Journal of Molecular Biology
Connectivity between Catalytic Landscapes of the Metallo-β-Lactamase Superfamily
Graphical abstract
Introduction
New enzymatic functions are thought to evolve through the recruitment and optimization of latent promiscuous functions of existing enzymes, leading to the functional expansion of superfamilies [1], [2], [3]. Closely related enzymes have shared promiscuous activities or crosswise promiscuity, as defined by each possessing a low level of catalytic activity against the other's native reaction [3], [4]. Thus, enzyme promiscuity can provide an additional layer of evolutionary connectivity between functional families in addition to their sequence and structural relationships. Systematic characterizations of substrate promiscuity among homologous and reconstructed ancestral enzymes have elucidated how substrate specificity has diverged within enzyme families [5], [6], [7], [8], [9], [10]. In addition, catalytic promiscuity, an enzyme's ability to catalyze distinct chemical reactions to their native one, provides functional connectivity between homologous enzymes [3], [11], [12], [13], [14], [15]. For example, lactonase, arylesterase and phosphotriesterase activities are shared among enzymes of the amidohydrolase superfamily [16], [17], [18]. Connectivity between phosphatase, phosphodiesterase, phosphonatase and arylsulfatase activities among members of the alkaline phosphatase superfamily has also been demonstrated [14], [19], [20], [21].
By extending Maynard-Smith's picture of a continuous network of functional proteins [22], we hypothesize that, through promiscuous enzymes, the shared and overlapping catalytic landscapes form a continuous network (Box 1). Therefore, within a given superfamily, functional changes can occur gradually and in a continuous manner [23]. Previous studies have focused on the connectivity between the native reactions of individual pairs of closely related homologues (~ 30% sequence identity) and included similar activities that share chemical properties such as transition-state geometry, hydrolyzable bond and bond charge [14], [16], [19], [20]. Hence, the extent to which catalytic landscapes are evolutionary and functionally connected, on a broad level that spans the vast sequence space of a functionally diverged superfamily, remains elusive.
The metallo-β-lactamase (MBL) superfamily served as our model enzyme superfamily. Members of the MBL superfamily are substantially diverged in sequence and function. Approximately 34,000 sequences are registered in the protein family database (Pfam) [24]. The amino acid sequence identity between members can be less than 5%, but members share structural features such as the αββα-fold (MBL fold) and a mononuclear or binuclear active-site center with a unique metal binding motif (H-X-H-X-D-H) [25] (Fig. 1 and Figs. S1 and S2). To date, at least 24 distinct functional families have been identified within the MBL superfamily, including DNA, RNA and nucleotide processing, detoxification, antibiotic resistance, quorum-quenching and pesticide hydrolysis [25], [26], [27], [28], [29], [30], [31], [32]. Most of these functions involve hydrolytic reactions and target diverse substrates with different chemical properties such as phosphodiester, phosphotriester, choline-phosphoester, thiol-ester, sulfate-ester, carbon-ester and β-lactam bond [25], [26], [27], [28], [29]. Other functions involve non-hydrolytic reactions such as nitric oxidoreduction [30] and sulfur dioxygenation [31], as well as non-enzymatic functions such as binding and transport [25], [32]. Many of the hydrolytic functions are amenable to characterization by simple colorimetric assays, which makes the MBL superfamily particularly well suited to analyze the connectivity of catalytic landscapes within a superfamily. In this study, we analyzed the sequence relationship within the MBL superfamily using sequence similarity networks, revealing evolutionary proximity among functional families. Furthermore, we assayed the activity profile of 24 MBL members from 15 different functional families for 10 catalytically distinct reactions. Finally, we relate the observed functional connections to evolutionary connections and chemical similarity between the reactions, and we discuss how the overlapped catalytic landscapes are related to evolutionary divergence and evolvability of the MBL superfamily.
Section snippets
Overview of the dataset and methodologies
To investigate the sequence relationship of MBL superfamily members, we retrieved 33,843 sequences from the Pfam database [24]. Due to high divergence and quantity of the sequences, conventional approaches to characterize evolutionary relationships, such as multiple sequence alignments and phylogenetic trees, were not applicable. As an alternative, we employed sequence similarity networks to show the relationships between sequences, described as independent pairwise alignments using the BLAST
Discussion
What is the molecular basis for the observed catalytic promiscuity and connectivity between the catalytic landscapes? Most members of the MBL superfamily possess a binuclear active-site center (generally two Zn2 + ions), which plays an essential role in catalysis by activating a water molecule for a nucleophilic attack and stabilizing the charge of the ground and/or transition state. The same mechanistic feature seems to be used for promiscuous activities because metal ions appear to be critical
Construction of sequence similarity networks
The pipeline to generate sequence similarity networks was adapted from Atkinson et al. [34]. In detail, 33,843 amino acid sequences of the MBL superfamily (Pfam IDs PF00753, PF12706 and PF13483) were retrieved from the Pfam database [24] on the 15th of June 2012. To facilitate further analysis, we extracted a representative set from the initial set (33,843 sequences) by applying a sequence identity threshold of 50% using CD-Hit [62]. Subsequently, we manually added the amino acid sequences of
Acknowledgements
We thank Janine N. Copp, Lindsay Eltis, Bert van Loo, Charlotte Miton, Joelle Pelletier, Roland Scholz, Dan S. Tawfik and members of the Tokuriki laboratory for useful comments on the manuscript. We thank Geoffrey Woollard for his help with structural bioinformatics and Anne Marie Di Guilmi, Wayne F. Anderson and Kurt Faber for providing plasmids containing the genes of PDB IDs 1wra, 1zkp and 2cfu, respectively. This work was supported by the Canadian Institute of Health Research and the Human
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