Michael A. Hicks

The Structure–Function Linkage Database

The Structure–Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure–function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies ‘look alike’, making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity.

Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites

Genetic factors modifying the blood metabolome have been investigated through genome-wide association studies (GWAS) of common genetic variants and through exome sequencing. We conducted a whole-genome sequencing study of common, low-frequency and rare variants to associate genetic variations with blood metabolite levels using comprehensive metabolite profiling in 1,960 adults. We focused the analysis on 644 metabolites with consistent levels across three longitudinal data collections. Genetic sequence variations at 101 loci were associated with the levels of 246 (38%) metabolites (P ≤ 1.9 × 10−11). We identified 113 (10.7%) among 1,054 unrelated individuals in the cohort who carried heterozygous rare variants likely influencing the function of 17 genes. Thirteen of the 17 genes are associated with inborn errors of metabolism or other pediatric genetic conditions. This study extends the map of loci influencing the metabolome and highlights the importance of heterozygous rare variants in determining abnormal blood metabolic phenotypes in adults.

The evolution of function in strictosidine synthase-like proteins.

The exponential growth of sequence data provides abundant information for the discovery of new enzyme reactions. Correctly annotating the functions of highly diverse proteins can be difficult, however, hindering use of this information. Global analysis of large superfamilies of related proteins is a powerful strategy for understanding the evolution of reactions by identifying catalytic commonalities and differences in reaction and substrate specificity, even when only a few members have been biochemically or structurally characterized. A comparison of >2500 sequences sharing the six‐bladed β‐propeller fold establishes sequence, structural, and functional links among the three subgroups of the functionally diverse N6P superfamily: the arylesterase‐like and senescence marker protein‐30/gluconolactonase/luciferin‐regenerating enzyme‐like (SGL) subgroups, representing enzymes that catalyze lactonase and related hydrolytic reactions, and the so‐called strictosidine synthase‐like (SSL) subgroup. Metal‐coordinating residues were identified as broadly conserved in the active sites of all three subgroups except for a few proteins from the SSL subgroup, which have been experimentally determined to catalyze the quite different strictosidine synthase (SS) reaction, a metal‐independent condensation reaction. Despite these differences, comparison of conserved catalytic features of the arylesterase‐like and SGL enzymes with the SSs identified similar structural and mechanistic attributes between the hydrolytic reactions catalyzed by the former and the condensation reaction catalyzed by SS. The results also suggest that despite their annotations, the great majority of these >500 SSL sequences do not catalyze the SS reaction; rather, they likely catalyze hydrolytic reactions typical of the other two subgroups instead. This prediction was confirmed experimentally for one of these proteins. Proteins 2011;.

Mechanistic and bioinformatic investigation of a conserved active site helix in α-isopropylmalate synthase from mycobacterium tuberculosis, a member of the DRE-TIM metallolyase superfamily

The characterization of functionally diverse enzyme superfamilies provides the opportunity to identify evolutionarily conserved catalytic strategies, as well as amino acid substitutions responsible for the evolution of new functions or specificities. Isopropylmalate synthase (IPMS) belongs to the DRE-TIM metallolyase superfamily. Members of this superfamily share common active site elements, including a conserved active site helix and an HXH divalent metal binding motif, associated with stabilization of a common enolate anion intermediate. These common elements are overlaid by variations in active site architecture resulting in the evolution of a diverse set of reactions that include condensation, lyase/aldolase, and carboxyl transfer activities. Here, using IPMS, an integrated biochemical and bioinformatics approach has been utilized to investigate the catalytic role of residues on an active site helix that is conserved across the superfamily. The construction of a sequence similarity network for the DRE-TIM metallolyase superfamily allows for the biochemical results obtained with IPMS variants to be compared across superfamily members and within other condensation-catalyzing enzymes related to IPMS. A comparison of our results with previous biochemical data indicates an active site arginine residue (R80 in IPMS) is strictly required for activity across the superfamily, suggesting that it plays a key role in catalysis, most likely through enolate stabilization. In contrast, differential results obtained from substitution of the C-terminal residue of the helix (Q84 in IPMS) suggest that this residue plays a role in reaction specificity within the superfamily.

Bioprospecting in the genomic age.

The genomic revolution promises great advances in the search for useful biocatalysts. Function-based metagenomic approaches have identified several enzymes with properties that make them useful candidates for a variety of bioprocesses. As DNA sequencing costs continue to decline, the volume of genomic data, along with their corresponding predicted protein sequences, will continue to increase dramatically, necessitating new approaches to leverage this information for gene-based bioprospecting efforts. Additionally, as new functions are discovered and correlated with this sequence information, the knowledge of the often complex relationship between a proteins sequence and function will improve. This in turn will lead to better gene-based bioprospecting approaches and facilitate the tailoring of desired properties through protein engineering projects. In this chapter, we discuss a number of recent advances in bioprospecting within the context of the genomic age.

Porting the synthetic D-glucaric acid pathway from Escherichia coli to Saccharomyces cerevisiae

D-Glucaric acid can be produced as a value-added chemical from biomass through a de novo pathway in Escherichia coli. However, previous studies have identified pH-mediated toxicity at product concentrations of 5 g/L and have also found the eukaryotic myo-inositol oxygenase (MIOX) enzyme to be rate-limiting. We ported this pathway to Saccaromyces cerevisiae, which is naturally acid-tolerant and evaluate a codon-optimized MIOX homologue. We constructed two engineered yeast strains that were distinguished solely by their MIOX gene - either the previous version from Mus musculus or a homologue from Arabidopsis thaliana codon-optimized for expression in S. cerevisiae - in order to identify the rate-limiting steps for D-glucaric acid production both from a fermentative and non-fermentative carbon source. myo-Inositol availability was found to be rate-limiting from glucose in both strains and demonstrated to be dependent on growth rate, whereas the previously used M. musculus MIOX activity was found to be rate-limiting from glycerol. Maximum titers were 0.56 g/L from glucose in batch mode, 0.98 g/L from glucose in fed-batch mode, and 1.6 g/L from glucose supplemented with myo-inositol. Future work focusing on the MIOX enzyme, the interplay between growth and production modes, and promoting aerobic respiration should further improve this pathway.

The human functional genome defined by genetic diversity

Large scale efforts to sequence whole human genomes provide extensive data on the non-coding portion of the genome. We used variation information from 11,257 human genomes to describe the spectrum of sequence conservation in the population. We established the genome-wide variability for each nucleotide in the context of the surrounding sequence in order to identify departure from expectation at the population level (context-dependent conservation). We characterized the population diversity for functional elements in the genome and identified the coordination of conserved sequences of distal and cis enhancers, chromatin marks, promoters, coding and intronic regions. The most context-dependent conserved regions of the genome are associated with unique functional annotations and a genomic organization that spreads up to one megabase. Importantly, these regions are enriched by over 100-fold of non-coding pathogenic variants. This analysis of human genetic diversity thus provides a detailed view of sequence conservation, functional constraint and genomic organization of the human genome. Specifically, it identifies highly conserved non-coding sequences that are not captured by analysis of interspecies conservation and are greatly enriched in disease variants.

Establishing the involvement of the novel gene AGBL5 in retinitis pigmentosa by whole genome sequencing

While more than 250 genes are known to cause inherited retinal degenerations (IRD), nearly 40-50% of families have the genetic basis for their disease unknown. In this study we sought to identify the underlying cause of IRD in a family by whole genome sequence (WGS) analysis. Clinical characterization including standard ophthalmic examination, fundus photography, visual field testing, electroretinography, and review of medical and family history was performed. WGS was performed on affected and unaffected family members using Illumina HiSeq X10. Sequence reads were aligned to hg19 using BWA-MEM and variant calling was performed with Genome Analysis Toolkit. The called variants were annotated with SnpEff v4.11, PolyPhen v2.2.2, and CADD v1.3. Copy number variations were called using Genome STRiP (svtoolkit 2.00.1611) and SpeedSeq software. Variants were filtered to detect rare potentially deleterious variants segregating with disease. Candidate variants were validated by dideoxy sequencing. Clinical evaluation revealed typical adolescent-onset recessive retinitis pigmentosa (arRP) in affected members. WGS identified about 4 million variants in each individual. Two rare and potentially deleterious compound heterozygous variants p.Arg281Cys and p.Arg487* were identified in the gene ATP/GTP binding protein like 5 (AGBL5) as likely causal variants. No additional variants in IRD genes that segregated with disease were identified. Mutation analysis confirmed the segregation of these variants with the IRD in the pedigree. Homology models indicated destabilization of AGBL5 due to the p.Arg281Cys change. Our findings establish the involvement of mutations in AGBL5 in RP and validate the WGS variant filtering pipeline we designed.

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: A proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

Biocuration in the structure-function linkage database: the anatomy of a superfamily

Abstract With ever-increasing amounts of sequence data available in both the primary literature and sequence repositories, there is a bottleneck in annotating molecular function to a sequence. This article describes the biocuration process and methods used in the structure-function linkage database (SFLD) to help address some of the challenges. We discuss how the hierarchy within the SFLD allows us to infer detailed functional properties for functionally diverse enzyme superfamilies in which all members are homologous, conserve an aspect of their chemical function and have associated conserved structural features that enable the chemistry. Also presented is the Enzyme Structure-Function Ontology (ESFO), which has been designed to capture the relationships between enzyme sequence, structure and function that underlie the SFLD and is used to guide the biocuration processes within the SFLD. Database URL: http://sfld.rbvi.ucsf.edu/