| Literature DB >> 25399309 |
Jan Kjølhede Vester1, Mikkel Andreas Glaring, Peter Stougaard.
Abstract
Only a small minority of microorganisms from an environmental sample can be cultured in the laboratory leaving the enormous bioprospecting potential of the uncultured diversity unexplored. This resource can be accessed by improved cultivation methods in which the natural environment is brought into the laboratory or through metagenomic approaches where culture-independent DNA sequence information can be combined with functional screening. The coupling of these two approaches circumvents the need for pure, cultured isolates and can be used to generate targeted information on communities enriched for specific activities or properties. Bioprospecting in extreme environments is often associated with additional challenges such as low biomass, slow cell growth, complex sample matrices, restricted access, and problematic in situ analyses. In addition, the choice of vector system and expression host may be limited as few hosts are available for expression of genes with extremophilic properties. This review summarizes the methods developed for improved cultivation as well as the metagenomic approaches for bioprospecting with focus on the challenges faced by bioprospecting in cold environments.Entities:
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Year: 2014 PMID: 25399309 PMCID: PMC4272415 DOI: 10.1007/s00792-014-0704-3
Source DB: PubMed Journal: Extremophiles ISSN: 1431-0651 Impact factor: 2.395
Fig. 1Simplified and general overview of culture-dependent and metagenomic methods for bioprospecting. In principle any environmental sample can be used. Culture-dependent methods (gray boxes) include a culturing step ranging from traditional culturing to various combinations of improved culturing techniques, leading to isolation and screening of natural isolates. Metagenomic methods (blue boxes) rely on DNA extraction, which can be either direct or indirect. Extracted DNA can be used for either sequence-based (red) or functional (green) screening approaches, where the latter might require amplification. Identified activities from natural isolates or recombinantly expressed proteins are then characterized. Links between culture-dependent and metagenomic methods include using DNA from enrichment cultures or natural isolates (dotted lines). See text for details. Inspired by Akondi and Lakshmi (2013)
Fig. 2Cultivation techniques. Diffusion chamber (a), hollow-fiber membrane chambers (b), and encapsulated gel microdroplets (c). Modified from Kaeberlein et al. (2002, ©The American Association for the Advancement of Science), Aoi et al. (2009, ©American Society for Microbiology) and Ben-Dov et al. (2009, ©John Wiley and Sons), respectively
Cold-active enzymes identified by functional metagenomics
| Enzyme | Host/vector | Positive/total clones | Screening technique |
| pHopt | Origin of sample | References |
|---|---|---|---|---|---|---|---|
| Lipase |
| 70/>7,000 | Agar based | 35 | N.A. | Baltic sea sediment | Hardeman and Sjoling ( |
| Lipase |
| N.A. | Agar based | 30 | 7 | Oil-contaminated soil (Northern Germany) | Elend et al. ( |
| Lipase |
| 1/8,823 | Agar based | 25 | 8 | Deep-sea sediment (Papua New Guinea) | Jeon et al. ( |
| Lipase |
| 1/6,000 | Agar based | 30 | 8 | Intertidal sediment (Korea) | Kim et al. ( |
| Lipase |
| 2/N.A. | Agar based | 20 | 7–9 | Soil from different altitude of Taishan (China) | Wei et al. ( |
| Lipase |
| 1/2,400 | Agar based | 35 | 8 | Mangrove sediment (Brazil) | Couto et al. ( |
| Lipase |
| 1/386,400 | Agar based | 25 | 8 | Tidal sediment (Korea) | Lee et al. ( |
| Lipase |
| 6/81,100 | Agar based | 30–35 | 7.5–8.5 | Deep-sea sediment | Jeon et al. ( |
| Esterase |
| 1/N.A. | Agar based | 50–55 | 10–11 | Deep-sea sediment (Papua New Guiney) | Park et al. ( |
| Esterase |
| 3/100,000 | Agar based | 40 | 9.0 | Antarctic desert soil | Heath et al. ( |
| Esterase |
| 6/60,132 | Agar based | 30 | 8 | Arctic seashore sediment | Jeon et al. ( |
| Esterase |
| 1/N.A. | Agar based | 35 | 7.5 | Arctic intertidal sediment | Fu et al. ( |
| Esterase |
| 3/100,000 | Agar based | 20 | 11 | Antarctic desert soil | Hu et al. ( |
| Esterase |
| 1/31,872 | Agar based | 35 | 8.5 | Swamp sediment (Korea) | Seo et al. ( |
| Esterase |
| 121/60,000 | Agar based | 20–30 | 9 | Arctic soil | Yu et al. ( |
| Esterase |
| 95/274,000 | Agar based | 15–40 | 8–10 | Oil-contaminated seawater | Tchigvintsev et al. ( |
| Phthalate Esters Hydrolase |
| N.A./100,000 | Agar based | 10 | 7.5 | Wastewater treatment plant (China) | Jiao et al. ( |
| Amylase |
| 1/350,000 | Agar based | 40 | 6.5 | Soil (Himalaya) | Sharma et al. ( |
| Amylase |
| 2/2,843 | Agar based | 15 | 8–9 | Ikaite columns (Greenland) | Vester et al. ( |
| Cellulase |
| 11/10,000 | Agar based | 10–50 | 6–9 | Antarctic soil | Berlemont et al. ( |
| Cellulase |
| 1/8,500 | Agar based | 28 | 4.5 | Cold desert (Himalaya) | Bhat et al. ( |
| Cellulase |
| 1/40,000 | Agar based | 40 | 7 | Brown alga associated microorganism (France) | Martin et al. ( |
| β-Galactosidase |
| 3/1,200 | Agar based | 38 | 7 | Topsoil of oil field (China) | Wang et al. ( |
| β-Galactosidase |
| 2/2,843 | Agar based | 37 | 6–7 | Ikaite columns (Greenland) | Vester et al. ( |
| β-Galactosidase |
| 1/1,100 | Agar based | 40 | 6.5 | Baltic sea water | Wierzbicka-Wos et al. ( |
| Xylanase |
| 1/5,000,000 | Agar based | 20 | 6–7 | Waste lagoon of dairy farm (California) | Lee et al. ( |
| Chitinase |
| 1/29,000 | Agar based | 30 | N.A. | Genomes from Antarctic soil (1) and Arctic sea (9) bacteria | Kim et al. ( |
| DNA polymerase I |
| 15/23,000 and 1/4,000 | Growth assay | N.A. | N.A. | Glacial ice (Germany) | Simon et al. ( |
Adapted and updated from Cavicchioli et al. (2011, ©John Wiley and Sons)
N.A. not applicable or not available