Search

Volatile organic compounds (VOCs) pose significant risks to human health and environmental quality, prompting stringent regulations on their emissions from various industrial processes. Among VOCs, d-limonene stands out due to its low threshold and contribution to malodorous emissions. While biofiltration presents a promising approach for VOC removal, including d-limonene, a comprehensive understanding of its performance and kinetics is lacking. This study aims to comprehensively assess the performance of a lab-scale biotrickling filter in treating gas-phase d-limonene. The experimental results indicate that the biotrickling filter efficiently removed d-limonene, achieving a critical loading rate of 19.4 g m−3 h−1 and a maximum elimination capacity of 31.8 g m−3 h−1 (correspondingly, up to 85% removal) at the condition of 94.2 s of EBRT. Microbial activity played a significant role in biotrickling filter performance, with a strong linear correlation being observed between CO2 production and substrate consumption. The Michaelis–Menten model was employed to represent enzyme-catalyzed reactions, suggesting no inhibition during biotrickling filter operation. [ABSTRACT FROM AUTHOR]

Strategy to improve single-stage photofermentative hydrogen productivity of photosynthetic bacteria (PSB) by efficient use a formulated lignocellulosic substrate through suitable supplement of iron and molybdenum as enhancers of microbial activity of R. palustris was proposed. The maximum hydrogen production rate of 48.1 ml h−1 L−1 was obtained using response surface methodology as the result of accelerated bioreaction of proton reduction under inoculum density of 118.1 mg L−1, Fe2+ of 13.2 mg L−1 and Mo6+ of 2.65 μg L−1. Biokinetic analysis revealed the enhanced microbial activities in biomass synthesis and H 2 production. Suitable metal addition enabled PSB to act in whole as biocatalyst to facilitate assimilation of the formulated electron-rich carbon source from wheat straw through the efficient electron transfer needed for both cell growth and enzyme function of nitrogenase. Therefore, higher kinetic values of k c in 0.146 h−1 and R m in 59.4 ml h−1 L−1, accompanied with improved performances of H 2 yield in 1.56 mol mol−1 carbon and substrate degradation in 93.6% were attained. [Display omitted] • Enhancement strategy of lignocellulosic photofermentation was developed. • A higher production rate of 48.1 ml H 2 h−1 l−1 from wheat straw was attained by R. palustris. • Synergistic effect of metal Fe and Mo addition stimulated nitrogenase-catalyzed H 2 reaction. [ABSTRACT FROM AUTHOR]

Enhancement strategies of single-stage photofermentative hydrogen production from lignocellulosic residue by photosynthetic bacteria (PSB) were explored in this study. Hydrogen production rate (HPR) within batch operated bioreactor was observed to be improved through optimal control of the three key process parameters, which affected cellular hydrogen generation by nitrogenase mediated biochemical reaction. The maximum value of 25.6 ± 0.3 mL h−1 L−1 in HPR was thus obtained under the optimized operating conditions of 42 mM initial carbon substrate concentration, 0.38 mmol mg−1 initial substrate-inoculum ratio as well as intensity of 14.96 W m−2 at 590 nm light wavelength. Furthermore, studies on microbial kinetics of this optimized photofermentation process revealed a positive microenvironment around PSB cells can be established, which enabled microorganisms to maintain mutiple cellular activity for their efficient bioconversion of lignocellulosic carbon source into cell materials and hydrogen, so a higher value of kc in 0.139 h−1 and Rm in 34.2 mL h−1 L−1 can be attained. [ABSTRACT FROM AUTHOR]

In stratified lakes, methane oxidizing bacteria are critical methane converters that significantly reduce emissions of this greenhouse gas to the atmosphere. Efforts to better understand their ecology uncovered a surprising diversity, vertical structure, and seasonal succession. It is an open question how this diversity has to be considered in models of microbial methane oxidation. Likewise, it is unclear to what extent simple microbial traits related to the kinetics of the oxidation process and temperature optimum, suggested by previous studies, suffice to understand the observed ecology of methane oxidizing bacteria. Here we incorporate niche partitioning in a mechanistic model of seasonal lake mixing and microbial methane oxidation in a stratified lake. Can we model MOB diversity and niche partitioning based on differences in methane oxidation kinetics and temperature adaptation? We found that our model approach can closely reproduce diversity and niche preference patterns of methanotrophs that were observed in seasonally stratified lakes. We show that the combination of trait values resulting in coexisting methanotroph communities is limited to very confined regions within the parameter space of potential trait combinations. However, our model also indicates that the sequence of community assembly, and variations in the stratification and mixing behavior of the lake result in different stable combinations. A scenario analysis introducing variable mixing conditions showed that annual weather conditions and the pre-existing species also affect the developing stable methanotrophic species composition of the lake. Both, effect of pre-existing species and the environmental impact suggest that the MOB community in lakes may differ from year to year, and a stable community may never truly occur. The model further shows that there are always better-adapted species in the trait parameter space that would destabilize and replace an existing stable community. Thus, natural selection may drive trait values into the specific configurations observed in nature based on physiological limits and tradeoffs between traits.

ABSTRACT The Monod equation has been widely applied as the general rate law of microbial growth, but its applications are not always successful. By drawing on the frameworks of kinetic and stoichiometric metabolic models and metabolic control analysis, the modeling reported here simulated the growth kinetics of a methanogenic microorganism and illustrated that different enzymes and metabolites control growth rate to various extents and that their controls peak at either very low, intermediate, or very high substrate concentrations. In comparison, with a single term and two parameters, the Monod equation only approximately accounts for the controls of rate-determining enzymes and metabolites at very high and very low substrate concentrations, but neglects the enzymes and metabolites whose controls are most notable at intermediate concentrations. These findings support a limited link between the Monod equation and methanogen growth, and unify the competing views regarding enzyme roles in shaping growth kinetics. The results also preclude a mechanistic derivation of the Monod equation from methanogen metabolic networks and highlight a fundamental challenge in microbiology: single-term expressions may not be sufficient for accurate prediction of microbial growth. IMPORTANCE The Monod equation has been widely applied to predict the rate of microbial growth, but its application is not always successful. Using a novel metabolic modeling approach, we simulated the growth of a methanogen and uncovered a limited mechanistic link between the Monod equation and the methanogen’s metabolic network. Specifically, the equation provides an approximation to the controls by rate-determining metabolites and enzymes at very low and very high substrate concentrations, but it is missing the remaining enzymes and metabolites whose controls are most notable at intermediate concentrations. These results support the Monod equation as a useful approximation of growth rates and highlight a fundamental challenge in microbial kinetics: single-term rate expressions may not be sufficient for accurate prediction of microbial growth.

Chemotrophic microorganisms face the steep challenge of limited energy resources in natural environments. This observation has important implications for interpreting and modeling the kinetics and thermodynamics of microbial reactions. Current modeling frameworks treat microbes as autocatalysts, and simulate microbial energy conservation and growth with fixed kinetic and thermodynamic parameters. However, microbes are capable of acclimating to the environment and modulating their parameters in order to gain competitive fitness. Here we constructed an optimization model and described microbes as self-adapting catalysts by linking microbial parameters to intracellular metabolic resources. From the optimization results, we related microbial parameters to the substrate concentration and the energy available in the environment, and simplified the relationship between the kinetics and the thermodynamics of microbial reactions. We took as examples Methanosarcina and Methanosaeta – the methanogens that produce methane from acetate – and showed how the acclimation model extrapolated laboratory observations to natural environments and improved the simulation of methanogenesis and the dominance of Methanosaeta over Methanosarcina in lake sediments. These results highlight the importance of physiological acclimation in shaping the kinetics and thermodynamics of microbial reactions and in determining the outcome of microbial interactions.

Up to now, computational modeling of microbial electrosynthesis (MES) has been underexplored, but is necessary to achieve breakthrough understanding of the process-limiting steps. Here, a general framework for modeling microbial kinetics in a MES reactor is presented. A thermodynamic approach is used to link microbial metabolism to the electrochemical reduction of an intracellular mediator, allowing to predict cellular growth and current consumption. The model accounts for CO2 reduction to acetate, and further elongation to n-butyrate and n-caproate. Simulation results were compared with experimental data obtained from different sources and proved the model is able to successfully describe microbial kinetics (growth, chain elongation, and product inhibition) and reactor performance (current density, organics titer). The capacity of the model to simulate different system configurations is also shown. Model results suggest CO2 dissolved concentration might be limiting existing MES systems, and highlight the importance of the delivery method utilized to supply it. Simulation results also indicate that for biofilm-driven reactors, continuous mode significantly enhances microbial growth and might allow denser biofilms to be formed and higher current densities to be achieved.

The Q10 coefficient is the ratio of reaction rates at two temperatures 10°C apart, and has been widely applied to quantify the temperature sensitivity of organic matter decomposition. However, biogeochemists and ecologists have long recognized that a constant Q10 coefficient does not describe the temperature sensitivity of organic matter decomposition accurately. To examine the consequences of the constant Q10 assumption, we built a biogeochemical reaction model to simulate anaerobic organic matter decomposition in peatlands in the Upper Peninsula of Michigan, USA, and compared the simulation results to the predictions with Q10 coefficients. By accounting for the reactions of extracellular enzymes, mesophilic fermenting and methanogenic microbes, and their temperature responses, the biogeochemical reaction model reproduces the observations of previous laboratory incubation experiments, including the temporal variations in the concentrations of dissolved organic carbon, acetate, dihydrogen, carbon dioxide, and methane, and confirms that fermentation limits the progress of anaerobic organic matter decomposition. The modeling results illustrate the oversimplification inherent in the constant Q10 assumption and how the assumption undermines the kinetic prediction of anaerobic organic matter decomposition. In particular, the model predicts that between 5°C and 30°C, the decomposition rate increases almost linearly with increasing temperature, which stands in sharp contrast to the exponential relationship given by the Q10 coefficient. As a result, the constant Q10 approach tends to underestimate the rates of organic matter decomposition within the temperature ranges where Q10 values are determined, and overestimate the rates outside the temperature ranges. The results also show how biogeochemical reaction modeling, combined with laboratory experiments, can help uncover the temperature sensitivity of organic matter decomposition arising from underlying catalytic mechanisms. Plain Language Summary: The Q10 coefficient is a key parameter for quantifying the temperature sensitivity of organic matter decomposition. Most modeling studies fix the Q10 coefficient at a constant of 1.5 or 2, assuming that decomposition rates increase by a factor of 1.5 or 2 per 10°C increase, respectively. However, the Q10 coefficients obtained from laboratory and field experiments are not constant, varying from less than 2 to over 300. We evaluated the constant Q10 approach by simulating anaerobic organic matter decomposition in peatlands in the Upper Peninsula of Michigan, USA. Our biogeochemical reaction model was constructed and validated on the basis of previous laboratory incubation experiments, and accounts for the reactions of extracellular enzymes, mesophilic fermenting and methanogenic microbes, and their temperature responses. The modeling results show that organic matter decomposition responds almost linearly to temperature variations between 5°C and 30°C, and the resulting Q10 coefficients decrease from >400 around 0°C to close to 1 at 30°C. These results challenge Q10 coefficient as an effective parameter for studying organic matter decomposition, and suggest that biogeochemical reaction modeling, combined with laboratory experiments, can be applied to discover the temperature responses of decomposition arising from underlying enzymatic and microbial reaction mechanisms. Key Points: Built a biogeochemical reaction model to predict the rate response of anaerobic organic matter decomposition to temperature variationsDecomposition rate increases almost linearly with temperature from 5°C to 30°C, which contradicts the exponential relationship of Q10 approachQ10 coefficient of anaerobic organic matter decomposition decreases from >400 at around 0°C to near 1 at 30°C [ABSTRACT FROM AUTHOR]

Up to now, computational modeling of microbial electrosynthesis (MES) has been underexplored, but is necessary to achieve breakthrough understanding of the process-limiting steps. Here, a general framework for modeling microbial kinetics in a MES reactor is presented. A thermodynamic approach is used to link microbial metabolism to the electrochemical reduction of an intracellular mediator, allowing to predict cellular growth and current consumption. The model accounts for CO2 reduction to acetate, and further elongation to n-butyrate and n-caproate. Simulation results were compared with experimental data obtained from different sources and proved the model is able to successfully describe microbial kinetics (growth, chain elongation, and product inhibition) and reactor performance (current density, organics titer). The capacity of the model to simulate different system configurations is also shown. Model results suggest CO2 dissolved concentration might be limiting existing MES systems, and highlight the importance of the delivery method utilized to supply it. Simulation results also indicate that for biofilm-driven reactors, continuous mode significantly enhances microbial growth and might allow denser biofilms to be formed and higher current densities to be achieved. [ABSTRACT FROM AUTHOR]

Activated sludge processes with an ultra-short sludge retention time (ultra-short-SRT) are considered to have potential for energy and resource recovery from wastewater. The present study focused on the sludge characteristics, system performance and microbial kinetics in ultra-short-SRT activated sludge (USSAS) processes using typical domestic wastewater (SRT = 0.5, 1, 2, 3 and 4 d). The results showed that compared with the sludge in conventional activated sludge (CAS) processes, the sludge structure in USSAS system was looser (fractal dimension, D2P, 1.19–1.33), the boundary was rougher (pore boundary fractal dimension, DB, 1.44–1.59), the sludge concentration was lower, and the sludge volume index (SVI) was higher; bacteria such as Thiothrix and Trichococcus that cause sludge bulking, which poses an operation risk, were extensively detected, especially at SRTs of 0.5 d and 1.0 d. The performance in terms of total chemical oxygen demand (tCOD) and phosphorus removal increased with increasing SRT, and the highest removal rate (approximately 85% for tCOD and 90% for phosphorus) was observed when the SRT was 4 d. Both bioconversion and biosorption were responsible for the C/P separation, and their roles were different for different types of organic matter and phosphorus under different SRT conditions. The proportion of phosphate-accumulating organisms (PAO) reached 2.4% when the SRT was 3 d, resulting in highly effective biological phosphorus removal. The values of microbial kinetic parameters such as YH and KdH in USSAS systems were higher than those in CAS systems, indicating faster microbial community renewal. This study was helpful for understanding the characteristics of USSAS process.

This work reports a comparison study between an intelligent aeration-controlled Anoxic/Oxic system and a conventional continuing aeration Anoxic/Oxic system for the removal of major containment, which includes the performance of major containments treatment, microbial kinetics and microbial communities by high-throughput sequencing tool. The results showed that at the end of low dissolved oxygen start-up period, there was few differences on the performance between the intelligent aeration-controlled Anoxic/Oxic system, with a 60% aeration saving, and conventional continuing aeration Anoxic/Oxic system. Moreover, the differences of activated sludge microbial community were significant. The kinetics study shows that the microbial kinetics for the intelligent aeration-controlled Anoxic/Oxic system was faster than for the comparison system, especially the yield coefficient for autotrophic biomass was much higher. The high-throughput sequencing tool also have provided a reasonable comparison of microbial community in aeration tank and indicated that the low dissolved oxygen demand species were more abundant. Meanwhile, the functional relative abundance had little statistical differences. However, the more abundance of low dissolved oxygen demand species gradually represented function of the less abundance species in the end of the start-up process. This study can provide a helpful information in the intelligent aeration-controlled Anoxic/Oxic system optimization to further removal the specific contaminates in the domestic wastewater treatment. [ABSTRACT FROM AUTHOR]

Abstract Cellulose utilization by hydrogen producers remains an issue due to the low hydrogen yields reported and the pretreatment of cellulose prior to fermentation requires complex and expensive steps. Clostridium termitidis is able to breakdown cellulose into glucose and produce hydrogen. On the other hand, Clostridium beijerinckii is not able to degrade cellulose but is adept at hydrogen production from glucose; therefore, it was chosen to potentially enhance hydrogen production when co-cultured with C. termitidis on cellulose. In this study, batch fermentation tests were conducted to investigate the direct hydrogen production enhancement of mesophilic cellulolytic bacteria C. termitidis co-cultured with mesophilic hydrogen producer C. beijerinckii on cellulose at 2 g l−1 compared to C. termitidis mono-culture. Microbial kinetics parameters were determined by modeling in MATLAB. The achieved highest hydrogen yield was 1.92 mol hydrogen mol−1 hexose equivalentadded in the co-culture compared to 1.45 mol hydrogen mol−1 hexose equivalentadded in the mono-culture. The maximum hydrogen production rate of 26 ml d−1 was achieved in the co-culture. Co-culture exhibited an overall 32 % enhancement of hydrogen yield based on hexose equivalent added and 15 % more substrate utilization. The main metabolites were acetate, ethanol, lactate, and formate in the mono-culture, with also butyrate in the co-culture. Additionally, the hydrogen yield of C. beijerinckii only in glucose was 2.54 mol hydrogen mol−1 hexose equivalent. This study has proved the viability of co-culture of C. termitidis with C. beijerinckii for hydrogen production directly from a complex substrate like cellulose under mesophilic conditions.

BACKGROUND: A membrane bioreactor and two hybrid moving bed biofilm reactor‐membrane bioreactor systems were operated in parallel for the treatment of variable‐salinity wastewater. Influent salinity was changed according to tidal‐like cycles: 6 h of maximum salinity (4.5 or 8.5 mS cm−1) followed by 6 h of regular wastewater salinity (around 1 mS cm−1). RESULTS: For the two salinity scenarios, the bioprocesses operated under different conditions of mixed liquor total suspended solids (2500 and 3500 mg L−1), and hydraulic retention time (6, 9.5 and 12 h). The results showed that the bioprocesses had better performance under 4.5 mS cm−1 than under 8.5 mS cm−1 in terms of removal of biological oxygen demand at day 5 (BOD5) (+6.07%), ammonium cation (NH4+) (+41.29%) and total nitrogen (+37.64%), the heterotrophic and autotrophic yield coefficients (+0.02777 mgVSS mgCOD−1 and +0.13990 mgVSS mgN−1), and the autotrophic rate of substrate utilization (+3.39559 mgN L−1 h−1). CONCLUSIONS: The results obtained would become of help for the modeling of membrane‐based systems treating variable saline wastewater. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

In this study, a low-cost, efficient, and environmentally friendly anaerobic sludge process for the treatment of industrial beverage wastewater was investigated to analyze the effect of bacteria growth on the degradation of organic matter (chemical oxygen demand). Additionally, the mechanism, interactions between the microbe’s growth, and operating conditions of an anaerobic batch reactor along with the wastewater treatment efficiency were evaluated via microbial kinetics. The kinetic coefficients based on chemical oxygen demand (COD) by conventional techniques such as kinetic coefficients growth yield (0.46 mg VSS/mg COD), saturation coefficient (3500 mg/L COD), the maximum rate of substrate utilization per unit mass of biomass (0.0066 mg/L COD), growth rate by Monod equation, M (0.03833 L/h), and maximum growth rate, μm (0.03672 L/h) were calculated. The results show a higher rate of substrate degradation (0.54 day−1) due to the high COD removal efficiency (CRE) of 99.31% during 13 days that was achieved, which can be attributed to the active involvement of anaerobic microbes in the process of degradation. Based on these results, it can be concluded that the current study can be used as an effective way to analyze the industrial beverage wastewater at commercial levels.

The microbial enhanced oil recovery (MEOR) method is an eco-friendly and economical alternative technology. The technology involves a variety of uncertainties, and its success depends on controlling microbial growth and metabolism. Though a few numerical studies have been carried out to reduce the uncertainties, no attempt has been made to consider temperature, pressure, and salinity in an integrated manner. In this study, a new modeling method incorporating these environmental impacts was proposed, and MEOR analysis was performed. As a result, accurate modeling was possible to prevent overestimating the performance of MEOR. In addition, oil recovery was maximized through sensitivity analysis and optimization based on an integrative model. Finally, applying MEOR to an actual reservoir model showed a 7% increase in oil recovery compared to waterflooding. This result proved the practical applicability of the method.

In a companion paper, we examined the thermodynamic responses of microbial redox reactions to pH changes. Here we explore how these thermodynamic responses may affect the composition and function of microbial communities. We simulate butyrate syntrophic oxidation, sulfate reduction, and methanogenesis by microbial consortia at pH ranging from 7 to 5. The simulation accounts for the thermodynamics of microbial metabolisms and the interactions among microbes. The results show that thermodynamic responses to variation in pH can be strong enough to speed up or slow down microbial metabolisms. These kinetic changes then shape the outcome of microbial interactions, including the membership and activity of microbial consortia. Moreover, the kinetic changes modulate carbon fluxes and the efficiency of methane production. The simulation results support the hypothesis that environmental pH can shape the composition and metabolic function of microbial communities by changing the energy yields of redox reactions. They also add to the current theories of microbial ecology. Specifically, due to pH-induced thermodynamic responses, the principle of competitive exclusion fails for microbial processes with significant thermodynamic limitations, which allows the co-occurrence of competing respiration reactions in natural environments. Taken together, these results confirm that pH is a primary control in environmental microbiology. They also highlight the feasibility and potential of biogeochemical kinetic modeling in uncovering and illuminating mechanistic relationships between environmental parameters and microbial communities.

pH influences the occurrence and distribution of microorganisms. Microbes typically live over a range of 3–4 pH units and are described as acidophiles, neutrophiles, and alkaliphiles, depending on the optimal pH for growth. Their growth rates vary with pH along bell- or triangle-shaped curves, which reflect pH limits of cell structural integrity and the interference of pH with cell metabolism. We propose that pH can also affect the thermodynamics and kinetics of microbial respiration, which then help shape the composition and function of microbial communities. Here we use geochemical reaction modeling to examine how environmental pH controls the energy yields of common redox reactions in anoxic environments, including syntrophic oxidation, iron reduction, sulfate reduction, and methanogenesis. The results reveal that environmental pH changes energy yields both directly and indirectly. The direct change applies to reactions that consume or produce protons whereas the indirect effect, which applies to all redox reactions, comes from the regulation of chemical speciation by pH. The results also show that energy yields respond strongly to pH variation, which may modulate microbial interactions and help give rise to the pH limits of microbial metabolisms. These results underscore the importance of pH as a control on microbial metabolisms and provide insight into potential impacts of pH variation on the composition and activity of microbial communities. In a companion paper, we continue to explore how the kinetics of microbial metabolisms responds to pH variations, and how these responses control the outcome of microbial interactions, including the activity and membership of microbial consortia.

Abstract We propose a new method to predict microbial metabolic rates in natural environments using genome-scale metabolic models. This method is a hybrid of existing approaches, i.e., rate laws and flux balance analysis (FBA). It accounts for the availabilities of chemical energy and growth nutrients in the environment, and applies FBA independently to the respiration and biosynthesis pathways of genome-scale metabolic models. We illustrate the new method by modeling the metabolism of a representative methanogen – Methanosarcina barkeri – in laboratory reactors and in pristine and biostimulated aquifers. The laboratory application demonstrates that the hybrid method predicts the rates of individual biochemical reactions within overall cell metabolism and tracks, explicitly, cellular fluxes of carbon and energy. The aquifer applications reveal that the growth of methanogens in natural systems can be limited by multiple factors, including energy sources and growth nutrients, and that the limitations are subject to Liebig's Law of the Minimum. These results highlight the improvements of the new method in biogeochemical reaction modeling, including its applicability to diverse environments, from eutrophic to oligotrophic. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Chain elongation is a promising mixed culture bioprocess to convert acetate into medium chain carboxylates with ethanol as an electron donor. Caproate production using lignocellulosic ethanol (LE) as feedstock via chain elongation fermentation was examined in this study. Meanwhile, the effects of yeast extract and cellulose containing in the LE were investigated separately. Fermentation performance showed that the lag phase of caproate production were shortened in experimental group LE (4 days), yeast extract (6 days), and cellulose (9 days) compared with the control group (17 days) without extra supplement. The insufficiency of electron donor, ethanol, limited further elongation into caproate, resulting in comparable caproate yields and carbon conversion ratios in four experimental groups. Microbial community and microbial kinetics analysis revealed that yeast extract could be metabolized by protein-utilizing bacteria into short chain carboxylates (SCCs), which facilitated biological chain elongation. Meanwhile, yeast extract boosted microbial growth by serving as nitrogen and other nutrient sources. Furthermore, cellulose was utilized and further converted into SCCs, or even caproate, by cellulolytic bacteria. Together, caproate production was enhanced with high microbial activities and intermediates formation using LE. This study upgrades LE into a higher energy density product, caproate, via the energy-efficient chain elongation fermentation. Graphical abstract Image 1 Highlights • Lag phase of caproate formation was shortened by 13 d with lignocellulosic ethanol. • Insufficiency of ethanol limited further elongation of butyrate into caproate. • Lignocellulosic ethanol as feedstock enriched the microbial community. • Cellulose and yeast extract shortened the lag phase of caproate production. • Yeast extract boosted bacterial growth thus improving fermentation performance. [ABSTRACT FROM AUTHOR]

In this work, mathematical modeling of ethanol production in solid-state fermentation (SSF) has been done based on the variation in the dry weight of solid medium. This method was previously used for mathematical modeling of enzyme production; however, the model should be modified to predict the production of a volatile compound like ethanol. The experimental results of bioethanol production from the mixture of carob pods and wheat bran by Zymomonas mobilis in SSF were used for the model validation. Exponential and logistic kinetic models were used for modeling the growth of microorganism. In both cases, the model predictions matched well with the experimental results during the exponential growth phase, indicating the good ability of solid medium weight variation method for modeling a volatile product formation in solid-state fermentation. In addition, using logistic model, better predictions were obtained. [ABSTRACT FROM AUTHOR]

A membrane bioreactor and two hybrid moving bed biofilm reactor-membrane bioreactor systems were operated for the treatment of wastewater with tidal salinity fluctuations under hydraulic retention times of 6, 9.5 and 12 h, and operational solids concentrations of around 2500 and 3500 mg L −1 . The three configurations were studied in terms of carbon and nitrogen removal, heterotrophic and autotrophic kinetics, and bacterial community structure. The performance of the systems was good in terms of organic matter removal – between 85–100% and 95–100% for COD and BOD 5 , respectively, showing higher efficiencies at higher solids concentration and hydraulic retention times. Nitrogen removal obtained was in the range of 30–50%. The bacterial community structure of the suspended and attached biomass in the systems was more influenced by the operational solids (80% clustering cutoff) and hydraulic retention time (60% clustering cutoff) than by technological configuration (40% clustering cutoff), as determined by ordination analyses. Massive parallel sequencing showed the presence of Nitrobacter and Rhodanobacter at almost all operation scenarios, and thus were identified as major players in treatment of tidal salinity variation wastewater. Overall, this research proved that the MBR and hybrid MBBR-MBR systems could successfully treat urban wastewater subjected to tidal salinity variations. Nevertheless, more research is needed in order to enhance nitrogen removal performance under these conditions. [ABSTRACT FROM AUTHOR]

Kinetic modeling of microbial reactions is a common tool for addressing the central environmental questions of our time, from contaminant remediation to the global carbon cycle. This review presents an overview of trait-based frameworks for modeling the kinetics of microbial reactions, with an emphasis on environmental application. I first highlight two key model assumptions: the simplification of microbial communities as ensembles of microbial functional groups and the description of microbial metabolism at a coarse-grained level with three metabolic reactions – catabolic reaction, biomass synthesis, and maintenance. Next, I aim to establish a connection between microbial rate laws and the mechanisms of metabolic reactions. For metabolic reactions limited by single substrates, the widely used rate law is the Monod equation. However, in cases where substrates are solids or nonaqueous phase liquids (NAPLs), the Contois equation and the Best equation may offer better alternatives. In microbial metabolisms limited by multiple nutrients simultaneously, two competing rate laws exist: the multiplicative rate law and Liebig's law of the minimum. Then I present two strategies for extending the modeling framework developed for laboratory cultures to natural environments. One strategy follows the multiplicative rate law and incorporates dimensionless functions to account for pH, temperature, salinity, cell density, and other environmental conditions. The other strategy focuses on the physiology of natural microbes, explicitly considering dormancy, biomass decay, and physiological acclimation. After that, I highlight recent improvements enabled by the application of molecular biology tools, ranging from functional gene-based models to metabolic models. Finally, I discuss the inherent limitations of trait-based modeling frameworks and their implications for model development and evaluation, including the gap between functional groups represented in silico and microbial communities found in natural environments, as well as the requirement of internal consistency in microbial parameter sets. [Display omitted] • Functional groups should be divided into actively-growing and dormant subgroups. • Maintenance and cell lysis should be explicitly simulated. • Rate laws provide approximations, not accurate descriptions, of microbial rates. • Rate laws include the Monod equation, the Contois equation, and the Best equation. • Internal consistency is required for microbial parameter datasets. [ABSTRACT FROM AUTHOR]

Evaluating the carbon cycling driven by aerobic oxidation of methane (AeOM) in surface marine sediments and calculating the CH 4 flux to the seawater is critical for assessing the risk of greenhouse gas emission, as well as exploring for gas field. This study provides quantitative results of carbon cycling in the aerobic zone of the Bohai Sea, China, and the function of AeOM for CH 4 interception via numerical simulations constrained by laboratory experiments. TOUGH + HR, an integrated simulation package, was used to numerically characterize the microbial AeOM, which couples water/gas transport and biogeochemistry. Based on the laboratory experiments and measured data in the Bohai Sea, a one-dimensional column conceptual model was constructed and solved by TOUGH + HR. The results show that when the upward CH 4 flux into the aerobic zone is between 4.5 × 10−9 and 4.8 × 10−9 kg/s/m2, the simulated dissolved methane matched the measured data well. Under this condition, most of the CH 4 source flux (18.63 mmol·carbon/m2/day) was oxidized to dissolved inorganic carbon (DIC), which finally discharged into the seawater with the flux of 18.44 mmol·carbon/m2/day, while only a tiny part of CH 4 leaked into the seawater with the flux of 0.0003 mmol·carbon/m2/day. Therefore, it can be concluded that the aerobic zone in the sediments intercepts the majority of CH 4 , which mitigates the greenhouse gas emission from marine sediments. At the same time, the sensitivity analyses in this study indicate that carbon cycling is affected by methane flux and temperature, which influences the proportion of carbon sources and sinks. The results have important guidance for gas exploration and carbon cycling when the AeOM in the aerobic zone is considered. • The kinetic parameters used to simulate the microbial AeOM were calibrated by laboratory experiments. • The flux of CH 4 leaking into the aerobic zone in the sediment of the study site was estimated. • The carbon cycling mode in the aerobic zone was quantitatively analyzed. • Sensitivity analysis of carbon cycling to CH 4 flux and temperature under AeOM was conducted. [ABSTRACT FROM AUTHOR]

Three pilot-scale bioreactors were started up and operated under salinity-amended urban wastewater feeding. The bioreactors were configured as membrane bioreactor and two different hybrid, moving bed biofilm reactor-membrane bioreactor and operated with a hydraulic retention time of 9.5 h, a solid residence time of 11.75 days and a total solids concentration of 2500 mg L−1. The three systems showed excellent performance in suspended solids, BOD5, and COD removal (values of 96-100%, 97-99%, and 88-90%, respectively), but poor nitrogen removal (values of 20-30%). The bacterial community structure during the start-up phase and the stabilization phase were different, as showed by β-diversity analyses. The differences between aerobic and anoxic biomass-and between suspended and attached biomass-were higher at the start-up phase than at the stabilization phase. The start-up phase showed high abundances of Chiayiivirga (mean values around 3-12% relative abundance) and Luteimonas (5-8%), but in the stabilization phase, the domination belonged to Thermomonas (3-14%), Nitrobacter (3-7%), Ottowia (3-11.5%), and Comamonas (2-6%), among others. Multivariate redundancy analyses showed that Thermomonas and Nitrosomonas were positively correlated with fast autotrophic kinetics, while Caulobacter and Ottowia were positively correlated with fast heterotrophic kinetics. Nitrobacter, Rhodanobacter, and Comamonas were positively correlated with fast autotrophic and heterotrophic kinetics. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1483-1495, 2017 [ABSTRACT FROM AUTHOR]

A membrane bioreactor (MBR) and two hybrid moving bed biofilm reactor-membrane bioreactor systems (hybrid MBBR-MBRs) were studied in terms of the process modeling and operation optimization through different mathematical models for organic matter and nitrogen removal. A multiple linear regression method and a multivariable statistical analysis were applied. The process variables were hydraulic retention time, total biomass concentration, temperature, chemical oxygen demand of the influent, and total nitrogen of the influent. In general, the values of the coefficient of determination ( R2) for the different model fittings were higher for the hybrid MBBR-MBR processes than those obtained for the MBR, which was probably attributable to the presence of suspended and attached biomass in the hybrid MBBR-MBR systems. [ABSTRACT FROM AUTHOR]

This study assessed the effect of 0.5T static magnetic field (SMF) on microbial growth kinetics and physiochemical properties of Nono drinks stored at uncertain condition for six days. Magnetatic bacterial were predominated by Lactobacillus casei (40%), Corynebacterium sp(50%), and Staphylococcus sp (10%); while fungi were Penicillum sp(30%), Mucorsp(20%) and Aspergillus sp(50%). SMF significantly (P<0.05) altered the average pH (2.26-2.31) and total titratable acidity (0.13-0.17%v/v) compared to the average controls of 2.08 and 0.20%v/v respectively. However, SMF had no significant impact on the temperature and sensory properties (≤ 3 score of 7-point hedonic scale ranking) of Nono drinks when compared to the control samples after six days assessment. Microbial growth kinetic was relatively stable within 72hrs, thereafter, SMF treated samples steadily declined by 30.5%while non-SMF (control) samples increased by 26.25%. Microbial growth kinetics was observed to have direct and inverse correlations to total titratable acidity and pH respectively. Conclusively, SMFhave correlative inhibitory impact on microbial growth rate with consequential acidityincrease that would slow down the rate of spoilage. Thus, inclusion of SMF to hurdle technology would prolong diary products' shelf-life with minimal sensory alterations. [ABSTRACT FROM AUTHOR]

A pilot-plant membrane bioreactor (MBR) and two pilot-plant hybrid moving bed biofilm reactor-membrane bioreactors (MBBR-MBRs), divided into three aerobic and one anoxic chambers, were started up for the treatment of salinity-amended urban wastewater. The MBBR-MBR systems worked with and without carriers in the anoxic zone (MBBR-MBRanox and MBBR-MBRn/anox, respectively). The systems were operated from start-up to stabilization, showing high removal of organic matter-a maximum of 90% chemical oxygen demand and 98% biochemical oxygen demand on the fifth day for MBBR-MBRn/anox in the stabilization phase-but low nitrogen elimination-30% maximum for MBBR-MBRn/anox in the stabilization phase. Biofilm attached to carriers reached less than 50 mg L−1 in the hybrid system. MBR showed faster kinetics than the two MBBR-MBR systems during start-up, but the opposite occurred during stabilization. Maximum specific growth rates for heterotrophic and autotrophic biomass were 0.0500 and 0.0059 h−1 for MBBR-MBRn/anox in the stabilization phase. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3329-3342, 2017 [ABSTRACT FROM AUTHOR]

Cellulose utilization by hydrogen producers remains an issue due to the low hydrogen yields reported and the pretreatment of cellulose prior to fermentation requires complex and expensive steps. Clostridium termitidis is able to breakdown cellulose into glucose and produce hydrogen. On the other hand, Clostridium beijerinckii is not able to degrade cellulose but is adept at hydrogen production from glucose; therefore, it was chosen to potentially enhance hydrogen production when co-cultured with C. termitidis on cellulose. In this study, batch fermentation tests were conducted to investigate the direct hydrogen production enhancement of mesophilic cellulolytic bacteria C. termitidis co-cultured with mesophilic hydrogen producer C. beijerinckii on cellulose at 2 g l compared to C. termitidis mono-culture. Microbial kinetics parameters were determined by modeling in MATLAB. The achieved highest hydrogen yield was 1.92 mol hydrogen mol hexose equivalent in the co-culture compared to 1.45 mol hydrogen mol hexose equivalent in the mono-culture. The maximum hydrogen production rate of 26 ml d was achieved in the co-culture. Co-culture exhibited an overall 32 % enhancement of hydrogen yield based on hexose equivalent added and 15 % more substrate utilization. The main metabolites were acetate, ethanol, lactate, and formate in the mono-culture, with also butyrate in the co-culture. Additionally, the hydrogen yield of C. beijerinckii only in glucose was 2.54 mol hydrogen mol hexose equivalent. This study has proved the viability of co-culture of C. termitidis with C. beijerinckii for hydrogen production directly from a complex substrate like cellulose under mesophilic conditions. [ABSTRACT FROM AUTHOR]

Geological carbon sequestration captures CO2 from industrial sources and stores the CO2 in subsurface reservoirs, a viable strategy for mitigating global climate change. In assessing the environmental impact of the strategy, a key question is how microbial reactions respond to the elevated CO2 concentration. This study uses biogeochemical modeling to explore the influence of CO2 on the thermodynamics and kinetics of common microbial reactions in subsurface environments, including syntrophic oxidation, iron reduction, sulfate reduction, and methanogenesis. The results show that increasing CO2 levels decreases groundwater pH and modulates chemical speciation of weak acids in groundwater, which in turn affect microbial reactions in different ways and to different extents. Specifically, a thermodynamic analysis shows that increasing CO2 partial pressure lowers the energy available from syntrophic oxidation and acetoclastic methanogenesis, but raises the available energy of microbial iron reduction, hydrogenotrophic sulfate reduction and methanogenesis. Kinetic modeling suggests that high CO2 has the potential of inhibiting microbial sulfate reduction while promoting iron reduction. These results are consistent with the observations of previous laboratory and field studies, and highlight the complexity in microbiological responses to elevated CO2 abundance, and the potential power of biogeochemical modeling in evaluating and quantifying these responses. [ABSTRACT FROM AUTHOR]

A membrane bioreactor (MBR), a hybrid moving-bed biofilm reactor-membrane bioreactor (hybrid MBBR-MBRa) containing carriers in the anoxic and aerobic compartments, and a hybrid MBBR-MBRb containing carriers only in the aerobic zone were used in parallel and compared for treating municipal wastewater. The microbial kinetics and the evolution of the enzymatic activities of α-glucosidase and acid and alkaline phosphatase as well as the bacterial diversity and bacterial community structure were studied to explain the removal of organic matter and nutrients. The MBR and the hybrid MBBR-MBRb showed the highest reduction percentages of chemical oxygen demand. Moreover, the hybrid MBBR-MBRb exhibited the highest removal performance of total nitrogen. [ABSTRACT FROM AUTHOR]

Kefir is a fermented milk product, made up of a set of microorganisms of lactic acid bacteria (LAB), yeasts, mixed in a polysaccharide matrix called kefir. The substrate used and studied so far has been lactose, by inoculation of kefir in milk. The biomass of kefir grains increases slowly after successive fermentations. Therefore, in this work, the growth of kefir granule biomass was investigated with the addition of 4% and 6% (w/v) fructose and dextrose, respectively. Fermentation kinetics were carried out at 25°C for 36 h, with an initial inoculum of 2% kefir granules in pasteurized milk taken as a control. Measurements of biomass content, pH and °Brix were made during the fermentation kinetics. The kinetics showed that the control fermentation has a maximum biomass peak of 5.16±0.57 gr/ml, pH of 4.2 and 6.25°Brix at 24 hr, for fructose and dextrose their maximum biomass peak was 7.51±0.14 gr/ml, pH of 4.2, 12.25°Brix and 6.46±0.02 gr/ml, pH of 4.1, 12.5 °Brix at 30 h, respectively. Incorporation with different sugars can lead to improve the increase of kefir granule biomass. [ABSTRACT FROM AUTHOR]

High pressure inactivation of natural microbiota viz. aerobic mesophiles (AM), psychrotrophs (PC), yeasts and molds (YM), total coliforms (TC) and lactic acid bacteria (LAB) in pineapple puree was studied within the experimental domain of 0.1–600 MPa and 30–50 °C with a treatment time up to 20 min. A complete destruction of yeasts and molds was obtained at 500 MPa/50 °C/15 min; whereas no counts were detected for TC and LAB at 300 MPa/30 °C/15 min. A maximum of two log cycle reductions was obtained for YM during pulse pressurization at the severe process intensity of 600 MPa/50 °C/20 min. The Weibull model clearly described the non-linearity of the survival curves during the isobaric period. The tailing effect, as confirmed by the shape parameter ( β ) of the survival curve, was obtained in case of YM ( β < 1); whereas a shouldering effect ( β > 1) was observed for the other microbial groups. Analogous to thermal death kinetics, the activation energy ( E a , kJ·mol − 1 ) and the activation volume ( V a , mL·mol − 1 ) values were computed further to describe the temperature and pressure dependencies of the scale parameter (δ, min), respectively. A higher δ value was obtained for each microbe at a lower temperature and it decreased with an increase in pressure. A secondary kinetic model was developed describing the inactivation rate ( k , min − 1 ) as a function of pressure ( P , MPa) and temperature ( T , K) including the dependencies of E a and V a on P and T , respectively. [ABSTRACT FROM AUTHOR]

Due to lack of understanding of the complex nature of the composting process, there is a need to provide a valuable tool that can help to improve the prediction of the process performance but also its optimization. Therefore, the main objective of this study is to develop a comprehensive mathematical model of the composting process based on microbial kinetics. The model incorporates two different microbial populations that metabolize the organic matter in two different substrates. The model was validated by comparison of the model and experimental data obtained from the composting process of the mixture of poultry manure and wheat straw. Comparison of simulation results and experimental data for five dynamic state variables (organic matter conversion, oxygen concentration, carbon dioxide concentration, substrate temperature and moisture content) showed that the model has very good predictions of the process performance. According to simulation results, the optimum values for air flow rate and ambient air temperature are 0.43 l min −1 kg −1 OM and 28 °C, respectively. On the basis of sensitivity analysis, the maximum organic matter conversion is the most sensitive among the three objective functions. Among the twelve examined parameters, μ max ,1 is the most influencing parameter and X 1 is the least influencing parameter. [ABSTRACT FROM AUTHOR]

Aims Ureolysis drives microbially induced calcium carbonate precipitation ( MICP). MICP models typically employ simplified urea hydrolysis kinetics that do not account for cell density, pH effect or product inhibition. Here, ureolysis rate studies with whole cells of Sporosarcina pasteurii aimed to determine the relationship between ureolysis rate and concentrations of (i) urea, (ii) cells, (iii) [ABSTRACT FROM AUTHOR]

ABSTRACT Biofilms of the ammonia oxidizing bacterium Nitrosomonas europaea were cultivated to study microbial processes associated with ammonia oxidation in pure culture. We explored the hypothesis that the kinetic parameters of ammonia oxidation in N. europaea biofilms were in the range of those determined with batch suspended cells. Oxygen and pH microelectrodes were used to measure dissolved oxygen (DO) concentrations and pH above and inside biofilms and reactive transport modeling was performed to simulate the measured DO and pH profiles. A two dimensional (2-D) model was used to simulate advection parallel to the biofilm surface and diffusion through the overlying fluid while reaction and diffusion were simulated in the biofilm. Three experimental studies of microsensor measurements were performed with biofilms: i) NH3 concentrations near the Ksn value of 40 μM determined in suspended cell tests ii) Limited buffering capacity which resulted in a pH gradient within the biofilms and iii) NH3 concentrations well below the Ksn value. Very good fits to the DO concentration profiles both in the fluid above and in the biofilms were achieved using the 2-D model. The modeling study revealed that the half-saturation coefficient for NH3 in N. europaea biofilms was close to the value measured in suspended cells. However, the third study of biofilms with low availability of NH3 deviated from the model prediction. The model also predicted shifts in the DO profiles and the gradient in pH that resulted for the case of limited buffering capacity. The results illustrate the importance of incorporating both key transport and chemical processes in a biofilm reactive transport model. Biotechnol. Bioeng. 2015;112: 1122-1131. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]