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Tetanus is a fatal disease caused by Clostridium tetani infections. To prevent infections, a toxoid vaccine, developed almost a century ago, is routinely used in humans and animals. The vaccine is listed in the World Health Organisation list of Essential Medicines and can be produced and administered very cheaply in the developing world for less than one US Dollar per dose. Recent developments in both analytical tools and frameworks for systems biology provide industry with an opportunity to gain a deeper understanding of the parameters that determine C. tetani virulence and physiological behaviour in bioreactors. Here, we compared a traditional fermentation process with a fermentation medium supplemented with five heavily consumed amino acids. The experiment demonstrated that amino acid catabolism plays a key role in the virulence of C. tetani. The addition of the five amino acids favoured growth, decreased toxin production and changed C. tetani morphology. Using time-course transcriptomics, we created a "fermentation map", which shows that the tetanus toxin transcriptional regulator BotR, P21 and the tetanus toxin gene was downregulated. Moreover, this in-depth analysis revealed potential genes that might be involved in C. tetani virulence regulation. We observed differential expression of genes related to cell separation, surface/cell adhesion, pyrimidine biosynthesis and salvage, flagellar motility, and prophage genes. Overall, the fermentation map shows that, mediated by free amino acid concentrations, virulence in C. tetani is regulated at the transcriptional level and affects a plethora of metabolic functions.

Propionibacteria have been studied extensively since the early 1930s due to their relevance to industry and importance as human pathogens. Still, their unique metabolism is far from fully understood. This is partly due to their signature high GC content, which has previously hampered the acquisition of quality sequence data, the accurate annotation of the available genomes, and the functional characterization of genes. The recent completion of the genome sequences for several species has led researchers to reassess the taxonomical classification of the genus Propionibacterium , which has been divided into several new genres. Such data also enable a comparative genomic approach to annotation and provide a new opportunity to revisit our understanding of their metabolism. Using pan-genome analysis combined with the reconstruction of the first high-quality Propionibacterium genome-scale metabolic model and a pan-metabolic model of current and former members of the genus Propionibacterium, we demonstrate that despite sharing unique metabolic traits, these organisms have an unexpected diversity in central carbon metabolism and a hidden layer of metabolic complexity. This combined approach gave us new insights into the evolution of Propionibacterium metabolism and led us to propose a novel, putative ferredoxin-linked energy conservation strategy. The pan-genomic approach highlighted key differences in Propionibacterium metabolism that reflect adaptation to their environment. Results were mathematically captured in genome-scale metabolic reconstructions that can be used to further explore metabolism using metabolic modeling techniques. Overall, the data provide a platform to explore Propionibacterium metabolism and a tool for the rational design of strains.

Acetogens can fix carbon (CO or CO 2 ) into acetyl-CoA via the Wood-Ljungdahl pathway (WLP) that also makes them attractive cell factories for the production of fuels and chemicals from waste feedstocks. Although most biochemical details of the WLP are well understood and systems-level characterization of acetogen metabolism has recently improved, key transcriptional features such as promoter motifs and transcriptional regulators are still unknown in acetogens. Here, we use differential RNA-sequencing to identify a previously undescribed promoter motif associated with essential genes for autotrophic growth of the model-acetogen Clostridium autoethanogenum . RNA polymerase was shown to bind to the new promoter motif using a DNA-binding protein assay and proteomics enabled the discovery of four candidates to potentially function directly in control of transcription of the WLP and other key genes of C 1 fixation metabolism. Next, in vivo experiments showed that a TetR-family transcriptional regulator (CAETHG_0459) and the housekeeping sigma factor (σ A ) activate expression of a reporter protein (GFP) in-frame with the new promoter motif from a fusion vector in Escherichia coli . Lastly, a protein-protein interaction assay with the RNA polymerase (RNAP) shows that CAETHG_0459 directly binds to the RNAP. Together, the data presented here advance the fundamental understanding of transcriptional regulation of C 1 fixation in acetogens and provide a strategy for improving the performance of gas-fermenting bacteria by genetic engineering., (Copyright © 2019 de Souza Pinto Lemgruber, Valgepea, Gonzalez Garcia, de Bakker, Palfreyman, Tappel, Köpke, Simpson, Nielsen and Marcellin.)

Gas fermentation is emerging as an economically attractive option for the sustainable production of fuels and chemicals from gaseous waste feedstocks. Clostridium autoethanogenum can use CO and/or CO 2 + H 2 as its sole carbon and energy sources. Fermentation of C. autoethanogenum is currently being deployed on a commercial scale for ethanol production. Expanding the product spectrum of acetogens will enhance the economics of gas fermentation. To achieve efficient heterologous product synthesis, limitations in redox and energy metabolism must be overcome. Here, we engineered and characterised at a systems-level, a recombinant poly-3-hydroxybutyrate (PHB)-producing strain of C. autoethanogenum. Cells were grown in CO-limited steady-state chemostats on two gas mixtures, one resembling syngas (20% H 2 ) and the other steel mill off-gas (2% H 2 ). Results were characterised using metabolomics and transcriptomics, and then integrated using a genome-scale metabolic model reconstruction. PHB-producing cells had an increased expression of the Rnf complex, suggesting energy limitations for heterologous production. Subsequent optimisation of the bioprocess led to a 12-fold increase in the cellular PHB content. The data suggest that the cellular redox state, rather than the acetyl-CoA pool, was limiting PHB production. Integration of the data into the genome-scale metabolic model showed that ATP availability limits PHB production. Altogether, the data presented here advances the fundamental understanding of heterologous product synthesis in gas-fermenting acetogens., (Copyright © 2019 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

The development of next-generation sequencing technologies has opened new opportunities to better characterize complex eukaryotic cells. Chinese hamster ovary (CHO) cells play a primary role in therapeutic protein production, with currently five of the top ten blockbuster drugs produced in CHO. However, engineering superior CHO cells with improved production features has had limited success to date and cell lines are still developed through the generation and screening of large strain pools. Here, we applied RNA sequencing to contrast a high and a low monoclonal antibody producing cell line. Rigorous experimental design achieved high reproducibility between biological replicates, remarkably reducing variation to less than 10%. More than 14 000 gene-transcripts are identified and surprisingly 58% are classified as differentially expressed, including 2900 with a fold change higher than 1.5. The largest differences are found for gene-transcripts belonging to regulation of apoptosis, cell death, and protein intracellular transport GO term classifications, which are found to be significantly enriched in the high producing cell line. RNA sequencing is also performed on subclones, where down-regulation of genes encoding secreted glycoproteins is found to be the most significant change. The large number of significant differences even between subclones challenges the notion of identifying and manipulating a few key genes to generate high production CHO cell lines., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Pichia pastoris (syn. Komagataella phaffii ) is one of the most common eukaryotic expression systems for heterologous protein production. Expression cassettes are typically integrated in the genome to obtain stable expression strains. In contrast to Saccharomyces cerevisiae , where short overhangs are sufficient to target highly specific integration, long overhangs are more efficient in P. pastoris and ectopic integration of foreign DNA can occur. Here, we aimed to elucidate the influence of ectopic integration by high-throughput screening of >700 transformants and whole-genome sequencing of 27 transformants. Different vector designs and linearization approaches were used to mimic the most common integration events targeted in P. pastoris Fluorescence of an enhanced green fluorescent protein (eGFP) reporter protein was highly uniform among transformants when the expression cassettes were correctly integrated in the targeted locus. Surprisingly, most nonspecifically integrated transformants showed highly uniform expression that was comparable to specific integration, suggesting that nonspecific integration does not necessarily influence expression. However, a few clones (<10%) harboring ectopically integrated cassettes showed a greater variation spanning a 25-fold range, surpassing specifically integrated reference strains up to 6-fold. High-expression strains showed a correlation between increased gene copy numbers and high reporter protein fluorescence levels. Our results suggest that for comparing expression levels between strains, the integration locus can be neglected as long as a sufficient numbers of transformed strains are compared. For expression optimization of highly expressible proteins, increasing copy number appears to be the dominant positive influence rather than the integration locus, genomic rearrangements, deletions, or single-nucleotide polymorphisms (SNPs). IMPORTANCE Yeasts are commonly used as biotechnological production hosts for proteins and metabolites. In the yeast Saccharomyces cerevisiae , expression cassettes carrying foreign genes integrate highly specifically at the targeted sites in the genome. In contrast, cassettes often integrate at random genomic positions in nonconventional yeasts, such as Pichia pastoris (syn. Komagataella phaffii ). Hence, cells from the same transformation event often behave differently, with significant clonal variation necessitating the screening of large numbers of strains. The importance of this study is that we systematically investigated the influence of integration events in more than 700 strains. Our findings provide novel insight into clonal variation in P. pastoris and, thus, how to avoid pitfalls and obtain reliable results. The underlying mechanisms may also play a role in other yeasts and hence could be generally relevant for recombinant yeast protein production strains., (Copyright © 2018 American Society for Microbiology.)

Acetogens are promising cell factories for producing fuels and chemicals from waste feedstocks via gas fermentation, but quantitative characterization of carbon, energy, and redox metabolism is required to guide their rational metabolic engineering. Here, we explore acetogen gas fermentation using physiological, metabolomics, and transcriptomics data for Clostridium autoethanogenum steady-state chemostat cultures grown on syngas at various gas-liquid mass transfer rates. We observe that C. autoethanogenum shifts from acetate to ethanol production to maintain ATP homeostasis at higher biomass concentrations but reaches a limit at a molar acetate/ethanol ratio of ∼1. This regulatory mechanism eventually leads to depletion of the intracellular acetyl-CoA pool and collapse of metabolism. We accurately predict growth phenotypes using a genome-scale metabolic model. Modeling revealed that the methylene-THF reductase reaction was ferredoxin reducing. This work provides a reference dataset to advance the understanding and engineering of arguably the first carbon fixation pathway on Earth., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Traditionally derived from fossil fuels, biological production of propionic acid has recently gained interest. Propionibacterium species produce propionic acid as their main fermentation product. Production of other organic acids reduces propionic acid yield and productivity, pointing to by-products gene-knockout strategies as a logical solution to increase yield. However, removing by-product formation has seen limited success due to our inability to genetically engineer the best producing strains (i.e. Propionibacterium acidipropionici). To overcome this limitation, random mutagenesis continues to be the best path towards improving strains for biological propionic acid production. Recent advances in next generation sequencing opened new avenues to understand improved strains. In this work, we use genome shuffling on two wild type strains to generate a better propionic acid producing strain. Using next generation sequencing, we mapped the genomic changes leading to the improved phenotype. The best strain produced 25% more propionic acid than the wild type strain. Sequencing of the strains showed that genomic changes were restricted to single point mutations and gene duplications in well-conserved regions in the genomes. Such results confirm the involvement of gene conversion in genome shuffling as opposed to long genomic insertions., (© 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica), as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S. italica. mRNA, protein, and metabolite abundances, were measured in mature and immature stem/leaf phytomers, and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME). Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin, and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study, we demonstrated that this systems approach is powerful enough to complement the functional metabolic annotation of bioenergy grasses.

Background: Our view of host-associated microbiota remains incomplete due to the presence of as yet uncultured constituents. The Bacteroidales family S24-7 is a prominent example of one of these groups. Marker gene surveys indicate that members of this family are highly localized to the gastrointestinal tracts of homeothermic animals and are increasingly being recognized as a numerically predominant member of the gut microbiota; however, little is known about the nature of their interactions with the host., Results: Here, we provide the first whole genome exploration of this family, for which we propose the name "Candidatus Homeothermaceae," using 30 population genomes extracted from fecal samples of four different animal hosts: human, mouse, koala, and guinea pig. We infer the core metabolism of "Ca. Homeothermaceae" to be that of fermentative or nanaerobic bacteria, resembling that of related Bacteroidales families. In addition, we describe three trophic guilds within the family, plant glycan (hemicellulose and pectin), host glycan, and α-glucan, each broadly defined by increased abundance of enzymes involved in the degradation of particular carbohydrates., Conclusions: "Ca. Homeothermaceae" representatives constitute a substantial component of the murine gut microbiota, as well as being present within the human gut, and this study provides important first insights into the nature of their residency. The presence of trophic guilds within the family indicates the potential for niche partitioning and specific roles for each guild in gut health and dysbiosis.

In planta production of the bioplastic polyhydroxybutyrate (PHB) is one important way in which plant biotechnology can address environmental problems and emerging issues related to peak oil. However, high biomass C4 plants such as maize, switch grass and sugarcane develop adverse phenotypes including stunting, chlorosis and reduced biomass as PHB levels in leaves increase. In this study, we explore limitations to PHB accumulation in sugarcane chloroplasts using a systems biology approach, coupled with a metabolic model of C4 photosynthesis. Decreased assimilation was evident in high PHB-producing sugarcane plants, which also showed a dramatic decrease in sucrose and starch content of leaves. A subtle decrease in the C/N ratio was found which was not associated with a decrease in total protein content. An increase in amino acids used for nitrogen recapture was also observed. Based on the accumulation of substrates of ATP-dependent reactions, we hypothesized ATP starvation in bundle sheath chloroplasts. This was supported by mRNA differential expression patterns. The disruption in ATP supply in bundle sheath cells appears to be linked to the physical presence of the PHB polymer which may disrupt photosynthesis by scattering photosynthetically active radiation and/or physically disrupting thylakoid membranes., (© 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.)

Monoterpenes are liquid hydrocarbons with applications ranging from flavor and fragrance to replacement jet fuel. Their toxicity, however, presents a major challenge for microbial synthesis. Here we evolved limonene-tolerant Saccharomyces cerevisiae strains and sequenced six strains across the 200-generation evolutionary time course. Mutations were found in the tricalbin proteins Tcb2p and Tcb3p. Genomic reconstruction in the parent strain showed that truncation of a single protein (tTcb3p(1-989)), but not its complete deletion, was sufficient to recover the evolved phenotype improving limonene fitness 9-fold. tTcb3p(1-989) increased tolerance toward two other monoterpenes (β-pinene and myrcene) 11- and 8-fold, respectively, and tolerance toward the biojet fuel blend AMJ-700t (10% cymene, 50% limonene, 40% farnesene) 4-fold. tTcb3p(1-989) is the first example of successful engineering of phase tolerance and creates opportunities for production of the highly toxic C10 alkenes in yeast., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Considerable progress has been made in plant genome-scale metabolic reconstruction and modeling in recent years. Such reconstructions made it possible to explore metabolic phenotypes through appropriate model formulation and optimization methods. As a result, plant genome-scale modeling has increasingly attracted interest from the plant research community. In this chapter, the first generation of plant genome-scale metabolic reconstructions is presented, along with the important concepts behind model and constraint formulation. A brief protocol describing the use of constraint-based reconstruction and analysis (COBRA) Toolbox in flux simulation and model modification is provided. This is followed by a presentation of metabolic constraints required to generate fluxes in AraGEM using COBRA that describe photosynthesis, photorespiration, and respiration, respectively. Overall, plant genome-scale modeling is a powerful approach that is accessible and readily adopted.

Background: Accurate bacterial genome annotations provide a framework to understanding cellular functions, behavior and pathogenicity and are essential for metabolic engineering. Annotations based only on in silico predictions are inaccurate, particularly for large, high G + C content genomes due to the lack of similarities in gene length and gene organization to model organisms., Results: Here we describe a 2D systems biology driven re-annotation of the Saccharopolyspora erythraea genome using proteogenomics, a genome-scale metabolic reconstruction, RNA-sequencing and small-RNA-sequencing. We observed transcription of more than 300 intergenic regions, detected 59 peptides in intergenic regions, confirmed 164 open reading frames previously annotated as hypothetical proteins and reassigned function to open reading frames using the genome-scale metabolic reconstruction. Finally, we present a novel way of mapping ribosomal binding sites across the genome by sequencing small RNAs., Conclusions: The work presented here describes a novel framework for annotation of the Saccharopolyspora erythraea genome. Based on experimental observations, the 2D annotation framework greatly reduces errors that are commonly made when annotating large-high G + C content genomes using computational prediction algorithms.

Background: Actinobacteria form a major bacterial phylum that includes numerous human pathogens. Actinobacteria are primary contributors to carbon cycling and also represent a primary source of industrial high value products such as antibiotics and biopesticides. Consistent with other members of the actinobacterial phylum, Saccharopolyspora erythraea undergo a transitional switch. This switch is characterized by numerous metabolic and morphological changes., Results: We performed RNA sequencing to analyze the transcriptional changes that occur during growth of Saccharopolyspora erythraea in batch culture. By sequencing RNA across the fermentation time course, at a mean coverage of 4000X, we found the vast majority of genes to be prominently expressed, showing that we attained close to saturating sequencing coverage of the transcriptome. During the metabolic switch, global changes in gene expression influence the metabolic machinery of Saccharopolyspora erythraea, resetting an entirely novel gene expression program. After the switch, global changes include the broad repression of half the genes regulated by complex transcriptional mechanisms. Paralogous transposon clusters, delineate these transcriptional programs. The new transcriptional program is orchestrated by a bottleneck event during which mRNA levels are severely restricted by targeted mRNA degradation., Conclusions: Our results, which attained close to saturating sequencing coverage of the transcriptome, revealed unanticipated transcriptional complexity with almost one third of transcriptional content originating from un-annotated sequences. We showed that the metabolic switch is a sophisticated mechanism of transcriptional regulation capable of resetting and re-synchronizing gene expression programs at extraordinary speed and scale.

The Heliothine insect complex contains some of the most destructive pests of agricultural crops worldwide, including the closely related Helicoverpa zea and H. armigera. Biological control using baculoviruses is practiced at a moderate level worldwide. In order to enable more wide spread use, a better understanding of cell-virus interactions is required. While many baculoviruses have been sequenced, none of the Heliothine insect genomes have been available. In this study, we sequenced, assembled and functionally annotated 29,586 transcripts from cultured H. zea cells using Illumina 100 bps and paired-end transcriptome sequencing (RNA-seq). The transcript sequences had high assembly coverage (64.5 times). 23,401 sequences had putative protein functions, and over 13,000 sequences had high similarities to available sequences in other insect species. The sequence database was estimated to cover at least 85% of all H. zea genes. The sequences were used to construct a microarray, which was evaluated on the infection of H. zea cells with H. Armigera single-capsid nucleopolyhedrovirus (HearNPV). The analysis revealed that up-regulation of apoptosis genes is the main cellular response in the early infection phase (18 hours post infection), while genes linked to four major immunological signalling pathways (Toll, IMD, Jak-STAT and JNK) were down-regulated. Only small changes (generally downwards) were observed for central carbon metabolism. The transcriptome and microarray platform developed in this study represent a greatly expanded resource base for H. zea insect-HearNPV interaction studies, in which key cellular pathways such as those for metabolism, immune response, transcription and replication have been identified. This resource will be used to develop better cell culture-based virus production processes, and more generally to investigate the molecular basis of host range and susceptibility, virus infectivity and virulence, and the ecology and evolution of baculoviruses.

Background: Microalgae have the potential to deliver biofuels without the associated competition for land resources. In order to realise the rates and titres necessary for commercial production, however, system-level metabolic engineering will be required. Genome scale metabolic reconstructions have revolutionized microbial metabolic engineering and are used routinely for in silico analysis and design. While genome scale metabolic reconstructions have been developed for many prokaryotes and model eukaryotes, the application to less well characterized eukaryotes such as algae is challenging not at least due to a lack of compartmentalization data., Results: We have developed a genome-scale metabolic network model (named AlgaGEM) covering the metabolism for a compartmentalized algae cell based on the Chlamydomonas reinhardtii genome. AlgaGEM is a comprehensive literature-based genome scale metabolic reconstruction that accounts for the functions of 866 unique ORFs, 1862 metabolites, 2249 gene-enzyme-reaction-association entries, and 1725 unique reactions. The reconstruction was compartmentalized into the cytoplasm, mitochondrion, plastid and microbody using available data for algae complemented with compartmentalisation data for Arabidopsis thaliana. AlgaGEM describes a functional primary metabolism of Chlamydomonas and significantly predicts distinct algal behaviours such as the catabolism or secretion rather than recycling of phosphoglycolate in photorespiration. AlgaGEM was validated through the simulation of growth and algae metabolic functions inferred from literature. Using efficient resource utilisation as the optimality criterion, AlgaGEM predicted observed metabolic effects under autotrophic, heterotrophic and mixotrophic conditions. AlgaGEM predicts increased hydrogen production when cyclic electron flow is disrupted as seen in a high producing mutant derived from mutational studies. The model also predicted the physiological pathway for H2 production and identified new targets to further improve H2 yield., Conclusions: AlgaGEM is a viable and comprehensive framework for in silico functional analysis and can be used to derive new, non-trivial hypotheses for exploring this metabolically versatile organism. Flux balance analysis can be used to identify bottlenecks and new targets to metabolically engineer microalgae for production of biofuels.

Background: Parasitoid insects manipulate their hosts' physiology by injecting various factors into their host upon parasitization. Transcriptomic approaches provide a powerful approach to study insect host-parasitoid interactions at the molecular level. In order to investigate the effects of parasitization by an ichneumonid wasp (Diadegma semiclausum) on the host (Plutella xylostella), the larval transcriptome profile was analyzed using a short-read deep sequencing method (Illumina). Symbiotic polydnaviruses (PDVs) associated with ichneumonid parasitoids, known as ichnoviruses, play significant roles in host immune suppression and developmental regulation. In the current study, D. semiclausum ichnovirus (DsIV) genes expressed in P. xylostella were identified and their sequences compared with other reported PDVs. Five of these genes encode proteins of unknown identity, that have not previously been reported., Results: De novo assembly of cDNA sequence data generated 172,660 contigs between 100 and 10000 bp in length; with 35% of > 200 bp in length. Parasitization had significant impacts on expression levels of 928 identified insect host transcripts. Gene ontology data illustrated that the majority of the differentially expressed genes are involved in binding, catalytic activity, and metabolic and cellular processes. In addition, the results show that transcription levels of antimicrobial peptides, such as gloverin, cecropin E and lysozyme, were up-regulated after parasitism. Expression of ichnovirus genes were detected in parasitized larvae with 19 unique sequences identified from five PDV gene families including vankyrin, viral innexin, repeat elements, a cysteine-rich motif, and polar residue rich protein. Vankyrin 1 and repeat element 1 genes showed the highest transcription levels among the DsIV genes., Conclusion: This study provides detailed information on differential expression of P. xylostella larval genes following parasitization, DsIV genes expressed in the host and also improves our current understanding of this host-parasitoid interaction.

Leaves of C(4) grasses (such as maize [Zea mays], sugarcane [Saccharum officinarum], and sorghum [Sorghum bicolor]) form a classical Kranz leaf anatomy. Unlike C(3) plants, where photosynthetic CO(2) fixation proceeds in the mesophyll (M), the fixation process in C(4) plants is distributed between two cell types, the M cell and the bundle sheath (BS) cell. Here, we develop a C(4) genome-scale model (C4GEM) for the investigation of flux distribution in M and BS cells during C(4) photosynthesis. C4GEM, to our knowledge, is the first large-scale metabolic model that encapsulates metabolic interactions between two different cell types. C4GEM is based on the Arabidopsis (Arabidopsis thaliana) model (AraGEM) but has been extended by adding reactions and transporters responsible to represent three different C(4) subtypes (NADP-ME [for malic enzyme], NAD-ME, and phosphoenolpyruvate carboxykinase). C4GEM has been validated for its ability to synthesize 47 biomass components and consists of 1,588 unique reactions, 1,755 metabolites, 83 interorganelle transporters, and 29 external transporters (including transport through plasmodesmata). Reactions in the common C(4) model have been associated with well-annotated C(4) species (NADP-ME subtypes): 3,557 genes in sorghum, 11,623 genes in maize, and 3,881 genes in sugarcane. The number of essential reactions not assigned to genes is 131, 135, and 156 in sorghum, maize, and sugarcane, respectively. Flux balance analysis was used to assess the metabolic activity in M and BS cells during C(4) photosynthesis. Our simulations were consistent with chloroplast proteomic studies, and C4GEM predicted the classical C(4) photosynthesis pathway and its major effect in organelle function in M and BS. The model also highlights differences in metabolic activities around photosystem I and photosystem II for three different C(4) subtypes. Effects of CO(2) leakage were also explored. C4GEM is a viable framework for in silico analysis of cell cooperation between M and BS cells during photosynthesis and can be used to explore C(4) plant metabolism.

Genome-scale metabolic network models have been successfully used to describe metabolism in a variety of microbial organisms as well as specific mammalian cell types and organelles. This systems-based framework enables the exploration of global phenotypic effects of gene knockouts, gene insertion, and up-regulation of gene expression. We have developed a genome-scale metabolic network model (AraGEM) covering primary metabolism for a compartmentalized plant cell based on the Arabidopsis (Arabidopsis thaliana) genome. AraGEM is a comprehensive literature-based, genome-scale metabolic reconstruction that accounts for the functions of 1,419 unique open reading frames, 1,748 metabolites, 5,253 gene-enzyme reaction-association entries, and 1,567 unique reactions compartmentalized into the cytoplasm, mitochondrion, plastid, peroxisome, and vacuole. The curation process identified 75 essential reactions with respective enzyme associations not assigned to any particular gene in the Kyoto Encyclopedia of Genes and Genomes or AraCyc. With the addition of these reactions, AraGEM describes a functional primary metabolism of Arabidopsis. The reconstructed network was transformed into an in silico metabolic flux model of plant metabolism and validated through the simulation of plant metabolic functions inferred from the literature. Using efficient resource utilization as the optimality criterion, AraGEM predicted the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. AraGEM is a viable framework for in silico functional analysis and can be used to derive new, nontrivial hypotheses for exploring plant metabolism.

The frequency of isolation of Burkholderia cepacia from the sputum of cystic fibrosis (CF) patients is increasing. Using the human A549 lung epithelial cell line, we have investigated the ability of B. cepacia exoproducts to stimulate interleukin-8 (IL-8) release. Cell-free supernatants from a panel of CF clinical, non-CF clinical, and nonclinical B. cepacia isolates were found to stimulate IL-8 release, with levels ranging from 11.8 +/- 2.8 to 80.0 +/- 3.5 ng/ml. A similar pattern was seen at the level of the IL-8 mRNA. The bioactivity of the IL-8 was confirmed by examining its effect on the intracellular free calcium in neutrophils and inhibition by a neutralizing anti-IL-8 antibody. B. cepacia lipopolysaccharide, which was able to stimulate IL-8 release from monocytes, did not release IL-8 from the A549 cells. Furthermore, the stimulating ability of the bacterial cell-free supernatant was not diminished by polymyxin B, was markedly reduced by boiling, and appeared unrelated to N-acylhomoserine lactones. The ability of B. cepacia to elicit IL-8 release from epithelial cells may be important in the pathology of CF.

A bis-mannose-photolabel-displacement method has been developed for resolving the separate kinetic properties of the glucose transporters GLUT1 and GLUT4, which are both present in 3T3-L1 cells. We have quantified the cell-surface transporter abundance (Bmax.) for the two isoforms by displacing radiolabelled 2-N-[4-(1-azi-2,2,2-trifluoroethyl)benzoyl]-1,3-bis-(D- mannos-4-yloxy)-2-propylamine (ATB-BMPA) by non-labelled ATB-BMPA. In cells acutely treated with insulin, the GLUT1 Bmax. was 0.19 microM and the GLUT4 Bmax. was 0.17 microM. In cells which were chronically treated with insulin, the GLUT1 Bmax. was increased by approximately 4-fold to 0.7 microM, whereas the GLUT4 was decreased by approximately 50% (Bmax. = 0.1 microM). However, this large increase in total concentrations of cell-surface transporters (the sum of GLUT1 and GLUT4 concentrations) was not reflected in a large increase in 3-O-methyl-D-glucose transport, suggesting that GLUT1 makes a smaller contribution to transport than does GLUT4. In acutely insulin-treated cells at 37 degrees C, the apparent kinetic parameters for 3-O-methyl-D-glucose transport were Vapp.max. = 0.52 mM.s-1 and Kapp.m = 12.3 mM. In chronically insulin-treated cells the Vapp.max. = 1.24 mM.s-1 and Kapp.m = 23.0 mM. We have measured the displacement of ATB-BMPA by different concentrations of 3-O-methyl-D-glucose to resolve the separate affinity constants of GLUT1 and GLUT4 for this transported ligand. In acute- and chronic-insulin-treated cells the GLUT1 Km for 3-O-methyl-D-glucose was approximately 20 mM, and the GLUT4 Km for 3-O-methyl-D-glucose was approximately 7 mM. An analysis of these data and the 3-O-methyl-D-glucose transport rates was carried out to calculate transport capacity (TK values) for the two isoforms at 37 degrees C. In acute- and chronic-insulin-treated cells the TK values were 0.36 x 10(4) mM-1.min-1 for GLUT1 and 1.13 x 10(4) mM-1.min-1 for GLUT4. Thus GLUT1 has an approximately 3-fold lower transport capacity than GLUT4 at low concentrations of transported sugar. The lower GLUT1 transport capacity was shown to be mainly due to the high Km of GLUT1. The calculated turnover numbers were 7.2 x 10(4) min-1 for GLUT1 and 7.9 x 10(4) min-1 for GLUT4.