Human liver rate-limiting enzymes influence metabolic flux via branch points and inhibitors

Amino Acid Catabolism: An Overlooked Area of Metabolism

Amino acids have been extensively studied in nutrition, mainly as key elements for maintaining optimal protein synthesis in the body as well as precursors of various nitrogen-containing compounds. However, it is now known that amino acid catabolism is an important element for the metabolic control of different biological processes, although it is still a developing field to have a deeper understanding of its biological implications. The mechanisms involved in the regulation of amino acid catabolism now include the contribution of the gut microbiota to amino acid oxidation and metabolite generation in the intestine, the molecular mechanisms of transcriptional control, and the participation of specific miRNAs involved in the regulation of amino acid degrading enzymes. In addition, molecules derived from amino acid catabolism play a role in metabolism as they are used in the epigenetic regulation of many genes. Thus, this review aims to examine the mechanisms of amino acid catabolism and to support the idea that this process is associated with the immune response, abnormalities during obesity, in particular insulin resistance, and the regulation of thermogenesis.

Rate-Limiting Enzymes in Cardiometabolic Health and Aging in Humans

INTRODUCTION

Rate-limiting enzymes (RLEs) are innate slow points in metabolic pathways, and many function in bio-processes related to nutrient sensing. Many RLEs carry causal mutations relevant to inherited metabolic disorders. Because the activity of RLEs in cardiovascular health is poorly characterized, our objective was to assess their involvement in cardiometabolic health and disease and where altered biophysical and biochemical functions can promote disease.

METHODS

A dataset of 380 human RLEs was compared to protein and gene datasets for factors likely to contribute to cardiometabolic disease, including proteins showing significant age-related altered expression in blood and genetic loci with variants that associate with common cardiometabolic phenotypes. The biochemical reactions catalyzed by RLEs were evaluated for metabolites enriched in RLE subsets associating with various cardiometabolic phenotypes. Most significance tests were based on Z-score enrichment converted to p values with a normal distribution function.

RESULTS

Of 380 RLEs analyzed, 112 function in mitochondria, and 53 are assigned to inherited metabolic disorders. There was a depletion of RLE proteins known as aging biomarkers. At the gene level, RLEs were assessed for common genetic variants that associated with important cardiometabolic traits of LDL-cholesterol or any of the five outcomes pertinent to metabolic syndrome. This revealed several RLEs with links to cardiometabolic traits, from a minimum of 26 for HDL-cholesterol to a maximum of 45 for plasma glucose. Analysis of these GWAS-linked RLEs for enrichment of the molecular constituents of the catalyzed reactions disclosed a number of significant phenotype-metabolite links. These included blood pressure with acetate (p = 2.2 × 10-4) and NADP+ (p = 0.0091), plasma HDL-cholesterol and triglyceride with diacylglycerol (p = 2.6 × 10-5, 6.4 × 10-5, respectively) and diolein (p = 2.2 × 10-6, 5.9 × 10-6), and waist circumference with d-glucosamine-6-phosphate (p = 1.8 × 10-4).

CONCLUSION

In the context of cardiometabolic health, aging, and disease, these results highlight key diet-derived metabolites that are central to specific rate-limited processes that are linked to cardiometabolic health. These metabolites include acetate and diacylglycerol, pertinent to blood pressure and triglycerides, respectively, as well as diacylglycerol and HDL-cholesterol.

Making small molecules in plants: A chassis for synthetic biology-based production of plant natural products

Plant natural products have been extensively exploited in food, medicine, flavor, cosmetic, renewable fuel, and other industrial sectors. Synthetic biology has recently emerged as a promising means for the cost-effective and sustainable production of natural products. Compared with engineering microbes for the production of plant natural products, the potential of plants as chassis for producing these compounds is underestimated, largely due to challenges encountered in engineering plants. Knowledge in plant engineering is instrumental for enabling the effective and efficient production of valuable phytochemicals in plants, and also paves the way for a more sustainable future agriculture. In this manuscript, we briefly recap the biosynthesis of plant natural products, focusing primarily on industrially important terpenoids, alkaloids, and phenylpropanoids. We further summarize the plant hosts and strategies that have been used to engineer the production of natural products. The challenges and opportunities of using plant synthetic biology to achieve rapid and scalable production of high-value plant natural products are also discussed.

Serotonin signaling modulates aging-associated metabolic network integrity in response to nutrient choice in Drosophila melanogaster

Aging arises from complex interactions among multiple biochemical products. Systems-level analyses of biological networks may provide insights into the causes and consequences of aging that evade single-gene studies. We have previously found that dietary choice is sufficient to modulate aging in the vinegar fly, Drosophila melanogaster. Here we show that nutrient choice influenced several measures of metabolic network integrity, including connectivity, community structure, and robustness. Importantly, these effects are mediated by serotonin signaling, as a mutation in serotonin receptor 2A (5-HT2A) eliminated the effects of nutrient choice. Changes in network structure were associated with organism resilience and increased susceptibility to genetic perturbation. Our data suggest that the behavioral or perceptual consequences of exposure to individual macronutrients, involving serotonin signaling through 5-HT2A, qualitatively change the state of metabolic networks throughout the organism from one that is highly connected and robust to one that is fragmented, fragile, and vulnerable to perturbations.

A bioinformatics investigation into the pharmacological mechanisms of the effect of the Yinchenhao decoction on hepatitis C based on network pharmacology

Background

Globally, more than 170 million people are infected with hepatitis C virus, a major cause of cirrhosis and hepatocellular carcinoma. The Yinchenhao Decoction (YCHD) is a classic formula comprising three herbal medicines. This decoction have long been used in China for clinically treating acute and chronic infectious hepatitis and other liver and gallbladder damp heat-accumulation disorders.

Methods

In this study, we identified 32 active ingredients and 200 hepatitis C proteins and established a compound-predicted target network and a hepatitis C protein–protein interaction network by using Cytoscape 3.6.1. Then, we systematically analyzed the potential targets of the YCHD for the treatment of hepatitis C. Finally, molecular docking was applied to verify the key targets. In addition, we analyzed the mechanism of action of the predicted targets by the Kyoto Encyclopedia of Genes and Genomes and gene ontology analyses.

Results

This study adopted a network pharmacology approach, mainly comprising target prediction, network construction, module detection, functional enrichment analysis, and molecular docking to systematically investigate the mechanisms of action of the YCHD in hepatitis C. The targets of the YCHD in the treatment of hepatitis C mainly involved PIK3CG, CASP3, BCL2, CASP8, and MMP1. The module and pathway enrichment analyses showed that the YCHD had the potential to influence varieties of biological pathways, including the TNF signaling pathway, Ras signaling pathway, PI3K-Akt signaling pathway, FoxO signaling pathway, and pathways in cancer, that play an important role in the pathogenesis of hepatitis C.

Conclusion

The results of this study preliminarily verified the basic pharmacological effects and related mechanisms of the YCHD in the treatment of hepatitis C.

The Signaling Pathways Project, an integrated 'omics knowledgebase for mammalian cellular signaling pathways

Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus 'omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org .

Constructing a comprehensive gene co-expression based interactome in Bos taurus

Integrating genomic information into cattle breeding is an important approach to exploring genotype-phenotype relationships for complex traits related to diary and meat production. To assist with genomic-based selection, a reference map of interactome is needed to fully understand and identify the functional relevant genes. To this end, we constructed a co-expression analysis of 92 tissues and this represents the systematic exploration of gene-gene relationship in Bos taurus. By using robust WGCNA (Weighted Gene Correlation Network Analysis), we described the gene co-expression network of 5,000 protein-coding genes with majority variations in expression across 92 tissues. Further module identifications found 55 highly organized functional clusters representing diverse cellular activities. To demonstrate the re-use of our interaction for functional genomics analysis, we extracted a sub-network associated with DNA binding genes in Bos taurus. The subnetwork was enriched within regulation of transcription from RNA polymerase II promoter representing central cellular functions. In addition, we identified 28 novel linker genes associated with more than 100 DNA binding genes. Our WGCNA-based co-expression network reconstruction will be a valuable resource for exploring the molecular mechanisms of incompletely characterized proteins and for elucidating larger-scale patterns of functional modulization in the Bos taurus genome.

A gene browser of colorectal cancer with literature evidence and pre-computed regulatory information to identify key tumor suppressors and oncogenes

Colorectal cancer (CRC) is a cancer of growing incidence that associates with a high mortality rate worldwide. There is a poor understanding of the heterogeneity of CRC with regard to causative genetic mutations and gene regulatory mechanisms. Previous studies have identified several susceptibility genes in small-scale experiments. However, the information has not been comprehensively and systematically compiled and interpreted. In this study, we constructed the gbCRC, the first literature-based gene resource for investigating CRC-related human genes. The features of our database include: (i) manual curation of experimentally-verified genes reported in the literature; (ii) comprehensive integration of five reliable data sources; and (iii) pre-computed regulatory patterns involving transcription factors, microRNAs and long non-coding RNAs. In total, 2067 genes associating with 2819 PubMed abstracts were compiled. Comprehensive functional annotations associated with all the genes, including gene expression profiles, homologous genes in other model species, protein-protein interactions, somatic mutations, and potential methylation sites. These comprehensive annotations and this pre-computed regulatory information highlighted the importance of the gbCRC with regard to the unexplored regulatory network of CRC. This information is available in a plain text format that is free to download.

Multi-tissue transcriptomics for construction of a comprehensive gene resource for the terrestrial snail Theba pisana

The land snail Theba pisana is native to the Mediterranean region but has become one of the most abundant invasive species worldwide. Here, we present three transcriptomes of this agriculture pest derived from three tissues: the central nervous system, hepatopancreas (digestive gland), and foot muscle. Sequencing of the three tissues produced 339,479,092 high quality reads and a global de novo assembly generated a total of 250,848 unique transcripts (unigenes). BLAST analysis mapped 52,590 unigenes to NCBI non-redundant protein databases and further functional analysis annotated 21,849 unigenes with gene ontology. We report that T. pisana transcripts have representatives in all functional classes and a comparison of differentially expressed transcripts amongst all three tissues demonstrates enormous differences in their potential metabolic activities. The genes differentially expressed include those with sequence similarity to those genes associated with multiple bacterial diseases and neurological diseases. To provide a valuable resource that will assist functional genomics study, we have implemented a user-friendly web interface, ThebaDB (http://thebadb.bioinfo-minzhao.org/). This online database allows for complex text queries, sequence searches, and data browsing by enriched functional terms and KEGG mapping.

CSGene: a literature-based database for cell senescence genes and its application to identify critical cell aging pathways and associated diseases

Cell senescence is a cellular process in which normal diploid cells cease to replicate and is a major driving force for human cancers and aging-associated diseases. Recent studies on cell senescence have identified many new genetic components and pathways that control cell aging. However, there is no comprehensive resource for cell senescence that integrates various genetic studies and relationships with cell senescence, and the risk associated with complex diseases such as cancer is still unexplored. We have developed the first literature-based gene resource for exploring cell senescence genes, CSGene. We complied 504 experimentally verified genes from public data resources and published literature. Pathway analyses highlighted the prominent roles of cell senescence genes in the control of rRNA gene transcription and unusual rDNA repeat that constitute a center for the stability of the whole genome. We also found a strong association of cell senescence with HIV-1 infection and viral carcinogenesis that are mainly related to promoter/enhancer binding and chromatin modification processes. Moreover, pan-cancer mutation and network analysis also identified common cell aging mechanisms in cancers and uncovered a highly modular network structure. These results highlight the utility of CSGene for elucidating the complex cellular events of cell senescence.

Cellular metabolic network analysis: discovering important reactions in Treponema pallidum

T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis.

METSP: a maximum-entropy classifier based text mining tool for transporter-substrate identification with semistructured text

The substrates of a transporter are not only useful for inferring function of the transporter, but also important to discover compound-compound interaction and to reconstruct metabolic pathway. Though plenty of data has been accumulated with the developing of new technologies such as in vitro transporter assays, the search for substrates of transporters is far from complete. In this article, we introduce METSP, a maximum-entropy classifier devoted to retrieve transporter-substrate pairs (TSPs) from semistructured text. Based on the high quality annotation from UniProt, METSP achieves high precision and recall in cross-validation experiments. When METSP is applied to 182,829 human transporter annotation sentences in UniProt, it identifies 3942 sentences with transporter and compound information. Finally, 1547 confidential human TSPs are identified for further manual curation, among which 58.37% pairs with novel substrates not annotated in public transporter databases. METSP is the first efficient tool to extract TSPs from semistructured annotation text in UniProt. This tool can help to determine the precise substrates and drugs of transporters, thus facilitating drug-target prediction, metabolic network reconstruction, and literature classification.

An evidence-based knowledgebase of pulmonary arterial hypertension to identify genes and pathways relevant to pathogenesis

Pulmonary arterial hypertension (PAH) is a major progressive form of pulmonary hypertension (PH) with more than 4800 patients in the United States. In the last two decades, many studies have identified numerous genes associated with this disease. However, there is no comprehensive research resource for PAH or other PH types that integrates various genetic studies and their related biological information. Thus, the number of associated genes, and their strength of evidence, is unclear. In this study, we tested the hypothesis that a web-based knowledgebase could be used to develop a biological map of highly interrelated, functionally important genes in PAH. We developed the pulmonary arterial hypertension knowledgebase (PAHKB, ), a comprehensive database with a user-friendly web interface. PAHKB extracts genetic data from all available sources, including those from association studies, genetic mutation, gene expression, animal model, supporting literature, various genomic annotations, gene networks, cellular and regulatory pathways, as well as microRNAs. Moreover, PAHKB provides online tools for data browsing and searching, data integration, pathway graphical presentation, and gene ranking. In the current release, PAHKB contains 341 human PH-related genes (293 protein coding and 48 non-coding genes) curated from over 1000 PubMed abstracts. Based on the top 39 ranked PAH-related genes in PAHKB, we constructed a core biological map. This core map was enriched with the TGF-beta signaling pathway, focal adhesion, cytokine-cytokine receptor interaction, and MAPK signaling. In addition, the reconstructed map elucidates several novel cancer signaling pathways, which may provide clues to support the application of anti-cancer therapeutics to PAH. In summary, we have developed a system for the identification of core PH-related genes and identified critical signaling pathways that may be relevant to PAH pathogenesis. This system can be easily applied to other pulmonary diseases.

Human transporter database: comprehensive knowledge and discovery tools in the human transporter genes

Transporters are essential in homeostatic exchange of endogenous and exogenous substances at the systematic, organic, cellular, and subcellular levels. Gene mutations of transporters are often related to pharmacogenetics traits. Recent developments in high throughput technologies on genomics, transcriptomics and proteomics allow in depth studies of transporter genes in normal cellular processes and diverse disease conditions. The flood of high throughput data have resulted in urgent need for an updated knowledgebase with curated, organized, and annotated human transporters in an easily accessible way. Using a pipeline with the combination of automated keywords query, sequence similarity search and manual curation on transporters, we collected 1,555 human non-redundant transporter genes to develop the Human Transporter Database (HTD) (http://htd.cbi.pku.edu.cn). Based on the extensive annotations, global properties of the transporter genes were illustrated, such as expression patterns and polymorphisms in relationships with their ligands. We noted that the human transporters were enriched in many fundamental biological processes such as oxidative phosphorylation and cardiac muscle contraction, and significantly associated with Mendelian and complex diseases such as epilepsy and sudden infant death syndrome. Overall, HTD provides a well-organized interface to facilitate research communities to search detailed molecular and genetic information of transporters for development of personalized medicine.

EDdb: a web resource for eating disorder and its application to identify an extended adipocytokine signaling pathway related to eating disorder

Eating disorder is a group of physiological and psychological disorders affecting approximately 1% of the female population worldwide. Although the genetic epidemiology of eating disorder is becoming increasingly clear with accumulated studies, the underlying molecular mechanisms are still unclear. Recently, integration of various high-throughput data expanded the range of candidate genes and started to generate hypotheses for understanding potential pathogenesis in complex diseases. This article presents EDdb (Eating Disorder database), the first evidence-based gene resource for eating disorder. Fifty-nine experimentally validated genes from the literature in relation to eating disorder were collected as the core dataset. Another four datasets with 2824 candidate genes across 601 genome regions were expanded based on the core dataset using different criteria (e.g., protein-protein interactions, shared cytobands, and related complex diseases). Based on human protein-protein interaction data, we reconstructed a potential molecular sub-network related to eating disorder. Furthermore, with an integrative pathway enrichment analysis of genes in EDdb, we identified an extended adipocytokine signaling pathway in eating disorder. Three genes in EDdb (ADIPO (adiponectin), TNF (tumor necrosis factor) and NR3C1 (nuclear receptor subfamily 3, group C, member 1)) link the KEGG (Kyoto Encyclopedia of Genes and Genomes) "adipocytokine signaling pathway" with the BioCarta "visceral fat deposits and the metabolic syndrome" pathway to form a joint pathway. In total, the joint pathway contains 43 genes, among which 39 genes are related to eating disorder. As the first comprehensive gene resource for eating disorder, EDdb ( http://eddb.cbi.pku.edu.cn ) enables the exploration of gene-disease relationships and cross-talk mechanisms between related disorders. Through pathway statistical studies, we revealed that abnormal body weight caused by eating disorder and obesity may both be related to dysregulation of the novel joint pathway of adipocytokine signaling. In addition, this joint pathway may be the common pathway for body weight regulation in complex human diseases related to unhealthy lifestyle.

High similarity of phylogenetic profiles of rate-limiting enzymes with inhibitory relation in Human, Mouse, Rat, budding Yeast and E. coli

Background

The phylogenetic profile is widely used to characterize functional linkage and conservation between proteins without amino acid sequence similarity. To survey the conservative regulatory properties of rate-limiting enzymes (RLEs) in metabolic inhibitory network across different species, we define the enzyme inhibiting pair as: where the first enzyme in a pair is the inhibitor provider and the second is the target of the inhibitor. Phylogenetic profiles of enzymes in the inhibiting pairs are further generated to measure the functional linkage of these enzymes during evolutionary history.

Results

We find that the RLEs generate, on average, over half of all in vivo inhibitors in each surveyed model organism. And these inhibitors inhibit on average over 85% targets in metabolic inhibitory network and cover the majority of targets of cross-pathway inhibiting relations. Furthermore, we demonstrate that the phylogenetic profiles of the enzymes in inhibiting pairs in which at least one enzyme is rate-limiting often show higher similarities than those in common inhibiting enzyme pairs. In addition, RLEs, compared to common metabolic enzymes, often tend to produce ADP instead of AMP in conservative inhibitory networks.

Conclusions

Combined with the conservative roles of RLEs in their efficiency in sensing metabolic signals and transmitting regulatory signals to the rest of the metabolic system, the RLEs may be important molecules in balancing energy homeostasis via maintaining the ratio of ATP to ADP in living cells. Furthermore, our results indicate that similarities of phylogenetic profiles of enzymes in the inhibiting enzyme pairs are not only correlated with enzyme topological importance, but also related with roles of the enzymes in metabolic inhibitory network.

Extending Asia Pacific bioinformatics into new realms in the "-omics" era

The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation dating back to 1998, was organized as the 8^th International Conference on Bioinformatics (InCoB), Sept. 7-11, 2009 at Biopolis, Singapore. Besides bringing together scientists from the field of bioinformatics in this region, InCoB has actively engaged clinicians and researchers from the area of systems biology, to facilitate greater synergy between these two groups. InCoB2009 followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India), Hong Kong and Taipei (Taiwan), with InCoB2010 scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010. The Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and symposia on Clinical Bioinformatics (CBAS), the Singapore Symposium on Computational Biology (SYMBIO) and training tutorials were scheduled prior to the scientific meeting, and provided ample opportunity for in-depth learning and special interest meetings for educators, clinicians and students. We provide a brief overview of the peer-reviewed bioinformatics manuscripts accepted for publication in this supplement, grouped into thematic areas. In order to facilitate scientific reproducibility and accountability, we have, for the first time, introduced minimum information criteria for our pubilcations, including compliance to a Minimum Information about a Bioinformatics Investigation (MIABi). As the regional research expertise in bioinformatics matures, we have delineated a minimum set of bioinformatics skills required for addressing the computational challenges of the "-omics" era.