Cofactor F420-dependent enzymes: An under-explored resource for asymmetric redox biocatalysis

The asymmetric reduction of enoates, imines and ketones are among the most important reactions in biocatalysis. These reactions are routinely conducted using enzymes that use nicotinamide cofactors as reductants. The deazaflavin cofactor F420 also has electrochemical properties that make it suitable as an alternative to nicotinamide cofactors for use in asymmetric reduction reactions. However, cofactor F420-dependent enzymes remain under-explored as a resource for biocatalysis. This review considers the cofactor F420-dependent enzyme families with the greatest potential for the discovery of new biocatalysts: the flavin/deazaflavin-dependent oxidoreductases (FDORs) and the luciferase-like hydride transferases (LLHTs). The characterized F420-dependent reductions that have the potential for adaptation for biocatalysis are discussed, and the enzymes best suited for use in the reduction of oxidized cofactor F420 to allow cofactor recycling in situ are considered. Further discussed are the recent advances in the production of cofactor F420 and its functional analog FO-5′-phosphate, which remains an impediment to the adoption of this family of enzymes for industrial biocatalytic processes. Finally, the prospects for the use of this cofactor and dependent enzymes as a resource for industrial biocatalysis are discussed

ToMI-FBA: A genome-scale metabolic flux based algorithm to select optimum hosts and media formulations for expressing pathways of interest

The Total Membrane Influx constrained Flux Balance Analysis (ToMI-FBA) algorithm was developed in this research as a new tool to help researchers decide which microbial host and medium formulation are optimal for expressing a new metabolic pathway. ToMI-FBA relies on genome-scale metabolic flux modeling and a novel in silico cell membrane influx constraint that specifies the flux of atoms (not molecules) into the cell through all possible membrane transporters. The ToMI constraint is constructed through the addition of an extra row and column to the stoichiometric matrix of a genome-scale metabolic flux model. In this research, the mathematical formulation of the ToMI constraint is given along with four case studies that demonstrate its usefulness. In Case Study 1, ToMI-FBA returned an optimal culture medium formulation for the production of isobutanol from Bacillus subtilis. Significant levels of L-valine were recommended to optimize production, and this result has been observed experimentally. In Case Study 2, it is demonstrated how the carbon to nitrogen uptake ratio can be specified as an additional ToMI-FBA constraint. This was investigated for maximizing medium chain length polyhydroxyalkanoates (mcl-PHA) production from Pseudomonas putida KT2440. In Case Study 3, ToMI-FBA revealed a strategy of adding cellobiose as a means to increase ethanol selectivity during the stationary growth phase of Clostridium acetobutylicum ATCC 824. This strategy was also validated experimentally. Finally, in Case Study 4, B. subtilis was identified as a superior host to Escherichia coli, Saccharomyces cerevisiae, and Synechocystis PCC6803 for the production of artemisinate

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 \u27omics\u27 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

Improved production of the non-native cofactor F420 in Escherichia coli

The deazaflavin cofactor F420 is a low-potential, two-electron redox cofactor produced by some Archaea and Eubacteria that is involved in methanogenesis and methanotrophy, antibiotic biosynthesis, and xenobiotic metabolism. However, it is not produced by bacterial strains commonly used for industrial biocatalysis or recombinant protein production, such as Escherichia coli, limiting our ability to exploit it as an enzymatic cofactor and produce it in high yield. Here we have utilized a genome-scale metabolic model of E. coli and constraint-based metabolic modelling of cofactor F420 biosynthesis to optimize F420 production in E. coli. This analysis identified phospho-enol pyruvate (PEP) as a limiting precursor for F420 biosynthesis, explaining carbon source-dependent differences in productivity. PEP availability was improved by using gluconeogenic carbon sources and overexpression of PEP synthase. By improving PEP availability, we were able to achieve a ~ 40-fold increase in the space–time yield of F420 compared with the widely used recombinant Mycobacterium smegmatis expression system. This study establishes E. coli as an industrial F420-production system and will allow the recombinant in vivo use of F420-dependent enzymes for biocatalysis and protein engineering applications.</p

MOESM2 of Assessing methanotrophy and carbon fixation for biofuel production by Methanosarcina acetivorans

Additional file 2. M. acetivorans gene re-annotation list

MOESM1 of Reversing methanogenesis to capture methane for liquid biofuel precursors

Additional file 1. This file consists of four supplemental tables and six supplemental figures. Table S1 lists the components in the HS medium used to grow ANME-1 Mcr-producing M. acetivorans on methane and 0.1 mM or 10 mM FeCl3. Table S2 shows the fold changes of differentially expressed genes in M. acetivorans/pES1-MATmcr3 grown on methane and 0.1 mM FeCl3, in comparison to the same strain grown on methanol. Table S3 lists the strains and plasmids, and Table S4 lists the oligonucleotides, used in this study. Figure S1 shows the three promoters used to express ANME-1 mcrBGA genes. Figure S2 shows the detected McrA-FLAG in M. acetivorans/pES1-MATmcr3-flag grown on methane after five days. Figure S3 shows the detection of ANME-1 mcrA after 30 days of growth on methane. Figure S4 shows the GC/MS spectra of culture supernatants used to identify acetate from H13CO. Figure S5 shows the flux through the various reactions in the methanogenesis pathway of M. acetivorans estimated by 13C-metabolic flux analysis using 13C-labeled bicarbonate as the input tracer. Figure S6 shows a simplified methanogenesis pathway from CO2 and CH3OH of M. acetivorans