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Preliminary studies have indicated metabolic dysfunction and gut dysbiosis in patients with bipolar disorder (BD). In this study, we aimed to clarify the impact of the gut microbial composition and function on metabolic dysfunction in BD patients with an acute depressive episode.Fresh fecal samples were provided from 58 patients with BD depression, including 29 with normal weight (NW) and 29 with overweight/obesity (OW), and 31 healthy controls (HCs). The hypervariable region of 16 S rRNA gene (V3-V4) sequencing was performed using IonS5TMXL platform to evaluate the bacterial communities. Differences of microbial community and correlation to clinical parameters across different groups were analyzed.Compared to NW and HCs, the OW group showed a decreased tendency in alpha diversity index. Beta diversity was markedly different among these groups (PERMANOVA: RSpecific bacterial taxa involved in pathways regulating the lipid, energy, and amino acid metabolisms may underlie the weight concerns in depressed BD patients. Potential targeting gut microbial therapy is provided for overweight/obesity patients with BD, which still need further studies in the future.

Antipsychotic-induced metabolic dysfunction (AIMD) is an intractable clinical challenge worldwide. The situation is becoming more critical as second-generation antipsychotics (SGAs), to a great extent, have replaced the role of first-generation antipsychotics in managing major psychiatric disorders. Although the exact mechanisms for developing AIMD is intricate, emerging evidence has indicated the involvement of the microbiota-gut-brain axis in AIMD. SGAs treatment may change the diversity and compositions of intestinal flora (e.g., decreased abundance of Bacteroidetes and Akkermansia muciniphila, and increased Firmicutes). Short-chain fatty acids and other metabolites derived from gut microbiota, on the one hand, can regulate the activity of intestinal endocrine cells and their secretion of satiety hormones (e.g., glucagon-like peptide 1, peptide YY, cholecystokinin and ghrelin); on the other hand, can activate the vagus nerve or transport into the brain to exert a central modulation of foraging behaviors via binding to neuropeptide receptors. Interestingly, metformin, a classical antidiabetic agent, is capable of alleviating AIMD possibly by regulating the microbiota-gut-brain axis. That is, metformin can not only partially reverse the alterations of gut microbial communities due to SGAs treatment, but also play a positive role in rectifying the disturbances of peripheral and central satiety-related neuropeptides. Current evidence has indicated a promising role for metformin on ameliorating AMID, but further verifications in well-designed clinical trials are still warranted.

Bipolar disorder (BD) is a common psychiatric illness with high prevalence and disease burden. Accumulating susceptibility genes for BD have been identified in recent years. However, the exact functions of these genes remain largely unknown. Despite its high heritability, gene and environment interaction is commonly accepted as the major contributing factor to BD pathogenesis. Intestine microbiota is increasingly recognized as a critical environmental factor for human health and diseases via the microbiota‐gut‐brain axis. BD individuals showed altered diversity and compositions in the commensal microbiota. In addition to pro‐inflammatory factors, such as interleukin‐6 and tumour necrosis factor‐α, type 1 interferon signalling pathway is also modulated by specific intestinal bacterial strains. Disruption of the microbiota‐gut‐brain axis contributes to peripheral and central nervous system inflammation, which accounts for the BD aetiology. Administration of type 1 interferon can induce the expression of TRANK1, which is associated with elevated circulating biomarkers of the impaired blood‐brain barrier in BD patients. In this review, we focus on the influence of intestine microbiota on the expression of bipolar gene TRANK1 and propose that intestine microbiota‐dependent type 1 interferon signalling is sufficient to induce the over‐expression of TRANK1, consequently causing the compromise of BBB integrity and facilitating the entrance of inflammatory mediators into the brain. Activated neuroinflammation eventually contributes to the occurrence and development of BD. This review provides a new perspective on how gut microbiota participate in the pathogenesis of BD. Future studies are needed to validate these assumptions and develop new treatment targets for BD.

Background: Venous thromboembolism (VTE) is a severe, life-threatening physical condition. However, the risk of developing VTE in patients with mental disorders has been insufficiently recognized.Methods: In this descriptive study, we retrospectively screened the hospital electronic medical record system and identified the asymptomatic VTE condition in hospitalized patients in the Mental Health Center, First Affiliated Hospital, Zhejiang University School of Medicine from January 2014 to January 2021. The diagnosis of VTE was made based on elevated plasma D-dimer levels and positive imaging findings, including arteriovenous color doppler ultrasonograpny of lower limbs and computed tomography angiography of pulmonary artery. For patients included, demographic and clinical profiles, and findings of laboratory and imaging examinations were collected. The anticoagulant therapy and clinical outcomes of these patients were also recorded.Results: A total of 8093 hospitalized patients were screened and eventually 24 psychiatric patients with asymptomatic VTE were included in the final analysis. The mean age of patients was 65.75±8.69 years old, with 20 patients (83.3%) older than 60 years. 18 (75%) patients were female and 6 (25%) were male. The number of patients with a history of smoking and previous pharmacotherapy was 3 and 19, respectively. And the average BMI of all subjects was 22.85±3.97, which was within the normal values. The average course of psychiatric disorders prior to the hospitalization was 9.15±10.38 years, the mean hospital stays were 23.17±9.14 days and the shortest hospital stay was 10 days. The average plasma levels of D-dimer before anticoagulant therapy was 4060.00±2824.88 ug/L FEU with a range of 920~10700 ug/L FEU (the normal range: 0~700 ug/L FEU). Following anticoagulant therapy, 83.3% (n=20) patients had a significant reduction in the plasma levels of D-dimer and the average reduced to 1678.25 ±1970.16 ug/L FEU, with a minimum level of 160 ug/L FEU. The plasma D-dimer levels between before and after anticoagulant treatment was significantly different (P＜0.05).Conclusion: Our data suggest the necessity screening the asymptomatic VTE among psychiatric patients, especially in those with advanced age, long duration of illness, and female with a long history of psychotropic treatment and high plasma levels of D-dimer. Once the diagnosis of asymptomatic VTE is confirmed, antithrombotic therapy should be initiated as early as possible to avoid fatal consequences.

Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naïve SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower α-diversity (the Shannon and Simpson’s indices) compared to HCs at baseline (p = 1.21 × 10−9, 1.23 × 10−8, respectively). We also found a significant difference in β-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of α-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.

Polygenic risk scores (PRS) have the potential to identify individuals at risk of diseases, optimizing treatment, and predicting survival outcomes. Here, we construct and validate a genome-wide association study (GWAS) derived PRS for nasopharyngeal carcinoma (NPC), using a multi-center study of six populations (6 059 NPC cases and 7 582 controls), and evaluate its utility in a nested case-control study. We show that the PRS enables effective identification of NPC high-risk individuals (AUC = 0.65) and improves the risk prediction with the PRS incremental deciles in each population (Ptrend ranging from 2.79 × 10−7 to 4.79 × 10−44). By incorporating the PRS into EBV-serology-based NPC screening, the test’s positive predictive value (PPV) is increased from an average of 4.84% to 8.38% and 11.91% in the top 10% and 5% PRS, respectively. In summary, the GWAS-derived PRS, together with the EBV test, significantly improves NPC risk stratification and informs personalized screening.

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures., Gut microbiome alterations are implicated in major depressive disorder (MDD) and bipolar disorder (BD); however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, the distinct microbial covarying units for MDD and BD are first identified, and microbial markers for distinguishing MDD from BD based on gut microbiome signatures are provided.

Acoustic data transmission in drill string is one of the effective methods to solve the bottleneck of downhole information transmission speed, but its channel characteristics are mainly affected by the structural changes of string. In the process of drilling, the downhole BHA changes constantly according to the well condition, and the shape of drill string changes indefinitely under the condition of wear and force, which leads to the uncertainty of acoustic channel. Through the numerical simulation analysis, we can get the channel changes of drill string in different shapes, and analyze the main factors that affect the information transmission. The size inconsistency of multiple drill strings will lead to the deterioration of the channel characteristics to a certain extent, but the aperiodic drilling tool structure in the channel will cause a significant change in the transmission characteristics.

Objectives: The hematopoietic stem cells transplantation (HSCT) is the only curable treatment in current for thalassemia major (TM).The quantity of auto stem cell of TM patients are very important for rescue the patients in case of failure of HSCT, and auto stem cells of TM will be used as target cells for gene therapy (GT) in the near future. Iron overload (IOL) can damage the hematopoiesis of TM. How to collect the auto stem cells in TM patients? How about the affects of iron overload in the mobilization and collection of auto stem cell? The aim of this study was to analyze quantity of auto stem cells in the TM and the affects of iron overload (IOL). Methods: We retrospectively analyzed a total of 134 patients and 25 normal donors undergoing PBSCs collection between January 2012 and December 2019. Patients with serum ferritin levels over 1,000 ng/mL and with a history of red blood cell transfusions prior to stem cell collection were defined as a group having transfusion-associated iron overload (IOL). In total one hundred and thirty-four patients and twenty-five donors were subcutaneous administrated G-CSF (Granulocyte Colony Stimulating Factor) 10 mg/kg/d Injection for 5 days, PBSCs was collected using a large volume leukapheresis (LVL) procedure. The data of WBC, MNC and CD34+ in product were analyzed by SPSS 20 software. Results: In 134 patients, median age is 8.60 range: (1-17),and 25 Normal donors, median age is 7.5 range: (1-18). The results demonstrated that cells either in patients with thalassemia or normal donors were effectively mobilized by G-CSF (10 mg / kg/d),as these children showed a marked increase in white blood cells and MNC cells in peripheral blood, reaching a peak in 4 to 5 days after the injection of G- CSF alone. Comparison of the MNC [(6.7±3.5) ×10⁸/kg vs (7.2±4.77) ×10⁸/kg] and CD34+cells [(10.29±4.5)×10⁶/kg vs (10.9±6.8)×10⁶/kg] in collected product in TM patients and normal donors groups revealed no significant difference. There was no significant difference between different Ferritin level (Mild, Intermediate and Severe) on WBC, MNC, and CD34+ in each group at the time point studied. But there was significant difference on MNC number (Normal liver iron (7.73±2.69)×10⁸/kg, Mild liver iron overload (7.66±4.64)×10⁸/kg, Intermediate (6.18± 2.84) ×10⁸/kg compared to Severe liver iron (4.45±3.34)×10⁸/kg, P=0.039. Significant difference was also can be seen in number of MNC of product in patients with intermediate cardiac iron overload compared to normal cardiac iron overload and mild cardiac iron overload (2.76±0.97) ×10⁶/kg vs(6.86±3.39) ×10⁶/kg and (6.88±3.72)×10⁶/kg, P=0.030. There was a statistically significant difference positive correlation between median age (P=0.011) and MNC/Kg (P=0.030). Conclusion:The quantity of mobilization of PBSC in TM patients had no significant difference compare to normal donor. The MNC in product was statistically decreased in intermediate cardiac iron overload and severe liver iron overload (IOL) subgroup. It indicated that iron overload (IOL) in organs may negatively relate to proliferation and mobilization of stem cells in TM. Further quality study of PBSC such as stem cell culture and ability of proliferation should be more evaluated. The sufficient quantity and high quality auto stem cell from TM patient can be more used in the future. Disclosures No relevant conflicts of interest to declare.

Rationale: Rapid eye movement sleep behavior disorder (RBD) is a kind of sleep disturbance characterized by a loss of normal paralysis of REM sleep with dream enactment behavior during REM sleep. The pharmacotherapy options for treating RBD are limited and the use of antidepressants remains controversial. Further, the role of vortioxetine in RBD has not been evaluated so far. Patient concerns: A 72-year-old woman presented with recurrent peculiar behaviors such as shouting, punching, kicking or even walking around her bedroom during sleep for over 3 years. Diagnosis: Clinical examinations and polysomnography indicated the diagnosis of RBD. Interventions: The patient received treatment with paroxetine and melatonin for 1 year and then paroxetine was discontinued and vortioxetine was initiated in a daily dose of 10 mg. Outcomes: Treatment with paroxetine and melatonin for one year was ineffective. A trial of vortioxetine 10 mg per day over 3 months resulted in significant clinical improvement. Lessons: To our knowledge, this is the first reported case of effective treatment of RBD with vortioxetine. Well-designed studies with large samples are needed to verify the clinical benefits.

Acoustic telemetry technology while drilling may effectively solve the practical and speed bottleneck of downhole information transmission, but its channel characteristics are subject to the influence of drill string structure in the channel. According to the requirements of reservoir exploitation and drilling technology, the directional well technology is becoming more complex, and the changeable bottom hole assembly (BHA) in the well causes the aperiodicity of acoustic channel. Through the modeling and analysis of BHA under different drilling technology, the characteristics of various aperiodic channels are obtained, and compared with the characteristics of ideal periodic channels, the acoustic transmission characteristics of drill string in directional well are obtained. The aperiodicity brought by BHA makes the high frequency section of the channel seriously attenuated, so the number of aperiodic drilling tools used in the acoustic remote transmission channel needs to be strictly controlled. It can be excluded from the channel if necessary.

To characterize the fractional amplitude of low-frequency fluctuation (fALFF) in drug-naïve first-episode female patients with anorexia nervosa (AN) using resting-state functional magnetic resonance imaging (rs-fMRI). Whole brain rs-fMRI data were collected from 7 drug-naïve first-episode female patients with DSM-5 AN and 14 age-matched healthy female controls. fALFF values were calculated and compared between the two groups using a two-sample t test. Correlation analysis between the fALFF values in the entire brain and body mass index (BMI) was performed. Compared with the healthy controls, increased fALFF values were observed in the AN patients in their right hippocampus and left superior frontal gyrus, while decreased fALFF values were observed in their left rectus and left middle occipital gyrus. Moreover, low BMI was significantly associated with decreased fALFF in the left inferior frontal gyrus but increased fALFF in the left calcarine. In particular, the z-standardized fALFF (zfALFF) value of the left rectus was positive associated with BMI. Our findings suggest that spontaneous brain activity in the frontal region, hippocampus and rectus, characterized by fALFF values, was altered in drug-naïve, first-episode female patients with AN.

The maize PI gene encodes a myb-homologous protein that regulates flavonoid pigment biosynthesis in floral organs including the kernel pericarp, cob glume and tassel glume. The Pl-rr allele coding sequence is flanked by long (5.2 kbp) direct repeats. To clarily the origin of the unusual P-rr gene structure, we isolated and characterized a second, tightly linked, maize gene {P2). and a related gene {P2-t) from teosinte parviglumis. the closest wild relative of maize. The maize P2 gene and the teosinte P2-t gene are homologous to the maize PI gene in the coding region and 3" flanking region, but not in the 5' flanking region. The 5" flanking regions of maize P2 and teosinte P2-t are similar to each other, but different from that of the maize PI gene. We propose that the maize PI and P2 genes were generated by a tandem (head-to-tail) gene duplication in which the 3" flanking sequence of the progenitor P gene was duplicated at the 5' side of the incipient PI gene, thereby generating the long direct repeats that flank the Pl-rr allele. This duplication event occurred approximately 2.75 MYA. and subsequent insertions of retroelements separated the PI and P2 genes. Pigmentation phenotypes and transcript analysis indicate that the two duplicated maize P genes and the teosinte P2-t gene have distinct tissue specific expression patterns. The

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible database describing metabolic pathways and enzymes from all domains of life. MetaCyc pathways are experimentally determined, mostly small-molecule metabolic pathways and are curated from the primary scientific literature. MetaCyc contains >2100 pathways derived from >37 000 publications, and is the largest curated collection of metabolic pathways currently available. BioCyc (BioCyc.org) is a collection of >3000 organism-specific Pathway/Genome Databases (PGDBs), each containing the full genome and predicted metabolic network of one organism, including metabolites, enzymes, reactions, metabolic pathways, predicted operons, transport systems and pathway-hole fillers. Additions to BioCyc over the past 2 years include YeastCyc, a PGDB for Saccharomyces cerevisiae, and 891 new genomes from the Human Microbiome Project. The BioCyc Web site offers a variety of tools for querying and analysis of PGDBs, including Omics Viewers and tools for comparative analysis. New developments include atom mappings in reactions, a new representation of glycan degradation pathways, improved compound structure display, better coverage of enzyme kinetic data, enhancements of the Web Groups functionality, improvements to the Omics viewers, a new representation of the Enzyme Commission system and, for the desktop version of the software, the ability to save display states.

Plant metabolism underpins many traits of ecological and agronomic importance. Plants produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have not yet been elucidated. To engineer and improve metabolic traits, we need comprehensive and accurate knowledge of the organization and regulation of plant metabolism at the genome scale. Here, we present a computational pipeline to identify metabolic enzymes, pathways, and gene clusters from a sequenced genome. Using this pipeline, we generated metabolic pathway databases for 22 species and identified metabolic gene clusters from 18 species. This unified resource can be used to conduct a wide array of comparative studies of plant metabolism. Using the resource, we discovered a widespread occurrence of metabolic gene clusters in plants: 11,969 clusters from 18 species. The prevalence of metabolic gene clusters offers an intriguing possibility of an untapped source for uncovering new metabolite biosynthesis pathways. For example, more than 1,700 clusters contain enzymes that could generate a specialized metabolite scaffold (signature enzymes) and enzymes that modify the scaffold (tailoring enzymes). In four species with sufficient gene expression data, we identified 43 highly coexpressed clusters that contain signature and tailoring enzymes, of which eight were characterized previously to be functional pathways. Finally, we identified patterns of genome organization that implicate local gene duplication and, to a lesser extent, single gene transposition as having played roles in the evolution of plant metabolic gene clusters.

Transcription factors (TFs) are proteins that regulate the expression of target genes by binding to specific cis-elements in promoter regions. Transcriptional regulators (TRs) also regulate the expression of target genes; however, they operate indirectly via interaction with the basal transcription apparatus (e.g. TFs), or by altering the accessibility of DNA to TFs via chromatin remodeling. Another type of regulatory proteins, protein kinases (PKs), function in signal transduction pathways and alter the activity of target proteins by phosphorylating them. These three important classes of regulatory proteins have been associated with numerous aspects of plant growth and development (Gapper et al., 2014; Xu and Zhang, 2015), and response to biotic and abiotic stimuli (Mickelbart et al., 2015; Zhang et al., 2013). Effective and accurate identification and classification of these genes is important for understanding their evolution, biological functions, and regulatory networks. Currently, more than 100 plant genomes have been sequenced and regulatory proteins have been systematically identified from several of these plant genomes. Databases presenting these regulatory proteins, especially TFs, have been developed, such as PlnTFDB (Pérez-Rodríguez et al., 2010) and PlantTFDB (Jin et al., 2013). However, annotations of TF/TR families and the associated classification rules have been inconsistent among different studies. For example, the PlantTFDB does not include TRs that are presented in PlnTFDB. As another example, the ?forbidden? domain (a domain that the specific TF families should not contain) of the C2H2 family is annotated as an RNase_T domain in PlantTFDB, but as a PHD domain in PlnTFDB. Presently, while the collection of genome sequences is rapidly expanding, cataloged and annotated TFs/TRs vary across different databases due to inconsistent identification and characterization criteria with serious consequences for genome scale and targeted analyses. Furthermore, in contrast to many studies focusing on specific families of plant regulators, computational tools for identification and classification of these regulatory proteins on a genome scale are very limited. Fil: Zheng, Yi. Boyce Thompson Institute; Estados Unidos Fil: Jiao, Chen. Boyce Thompson Institute; Estados Unidos Fil: Sun, Honghe. Boyce Thompson Institute; Estados Unidos Fil: Rosli, Hernan Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Fisiología Vegetal. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Instituto de Fisiología Vegetal; Argentina. Boyce Thompson Institute; Estados Unidos Fil: Pombo, Marina Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Fisiología Vegetal. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Instituto de Fisiología Vegetal; Argentina. Boyce Thompson Institute; Estados Unidos Fil: Zhang, Peifen. Carnegie Institution for Science; Estados Unidos Fil: Banf, Michael. Carnegie Institution for Science; Estados Unidos Fil: Dai, Xinbin. Samuel Roberts Noble Foundation; Estados Unidos Fil: Martin, Gregory B.. Boyce Thompson Institute; Estados Unidos. Cornell University; Estados Unidos Fil: Giovannoni, James J.. Boyce Thompson Institute; Estados Unidos. Center for Agriculture and Health; Estados Unidos Fil: Zhao, Patrick X.. Samuel Roberts Noble Foundation; Estados Unidos Fil: Rhee, Seung Y.. Carnegie Institution for Science; Estados Unidos Fil: Fei, Zhangjun. Boyce Thompson Institute; Estados Unidos. Center for Agriculture and Health; Estados Unidos

Background As metabolic pathway resources become more commonly available, researchers have unprecedented access to information about their organism of interest. Despite efforts to ensure consistency between various resources, information content and quality can vary widely. Two maize metabolic pathway resources for the B73 inbred line, CornCyc 4.0 and MaizeCyc 2.2, are based on the same gene model set and were developed using Pathway Tools software. These resources differ in their initial enzymatic function assignments and in the extent of manual curation. We present an in-depth comparison between CornCyc and MaizeCyc to demonstrate the effect of initial computational enzymatic function assignments on the quality and content of metabolic pathway resources. Results These two resources are different in their content. MaizeCyc contains GO annotations for over 21,000 genes that CornCyc is missing. CornCyc contains on average 1.6 transcripts per gene, while MaizeCyc contains almost no alternate splicing. MaizeCyc also does not match CornCyc’s breadth in representing the metabolic domain; MaizeCyc has fewer compounds, reactions, and pathways than CornCyc. CornCyc’s computational predictions are more accurate than those in MaizeCyc when compared to experimentally determined function assignments, demonstrating the relative strength of the enzymatic function assignment pipeline used to generate CornCyc. Conclusions Our results show that the quality of initial enzymatic function assignments primarily determines the quality of the final metabolic pathway resource. Therefore, biologists should pay close attention to the methods and information sources used to develop a metabolic pathway resource to gauge the utility of using such functional assignments to construct hypotheses for experimental studies. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0369-x) contains supplementary material, which is available to authorized users.

Method for extracting and comparing data from CornCyc and MaizeCyc. This document describes how CornCyc and MaizeCyc data were selected, extracted, and filtered and/or modified before comparison. The five major data types, Genes, Proteins, Compounds, Pathways, and Reactions were each handled in unique ways. (PDF 342 kb)

The Arabidopsis Information Resource (TAIR, http://arabidopsis.org) is the model organism database for the fully sequenced and intensively studied model plant Arabidopsis thaliana. Data in TAIR is derived in large part from manual curation of the Arabidopsis research literature and direct submissions from the research community. New developments at TAIR include the addition of the GBrowse genome viewer to the TAIR site, a redesigned home page, navigation structure and portal pages to make the site more intuitive and easier to use, the launch of several TAIR web services and a new genome annotation release (TAIR7) in April 2007. A combination of manual and computational methods were used to generate this release, which contains 27,029 protein-coding genes, 3889 pseudogenes or transposable elements and 1123 ncRNAs (32,041 genes in all, 37,019 gene models). A total of 681 new genes and 1002 new splice variants were added. Overall, 10,098 loci (one-third of all loci from the previous TAIR6 release) were updated for the TAIR7 release.

MetaCyc is a database of metabolic pathways and enzymes located at http://MetaCyc.org/. Its goal is to serve as a metabolic encyclopedia, containing a collection of non-redundant pathways central to small molecule metabolism, which have been reported in the experimental literature. Most of the pathways in MetaCyc occur in microorganisms and plants, although animal pathways are also represented. MetaCyc contains metabolic pathways, enzymatic reactions, enzymes, chemical compounds, genes and review-level comments. Enzyme information includes substrate specificity, kinetic properties, activators, inhibitors, cofactor requirements and links to sequence and structure databases. Data are curated from the primary literature by curators with expertise in biochemistry and molecular biology. MetaCyc serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. Querying, visualization and curation of the database is supported by SRI's Pathway Tools software. The PathoLogic component of Pathway Tools is used in conjunction with MetaCyc to predict the metabolic network of an organism from its annotated genome. SRI and the European Bioinformatics Institute employed this tool to create pathway/genome databases (PGDBs) for 165 organisms, available at the BioCyc.org website. These PGDBs also include predicted operons and pathway hole fillers.

Cultivated and wild potatoes contain a major disease-resistance cluster on the short arm of chromosome V, including the R1 resistance (R) gene against potato late blight. To explore the functional and evolutionary significance of clustering in the generation of novel disease-resistance genes, we constructed three approximately 1 Mb physical maps in the R1 gene region, one for each of the three genomes (haplotypes) of allohexaploid Solanum demissum, the wild potato progenitor of the R1 locus. Totals of 691, 919 and 559 kb were sequenced for each haplotype, and three distinct resistance-gene families were identified, one homologous to the potato R1 gene and two others homologous to either the Prf or the Bs4 R-gene of tomato. The regions with R1 homologues are highly divergent among the three haplotypes, in contrast to the conserved flanking non-resistance gene regions. The R1 locus shows dramatic variation in overall length and R1 homologue number among the three haplotypes. Sequence comparisons of the R1 homologues show that they form three distinct clades in a distance tree. Frequent sequence exchanges were detected among R1 homologues within each clade, but not among those in different clades. These frequent sequence exchanges homogenized the intron sequences of homologues within each clade, but did not homogenize the coding sequences. Our results suggest that the R1 homologues represent three independent groups of fast-evolving type I resistance genes, characterized by chimeric structures resulting from frequent sequence exchanges among group members. Such genes were first identified among clustered RGC2 genes in lettuce, where they were distinguished from slow-evolving type II R-genes. Our findings at the R1 locus in S. demissum may indicate that a common or similar mechanism underlies the previously reported differentiation of type I and type II R-genes and the differentiation of type I R-genes into distinct groups, identified here.

MetaCyc (http://metacyc.org) contains experimentally determined biochemical pathways to be used as a reference database for metabolism. In conjunction with the Pathway Tools software, MetaCyc can be used to computationally predict the metabolic pathway complement of an annotated genome. To increase the breadth of pathways and enzymes, more than 60 plant-specific pathways have been added or updated in MetaCyc recently. In contrast to MetaCyc, which contains metabolic data for a wide range of organisms, AraCyc is a species-specific database containing only enzymes and pathways found in the model plant Arabidopsis (Arabidopsis thaliana). AraCyc (http://arabidopsis.org/tools/aracyc/) was the first computationally predicted plant metabolism database derived from MetaCyc. Since its initial computational build, AraCyc has been under continued curation to enhance data quality and to increase breadth of pathway coverage. Twenty-eight pathways have been manually curated from the literature recently. Pathway predictions in AraCyc have also been recently updated with the latest functional annotations of Arabidopsis genes that use controlled vocabulary and literature evidence. AraCyc currently features 1,418 unique genes mapped onto 204 pathways with 1,156 literature citations. The Omics Viewer, a user data visualization and analysis tool, allows a list of genes, enzymes, or metabolites with experimental values to be painted on a diagram of the full pathway map of AraCyc. Other recent enhancements to both MetaCyc and AraCyc include implementation of an evidence ontology, which has been used to provide information on data quality, expansion of the secondary metabolism node of the pathway ontology to accommodate curation of secondary metabolic pathways, and enhancement of the cellular component ontology for storing and displaying enzyme and pathway locations within subcellular compartments.

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species.

The MetaCyc database (see URL http://MetaCyc.org) is a collection of metabolic pathways and enzymes from a wide variety of organisms, primarily microorganisms and plants. The goal of MetaCyc is to contain a representative sample of each experimentally elucidated pathway, and thereby to catalog the universe of metabolism. MetaCyc also describes reactions, chemical compounds and genes. Many of the pathways and enzymes in MetaCyc contain extensive information, including comments and literature citations. SRI’s Pathway Tools software supports querying, visualization and curation of MetaCyc. With its wide breadth and depth of metabolic information, MetaCyc is a valuable resource for a variety of applications. MetaCyc is the reference database of pathways and enzymes that is used in conjunction with SRI’s metabolic pathway prediction program to create Pathway/Genome Databases that can be augmented with curation from the scientific literature and published on the world wide web. MetaCyc also serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. In the past 2 years the data content and the Pathway Tools software used to query, visualize and edit MetaCyc have been expanded significantly. These enhancements are described in this paper.

The cultivated potato (Solanum tuberosum) shares similar biology with other members of the Solanaceae, yet has features unique within the family, such as modified stems (stolons) that develop into edible tubers. To better understand potato biology, we have undertaken a survey of the potato transcriptome using expressed sequence tags (ESTs) from diverse tissues. A total of 61,940 ESTs were generated from aerial tissues, below-ground tissues, and tissues challenged with the late-blight pathogen (Phytophthora infestans). Clustering and assembly of these ESTs resulted in a total of 19,892 unique sequences with 8,741 tentative consensus sequences and 11,151 singleton ESTs. We were able to identify a putative function for 43.7% of these sequences. A number of sequences (48) were expressed throughout the libraries sampled, representing constitutively expressed sequences. Other sequences (13,068, 21%) were uniquely expressed and were detected only in a single library. Using hierarchal and k means clustering of the EST sequences, we were able to correlate changes in gene expression with major physiological events in potato biology. Using pair-wise comparisons of tuber-related tissues, we were able to associate genes with tuber initiation, dormancy, and sprouting. We also were able to identify a number of characterized as well as novel sequences that were unique to the incompatible interaction of late-blight pathogen, thereby providing a foundation for further understanding the mechanism of resistance.

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) provides an integrated view of genomic data for Arabidopsis thaliana. The information is obtained from a battery of sources, including the Arabidopsis user community, the literature, and the major genome centers. Currently TAIR provides information about genes, markers, polymorphisms, maps, sequences, clones, DNA and seed stocks, gene families and proteins. In addition, users can find Arabidopsis publications and information about Arabidopsis researchers. Our emphasis is now on incorporating functional annotations of genes and gene products, genome-wide expression, and biochemical pathway data. Among the tools developed at TAIR, the most notable is the Sequence Viewer, which displays gene annotation, clones, transcripts, markers and polymorphisms on the Arabidopsis genome, and allows zooming in to the nucleotide level. A tool recently released is AraCyc, which is designed for visualization of biochemical pathways. We are also developing tools to extract information from the literature in a systematic way, and building controlled vocabularies to describe biological concepts in collaboration with other database groups. A significant new feature is the integration of the ABRC database functions and stock ordering system, which allows users to place orders for seed and DNA stocks directly from the TAIR site.

The formation of cytoplasmic stress granules and the innate immune response are two distinct cellular stress responses. Our study investigated the involvement of four innate immune proteins - retinoic-acid-inducible gene I (RIG-I, also known as DDX58), melanoma differentiation-associated gene 5 (MDA5, also known as IFIH1), IFN-β promoter stimulator (IPS-1, also known as MAVS) and protein kinase regulated by dsRNA (PKR, also known as EIF2AK2) in the formation of stress granules. Knockdown of IPS-1 or PKR significantly decreased the formation of stress granules induced by double-stranded (ds)RNA. IPS-1 depletion markedly attenuated the phosphorylation of PKR and eIF2α that was triggered by dsRNA, and IPS-1 facilitated the in vitro autophosphorylation of PKR. In IPS-1-depleted cells, the dsRNA-mediated dimerization of PKR through its dsRNA-binding domains was significantly abrogated, suggesting that IPS-1 might be involved in PKR dimerization. By co-immunoprecipitation and pulldown assays, our data demonstrate that IPS-1 directly binds to PKR through the IPS-1 caspase activation and recruitment domain (CARD), suggesting that the effect of IPS-1 on the formation of stress granules might be exerted through interacting with PKR and mediating its activation. PKR was recruited into stress granules upon activation, whereas the majority of IPS-1 protein formed clusters on mitochondrial membranes. Our work provides the first evidence that the innate signaling molecule IPS-1 plays an essential role in stress granule formation.

The myb-homologous p1 gene regulates the synthesis of flavonoid pigments in maize kernel pericarp and cob; these floral organs are greatly modified in size and shape compared with their counterparts in teosinte, the progenitor of maize. To elucidate the molecular evolution of the p1 gene in relation to its expression and possible functions in maize and teosinte, we have isolated a second maize gene (p2) that is highly homologous with the p1 gene, and a related gene (p2-t) from Zea mays subsp parviglumis. We present evidence that the maize p1 and p2 genes were generated by duplication of an ancestral p gene (p(pre)) and its downstream sequences; the duplicated 3' flanking sequences were inserted upstream of the p(pre) gene, thereby changing its transcription pattern. This model accounts for the structural organization and the observed differential expression of the p1 and p2 genes: p1 transcripts accumulate in kernel pericarp, cob, tassel glumes, and silk, whereas p2 transcripts are found in developing anther and silk. The duplication is estimated to have occurred 2.75 million years ago; subsequently, multiple retroelements have been inserted between the p1 and p2 genes. Our results demonstrate the evolution of a single gene into a compound locus containing two component genes with different tissue specificities. Expression of the p1 gene in the kernel pericarp may have provided a selective advantage during the evolution of maize kernel morphology.

The formation of cytoplasmic stress granules and the innate immune response are two distinct cellular stress responses. Our study investigated the involvement of four innate immune proteins - retinoic-acid-inducible gene I (RIG-I, also known as DDX58), melanoma differentiation-associated gene 5 (MDA5, also known as IFIH1), IFN-β promoter stimulator (IPS-1, also known as MAVS) and protein kinase regulated by dsRNA (PKR, also known as EIF2AK2) in the formation of stress granules. Knockdown of IPS-1 or PKR significantly decreased the formation of stress granules induced by double-stranded (ds)RNA. IPS-1 depletion markedly attenuated the phosphorylation of PKR and eIF2α that was triggered by dsRNA, and IPS-1 facilitated the in vitro autophosphorylation of PKR. In IPS-1-depleted cells, the dsRNA-mediated dimerization of PKR through its dsRNA-binding domains was significantly abrogated, suggesting that IPS-1 might be involved in PKR dimerization. By co-immunoprecipitation and pulldown assays, our data demonstrate that IPS-1 directly binds to PKR through the IPS-1 caspase activation and recruitment domain (CARD), suggesting that the effect of IPS-1 on the formation of stress granules might be exerted through interacting with PKR and mediating its activation. PKR was recruited into stress granules upon activation, whereas the majority of IPS-1 protein formed clusters on mitochondrial membranes. Our work provides the first evidence that the innate signaling molecule IPS-1 plays an essential role in stress granule formation.

Background Dengue virus (DENV) is found in the tropical and subtropical regions and affects millions of people annually. Currently, no specific vaccine or antiviral treatment against dengue virus is available. Innate immunity has been shown to be important for host resistance to DENV infection. Although protein kinase regulated by double-stranded RNA (PKR) has been found to promote the innate signaling in response to infection by several viruses, its role in the innate response to DENV infection is still unclear. Our study aimed to investigate the role of PKR in DENV-induced innate immune responses. Methodology/Principal Findings By RNAi, silencing of PKR significantly enhanced the expression of interferon (IFN)-β in DENV infected human lung epithelial A549 cells. Western blot and immunofluorescence microscopy data showed that PKR knockdown upregulated the activation of innate signaling cascades including p38 and JNK mitogen-activated protein kinases (MAPKs), interferon regulatory factor-3 and NF-κB, following DENV2 infection. Likewise, a negative regulatory effect of PKR on the IFN production was also observed in poly(IC) challenged cells. Moreover, the PKR knockdown-mediated IFN induction was attenuated by RIG-I or IPS-1 silencing. Finally, overexpression of a catalytically inactive PKR mutant (K296R), but not of a mutant lacking dsRNA binding activity (K64E) or the double mutant (K64EK296R), reversed the IFN induction mediated by PKR knockdown, suggesting that the dsRNA binding activity is required for PKR to downregulate IFN production. Conclusions/Significance PKR acts as a negative regulator of IFN induction triggered by DENVs and poly(IC), and this regulation relies on its dsRNA binding activity. These findings reveal a novel regulatory role for PKR in innate immunity, suggesting that PKR might be a promising target for anti-DENV treatments.

The MetaCyc database (http://metacyc.org/) provides a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. MetaCyc contains more than 1800 pathways derived from more than 30 000 publications, and is the largest curated collection of metabolic pathways currently available. Most reactions in MetaCyc pathways are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes and literature citations. BioCyc (http://biocyc.org/) is a collection of more than 1700 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference database, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs contain additional features, including predicted operons, transport systems and pathway-hole fillers. The BioCyc website and Pathway Tools software offer many tools for querying and analysis of PGDBs, including Omics Viewers and comparative analysis. New developments include a zoomable web interface for diagrams; flux-balance analysis model generation from PGDBs; web services; and a new tool called Web Groups.

Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http://plantcyc.org).

Cultivated and wild potatoes contain a major disease-resistance cluster on the short arm of chromosome V, including the R1 resistance (R) gene against potato late blight. To explore the functional and evolutionary significance of clustering in the generation of novel disease-resistance genes, we constructed three approximately 1 Mb physical maps in the R1 gene region, one for each of the three genomes (haplotypes) of allohexaploid Solanum demissum, the wild potato progenitor of the R1 locus. Totals of 691, 919 and 559 kb were sequenced for each haplotype, and three distinct resistance-gene families were identified, one homologous to the potato R1 gene and two others homologous to either the Prf or the Bs4 R-gene of tomato. The regions with R1 homologues are highly divergent among the three haplotypes, in contrast to the conserved flanking non-resistance gene regions. The R1 locus shows dramatic variation in overall length and R1 homologue number among the three haplotypes. Sequence comparisons of the R1 homologues show that they form three distinct clades in a distance tree. Frequent sequence exchanges were detected among R1 homologues within each clade, but not among those in different clades. These frequent sequence exchanges homogenized the intron sequences of homologues within each clade, but did not homogenize the coding sequences. Our results suggest that the R1 homologues represent three independent groups of fast-evolving type I resistance genes, characterized by chimeric structures resulting from frequent sequence exchanges among group members. Such genes were first identified among clustered RGC2 genes in lettuce, where they were distinguished from slow-evolving type II R-genes. Our findings at the R1 locus in S. demissum may indicate that a common or similar mechanism underlies the previously reported differentiation of type I and type II R-genes and the differentiation of type I R-genes into distinct groups, identified here.

AraCyc is a database containing biochemical pathways of Arabidopsis, developed at The Arabidopsis Information Resource (http://www.arabidopsis.org). The aim of AraCyc is to represent Arabidopsis metabolism as completely as possible with a user-friendly Web-based interface. It presently features more than 170 pathways that include information on compounds, intermediates, cofactors, reactions, genes, proteins, and protein subcellular locations. The database uses Pathway Tools software, which allows the users to visualize a bird's eye view of all pathways in the database down to the individual chemical structures of the compounds. The database was built using Pathway Tools' Pathologic module with MetaCyc, a collection of pathways from more than 150 species, as a reference database. This initial build was manually refined and annotated. More than 20 plant-specific pathways, including carotenoid, brassinosteroid, and gibberellin biosyntheses have been added from the literature. A list of more than 40 plant pathways will be added in the coming months. The quality of the initial, automatic build of the database was compared with the manually improved version, and with EcoCyc, an Escherichia coli database using the same software system that has been manually annotated for many years. In addition, a Perl interface, PerlCyc, was developed that allows programmers to access Pathway Tools databases from the popular Perl language. AraCyc is available at the tools section of The Arabidopsis Information Resource Web site (http://www.arabidopsis.org/tools/aracyc).