Breast Cancer-Derived Lung Metastases Show Increased Pyruvate Carboxylase-Dependent Anaplerosis.

Cellular proliferation depends on refilling the tricarboxylic acid (TCA) cycle to support biomass production (anaplerosis). The two major anaplerotic pathways in cells are pyruvate conversion to oxaloacetate via pyruvate carboxylase (PC) and glutamine conversion to α-ketoglutarate. Cancers often show an organ-specific reliance on either pathway. However, it remains unknown whether they adapt their mode of anaplerosis when metastasizing to a distant organ. We measured PC-dependent anaplerosis in breast-cancer-derived lung metastases compared to their primary cancers using in vivo 13C tracer analysis. We discovered that lung metastases have higher PC-dependent anaplerosis compared to primary breast cancers. Based on in vitro analysis and a mathematical model for the determination of compartment-specific metabolite concentrations, we found that mitochondrial pyruvate concentrations can promote PC-dependent anaplerosis via enzyme kinetics. In conclusion, we show that breast cancer cells proliferating as lung metastases activate PC-dependent anaplerosis in response to the lung microenvironment.

Integration of omics: more than the sum of its parts.

Genome scale data on biological systems has increasingly become available by sequencing of DNA and RNA, and by mass spectrometric quantification of proteins and metabolites. The cellular components from which these -omics regimes are derived act as one integrated system in vivo; thus, there is a natural instinct to integrate -omics data types. Statistical analyses, the use of previous knowledge in the form of networks, and the use of time-resolved measurements are three key design elements for life scientists to consider in planning integrated -omics studies. These design elements are reviewed in the context of multiple recent systems biology studies that leverage data from different types of -omics analyses. While most of these studies rely on well-established model organisms, the concepts for integrating -omics data that were developed in these studies can help to enable systems research in the field of cancer biology.

A novel TMEM16A splice variant lacking the dimerization domain contributes to calcium-activated chloride secretion in human sweat gland epithelial cells.

Sweating is an important physiological process to regulate body temperature in humans, and various disorders are associated with dysregulated sweat formation. Primary sweat secretion in human eccrine sweat glands involves Ca(2+) -activated Cl(-) channels (CaCC). Recently, members of the TMEM16 family were identified as CaCCs in various secretory epithelia; however, their molecular identity in sweat glands remained elusive. Here, we investigated the function of TMEM16A in sweat glands. Gene expression analysis revealed that TMEM16A is expressed in human NCL-SG3 sweat gland cells as well as in isolated human eccrine sweat gland biopsy samples. Sweat gland cells express several previously described TMEM16A splice variants, as well as one novel splice variant, TMEM16A(acΔe3) lacking the TMEM16A-dimerization domain. Chloride flux assays using halide-sensitive YFP revealed that TMEM16A is functionally involved in Ca(2+) -dependent Cl(-) secretion in NCL-SG3 cells. Recombinant expression in NCL-SG3 cells showed that TMEM16A(acΔe3) is forming a functional CaCC, with basal and Ca(2+) -activated Cl(-) permeability distinct from canonical TMEM16A(ac). Our results suggest that various TMEM16A isoforms contribute to sweat gland-specific Cl(-) secretion providing opportunities to develop sweat gland-specific therapeutics for treatment of sweating disorders.

Coping with complexity in metabolic engineering.

In the past decade, systems biology has revealed great metabolic and regulatory complexity even in seemingly simple microbial systems. Metabolic engineering aims to control this complexity in order to establish sustainable and economically viable production routes for valuable chemicals. Recent advances in systems-level data generation and modeling of cellular metabolism and regulation together with tremendous progress in synthetic biology will provide the tools to put biotechnologists on the fast track for implementing novel production processes. Great potential lies in the reduction of cellular complexity by orthogonalization of metabolic modules. Here, we review recent advances that will eventually enable metabolic engineers to predict, design, and build streamlined microbial cell factories with reduced time and effort.

Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism.

Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and model-based data analyses of dynamic transcript, protein, and metabolite abundances and promoter activities. Adaptation to malate was rapid and primarily controlled posttranscriptionally compared with the slow, mainly transcriptionally controlled adaptation to glucose that entailed nearly half of the known transcription regulation network. Interactions across multiple levels of regulation were involved in adaptive changes that could also be achieved by controlling single genes. Our analysis suggests that global trade-offs and evolutionary constraints provide incentives to favor complex control programs.

Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites.

Quantification of metabolites is of pivotal relevance in biology, where it complements more established omics techniques such as transcriptomics and proteomics. Here, we present a 25 min ion-pairing ultrahigh performance liquid chromatography-tandem mass spectrometry method that was developed for comprehensive coverage of central metabolism (glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle) and closely related biosynthetic reactions. We demonstrate quantification of 138 compounds, including carboxylic acids, amino acids, sugar phosphates, nucleotides, and functionalized aromatics. Biologically relevant isomers such as sugar phosphates are individually quantified by combining chromatographic separation and fragmentation. The obtained sensitivity and robustness enabled the detection of more than half all tested compounds in each of eight diverse biological samples of 0.5-50 mg dry cell weight. We recommend this method for routine and yet comprehensive quantification of primary metabolites in a wide variety of biological matrices.

Tradeoff between enzyme and metabolite efficiency maintains metabolic homeostasis upon perturbations in enzyme capacity.

What is the relationship between enzymes and metabolites, the two major constituents of metabolic networks? We propose three alternative relationships between enzyme capacity and metabolite concentration alterations based on a Michaelis-Menten kinetic; that is enzyme capacities, metabolite concentrations, or both could limit the metabolic reaction rates. These relationships imply different correlations between changes in enzyme capacity and metabolite concentration, which we tested by quantifying metabolite, transcript, and enzyme abundances upon local (single-enzyme modulation) and global (GCR2 transcription factor mutant) perturbations in Saccharomyces cerevisiae. Our results reveal an inverse relationship between fold-changes in substrate metabolites and their catalyzing enzymes. These data provide evidence for the hypothesis that reaction rates are jointly limited by enzyme capacity and metabolite concentration. Hence, alteration in one network constituent can be efficiently buffered by converse alterations in the other constituent, implying a passive mechanism to maintain metabolic homeostasis upon perturbations in enzyme capacity.