Enzymatic and structural characterization of rTSγ provides insights into the function of rTSβ

Hydroxysteroid 17-β dehydrogenase 14 (HSD17B14) is an L-fucose dehydrogenase, the initial enzyme of the L-fucose degradation pathway

L-Fucose (6-deoxy-L-galactose), a monosaccharide abundant in glycolipids and glycoproteins produced by mammalian cells, has been extensively studied for its role in intracellular biosynthesis and recycling of GDP-L-fucose for fucosylation. However, in certain mammalian species, L-fucose is efficiently broken down to pyruvate and lactate in a poorly understood metabolic pathway. In the 1970s, L-fucose dehydrogenase, an enzyme responsible for the initial step of this pathway, was partially purified from pig and rabbit livers and characterized biochemically. However, its molecular identity remained elusive until recently. This study reports the purification, identification, and biochemical characterization of the mammalian L-fucose dehydrogenase. The enzyme was purified from rabbit liver approximately 340-fold. Mass spectrometry analysis of the purified protein preparation identified mammalian hydroxysteroid 17-β dehydrogenase 14 (HSD17B14) as the sole candidate enzyme. Rabbit and human HSD17B14 were expressed in HEK293T and Escherichia coli, respectively, purified, and demonstrated to catalyze the oxidation of L-fucose to L-fucono-1,5-lactone, as confirmed by mass spectrometry and NMR analysis. Substrate specificity studies revealed that L-fucose is the preferred substrate for both enzymes. The human enzyme exhibited a catalytic efficiency for L-fucose that was 359-fold higher than its efficiency for estradiol. Additionally, recombinant rat HSD17B14 exhibited negligible activity towards L-fucose, consistent with the absence of L-fucose metabolism in this species. The identification of the gene-encoding mammalian L-fucose dehydrogenase provides novel insights into the substrate specificity of enzymes belonging to the 17-β-hydroxysteroid dehydrogenase family. This discovery also paves the way for unraveling the physiological functions of the L-fucose degradation pathway, which remains enigmatic.

Crystal structure of L-2-keto-3-deoxyfuconate 4-dehydrogenase reveals a unique binding mode as a α-furanosyl hemiketal of substrates

L-2-Keto-3-deoxyfuconate 4-dehydrogenase (L-KDFDH) catalyzes the NAD+-dependent oxidization of L-2-keto-3-deoxyfuconate (L-KDF) to L-2,4-diketo-3-deoxyfuconate (L-2,4-DKDF) in the non-phosphorylating L-fucose pathway from bacteria, and its substrate was previously considered to be the acyclic α-keto form of L-KDF. On the other hand, BDH2, a mammalian homolog with L-KDFDH, functions as a dehydrogenase for cis-4-hydroxy-L-proline (C4LHyp) with the cyclic structure. We found that L-KDFDH and BDH2 utilize C4LHyp and L-KDF, respectively. Therefore, to elucidate unique substrate specificity at the atomic level, we herein investigated for the first time the crystal structures of L-KDFDH from Herbaspirillum huttiense in the ligand-free, L-KDF and L-2,4-DKDF, D-KDP (D-2-keto-3-deoxypentonate; additional substrate), or L-2,4-DKDF and NADH bound forms. In complexed structures, L-KDF, L-2,4-DKDF, and D-KDP commonly bound as a α-furanosyl hemiketal. Furthermore, L-KDFDH showed no activity for L-KDF and D-KDP analogs without the C5 hydroxyl group, which form only the acyclic α-keto form. The C1 carboxyl and α-anomeric C2 hydroxyl groups and O5 oxygen atom of the substrate (and product) were specifically recognized by Arg148, Arg192, and Arg214. The side chain of Trp252 was important for hydrophobically recognizing the C6 methyl group of L-KDF. This is the first example showing the physiological role of the hemiketal of 2-keto-3-deoxysugar acid.

Role of Single-Nucleotide Polymorphisms in Genes Implicated in Capecitabine Pharmacodynamics on the Effectiveness of Adjuvant Therapy in Colorectal Cancer

Colorectal cancer (CRC) is a highly prevalent form of neoplasm worldwide. Capecitabine, an oral antimetabolite, is widely used for CRC treatment; however, there exists substantial variation in individual therapy response. This may be due to genetic variations in genes involved in capecitabine pharmacodynamics (PD). In this study, we investigated the role of single-nucleotide polymorphisms (SNPs) related to capecitabine's PD on disease-free survival (DFS) in CRC patients under adjuvant treatment. Thirteen SNPs in the TYMS, ENOSF1, MTHFR, ERCC1/2, and XRCC1/3 genes were genotyped in 142 CRC patients using real-time PCR with predesigned TaqMan® probes. A significant association was found between favorable DFS and the ENOSF1 rs2612091-T allele (p = 0.010; HR = 0.34; 95% CI = 0.14-0.83), as well as with the TYMS/ENOSF1 region ACT haplotype (p = 0.012; HR = 0.37; 95% CI = 0.17-0.80). Other factors such as low histological grade (p = 0.009; HR = 0.34; 95% CI = 0.14-0.79) and a family history of cancer (p = 0.040; HR = 0.48; 95% CI = 0.23-0.99) were also linked to improved DFS. Therefore, the SNP ENOSF1 rs2612091 could be considered as a predictive genetic biomarker for survival in CRC patients receiving capecitabine-based adjuvant regimens.

The Birth of Genomic Enzymology: Discovery of the Mechanistically Diverse Enolase Superfamily

Enzymes are categorized into superfamilies by sequence, structural, and mechanistic similarities. The evolutionary implications can be profound. Until the mid-1990s, the approach was fragmented largely due to limited sequence and structural data. However, in 1996, Babbitt et al. published a paper in Biochemistry that demonstrated the potential power of mechanistically diverse superfamilies to identify common ancestry, predict function, and, in some cases, predict specificity. This Perspective describes the findings of the original work and reviews the current understanding of structure and mechanism in the founding family members. The outcomes of the genomic enzymology approach have reached far beyond the functional assignment of members of the enolase superfamily, inspiring the study of superfamilies and the adoption of sequence similarity networks and genome context and yielding fundamental insights into enzyme evolution.

Genome-wide scan identifies novel genetic loci regulating salivary metabolite levels

Saliva, as a biofluid, is inexpensive and non-invasive to obtain, and provides a vital tool to investigate oral health and its interaction with systemic health conditions. There is growing interest in salivary biomarkers for systemic diseases, notably cardiovascular disease. Whereas hundreds of genetic loci have been shown to be involved in the regulation of blood metabolites, leading to significant insights into the pathogenesis of complex human diseases, little is known about the impact of host genetics on salivary metabolites. Here we report the first genome-wide association study exploring 476 salivary metabolites in 1419 subjects from the TwinsUK cohort (discovery phase), followed by replication in the Study of Health in Pomerania (SHIP-2) cohort. A total of 14 distinct locus-metabolite associations were identified in the discovery phase, most of which were replicated in SHIP-2. While only a limited number of the loci that are known to regulate blood metabolites were also associated with salivary metabolites in our study, we identified several novel saliva-specific locus-metabolite associations, including associations for the AGMAT (with the metabolites 4-guanidinobutanoate and beta-guanidinopropanoate), ATP13A5 (with the metabolite creatinine) and DPYS (with the metabolites 3-ureidopropionate and 3-ureidoisobutyrate) loci. Our study suggests that there may be regulatory pathways of particular relevance to the salivary metabolome. In addition, some of our findings may have clinical significance, such as the utility of the pyrimidine (uracil) degradation metabolites in predicting 5-fluorouracil toxicity and the role of the agmatine pathway metabolites as biomarkers of oral health.

Proteome-Wide Analysis of Lysine 2-Hydroxyisobutyrylation in the Phytopathogenic Fungus Botrytis cinerea

Posttranslational modifications (PTMs) of the whole proteome have become a hot topic in the research field of epigenetics, and an increasing number of PTM types have been identified and shown to play significant roles in different cellular processes. Protein lysine 2-hydroxyisobutyrylation (K_hib) is a newly detected PTM, and the 2-hydroxyisobutyrylome has been identified in several species. Botrytis cinerea is recognized as one of the most destructive pathogens due to its broad host distribution and very large economic losses; thus the many aspects of its pathogenesis have been continuously studied. However, distribution and function of K_hib in this phytopathogenic fungus are not clear. In this study, a proteome-wide analysis of K_hib in B. cinerea was performed, and 5,398 K_hib sites on 1,181 proteins were identified. Bioinformatics analysis showed that the 2-hydroxyisobutyrylome in B. cinerea contains both conserved proteins and novel proteins when compared with K_hib proteins in other species. Functional classification, functional enrichment and protein interaction network analyses showed that K_hib proteins are widely distributed in cellular compartments and involved in diverse cellular processes. Significantly, 37 proteins involved in different aspects of regulating the pathogenicity of B. cinerea were detected as K_hib proteins. Our results provide a comprehensive view of the 2-hydroxyisobutyrylome and lay a foundation for further studying the regulatory mechanism of K_hib in both B. cinerea and other plant pathogens.

Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population

We performed a metabolome genome-wide association study for the Japanese population in the prospective cohort study of Tohoku Medical Megabank. By combining whole-genome sequencing and nontarget metabolome analyses, we identified a large number of novel associations between genetic variants and plasma metabolites. Of the identified metabolite-associated genes, approximately half have already been shown to be involved in various diseases. We identified metabolite-associated genes involved in the metabolism of xenobiotics, some of which are from intestinal microorganisms, indicating that the identified genetic variants also markedly influence the interaction between the host and symbiotic bacteria. We also identified five associations that appeared to be female-specific. A number of rare variants that influence metabolite levels were also found, and combinations of common and rare variants influenced the metabolite levels more profoundly. These results support our contention that metabolic phenotyping provides important insights into how genetic and environmental factors provoke human diseases.

Novel non-phosphorylative pathway of pentose metabolism from bacteria

Pentoses, including D-xylose, L-arabinose, and D-arabinose, are generally phosphorylated to D-xylulose 5-phosphate in bacteria and fungi. However, in non-phosphorylative pathways analogous to the Entner-Dodoroff pathway in bacteria and archaea, such pentoses can be converted to pyruvate and glycolaldehyde (Route I) or α-ketoglutarate (Route II) via a 2-keto-3-deoxypentonate (KDP) intermediate. Putative gene clusters related to these metabolic pathways were identified on the genome of Herbaspirillum huttiense IAM 15032 using a bioinformatic analysis. The biochemical characterization of C785_RS13685, one of the components encoded to D-arabinonate dehydratase, differed from the known acid-sugar dehydratases. The biochemical characterization of the remaining components and a genetic expression analysis revealed that D- and L-KDP were converted not only to α-ketoglutarate, but also pyruvate and glycolate through the participation of dehydrogenase and hydrolase (Route III). Further analyses revealed that the Route II pathway of D-arabinose metabolism was not evolutionally related to the analogous pathway from archaea.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of “genomic enzymology” web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence–function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

A Paradigm for CH Bond Cleavage: Structural and Functional Aspects of Transition State Stabilization by Mandelate Racemase

Mandelate racemase (MR) from Pseudomonas putida catalyzes the Mg²⁺-dependent, 1,1-proton transfer reaction that racemizes (R)- and (S)-mandelate. MR shares a partial reaction (i.e., the metal ion-assisted, Brønsted base-catalyzed proton abstraction of the α-proton of carboxylic acid substrates) and structural features ((β/α)₇β-barrel and N-terminal α + β capping domains) with a vast group of homologous, yet functionally diverse, enzymes in the enolase superfamily. Mechanistic and structural studies have developed this enzyme into a paradigm for understanding how enzymes such as those of the enolase superfamily overcome kinetic and thermodynamic barriers to catalyze the abstraction of an α-proton from a carbon acid substrate with a relatively high pK_a value. Structural studies on MR bound to intermediate/transition state analogues have delineated those structural features that MR uses to stabilize transition states and enhance reaction rates of proton abstraction. Kinetic, site-directed mutagenesis, and structural studies have also revealed that the phenyl ring of the substrate migrates through the hydrophobic cavity within the active site during catalysis and that the Brønsted acid-base catalysts (Lys 166 and His 297) may be utilized as binding determinants for inhibitor recognition. In addition, structural studies on the adduct formed from the irreversible inhibition of MR by 3-hydroxypyruvate revealed that MR can form and deprotonate a Schiff-base with 3-hydroxypyruvate to yield an enol(ate)-aldehyde adduct, suggesting a possible evolutionary link between MR and the Schiff-base forming aldolases. As the archetype of the enolase superfamily, mechanistic and structural studies on MR will continue to enhance our understanding of enzyme catalysis and furnish insights into the evolution of enzyme function.

The interdigitating loop of the enolase superfamily as a specificity binding determinant or 'flying buttress'

BACKGROUND

Enzymes of the enolase superfamily (ENS) are mechanistically diverse, yet share a common partial reaction (abstraction of the α-proton from a carboxylate substrate). While the catalytic machinery responsible for the deprotonation reaction has been conserved, divergent evolution has led to numerous ENS members that catalyze different overall reactions. This rich functional diversity has made the ENS an excellent model system for developing the approaches necessary to validate enzyme function. However, enzymes of the ENS also share a common bidomain structure ((β/α)₇β-barrel domain and α+β capping domain) which makes validation of function from structural information challenging.

SCOPE OF THE REVIEW

This review presents a comparative survey of the structural data obtained over the past decade for enzymes from all seven subgroups that comprise the ENS.

MAJOR CONCLUSIONS

Of the seven ENS subgroups (enolase, mandelate racemase (MR), muconate lactonizing enzyme, β-methylaspartate ammonia lyase, d-glucarate dehydratase, d-mannonate dehydratase (ManD), and galactarate dehydratase 2), only enzymes of the MR and ManD subgroups exhibit an additional feature of structural complexity-an interdigitating loop. This loop emanates from one protomer of a homodimeric pair and penetrates into the adjacent, symmetry-related protomer to either contribute a binding determinant to the active site of the adjacent protomer, or act as a 'flying buttress' to support residues of the active site.

GENERAL SIGNIFICANCE

The analysis presented in this review suggests that the interdigitating loop is the only gross structural element that permits functional distinction between ENS subgroups at the tertiary level of protein structure.

Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST): A web tool for generating protein sequence similarity networks

The Enzyme Function Initiative, an NIH/NIGMS-supported Large-Scale Collaborative Project (EFI; U54GM093342; http://enzymefunction.org/), is focused on devising and disseminating bioinformatics and computational tools as well as experimental strategies for the prediction and assignment of functions (in vitro activities and in vivo physiological/metabolic roles) to uncharacterized enzymes discovered in genome projects. Protein sequence similarity networks (SSNs) are visually powerful tools for analyzing sequence relationships in protein families (H.J. Atkinson, J.H. Morris, T.E. Ferrin, and P.C. Babbitt, PLoS One 2009, 4, e4345). However, the members of the biological/biomedical community have not had access to the capability to generate SSNs for their "favorite" protein families. In this article we announce the EFI-EST (Enzyme Function Initiative-Enzyme Similarity Tool) web tool (http://efi.igb.illinois.edu/efi-est/) that is available without cost for the automated generation of SSNs by the community. The tool can create SSNs for the "closest neighbors" of a user-supplied protein sequence from the UniProt database (Option A) or of members of any user-supplied Pfam and/or InterPro family (Option B). We provide an introduction to SSNs, a description of EFI-EST, and a demonstration of the use of EFI-EST to explore sequence-function space in the OMP decarboxylase superfamily (PF00215). This article is designed as a tutorial that will allow members of the community to use the EFI-EST web tool for exploring sequence/function space in protein families.

UniProt: a hub for protein information

UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.