Mitochondrial ATP generation is more proteome efficient than glycolysis

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. We accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Evaluating proteome allocation of Saccharomyces cerevisiae phenotypes with resource balance analysis

Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (k_app) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by ¹³C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Building kinetic models for metabolic engineering

Kinetic formalisms of metabolism link metabolic fluxes to enzyme levels, metabolite concentrations and their allosteric regulatory interactions. Though they require the identification of physiologically relevant values for numerous parameters, kinetic formalisms uniquely establish a mechanistic link across heterogeneous omics datasets and provide an overarching vantage point to effectively inform metabolic engineering strategies. Advances in computational power, gene annotation coverage, and formalism standardization have led to significant progress over the past few years. However, careful interpretation of model predictions, limited metabolic flux datasets, and assessment of parameter sensitivity remain as challenges. In this review we highlight fundamental considerations which influence model quality and prediction, advances in methodologies, and success stories of deploying kinetic models to guide metabolic engineering.

Genome-scale metabolic reconstruction of the non-model yeast Issatchenkia orientalis SD108 and its application to organic acids production

Many platform chemicals can be produced from renewable biomass by microorganisms, with organic acids making up a large fraction. Intolerance to the resulting low pH growth conditions, however, remains a challenge for the industrial production of organic acids by microorganisms. Issatchenkia orientalis SD108 is a promising host for industrial production because it is tolerant to acidic conditions as low as pH 2.0. With the goal to systematically assess the metabolic capabilities of this non-model yeast, we developed a genome-scale metabolic model for I. orientalis SD108 spanning 850 genes, 1826 reactions, and 1702 metabolites. In order to improve the model’s quantitative predictions, organism-specific macromolecular composition and ATP maintenance requirements were determined experimentally and implemented. We examined its network topology, including essential genes and flux coupling analysis and drew comparisons with the Yeast 8.3 model for Saccharomyces cerevisiae. We explored the carbon substrate utilization and examined the organism’s production potential for the industrially-relevant succinic acid, making use of the OptKnock framework to identify gene knockouts which couple production of the targeted chemical to biomass production. The genome-scale metabolic model iIsor850 is a data-supported curated model which can inform genetic interventions for overproduction.

•

Genome-scale metabolic model iIsor850 describes metabolism of I. orientalis SD108.

•

Customized biomass reaction highlights differences with S. cerevisiae.

•

Chemostat data elucidate growth-associated ATP maintenance.

•

Substrate utilization and CRISPR/Cas9 gene knockout phenotypes validate model.

•

Model pinpoints candidate gene deletions coupling succinic acid production to growth.

A comprehensive genome-scale model for Rhodosporidium toruloides IFO0880 accounting for functional genomics and phenotypic data

Rhodosporidium toruloides is a red, basidiomycetes yeast that can accumulate a large amount of lipids and produce carotenoids. To better assess this non-model yeast's metabolic capabilities, we reconstructed a genome-scale model of R. toruloides IFO0880's metabolic network (iRhto1108) accounting for 2204 reactions, 1985 metabolites and 1108 genes. In this work, we integrated and supplemented the current knowledge with in-house generated biomass composition and experimental measurements pertaining to the organism's metabolic capabilities. Predictions of genotype-phenotype relations were improved through manual curation of gene-protein-reaction rules for 543 reactions leading to correct recapitulations of 84.5% of gene essentiality data (sensitivity of 94.3% and specificity of 53.8%). Organism-specific macromolecular composition and ATP maintenance requirements were experimentally measured for two separate growth conditions: (i) carbon and (ii) nitrogen limitations. Overall, iRhto1108 reproduced R. toruloides's utilization capabilities for 18 alternate substrates, matched measured wild-type growth yield, and recapitulated the viability of 772 out of 819 deletion mutants. As a demonstration to the model's fidelity in guiding engineering interventions, the OptForce procedure was applied on iRhto1108 for triacylglycerol overproduction. Suggested interventions recapitulated many of the previous successful implementations of genetic modifications and put forth a few new ones.

Identification of growth-coupled production strains considering protein costs and kinetic variability

Conversion of renewable biomass to useful molecules in microbial cell factories can be approached in a rational and systematic manner using constraint-based reconstruction and analysis. Filtering for high confidence in silico designs is critical because in vivo construction and testing of strains is expensive and time consuming. As such, a workflow was devised to analyze the robustness of growth-coupled production when considering the biosynthetic costs of the proteome and variability in enzyme kinetic parameters using a genome-scale model of metabolism and gene expression (ME-model). A collection of 2632 unfiltered knockout designs in Escherichia coli was evaluated by the workflow. A ME-model was used in the workflow to test the designs' growth-coupled production in addition to a less complex genome-scale metabolic model (M-model). The workflow identified 634 M-model growth-coupled designs which met the filtering criteria and 42 robust designs, which met growth-coupled production criteria using both M and ME-models. Knockouts were found to follow a pattern of controlling intermediate metabolite consumption such as pyruvate consumption and high flux subsystems such as glycolysis. Kinetic parameter sampling using the ME-model revealed how enzyme efficiency and pathway tradeoffs can affect growth-coupled production phenotypes.

Leukaemia cutis in chronic lymphocytic leukaemia following varicella zoster virus reactivation

We report a case of a 75-year-old male with indolent chronic lymphocytic leukaemia (CLL) for 8 years, who presented with a 6-month history of a painful, zosteriform eruption in a T3-4 distribution that evolved into an unusual crop of papular nodules. Upon biopsy and immunostaining of these lesions CLL was proven consistent with leukaemia cutis related to varicella-zoster virus reactivation. In the absence of other treatment indices, he was commenced on chlorambucil with successful resolution of both his pain and the lesions.

Evidence that the bulge region is a site of relative immune privilege in human hair follicles

BACKGROUND

Recent gene profiling data suggest that, besides the anagen hair bulb, the epithelial stem cell region in the outer root sheath of hair follicles (HFs), termed the bulge, may also represent an area of relative immune privilege (IP).

OBJECTIVES

To investigate whether the human HF bulge is a site of relative IP within anagen VI HFs.

METHODS

Anagen VI HFs from normal human scalp skin were analysed using immunohistological staining techniques, quantitative histomorphometry and statistical analysis. For functional evidence we performed full-thickness human scalp skin organ cultures to investigate whether interferon (IFN)-gamma, a key inducer of IP collapse in hair bulbs, has a similar effect on the putative bulge IP.

RESULTS

Major histocompatibility complex (MHC) class Ia, beta(2)-microglobulin and MHC class II immunoreactivity are downregulated in the human bulge. The immunosuppressants alpha-melanocyte stimulating hormone, transforming growth factor-beta2, macrophage migration inhibitory factor and indoleamine-2,3-dioxygenase (IDO) are upregulated in the CD200+, stem cell-rich bulge region. These CD200+ cells also co-express HLA-E. Furthermore, IFN-gamma induces significant ectopic MHC class Ia expression in bulge cells of organ-cultured human scalp skin.

CONCLUSIONS

These data suggest that the bulge of human anagen HFs represents a hitherto unrecognized site of relative IP in human skin. Simultaneously, we present the first evidence of IDO and HLA-E protein expression in normal human HFs. Bulge IP presumably protects the HF epithelial stem cell reservoir from autoaggressive immune attack whereas a loss of bulge IP may play a central role in the pathogenesis of cicatricial alopecias.

Rituximab in the adjuvant treatment of pemphigus vulgaris: a prospective open-label pilot study in five patients

BACKGROUND

Rituximab is a monoclonal antibody directed against the CD20 antigen expressed on B lymphocytes. There are reports of its efficacy in the treatment of autoimmune diseases, including pemphigus.

OBJECTIVES

Prospectively to evaluate the efficacy of rituximab as adjuvant treatment for pemphigus vulgaris (PV).

METHODS

Patients with PV were treated with intravenous rituximab (375 mg m(-2)) weekly for 4 weeks in this prospective open-label pilot study. Other concurrent immunosuppression was continued.

RESULTS

Of five patients, one achieved complete remission and was able to cease all medication, while two achieved clearance of clinical lesions but continued on systemic therapy. Two patients had progressive disease. Time to response was 2-8 months, with a 13- to 18-month response duration. Response was associated with reduction in serum antiepithelial antibodies. Two patients had significant infectious complications (one developed community-acquired pneumonia associated with delayed-onset neutropenia and the other developed cytomegalovirus infection).

CONCLUSIONS

Rituximab has shown efficacy in the treatment of PV. Patients on multiple immunosuppressives should be closely monitored for infectious complications.