A Systems Biology Approach Uncovers Cellular Strategies Used by Methylobacterium extorquens AM1 During the Switch from Multi- to Single-Carbon Growth

When organisms experience environmental change, how does their metabolic network reset and adapt to the new condition? Methylobacterium extorquens is a bacterium capable of growth on both multi- and single-carbon compounds. These different modes of growth utilize dramatically different central metabolic pathways with limited pathway overlap.This study focused on the mechanisms of metabolic adaptation occurring during the transition from succinate growth (predicted to be energy-limited) to methanol growth (predicted to be reducing-power-limited), analyzing changes in carbon flux, gene expression, metabolites and enzymatic activities over time. Initially, cells experienced metabolic imbalance with excretion of metabolites, changes in nucleotide levels and cessation of cell growth. Though assimilatory pathways were induced rapidly, a transient block in carbon flow to biomass synthesis occurred, and enzymatic assays suggested methylene tetrahydrofolate dehydrogenase as one control point. This "downstream priming" mechanism ensures that significant carbon flux through these pathways does not occur until they are fully induced, precluding the buildup of toxic intermediates. Most metabolites that are required for growth on both carbon sources did not change significantly, even though transcripts and enzymatic activities required for their production changed radically, underscoring the concept of metabolic setpoints.This multi-level approach has resulted in new insights into the metabolic strategies carried out to effect this shift between two dramatically different modes of growth and identified a number of potential flux control and regulatory check points as a further step toward understanding metabolic adaptation and the cellular strategies employed to maintain metabolic setpoints

Analysis of Hypoxia and Hypoxia-Like States through Metabolite Profiling

In diverse organisms, adaptation to low oxygen (hypoxia) is mediated through complex gene expression changes that can, in part, be mimicked by exposure to metals such as cobalt. Although much is known about the transcriptional response to hypoxia and cobalt, little is known about the all-important cell metabolism effects that trigger these responses.Herein we use a low molecular weight metabolome profiling approach to identify classes of metabolites in yeast cells that are altered as a consequence of hypoxia or cobalt exposures. Key findings on metabolites were followed-up by measuring expression of relevant proteins and enzyme activities. We find that both hypoxia and cobalt result in a loss of essential sterols and unsaturated fatty acids, but the basis for these changes are disparate. While hypoxia can affect a variety of enzymatic steps requiring oxygen and heme, cobalt specifically interferes with diiron-oxo enzymatic steps for sterol synthesis and fatty acid desaturation. In addition to diiron-oxo enzymes, cobalt but not hypoxia results in loss of labile 4Fe-4S dehydratases in the mitochondria, but has no effect on homologous 4Fe-4S dehydratases in the cytosol. Most striking, hypoxia but not cobalt affected cellular pools of amino acids. Amino acids such as aromatics were elevated whereas leucine and methionine, essential to the strain used here, dramatically decreased due to hypoxia induced down-regulation of amino acid permeases.These studies underscore the notion that cobalt targets a specific class of iron proteins and provide the first evidence for hypoxia effects on amino acid regulation. This research illustrates the power of metabolite profiling for uncovering new adaptations to environmental stress

Systems Biology of the qa Gene Cluster in Neurospora crassa

An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa

Salmonella enterica Strains Lacking the Frataxin Homolog CyaY Show Defects in Fe-S Cluster Metabolism In Vivo

In Salmonella enterica, the isc operon contains genes necessary for the synthesis of Fe-S clusters and strains lacking this operon have severe defects in a variety of cellular processes. Other cellular loci that impact Fe-S cluster synthesis to a lesser extent have been described. The cyaY locus encodes a frataxin homolog, and it is shown here that lesions in this locus affect Fe-S cluster metabolism. When present in combination with other lesions, mutations in cyaY can result in a strain with more severe defects than those lacking the isc locus