Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi

Rational construction of synthetic consortia: Key considerations and model-based methods for guiding the development of a novel biosynthesis platform

The rapid development of synthetic biology has significantly improved the capabilities of mono-culture systems in converting different substrates into various value-added bio-chemicals through metabolic engineering. However, overexpression of biosynthetic pathways in recombinant strains can impose a heavy metabolic burden on the host, resulting in imbalanced energy distribution and negatively affecting both cell growth and biosynthesis capacity. Synthetic consortia, consisting of two or more microbial species or strains with complementary functions, have emerged as a promising and efficient platform to alleviate the metabolic burden and increase product yield. However, research on synthetic consortia is still in its infancy, with numerous challenges regarding the design and construction of stable synthetic consortia. This review provides a comprehensive comparison of the advantages and disadvantages of mono-culture systems and synthetic consortia. Key considerations for engineering synthetic consortia based on recent advances are summarized, and simulation and computational tools for guiding the advancement of synthetic consortia are discussed. Moreover, further development of more efficient and cost-effective synthetic consortia with emerging technologies such as artificial intelligence and machine learning is highlighted.

Phylogenetic diversity, distribution, and gene structure of the pyruvic oxime dioxygenase involved in heterotrophic nitrification

Some heterotrophic microorganisms carry out nitrification to produce nitrite and nitrate from pyruvic oxime. Pyruvic oxime dioxygenase (POD) is an enzyme that catalyzes the degradation of pyruvic oxime to pyruvate and nitrite from the heterotrophic nitrifying bacterium Alcaligenes faecalis. Sequence similarity searches revealed the presence of genes encoding proteins homologous to A. faecalis POD in bacteria of the phyla Proteobacteria and Actinobacteria and in fungi of the phylum Ascomycota, and their gene products were confirmed to have POD activity in recombinant experiments. Phylogenetic analysis further classified these POD homologs into three groups. Group 1 POD is mainly found in heterotrophic nitrifying Betaproteobacteria and fungi, and is assumed to be involved in heterotrophic nitrification. It is not clear whether group 2 POD, found mainly in species of the Gammaproteobacteria and Actinobacteria, and group 3 POD, found simultaneously with group 1 POD, are involved in heterotrophic nitrification. The genes of bacterial group 1 POD comprised a single transcription unit with the genes related to the metabolism of aromatic compounds, and many of the genes group 2 POD consisted of a single transcription unit with the gene encoding the protein homologous to 4-hydroxy-tetrahydrodipicolinate synthase (DapA). LysR- or Cro/CI-type regulatory genes were present adjacent to or in the vicinity of these POD gene clusters. POD may be involved not only in nitrification, but also in certain metabolic processes whose functions are currently unknown, in coordination with members of gene clusters.

Thermodynamic Analysis of Intermediary Metabolic Steps and Nitrous Oxide Production by Ammonium-Oxidizing Bacteria

Nitrous oxide (N₂O) is a greenhouse gas emitted from wastewater treatment, soils, and agriculture largely by ammonium-oxidizing bacteria (AOB). While AOB are characterized by being aerobes that oxidize ammonium (NH₄⁺) to nitrite (NO₂^-), fundamental studies in microbiology are revealing the importance of metabolic intermediates and reactions that can lead to the production of N₂O. These findings about the metabolic pathways for AOB were integrated with thermodynamic electron-equivalents modeling (TEEM) to estimate kinetic and stoichiometric parameters for each of the AOB's nitrogen (N)-oxidation and -reduction reactions. The TEEM analysis shows that hydroxylamine (NH₂OH) oxidation to nitroxyl (HNO) is the most energetically efficient means for the AOB to provide electrons for ammonium monooxygenation, while oxidations of HNO to nitric oxide (NO) and NO to NO₂^- are energetically favorable for respiration and biomass synthesis. The respiratory electron acceptor can be O₂ or NO, and both have similar energetics. The TEEM-predicted value for biomass yield, maximum-specific rate of NH₄⁺ utilization, and maximum specific growth rate are consistent with empirical observations. NO reduction to N₂O is thermodynamically favorable for respiration and biomass synthesis, but the need for O₂ as a reactant in ammonium monooxygenation likely precludes NO reduction to N₂O from becoming the major pathway for respiration.

Flux balance analysis of the ammonia-oxidizing bacterium Nitrosomonas europaea ATCC19718 unravels specific metabolic activities while degrading toxic compounds

The ammonia-oxidizing bacterium Nitrosomonas europaea has been widely recognized as an important player in the nitrogen cycle as well as one of the most abundant members in microbial communities for the treatment of industrial or sewage wastewater. Its natural metabolic versatility and extraordinary ability to degrade environmental pollutants (e.g., aromatic hydrocarbons such as benzene and toluene) enable it to thrive under various harsh environmental conditions. Constraint-based metabolic models constructed from genome sequences enable quantitative insight into the central and specialized metabolism within a target organism. These genome-scale models have been utilized to understand, optimize, and design new strategies for improved bioprocesses. Reduced modeling approaches have been used to elucidate Nitrosomonas europaea metabolism at a pathway level. However, genome-scale knowledge about the simultaneous oxidation of ammonia and pollutant metabolism of N. europaea remains limited. Here, we describe the reconstruction, manual curation, and validation of the genome-scale metabolic model for N. europaea, iGC535. This reconstruction is the most accurate metabolic model for a nitrifying organism to date, reaching an average prediction accuracy of over 90% under several growth conditions. The manually curated model can predict phenotypes under chemolithotrophic and chemolithoorganotrophic conditions while oxidating methane and wastewater pollutants. Calculated flux distributions under different trophic conditions show that several key pathways are affected by the type of carbon source available, including central carbon metabolism and energy production.

Nitrosomonas europaea catalyzes the first step of the nitrification process (ammonia to nitrite). It has been recognized as one of the most important members of microbial communities of wastewater treatment processes. Genome-scale models are powerful tools in process optimization since they can predict the organism’s behavior under different growth conditions. The final genome-scale model of N. europaea ATCC19718, iGC535, can predict growth and oxygen uptake rates with 90.52% accuracy under chemolithotrophic and chemolitoorganotrophic conditions. Moreover, iGC535 can predict the simultaneous oxidation of ammonia and wastewater pollutants, such as benzene, toluene, phenol and, chlorobenzene. iGC535 represents the most comprehensive knowledge-base for a nitrifying organism available to date. The genome-scale model reconstructed in this work brings us closer to understanding N. europaea’s role in a community with other nitrifying bacteria.

Investigating the Chemolithoautotrophic and Formate Metabolism of Nitrospira moscoviensis by Constraint-Based Metabolic Modeling and 13C-Tracer Analysis

Nitrite-oxidizing bacteria belonging to the genus Nitrospira mediate a key step in nitrification and play important roles in the biogeochemical nitrogen cycle and wastewater treatment. While these organisms have recently been shown to exhibit metabolic flexibility beyond their chemolithoautotrophic lifestyle, including the use of simple organic compounds to fuel their energy metabolism, the metabolic networks controlling their autotrophic and mixotrophic growth remain poorly understood. Here, we reconstructed a genome-scale metabolic model for Nitrospira moscoviensis (iNmo686) and used flux balance analysis to evaluate the metabolic networks controlling autotrophic and formatotrophic growth on nitrite and formate, respectively. Subsequently, proteomic analysis and [¹³C]bicarbonate and [¹³C]formate tracer experiments coupled to metabolomic analysis were performed to experimentally validate model predictions. Our findings corroborate that N. moscoviensis uses the reductive tricarboxylic acid cycle for CO₂ fixation, and we also show that N. moscoviensis can indirectly use formate as a carbon source by oxidizing it first to CO₂ followed by reassimilation, rather than direct incorporation via the reductive glycine pathway. Our study offers the first measurements of Nitrospira’s in vivo central carbon metabolism and provides a quantitative tool that can be used for understanding and predicting their metabolic processes.

IMPORTANCENitrospira spp. are globally abundant nitrifying bacteria in soil and aquatic ecosystems and in wastewater treatment plants, where they control the oxidation of nitrite to nitrate. Despite their critical contribution to nitrogen cycling across diverse environments, detailed understanding of their metabolic network and prediction of their function under different environmental conditions remains a major challenge. Here, we provide the first constraint-based metabolic model of Nitrospira moscoviensis representing the ubiquitous Nitrospira lineage II and subsequently validate this model using proteomics and ¹³C-tracers combined with intracellular metabolomic analysis. The resulting genome-scale model will serve as a knowledge base of Nitrospira metabolism and lays the foundation for quantitative systems biology studies of these globally important nitrite-oxidizing bacteria.

Towards a Systems Biology Approach to Understanding the Lichen Symbiosis: Opportunities and Challenges of Implementing Network Modelling

Lichen associations, a classic model for successful and sustainable interactions between micro-organisms, have been studied for many years. However, there are significant gaps in our understanding about how the lichen symbiosis operates at the molecular level. This review addresses opportunities for expanding current knowledge on signalling and metabolic interplays in the lichen symbiosis using the tools and approaches of systems biology, particularly network modelling. The largely unexplored nature of symbiont recognition and metabolic interdependency in lichens could benefit from applying a holistic approach to understand underlying molecular mechanisms and processes. Together with ‘omics’ approaches, the application of signalling and metabolic network modelling could provide predictive means to gain insights into lichen signalling and metabolic pathways. First, we review the major signalling and recognition modalities in the lichen symbioses studied to date, and then describe how modelling signalling networks could enhance our understanding of symbiont recognition, particularly leveraging omics techniques. Next, we highlight the current state of knowledge on lichen metabolism. We also discuss metabolic network modelling as a tool to simulate flux distribution in lichen metabolic pathways and to analyse the co-dependence between symbionts. This is especially important given the growing number of lichen genomes now available and improved computational tools for reconstructing such models. We highlight the benefits and possible bottlenecks for implementing different types of network models as applied to the study of lichens.

Metabolic modelling approaches for describing and engineering microbial communities

Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to growing awareness of their influence on a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications involving microorganisms, both in vivo and in silico, have been developed in the context of isolated microbes. In vivo microbial consortia development is extremely difficult and costly because it implies replicating suitable environments in the wet-lab. Computational approaches are thus a good, cost-effective alternative to study microbial communities, mainly via descriptive modelling, but also via engineering modelling. In this review we provide a detailed compilation of examples of engineered microbial communities and a comprehensive, historical revision of available computational metabolic modelling methods to better understand, and rationally engineer wild and synthetic microbial communities.

Understanding the metabolism of the tetralin degrader Sphingopyxis granuli strain TFA through genome-scale metabolic modelling

Sphingopyxis granuli strain TFA is an α-proteobacterium that belongs to the sphingomonads, a group of bacteria well-known for its degradative capabilities and oligotrophic metabolism. Strain TFA is the only bacterium in which the mineralisation of the aromatic pollutant tetralin has been completely characterized at biochemical, genetic, and regulatory levels and the first Sphingopyxis characterised as facultative anaerobe. Here we report additional metabolic features of this α-proteobacterium using metabolic modelling and the functional integration of genomic and transcriptomic data. The genome-scale metabolic model (GEM) of strain TFA, which has been manually curated, includes information on 743 genes, 1114 metabolites and 1397 reactions. This represents the largest metabolic model for a member of the Sphingomonadales order thus far. The predictive potential of this model was validated against experimentally calculated growth rates on different carbon sources and under different growth conditions, including both aerobic and anaerobic metabolisms. Moreover, new carbon and nitrogen sources were predicted and experimentally validated. The constructed metabolic model was used as a platform for the incorporation of transcriptomic data, generating a more robust and accurate model. In silico flux analysis under different metabolic scenarios highlighted the key role of the glyoxylate cycle in the central metabolism of strain TFA.

Transcriptomic Response of Nitrosomonas europaea Transitioned from Ammonia- to Oxygen-Limited Steady-State Growth

Nitrification is a ubiquitous microbially mediated process in the environment and an essential process in engineered systems such as wastewater and drinking water treatment plants. However, nitrification also contributes to fertilizer loss from agricultural environments, increasing the eutrophication of downstream aquatic ecosystems, and produces the greenhouse gas nitrous oxide. As ammonia-oxidizing bacteria are the most dominant ammonia-oxidizing microbes in fertilized agricultural soils, understanding their responses to a variety of environmental conditions is essential for curbing the negative environmental effects of nitrification. Notably, oxygen limitation has been reported to significantly increase nitric oxide and nitrous oxide production during nitrification. Here, we investigate the physiology of the best-characterized ammonia-oxidizing bacterium, Nitrosomonas europaea, growing under oxygen-limited conditions.

Ammonia-oxidizing microorganisms perform the first step of nitrification, the oxidation of ammonia to nitrite. The bacterium Nitrosomonas europaea is the best-characterized ammonia oxidizer to date. Exposure to hypoxic conditions has a profound effect on the physiology of N. europaea, e.g., by inducing nitrifier denitrification, resulting in increased nitric and nitrous oxide production. This metabolic shift is of major significance in agricultural soils, as it contributes to fertilizer loss and global climate change. Previous studies investigating the effect of oxygen limitation on N. europaea have focused on the transcriptional regulation of genes involved in nitrification and nitrifier denitrification. Here, we combine steady-state cultivation with whole-genome transcriptomics to investigate the overall effect of oxygen limitation on N. europaea. Under oxygen-limited conditions, growth yield was reduced and ammonia-to-nitrite conversion was not stoichiometric, suggesting the production of nitrogenous gases. However, the transcription of the principal nitric oxide reductase (cNOR) did not change significantly during oxygen-limited growth, while the transcription of the nitrite reductase-encoding gene (nirK) was significantly lower. In contrast, both heme-copper-containing cytochrome c oxidases encoded by N. europaea were upregulated during oxygen-limited growth. Particularly striking was the significant increase in transcription of the B-type heme-copper oxidase, proposed to function as a nitric oxide reductase (sNOR) in ammonia-oxidizing bacteria. In the context of previous physiological studies, as well as the evolutionary placement of N. europaea’s sNOR with regard to other heme-copper oxidases, these results suggest sNOR may function as a high-affinity terminal oxidase in N. europaea and other ammonia-oxidizing bacteria.

IMPORTANCE Nitrification is a ubiquitous microbially mediated process in the environment and an essential process in engineered systems such as wastewater and drinking water treatment plants. However, nitrification also contributes to fertilizer loss from agricultural environments, increasing the eutrophication of downstream aquatic ecosystems, and produces the greenhouse gas nitrous oxide. As ammonia-oxidizing bacteria are the most dominant ammonia-oxidizing microbes in fertilized agricultural soils, understanding their responses to a variety of environmental conditions is essential for curbing the negative environmental effects of nitrification. Notably, oxygen limitation has been reported to significantly increase nitric oxide and nitrous oxide production during nitrification. Here, we investigate the physiology of the best-characterized ammonia-oxidizing bacterium, Nitrosomonas europaea, growing under oxygen-limited conditions.

Metabolic and Proteomic Responses to Salinity in Synthetic Nitrifying Communities of Nitrosomonas spp. and Nitrobacter spp

Typically, nitrification is a two-stage microbial process and is key in wastewater treatment and nutrient recovery from waste streams. Changes in salinity represent a major stress factor that can trigger response mechanisms, impacting the activity and the physiology of bacteria. Despite its pivotal biotechnological role, little information is available on the specific response of nitrifying bacteria to varying levels of salinity. In this study, synthetic communities of ammonia-oxidizing bacteria (AOB Nitrosomonas europaea and/or Nitrosomonas ureae) and nitrite-oxidizing bacteria (NOB Nitrobacter winogradskyi and/or Nitrobacter vulgaris) were tested at 5, 10, and 30 mS cm^-1 by adding sodium chloride to the mineral medium (0, 40, and 200 mM NaCl, respectively). Ammonia oxidation activity was less affected by salinity than nitrite oxidation. AOB, on their own or in combination with NOB, showed no significant difference in the ammonia oxidation rate among the three conditions. However, N. winogradskyi improved the absolute ammonia oxidation rate of both N. europaea and N. ureae. N. winogradskyi’s nitrite oxidation rate decreased to 42% residual activity upon exposure to 30 mS cm^-1, also showing a similar behavior when tested with Nitrosomonas spp. The nitrite oxidation rate of N. vulgaris, as a single species, was not affected when adding sodium chloride up to 30 mS cm^-1, however, its activity was completely inhibited when combined with Nitrosomonas spp. in the presence of ammonium/ammonia. The proteomic analysis of a co-culture of N. europaea and N. winogradskyi revealed the production of osmolytes, regulation of cell permeability and an oxidative stress response in N. europaea and an oxidative stress response in N. winogradskyi, as a result of increasing the salt concentration from 5 to 30 mS cm^-1. A specific metabolic response observed in N. europaea suggests the role of carbon metabolism in the production of reducing power, possibly to meet the energy demands of the stress response mechanisms, induced by high salinity. For the first time, metabolic modifications and response mechanisms caused by the exposure to salinity were described, serving as a tool toward controllability and predictability of nitrifying systems exposed to salt fluctuations.

Preparation of Biocomposite Microfibers Ready for Processing into Biologically Active Textile Fabrics for Bioremediation

Biocomposites, i.e., materials consisting of metabolically active microorganisms embedded in a synthetic extracellular matrix, may find applications as highly specific catalysts in bioproduction and bioremediation. 3D constructs based on fibrous biocomposites, so-called "artificial biofilms," are of particular interest in this context. The inability to produce biocomposite fibers of sufficient mechanical strength for processing into bioactive fabrics has so far hindered progress in the area. Herein a method is proposed for the direct wet spinning of microfibers suitable for weaving and knitting. Metabolically active bacteria (either Shewanella oneidensis or Nitrobacter winogradskyi (N. winogradskyi)) are embedded in these fibers, using poly(vinyl alcohol) as matrix. The produced microfibers have a partially crystalline structure and are stable in water without further treatment, such as coating. In a first application, their potential for nitrite removal (N. winogradskyi) is demonstrated, a typical challenge in potable water treatment.