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Experimental strategies for functional annotation and metabolism discovery: targeted screening of solute binding proteins and unbiased panning of metabolomes

Vetting MW, Al-Obaidi N, Zhao S, San Francisco B, Kim J, Wichelecki DJ, Bouvier JT, Solbiati JO, Vu H, Zhang X, Rodionov DA, Love JD, Hillerich BS, Seidel RD, Quinn RJ, Osterman AL, Cronan JE, Jacobson MP, Gerlt JA, Almo SC (2014) Biochemistry, 54, 909-93

This Current Topic An impressive accumulation of work from several EFI cores and projects, this publication showcases the EFI's new focus on mining transporter-containing gene clusters for novel metabolic pathways. This technique represents a dramatic shift away from restricting discovery to specifc enzyme superfamilies. When targeted via the ligand/metabolite screening platform discussed here, transporters have been extremely fruitful at providing the starting point for downstream pathway discovery.  

Abstract

The rate at which genome sequencing data is accruing demands enhanced methods for functional annotation and metabolism discovery. Solute binding proteins (SBPs) facilitate the transport of the first reactant in a metabolic pathway, thereby constraining the regions of chemical space and the chemistries that must be considered for pathway reconstruction. We describe high-throughput protein production and differential scanning fluorimetry platforms, which enabled the screening of 158 SBPs against a 189 component library specifically tailored for this class of proteins. Like all screening efforts, this approach is limited by the practical constraints imposed by construction of the library, i.e., we can study only those metabolites that are known to exist and which can be made in sufficient quantities for experimentation. To move beyond these inherent limitations, we illustrate the promise of crystallographic- and mass spectrometric-based approaches for the unbiased use of entire metabolomes as screening libraries. Together, our approaches identified 40 new SBP ligands, generated experiment-based annotations for 2084 SBPs in 71 isofunctional clusters, and defined numerous metabolic pathways, including novel catabolic pathways for the utilization of ethanolamine as sole nitrogen source and the use of d-Ala-d-Ala as sole carbon source. These efforts begin to define an integrated strategy for realizing the full value of amassing genome sequence data.

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Abstract Image

Figure 1: TRAP SBP ligands and structures prior to this study. TRAP SBP SSN network at an e-value of 10–120. In the network, each node is labeled with its cluster number, and each color represents a unique function (see Table S2 for ligand to color mapping).

Figure 2: Schematic of TRAP SBP ligands determined in this study. These ligands were determined either by DSF and/or were co-purified (CO) ligands observed by crystallography.

Figure 3: Annotated 10–120 TRAP SBP SSN network with data from this study. Targets are colored by ligand(s).

Figure 4: DSF of the TRAP SBP BH2673 from Bacillus halodurans. Denaturation of BH2673 as a function of temperature as observed by increase in fluorescence of the indicator dye SYPRO Orange, which binds nonspecifically to hydrophobic surfaces.

Figure 5: Functional implications from d-glucuronate/d-galacturonate TRAP SBPs.

Figure 6: Functional implications from l-galactonate/l-gulonate TRAP SBPs.

Figure 7: Functional implications from d-Ala-d-Ala TRAP SBPs.

Figure 8: TRAP SBP co-purified ligands. Omit maps for adventitiously bound ligands contoured at 3 RMSD and the associated TRAP SBPs genomic environment.

Figure 9: Functional implications from ethanolamine TRAP SBP.

Reprinted with permission from Vetting et al. Biochemistry 54, Epub ahead of print. Copyright 2014 American Chemical Society.