Background: Acidithiobacillus ferrooxidans is a major participant in consortia of microorganisms used for the industrial recovery of copper (bioleaching or biomining). It is a chemolithoautrophic, γ-proteobacterium using energy from the oxidation of iron- and sulfur-containing minerals for growth. It thrives at extremely low pH (pH 1–2) and fixes both carbon and nitrogen from the atmosphere. It solubilizes copper and other metals from rocks and plays an important role in nutrient and metal biogeochemical cycling in acid environments. The lack of a well-developed system for genetic manipulation has prevented thorough exploration of its physiology. Also, confusion has been caused by prior metabolic models constructed based upon the examination of multiple, and sometimes distantly related, strains of the microorganism. Results: The genome of the type strain A. ferrooxidans ATCC 23270 was sequenced and annotated to identify general features and provide a framework for in silico metabolic reconstruction. Earlier models of iron and sulfur oxidation, biofilm formation, quorum sensing, inorganic ion uptake, and amino acid metabolism are confirmed and extended. Initial models are presented for central carbon metabolism, anaerobic metabolism (including sulfur reduction, hydrogen metabolism and nitrogen fixation), stress responses, DNA repair, and metal and toxic compound fluxes. Conclusion: Bioinformatics analysis provides a valuable platform for gene discovery and functional prediction that helps explain the activity of A. ferrooxidans in industrial bioleaching and its role as a primary producer in acidic environments. An analysis of the genome of the type strain provides a coherent view of its gene content and metabolic potential.

The γ-proteobacterium Acidithiobacillus ferrooxidans lives in extremely acidic conditions (pH 2) and, unlike most organisms, is confronted with an abundant supply of soluble iron. It is also unusual in that it oxidizes iron as an energy source. Consequently, it faces the challenging dual problems of (i) maintaining intracellular iron homeostasis when confronted with extremely high environmental loads of iron and (ii) of regulating the use of iron both as an energy source and as a metabolic micronutrient. A combined bioinformatic and experimental approach was undertaken to identify Fur regulatory sites in the genome of A. ferrooxidans and to gain insight into the constitution of its Fur regulon. Fur regulatory targets associated with a variety of cellular functions including metal trafficking (e.g. feoPABC, tdr, tonBexbBD, copB, cdf), utilization (e.g. fdx, nif), transcriptional regulation (e.g. phoB, irr, iscR) and redox balance (grx, trx, gst) were identified. Selected predicted Fur regulatory sites were confirmed by FURTA, EMSA and in vitro transcription analyses. This study provides the first model for a Fur-binding site consensus sequence in an acidophilic iron-oxidizing microorganism and lays the foundation for future studies aimed at deepening our understanding of the regulatory networks that control iron uptake, homeostasis and oxidation in extreme acidophiles.

Disruption of the circadian rhythm is a key feature of bipolar disorder. Variation in genes encoding components of the molecular circadian clock has been associated with increased risk of the disorder in clinical populations. Similarly in animal models, disruption of the circadian clock can result in altered mood and anxiety which resemble features of human mania; including hyperactivity, reduced anxiety and reduced depression-like behaviour. One such mutant, after hours (Afh), an ENU-derived mutant with a mutation in a recently identified circadian clock gene Fbxl3, results in a disturbed (long) circadian rhythm of approximately 27 hours. Anxiety, exploratory and depression-like behaviours were evaluated in Afh mice using the open-field, elevated plus maze, light-dark box, holeboard and forced swim test. To further validate findings for human mania, polymorphisms in the human homologue of FBXL3, genotyped by three genome wide case control studies, were tested for association with bipolar disorder. Afh mice showed reduced anxiety- and depression-like behaviour in all of the behavioural tests employed, and some evidence of increased locomotor activity in some tests. An analysis of three separate human data sets revealed a gene wide association between variation in FBXL3 and bipolar disorder (P = 0.009). Our results are consistent with previous studies of mutants with extended circadian periods and suggest that disruption of FBXL3 is associated with mania-like behaviours in both mice and humans.

Despite high heritability, the genetic variants influencing bipolar disorder (BD) susceptibility remain largely unknown. Low statistical power to detect the small effect-size alleles believed to underlie much of the genetic risk and possible heterogeneity between cohorts are an increasing concern. Integrative biology approaches might offer advantages over genetic analysis alone by combining different genomic datasets at the higher level of biological processes rather than the level of specific genetic variants or genes. We employed this strategy to identify biological processes involved in BD etiopathology. Three genome-wide association studies and a brain gene-expression study were combined with the Human Protein Reference Database protein-protein interaction network data. We used bioinformatic analysis to search for biological networks with evidence of association on the basis of enrichment among both genetic and differential-expression associations with BD. We identified association with gene networks involved in transmission of nerve impulse, Wnt, and Notch signaling. Three features stand out among these genes: 1) they localized to the human postsynaptic density, which is crucial for neuronal function; 2) their mouse knockouts present altered behavioral phenotypes; and 3) some are known targets of the pharmacological treatments for BD. Genetic and gene-expression associations of BD cluster in discrete regions of the protein-protein interaction network. We found replicated evidence for association for networks involving several interlinked signaling pathways. These genes are promising candidates to generate animal models and pharmacological interventions. Our results demonstrate the potential advantage of integrative biology analyses of BD datasets.