Reconstruction and analysis of a three‐compartment genome‐scale metabolic model for Pseudomonas fluorescens

Genome-scale metabolic network model and phenome of solvent-tolerant Pseudomonas putida S12

BACKGROUND

Pseudomonas putida S12 is a gram-negative bacterium renowned for its high tolerance to organic solvents and metabolic versatility, making it attractive for various applications, including bioremediation and the production of aromatic compounds, bioplastics, biofuels, and value-added compounds. However, a metabolic model of S12 has yet to be developed.

RESULTS

In this study, we present a comprehensive and highly curated genome-scale metabolic network model of S12 (iSH1474), containing 1,474 genes, 1,436 unique metabolites, and 2,938 metabolic reactions. The model was constructed by leveraging existing metabolic models and conducting comparative analyses of genomes and phenomes. Approximately 2,000 different phenotypes were measured for S12 and its closely related KT2440 strain under various nutritional and environmental conditions. These phenotypic data, combined with the reported experimental data, were used to refine and validate the reconstruction. Model predictions quantitatively agreed well with in vivo flux measurements and the batch cultivation of S12, which demonstrated that iSH1474 accurately represents the metabolic capabilities of S12. Furthermore, the model was simulated to investigate the maximum theoretical metabolic capacity of S12 growing on toxic organic solvents.

CONCLUSIONS

iSH1474 represents a significant advancement in our understanding of the cellular metabolism of P. putida S12. The combined results of metabolic simulation and comparative genome and phenome analyses identified the genetic and metabolic determinants of the characteristic phenotypes of S12. This study could accelerate the development of this versatile organism as an efficient cell factory for various biotechnological applications.

Synthetic biology tools for environmental protection

Synthetic biology transforms the way we perceive biological systems. Emerging technologies in this field affect many disciplines of science and engineering. Traditionally, synthetic biology approaches were commonly aimed at developing cost-effective microbial cell factories to produce chemicals from renewable sources. Based on this, the immediate beneficial impact of synthetic biology on the environment came from reducing our oil dependency. However, synthetic biology is starting to play a more direct role in environmental protection. Toxic chemicals released by industries and agriculture endanger the environment, disrupting ecosystem balance and biodiversity loss. This review highlights synthetic biology approaches that can help environmental protection by providing remediation systems capable of sensing and responding to specific pollutants. Remediation strategies based on genetically engineered microbes and plants are discussed. Further, an overview of computational approaches that facilitate the design and application of synthetic biology tools in environmental protection is presented.

Exploring novel Cr(VI) remediation genes for Cr(VI)-contaminated industrial wastewater treatment by comparative metatranscriptomics and metagenomics

Microbial remediation is a promising method to treat Cr(VI) in industrial wastewater. The remediation efficiency and stress-resistance ability of Cr(VI) remediation genes in microbes are the limiting factors for their application in industrial wastewater treatment. To screen novel highly efficient Cr(VI) remediation genes, comparative metatranscriptomic and metagenomic analyses were performed on long-term Cr(VI)-contaminated riparian soil with/without additional Cr(VI) treatment. The most suitable Cr(VI) treatment time was determined to be 30 min according to the high quality RNA yield and fold changes in gene expression. Six novel genes, which had complete open reading frames (ORFs) in metagenomic libraries, were identified from unculturable microbes. In the phenotypic functional assay, all novel genes enhanced the Cr(VI) resistance/reduction ability of E. coli. In the industrial wastewater treatment, E-mcr and E-gsr presented at least 50% Cr(VI) removal efficiencies in the presence of 200-600 μM of Cr(VI), without a decrease in efficiency over 17 days. The stress resistance assay showed that gsr increased the growth rate of E. coli by at least 30% under different extreme conditions, and thus, gsr was identified as a general stress-response gene. In the Cr valence distribution assay, E-mcr presented ~40 μM higher extracellular Cr (III) compared to E-yieF. Additionally, transmission electron microscopy (TEM) of E-mcr showed bulk black agglomerates on the cell surface. Thus, mcr was identified as a membrane chromate reductase gene. This research provides a new idea for studying novel highly efficient contaminant remediation genes from unculturable microbes.