Cyanobacterial carboxysome mutant analysis reveals the influence of enzyme compartmentalization on cellular metabolism and metabolic network rigidity.

Cyanobacterial carboxysomes encapsulate carbonic anhydrase and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). Genetic deletion of the major structural proteins encoded within the ccm operon in Synechococcus sp. PCC 7002 (ΔccmKLMN) disrupts carboxysome formation and significantly affects cellular physiology. Here we employed both metabolite pool size analysis and isotopically nonstationary metabolic flux analysis (INST-MFA) to examine metabolic regulation in cells lacking carboxysomes. Under high CO2 environments (1%), the ΔccmKLMN mutant could recover growth and had a similar central flux distribution as the control strain, with the exceptions of moderately decreased photosynthesis and elevated biomass protein content and photorespiration activity. Metabolite analyses indicated that the ΔccmKLMN strain had significantly larger pool sizes of pyruvate (>18 folds), UDPG (uridine diphosphate glucose), and aspartate as well as higher levels of secreted organic acids (e.g., malate and succinate). These results suggest that the ΔccmKLMN mutant is able to largely maintain a fluxome similar to the control strain by changing in intracellular metabolite concentrations and metabolite overflows under optimal growth conditions. When CO2 was insufficient (0.2%), provision of acetate moderately promoted mutant growth. Interestingly, the removal of microcompartments may loosen the flux network and promote RuBisCO side-reactions, facilitating redirection of central metabolites to competing pathways (i.e., pyruvate to heterologous lactate production). This study provides important insights into metabolic regulation via enzyme compartmentation and cyanobacterial compensatory responses.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Isotopomer measurement techniques in metabolic flux analysis II: mass spectrometry.

Mass spectrometry (MS) offers a sensitive, reliable, and highly accurate method for measurement of isotopic labeling, which is required for generating comprehensive flux maps using metabolic flux analysis (MFA). We present protocols for assessing isotope labeling in a wide range of biochemical species, including proteinogenic amino acids, free organic and amino acids, sugar phosphates, lipids, starch-glucose, and RNA-ribose. We describe the steps of sample preparation, MS analysis, and data handling required to obtain high-quality isotope labeling measurements that are applicable to MFA. By selecting target analytes that maximize identifiability of the key fluxes of interest, MS measurements of isotope labeling can provide a powerful platform for assessing metabolic fluxes in complex biochemical networks.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

BACKGROUND: Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. RESULTS: Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. CONCLUSION: Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.