Anaerobic Fermentation Pathway Research Articles

The coupling of carbon and energy fluxes reveals anaerobiosis in an aerobic soil incubation with a Bacillota-dominated community

Soil microorganisms rely on coupled fluxes of carbon and energy to fuel their maintenance, to switch from dormancy to activity and to grow under dynamically changing conditions in microhabitats. To identify the principles underlying this coupling, we measured heat and CO2 release from soil after glucose addition along with estimates of microbial biomass and community composition. The results revealed bi-directional deviations of the ratio of heat to CO2 release (Calorespirometric Ratio, CR) that are inconsistent with theoretical predictions for aerobic respiration, which is commonly assumed to be the major metabolic pathway in incubation experiments. Moreover, the microbial community was dominated by members of the Bacillota, whose relative abundance increased from 4 percent to 65 percent in 18 h. To interpret these findings, we developed a dynamic model of carbon and energy fluxes during the microbial growth on glucose. The model simulates aerobic respiration as well as anaerobic fermentation pathways to lactate, acetate and propionate depending on the time-varying availability of O2. Simulations captured the observed temporal CR pattern and suggested a gradual depletion of O2 and a shift to anaerobic pathways as the main driver. This interpretation is consistent with the dominance of Bacillota, many members of which are well adapted to anaerobic conditions. Our results highlight the potential of the joint analysis of matter and energy fluxes in combined experimental and modeling approaches and indicate the presence of facultative anaerobiosis under common experimental conditions, which could confer a competitive advantage to certain microbial taxa during growth on labile substrate.

Bifunctional alcohol/aldehyde dehydrogenase AdhE controls phospho-transferase system sugar utilization and virulence gene expression by interacting PtsH in Edwardsiella piscicida

The bifunctional alcohol/aldehyde dehydrogenase (AdhE), one of the key enzymes in the bacterial ethanol anaerobic fermentation pathway, is critical for appropriate expression of the genes for the utilization of carbon sources. Knowledge about its global roles in modulating gene expression and metabolomics remains limited. Edwardsiella bacteria includes several important zoonotic pathogenic species including Edwardsiella piscicida, a leading fish pathogen that causes severe economic losses in the aquaculture industry. It is well known to utilize few sugars. In this study, we showed that AdhE is involved in various processes including sugar utilization, bacteria growth, intracellular pH homeostasis, type III/VI secretion system (T3/T6SS) production, and survival in fish. Moreover, our unbiased metabolomics approaches revealed that AdhE modulates a large quantity of metabolic pathways, including amino acids, tricarboxylic acid (TCA) intermediates, sugar and fatty acids. Pull-down and Co-immunoprecipitation (IP) analysis revealed that AdhE interacts with the phospho-transferase system component PtsH that supports the transform of its PTS sugars including mannose to mannose-6P, the established metabolic ligand modulating EvrA activity to control T3/T6SS expression. Collectively, AdhE appears to play important roles in bacterial adapting to the internal environment changes by regulating sugar metabolic pathways and bacterial virulence expression. These observations support a model in which AdhE acts a macromolecule hub accommodating proteins to modulate the PTS and other signaling cascades related to pathogenesis and environmental adaptation in bacterial pathogens, which may provide new perspectives for attempts to attenuate bacterial virulence.

Electron flow: key to mitigating ruminant methanogenesis.

Disposal of electrons generated during the fermentation of ingested feed is a fundamental feature of anaerobic microbial gut ecosystems. Here, we focus on the well-studied rumen environment to highlight how electrons are transferred through anaerobic fermentation pathways and how manipulating this electron flow is important to reducing methane emissions from ruminants. Priorities for research that can accelerate understanding in this area are highlighted.

Independent Decompositions of Chemical Reaction Networks.

A chemical reaction network (CRN) is composed of reactions that can be seen as interactions among entities called species, which exist within the system. Endowed with kinetics, CRN has a corresponding set of ordinary differential equations (ODEs). In chemical reaction network theory, we are interested with connections between the structure of the CRN and qualitative properties of the corresponding ODEs. One of the results in decomposition theory of CRNs is that the intersection of the sets of positive steady states of the subsystems is equal to the set of positive steady states of the whole system, if the decomposition is independent. Hence, computational approach using independent decompositions can be used as an efficient tool in studying large systems. In this work, we provide a necessary and sufficient condition for the existence of a nontrivial independent decomposition of a CRN, which leads to a novel step-by-step method to obtain such decomposition, if it exists. We also illustrate these results using real-life examples. In particular, we show that a CRN of a popular model of anaerobic yeast fermentation pathway has a nontrivial independent decomposition, while a particular biological system, which is a metabolic network with one positive feedforward and a negative feedback has none. Finally, we analyze properties of positive steady states of reaction networks of specific influenza virus models.

Comparative analysis of maize root sRNA transcriptome unveils the regulatory roles of miRNAs in submergence stress response mechanism

Oxygen limitation under submerged condition induces hypoxic stress and causes a metabolic shift from aerobic respiration to anaerobic fermentation. Submergence stress often limits plant growth and causes substantial yield loss. The present small RNA (sRNA) transcriptome study aims to identify and characterise submergence responsive miRNAs to delineate the response mechanisms of maize seedlings to complete submergence. In this study, we constructed two sRNA libraries from control and submerged maize roots. Deep sequencing revealed 524 known (conserved and non-conserved) and 48 novel miRNAs from two libraries. Out of 188 commonly expressed known miRNAs, 45 miRNAs were found to be differentially expressed (43 down- and 2 up-regulated) in maize roots upon submergence. Submergence responsive miRNAs were found to be associated with diverse biological processes such as plant growth and development (miR172a, miR393b-3p), hormone signalling pathways (miR159c,f, miR160f-5p, miR167d-3p, miR172a, miR393a-5p), redox homeostasis (miR164a,b,c-5p, miR166h, a-3p, miR167e-3p.1), miRNA biogenesis (miR168a, miR168a-5p), chromatin remodeling (miR156a,g, miR159f, miR827-3p), and protein transport (miR156d-3p, miR159c,f, miR169c-3p). Moreover, dynamic correlations between selected miRNAs and their target genes were validated by qRT-PCR. The miR172a mediated upregulation of ERTF RAP2-7 ISOFORM X2 might be a pre-requisite for shifting of aerobic respiration to a less efficient anaerobic fermentation leading to restricted plant growth under flooded condition. To further understand the overall modulation of antioxidant defense system and metabolic adaptation strategy, fine tuning of ascorbate–glutathione cycle, anaerobic fermentation pathway genes, membrane damage, in vivo ROS detection and root MDA accumulation under flooding stress were also investigated in details. Taken together, our findings indicate that deregulation of ROS scavenging system might be the determining factor of meagre performance of maize seedlings under submerged condition. In a nutshell, our study adds new insights into the stress response mechanisms of maize seedlings towards submergence stress at post-transcriptional level.

A computational approach to multistationarity of power-law kinetic systems

This paper presents a computational solution to determine if a chemical reaction network endowed with power-law kinetics (PLK system) has the capacity for multistationarity, i.e., whether there exist positive rate constants such that the corresponding differential equations admit multiple positive steady states within a stoichiometric class. The approach, which is called the "Multistationarity Algorithm for PLK systems" (MSA), combines (i) the extension of the "higher deficiency algorithm" of Ji and Feinberg for mass action to PLK systems with reactant-determined interactions, and (ii) a method that transforms any PLK system to a dynamically equivalent one with reactant-determined interactions. Using this algorithm, we obtain two new results: the monostationarity of a popular model of anaerobic yeast fermentation pathway, and the multistationarity of a global carbon cycle model with climate engineering, both in the generalized mass action format of biochemical systems theory. We also provide examples of the broader scope of our approach for deficiency one PLK systems in comparison to the extension of Feinberg's "deficiency one algorithm" to such systems.

In silico profiling of cell growth and succinate production in Escherichia coli NZN111.

BackgroundSuccinic acid is a valuable product due to its wide-ranging utilities. To improve succinate production and reduce by-products formation, Escherichia coli NZN111 was constructed by insertional inactivation of lactate dehydrogenase (LDH) and pyruvate formate lyase (PFL) encoded by the genes ldhA and pflB, respectively. However, this double-deletion mutant is incapable of anaerobically growing on glucose in rich or minimal medium even with acetate supplementation. A widespread hold view is that the inactivation of NADH-dependent LDH limits the regeneration of NAD+ and consequently disables proper growth under anaerobic conditions.ResultsIn this study, genome-scale metabolic core model of E. coli was reconstructed and employed to perform all simulations in silico according to the reconstruction of engineered strain E. coli NZN111. Non-optimized artificial centering hit-and-run (ACHR) method and metabolite flux-sum analysis were utilized to evaluate metabolic characteristics of strains. Thus, metabolic characteristics of the strains wild-type E. coli, ldhA mutant, pflB mutant, and NZN111 under anaerobic conditions were successfully unraveled.Conclusions We found a viewpoint contrary to the widespread realization that an NADH/NAD+ in NZN111 mainly resulted from the inactivation of PFL rather than the inactivation of LDH. In addition, the two alternative anaerobic fermentation pathways, lactate and ethanol production pathways, were blocked owing to the disruption of ldhA and pflB, resulting in insufficient NAD+ regeneration to oxidize or metabolize glucose for cell growth. Furthermore, we speculated reaction NADH16, the conversion of ubiquinone-8 (q8) to ubiquinol-8 (q8h2), as a potential amplification target for anaerobically improving cell growth and succinate production in NZN111.Electronic supplementary materialThe online version of this article (doi:10.1186/s40643-016-0125-5) contains supplementary material, which is available to authorized users.

Tweaking Metabolic Networks: A Design Method

A robust synthesis technique is devised for synergism and saturation systems, commonly known as S-systems, for steering steady-states of the anaerobic fermentation pathway (AFP) of Saccharomyces cerevisae. The stability, steady-state error and robustness aspects are analyzed. The synthesis problem is framed in a computationally efficient convex optimization framework. The linear matrix inequalities are formulated for minimization of steady-state error, improvement of robustness and utilization of minimum control inputs ensuring the stability of the synthetic AFP.

Waterlogging-induced increase in fermentation and related gene expression in the root of cucumber (Cucumis sativus L.)

Waterlogging usually leads plant cells to shift their metabolism towards anaerobic fermentation pathways due to the hypoxia stress. The roles of two different levels of waterlogging treatments (water level was kept on the base of hypocotyls and on the base of the first true leaf) in induction of fermentation in waterlogged roots of cucumber line ‘Zaoer-N’ (waterlogging tolerant line) were examined. Root activities, numbers of dead cells, transcripts of genes encoding pyruvate decarboxylase (PDC), alcohol dehydrogenase (ADH) and lactate dehydrogenase (LDH), and activities of the PDC, ADH, and LDH enzymes, concentrations of acetaldehyde, alcohol and lactate were quantified during 48h of waterlogging, and 48h of subsequent recovery. The results showed that PDC, ADH, and LDH transcripts, activities of PDC, ADH and LDH, and concentrations of acetaldehyde, alcohol and lactate were upregulated or increased during waterlogging, and decreased with recovery time prolonged. The results revealed that waterlogging up to the base of first true leaf responded more severe than waterlogging up to the base of hypocotyls in root activity and numbers of dead cells, which were mainly caused by alcohol fermentation.

Production of n-butanol from biodiesel derived crude glycerol using Clostridium pasteurianum immobilized on Amberlite

This paper presents accounts of research on conversion of biodiesel derived crude glycerol to n-butanol via anaerobic fermentation pathway, using immobilized Clostridium pasteurianum cells. Experiments were done to optimize the growth conditions and growth medium, viz. Reinforced Clostridial Media (RCM) and Cooked Meat Media (CMM). Out of these two media, growth was found to be faster in RCM, which was used for experiments. The cells were immobilized on a hydrophilic support Amberlite, an ion exchange resin. Varying concentration of crude glycerol as a substrate was found to have significant effect on product profile with 25gL−1 glycerol giving maximum yield of n-butanol after 120h. High concentration of 150gL−1 glycerol exerted an inhibitory effect on n-butanol production with decreased 1,3-propanediol production, and absolutely no formation of ethanol. Maximum yield of ethanol and 1,3-propanediol was obtained with 5gL−1 and 10gL−1 crude glycerol respectively. To the best of our knowledge, this is the first report of use of the immobilized cells (immobilization of C. pasteurianum cells on Amberlite) for bioconversion of glycerol to butanol.

Isolation and characterization of Bradh1 gene encoding alcohol dehydrogenase from Chinese cabbage (Brassica rapa)

Alcohol dehydrogenase (E.C.1.1.1.1) is an enzyme present in higher plants involved in the anaerobic fermentation pathway that catalyzes the reduction of pyruvate to ethanol, resulting in continuous <TEX>$NAD^+$</TEX> regeneration. It also plays an important role in many plant developments including tolerance to anoxia condition. Here, a cDNA clone encoding alcohol dehydrogenase (ADH) was isolated from Chinese cabbage (Brassica rapa) seedlings. The gene named Bradh1 had a total length of 1,326 bp that contains a single open reading frame of 1,140 bp. The predicted protein consists of 379 amino acid residues with a calculated molecular mass of 41.17 kDa. Expression pattern analysis revealed a tissue-specific expressing gene in different tissues and strongly expressed in the shoot, roots and seeds of Chinese cabbage. Agrobacterium transformation of full-length cDNA Bradh1 into rice Gopumbyeo showed high efficiency. Furthermore, induction of ADH in transgenic rice enhanced tolerance to anaerobiosis stresses and elevated mRNA transcripts. The overexpression of Bradh1 in rice increases germination under anaerobiosis stresses, implying the possibility of developing new varieties suited for direct seeding or flood-prone rice field.

Outer approximation-based algorithm for biotechnology studies in systems biology

Optimization methods play a central role in systems biology studies as they can help in identifying key processes that can be experimentally changed so that specific biological goals can be attained. Standard optimization methods used in this field rely on simplified linear models that may fail in capturing the underlying complexity of the target metabolic network. Within this general context, we present a novel approach to globally optimize metabolic networks. The approach presented relies on (1) adopting a general modeling framework for metabolic networks: the Generalized Mass Action (GMA) representation; (2) posing the optimization task as a non-convex nonlinear programming (NLP) problem; and (3) devising an efficient solution method for globally optimizing the resulting NLP that embeds a GMA model of the metabolic network. The capabilities of our method are illustrated through two case studies: the anaerobic fermentation pathway in Saccharomyces cerevisiae and the citric acid production using Aspergillus niger. Numerical results show that the method presented provides near optimal solutions in low CPU times even in cases where the commercial global optimization package BARON fails to close the optimality gap.

Physiological and biochemical changes in plants under waterlogging

Waterlogging usually results from overuse and/or poor management of irrigation water and is a serious constraint with damaging effects. The rapidly depleting oxygen from submerged root zone is sensed and plant adjusts expressing anaerobic proteins. Plant cells shift their metabolism towards low energy yielding anaerobic fermentation pathways in the absence of oxygen. Structural modifications are also induced as aerenchyma formation and adventitious rootings, etc. Studies at molecular and biochemical levels to facilitate early perception and subsequent responses have also been worked out to produce resistant transgenic plants. This review explores the sequential changes of plant responses at different levels regarding their defense strategies and efforts made to enhance them, tailoring crucial regulators so that they can withstand waterlogging stress.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

BackgroundOptimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements.ResultsWe first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer-approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shockConclusionOur results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Structural and Kinetic Properties of a β-Hydroxyacid Dehydrogenase Involved in Nicotinate Fermentation

2-(Hydroxymethyl)glutarate dehydrogenase, the fourth enzyme of the anaerobic nicotinate fermentation pathway of Eubacterium barkeri, catalyzes the NADH-dependent conversion between (S)-2-formylglutarate and (S)-2-(hydroxymethyl)glutarate. As shown by its 2.3-Å crystal structure, this enzyme is a novel member of the β-hydroxyacid dehydrogenase family and adopts a tetrameric architecture with monomers interacting via their C-terminal catalytic domains. The NAD-binding domains protrude heterogeneously from the central, tetrameric core with domain rotation angles differing up to 12°. Kinetic properties of the enzyme, including NADH inhibition constants, were determined. A strong NADH binding in contrast to weaker NAD+ binding of the protein was inferred from fluorometrically determined binding constants for the dinucleotide cofactor. The data support either an Iso Ordered Bi Bi mechanism or a more common Ordered Bi Bi mechanism as found in other dehydrogenases.

Optimization of biotechnological systems through geometric programming

BackgroundIn the past, tasks of model based yield optimization in metabolic engineering were either approached with stoichiometric models or with structured nonlinear models such as S-systems or linear-logarithmic representations. These models stand out among most others, because they allow the optimization task to be converted into a linear program, for which efficient solution methods are widely available. For pathway models not in one of these formats, an Indirect Optimization Method (IOM) was developed where the original model is sequentially represented as an S-system model, optimized in this format with linear programming methods, reinterpreted in the initial model form, and further optimized as necessary.ResultsA new method is proposed for this task. We show here that the model format of a Generalized Mass Action (GMA) system may be optimized very efficiently with techniques of geometric programming. We briefly review the basics of GMA systems and of geometric programming, demonstrate how the latter may be applied to the former, and illustrate the combined method with a didactic problem and two examples based on models of real systems. The first is a relatively small yet representative model of the anaerobic fermentation pathway in S. cerevisiae, while the second describes the dynamics of the tryptophan operon in E. coli. Both models have previously been used for benchmarking purposes, thus facilitating comparisons with the proposed new method. In these comparisons, the geometric programming method was found to be equal or better than the earlier methods in terms of successful identification of optima and efficiency.ConclusionGMA systems are of importance, because they contain stoichiometric, mass action and S-systems as special cases, along with many other models. Furthermore, it was previously shown that algebraic equivalence transformations of variables are sufficient to convert virtually any types of dynamical models into the GMA form. Thus, efficient methods for optimizing GMA systems have multifold appeal.

Alternate metabolism during the dauer stage of the nematode Caenorhabditis elegans

When environmental conditions are unsuitable to support nematode reproduction, Caenorhabditis elegans arrests development before the onset of sexual maturity and specialised ‘dauer’ larvae, adapted for dispersal, and extended diapause are formed. Dauer larvae do not feed and their metabolism is dependent on internal food reserves. Adult worms which express defects in the insulin/insulin-like growth factor receptor DAF-2 also display enhanced longevity. Whole genome mRNA expression profiling has demonstrated that C. elegans dauer larvae and daf-2 adults have similar transcription profiles for a cohort of longevity genes. Important components of this enhanced longevity system are the α-crystallin family of small heat shock proteins, anti-ROS defence systems, increased activity of cellular detoxification processes and possibly also increased chromatin stability and decreased protein turnover. Anaerobic fermentation pathways are upregulated in dauer larvae, while long-lived daf-2 adults appear to have normal oxidative metabolism. Anabolic pathways are down regulated in dauer larvae (and possibly in daf-2 adults as well), and energy consumption appears to be diverted to enhanced cellular maintenance and detoxification processes in both systems.

Computation and analysis of time-dependent sensitivities in Generalized Mass Action systems

Understanding biochemical system dynamics is becoming increasingly important for insights into the functioning of organisms and for biotechnological manipulations, and additional techniques and methods are needed to facilitate investigations of dynamical properties of systems. Extensions to the method of Ingalls and Sauro, addressing time-dependent sensitivity analysis, provide a new tool for executing such investigations. We present here the results of sample analyses using time-dependent sensitivities for three model systems taken from the literature, namely an anaerobic fermentation pathway in yeast, a negative feedback oscillator modeling cell-cycle phenomena, and the Mitogen Activated Protein (MAP) kinase cascade. The power of time-dependent sensitivities is particularly evident in the case of the MAPK cascade. In this example it is possible to identify the emergence of a concentration of MAPKK that provides the best response with respect to rapid and efficient activation of the cascade, while over- and under-expression of MAPKK relative to this concentration have qualitatively different effects on the transient response of the cascade. Also of interest is the quite general observation that phase-plane representations of sensitivities in oscillating systems provide insights into the manner with which perturbations in the envelope of the oscillation result from small changes in initial concentrations of components of the oscillator. In addition to these applied analyses, we present an algorithm for the efficient computation of time-dependent sensitivities for Generalized Mass Action (GMA) systems, the most general of the canonical system representations of Biochemical Systems Theory (BST). The algorithm is shown to be comparable to, or better than, other methods of solution, as exemplified with three biochemical systems taken from the literature.

Anaerobic bio-hydrogen production from ethanol fermentation: the role of pH

Hydrogen was produced by an ethanol–acetate fermentation at pH of 5.0 ± 0.2 and HRT of 3 days. The yield of hydrogen was 100–200 ml g Glu −1 with a hydrogen content of 25–40%. This fluctuation in the hydrogen yield was attributed to the formation of propionate and the activity of hydrogen utilizing methanogens. The change in the operational pH for the inhibition of this methanogenic activity induced a change in the main fermentation pathway. In this study, the main products were butyrate, ethanol and propionate, in the pH ranges 4.0–4.5, 4.5–5.0 and 5.0–6.0, respectively. However, the activity of all the microorganisms was inhibited below pH 4.0. Therefore, pH 4.0 was regarded as the operational limit for the anaerobic bio-hydrogen production process. These results indicate that the pH plays an important role in determining the type of anaerobic fermentation pathway in anaerobic bio-hydrogen processes.

Signal-dependent phosphorylation of the membrane-bound NarX two-component sensor-transmitter protein of Escherichia coli: nitrate elicits a superior anion ligand response compared to nitrite.

The Nar two-component regulatory system, consisting of the dual sensor-transmitters NarX and NarQ and the dual response regulators NarL and NarP, controls the expression of various anaerobic respiratory pathway genes and fermentation pathway genes. Although both NarX and NarQ are known to detect the two environmental signals nitrate and nitrite, little is known regarding the sensitivity and selectivity of ligand for detection or activation of the sensor-transmitters. In this study, we have developed a sensitive anion-specific in vitro assay for NarX autophosphorylation by using Escherichia coli membranes highly enriched in the full-length NarX protein. In this ATP- and magnesium-dependent reaction, nitrate elicited a greater signal output (i.e., NarX autophosphorylation) than did nitrite. Nitrate stimulation occurred at concentrations as low as 5 microM, and the half-maximal level of NarX autophosphorylation occurred at approximately 35 microM nitrate. In contrast, nitrite-dependent stimulation was detected only at 500 microM, while 3.5 mM nitrite was needed to achieve half-maximal NarX autophosphorylation. Maximal nitrate- and nitrite-stimulated levels of NarX phosphorylation were five and two times, respectively, over the basal level of NarX autophosphorylation. The presence of Triton X-100 eliminated the nitrate-stimulated kinase activity and lowered the basal level of activity, suggesting that the membrane environment plays a crucial role in nitrate detection and/or regulation of kinase activity. These results provide in vitro evidence for the differential detection of dual signaling ligands by the NarX sensor-transmitter protein, which modulates the cytoplasmic NarX autokinase activity and phosphotransfer to NarL, the cognate response regulator.