Metabolite Damage and Damage Control in a Minimal Genome.

Analysis of the genes retained in the minimized Mycoplasma JCVI-Syn3A genome established that systems that repair or preempt metabolite damage are essential to life. Several genes known to have such functions were identified and experimentally validated, including 5-formyltetrahydrofolate cycloligase, coenzyme A (CoA) disulfide reductase, and certain hydrolases. Furthermore, we discovered that an enigmatic YqeK hydrolase domain fused to NadD has a novel proofreading function in NAD synthesis and could double as a MutT-like sanitizing enzyme for the nucleotide pool. Finally, we combined metabolomics and cheminformatics approaches to extend the core metabolic map of JCVI-Syn3A to include promiscuous enzymatic reactions and spontaneous side reactions. This extension revealed that several key metabolite damage control systems remain to be identified in JCVI-Syn3A, such as that for methylglyoxal. IMPORTANCE Metabolite damage and repair mechanisms are being increasingly recognized. We present here compelling genetic and biochemical evidence for the universal importance of these mechanisms by demonstrating that stripping a genome down to its barest essentials leaves metabolite damage control systems in place. Furthermore, our metabolomic and cheminformatic results point to the existence of a network of metabolite damage and damage control reactions that extends far beyond the corners of it that have been characterized so far. In sum, there can be little room left to doubt that metabolite damage and the systems that counter it are mainstream metabolic processes that cannot be separated from life itself.

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions.

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways' side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl.gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency.

Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at http://modelseed.org, which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.

'Nothing of chemistry disappears in biology': the Top 30 damage-prone endogenous metabolites.

Many common metabolites are intrinsically unstable and reactive, and hence prone to chemical (i.e. non-enzymatic) damage in vivo Although this fact is widely recognized, the purely chemical side-reactions of metabolic intermediates can be surprisingly hard to track down in the literature and are often treated in an unprioritized case-by-case way. Moreover, spontaneous chemical side-reactions tend to be overshadowed today by side-reactions mediated by promiscuous ('sloppy') enzymes even though chemical damage to metabolites may be even more prevalent than damage from enzyme sloppiness, has similar outcomes, and is held in check by similar biochemical repair or pre-emption mechanisms. To address these limitations and imbalances, here we draw together and systematically integrate information from the (bio)chemical literature, from cheminformatics, and from genome-scale metabolic models to objectively define a 'Top 30' list of damage-prone metabolites. A foundational part of this process was to derive general reaction rules for the damage chemistries involved. The criteria for a 'Top 30' metabolite included predicted chemical reactivity, essentiality, and occurrence in diverse organisms. We also explain how the damage chemistry reaction rules ('operators') are implemented in the Chemical-Damage-MINE (CD-MINE) database (minedatabase.mcs.anl.gov/#/top30) to provide a predictive tool for many additional potential metabolite damage products. Lastly, we illustrate how defining a 'Top 30' list can drive genomics-enabled discovery of the enzymes of previously unrecognized damage-control systems, and how applying chemical damage reaction rules can help identify previously unknown peaks in metabolomics profiles.

Systematic identification and analysis of frequent gene fusion events in metabolic pathways.

BACKGROUND: Gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. RESULTS: Here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These sets were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database at http://modelseed.org/projects/fusions/ . A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. CONCLUSIONS: Customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.

Identification of mitochondrial coenzyme a transporters from maize and Arabidopsis.

Plants make coenzyme A (CoA) in the cytoplasm but use it for reactions in mitochondria, chloroplasts, and peroxisomes, implying that these organelles have CoA transporters. A plant peroxisomal CoA transporter is already known, but plant mitochondrial or chloroplastic CoA transporters are not. Mitochondrial CoA transporters belonging to the mitochondrial carrier family, however, have been identified in yeast (Saccharomyces cerevisiae; Leu-5p) and mammals (SLC25A42). Comparative genomic analysis indicated that angiosperms have two distinct homologs of these mitochondrial CoA transporters, whereas nonflowering plants have only one. The homologs from maize (Zea mays; GRMZM2G161299 and GRMZM2G420119) and Arabidopsis (Arabidopsis thaliana; At1g14560 and At4g26180) all complemented the growth defect of the yeast leu5Δ mitochondrial CoA carrier mutant and substantially restored its mitochondrial CoA level, confirming that these proteins have CoA transport activity. Dual-import assays with purified pea (Pisum sativum) mitochondria and chloroplasts, and subcellular localization of green fluorescent protein fusions in transiently transformed tobacco (Nicotiana tabacum) Bright Yellow-2 cells, showed that the maize and Arabidopsis proteins are targeted to mitochondria. Consistent with the ubiquitous importance of CoA, the maize and Arabidopsis mitochondrial CoA transporter genes are expressed at similar levels throughout the plant. These data show that representatives of both monocotyledons and eudicotyledons have twin, mitochondrially located mitochondrial carrier family carriers for CoA. The highly conserved nature of these carriers makes possible their reliable annotation in other angiosperm genomes.

Plant B vitamin pathways and their compartmentation: a guide for the perplexed.

The B vitamins and the cofactors derived from them are essential for life. B vitamin synthesis in plants is consequently as crucial to plants themselves as it is to humans and animals, whose B vitamin nutrition depends largely on plants. The synthesis and salvage pathways for the seven plant B vitamins are now broadly known, but certain enzymes and many transporters have yet to be identified, and the subcellular locations of various reactions are unclear. Although very substantial, what is not known about plant B vitamin pathways is regrettably difficult to discern from the literature or from biochemical pathway databases. Nor do databases accurately represent all that is known about B vitamin pathways-above all their compartmentation-because the facts are scattered throughout the literature, and thus hard to piece together. These problems (i) deter discoveries because newcomers to B vitamins cannot see which mysteries still need solving; and (ii) impede metabolic reconstruction and modelling of B vitamin pathways because genes for reactions or transport steps are missing. This review therefore takes a fresh approach to capture current knowledge of B vitamin pathways in plants. The synthesis pathways, key salvage routes, and their subcellular compartmentation are surveyed in depth, and encoded in the SEED database (http://pubseed.theseed.org/seedviewer.cgi?page=PlantGateway) for Arabidopsis and maize. The review itself and the encoded pathways specifically identify enigmatic or missing reactions, enzymes, and transporters. The SEED-encoded B vitamin pathway collection is a publicly available, expertly curated, one-stop resource for metabolic reconstruction and modeling.

Identification of mitochondrial thiamin diphosphate carriers from Arabidopsis and maize.

It is currently held that thiamin is made in chloroplasts and converted in the cytosol to the active cofactor thiamin diphosphate (ThDP), and that mitochondria and plastids import ThDP. The organellar transporters that mediate ThDP import in plants have not been identified. Comparative genomic analysis indicated that two members of the mitochondrial carrier family (MCF) in Arabidopsis (At5g48970 and At3g21390) and two in maize (GRMZM2G118515 and GRMZM2G124911) are related to the ThDP carriers of animals and Saccharomyces cerevisiae. Expression of each of these plant proteins in a S. cerevisiae ThDP carrier (TPC1) null mutant complemented the growth defect on fermentable carbon sources and restored the level of mitochondrial ThDP and the activity of the mitochondrial ThDP-dependent enzyme acetolactate synthase. The plant proteins were targeted to mitochondria as judged by dual import assays with purified pea mitochondria and chloroplasts, and by microscopic analysis of the subcellular localization of green fluorescent protein fusions in transiently transformed tobacco suspension cells. Both maize genes were shown to be expressed throughout the plant, which is consistent with the known ubiquity of mitochondrial ThDP-dependent enzymes. Collectively, these data establish that plants have mitochondrially located MCF carriers for ThDP, and indicate that these carriers are highly evolutionarily conserved. Our data provide a firm basis to propagate the functional annotation of mitochondrial ThDP carriers to other angiosperm genomes.