Enzyme Commission Research Articles

Comparative transcriptome analysis of Gastrodia elata (Orchidaceae) in response to fungus symbiosis to identify gastrodin biosynthesis-related genes.

BackgroundGastrodia elata Blume (Orchidaceae) is an important Chinese medicine with several functional components. In the life cycle of G. elata, the orchid develops a symbiotic relationship with two compatible mycorrhizal fungi Mycena spp. and Armillaria mellea during seed germination to form vegetative propagation corm and vegetative growth to develop tubers, respectively. Gastrodin (p-hydroxymethylphenol-beta-D-glucoside) is the most important functional component in G. elata, and gastrodin significantly increases from vegetative propagation corms to tubers. To address the gene regulation mechanism in gastrodin biosynthesis in G. elata, a comparative analysis of de novo transcriptome sequencing among the vegetative propagation corms and tubers of G. elata and A. mellea was conducted using deep sequencing.ResultsTranscriptome comparison between the vegetative propagation corms and juvenile tubers of G. elata revealed 703 differentially expressed unigenes, of which 298 and 405 unigenes were, respectively up-regulated (fold-change ≥ 2, q-value < 0.05, the trimmed mean of M-values (TMM)-normalized fragments per kilobase of transcript per Million mapped reads (FPKM) > 10) and down-regulated (fold-change ≤ 0.5, q-value <0.05, TMM-normalized FPKM > 10) in juvenile tubers. After Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, 112 up-regulated unigenes with KEGG Ortholog identifiers (KOids) or enzyme commission (EC) numbers were assigned to 159 isogroups involved in seventy-eight different pathways, and 132 down-regulated unigenes with KOids or EC numbers were assigned to 168 isogroups, involved in eighty different pathways. The analysis of the isogroup genes from all pathways revealed that the two unigenes TRINITY_DN54282_c0_g1 (putative monooxygenases) and TRINITY_DN50323_c0_g1 (putative glycosyltransferases) might participate in hydroxylation and glucosylation in the gastrodin biosynthetic pathway.ConclusionsThe gene expression of the two unique unigenes encoding monooxygenase and glycosyltransferase significantly increases from vegetative propagation corms to tubers, and the molecular basis of gastrodin biosynthesis in the tubers of G. elata is proposed.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2508-6) contains supplementary material, which is available to authorized users.

Exploring the chemistry and evolution of the isomerases

Isomerization reactions are fundamental in biology, and isomers usually differ in their biological role and pharmacological effects. In this study, we have cataloged the isomerization reactions known to occur in biology using a combination of manual and computational approaches. This method provides a robust basis for comparison and clustering of the reactions into classes. Comparing our results with the Enzyme Commission (EC) classification, the standard approach to represent enzyme function on the basis of the overall chemistry of the catalyzed reaction, expands our understanding of the biochemistry of isomerization. The grouping of reactions involving stereoisomerism is straightforward with two distinct types (racemases/epimerases and cis-trans isomerases), but reactions entailing structural isomerism are diverse and challenging to classify using a hierarchical approach. This study provides an overview of which isomerases occur in nature, how we should describe and classify them, and their diversity.

Characterising Complex Enzyme Reaction Data

The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC) number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g., KEGG). Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution.

Phenolic Precipitates from Soybean Peroxidase–Catalyzed Wastewater Treatment: Concentrated Waste Serves to Concentrate Its Progenitor

AbstractThe use of Triton X-100 (Triton) significantly improves enzyme economy for the removal of phenol from wastewater with crude soybean peroxidase (SBP, Enzyme Commission Number 1.11.1.7), a polymerization process that forms (poly) phenolic precipitates. The observation of SBP elution from phenolic precipitates in the presence of Triton was considered a competitive adsorption displacement phenomenon in order to explain the protection mechanism (Triton effect). Both SBP and Triton adsorption on the precipitates were characterized by Langmuir adsorption isotherms as single-adsorbate systems. As a binary-adsorbate system, the adsorption of Triton gradually reversed the adsorbed SBP back into the aqueous phase. The sigmoid elution curve was consistent with an orogenic displacement mechanism. A quantitative relationship between SBP elution as a function of Triton and precipitates concentrations was established by adapting the curves to a logistic function. The concept of using phenolic precipitates as an a...

Protein Structure and Function Prediction Using I-TASSER.

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets.

The alignment of enzymatic steps reveals similar metabolic pathways and probable recruitment events in Gammaproteobacteria.

BackgroundIt is generally accepted that gene duplication followed by functional divergence is one of the main sources of metabolic diversity. In this regard, there is an increasing interest in the development of methods that allow the systematic identification of these evolutionary events in metabolism. Here, we used a method not based on biomolecular sequence analysis to compare and identify common and variable routes in the metabolism of 40 Gammaproteobacteria species.MethodThe metabolic maps deposited in the KEGG database were transformed into linear Enzymatic Step Sequences (ESS) by using the breadth-first search algorithm. These ESS represent subsequent enzymes linked to each other, where their catalytic activities are encoded in the Enzyme Commission numbers. The ESS were compared in an all-against-all (pairwise comparisons) approach by using a dynamic programming algorithm, leaving only a set of significant pairs.Results and conclusionFrom these comparisons, we identified a set of functionally conserved enzymatic steps in different metabolic maps, in which cell wall components and fatty acid and lysine biosynthesis were included. In addition, we found that pathways associated with biosynthesis share a higher proportion of similar ESS than degradation pathways and secondary metabolism pathways. Also, maps associated with the metabolism of similar compounds contain a high proportion of similar ESS, such as those maps from nucleotide metabolism pathways, in particular the inosine monophosphate pathway. Furthermore, diverse ESS associated with the low part of the glycolysis pathway were identified as functionally similar to multiple metabolic pathways. In summary, our comparisons may help to identify similar reactions in different metabolic pathways and could reinforce the patchwork model in the evolution of metabolism in Gammaproteobacteria.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2113-0) contains supplementary material, which is available to authorized users.

Identification of the nicotinamide mononucleotide adenylyltransferase of Trypanosoma cruzi.

The intracellular parasite Trypanosoma cruzi is the aetiological agent of Chagas disease, a public health concern with an increasing incidence rate. This increase is due, among other reasons, to the parasite's drug resistance mechanisms, which require nicotinamide adenine dinucleotide (NAD+). Furthermore, this molecule is involved in metabolic and intracellular signalling processes necessary for the survival of T. cruzi throughout its life cycle. NAD+ biosynthesis is performed by de novo and salvage pathways, which converge on the step that is catalysed by the enzyme nicotinamide mononucleotide adenylyltransferase (NMNAT) (enzyme commission number: 2.7.7.1). The identification of the NMNAT of T. cruzi is important for the development of future therapeutic strategies to treat Chagas disease. In this study, a hypothetical open reading frame (ORF) for NMNAT was identified in the genome of T. cruzi. The corresponding putative protein was analysed by simulating structural models. The ORF was amplified from genomic DNA by polymerase chain reaction and was further used for the construction of a corresponding recombinant expression vector. The expressed recombinant protein was partially purified and its activity was evaluated using enzymatic assays. These results comprise the first identification of an NMNAT in T. cruzi using bioinformatics and experimental tools and hence represent the first step to understanding NAD+ metabolism in these parasites.

RNA-Seq mediated root transcriptome analysis of Chlorophytum borivilianum for identification of genes involved in saponin biosynthesis.

Chlorophytum borivilianum is an important species of liliaceae family, owing to its vital medicinal properties. Plant roots are used for aphrodisiac, adaptogen, anti-aging, health-restorative and health-promoting purposes. Saponins, are considered to be the principal bioactive components responsible for the wide variety of pharmacological properties of this plant. In the present study, we have performed de novo root transcriptome sequencing of C. borivilianum using Illumina Hiseq 2000 platform, to gain molecular insight into saponins biosynthesis. A total of 33,963,356 high-quality reads were obtained after quality filtration. Sequences were assembled using various programs which generated 97,344 transcripts with a size range of 100-5,216 bp and N50 value of 342. Data was analyzed against non-redundant proteins, gene ontology (GO), and enzyme commission (EC) databases. All the genes involved in saponins biosynthesis along with five full-length genes namely farnesyl pyrophosphate synthase, cycloartenol synthase, β-amyrin synthase, cytochrome p450, and sterol-3-glucosyltransferase were identified. Read per exon kilobase per million (RPKM)-based comparative expression profiling was done to study the differential regulation of the genes. In silico expression analysis of seven selected genes of saponin biosynthetic pathway was validated by qRT-PCR.

MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics

BackgroundIn spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases.DescriptionHere we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted.ConclusionsMINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures.Graphical abstractMINE database construction and access methods. The process of constructing a MINE database from the curated source databases is depicted on the left. The methods for accessing the database are shown on the right.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0087-1) contains supplementary material, which is available to authorized users.

The lifestyle of prokaryotic organisms influences the repertoire of promiscuous enzymes.

The metabolism of microbial organisms and its diversity are partly the result of an adaptation process to the characteristics of the environments that they inhabit. In this work, we analyze the influence of lifestyle on the content of promiscuous enzymes in 761 nonredundant bacterial and archaeal genomes. Promiscuous enzymes were defined as those proteins whose catalytic activities are defined by two or more different Enzyme Commission (E.C.) numbers. The genomes analyzed were categorized into four lifestyles for their exhaustive comparisons: free-living, extremophiles, pathogens, and intracellular. From these analyses we found that free-living organisms have larger genomes and an enrichment of promiscuous enzymes. In contrast, intracellular organisms showed smaller genomes and the lesser proportion of promiscuous enzymes. On the basis of our data, we show that the proportion of promiscuous enzymes in an organism is mainly influenced by the lifestyle, where fluctuating environments promote its emergence. Finally, we evidenced that duplication processes occur preferentially in metabolism of free-living and extremophiles species.

Transcriptomic landscape of Pueraria lobata demonstrates potential for phytochemical study

Pueraria lobata (Willd.) Ohwi has a long and broad application in the treatment of disease. However, in the US and EU, it is treated as a notorious weed. The information to be gained from decoding the deep transcriptome profile would facilitate further research on P. lobata. In this study, more than 93 million fastq format reads were generated by Illumina’s next-generation sequencing approach using five types of P. lobata tissue, followed by CLC de novo assembly methods, ultimately yielding about 83,041 contigs in total. Then BLASTx similarity searches against the NCBI NR database and UniProtKB database were conducted. Once the duplicates among BLASTx hits were eliminated, ID mapping against the UniProt database was conducted online to retrieve Gene Ontology information. In search of the putative genes relevant to essential biosynthesis pathways, all 1,348 unique enzyme commission numbers were used to map pathways against the Kyoto Encyclopedia of Genes and Genomes. Enzymes related to the isoflavonoid and flavonoid biosynthesis pathways were focused for detailed investigation and subsequently, quantitative real-time reverse transcription polymerase chain reaction was conducted for biological validation. Metabolites of interest, puerarin and daidzin were studied by HPLC. The findings in this report may serve as a footstone for further research into this promising medicinal plant.

High-Throughput Sequencing and De Novo Assembly of Red and Green Forms of the Perilla frutescens var. crispa Transcriptome.

Perilla frutescens var. crispa (Labiatae) has two chemo-varietal forms, i.e. red and green forms of perilla, that differ in the production of anthocyanins. To facilitate molecular biological and biochemical studies in perilla-specialized metabolism we used Illumina RNA-sequencing technology in our comprehensive comparison of the transcriptome map of the leaves of red and green forms of perilla. Sequencing generated over 1.2 billion short reads with an average length of 101 nt. De novo transcriptome assembly yielded 47,788 and 47,840 unigenes in the red and green forms of perilla plants, respectively. Comparison of the assembled unigenes and existing perilla cDNA sequences showed highly reliable alignment. All unigenes were annotated with gene ontology (GO) and Enzyme Commission numbers and entered into the Kyoto Encyclopedia of Genes and Genomes. We identified 68 differentially expressed genes (DEGs) in red and green forms of perilla. GO enrichment analysis of the DEGs showed that genes involved in the anthocyanin metabolic process were enriched. Differential expression analysis revealed that the transcript level of anthocyanin biosynthetic unigenes encoding flavonoid 3’-hydroxylase, dihydroflavonol 4-reductase, and anthocyanidin synthase was significantly higher in red perilla, while the transcript level of unigenes encoding limonene synthase was significantly higher in green perilla. Our data serve as a basis for future research on perilla bio-engineering and provide a shortcut for the characterization of new functional genes in P. frutescens.

AntiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.

DomSign: a top-down annotation pipeline to enlarge enzyme space in the protein universe.

BackgroundComputational predictions of catalytic function are vital for in-depth understanding of enzymes. Because several novel approaches performing better than the common BLAST tool are rarely applied in research, we hypothesized that there is a large gap between the number of known annotated enzymes and the actual number in the protein universe, which significantly limits our ability to extract additional biologically relevant functional information from the available sequencing data. To reliably expand the enzyme space, we developed DomSign, a highly accurate domain signature–based enzyme functional prediction tool to assign Enzyme Commission (EC) digits.ResultsDomSign is a top-down prediction engine that yields results comparable, or superior, to those from many benchmark EC number prediction tools, including BLASTP, when a homolog with an identity >30% is not available in the database. Performance tests showed that DomSign is a highly reliable enzyme EC number annotation tool. After multiple tests, the accuracy is thought to be greater than 90%. Thus, DomSign can be applied to large-scale datasets, with the goal of expanding the enzyme space with high fidelity. Using DomSign, we successfully increased the percentage of EC-tagged enzymes from 12% to 30% in UniProt-TrEMBL. In the Kyoto Encyclopedia of Genes and Genomes bacterial database, the percentage of EC-tagged enzymes for each bacterial genome could be increased from 26.0% to 33.2% on average. Metagenomic mining was also efficient, as exemplified by the application of DomSign to the Human Microbiome Project dataset, recovering nearly one million new EC-labeled enzymes.ConclusionsOur results offer preliminarily confirmation of the existence of the hypothesized huge number of “hidden enzymes” in the protein universe, the identification of which could substantially further our understanding of the metabolisms of diverse organisms and also facilitate bioengineering by providing a richer enzyme resource. Furthermore, our results highlight the necessity of using more advanced computational tools than BLAST in protein database annotations to extract additional biologically relevant functional information from the available biological sequences.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0499-y) contains supplementary material, which is available to authorized users.

RNA-Seq transcriptome analysis of maize inbred carrying nicosulfuron-tolerant and nicosulfuron-susceptible alleles.

Postemergence applications of nicosulfuron can cause great damage to certain maize inbred lines and hybrids. Variation among different responses to nicosulfuron may be attributed to differential rates of herbicide metabolism. We employed RNA-Seq analysis to compare transcriptome responses between nicosulfuron-treated and untreated in both tolerant and susceptible maize plants. A total of 71.8 million paired end Illumina RNA-Seq reads were generated, representing the transcription of around 40,441 unique reads. About 345,171 gene ontology (GO) term assignments were conducted for the annotation in terms of biological process, cellular component and molecular function categories, and 6413 sequences with 108 enzyme commission numbers were assigned to 134 predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways. Digital gene expression profile (DGE) analysis using Solexa sequencing was performed within the susceptible and tolerant maize between the nicosulfuron-treated and untreated conditions, 13 genes were selected as the candidates most likely involved in herbicide metabolism, and quantitative RT-PCR validated the RNA-Seq results for eight genes. This transcriptome data may provide opportunities for the study of sulfonylurea herbicides susceptibility emergence of Zea mays.

Fragment profiling of low molecular weight heparins using reversed phase ion pair liquid chromatography-electrospray mass spectrometry

Low molecular weight heparins (LMWHs) are linear and highly charged carbohydrate polymers prepared by chemical or enzymatic depolymerization of heparin. Compared to unfractionated heparin (UFH), LMWHs are prevalently used as clinical anticoagulant drugs due to their lower side effects and better bioavailability. The work presented herein provides a rapid and powerful fragment mapping method for structural characterization of LMWHs. The chain fragments of two types of LMWHs, enoxaparin and nadroparin, were generated by controlled enzymatic digestion with each of heparinase I (Hep I, Enzyme Commission (EC) # 4.2.2.7), heparinase II (Hep II, no EC # assigned) and heparinase III (Hep III, EC # 4.2.2.8). Reversed phase ion pair high performance liquid chromatography (RPIP-HPLC) coupled with electrospray ion trap time-of-flight mass spectrometry (ESI-IT-TOF-MS) was used to profile the oligosaccharide chains ranging from disaccharides to decasaccharides. A database containing all theoretical structural compositions was established to assist the mass spectra interpretation. The six digests derived by three enzymes from two types of LMWHs exhibited distinguishable fingerprinting patterns. And a total of 94 enoxaparin fragments and 109 nadroparin fragments were detected and identified. Besides the common LMWH oligosaccharides, many components containing characteristic LMWH structures such as saturated l-idopyranosuronic acid, 2,5-anhydro-d-mannitol, 1,6-anhydro-d-aminopyranose, as well as odd number oligosaccharides were also revealed. Quantitative comparison of major components derived from innovator and generic nadroparin products was presented. This approach to profile LMWHs' fragments offers a highly reproducible, high resolution and information-rich tool for evaluating the quality of this category of anticoagulant drugs or comparing structural similarities among samples from various sources.

Analysis of expressed sequence tags from cDNA library of Fusarium culmorum infected barley (Hordeum vulgare L.) roots.

Fusarium culmorum is one of the most common and globally important causal agent of root and crown rot diseases of cereals. These diseases cause grain yield loss and reduced grain quality in barley. In this study, we have analyzed an expressed sequence tag (EST) database derived from F. culmorum infected barley root tissues available at the National Center for Biotechnology Information (NCBI). The 2294 sequences were assembled into 1619 non-redundant sequences consisting of 359 contigs and 1260 singletons using the program CAP3. BLASTX analysis for these sequences was conducted in order to find similar sequences in all databases. Gene Ontology search, enzyme search, KEGG mapping and InterProScan search were done using Blast2GO 3.0.7 tool. By BLASTX analysis, 41.7%, 7.7%, 3.2% and 47.4% of ESTs were categorized as annotated, unannotated, not mapping and without blast hits, respectively. BLASTX analysis revealed that the majority of top hits were barley proteins (43.5%). Based on Gene Ontology classification, 38.3%, 31.3%, and 16% of ESTs were assigned to molecular function, biological process, and cellular component GO terms, respectively. Most abundant GO terms were as follows: 157 sequences were related to response to stress (biological process), 207 sequences were related to ion binding (molecular function), and 160 sequences were related to plastid (cellular component). Furthermore, based on KEGG mapping, 369 sequences could be assigned to 264 enzymes and 83 different KEGG pathways. According to Enzyme Commission (EC) distribution; 94 sequences were transferases (EC2) while 70 sequences were hydrolases (EC3).

The enzymatic nature of an anonymous protein sequence cannot reliably be inferred from superfamily level structural information alone.

As the largest fraction of any proteome does not carry out enzymatic functions, and in order to leverage 3D structural data for the annotation of increasingly higher volumes of sequence data, we wanted to assess the strength of the link between coarse grained structural data (i.e., homologous superfamily level) and the enzymatic versus non-enzymatic nature of protein sequences. To probe this relationship, we took advantage of 41 phylogenetically diverse (encompassing 11 distinct phyla) genomes recently sequenced within the GEBA initiative, for which we integrated structural information, as defined by CATH, with enzyme level information, as defined by Enzyme Commission (EC) numbers. This analysis revealed that only a very small fraction (about 1%) of domain sequences occurring in the analyzed genomes was found to be associated with homologous superfamilies strongly indicative of enzymatic function. Resorting to less stringent criteria to define enzyme versus non-enzyme biased structural classes or excluding highly prevalent folds from the analysis had only modest effect on this proportion. Thus, the low genomic coverage by structurally anchored protein domains strongly associated to catalytic activities indicates that, on its own, the power of coarse grained structural information to infer the general property of being an enzyme is rather limited.

Transcriptome Analysis of Nine Tissues to Discover Genes Involved in the Biosynthesis of Active Ingredients in Sophora flavescens.

Sophora flavescens AITON (kurara) has long been used to treat various diseases. Although several research findings revealed the biosynthetic pathways of its characteristic chemical components as represented by matrine, insufficient analysis of transcriptome data hampered in-depth analysis of the underlying putative genes responsible for the biosynthesis of pharmaceutical chemical components. In this study, more than 200 million fastq format reads were generated by Illumina's next-generation sequencing approach using nine types of tissue from S. flavescens, followed by CLC de novo assembly, ultimately yielding 83,325 contigs in total. By mapping the reads back to the contigs, reads per kilobase of the transcript per million mapped reads values were calculated to demonstrate gene expression levels, and overrepresented gene ontology terms were evaluated using Fisher's exact test. In search of the putative genes relevant to essential metabolic pathways, all 1350 unique enzyme commission numbers were used to map pathways against the Kyoto Encyclopedia of Genes and Genomes. By analyzing expression patterns, we proposed some candidate genes involved in the biosynthesis of isoflavonoids and quinolizidine alkaloids. Adopting RNA-Seq analysis, we obtained substantially credible contigs for downstream work. The preferential expression of the gene for putative lysine/ornithine decarboxylase committed in the initial step of matrine biosynthesis in leaves and stems was confirmed in semi-quantitative polymerase chain reaction (PCR) analysis. The findings in this report may serve as a stepping-stone for further research into this promising medicinal plant.

Comparison of Metabolic Pathways in Escherichia coli by Using Genetic Algorithms

In order to understand how cellular metabolism has taken its modern form, the conservation and variations between metabolic pathways were evaluated by using a genetic algorithm (GA). The GA approach considered information on the complete metabolism of the bacterium Escherichia coli K-12, as deposited in the KEGG database, and the enzymes belonging to a particular pathway were transformed into enzymatic step sequences by using the breadth-first search algorithm. These sequences represent contiguous enzymes linked to each other, based on their catalytic activities as they are encoded in the Enzyme Commission numbers. In a posterior step, these sequences were compared using a GA in an all-against-all (pairwise comparisons) approach. Individual reactions were chosen based on their measure of fitness to act as parents of offspring, which constitute the new generation. The sequences compared were used to construct a similarity matrix (of fitness values) that was then considered to be clustered by using a k-medoids algorithm. A total of 34 clusters of conserved reactions were obtained, and their sequences were finally aligned with a multiple-sequence alignment GA optimized to align all the reaction sequences included in each group or cluster. From these comparisons, maps associated with the metabolism of similar compounds also contained similar enzymatic step sequences, reinforcing the Patchwork Model for the evolution of metabolism in E. coli K-12, an observation that can be expanded to other organisms, for which there is metabolism information. Finally, our mapping of these reactions is discussed, with illustrations from a particular case.