IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001).Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-016-1051-4) contains supplementary material, which is available to authorized users.

SUMMARY Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells, provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show the metabolic resources in CHO are >3 times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

Chinese hamster ovary (CHO) cells are the preferred production host for therapeutic monoclonal antibodies (mAb) due to their ability to perform post-translational modifications and their successful approval history. The completion of the genome sequence for CHO cells has reignited interest in using quantitative proteomics to identify markers of good production lines. Here we applied two different proteomic techniques, iTRAQ and SWATH, for the identification of expression differences between a high- and low-antibody-producing CHO cell lines derived from the same transfection. More than 2000 proteins were quantified with 70 of them classified as differentially expressed in both techniques. Two biological processes were identified as differentially regulated by both methods: up-regulation of glutathione biosynthesis and down-regulation of DNA replication. Metabolomic analysis confirmed that the high producing cell line displayed higher intracellular levels of glutathione. SWATH further identified up-regulation of actin filament processes and intracellular transport and down regulation of several growth-related processes. These processes may be important for conferring high mAb production and as such are promising candidates for targeted engineering of high-expression cell lines.

Clostridium is a large genus of obligate anaerobes belonging to the Firmicutes phylum of bacteria, most of which have a Gram-positive cell wall structure. The genus includes significant human and animal pathogens, causative of potentially deadly diseases such as tetanus and botulism. Despite their relevance and many studies suggesting that they are not a monophyletic group, the taxonomy of the group has largely been neglected. Currently, species belonging to the genus are placed in the unnatural order defined as Clostridiales, which includes the class Clostridia. Here, we used genomic data from 779 strains to study the taxonomy and evolution of the group. This analysis allowed us to 1) confirm that the group is composed of more than one genus, 2) detect major differences between pathogens classified as a single species within the group of authentic Clostridium spp. (sensu stricto), 3) identify inconsistencies between taxonomy and toxin evolution that reflect on the pervasive misclassification of strains, and 4) identify differential traits within central metabolism of members of what has been defined earlier and confirmed by us as cluster I. Our analysis shows that the current taxonomic classification of Clostridium species hinders the prediction of functions and traits, suggests a new classification for this fascinating class of bacteria, and highlights the importance of phylogenomics for taxonomic studies.

Chinese hamster ovary (CHO) cells are the predominant host cell line for the production of biopharmaceuticals, a growing industry currently worth more than $188 billion USD in global sales. CHO cells undergo programmed cell death (apoptosis) following different stresses encountered in cell culture, such as substrate limitation, accumulation of toxic by‐products, and mechanical shear, hindering production. Genetic engineering strategies to reduce apoptosis in CHO cells have been investigated with mixed results. In this review, a contemporary understanding of the real complexity of apoptotic mechanisms and signaling pathways is described; followed by an overview of antiapoptotic cell line engineering strategies tested so far in CHO cells.