CH391L/S12/Bioprospecting

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What's Bioprospecting?

Bioprospecting is a catch-all term for activities including discovery, acquisition, and utilization of novel biomaterials. This has historically been a controversial activity, often leading to unregulated commercialization of fauna (e.g., plants and medicinals) from third world countries for the benefit of commercial interests [Pros/Cons of Bioprospecting]. However, as a term in Molecular Biology, it reflects the growing need to discover new types of protein and nucleic acid parts, which can be used in biotechnology and basic research. The advent of multiple Next-Generation Sequencing technologies since 2006 now provides depth of information into the entire genomes (Metagenomics) of species previously inaccessible to basic research. [1]

Examples of Genes Identified via Bioprospecting

GFP

Although not planned, one of the great examples of Bioprospecting is the story of Green Fluorescent Protein (GFP), a protein that has had a profound impact on every major field in modern biology. Originally isolated and characterized by Osamu Shimomura in the 1960's and 1970's from jellyfish and sea pansies, it was a mere oddity that conferred the eery bioluminescence of certain deep sea creatures. However, the subsequent cloning of the gene by Martin Chalfie and improvement into enhanced GFP by Roger Tsien made it into one of the modern workhorses in biology. This 40-year journey earned Shimomura, Chalfie, and Tsien the 2008 Nobel Prize in Chemistry. [History of GFP]

Polymerases

Polymerases such as the Klenow fragment and more importantly Taq polymerase, have permitted the synthesis of DNA fragments. For instance, Taq was discovered in a thermophilic bacterium, and because it can withstand extreme heat (~95 celcius) without losing activity permitted the use of thermal cycling in the Polymerase Chain Reaction (PCR). This allows for denaturation and subsequent reannealing of DNA strands used in the exponential amplification of target sequences. PCR earned Mullis and Smith the 1993 Nobel Prize. Polymerases also include the important phage RNA polymerases such T7, T3, or SP6 which have permitted the in vitro transcription of DNA templates into RNA.

Reverse Transcriptases

The discovery of Reverse-Transcriptases, essentially polymerases that copy RNA into DNA, have allowed for the study of RNA via generation of cDNA's. The world led to the 1974 Nobel Prize for David Baltimore and Howard Temin.

Restriction Endonucleases

The discovery of Restriction Endonucleases in the 1970's fueled the Molecular Biology revolution and the advent of genetic engineering. Found in bacteria and archaea, they act to degrade foreign DNA by cleaving at specific palindromic sequences. This work led to the 1978 Nobel prize to Nathans, Arber, and Smith.

Metagenomics

GOLD genome projects
GOLD genome projects

Metagenomics uses Next Generation Sequencing Technologies (e.g., Whole Genome Shotgun Sequencing (WGS), Roche 454, Illumina, ABI Solid) or Protein analysis (Mass Spectrometry) to completely sample the genomes of mixed microbial communities, generating an unbiased view of genomic sequence space. Estimates have suggested that greater than 99% of all microbes are unculturable in the lab and inaccessable to traditional laboratory analysis. Thus, these Next Generation Sequencing approaches allow for analysis of microbes that are small percentages of a microbial community. The current explosion in various Metagenomic projects (340 current projects, 1990 samples [GOLD database]) permits for entirely in silico approaches to identifying new gene families, with potential as parts in Synthetic Biology.

Craig Venter and his Yacht

Global Ocean Explorer
Global Ocean Explorer

In the early 2000's, the J. Craig Venter Institute set as one of its goals to sequence the genomic diversity in the oceans. Craig Venter used his personal yacht, the Sorcerer II, to traverse the Earth's oceans, taking samples of oceanic life and sequencing using Whole Genome Shotgun Sequencing. From this adventure, they uncovered 6 million proteins (double the current database), which consisted of 1,700 clusters of gene families with no known homology. The data also revealed homology for 6,000 unknown ORF families (ORFan). They found that a very high proportion of new genes belonged to viruses (likely marine phage), which current databases had underrepresented. [2]

Examples of Bioprospecting using Metagenomics (Targeted Metagenomics)

A useful approach to Bioprospecting new genes involves either functional screening or pure sequence screening in what is called Targeted Metagenomics. This involves either challenging microbiota to a particular activity, or looking for specific families of genes. Both types of Targeted Metagenomic screens have led to new antibiotic resistance genes, cold-adaptive rRNA's, and cellulosic enzymes, to name just a few. [3].

----Typical Targeted Metagenomic Pipeline----
  1. Extract (DNA, RNA, or Protein) from Environmental Sample
  2. Next Gen Sequencing or Mass Spec
  3. Computational analysis for ORFs and homology searches
  4. Heterologous Expression and Testing for function
Cellulosic Biomass degrading genes found in Cow Rumen

Plant polysaccharides such as cellulose are not broken down with enyzmes found in mammals, but species such as Ruminents (cows) carry symbiotic bacteria that perform this job. These microbes cannot be cultured in lab. However, acquisition of the enzymes used to break down cellulose could be used to generate biofuel from easily grown plants like grass. Here, Mattias Hess and colleagues used Metagenomic analysis to identify 51 enzymes active in breaking down polysaccharides [4]. The authors isolated microbes from a nylon bag filled with switchgrass placed inside a fistula created into a cow's rumen. Various Next-Gen Sequencing technologies were used to generate 268 Giga-basepairs of sequences. From the various organisms, they predicted 27,755 putative polysaccharide enyzymes, of which 43% had less than 50% similarity to any known sequence. The authors expressed and tested 90 of these genes based on similarity to glycosyl hyrdolase domains, which identified 51 active enzymes. The enyzmes were active against various substrates used as biofuel crops. Finally, the authors generated 15 draft genomes of new microbial species. A number of earlier studies have also attempted to identify glycosyl hydrolases in species such as termites and panda [1][3]

Uranium Bioremediation

Bioremediation of uranium waste is an important industrial process. Here, the authors used a proteomics based approach to identify proteins in iron-reducing (FeIII) microbial species used in the reduction of soluble uranium to insoluble uranium [5]. Although the study here does identify new genes, it identifies new metabolic pathways. The authors started with 3 known Geobacter species stimulated with acetate and used in a bioremediation project and used the known proteins as a reference for performming 2D liquid chromatography tandem mass spectrometry. They identified over 13,000 peptides and 2,500 proteins. Not surprisingly, the authors show that acetate utilization increases via the TCA cycles (acetyl-CoA enzymes) presumably for increased growth as a fuel source. They also note high abundances of pyruvate ferrodoxin oxidoreductase, suggesting the bacteria are undergoing high carbon fixation processes.

New Parts

New genes found from Ruminant microbes are being used for generating fuel from biomass, proteins which have thus far been unknown to man. Genes identified in more extromophilic bacteria and archaea may be useful in metabolism of inorganic compounds. They may be useful in new genetic circuits in biotech applications. Finally, the genes will ultimately be useful as scaffolds for directed evolution studies, to generate new functions.

List of Parts found by Metagenomics

  1. glycosyl hydrolases (cellulose degradation)
  2. antibiotic resistance (tetracycline/bleomycin)
  3. extradiol dioxygenases (aromatic carbon usage)
  4. sulfate reductases
  5. deaminases
  6. Zn-dependent carboxypeptidases
  7. RNA-binding proteins
  8. many unique ORFans

Limitations

First, many of the current Next-Gen Sequencers are limited by short read lengths, which can prove problematic in the de novo construction of a genome. In addition, many protocols utilize emPCR after nebulization of DNA, which can introduce sequencing coverage bias. Nebulization randomly fragments sample genomic DNA into various lengths, which can be of varying GC content and secondary structure. Since emPCR amplifies single fragments, this can often lead to underrepresentation of difficult to PCR fragments. For low copy templates, this can often mean low sequence coverage in important areas.

Cloning of genes from a diverse sample can be helped with prior knowledge of the target gene family. Various domains of a given gene family can be targeted with degenerate primers to isolate similar genes in a microbial community sample. However, the use of degenerate primers may not capture the entirety of gene families in a diverse sample. Alternatively, phylogenetic analysis of regions with high similarity (low degeneracy) can help for designing primers that better capture the genes.

The coming introduction of single-molecule long read sequencers, such as that by Pacific Biosciences may alleviate some of these limitations. Finally, it is unlikely that genes found in nature will cover all the uses humanity may come up with. Since nature settles for genes that function "well-enough", this may be inadequate since humans require efficiency.

References

  1. Chistoserdova L. . pmid:20495950. PubMed HubMed [BiotechLettReview2010]
  2. Yooseph S, Sutton G, Rusch DB, Halpern AL, Williamson SJ, Remington K, Eisen JA, Heidelberg KB, Manning G, Li W, Jaroszewski L, Cieplak P, Miller CS, Li H, Mashiyama ST, Joachimiak MP, van Belle C, Chandonia JM, Soergel DA, Zhai Y, Natarajan K, Lee S, Raphael BJ, Bafna V, Friedman R, Brenner SE, Godzik A, Eisenberg D, Dixon JE, Taylor SS, Strausberg RL, Frazier M, and Venter JC. . pmid:17355171. PubMed HubMed [PLOSbio2007]
  3. Suenaga H. . pmid:21366818. PubMed HubMed [EnviroMicroReview2011]
  4. Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, Luo S, Clark DS, Chen F, Zhang T, Mackie RI, Pennacchio LA, Tringe SG, Visel A, Woyke T, Wang Z, and Rubin EM. . pmid:21273488. PubMed HubMed [Science2011]
  5. Wilkins MJ, Verberkmoes NC, Williams KH, Callister SJ, Mouser PJ, Elifantz H, N'guessan AL, Thomas BC, Nicora CD, Shah MB, Abraham P, Lipton MS, Lovley DR, Hettich RL, Long PE, and Banfield JF. . pmid:19717633. PubMed HubMed [ApplEnviroMicro2009]
All Medline abstracts: PubMed HubMed
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