Clinical and echocardiographic evolution of patients with arrhythmogenic cardiomyopathy before heart transplantation.

BACKGROUND: Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiomyopathy characterized by fibrofatty myocardial replacement, and accurate diagnosis can be challenging. The clinical course of patients expressing a severe phenotype of the disease needing heart transplantation (HTx) is not well described in the literature. Therefore, this study aims to describe the clinical and echocardiographic evolution of patients with ACM necessitating HTx. METHODS: We retrospectively studied all patients who underwent HTx in our institution between 1998 and 2019 with a definite diagnosis of ACM according to the explanted heart examination. RESULTS: Ten patients with confirmed ACM underwent HTx. Only four of them had a diagnosis of ACM before HTx. These patients were 28 ± 15 years old at the time of their first symptoms. Patients received a diagnosis of heart failure (HF) after 5.9 ± 8.7 years of symptom evolution. The mean age at transplantation was 40 ± 17 years old. All the patients experienced ventricular tachycardia (VT) at least once before their HTx and 50% were resuscitated after sudden death. The mean left ventricular ejection at diagnosis and before transplantation was similar (32% ± 21% vs. 35.0% ± 19.3%, p = NS). Right ventricular dysfunction was present in all patients at the time of transplantation. CONCLUSION: Patients with ACM necessitating HTx show a high burden of ventricular arrhythmias and frequently present a biventricular involvement phenotype, making early diagnosis challenging. HF symptoms are the most frequent reason leading to the decision to transplant.

EcoCyc: fusing model organism databases with systems biology.

EcoCyc (http://EcoCyc.org) is a model organism database built on the genome sequence of Escherichia coli K-12 MG1655. Expert manual curation of the functions of individual E. coli gene products in EcoCyc has been based on information found in the experimental literature for E. coli K-12-derived strains. Updates to EcoCyc content continue to improve the comprehensive picture of E. coli biology. The utility of EcoCyc is enhanced by new tools available on the EcoCyc web site, and the development of EcoCyc as a teaching tool is increasing the impact of the knowledge collected in EcoCyc.

Addition of Escherichia coli K-12 growth observation and gene essentiality data to the EcoCyc database.

The sets of compounds that can support growth of an organism are defined by the presence of transporters and metabolic pathways that convert nutrient sources into cellular components and energy for growth. A collection of known nutrient sources can therefore serve both as an impetus for investigating new metabolic pathways and transporters and as a reference for computational modeling of known metabolic pathways. To establish such a collection for Escherichia coli K-12, we have integrated data on the growth or nongrowth of E. coli K-12 obtained from published observations using a variety of individual media and from high-throughput phenotype microarrays into the EcoCyc database. The assembled collection revealed a substantial number of discrepancies between the high-throughput data sets, which we investigated where possible using low-throughput growth assays on soft agar and in liquid culture. We also integrated six data sets describing 16,119 observations of the growth of single-gene knockout mutants of E. coli K-12 into EcoCyc, which are relevant to antimicrobial drug design, provide clues regarding the roles of genes of unknown function, and are useful for validating metabolic models. To make this information easily accessible to EcoCyc users, we developed software for capturing, querying, and visualizing cellular growth assays and gene essentiality data.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases.

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.

Young patient presenting with cardiogenic shock and refractory ventricular tachycardia: a case of unsuspected arrhythmogenic cardiomyopathy leading to urgent heart transplantation.

Arrhythmogenic right ventricular cardiomyopathy is an important differential diagnosis in young patients presenting with palpitations and/or dyspnea and must be appropriately investigated. A 23-year-old man presented with cardiogenic shock and monomorphic ventricular tachycardia. He reported palpitations and progressive dyspnea for more than two years, but those symptoms were attributed to anxiety without any further investigation by his family physician. Investigations after the catastrophic presentation in our center suggested terminal right-sided heart failure with severe hepatic insufficiency and acute kidney injury. The patient benefited from extracorporeal membrane oxygenation, followed by an urgent heart transplant 16 days later after the exclusion of liver cirrhosis. Histopathologic analysis of the explanted heart confirmed arrhythmogenic cardiomyopathy.

Computing minimal nutrient sets from metabolic networks via linear constraint solving.

BACKGROUND: As more complete genome sequences become available, bioinformatics challenges arise in how to exploit genome sequences to make phenotypic predictions. One type of phenotypic prediction is to determine sets of compounds that will support the growth of a bacterium from the metabolic network inferred from the genome sequence of that organism. RESULTS: We present a method for computationally determining alternative growth media for an organism based on its metabolic network and transporter complement. Our method predicted 787 alternative anaerobic minimal nutrient sets for Escherichia coli K-12 MG1655 from the EcoCyc database. The program automatically partitioned the nutrients within these sets into 21 equivalence classes, most of which correspond to compounds serving as sources of carbon, nitrogen, phosphorous, and sulfur, or combinations of these essential elements. The nutrient sets were predicted with 72.5% accuracy as evaluated by comparison with 91 growth experiments. Novel aspects of our approach include (a) exhaustive consideration of all combinations of nutrients rather than assuming that all element sources can substitute for one another(an assumption that can be invalid in general) (b) leveraging the notion of a machinery-duplicating constraint, namely, that all intermediate metabolites used in active reactions must be produced in increasing concentrations to prevent successive dilution from cell division, (c) the use of Satisfiability Modulo Theory solvers rather than Linear Programming solvers, because our approach cannot be formulated as linear programming, (d) the use of Binary Decision Diagrams to produce an efficient implementation. CONCLUSIONS: Our method for generating minimal nutrient sets from the metabolic network and transporters of an organism combines linear constraint solving with binary decision diagrams to efficiently produce solution sets to provided growth problems.

EcoCyc: a comprehensive database of Escherichia coli biology.

EcoCyc (http://EcoCyc.org) is a comprehensive model organism database for Escherichia coli K-12 MG1655. From the scientific literature, EcoCyc captures the functions of individual E. coli gene products; their regulation at the transcriptional, post-transcriptional and protein level; and their organization into operons, complexes and pathways. EcoCyc users can search and browse the information in multiple ways. Recent improvements to the EcoCyc Web interface include combined gene/protein pages and a Regulation Summary Diagram displaying a graphical overview of all known regulatory inputs to gene expression and protein activity. The graphical representation of signal transduction pathways has been updated, and the cellular and regulatory overviews were enhanced with new functionality. A specialized undergraduate teaching resource using EcoCyc is being developed.

Discovering novel subsystems using comparative genomics.

MOTIVATION: Key problems for computational genomics include discovering novel pathways in genome data, and discovering functional interaction partners for genes to define new members of partially elucidated pathways. RESULTS: We propose a novel method for the discovery of subsystems from annotated genomes. For each gene pair, a score measuring the likelihood that the two genes belong to a same subsystem is computed using genome context methods. Genes are then grouped based on these scores, and the resulting groups are filtered to keep only high-confidence groups. Since the method is based on genome context analysis, it relies solely on structural annotation of the genomes. The method can be used to discover new pathways, find missing genes from a known pathway, find new protein complexes or other kinds of functional groups and assign function to genes. We tested the accuracy of our method in Escherichia coli K-12. In one configuration of the system, we find that 31.6% of the candidate groups generated by our method match a known pathway or protein complex closely, and that we rediscover 31.2% of all known pathways and protein complexes of at least 4 genes. We believe that a significant proportion of the candidates that do not match any known group in E.coli K-12 corresponds to novel subsystems that may represent promising leads for future laboratory research. We discuss in-depth examples of these findings. AVAILABILITY: Predicted subsystems are available at http://brg.ai.sri.com/pwy-discovery/journal.html. CONTACT: lferrer@ai.sri.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases.

The MetaCyc database (MetaCyc.org) is 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. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 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, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism.

EcoCyc: a comprehensive view of Escherichia coli biology.

EcoCyc (http://EcoCyc.org) provides a comprehensive encyclopedia of Escherichia coli biology. EcoCyc integrates information about the genome, genes and gene products; the metabolic network; and the regulatory network of E. coli. Recent EcoCyc developments include a new initiative to represent and curate all types of E. coli regulatory processes such as attenuation and regulation by small RNAs. EcoCyc has started to curate Gene Ontology (GO) terms for E. coli and has made a dataset of E. coli GO terms available through the GO Web site. The curation and visualization of electron transfer processes has been significantly improved. Other software and Web site enhancements include the addition of tracks to the EcoCyc genome browser, in particular a type of track designed for the display of ChIP-chip datasets, and the development of a comparative genome browser. A new Genome Omics Viewer enables users to paint omics datasets onto the full E. coli genome for analysis. A new advanced query page guides users in interactively constructing complex database queries against EcoCyc. A Macintosh version of EcoCyc is now available. A series of Webinars is available to instruct users in the use of EcoCyc.

The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases.

MetaCyc (MetaCyc.org) is a universal database of metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are curated from the primary scientific literature, and are experimentally determined small-molecule metabolic pathways. Each reaction in a MetaCyc pathway is annotated with one or more well-characterized enzymes. Because MetaCyc contains only experimentally elucidated knowledge, it provides a uniquely high-quality resource for metabolic pathways and enzymes. BioCyc (BioCyc.org) is a collection of more than 350 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the predicted metabolic network of one organism, including metabolic pathways, enzymes, metabolites and reactions predicted by the Pathway Tools software using MetaCyc as a reference database. BioCyc PGDBs also contain predicted operons and predicted pathway hole fillers-predictions of which enzymes may catalyze pathway reactions that have not been assigned to an enzyme. The BioCyc website offers many tools for computational analysis of PGDBs, including comparative analysis and analysis of omics data in a pathway context. The BioCyc PGDBs generated by SRI are offered for adoption by any interested party for the ongoing integration of metabolic and genome-related information about an organism.

Multidimensional annotation of the Escherichia coli K-12 genome.

The annotation of the Escherichia coli K-12 genome in the EcoCyc database is one of the most accurate, complete and multidimensional genome annotations. Of the 4460 E. coli genes, EcoCyc assigns biochemical functions to 76%, and 66% of all genes had their functions determined experimentally. EcoCyc assigns E. coli genes to Gene Ontology and to MultiFun. Seventy-five percent of gene products contain reviews authored by the EcoCyc project that summarize the experimental literature about the gene product. EcoCyc information was derived from 15 000 publications. The database contains extensive descriptions of E. coli cellular networks, describing its metabolic, transport and transcriptional regulatory processes. A comparison to genome annotations for other model organisms shows that the E. coli genome contains the most experimentally determined gene functions in both relative and absolute terms: 2941 (66%) for E. coli, 2319 (37%) for Saccharomyces cerevisiae, 1816 (5%) for Arabidopsis thaliana, 1456 (4%) for Mus musculus and 614 (4%) for Drosophila melanogaster. Database queries to EcoCyc survey the global properties of E. coli cellular networks and illuminate the extent of information gaps for E. coli, such as dead-end metabolites. EcoCyc provides a genome browser with novel properties, and a novel interactive display of transcriptional regulatory networks.

Finding sequences for over 270 orphan enzymes.

Despite advances in sequencing technology, there are still significant numbers of well-characterized enzymatic activities for which there are no known associated sequences. These 'orphan enzymes' represent glaring holes in our biological understanding, and it is a top priority to reunite them with their coding sequences. Here we report a methodology for resolving orphan enzymes through a combination of database search and literature review. Using this method we were able to reconnect over 270 orphan enzymes with their corresponding sequence. This success points toward how we can systematically eliminate the remaining orphan enzymes and prevent the introduction of future orphan enzymes.

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Lipid-mediated, reversible misfolding of a sterol-sensing domain protein.

Cellular quality control requires recognition of common features of misfolding, and so is not typically associated with the specific targeting of individual proteins. However, physiologically regulated degradation of yeast HMG-CoA reductase (Hmg2p) occurs by the HRD endoplasmic reticulum quality control pathway, implying that Hmg2p undergoes a regulated transition to a quality control substrate in response to a sterol pathway molecule. Using in vitro structural assays, we now show that the pathway derivative farnesol causes Hmg2p to undergo a change to a less folded structure. The effect is reversible, biologically relevant by numerous criteria, highly specific for farnesol structure, and requires an intact Hmg2p sterol-sensing domain. This represents a distinct lipid-sensing function for this highly conserved motif that suggests novel approaches to cholesterol management. More generally, our observation of reversible small-molecule-mediated misfolding may herald numerous examples of regulated quality control to be discovered in biology or applied in the clinic.

INSIG: a broadly conserved transmembrane chaperone for sterol-sensing domain proteins.

INSIGs are proteins that underlie sterol regulation of the mammalian proteins SCAP (SREBP cleavage activating protein) and HMG-CoA reductase (HMGR). The INSIGs perform distinct tasks in the regulation of these effectors: they promote ER retention of SCAP, but ubiquitin-mediated degradation of HMGR. Two questions that arise from the discovery and study of INSIGs are: how do they perform these distinct tasks, and how general are the actions of INSIGs in biology? We now show that the yeast INSIG homologs NSG1 and NSG2 function to control the stability of yeast Hmg2p, the HMGR isozyme that undergoes regulated ubiquitination. Yeast Nsgs inhibit degradation of Hmg2p in a highly specific manner, by directly interacting with the sterol-sensing domain (SSD)-containing transmembrane region. Nsg1p functions naturally to limit degradation of Hmg2p when both proteins are at native levels, indicating a long-standing functional interplay between these two classes of proteins. One way to unify the known, disparate actions of INSIGs is to view them as known adaptations of a chaperone dedicated to SSD-containing client proteins.

Structural control of endoplasmic reticulum-associated degradation: effect of chemical chaperones on 3-hydroxy-3-methylglutaryl-CoA reductase.

The endoplasmic reticulum (ER) quality control pathway destroys misfolded and unassembled proteins in the ER. Most substrates of this ER-associated degradation (ERAD) pathway are constitutively targeted for destruction through recognition of poorly understood structural hallmarks of misfolding. However, the normal yeast ER membrane protein 3-hydroxy-3-methylglutaryl-CoA reductase (Hmg2p) undergoes ERAD that is physiologically regulated by sterol pathway signals. We have proposed that Hmg2p ERAD occurs by a regulated transition to an ERAD quality control substrate. Consistent with this, we had previously shown that Hmg2p is strongly stabilized by chemical chaperones such as glycerol, which stabilize misfolded proteins. To understand the features of Hmg2p that permit regulated ERAD, we have thoroughly characterized the effects of chemical chaperones on Hmg2p. These agents caused a reversible, immediate, direct change in Hmg2p degradation consistent with an effect on Hmg2p structure. We devised an in vitro limited proteolysis assay of Hmg2p in its native membranes. In vitro, chemical chaperones caused a dramatic, rapid change in Hmg2p structure to a less accessible form. As in the living cell, the in vitro action of chemical chaperones was highly specific for Hmg2p and completely reversible. To evaluate the physiological relevance of this model behavior, we used the limited proteolysis assay to examine the effects of changing in vivo degradation signals on Hmg2p structure. We found that changes similar to those observed with chemical chaperones were brought about by alteration of natural degradation signal. Thus, Hmg2p can undergo significant, reversible structural changes that are relevant to the physiological control of Hmg2p ERAD. These findings support the idea that Hmg2p regulation is brought about by regulated alteration of folding state. Considering the ubiquitous nature of quality control pathways in biology, it may be that this strategy of regulation is widespread.