers and of cells that lose the production traits, here defined as retro-mutants, is recorded. Here, a mathematical model that describes the dynamics of retro-mutants into a population of metabolically engineered photosynthetic microorganisms has been developed. The model has been used to simulate evolution experiments, conducted both in continuous (chemostat and turbidostat) and semi-continuous (serial batch transfer) culturing modes. These simulations allowed identifying the set of operative parameters for each cultivation mode that optimizes an evolution experiment in terms of experimental time needed to detect the arising of retro-mutants. Moreover, it has been found that in a scale of number of microbial generations only two parameters, precisely the production burden and the mutation rate, are determinant for the appearance of retro-mutants. These parameters are intrinsic features of any metabolically engineered strain and do not depend on the adopted cultivation system or on the microbial growth kinetics characteristics. This result further extends the applicability of the model also to non-photosynthetic metabolically engineered microorganisms.

The potential of Streptococcus salivarius oral films in the management of dental caries: An inkjet printing approach.

The use of probiotics, which can be administered in oro-dispersible films (ODFs) and have prolonged activity in the mouth, was explored. ODFs made of xylitol and containing Streptococcus salivarius were formulated using inkjet printing and tested against Streptococcus mutans - a causative organism of dental caries. The testing of the prepared ODFs involved co-incubating an ink-jetted formulation of S. salivarius and xylitol with S. mutans and monitoring the microbial growth kinetics in real-time using isothermal microcalorimetry and colony plate counts. Cell-free supernatants (CFS) of S. salivarius were also tested against S. mutans. The phosphate solubilisation potential of S. salivarius was also determined and found to be negative, an indication that the species will not deplete phosphate from teeth. From the tests, it was observed that the formulation reduced the S. mutans population from 7.9 to 5.04 Log CFU/mL post-calorimetry (approximately 3 Log reduction) which was comparable to the 99.9% reduction expected during antimicrobial activity testing. A gradual decrease in S. mutans population was also observed with increasing of CFS of S. salivarius volumes indicative of pathogen suppression. This study demonstrates that S. salivarius can be useful in managing dental caries and ODFs of S. salivarius can be formulated easily using ink-jetting for such management.

Microbially induced dolomite precipitates in Eocene lacustrine siliciclastic sequences in the Dongying depression, Bohai Bay Basin, China: Evidence from petrology, geochemistry, and numerical modeling

This study investigates the origin of dolomite by examining thick lacustrine sequences of evaporites, mudstones, and deep-water sublacustrine fan sandstones in the lower unit of the fourth member of the Eocene Shahejie Formation (Es4x) in Bohai Bay Basin, China. This petrographic, geochemical, and numerical modeling study recognizes evidence for microbially mediated dolomite precipitates in the Es4x sandstones, including the following: (1) spherical or elliptical dolomite aggregates consisting of submicrometer-sized crystals; (2) negative δ13CVPDB (VPDB refers to Vienna Peedee belemnite) values of the dolomite cements (–6.56‰ to –3.35‰); (3) relatively low precipitation temperatures of dolomite cements (39°C–65°C [102°F–149°F]) based on δ18OVPDB values from –8.76‰ to –4.65‰; and (4) negative 34SVCDT (VCDT refers to Vienna Canon Diablo troilite) values of associated framboidal pyrite (–3.9‰ to +5.7‰) with respect to an anhydrite precursor (+21.2‰ to +37.8‰). One-dimensional reactive transport modeling incorporating biodegradation kinetics was conducted to evaluate the link between biodegradation of organic matter and geochemical reactions of inorganic minerals during microbial sulfate reduction (MSR). Microbial metabolism in the model creates favorable geochemical conditions for dolomite precipitation by increasing pH, carbonate alkalinity, and Mg2+/Ca2+ ratio. The modeling results reproduce petrographic observations associated with the MSR process and indicate that the kinetics of microbial growth can significantly modify the geochemistry of simulated waters and enhance microbially mediated dolomite precipitation. Therefore, this study illustrates the effect of MSR in dolomite precipitation in a semiclosed and reducing continental lacustrine basin.

Application of monod two-substrate kinetics with an intermediate for anaerobic co-digestion of distillery wastewater and molasses/glycerol waste in batch experiments

Abstract Anaerobic digestion is a highly complex process, particularly in co-digestion between poorly-defined, complex co-substrates like distillery wastewater, molasses, and crude glycerine. Thus, in this article, the authors tackled the problems by using Monod two-substrate with an intermediate (M2SI) model to represent accumulated biomethane evolution (ABE) obtained from the co-substrates, including easily degradable, slowly degradable substrates and intermediate. The M2SI model predictions were compared with the traditional Monod model's simulation results to clarify an outstanding of the present model in the aspect of modeling and control. Different behaviors of ABE curves from batch experiments were used to calibrate the M2SI model prediction with sensitivity analysis of the model parameters. It was found that the M2SI model gives a correct trend to describe the co-digestion process with multiple substrates and complex microbial activities with satisfactory fitting accuracy. At the same time, simple Monod kinetics have a good fit for dilute pure distillery wastewater, but the estimated microbial growth kinetics were counterintuitive. Therefore, the M2SI Model has a broader range of applications for co-digestion dealing with the complexity of multiple microbial activities to consume inherently complex or artificial co-substrates.

Activated carbon from termite feces impregnated with silver: Preparation and evaluation of antimicrobial activity and ecotoxicity

Silver has a potent antimicrobial action, but its use is still restricted due to toxicity and aggregation problems. Impregnation with active carbon (AC) has been suggested as an alternative to solve this problem. In this study, termite feces were used to prepare composites containing silver nanoparticles and AC. Reducing agents and different amounts of H2 SO4 and silver were used. Antimicrobial activity was assessed using the minimum inhibitory concentration (MIC) and the kinetics of microbial growth of S. aureus, E. coli and C. albicans. Phytotoxicity and acute toxicity were assessed for Cucumis sativus and Artemia salina. The composites that presented MIC 500 μg/mL for S. aureus and E. coli were AC25Ag (6 μg/mL Ag) and AC25AgB (78 μg/mL Ag), respectively. AC6AgS showed antimicrobial activity in C. albicans with MIC of 500 μg/mL (23 μg/mL Ag). AC25AgB inhibited the growth of S. aureus and E. coli for 48 and 32 h, respectively. At a concentration of 10 g/L, the compounds showed deleterious effects on seedling germination and elongation and on the chlorophyll synthesis of C. sativus. The composites showed no toxicity to A. salina. Based on these results, AC25AgB has the potential to be used in water disinfection.

Droplet-Based Screening for the Investigation of Microbial Nonlinear Dose-Response Characteristics System, Background and Examples.

Droplet-based microfluidics is a versatile tool to reveal the dose–response relationship of different effectors on the microbial proliferation. Traditional readout parameter is the temporal development of the cell density for different effector concentrations. To determine nonlinear or unconventional dose–response relationships, data with high temporal resolution and dense concentration graduation are essential. If microorganisms with slow microbial growth kinetics are investigated, a sterile and evaporation-free long-term incubation technique is required. Here, we present a modular droplet-based screening system which was developed to solve these issues. Beside relevant technical aspects of the developed modules, the procedural workflow, and exemplary dose–response data for 1D and 2D dose–response screenings are presented.

Kinetics of crude oil degradation by an indigenous mixed culture isolated from palm oil mill effluent

Objectives: To investigate the microbial growth kinetics and degradation of crude oil (CO) by mixed cultures isolated from palm oil mill effluent (POME). Methods/Statistical analysis: The scanning electron microscope was employed to examine the surface morphology of POME and the CO contaminated soil. Microbial count using the total viable count (TVC), mold, and coliform counts were investigated at different levels of CO contamination. Findings: The TVCs at 20, 40, and 60 mg/L of CO were 7.3x107 CFU/g, 6.8x106 CFU/g and 7.2 x 106 CFU/g, respectively. The concentration of the CO was utilized at 20 mg/L indicating that this concentration did not inhibit microbial growth. Based on the correlation coefficient (R2) values obtained for the four growth kinetic models, the Haldane model with R2 of 0.97 gave the best fit. Application/Improvements: Finally, the one way ANOVA and Tukey\'s honest significant difference (HSD) indicated the statistically significant effect (P< 0.05) of the initial CO concentration on microbial growth. Keywords: Kinetics; Degradation; Mixed culture; Crude oil; Palm oil mill effluent

Development of a green liquor dregs pretreatment for enhanced glucose recovery from corn cobs and kinetic assessment on various bioethanol fermentation types

This study optimized a novel pretreatment of corn cob wastes (CCW) using green liquor dregs (GLD), a waste product from the chemical kraft pulping industry. Subsequently, the microbial growth and ethanol production kinetics of different bioprocess types were comparatively evaluated using the logistic and modified Gompertz models respectively. The optimized GLD pretreatment conditions released a maximum glucose yield of 0.42 g/g. Separate hydrolysis and fermentation (SHF), simultaneous saccharification and fermentation (SSF) and SSF with pre hydrolysis (PSSF) processes were assessed and gave comparable kinetic data. The SHF and PSSF processes displayed slightly higher microbial and bioethanol kinetic coefficients compared to the SSF system. Implications from this study provide major insights for reducing energy, time and costs incurred with lignocellulosic substrate pretreatment, bioethanol process design and scale up. Additionally, the study demonstrates a possible route for beneficiation of waste material such as GLD.

Computer Vision Approach for the Determination of Microbial Concentration and Growth Kinetics Using a Low Cost Sensor System.

The measurement of microbial contamination is of primary importance in different fields, from environmental monitoring to food safety and clinical analysis. Today, almost all microbiology laboratories make microbial concentration measurements using the standard Plate Count Technique (PCT), a manual method that must be performed by trained personnel. Since manual PCT analysis can result in eye fatigue and errors, in particular when hundreds of samples are processed every day, automatic colony counters have been built and are commercially available. While quick and reliable, these instruments are generally expensive, thus, portable colony counters based on smartphones have been developed and are of low cost but also not accurate as the commercial benchtop instruments. In this paper, a novel computer vision sensor system is presented that can measure the microbial concentration of a sample under test and also estimate the microbial growth kinetics by monitoring the colonies grown on a Petri dish at regular time intervals. The proposed method has been in-house validated by performing PCT analysis in parallel under the same conditions and using these results as a reference. All the measurements have been carried out in a laboratory using benchtop instruments, however, such a system can also be realized as an embedded sensor system to be deployed for microbial analysis outside a laboratory environment.

A mathematical modeling approach to the quantification of lactic acid bacteria in vacuum-packaged samples of cooked meat: Combining the TaqMan-based quantitative PCR method with the plate-count method

The TaqMan-based quantitative Polymerase Chain Reaction (qPCR) method and the Plate Count (PC) method are both used in combination with primary and secondary mathematical modeling, to describe the growth curves of Leuconostoc mesenteroides and Weissella viridescens in vacuum-packaged meat products during storage under different isothermal conditions. Vacuum-Packaged Morcilla (VPM), a typical cooked blood sausage, is used as a representative meat product, with the aim of improving shelf-life prediction methods for those sorts of meat products. The standard curves constructed by qPCR showed good linearity between the cycle threshold (CT) and log10 CFU/g, demonstrating the high precision and the reproducible results of the qPCR method. The curves were used for the quantification of L. mesenteroides and W. viridescens in artificially inoculated VPM samples under isothermal storage (5, 8, 13 and 18 °C). Primally, both the qPCR and the PC methods were compared, and a linear regression analysis demonstrated a statistically significant linear correlation between the methods. Secondly, the Baranyi and Roberts model was fitted to the growth curve data to estimate the kinetic parameters of L. mesenteroides and W. viridescens under isothermal conditions, and secondary models were used to establish the dependence of the maximum specific growth rate on the temperature. The results proved that primary and secondary models were adequate for describing the growth curves of both methods in relation to both bacteria. In conclusion, the results of all the experiments proved that the qPCR method in combination with the PC method can be used to construct microbial growth kinetics and that primary and secondary mathematical modeling can be successfully applied to describe the growth of L. mesenteroides and W. viridescens in vacuum-packaged morcilla and, by extension, other cooked meat products with similar characteristics.

A novel simulation model, BK_BiogaSim for design of onsite anaerobic digesters using two-stage biochemical kinetics: Codigestion of blackwater and organic waste

The design of biogas reactors for blackwater treatment provides special challenges due to significant variability in blackwater characteristics, the complexity of biological systems, and the need, in many cases, to operate in an extremely hygienic environment. In this study, mathematical models were formulated based on microbial growth kinetics to analyze the anaerobic codigestion of blackwater with kitchen waste as well as compare different substrate mixing ratios. The modelling approach used has the advantage of simulating the process with very little input data and eliminates the need to quantify the viable bacteria biomass, which is usually very difficult to estimate during anaerobic digestion. The validity of models is assessed by using a new statistical coefficient (α), which cumulates the effect of four known parameters: coefficient of determination (R2), adjusted coefficient of determination (R2Adj), reduced chi-square (χ2) and root mean square error (RMSE). A numerical calculation interface was designed to quickly and cheaply simulate different digestion scenarios, display results to user and evaluate the effect of input variation on the system's dynamics. Three simulation cases studies were considered each with different mixing ratios of black water to kitchen waste: Case 1 (50:50), Case 2 (25:75) and Case 3 (pure kitchen waste). The, Moser and Andrew based models were most appropriate in describing biogas kinetics for case study 1 (α-values of 0.2238 and 0.2596 respectively), the Monod and Moser based models most appropriate for case 2 (α-values of 0.0987 and 0.1266 respectively), while the Bergter and Haldane based models were most appropriate for case 3 (α-value of 0.0348 and 0.0347 respectively). The results of this study can be used to facilitate design and optimization of biogas sanitation units treating blackwater and kitchen waste.

Microbial growth and enzyme kinetics in rhizosphere hotspots are modulated by soil organics and nutrient availability

The input of labile organics by plant roots stimulates microbial activity and therefore facilitates biochemical process rates in the rhizosphere compared to bulk soil, forming microbial hotspots. However, the extent to which the functional properties of soil microorganisms are different in the hotspots formed in soils with contrasting fertility remains unclear. We identified the hotspots related to different levels of Zea mays L. root architecture by zymography of leucine aminopeptidase in two soils with contrasting fertility. The hotspots localized by tiny wet-needle approach around first- and second-order roots were compared for parameters of microbial growth and enzyme kinetics. The pattern of hotspot distribution was more dispersed and the hotspot area was one order of magnitude smaller around first-versus second-order roots. The specific microbial growth rate (μm) and biomass of active microorganisms were soil-specific, with no difference between the hotspots and bulk soil in the fertile soil. In contrast, in the soil poor in organic matter and nutrients, 1.2-fold higher μm and greater growing biomass were found in the hotspots versus bulk soil. Lower enzyme affinity (1.3–2.2 times higher Km value) of β-glucosidase and leucine aminopeptidase to the substrate was detected in the hotspots versus bulk soil, whereas only β-glucosidase showed higher potential enzyme activity (Vmax) in the hotspots, being 1.7–2.1 times greater than that in bulk soil. Notably, the activity of C-acquiring enzyme, β-glucosidase positively correlated with the biomass of actively growing microorganisms. The fertile soil, on the whole, showed greater Vmax and catalytic efficiency (Vmax/Km) and an approximately 2.5 times shorter substrate turnover time as compared to the poor soil. Therefore, we conclude that i) the differences in microbial growth strategy between rhizosphere hotspots and bulk soil were dependent on soil fertility; ii) affinity of hydrolytic enzyme systems to substrate was mainly modulated by plant, whereas potential enzymatic activity was driven by both plant and soil quality.

A rheological study of the bioleaching process of an iron ore for the elimination of gangue minerals

Bioleaching was used to dissolve zinc, phosphorus, potassium and calcium oxide found in iron concentrates using acidophilic microorganisms to enhance the iron yield. Rheological properties of the mineral pulps revealed a maximum in the zero shear-rate viscosity (0.068 Pa s) during day 5 of the process. The mineral concentrate contained hematite (Fe2O3) and magnetite (Fe3O4). Dissolution kinetics were followed in a continuous stirring tank reactor (CSTR) and pulp rheological properties were measured. Various analytical techniques were employed to evaluate the initial and final compositions of the mineral iron concentrates, such as scanning electron microscopy (SEM) and X-ray diffraction using the powder method (XRD). Data obtained from SAOS (small amplitude oscillatory shear) and simple shear were modeled using the multimodal Maxwell model and a kinetic rheological model (BMP), respectively. Up to 72% P, 91% CaO, 74% K and 53% Zn were dissolved in 5 days, where a maximum in both rheological analysis (continuous and oscillatory flow) was observed. This maximum coincided with the end of the microbial growth phase, demonstrating that the microbial growth kinetics influenced the rheological property, which can be modeled using a kinetic-like constitutive equation. The linear viscoelastic response of the pulp is consistent with the appearance of a weak gel at long times (low frequency) with relaxation exponent of n = 0.91 and gel strength of S = 0.0151 Pa sn. A generalized Maxwellian behavior with three relaxation times was observed at high frequency, associated with biofilm–particle interactions. Further investigations may consider other rheological analysis such as LAOS or stress relaxation.

A multi‐scale analysis of the effect of complex viscoelastic models on Listeria dynamics and adaptation in co‐culture systems

AbstractNatural antimicrobials are of interest to replace traditional food decontamination methods: they are milder and maintain desirable sensory characteristics. However, efficacy can be affected by food structure/composition, thus structural effects in a co‐culture pathogen/microflora system are investigated. Listeria was grown planktonically (liquid broth) or on a biphasic viscoelastic system, in monoculture with/without artificial nisin, or in co‐culture with Lactococcus lactis (nisin/non‐nisin producing). Microbial growth kinetics were monitored and advanced microscopy techniques were utilized to quantify cellular interactions and spatial organization. Microstructural effects are observed on the kinetics, with differences in monoculture/co‐culture. Significant microscopic differences are observed in spatial organization and colony size. We are the first to observe changing growth location for all species in monoculture/co‐culture, with differences in colony size/organization through stationary phase. This study provides insight into the environmental stress response/adaptation of Listeria grown on structured systems in response to L. lactis and natural antimicrobials.

Bioethanol production from woody stem Prosopis juliflora using thermo tolerant yeast Kluyveromyces marxianus and its kinetics studies

In the present study, Kluyveromyces marxianus was utilized to study the batch fermentation kinetics of biomass production, substrate utilization and bioethanol production from woody stem Prosopis juliflora. The pre-treated substrate was subjected to Simultaneous Saccharification and Fermentation (SSF) under optimised conditions of pH (4.9), temperature (41 °C), substrate concentration 5% (w/v), inoculum concentration 3% (v/v) and the maximum concentration of bioethanol was found to be 21.45 g/l. The experimental data thus obtained from cell growth, substrate utilization and product formation are employed in the determination of kinetic parameters. Biological models such as Logistic model, Hinshelwood model were used for microbial growth and substrate utilization kinetics respectively. In case of product kinetics, Leudking-Piret plot, Gompertz model and Modified Gompertz model were utilised. Based on these models, kinetic parameters like maximum specific growth rate (µm), saturation constant (Ks), growth associated (α), non-growth associated (β) and yield coefficients (YX/S, YP/S) were estimated.