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

Deep Sequencing Whole Transcriptome Exploration of the σE Regulon in Neisseria meningitidis

Bacteria live in an ever-changing environment and must alter protein expression promptly to adapt to these changes and survive. Specific response genes that are regulated by a subset of alternative σ70-like transcription factors have evolved in order to respond to this changing environment. Recently, we have described the existence of a σE regulon including the anti-σ-factor MseR in the obligate human bacterial pathogen Neisseria meningitidis. To unravel the complete σE regulon in N. meningitidis, we sequenced total RNA transcriptional content of wild type meningococci and compared it with that of mseR mutant cells (ΔmseR) in which σE is highly expressed. Eleven coding genes and one non-coding gene were found to be differentially expressed between H44/76 wildtype and H44/76ΔmseR cells. Five of the 6 genes of the σE operon, msrA/msrB, and the gene encoding a pepSY-associated TM helix family protein showed enhanced transcription, whilst aniA encoding a nitrite reductase and nspA encoding the vaccine candidate Neisserial surface protein A showed decreased transcription. Analysis of differential expression in IGRs showed enhanced transcription of a non-coding RNA molecule, identifying a σE dependent small non-coding RNA. Together this constitutes the first complete exploration of an alternative σ-factor regulon in N. meningitidis. The results direct to a relatively small regulon indicative for a strictly defined response consistent with a relatively stable niche, the human throat, where N. meningitidis resides

Mutant phenotypes for thousands of bacterial genes of unknown function.

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations