Sulfate-dependant microbially induced corrosion of mild steel in the deep sea: a 10-year microbiome study

Background Metal corrosion in seawater has been extensively studied in surface and shallow waters. However, infrastructure is increasingly being installed in deep-sea environments, where extremes of temperature, salinity, and high hydrostatic pressure increase the costs and logistical challenges associated with monitoring corrosion. Moreover, there is currently only a rudimentary understanding of the role of microbially induced corrosion, which has rarely been studied in the deep-sea. We report here an integrative study of the biofilms growing on the surface of corroding mooring chain links that had been deployed for 10 years at ~2 km depth and developed a model of microbially induced corrosion based on flux-balance analysis. Methods We used optical emission spectrometry to analyze the chemical composition of the mooring chain and energy-dispersive X-ray spectrometry coupled with scanning electron microscopy to identify corrosion products and ultrastructural features. The taxonomic structure of the microbiome was determined using shotgun metagenomics and was confirmed by 16S amplicon analysis and quantitative PCR of the dsrB gene. The functional capacity was further analyzed by generating binned, genomic assemblies and performing flux-balance analysis on the metabolism of the dominant taxa. Results The surface of the chain links showed intensive and localized corrosion with structural features typical of microbially induced corrosion. The microbiome on the links differed considerably from that of the surrounding sediment, suggesting selection for specific metal-corroding biofilms dominated by sulfur-cycling bacteria. The core metabolism of the microbiome was reconstructed to generate a mechanistic model that combines biotic and abiotic corrosion. Based on this metabolic model, we propose that sulfate reduction and sulfur disproportionation might play key roles in deep-sea corrosion. Conclusions The corrosion rate observed was higher than what could be expected from abiotic corrosion mechanisms under these environmental conditions. High corrosion rate and the form of corrosion (deep pitting) suggest that the corrosion of the chain links was driven by both abiotic and biotic processes. We posit that the corrosion is driven by deep-sea sulfur-cycling microorganisms which may gain energy by accelerating the reaction between metallic iron and elemental sulfur. The results of this field study provide important new insights on the ecophysiology of the corrosion process in the deep sea.

Critical assessment of genome-scale metabolic models of Arabidopsis thaliana

Genome-scale metabolic models (GSMMs) have enabled researchers to perform systems-level studies of living organisms. As a constraint-based technique, flux balance analysis (FBA) aids computation of reaction fluxes and prediction of...

Vitreoscilla Haemoglobin: A Tool to Reduce Overflow Metabolism

Overflow metabolism is a phenomenon extended in nature, ranging from microbial to cancer cells. Accumulation of overflow metabolites pose a challenge for large-scale bioprocesses. Yet, the causes of overflow metabolism are not fully clarified. In this work, the underlying mechanisms, reasons and consequences of overflow metabolism in different organisms have been summarized. The reported effect of aerobic expression of Vitreoscilla haemoglobin (VHb) in different organisms are revised. The use of VHb to reduce overflow metabolism is proposed and studied through flux balance analysis in E. coli at a fixed maximum substrate and oxygen uptake rates. Simulations showed that the presence of VHb increases the growth rate, while decreasing acetate production, in line with the experimental measurements. Therefore, aerobic VHb expression is considered a potential tool to reduce overflow metabolism in cells.

Spatial resolution of an integrated C4+CAM photosynthetic metabolism

C4 and CAM photosynthesis have repeatedly evolved in plants over the past 30 million years. Because both repurpose the same set of enzymes but differ in their spatial and temporal deployment, they have long been considered as distinct and incompatible adaptations. Remarkably, Portulaca contains multiple C4 species that perform CAM when droughted. Spatially explicit analyses of gene expression reveal that C4 and CAM systems are completely integrated in P. oleracea, with CAM and C4 carbon fixation occurring in the same cells and CAM-generated metabolites likely incorporated directly into the C4 cycle. Flux balance analysis corroborates the gene expression and predicts an integrated C4+CAM system under drought. This first spatially explicit description of a C4+CAM photosynthetic metabolism presents a new blueprint for crop improvement.

Optimality of extracellular enzyme production and activity in dynamic flux balance modeling

In microbial communities, many vital metabolic functions, including the degradation of cellulose, proteins and other complex macromolecules, are carried out by costly, extracellularly secreted enzymes. While significant effort has been dedicated to analyzing genome-scale metabolic networks for individual microbes and communities, little is known about the interplay between global allocation of metabolic resources in the cell and extracellular enzyme secretion and activity. Here we introduce a method for modeling the secretion and catalytic functions of extracellular enzymes using dynamic flux balance analysis. This new addition, implemented within COMETS (Computation Of Microbial Ecosystems in Time and Space), simulates the costly production and secretion of enzymes and their diffusion and activity throughout the environment, independent of the producing organism. After tuning our model based on data for a Saccharomyces cerevisiae strain engineered to produce exogenous cellulases, we explored the dynamics of the system at different cellulose concentrations and enzyme production rates. We found that there are distinct rates of constitutive enzyme secretion which maximize either growth rate or biomass yield. These optimal rates are strongly dependent on enzyme kinetic properties and environmental conditions, including the amount of cellulose substrate available. Our framework will facilitate the development of more realistic simulations of microbial community dynamics within environments rich in complex macromolecules, with applications in the study of soil and plant-associated ecosystems, and other natural and engineered microbiomes.

Sulfate-dependant microbially induced corrosion of mild steel in the deep-sea: a 10-year microbiome study

Background Metal corrosion in seawater has been extensively studied in surface and shallow waters. However, infrastructure is increasingly being installed in deep-sea environments, where extremes of temperature, salinity and high hydrostatic pressure increase the costs and logistical challenges associated with monitoring corrosion. Moreover, there is currently only a rudimentary understanding of the role of microbially induced corrosion, which has rarely been studied in the deep-sea. We report here an integrative study of the biofilms growing on the surface of corroding mooring chain links that had been deployed for 10 years at ~2 km depth and developed a model of microbially induced corrosion based on flux-balance analysis. Methods We used optical emission spectrometry to analyse the chemical composition of the mooring chain and energy-dispersive X-ray spectrometry coupled with scanning electron microscopy to identify corrosion products and ultrastructural features. The taxonomic structure of the microbiome was determined using shotgun metagenomics and was confirmed by 16S amplicon analysis and quantitative PCR of the dsrB gene. The functional capacity was further analysed by generating binned, genomic assemblies and performing flux-balance analysis on the metabolism of the dominant taxa. Results The surface of the chain links showed intensive and localised corrosion with structural features typical of microbially induced corrosion. The microbiome on the links differed considerably from that of the surrounding sediment, suggesting selection for specific metal-corroding biofilms dominated by sulfur-cycling bacteria. The core metabolism of the microbiome was reconstructed to generate a mechanistic model that combines biotic and abiotic corrosion. Based on this metabolic model, we propose that sulfate reduction and sulfur disproportionation might play key roles in deep-sea corrosion. Conclusions The corrosion rate observed was higher than what could be expected from abiotic corrosion mechanisms under these environmental conditions. High corrosion rate and the form of corrosion (deep pitting) suggest that the corrosion of the chain links was driven by both abiotic and biotic processes. We posit that the corrosion is driven by deep-sea sulfur-cycling microorganisms which may gain energy by accelerating the reaction between metallic iron and elemental sulfur. The results of this field study provide important new insights on the ecophysiology of the corrosion process in the deep sea.

Klimapflanzen und biologische Wege zu negativen Kohlendioxidemissionen

Climate plants are critical to prevent global warming as all efforts to save carbon dioxide are too slow and climate disasters on the rise. For best carbon dioxide harvesting we compare algae, trees and crop plants and use metagenomic analysis of environmental samples. We compare different pathways, carbon harvesting potentials of different plants as well as synthetic modifications including carbon dioxide flux balance analysis. For implementation, agriculture and modern forestry are important.

Metabolic engineering design to enhance (R,R)-2,3-butanediol production from glycerol in Bacillus subtilis based on flux balance analysis

Background Glycerol is a desirable alternative substrate for 2,3-butanediol (2,3-BD) production for sustainable development in biotechnological industries and non-food competitive feedstock. B. subtilis, a “generally recognized as safe” organism that is highly tolerant to fermentation products, is an ideal platform microorganism to engineer the pathways for the production of valuable bio-based chemicals, but it has never been engineered to improve 2,3-BD production from glycerol. In this study, we aimed to enhance 2,3-BD production from glycerol in B. subtilis through in silico analysis. Genome-scale metabolic model (GSM) simulations was used to design and develop the metabolic pathways of B. subtilis. Flux balance analysis (FBA) simulation was used to evaluate the effects of step-by-step gene knockouts to improve 2,3-BD production from glycerol in B. subtilis. Results B. subtilis was bioengineered to enhance 2,3-BD production from glycerol using FBA in a published GSM model of B. subtilis, iYO844. Four genes, ackA, pta, lctE, and mmgA, were knocked out step by step, and the effects thereof on 2,3-BD production were evaluated. While knockout of ackA and pta had no effect on 2,3-BD production, lctE knockout led to a substantial increase in 2,3-BD production. Moreover, 2,3-BD production was improved by mmgA knockout, which had never been investigated. In addition, comparisons between in silico simulations and fermentation profiles of all B. subtilis strains are presented in this study. Conclusions The strategy developed in this study, using in silico FBA combined with experimental validation, can be used to optimize metabolic pathways for enhanced 2,3-BD production from glycerol. It is expected to provide a novel platform for the bioengineering of strains to enhance the bioconversion of glycerol into other highly valuable chemical products.