Metabolic modelling of polyhydroxyalkanoate copolymers production by mixed microbial cultures

Characterization of polyhydroxybutyrate (PHB) synthesized by newly isolated rare actinomycetes Aquabacterium sp. A7-Y

Polyhydroxyalkanoates (PHAs) as biodegradable plastics have attracted increasing attention due to its biodegradable, biocompatible and renewable advantages. Exploitation some unique microbes for PHAs production is one of the most competitive approaches to meet complex industrial demand, and further develop next-generation industrial biotechnology. In this study, a rare actinomycetes strain A7-Y was isolated and identified from soil as the first PHAs producer of Aquabacterium genus. Produced PHAs by strain A7-Y was identified as poly(3-hydroxybutyrate) (PHB) based on its structure characteristics, which is also similar with commercial PHB. After optimization of fermentation conditions, strain A7-Y can produce 10.2 g/L of PHB in 5 L fed-batch fermenter, corresponding with 54 % PHB content of dry cell weight, which is superior to the reported actinomycetes species. Furthermore, the phaCAB operon in stain A7-Y was excavated to be responsible for the efficient PHB production and verified in recombinant Escherichia coli. Our results indicate that strain A7-Y and its biosynthetic gene cluster are potential candidates for developing a microbial formulation for the PHB production.

Dynamic modeling of Rhodospirillum rubrum PHA production triggered by redox stress during VFA photoheterotrophic assimilations

Polyhydroxyalkanoates (PHA) represent an environmentally friendly alternative to petroleum based plastics for a broad range of applications from packaging to biomedical devices. In the prospect of an industrial PHA production, it is highly valuable to accurately control the incorporation of different repeating units into the polymer, to produce a polyester with specific material characteristics. In this study, we develop macroscopic dynamic models predicting the polymer production and composition when mixtures containing up to four volatile fatty acids (VFA) are used as substrates. These models successfully reproduce the sequential (and preferential) substrate consumption and polymer production/reconsumption patterns, experimentally observed during biomass growth, thanks to simple kinetic structures based on Monod and inhibition factors. These models can serve as a basis for numerical simulation and process analysis, as well as process intensification through model-based optimization and control.

Polyhydroxyalkanoates synthesis using acidogenic fermentative effluents

Polyhydroxyalkanoates (PHA) are natural polyesters synthesized by microbes which consume excess amount of carbon and less amount of nutrients. It is biodegradable in nature, and it synthesized from renewable resources. It is considered as a future polymer, which act as an attractive replacement to petrochemical based polymers. The main hindrance to the commercial application of PHA is the high manufacturing cost. This article provides an overview of different cost-effective substrates, their characteristics and composition, major strains involved in economical production of PHA and biosynthetic pathways leading to accumulation of PHA. This review also covers the operational parameters, various fermentative modes including batch, fed-batch, repeated fed-batch and continuous fed-batch systems, along with advanced feeding strategies such as single pulse carbon feeding, feed forward control, intermittent carbon feeding, feast famine conditions to observe their effects for improving PHA synthesis and associated challenges. In addition, it also presents the economic analysis and future perspectives for the commercialization of PHA production process thereby making the process sustainable and lucrative with the possibility of commercial biomanufacturing.

Structural assessment of the bioplastic (poly-3-hydroxybutyrate) produced by Bacillus flexus Azu-A2 through cheese whey valorization

The demand for the production of biodegradable plastics has significantly increased. Bioplastics have become an essential alternative to the threats of the daily consumable plastics, sourced from fossil fuels, to the environment. Polyhydroxyalkonates (PHAs) are a ubiquitous group of bioderived and biodegradable plastics, however their production is limited by the costs associated mainly with the carbon sources. Herein, this study aims to reduce the PHAs production cost by using a by-product from the dairy industry, i.e., cheese whey (CW), as a sole carbon source. The developed process recruits an aquatic isolate, Bacillus flexus Azu-A2, and is optimized via studying various parameters using the shaking flasks technique. The results showed that the maximum PHA production (0.95 g L^-1) and PHA content (20.96%, w/w), were obtained after incubation period 72 h at 45 °C, 100 rpm agitation rate, 50% CWS concentration, pH 8.5, and 1.0 g L^-1 ammonium chloride. Physiochemically, Fourier transform infrared spectroscopy (FTIR), gas chromatography-mass spectroscopy (GC-MS), nuclear magnetic resonance (NMR), and energy-dispersive X-ray (EDX) techniques, emphasized the type of the extracted PHA as polyhydroxybutyrate (PHB). The thermal properties of PHB were measured using differential scanning calorimetry (DSC), recording melting transition temperature (Tm) at 170.96 °C. Furthermore, a scanning electron microscope (SEM) visualized a homogenous microporous structure for the thin PHB biofilm. In essence, this study highlights the ability of Bacillus flexus Azu-A2 to produce a good yield of highly purified PHB at reduced production cost from dairy CW. Consequently, the current study paves the way for an improved whey management strategy.

Integrating dairy manure for enhanced resource recovery at a WRRF: Environmental life cycle and pilot-scale analyses

The Twin Falls, Idaho wastewater treatment plant (WWTP), currently operates solely to achieve regulatory permit compliance. Research was conducted to evaluate conversion of the WWTP to a water resource recovery facility (WRRF) and to assess the WRRF environmental sustainability; process configurations were evaluated to produce five resources-reclaimed water, biosolids, struvite, biogas, and bioplastics (polyhydroxyalkanoates, PHA). PHA production occurred using fermented dairy manure. State-of-the-art biokinetic modeling, performed using Dynamita's SUMO process model, was coupled with environmental life cycle assessment to quantify environmental sustainability. Results indicate that electricity production via combined heat and power (CHP) was most important in achieving environmental sustainability; energy offset ranged from 43% to 60%, thereby reducing demand for external fossil fuel-based energy. While struvite production helps maintain a resilient enhanced biological phosphorus removal (EBPR) process, MgO₂ production exhibits negative environmental impacts; integration with CHP negates the adverse consequences. Integrating dairy manure to produce bioplastics diversifies the resource recovery portfolio while maintaining WRRF environmental sustainability; pilot-scale evaluations demonstrated that WRRF effluent quality was not affected by the addition of effluent from PHA production. Collectively, results show that a WRRF integrating dairy manure can yield a diverse portfolio of products while operating in an environmentally sustainable manner. PRACTITIONER POINTS: Wastewater carbon recovery via anaerobic digestion with combined heat/power production significantly reduces water resource recovery facility (WRRF) environmental emissions. Wastewater phosphorus recovery is of value; however, struvite production exhibits negative environmental impacts due to MgO₂ production emissions. Bioplastics production on imported organic-rich agri-food waste can diversify the WRRF portfolio. Dairy manure can be successfully integrated into a WRRF for bioplastics production without compromising WRRF performance. Diversifying the WRRF products portfolio is a strategy to maximize resource recovery from wastewater while concurrently achieving environmental sustainability.

Modeling of Continuous PHA Production by a Hybrid Approach Based on First Principles and Machine Learning

Polyhydroxyalkanoates (PHA) are renewable alternatives to traditional oil-derived polymers. PHA can be produced by different microorganisms in continuous culture under specific media composition, which makes the production process both promising and challenging. In order to achieve large productivities while maintaining high yield and efficiency, the continuous culture needs to be operated in the so-called dual nutrient limitation condition, where both the nitrogen and carbon sources are kept at very low concentrations. Mathematical models can greatly assist both design and operation of the bioprocess, but are challenged by the complexity of the system, in particular by the dual nutrient-limited growth phenomenon, where the cells undergo a metabolic shift that abruptly changes their behavior. Traditional, non-structured mechanistic models based on Monod uptake kinetics can be used to describe the bioreactor operation under specific process conditions. However, in the absence of a model description of the metabolic phenomena inside the cell, the extrapolation to a broader operation domain (e.g., different feeding concentrations and dilution rates) may present mismatches between the predictions and the actual process outcomes. Such detailed models may require almost perfect knowledge of the cell metabolism and omic-level measurements, hampering their development. On the other hand, purely data-driven models that learn correlations from experimental data do not require any prior knowledge of the process and are therefore unbiased and flexible. However, many more data are required for their development and their extrapolation ability is limited to conditions that are similar to the ones used for training. An attractive alternative is the combination of the extrapolation power of first principles knowledge with the flexibility of machine learning methods. This approach results in a hybrid model for the growth and uptake rates that can be used to predict the dynamic operation of the bioreactor. Here we develop a hybrid model to describe the continuous production of PHA by Pseudomonas putida GPo1 culture. After training, the model with experimental data gained under different dilution rates and medium compositions, we demonstrate how the model can describe the process in a wide range of operating conditions, including both single and dual nutrient-limited growth.

Advanced Kinetic Modeling of Bio-co-polymer Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Production Using Fructose and Propionate as Carbon Sources

Biopolymers are a promising alternative to petroleum-based plastic raw materials. They are bio-based, non-toxic and degradable under environmental conditions. In addition to the homopolymer poly(3-hydroxybutyrate) (PHB), there are a number of co-polymers that have a broad range of applications and are easier to process in comparison to PHB. The most prominent representative from this group of bio-copolymers is poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). In this article, we show a new kinetic model that describes the PHBV production from fructose and propionic acid in Cupriavidus necator (C. necator). The developed model is used to analyze the effects of process parameter variations such as the CO2 amount in the exhaust gas and the feed rate. The presented model is a valuable tool to improve the microbial PHBV production process. Due to the coupling of CO2 online measurements in the exhaust gas to the biomass production, the model has the potential to predict the composition and the current yield of PHBV in the ongoing process.

Polyhydroxyalkanoate (PHA) production via resource recovery from industrial waste streams: A review of techniques and perspectives

The problem of waste generation in the form of wastewater and solid wastes has caused an urgent, yet persisting, global issue that calls for the development of sustainable treatment and resource recovery technologies. The production of value-added polyhydroxyalkanoates (PHAs) from industrial waste streams has attracted the attention of researchers and process industries because they could replace traditional plastics. PHAs are biopolymers with high degradability, with a variety of applications in the manufacturing sector (e.g. medical equipment, packaging). The aim of this review is to describe the techniques and industrial waste streams that are applied for PHA production. The different enrichment and accumulation techniques that employ mixed microbial communities and carbon recovery from industrial waste streams and various downstream processes were reviewed. PHA yields between 7.6 and 76 wt% were reported for pilot-scale PHA production; while, at the laboratory-scale, yields from PHA accumulation range between 8.6 and 56 wt%. The recent advances in the application of waste streams for PHA production could result in more widely spread PHA production at the industrial scale via its integration into biorefineries for co-generation of PHAs with other added-value products like biohydrogen and biogas.

Effects of chemical oxygen demand concentration, pH and operation cycle on polyhydroxyalkanoates synthesis with waste sludge

To reduce the cost of polyhydroxyalkanoate (PHA) production and dispose the amount of waste sludge simultaneously, chemical oxygen demand (COD) concentration, pH and operation cycle were investigated to find the optimal PHA synthesis conditions with waste sludge in this study. The maximum PHA content (31.3% of the cell dry weight (CDW)), as well as the highest PHA conversion rate (0.30 mg COD/mg COD) and PHA-specific synthesis rate (6.12 mg COD/mg CDW·h), was achieved with initial COD concentration, pH value and operation cycle: 6000 mg/L, 8.5 and 24 h. In order to further investigate the process of PHA synthesis, COD removal rate and CDW were also introduced. This study could provide valuable information for increasing the production of PHA with waste sludge.

Challenges and Perspectives of Polyhydroxyalkanoate Production From Microalgae/Cyanobacteria and Bacteria as Microbial Factories: An Assessment of Hybrid Biological System

Polyhydroxyalkanoates (PHAs) are the biopolymer of choice if we look for a substitute of petroleum-based non-biodegradable plastics. Microbial production of PHAs as carbon reserves has been studied for decades and PHAs are gaining attention for a wide range of applications in various fields. Still, their uneconomical production is the major concern largely attributed to high cost of organic substrates for PHA producing heterotrophic bacteria. Therefore, microalgae/cyanobacteria, being photoautotrophic, prove to have an edge over heterotrophic bacteria. They have minimal metabolic requirements, such as inorganic nutrients (CO2, N, P, etc.) and light, and they can survive under adverse environmental conditions. PHA production under photoautotrophic conditions has been reported from cyanobacteria, the only candidate among prokaryotes, and few of the eukaryotic microalgae. However, an efficient cultivation system is still required for photoautotrophic PHA production to overcome the limitations associated with (1) stringent management of closed photobioreactors and (2) optimization of monoculture in open pond culture. Thus, a hybrid system is a necessity, involving the participation of microalgae/cyanobacteria and bacteria, i.e., both photoautotrophic and heterotrophic components having mutual interactive benefits for each other under different cultivation regime, e.g., mixotrophic, successive two modules, consortium based, etc. Along with this, further strategies like optimization of culture conditions (N, P, light exposure, CO2 dynamics, etc.), bioengineering, efficient downstream processes, and the application of mathematical/network modeling of metabolic pathways to improve PHA production are the key areas discussed here. Conclusively, this review aims to critically analyze cyanobacteria as PHA producers and proposes economically sustainable production of PHA from microbial autotrophs and heterotrophs in "hybrid biological system."

Dark fermentation metabolic models to study strategies for hydrogen consumers inhibition

A Flux Balance Analysis (FBA) metabolic model of dark fermentation was developed for anaerobic mixed cultures. In particular, the model was applied to evaluate the effect of a specific inoculum pre-treatment strategy, addition of waste frying oil (WFO) on H₂-producing and H₂-consuming metabolic pathways. Productions of volatile fatty acid (VFAs), CO₂, H₂ and CH₄ measured through triplicate batch experiments, were used as constraints for the FBA model, to compute fluxes trough different metabolic pathways. FBA model could estimate the effect of pre-treatment with WFO on major microbial populations present in the mixed community (H₂ producing bacteria, homoacetogen and methanogens). Results revealed that low concentrations of WFO did not completely inhibited hydrogenotrophic methanogens. FBA showed that acetoclastic methanogens were more sensitive to WFO, in comparison to hydrogenotrophic methanogens. The proposed model can be used to study H₂ production by any other mixed microbial culture with similar substrates.

Combined polyhydroxyalkanoates (PHA) and 1,3-propanediol production from crude glycerol: Selective conversion of volatile fatty acids into PHA by mixed microbial consortia

Crude glycerol is an important by-product of the biodiesel industry, which can be converted into volatile fatty acids (VFA) and/or 1,3-propanediol (1,3-PDO) by fermentation. In this study, a selective conversion of VFA to polyhydroxyalkanoates (PHA) was attained while leaving 1,3-PDO in the supernatant by means of mixed microbial consortia selection strategies. The process showed highly reproducible results in terms of PHA yield, 0.99 ± 0.07 C_mol PHA/C_mol S (0.84 g COD PHA/g COD S), PHA content (76 ± 3.1 g PHA/100 g TSS) and 1,3-PDO recovery (99 ± 2.1%). The combined process had an ultimate yield from crude glycerol of 0.19 g COD PHA and 0.42 g COD 1,3-PDO per g of input COD. The novel enrichment strategy applied for selectively transforming fermentation by-products into a high value product (PHA) demonstrates the significance of the enrichment process for targeting specific bio-transformations and could potentially prove valuable for other biotechnological applications as well.

The link of feast-phase dissolved oxygen (DO) with substrate competition and microbial selection in PHA production

Polyhydroxyalkanoates (PHAs) are biobased and biodegradable polyesters with the potential to replace conventional plastics. Aeration requires large amounts of energy in PHA production by mixed microbial cultures (MMCs), particularly during the feast phase due to substrate uptake. The objective of this study was to investigate the impact of DO concentrations on microbial selection, substrate competition and PHA production performance by MMCs. This represents the first study investigating DO impact on PHA production while feeding the multiple volatile fatty acids (VFAs) typically encountered in real fermented feedstocks, as well as the substrate preferences at different DO levels. Efficient microbial cultures were enriched under both high (3.47 ± 1.12 mg/L) and low (0.86 ± 0.50 mg/L) DO conditions in the feast phase containing mostly the same populations but with different relative abundance. The most abundant microorganisms in the two MMCs were Plasticicumulans, Zoogloea, Paracoccus, and Flavobacterium. Butyrate and valerate were found to be the preferred substrates as compared to acetate and propionate regardless of DO concentrations. In the accumulation step, the PHA storage capacity and yield were less affected by the change of DO levels when applying the culture selected under low DO in the feast phase (PHA storage capacity >60% and yield > 0.9 Cmol PHA/Cmol VFA). A high DO level is required for maximal PHA accumulation rates with the four VFAs (acetate, propionate, butyrate and valerate) present, due to the lower specific uptake rates of acetate and propionate under low DO conditions. However, butyrate and valerate specific uptake rates were less impacted by DO levels and hence low DO for PHA accumulation may be effective when feed is composed of these substrates only.

The Evolution of Polymer Composition during PHA Accumulation: The Significance of Reducing Equivalents

This paper presents a systematic investigation into monomer development during mixed culture Polyhydroxyalkanoates (PHA) accumulation involving concurrent active biomass growth and polymer storage. A series of mixed culture PHA accumulation experiments, using several different substrate-feeding strategies, was carried out. The feedstock comprised volatile fatty acids, which were applied as single carbon sources, as mixtures, or in series, using a fed-batch feed-on-demand controlled bioprocess. A dynamic trend in active biomass growth as well as polymer composition was observed. The observations were consistent over replicate accumulations. Metabolic flux analysis (MFA) was used to investigate metabolic activity through time. It was concluded that carbon flux, and consequently copolymer composition, could be linked with how reducing equivalents are generated.

Biotransformation of volatile fatty acids to polyhydroxyalkanoates by employing mixed microbial consortia: The effect of pH and carbon source

Mixed microbial cultures that undergo successful enrichment, following eco-biotechnological approaches, to form a community dominant in polyhydroxyalkanoates (PHA) forming bacteria, represent an attractive economic alternative towards the production of those biopolymers. In the present study, an enriched mixed culture was investigated for the production of PHA at different initial pH values under non-controlled conditions in order to minimize process control and operational costs. Short-chain fatty acids were provided as PHA precursors and they were tested as sole carbon sources and as mixtures under nitrogen deficiency. By the obtained kinetic and stoichiometric parameters it was shown that at an initial pH value of 6.90 PHA production was favored. Butyrate was characterized as the preferred carbon source, whereas simultaneous feeding led to increased rates and yields when butyrate and acetate were present.

Microbial Cometabolism and Polyhydroxyalkanoate Co-polymers

Polyhydroxyalkanoate (PHAs) are natural, biodegradable biopolymers, which can be produced from renewable materials. PHAs have potential to replace petroleum derived plastics. Quite a few bacteria can produce PHA under nutritional stress. They generally produce homopolymers of butyrate i.e., polyhydroxybutyrate (PHB), as a storage material. The biochemical characteristics of PHB such as brittleness, low strength, low elasticity, etc. make these unsuitable for commercial applications. Co-polymers of PHA, have high commercial value as they overcome the limitations of PHBs. Co-polymers can be produced by supplementing the feed with volatile fatty acids or through hydrolysates of different biowastes. In this review, we have listed the potential bacterial candidates and the substrates, which can be co-metabolized to produce PHA co-polymers.

Production of poly-3-hydroxybutyrate (P3HB) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) P(3HB-co-3HV) from synthetic wastewater using Hydrogenophaga palleronii

In the present study, synthetic wastewater (SW) was used for production of poly-3-hydroxybutyrate (P3HB) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) P(3HB-co-3HV) using the bacteria Hydrogenophaga palleronii. SW at various volatile fatty acids concentrations (5-60g/l) was evaluated for the growth and biopolymer production using H. palleronii. Substrate degradation was analyzed using total organic carbon (TOC) analyzer and high pressure liquid chromatography (HPLC). H. palleronii showed highest and lowest removal of TOC at 5g/l (88±4%) and 60g/l (15±6%) respectively. Among all the concentrations evaluated, bacteria showed highest biopolymer production with 20g/l (63±5%), followed by 30g/l (58±3%) and 40g/l (56±2%). Lowest biopolymer production was observed at 5g/l concentration (21±3%). Structure, molecular weight, and thermal properties of the produced biopolymer were analyzed. These results denoted that the strain H. palleronii can be used for degradation of high concentration of volatile fatty acids persistent in wastewaters and their subsequent conversion into useable biopolymers.

Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations.

Estimation of parameter uncertainty for an activated sludge model using Bayesian inference: a comparison with the frequentist method

The procedure commonly used for the assessment of the parameters included in activated sludge models (ASMs) relies on the estimation of their optimal value within a confidence region (i.e. frequentist inference). Once optimal values are estimated, parameter uncertainty is computed through the covariance matrix. However, alternative approaches based on the consideration of the model parameters as probability distributions (i.e. Bayesian inference), may be of interest. The aim of this work is to apply (and compare) both Bayesian and frequentist inference methods when assessing uncertainty for an ASM-type model, which considers intracellular storage and biomass growth, simultaneously. Practical identifiability was addressed exclusively considering respirometric profiles based on the oxygen uptake rate and with the aid of probabilistic global sensitivity analysis. Parameter uncertainty was thus estimated according to both the Bayesian and frequentist inferential procedures. Results were compared in order to evidence the strengths and weaknesses of both approaches. Since it was demonstrated that Bayesian inference could be reduced to a frequentist approach under particular hypotheses, the former can be considered as a more generalist methodology. Hence, the use of Bayesian inference is encouraged for tackling inferential issues in ASM environments.

Modeling pure culture heterotrophic production of polyhydroxybutyrate (PHB)

In this contribution a mechanistic model describing the production of polyhydroxybutyrate (PHB) through pure-culture fermentation was developed, calibrated and validated for two different substrates, namely glucose and waste glycerol. In both cases, non-growth-associated PHB production was triggered by applying nitrogen limitation. The occurrence of some growth-associated PHB production besides non-growth-associated PHB production was demonstrated, although it is inhibited in the presence of nitrogen. Other phenomena observed experimentally and described by the model included biomass growth on PHB and non-linear product inhibition of PHB production. The accumulated impurities from the waste substrate negatively affected the obtained maximum PHB content. Overall, the developed mathematical model provided an accurate prediction of the dynamic behavior of heterotrophic biomass growth and PHB production in a two-phase pure culture system.

Segregated flux balance analysis constrained by population structure/function data: the case of PHA production by mixed microbial cultures

In this study we developed a segregated flux balance analysis (FBA) method to calculate metabolic flux distributions of the individual populations present in a mixed microbial culture (MMC). Population specific flux data constraints were derived from the raw data typically obtained by the fluorescence in situ hybridization (FISH) and microautoradiography (MAR)-FISH techniques. This method was applied to study the metabolic heterogeneity of a MMC that produces polyhydroxyalkanoates (PHA) from fermented sugar cane molasses. Three populations were identified by FISH, namely Paracoccus sp., Thauera sp., and Azoarcus sp. The segregated FBA method predicts a flux distribution for each of the identified populations. The method is shown to predict with high accuracy the average PHA storage flux and the respective monomeric composition for 16 independent experiments. Moreover, flux predictions by segregated FBA were slightly better than those obtained by nonsegregated FBA, and also highly concordant with metabolic flux analysis (MFA) estimated fluxes. The segregated FBA method can be of high value to assess metabolic heterogeneity in MMC systems and to derive more efficient eco-engineering strategies. For the case of PHA-producing MMC considered in this work, it becomes apparent that the PHA average monomeric composition might be controlled not only by the volatile fatty acids (VFA) feeding profile but also by the population composition present in the MMC.

Microbial Consortia Engineering for Cellular Factories: in vitro to in silico systems

This mini-review discusses the current state of experimental and computational microbial consortia engineering with a focus on cellular factories. A discussion of promising ecological theories central to community resource usage is presented to facilitate interpretation of consortial designs. Recent case studies exemplifying different resource usage motifs and consortial assembly templates are presented. The review also highlights in silico approaches to design and to analyze consortia with an emphasis on stoichiometric modeling methods. The discipline of microbial consortia engineering possesses a widely accepted potential to generate highly novel and effective bio-catalysts for applications from biofuels to specialty chemicals to enhanced mineral recovery.

Link between microbial composition and carbon substrate-uptake preferences in a PHA-storing community

The microbial community of a fermented molasses-fed sequencing batch reactor (SBR) operated under feast and famine conditions for production of polyhydroxyalkanoates (PHAs) was identified and quantified through a 16 S rRNA gene clone library and fluorescence in situ hybridization (FISH). The microbial enrichment was found to be composed of PHA-storing populations (84% of the microbial community), comprising members of the genera Azoarcus, Thauera and Paracoccus. The dominant PHA-storing populations ensured the high functional stability of the system (characterized by high PHA-storage efficiency, up to 60% PHA content). The fermented molasses contained primarily acetate, propionate, butyrate and valerate. The substrate preferences were determined by microautoradiography-FISH and differences in the substrate-uptake capabilities for the various probe-defined populations were found. The results showed that in the presence of multiple substrates, microbial populations specialized in different substrates were selected, thereby co-existing in the SBR by adapting to different niches. Azoarcus and Thauera, primarily consumed acetate and butyrate, respectively. Paracoccus consumed a broader range of substrates and had a higher cell-specific substrate uptake. The relative species composition and their substrate specialization were reflected in the substrate removal rates of different volatile fatty acids in the SBR reactor.

OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models.

Systems analysis of microbial adaptations to simultaneous stresses

Microbes live in multi-factorial environments and have evolved under a variety of concurrent stresses including resource scarcity. Their metabolic organization is a reflection of their evolutionary histories and, in spite of decades of research, there is still a need for improved theoretical tools to explain fundamental aspects of microbial physiology. Using ecological and economic concepts, this chapter explores a resource-ratio based theory to elucidate microbial strategies for extracting and channeling mass and energy. The theory assumes cellular fitness is maximized by allocating scarce resources in appropriate proportions to multiple stress responses. Presented case studies deconstruct metabolic networks into a complete set of minimal biochemical pathways known as elementary flux modes. An economic analysis of the elementary flux modes tabulates enzyme atomic synthesis requirements from amino acid sequences and pathway operating costs from catabolic efficiencies, permitting characterization of inherent tradeoffs between resource investment and phenotype. A set of elementary flux modes with competitive tradeoffs properties can be mathematically projected onto experimental fluxomics datasets to decompose measured phenotypes into metabolic adaptations, interpreted as cellular responses proportional to the experienced culturing stresses. The resource-ratio based method describes the experimental phenotypes with greater accuracy than other contemporary approaches and further analysis suggests the results are both statistically and biologically significant. The insight into metabolic network design principles including tradeoffs associated with concurrent stress adaptation provides a foundation for interpreting physiology as well as for rational control and engineering of medically, environmentally, and industrially relevant microbes.

Modelling the population dynamics and metabolic diversity of organisms relevant in anaerobic/anoxic/aerobic enhanced biological phosphorus removal processes

In this study, enhanced biological phosphorus removal (EBPR) metabolic models are expanded in order to incorporate the competition between polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) under sequential anaerobic/anoxic/aerobic conditions, which are representative of most full-scale EBPR plants. Since PAOs and GAOs display different denitrification tendencies, which is dependent on the phylogenetic identity of the organism, the model was separated into six distinct biomass groups, constituting Accumulibacter Types I and II, as well as denitrifying and non-denitrifying Competibacter and Defluviicoccus GAOs. Denitrification was modelled as a multi-step process, with nitrate (NO(3)), nitrite (NO(2)), nitrous oxide (N(2)O) and di-nitrogen gas (N(2)) being the primary components. The model was calibrated and validated using literature data from enriched cultures of PAOs and GAOs, obtaining a good description of the observed biochemical transformations. A strong correlation was observed between Accumulibacter Types I and II, and nitrate-reducing and non-nitrate-reducing PAOs, respectively, where the abundance of each PAO subgroup was well predicted by the model during an acclimatization period from anaerobic-aerobic to anaerobic-anoxic conditions. Interestingly, a strong interdependency was observed between the anaerobic, anoxic and aerobic kinetic parameters of PAOs and GAOs. This could be exploited when metabolic models are calibrated, since all of these parameters should be changed by an identical factor from their default value. Factors that influence these kinetic parameters include the fraction of active biomass, relative aerobic/anoxic fraction and the ratio of acetyl-CoA to propionyl-CoA. Employing a metabolic approach was found to be advantageous in describing the performance and population dynamics in such complex microbial ecosystems.

Polyhydroxyalkanoate (PHA) production by a mixed microbial culture using sugar molasses: effect of the influent substrate concentration on culture selection

In Polyhydroxyalkanoate (PHA) production processes using Mixed Microbial Culture (MMC), the success of the culture selection step determines, to a great extent, the PHA accumulation performance obtained in the final PHA production stage. In this study, the effect of the influent substrate concentration (30-60Cmmol VFA/L) on the selection of a PHA-storing culture using a complex feedstock, fermented sugar molasses, was assessed. At 30 and 45Cmmol VFA/L, substrate concentration impacted on the process kinetics through a substrate dependent kinetic limitation effect. However, further increasing the carbon substrate concentration to 60Cmmol VFA/L, resulted in an unforeseen growth limitation effect associated with a micronutrient deficiency of the fermented feedstock (magnesium) and high operating pH. Struvite precipitation caused a nutrient limitation which prevented biomass concentration increase, thus causing the feast to famine length ratio to vary in the selection reactor, with subsequent impact on the selective pressure for PHA-storing organisms. A highly dynamic response of the selected population to transient conditions of feast to famine ratio, in the range of 0.21-1.1, was observed. Kinetic (limiting concentration of carbon source) and physiological (loss of internal growth limitation due to the shorter length of famine phase) effects, resulting from variation of the influent substrate concentration, were subsequently demonstrated in batch studies. The culture selected at an influent substrate concentration of 45Cmmol VFA/L showed the best PHA-storing capacity since neither substrate concentration nor feast to famine ratio were limiting factors. This culture, highly enriched in PHA-storing organisms (88%), reached a maximum PHA content of 74.6%.

Modeling the PAO-GAO competition: effects of carbon source, pH and temperature

The influence of different carbon sources (acetate to propionate ratios), temperature and pH levels on the competition between polyphosphate- and glycogen-accumulating organisms (PAO and GAO, respectively) was evaluated using a metabolic model that incorporated the carbon source, temperature and pH dependences of these microorganisms. The model satisfactorily described the bacterial activity of PAO (Accumulibacter) and GAO (Competibacter and Alphaproteobacteria-GAO) laboratory-enriched cultures cultivated on propionate (HPr) and acetate (HAc) at standard conditions (20 degrees C and pH 7.0). Using the calibrated model, the effects of different influent HAc to HPr ratios (100-0, 75-25, 50-50 and 0-100%), temperatures (10, 20 and 30 degrees C) and pH levels (6.0, 7.0 and 7.5) on the competition among Accumulibacter, Competibacter and Alphaproteobacteria-GAO were evaluated. The main aim was to assess which conditions were favorable for the existence of PAO and, therefore, beneficial for the biological phosphorus removal process in sewage treatment plants. At low temperature (10 degrees C), PAO were the dominant microorganisms regardless of the used influent carbon source or pH. At moderate temperature (20 degrees C), PAO dominated the competition when HAc and HPr were simultaneously supplied (75-25 and 50-50% HAc to HPr ratios). However, the use of either HAc or HPr as sole carbon source at 20 degrees C was not favorable for PAO unless a high pH was used (7.5). Meanwhile, at higher temperature (30 degrees C), GAO tended to be the dominant microorganisms. Nevertheless, the combined presence of acetate and propionate in the influent (75-25 and 50-50% HAc to HPr ratios) as well as a high pH (7.5) appear to be potential factors to favor the metabolism of PAO over GAO at higher sewage temperature (30 degrees C).

Strategies for PHA production by mixed cultures and renewable waste materials

Production of polyhydroxyalkanoates (PHA) by mixed cultures has been widely studied in the last decade. Storage of PHA by mixed microbial cultures occurs under transient conditions of carbon or oxygen availability, known respectively as aerobic dynamic feeding and anaerobic/aerobic process. In these processes, PHA-accumulating organisms, which are quite diverse in terms of phenotype, are selected by the dynamic operating conditions imposed to the reactor. The stability of these processes during long-time operation and the similarity of the polymer physical/chemical properties to the one produced by pure cultures were demonstrated. This process could be implemented at industrial scale, providing that some technological aspects are solved. This review summarizes the relevant research carried out with mixed cultures for PHA production, with main focus on the use of wastes or industrial surplus as feedstocks. Basic concepts, regarding the metabolism and microbiology, and technological approaches, with emphasis on the kind of feedstock and reactor operating conditions for culture selection and PHA accumulation, are described. Challenges for the process optimization are also discussed.