Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

Abstract

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

The methanogenic redox cofactor F420 is widely synthesized by aerobic soil bacteria

“…Taxonomic annotations for the sequences were obtained from the NCBI Taxonomy database and sequences duplicated at the species level were deleted. Clustering on sequence similarity networks (Atkinson et al, 2009) generated using the Enzyme Function-Initiative Enzyme Similarity Tool (Gerlt et al, 2015) were used to identify homologs of characterized proteins from nonspecific hits. In this analysis, nodes represent individual proteins and edges represent the all-versus-all BLAST E-values (Altschul et al, 1990) between them.…”

“…In this analysis, nodes represent individual proteins and edges represent the all-versus-all BLAST E-values (Altschul et al, 1990) between them. Closely related proteins form visual clusters, allowing the identification of sequences belonging to a protein family from those belonging to related families (Atkinson et al, 2009). Final sequence sets were obtained by decreasing logE-value cutoffs until no major changes in clustering were observed with large increases in cutoff value.…”

The Chlorite Dismutase (HemQ) from Staphylococcus aureus Has a Redox-sensitive Heme and Is Associated with the Small Colony Variant Phenotype

“…The resulting 5923 sequences were used to generate sequence similarity networks using previously published methods (31) and visualized using the Cytoscape program. Nodes in the network represent sequences, and edges represent BLAST E-values.…”

In-vitro Characterization of an L-Kynurenine-Responsive Transcription Regulator of the Oxidative Tryptophan Degradation Pathway in Burkholderia xenovorans

“…A sequence similarity network was constructed according to the method of Atkinson and coworkers (Atkinson, Morris, Ferrin, & Babbitt, 2009). Their method of independent pairwise alignments between sequences allows functional relationships to be observed over very large sets of evolutionarily related proteins, such as members of www.ccsenet.org/jmbr Journal of Molecular Biology Research Vol.…”

“…To examine this apparent discrepancy, we first carried out a sequence similarity network analysis (Atkinson et al, 2009) of COG 1522, which contains the diverse members of the AsnC/Lrp TR family in 66 genomes of unicellular organisms (Figure 3). Bxe_A0736 and the L-kynurenine responsive TR KynR from P. aeruginosa are together in group 24 while AsnC is in group 17.…”