Extremophiles are remarkable organisms that thrive in the harshest environments on Earth, such as hydrothermal vents, hypersaline lakes and pools, alkaline soda lakes, deserts, cold oceans, and volcanic areas. These organisms have developed several strategies to overcome environmental stress and nutrient limitations. Thus, they are among the best model organisms to study adaptive mechanisms that lead to stress tolerance. Genetic and structural information derived from extremophiles and extremozymes can be used for bioengineering other nontolerant enzymes. Furthermore, extremophiles can be a valuable resource for novel biotechnological and biomedical products due to their biosynthetic properties. However, understanding life under extreme conditions is challenging due to the difficulties of in vitro cultivation and observation since > 99% of organisms cannot be cultivated. Consequently, only a minor percentage of the potential extremophiles on Earth have been discovered and characterized. Herein, we present a review of culture-independent methods, sequence-based metagenomics (SBM), and single amplified genomes (SAGs) for studying enzymes from extremophiles, with a focus on prokaryotic (archaea and bacteria) microorganisms. Additionally, we provide a comprehensive list of extremozymes discovered via metagenomics and SAGs.

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

BackgroundProtein aggregation and its pathological effects are the major cause of several neurodegenerative diseases. In Huntington’s disease an elongated stretch of polyglutamines within the protein Huntingtin leads to increased aggregation propensity. This induces cellular defects, culminating in neuronal loss, but the connection between aggregation and toxicity remains to be established.ResultsTo uncover cellular pathways relevant for intoxication we used genome-wide analyses in a yeast model system and identify fourteen genes that, if deleted, result in higher polyglutamine toxicity. Several of these genes, like UGO1, ATP15 and NFU1 encode mitochondrial proteins, implying that a challenged mitochondrial system may become dysfunctional during polyglutamine intoxication. We further employed microarrays to decipher the transcriptional response upon polyglutamine intoxication, which exposes an upregulation of genes involved in sulfur and iron metabolism and mitochondrial Fe-S cluster formation. Indeed, we find that in vivo iron concentrations are misbalanced and observe a reduction in the activity of the prominent Fe-S cluster containing protein aconitase. Like in other yeast strains with impaired mitochondria, non-fermentative growth is impossible after intoxication with the polyglutamine protein. NMR-based metabolic analyses reveal that mitochondrial metabolism is reduced, leading to accumulation of metabolic intermediates in polyglutamine-intoxicated cells.ConclusionThese data show that damages to the mitochondrial system occur in polyglutamine intoxicated yeast cells and suggest an intricate connection between polyglutamine-induced toxicity, mitochondrial functionality and iron homeostasis in this model system.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1831-7) contains supplementary material, which is available to authorized users.

Because only 0.01% of prokaryotic genospecies can be cultured and in situ observations are often impracticable, culture-independent methods are required to understand microbial life and harness potential applications of microbes. Here, we report a methodology for the production of proteins with desired functions based on single amplified genomes (SAGs) from unculturable species. We use this method to resurrect an alcohol dehydrogenase (ADH/D1) from an uncharacterized halo-thermophilic archaeon collected from a brine pool at the bottom of the Red Sea. Our crystal structure of 5,6-dihydroxy NADPH-bound ADH/D1 combined with biochemical analyses reveal the molecular features of its halo-thermophily, its unique habitat adaptations, and its possible reaction mechanism for atypical oxygen activation. Our strategy offers a general guide for using SAGs as a source for scientific and industrial investigations of "microbial dark matter."