Development of a laboratory-based model to study the interaction between nutrients and Vibrio cholerae and predicting the spread of cholera outbreaks in the Indian subcontinent.

Cholera is an infectious disease that is transmitted through contaminated water. The disease includes a long back history of epidemics. Despite the numerous hygiene and prevention techniques that have been developed for Cholera, outbreaks of cholera are still reported worldwide. The resolution to this issue lies in promptly identifying the area susceptible to cholera outbreaks, a matter that continues to perplex scientists and medical professionals. It has been reported that Vibrio is effective in nitrogen digestion because it contains the nasA gene. In this study, initially the impact of nutrients (nitrate and nitrite) on growth of Vibrio cholerae was determined, subsequently a relationship was developed between nutrient substrates and V. cholerae growth rate, using Monod model. Subsequently, the model was applied to large national river quality data set (2012-2014) developed by Central Pollution Control Board (CPCB) and a possible cholerae outbreak zone was predicted. This work will definitely help the policy makers to develop management strategy for keeping rivers safe from future cholera outbreak.

In-situ substitution and community dynamics modeling for enhanced safety in Chinese rice wine brewing.

This research paper focuses on the application of the "Design-Build-Test-Learn" framework to design and evaluate a synthetic microbial community aimed at studying the impact of Lactic Acid Bacteria (LAB) interactions and fitness on the formation of biogenic amines (BAs) in Chinese rice wine (CRW). The study reveals a close correlation between the assembly model of LAB and the accumulation of BAs in CRW, and multiple interactions were observed between amine-producing and non-amine-producing LAB, including commensalism, amensalism, and competition. The commensalism among amine-producing LAB was found to promote BAs accumulation through metabolic cross-feeding of amino acids. Moreover, the higher-order interaction community was designed to regulate the BAs formation effectively. For instance, the interference of Lactiplantibacillus plantarum (ACBC271) resulted in the elimination of amine-producing LAB viability, resulting in a 22% decrease (not exceeding 43.54 mg/L) in the total amount of BAs. Simulation of community dynamics models further suggests that LAB with quantitative social interactions can effectively control LAB accumulation in CRW by forecasting fluctuation in BAs generation through fitness competition and metabolic interference. Overall, this study provides valuable insights into the complex interaction networks within microbial communities in traditional fermentation ecosystems. It also proposes a novel approach for quality control of nitrogen food safety factors in fermented foods.

Kinetic modeling and experiments on removal of COD/nutrients from dairy effluent using chlorella and co-culture.

A sustainable and cost-effective approach of waste water management is biological treatment for reducing organic carbon, nitrate, and phosphate content. Co-culturing of algae with bacteria in wastewater leads to higher biomass yield and improvement in COD/nutrients removal compared to the single strain counterparts. In this study, a mathematical modeling framework is proposed to predict the dynamic behavior of microbial co-culture in dairy waste water. Initially, the model has been developed to predict the biomass growth and COD/nutrients removal with discrete cultures (algae and bacteria). As an extension of the single strain kinetic model, Lotka-Volterra model was formulated to explore the symbiotic relationship between algae and bacteria in a co-culture and the impact of the interactions on the COD/nutrients removal efficiency and growth dynamics. Supporting experiments were carried out in 6 parallel sets (3 sets with triplicates) with standalone algae (Chlorella vulgaris, CV), bacteria (activated sludge), and co-culture in real-time dairy liquid effluent in lab flasks and predicted values from modeling were validated against experimental findings. Statistical analysis confirms reasonably good agreement between the model predictions and experimental findings indicating a positive synergistic effect of the algae-bacterial co-culture on COD removal.

Microbial population dynamics decouple growth response from environmental nutrient concentration.

How the growth rate of a microbial population responds to the environmental availability of chemical nutrients and other resources is a fundamental question in microbiology. Models of this response, such as the widely used Monod model, are generally characterized by a maximum growth rate and a half-saturation concentration of the resource. What values should we expect for these half-saturation concentrations, and how should they depend on the environmental concentration of the resource? We survey growth response data across a wide range of organisms and resources. We find that the half-saturation concentrations vary across orders of magnitude, even for the same organism and resource. To explain this variation, we develop an evolutionary model to show that demographic fluctuations (genetic drift) can constrain the adaptation of half-saturation concentrations. We find that this effect fundamentally differs depending on the type of population dynamics: Populations undergoing periodic bottlenecks of fixed size will adapt their half-saturation concentrations in proportion to the environmental resource concentrations, but populations undergoing periodic dilutions of fixed size will evolve half-saturation concentrations that are largely decoupled from the environmental concentrations. Our model not only provides testable predictions for laboratory evolution experiments, but it also reveals how an evolved half-saturation concentration may not reflect the organism's environment. In particular, this explains how organisms in resource-rich environments can still evolve fast growth at low resource concentrations. Altogether, our results demonstrate the critical role of population dynamics in shaping fundamental ecological traits.

Biodegradation kinetics of binary mixture of hexadecane and phenanthrene by the bacterial microconsortium.

Crude oil bioremediation requires a correct selection of potential biodegraders to address the hazard. The present study investigates biodegradation kinetics of single aliphatic (Hexadecane, HEX), aromatic (Phenanthrene, PHE), and binary mixture (HEX + PHE) as co-contaminants by axenic cultures of A. fabrum SLAJ 731, B. subtilis RSL2 and P. aeruginosa P7815 and their consortium. A proposed integrated kinetic model combining first-order exponential decay and the Monod equation is well-fitted to degradation data. Maximum degradations of both the substrates were observed for microcosm, indicating synergistic effects of selected strains. The degradation rate indicated parallel utilization of HEX while serial utilization of PHE by selected strains. Maximum HEX and PHE degradations of 92.4 and 88.7 % were achieved by microconsortium, which increased to 97.2 and 91.9 % for the binary mixture. The biodegradation efficiencies of HEX and PHE were linearly correlated with Alkane hydroxylase and Catechol-2,3-dioxygenase activities, respectively.

Reaction kinetics of anodic biofilms under changing substrate concentrations: Uncovering shifts in Nernst-Monod curves via substrate pulses.

In the present study, it is shown that the concentration dependency of undefined mixed culture anodic biofilms does not follow a single kinetic curve, such as the Nernst-Monod curve. The biofilms adapt to concentration changes, which inevitably have to be applied to record kinetic curves, resulting in strong shifts of the kinetic parameters. The substrate concentration in a continuously operated bioelectrochemical system was changed rapidly via acetate pulses to record Nernst-Monod curves which are not influenced by biofilm adaptation processes. The values of the maximum current density j max and apparent half-saturation rate constant K s increased from 0.5 to 1 mA cm-2 and from 0.5 to 1.6 mmol L-1, respectively, within approximately 5 h. Double pulse experiments with a starvation phase between the two acetate pulses showed that j max and K s decrease reversibly through an adaptation process when no acetate is available. Pseudo-capacitive charge values estimated from non-turnover cyclic voltammograms (CV) led to the hypothesis that biofilm adaptation and the observed shift of the Nernst-Monod curves occurred due to changes in the concentration of active redox proteins in the biofilm. It is argued that concentration-related parameters of kinetic models for electroactive biofilms are only valid for the operating points where they have been determined and should always be reported with those conditions.

Machine learning aided experimental approach for evaluating the growth kinetics of Candida antarctica for lipase production.

A hybrid machine learning (ML) aided experimental approach was proposed in this study to evaluate the growth kinetics of Candida antarctica for lipase production. Different ML models were trained and optimized to predict the growth curves at various substrate concentrations. Results on comparison demonstrate the superior performance of the Gradient boosting regression (GBR) model in growth curves prediction. GBR-based growth kinetics was found to be matching well with the results of the conventional experimental approach while significantly reducing the experimental effort, time, and resources by âˆ¼ 50%. Further, the activity and enzyme kinetics of lipase produced in this study was investigated on hydrolysis of p-nitrophenyl butyrate resulting in a maximum lipase activity of 24.07 U at 44 h. The robustness and significance of developed kinetic models were ensured through detailed statistical analysis. The application of the proposed hybrid approach can be extended to any other microbial process.

Microalgal mediated antibiotic co-metabolism: Kinetics, transformation products and pathways.

The mutual interaction of a microalga Chlorella vulgaris with four antibiotics viz. sulfamethoxazole (SMX), trimethoprim (TMP), azithromycin (AZI), and levofloxacin (LEV) individually and in mixture was studied in batch culture. SMX, TMP, and LEV stimulated algal growth, while AZI inhibited its growth. The Combination Index (CI)-isobologram indicated antagonism of the antibiotic mixture on the growth of C. vulgaris. Higher removal efficiency was observed in the mixed antibiotic than in the single antibiotic batch cultures. Biodegradation was the main antibiotic removal mechanism with a similar antibiotic biosorption pattern in single and mix antibiotic cultures. Scanning electron microscopy and Fourier transform infrared spectrophotometry showed minor biochemical alterations on algal cells surface and a stable algal population. Monod kinetics model was successfully applied to understand the growth with respect to the removal efficiency of C. vulgaris in single and mix antibiotic batch cultures. Results indicated relatively higher specific growth rate in the mix antibiotic batch culture with removal efficiency in the order of SMX > LEV > TMP > AZI. In total, 46 metabolites with 18 novel ones of the four antibiotics were identified by using high-resolution mass spectrometry based on the suspect screening approach to propose the potential transformation pathways. Most of the transformation products demonstrated lower toxicity than their respective parents. These findings implied that C. vulgaris could be an outstanding candidate for advanced treatment of antibiotic removal in wastewater.

Co-digestion of palm oil mill effluent with chicken manure and crude glycerol: biochemical methane potential by monod kinetics.

In Thailand, the palm oil industry produces a huge amount of palm oil mill effluent (POME), mostly used for electricity generation through biogas production. Co-digestion with other waste can further improve biogas yield and solve waste management problems. Most previous studies relied on biochemical methane potential (BMP) assay or batch co-digestion to obtain the optimal mixing ratio, ignoring the kinetic part or treat it for sole discussion of the results. This work directly uses mechanistic models based on Monod kinetics to describe the experimental results obtained from the co-digestion of POME (40 ml, BMP = 281.2 mlCH4/gCODadded)) with chicken manure (CM) (0-50 g) and crude glycerol (Gly) (0-10 ml). The best mixing ratio between CM and POME was 5 gCM: 40 mlPOME (BMP = 276.9 mlCH4/gCODadded). The best ratio for Gly and POME was 2 mlGly: 40 mlPOME (BMP = 211.9 mlCH4/gCODadded). Adding Gly only 2 mlGly/40 mlPOME doubled the amount of biogas. Hence, crude glycerol is a good substrate for on-demand biogas output. The co-digestion increases the methane output but with a decreased yield. A multi-substrate Monod model was developed based on the levels of digestion difficulty. A partial-least squared fitting was used to estimate its main parameters. All parameters included in the model passed the significant tests at a 95% confidence level. The model can describe the experimental results very well, predict observable state variables of batch co-digestion, and allow a simple extension for continuous co-digestion dynamics. A limited continuous experiment was conducted to confirm the applicability of the model parameters of POME digestion obtained from BMP tests to predict a continuous AD. The results show good potential but must be carefully interpreted. It is generally possible and practical to directly obtain design and operational parameters from BMP assays based on only accumulated biogas curves and initial and final COD/VS.

Biodegradation of reactive yellow dye using mixed cells immobilized in different biocarriers by sequential anaerobic/aerobic biotreatment: experimental and modelling study.

In this study, the application of immobilized mixed cells for decolourization, biodegradation, and detoxification of reactive yellow dye (RY15) in textile wastewater was investigated via a sequential anaerobic-aerobic process in bench-scale bioreactors and lab-scale bioreactors as well. The mixed cultures were immobilized using three different biocarriers which were sodium alginate (SA), starch (St), and Gelatin (Ge), by the cross-linking with polyvinyl alcohol (PVA). Results revealed that the immobilized cultures had a potential degrading efficiency in the anaerobic and aerobic environment, targeting the initial structure and the formed compounds, respectively. Complete decolourization (100%) of RY15 was observed with a significant chemical oxygen demand (COD) removal, which enhanced the subsequent aerobic phase. Results demonstrated that COD removals were 92% ± 6.8, 96% ± 3.5, and 100%, using PVA-SA, PVA-St, and PVA-Ge at RY15 initial concentrations of 10 mg/L, respectively. The experimental work was extended to investigate the dye biodegradation in real textile wastewater using mixed cells in immobilized in PVA-SA. The Overloading rate (OLR) and Hydraulic retention time (HRT) of the aerobic bioreactor are 24.5 mg/L h and 41.37 h, respectively. The experimental profiles of RY concentration, COD reduction along with biomass growth, were in good agreement with the model predicted profiles. The effectiveness factors were 0.96 and 0.99 for the anaerobic and aerobic phases, respectively.

Denitrification performance of Pseudomonas fluorescens Z03 immobilized by graphene oxide-modified polyvinyl-alcohol and sodium alginate gel beads at low temperature.

Improving the effect of microbial denitrification under low-temperature conditions has been a popular focus of research in recent years. In this study, graphene oxide (GO)-modified polyvinyl-alcohol (PVA) and sodium alginate (SA) (GO/PVA-SA) gel beads were used as a heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria (Pseudomonas fluorescens Z03) carrier to enhance nitrogen removal efficiency levels at low temperatures (6-8°C). The removal efficiency of N H 4 + -N and N O 3 - -N and the variations in concentrations of extracellular polymeric substances (EPS) under different GO doses (0.03-0.15 g l-1) were studied. The results indicated that the addition of GO can improve the efficiency of nitrogen removal, and the highest removal efficiency level and highest carbohydrate, protein, and total EPS content levels (50.28 mg, 132.78 mg and 183.06 mg (g GO/PVA-SA gel)-1, respectively) were obtained with 0.15 g l-1 GO. The simplified Monod model accurately predicted the nitrogen removal efficiency level. These findings suggested that the application of GO serves as an effective means to enhance nitrogen removal by stimulating the activity of HN-AD bacteria.

Kinetics of biocathodic electron transfer in a bioelectrochemical system coupled with chemical absorption for NO removal.

A microbial electrolysis cell (MEC) has been developing for enhanced absorbent regeneration in a chemical absorption-biological reduction integrated process for NO removal. In this work, the kinetics of electron transfer involved in the biocathodes along Fe(III)EDTA and Fe(II)EDTA-NO reduction was analyzed simultaneously. A modified Nernst-Monod kinetics considering the Faraday efficiency was applied to describe the electron transfer kinetics of Fe(III)EDTA reduction. The effects of substrate concentration, biocathodic potential on current density predicted by the model have been validated by the experimental results. Furthermore, extended from the kinetics of Fe(III)EDTA reduction, the electron transfer kinetics of Fe(II)EDTA-NO reduction was developed with a semi-experimental method, while both direct electrochemical and bioelectrochemical processes were taken into consideration at the same time. It was revealed that the developed model could simulate the electron transfer kinetics well. This work could not only help advance the biocathodic reduction ability and the utilization efficiency of electric power, but also provide insights into the industrial scale-up and application of the system.

Kinetics simulation of Cu and Cd removal and the microbial community adaptation in a periphytic biofilm reactor.

Periphytic biofilm reactor (PBfR) shows great potential in pollutants removal. However, few studies were focused on mathematical model of pollutants removal in PBfR. A three-step PBfR was designed and a new model was developed to simulate the kinetics of Cu and Cd removal from simulated wastewater. The results show that the PBfR could remove 99.0% Cu and 99.7% Cd from liquid wastewater. The experiment data could be well fitted with a high correlation coefficients both for Cu and Cd. The microbial community in the PBfR could be self-adjusted to tolerate the toxicities of Cu and Cd, resulting in sustainable and high decontamination efficiencies. The eukaryote in the PBfR played a vital role in Cu and Cd removal. The prokaryote showed negative effect on Cu and Cd removal, though it had more diversity than eukaryote. This study provides a new approach for Cu and Cd removal and their kinetics simulation in photoautotrophic bioreactor.

Effect of process parameters on enhanced biohydrogen production from tequila vinasse via the lactate-acetate pathway.

In this study, a lactate-type fermentation entailing the consumption of lactate and acetate (lactate-acetate pathway) is proposed to deal with lactic acid bacteria (LAB) inhibition during the production of biohydrogen (bioH2) from tequila vinasse. The effects of total solids content, substrate concentration, nutrient formulation and inoculum addition on bioH2 production performance were investigated. Batch experiments were performed in a 3-L completely mixed reactor at 35 °C and pH 6.5-5.8. The lactate-acetate pathway mediated consistent bioH2 production which was influenced by inoculum addition followed by substrate concentration, nutrient formulation and solids content. Maximum bioH2 production rate (225 NmL/L-h) and yield (124 NmL/g VSadded) were achieved by removing suspended solids and enhancing nutrient content, respectively. Illumina sequencing-based analysis revealed a dominance of Clostridium in the inoculum, which together with LAB and acetic acid bacteria shaped a keystone cluster for avoiding LAB inhibition while ensuring consistent bioH2 production performance.

Growth, substrate consumption, and product formation kinetics of Phanerochaete chrysosporium and Schizophyllum commune mixed culture under solid-state fermentation of fruit peels.

Kinetic analysis of solid-state fermentation (SSF) of fruit peels with Phanerochaete chrysosporium and Schizophyllum commune mixed culture was studied in flask and 7 kg capacity reactor. Modified Monod kinetic model suggested by Haldane sufficiently described microbial growth with co-efficient of determination (R 2) reaching 0.908 at increased substrate concentration than the classical Monod model (R 2 = 0.932). Leudeking-Piret model adequately described product synthesis in non-growth-dependent manner (R 2 = 0.989), while substrate consumption by P. chrysosporium and S. commune fungal mixed culture was growth-dependent (R 2 = 0.938). Hanes-Woolf model sufficiently represented α-amylase and cellulase enzymes synthesis (R 2 = 0.911 and 0.988); α-amylase had enzyme maximum velocity (V max) of 25.19 IU/gds/day and rate constant (K m) of 11.55 IU/gds/day, while cellulase enzyme had V max of 3.05 IU/gds/day and K m of 57.47 IU/gds/day. Product yield in the reactor increased to 32.65 mg/g/day compared with 28.15 mg/g/day in shake flask. 2.5 cm media thickness was adequate for product formation within a 6 day SSF in the tray reactor.

Biohydrogen production under hyper salinity stress by an anaerobic sequencing batch reactor with mixed culture.

BACKGROUND: This study investigated the effect of organic loading rate (OLR) and NaCl concentration on biohydrogen production by preheated anaerobic sludge in a lab scale anaerobic sequencing batch reactor (ASBR) fed with glucose during long time operation. METHODS: During ASBR operation, the OLR was increased in steps from 0.5 to 5 g glucose/L.d and NaCl addition started at an OLR of 5 g glucose/L.d, to obtain NaCl concentrations in the reactor in the range of 0.5-30 g/L. RESULTS: With an increasing OLR from 0.5 to 5 g glucose/L.d, the biohydrogen yield increased and reached 0.8 ± 0.4 mol H2/mol glucose at an OLR of 5 g glucose/L.d. A NaCl concentration of 0.5 g/L resulted in a higher yield of biohydrogen (1.1 ± 0.2 mol H2/mol glucose). Concentrations above 0.5 g/L NaCl led to decreasing biohydrogen yield and the lowest yield (0.3 ± 0.1 mol H2/mol glucose) was obtained at 30 g/L of NaCl. The mass balance errors for C, H, and O in all constructed stoichiometric reactions were below 5%. CONCLUSIONS: The modified Monod model indicated that r (H2)max and Ccrit values were 23.3 mL H2/g VSS/h and 119.9 g/L, respectively. Additionally, ASBR operation at high concentrations of NaCl shifted the metabolic pathway from acidogenic toward solventogenic.

Kinetic parameter estimation model for anaerobic co-digestion of waste activated sludge and microalgae.

Anaerobic co-digestion has a potential to improve biogas production, but limited kinetic information is available for co-digestion. This study introduced regression-based models to estimate the kinetic parameters for the co-digestion of microalgae and Waste Activated Sludge (WAS). The models were developed using the ratios of co-substrates and the kinetic parameters for the single substrate as indicators. The models were applied to the modified first-order kinetics and Monod model to determine the rate of hydrolysis and methanogenesis for the co-digestion. The results showed that the model using a hyperbola function was better for the estimation of the first-order kinetic coefficients, while the model using inverse tangent function closely estimated the Monod kinetic parameters. The models can be used for estimating kinetic parameters for not only microalgae-WAS co-digestion but also other substrates' co-digestion such as microalgae-swine manure and WAS-aquatic plants.

Competition and coexistence between a syntrophic consortium and a metabolic generalist, and its effect on productivity.

Syntrophic interactions, where species consume metabolites excreted by others, are common in microbial communities, and have uses in synthetic biology. Syntrophy is likely to arise when trade-offs favor an organism that specializes on particular metabolites, rather than all possible metabolites. Several trade-offs have been suggested; however, few models consider different trade-offs to test which are most consistent with observed patterns. Here, we develop a differential equation model to study competition between a syntrophic processing chain, where each microbe can perform one step in metabolizing an initial resource to a final state, and a metabolic generalist that can perform all metabolic functions. We also examine how competition affects the production of the final metabolic compound. We find that competitive outcomes can be predicted by a generalization of the R(⁎)-rule and relative nonlinearity. Therefore, the species that can persist at the lowest resource level is the competitive dominant in a constant environment, and species can coexist by partitioning variation in resources. We derive a simple rule for predicting production rates of the final metabolite, and show that competition may not maximize final metabolite production. We show that processing chains are inherently less efficient, because resources are lost during each step of the process. Our results also suggest which trade-offs are capable of explaining certain empirical observations. For example, processing chains appear to be more common in nutrient-rich environments; our model suggests that a specificity trade-off and an affinity-yield trade-off would not predict this, but a yield-maximum growth trade-off might.

Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality.

In the present work, a generalization of the classical model of Monod accounting the influence of both delayed and instant mortalities on the dynamics of the micro-organism population is proposed. The model was analysed and compared with respect to its quality and applicability for simulation of the cultivation process of micro-organisms. Existence of a unique global positive solution of the Cauchy problem for the proposed model is proved and explicit relations between the decay parameters and the nutrition substrate concentration are obtained. These mathematical results allow us to calculate the nutrient substrate concentration which guarantees that the biomass concentration is maximal for every specific type of taxonomic groups of micro-organisms (bacteria, yeasts).

Combined treatment of olive mill wastewater by Fenton's reagent and anaerobic biological process.

This work presents the application of Fenton's reagent process combined with anaerobic digestion to treat an olive mill wastewater (OMW). Firstly, OMW was pre-treated by chemical oxidation in a batch reactor with Fenton's reagent, using a fixed H2O2/COD ratio of 0.20, pH = 3.5 and a H2O2/Fe(2+) molar ratio of 15:1. This advanced oxidation treatment allowed reaching reductions of 17.6 and 82.5% of chemical oxygen demand (COD) and total polyphenols (TP), respectively. Secondly, OMW treatment by anaerobic digestion was performed using previously adapted microorganisms immobilized in Sepiolite. These biological tests were carried out varying the substrate concentration supplied to the reactor and COD conversions from 52 to 74% were obtained. Afterwards, Fenton's reagent followed by anaerobic digestion was applied to OMW treatment. This combined process presented a significant improvement on organic load removal, reaching COD degradations from 64 to 88%. Beyond the pollutant load removal, it was also monitored the yield of methane generated throughout anaerobic experiments. The methane produced ranged from 281 cm(3) to 322 cm(3) of CH4/g COD removed. Additionally, a methane generation kinetic study was performed using the Monod Model. The application of this model allowed observing a kinetic constant increase of the combined process (kFN = 0.036 h(-1)) when compared to the single anaerobic process (kF = 0.017 h(-1)).