A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber

Exploring Microbiological Dynamics in a Salt Cavern for Potential Hydrogen Storage Use

Hydrogen storage in salt caverns is important for supporting the energy transition. However, there is limited knowledge about microbial communities within these caverns and associated risks of hydrogen loss. In this study we characterised a salt-saturated brine from a salt cavern and found a high sulphate content (4.2 g/L) and low carbon content (84.9 mg/L inorganic, 7.61 mg/L organic). The brine contained both Bacteria and Archaea, and 16S rRNA gene analysis revealed a halophilic community with members of Acetohalobium, Thiohalorhabdus, Salinibacter and up to 40% of unknown sequences. Within the Archaea, Euryarchaeota and the symbiotic Nanohaloarcheaota were dominant. Growth experiments showed that some microbes are resistant to autoclaving and pass through 0.22 μm filters. Heyndrickxia-related colonies grew on aerobic plates up to 10% salt, indicating the presence of inactive spores. The highest anaerobic activity was observed at 30°C, including glucose- and yeast extract fermentation, hydrogen-oxidation, lactate-utilisation, methane- and acetate-formation and sulphate-reduction, which was observed up to 80°C. However, microbial activity was slow, with incubations taking up to 1 year to measure microbial products. This study indicates that artificial salt caverns are an extreme environment containing potential hydrogen-consuming microbes.

Unraveling the metabolic landscape of Exophiala spinifera strain FM: Model reconstruction, insights into biodesulfurization and beyond

Exophiala spinifera strain FM, a black yeast and melanized ascomycete, shows potential for oil biodesulfurization by utilizing dibenzothiophene (DBT) as its sole sulfur source. However, the specific pathway and enzymes involved in this process remain unclear due to limited genome sequencing and metabolic understanding of E. spinifera. In this study, we sequenced the complete genome of E. spinifera FM to construct the first genome-scale metabolic model (GSMM) for this organism. Through bioinformatics analysis, we identified genes potentially involved in DBT desulfurization and degradation pathways for hazardous pollutants. We focused on understanding the cost associated with metabolites in sulfur assimilation pathway to assess economic feasibility, optimize resource allocation, and guide metabolic engineering and process design. To overcome knowledge gaps, we developed a genome-scale model for E. spinifera, iEsp1694, enabling a comprehensive investigation into its metabolism. The model was rigorously validated against growth phenotypes and gene essentiality data. Through shadow price analysis, we identified costly metabolites such as 3'-phospho-5'-adenylyl sulfate, 5'-adenylyl sulfate, and choline sulfate when DBT was used as the sulfur source. iEsp1694 encompasses the degradation of aromatic compounds, which serves as a crucial first step in comprehending the pan metabolic capabilities of this strain.

Elucidating metabolic pathways through genomic analysis in highly heavy metal-resistant Halobacterium salinarum strains

The annotated and predicted genomes of five archaeal strains (AS1, AS2, AS8, AS11 and AS19), isolated from Sfax solar saltern sediments (Tunisia) and affiliated with Halobacterium salinarum, were performed by RAST webserver (Rapid Annotation using Subsystem Technology) and NCBI prokaryotic genome annotation pipeline (PGAP). The results showed the ability of strains to use a reduced semi-phosphorylative Entner-Doudoroff pathway for glucose degradation and an Embden-Meyerhof one for gluconeogenesis. They could use glucose, fructose, glycerol, and acetate as sole source of carbon and energy. ATP synthase, various cytochromes and aerobic respiration proteins were encoded. All strains showed fermentation capability through the arginine deiminase pathway and facultative anaerobic respiration using electron acceptors (Dimethyl sulfoxide and trimethylamine N-oxide). Several biosynthesis pathways for many amino acids were identified. Comparative and pangenome analyses between the strains and the well-studied halophilic archaea Halobacterium NRC-1 highlighted a notable dissimilarity. Besides, the strains shared a core genome of 1973 genes and an accessory genome of 767 genes. 129, 94, 67, 15 and 29 unique genes were detected in the AS1, AS2, AS8, AS11 and AS19 genomes, respectively. Most of these unique genes code for hypothetical proteins. The strains displayed plant-growth promoting characteristics under heavy metal stress (Ammonium assimilation, phosphate solubilization, chemotaxis, cell motility and production of indole acetic acid, siderophore and phenazine). Therefore, they could be used as a biofertilizer to promote plant growth. The genomes encoded numerous biotechnologically relevant genes responsible for vitamin biosynthesis, including cobalamin, folate, biotin, pantothenate, riboflavin, thiamine, menaquinone, nicotinate, and nicotinamide. The carotenogenetic pathway of the studied strains was also predicted. Consequently, the findings of this study contribute to a better understanding of the halophilic archaea metabolism providing valuable insights into their ecophysiology as well as relevant biotechnological applications.

Genome-scale metabolic modelling of extremophiles and its applications in astrobiological environments

Metabolic modelling approaches have become the powerful tools in modern biology. These mathematical models are widely used to predict metabolic phenotypes of the organisms or communities of interest, and to identify metabolic targets in metabolic engineering. Apart from a broad range of industrial applications, the possibility of using metabolic modelling in the contexts of astrobiology are poorly explored. In this mini-review, we consolidated the concepts and related applications of applying metabolic modelling in studying organisms in space-related environments, specifically the extremophilic microbes. We recapitulated the current state of the art in metabolic modelling approaches and their advantages in the astrobiological context. Our review encompassed the applications of metabolic modelling in the theoretical investigation of the origin of life within prebiotic environments, as well as the compilation of existing uses of genome-scale metabolic models of extremophiles. Furthermore, we emphasize the current challenges associated with applying this technique in extreme environments, and conclude this review by discussing the potential implementation of metabolic models to explore theoretically optimal metabolic networks under various space conditions. Through this mini-review, our aim is to highlight the potential of metabolic modelling in advancing the study of astrobiology.

A systems level approach to study metabolic networks in prokaryotes with the aromatic amino acid biosynthesis pathway

Metabolism of an organism underlies its phenotype, which depends on many factors, such as the genetic makeup, habitat, and stresses to which it is exposed. This is particularly important for the prokaryotes, which undergo significant vertical and horizontal gene transfers. In this study we have used the energy-intensive Aromatic Amino Acid (Tryptophan, Tyrosine and Phenylalanine, TTP) biosynthesis pathway, in a large number of prokaryotes, as a model system to query the different levels of organization of metabolism in the whole intracellular biochemical network, and to understand how perturbations, such as mutations, affects the metabolic flux through the pathway - in isolation and in the context of other pathways connected to it. Using an agglomerative approach involving complex network analysis and Flux Balance Analyses (FBA), of the Tryptophan, Tyrosine and Phenylalanine and other pathways connected to it, we identify several novel results. Using the reaction network analysis and Flux Balance Analyses of the Tryptophan, Tyrosine and Phenylalanine and the genome-scale reconstructed metabolic pathways, many common hubs between the connected networks and the whole genome network are identified. The results show that the connected pathway network can act as a proxy for the whole genome network in Prokaryotes. This systems level analysis also points towards designing functional smaller synthetic pathways based on the reaction network and Flux Balance Analyses analysis.

Metabolic Potential of Microbial Communities in the Hypersaline Sediments of the Bonneville Salt Flats

The Bonneville Salt Flats (BSF) appear to be entirely desolate when viewed from above, but they host rich microbial communities just below the surface salt crust. In this study, we investigated the metabolic potential of the BSF microbial ecosystem. The predicted and measured metabolic activities provide new insights into the ecosystem functions of evaporite landscapes and are an important analog for potential subsurface microbial ecosystems on ancient and modern Mars. Hypersaline and evaporite systems have been investigated previously as astrobiological analogs for Mars and other salty celestial bodies, but these studies have generally focused on aquatic systems and cultivation-dependent approaches. Here, we present an ecosystem-level examination of metabolic pathways within the shallow subsurface of evaporites. We detected aerobic and anaerobic respiration as well as methanogenesis in BSF sediments. Metagenome-assembled genomes of diverse bacteria and archaea encode a remarkable diversity of metabolic pathways, including those associated with carbon fixation, carbon monoxide oxidation, acetogenesis, methanogenesis, sulfide oxidation, denitrification, and nitrogen fixation. These results demonstrate the potential for multiple energy sources and metabolic pathways in BSF and highlight the possibility for vibrant microbial ecosystems in the shallow subsurface of evaporites. IMPORTANCE The Bonneville Salt Flats is a unique ecosystem created from 10,000 years of desiccation and serves as an important natural laboratory for the investigation of the habitability of salty, halite, and gypsum-rich environments. Here, we show that gypsum-rich mineral deposits host a surprising diversity of organisms and appear to play a key role in stimulating the microbial cycling of sulfur and nitrogen compounds. This work highlights how diverse microbial communities within the shallow subsurface sediments are capable of maintaining an active and sustainable ecosystem, even though the surface salt crust appears to be completely devoid of life.

Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways

Prediction and reconstruction of metabolic pathways play significant roles in many fields such as genetic engineering, metabolic engineering, drug discovery, and are becoming the most active research topics in synthetic biology. With the increase of related data and with the development of machine learning techniques, there have many machine leaning based methods been proposed for prediction or reconstruction of metabolic pathways. Machine learning techniques are showing state-of-the-art performance to handle the rapidly increasing volume of data in synthetic biology. To support researchers in this field, we briefly review the research progress of metabolic pathway reconstruction and prediction based on machine learning. Some challenging issues in the reconstruction of metabolic pathways are also discussed in this paper.