CH391L/S13/CleanGenomes

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=Introduction=
=Introduction=
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A clean or minimal genome refers to the minimum set of genes that an organism needs to survive and reproduce.  This implies that there are genes that are “nonessential” to the organism’s survival and can be removed without destroying the cell or disrupting its growth cycle.  Examples of nonessential DNA would include duplicate genes, transposable elements and catabolic pathways used for the intake and breakdown of certain complex biomolecules and would be removed from a minimal genome.<cite>ForsterChurch2006</cite><cite>Hutchison1999</cite>
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A clean or minimal genome refers to the minimum set of genes that an organism needs to survive and reproduce.  This implies that there are genes that are “nonessential” to the organism’s survival and can be removed without destroying the cell or disrupting its growth cycle.  Examples of nonessential DNA would include duplicate genes, [http://openwetware.org/wiki/Transposable_elements transposable elements] and catabolic pathways used for the intake and breakdown of certain complex biomolecules and would be removed from a minimal genome.<cite>ForsterChurch2006</cite><cite>Hutchison1999</cite>
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As the complexity of synthetic biology projects increases, so too will the problems it will run into due to the somewhat inherent randomness inside each cell.  A minimal genome would give synthetic biologists a reliable and predictable “chassis” that could provide an ideal platform for perusing new research.   
As the complexity of synthetic biology projects increases, so too will the problems it will run into due to the somewhat inherent randomness inside each cell.  A minimal genome would give synthetic biologists a reliable and predictable “chassis” that could provide an ideal platform for perusing new research.   
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Current model organisms used in modern research contain deleterious DNA and gene products (like insertion sequences and unforeseen molecular interactions) which could disable or prohibit future endeavors by interacting unfavorably with whatever the “subject of interest” is.<cite>ForsterChurch2006</cite><cite>JewettForster2010</cite>  "Depending on the genetic and physiological context, their [IS] contribution to gene inactivation ranges from 3.9% to 98%."<cite>Umenhoffer2010</cite>  Smaller amounts of extraneous gene products would simplify and reduce the cost of extraction and purification of cell parts, biomolecules and pharmaceuticals, many of which would be more expensive and time consuming to separate from a population of cells by conventional means.<cite>Kolisnychenko2002</cite>
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Current model organisms used in modern research contain deleterious DNA and gene products (like [http://en.wikipedia.org/wiki/Insertion_sequence insertion sequences] and unforeseen molecular interactions) which could disable or prohibit future endeavors by interacting unfavorably with whatever the “subject of interest” is.<cite>ForsterChurch2006</cite><cite>JewettForster2010</cite>  "Depending on the genetic and physiological context, their [IS] contribution to gene inactivation ranges from 3.9% to 98%."<cite>Umenhoffer2010</cite>  Smaller amounts of extraneous gene products would simplify and reduce the cost of extraction and purification of cell parts, biomolecules and pharmaceuticals, many of which would be more expensive and time consuming to separate from a population of cells by conventional means.<cite>Kolisnychenko2002</cite>
Gene stability in reduced genomes has been improved by removing transposable elements (TEs), error prone DNA polymerases and the enzymes responsible for the SOS response.  Spontaneous, random genetic changes would be extremely harmful toward a minimal cell lacking a number of redundant systems. A stable genome would be a very desirable trait for research and experiment replication.<cite>Kolisnychenko2002</cite><cite>
Gene stability in reduced genomes has been improved by removing transposable elements (TEs), error prone DNA polymerases and the enzymes responsible for the SOS response.  Spontaneous, random genetic changes would be extremely harmful toward a minimal cell lacking a number of redundant systems. A stable genome would be a very desirable trait for research and experiment replication.<cite>Kolisnychenko2002</cite><cite>
Iwadate2011</cite>
Iwadate2011</cite>
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Future advances in genome replication, unnatural amino acids, drug development, fuel production, biofilm formation<cite>May2011</cite> and biomaterial synthesis could be accelerated by simplifying and streamlining the genome used to code for a cell.<cite>ForsterChurch2006</cite><cite>JewettForster2010</cite>
+
Future advances in genome replication, unnatural amino acids, drug development, fuel production, biofilm formation<cite>May2011</cite> biomaterial synthesis and other cellular applications and processes<cite>Iwadate2011</cite> could be accelerated by simplifying and streamlining the genome used to code for a cell.<cite>ForsterChurch2006</cite><cite>JewettForster2010</cite>
===Minimal/Clean Genomes vs. Wild Type Genomes===
===Minimal/Clean Genomes vs. Wild Type Genomes===

Revision as of 14:18, 8 February 2013

Contents

Introduction

A clean or minimal genome refers to the minimum set of genes that an organism needs to survive and reproduce. This implies that there are genes that are “nonessential” to the organism’s survival and can be removed without destroying the cell or disrupting its growth cycle. Examples of nonessential DNA would include duplicate genes, transposable elements and catabolic pathways used for the intake and breakdown of certain complex biomolecules and would be removed from a minimal genome.[1][2]


Advantages of a Minimal Genome

As the complexity of synthetic biology projects increases, so too will the problems it will run into due to the somewhat inherent randomness inside each cell. A minimal genome would give synthetic biologists a reliable and predictable “chassis” that could provide an ideal platform for perusing new research.

Current model organisms used in modern research contain deleterious DNA and gene products (like insertion sequences and unforeseen molecular interactions) which could disable or prohibit future endeavors by interacting unfavorably with whatever the “subject of interest” is.[1][3] "Depending on the genetic and physiological context, their [IS] contribution to gene inactivation ranges from 3.9% to 98%."[4] Smaller amounts of extraneous gene products would simplify and reduce the cost of extraction and purification of cell parts, biomolecules and pharmaceuticals, many of which would be more expensive and time consuming to separate from a population of cells by conventional means.[5]

Gene stability in reduced genomes has been improved by removing transposable elements (TEs), error prone DNA polymerases and the enzymes responsible for the SOS response. Spontaneous, random genetic changes would be extremely harmful toward a minimal cell lacking a number of redundant systems. A stable genome would be a very desirable trait for research and experiment replication.[5][6]

Future advances in genome replication, unnatural amino acids, drug development, fuel production, biofilm formation[7] biomaterial synthesis and other cellular applications and processes[6] could be accelerated by simplifying and streamlining the genome used to code for a cell.[1][3]

Minimal/Clean Genomes vs. Wild Type Genomes

Cells with reduced genomes have less relative fitness than similar wild type cells and cannot easily cope with changes in its environment. For example, reduced cells are more sensitive to reactive oxygen species, even when the cells still retain the genes needed to respond towards oxidative stress. [6]

The mutation rate in cells with minimal genomes is significantly reduced compared to wild type genomes.[6] This would decrease the genetic diversity of the reduced genome cell population. It is conceivable that if a bacteriophage ever infected a reduced or minimal genome line, then it would quickly become a phage genome line.

Estimating the Number of Essential Genes

There are several different methods used for estimating the minimum number of essential genes an organism needs to survive in a controlled environment. Each method has its own shortcomings which limits their applications.

Comparative Genomics

Comparative genomics looks for genomic homology between different organisms. Genetic homology over a wide number of similar organisms could be an indicator of essential genes since they were conserved throughout those strains or species.[1][5] Unfortunately, a comparative approach could underestimate the number of essential genes since in only accounts for true genetic orthologs. For example, this gene estimate would not account for genes with different morphologies that code for functionally similar gene products.[8][9] In some instances, it could also underestimate the number of essential genes since homologous genes do not have to be useful or essential. For example, certain virulence factors that are homologous in many pathogenic microbes are not essential genes. [5]

Gene Disruption using Transposable Mutagenesis

Targeted gene disruption using Transposable mutagenesis involves attempting to inactivate genes using a large number of transposable elements, then sequencing the resulting genome. Theoretically, if transposable elements are unable to insert themselves into a gene, then those genes must be more essential to the cell than other genes that are susceptible to disruption.[10] Some of the genes screened may read a false positive for essentiality since there is the chance that some transducable genes may not have been moved to that gene. Also, one transposon may disable multiple genes (like in alternatively spliced genes). An essential gene could also function normally with a transposable element inside it.[1][8]

mRNA Disruption using Antisense RNA

Antisense RNA (asRNA) is a single strand of RNA that complementary to an mRNA inside a cell. When antisense RNA base pairs with mRNA, the mRNA is unable to be translated. Cells that can't survive in the presence of certain asRNAs indicate that those gene products are essential to cellular survival. Antisense RNA disruption can only work is there is an adequate amount of mRNA to disrupt. Intracellular signaling polypeptides may not be targeted by asRNA disruption since they don't need to be highly expressed.[8][11]

Genome Reduction

One of the most strait forward approaches to determining a minimal gene set is to reduce the number of genes in a cells genome until it can no longer survive. This method would be able to determine the essentiality of unknown genes as well as confirming genes thought to be essential by other methods. Current findings have shown that cells such as e. coli can live with no ill effects with 14.3% of the original genome removed.[12]

Genome Synthesis

Full genome synthesis involves synthesising a genome from scratch or building a genome from existing genes extracted from cells, then inserting the new genome into a cell. The most visable research in the area of genome synthesis has been the has been the synthesis of an M. genitalium genome by Gibson et. al.[13]


Genome Reduction

One approach to creating more reliable, efficient host organisms for synthetic constructs is the reduction of the genome to eliminate extraneous genes, mutagenic mobile elements, and other unnecessary or destabilizing factors. This can be viewed as a form of reverse engineering of extant strains.

Systematic Genome Reduction

One natural approach to engineering strains with a reduced genome is to systematically identify and delete regions of the genome not necessary for host cell survival. Posfai et al. created the MDS strains (multiple deletion strains) by aligning the genomes of multiple genomes of E. coli, identifying regions which were absent in multiple strains, and deleting them via Lambda Red recombination. All IS elements were removed as well, lowering the mutation rate and increasing the stability of genetic constructs introduced into the cell. The strain had comparable growth rate compared to wild type.[5][12]

Ara et al. constructed a minimal version of the B. subtilis genome in 2007. [14] This strain had slightly decreased growth rate compared to wild-type, but displayed normal morphology and similar protein production capabilities.

Selection for Reduced Genome

Long-term evolution of strains under the correct conditions could select for a genome of minimal size. Such conditions may include growth in rich media lacking sugars to favor the loss of biosynthetic pathways or sugar metabolism operons, growth in structured environments which favor a smaller cell, or growth under other conditions which favor the loss of unnecessary genes.

Mycoplasma mycoides genome synthesis strategy
Mycoplasma mycoides genome synthesis strategy


Minimal Genome Synthesis

Another approach is the synthesis of a minimal, designed genome from scratch using DNA synthesis technology and the transformation of this genome into cells to create a viable, novel, synthetic organism. This approach can be viewed as forward engineering of a novel organism, but would likely be informed by studies which determine the minimal set of genes necessary for a living organism.

Mycoplasma mycoides Synthesis

Gibson et al synthesized the first artificial cell by generating the Mycoplasma mycoides genome from digitized genome information and transforming it into Mycoplasma capricolum cells devoid of genomic information. These cells were capable of continuous self-replication and were identified by "watermarks" inserted in the genome. This technology could be utilized in the future to create cells with novel and useful properties from scratch.[15][13]

Images of M. genitalium that contain synthetic genomes.
Images of M. genitalium that contain synthetic genomes.




References

  1. Forster AC and Church GM. . pmid:16924266. PubMed HubMed [ForsterChurch2006]
  2. Hutchison CA, Peterson SN, Gill SR, Cline RT, White O, Fraser CM, Smith HO, and Venter JC. . pmid:10591650. PubMed HubMed [Hutchison1999]
  3. Jewett MC and Forster AC. . pmid:20638265. PubMed HubMed [JewettForster2010]
  4. K. Umenhoffer, T. Fehér, G. Balikó, F. Ayaydin, J. Pósfai, F. R Blattner, and G. Pósfai. Reduced evolvability of Escherichia coli MDS42, an IS-less cellular chassis for molecular and synthetic biology applications. Microb Cell Fact. 2010; 9: 38 [Umenhoffer2010]
  5. Kolisnychenko V, Plunkett G 3rd, Herring CD, Fehér T, Pósfai J, Blattner FR, and Pósfai G. . pmid:11932248. PubMed HubMed [Kolisnychenko2002]
  6. Kolisnychenko V, Plunkett G 3rd, Herring CD, Fehér T, Pósfai J, Blattner FR, and Pósfai G. . pmid:11932248. PubMed HubMed [Kolisnychenko2002]
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  8. May T and Okabe S. . pmid:21980953. PubMed HubMed [May2011]
  9. Kobayashi K, Ehrlich SD, Albertini A, Amati G, Andersen KK, Arnaud M, Asai K, Ashikaga S, Aymerich S, Bessieres P, Boland F, Brignell SC, Bron S, Bunai K, Chapuis J, Christiansen LC, Danchin A, Débarbouille M, Dervyn E, Deuerling E, Devine K, Devine SK, Dreesen O, Errington J, Fillinger S, Foster SJ, Fujita Y, Galizzi A, Gardan R, Eschevins C, Fukushima T, Haga K, Harwood CR, Hecker M, Hosoya D, Hullo MF, Kakeshita H, Karamata D, Kasahara Y, Kawamura F, Koga K, Koski P, Kuwana R, Imamura D, Ishimaru M, Ishikawa S, Ishio I, Le Coq D, Masson A, Mauël C, Meima R, Mellado RP, Moir A, Moriya S, Nagakawa E, Nanamiya H, Nakai S, Nygaard P, Ogura M, Ohanan T, O'Reilly M, O'Rourke M, Pragai Z, Pooley HM, Rapoport G, Rawlins JP, Rivas LA, Rivolta C, Sadaie A, Sadaie Y, Sarvas M, Sato T, Saxild HH, Scanlan E, Schumann W, Seegers JF, Sekiguchi J, Sekowska A, Séror SJ, Simon M, Stragier P, Studer R, Takamatsu H, Tanaka T, Takeuchi M, Thomaides HB, Vagner V, van Dijl JM, Watabe K, Wipat A, Yamamoto H, Yamamoto M, Yamamoto Y, Yamane K, Yata K, Yoshida K, Yoshikawa H, Zuber U, and Ogasawara N. . pmid:12682299. PubMed HubMed [Kobayashi2003]
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  11. C. M. Trepod,J. E. Mott. Elucidation of Essential and Nonessential Genes in the Haemophilus influenzae Rd Cell Wall Biosynthetic Pathway by Targeted Gene Disruption Antimicrob Agents Chemother. 2005 February; 49(2): 824–826 [Catherine2005]
  12. Ji Y, Zhang B, Van SF, Horn, Warren P, Woodnutt G, Burnham MK, and Rosenberg M. . pmid:11567142. PubMed HubMed [yinduo2001]
  13. Pósfai G, Plunkett G 3rd, Fehér T, Frisch D, Keil GM, Umenhoffer K, Kolisnychenko V, Stahl B, Sharma SS, de Arruda M, Burland V, Harcum SW, and Blattner FR. . pmid:16645050. PubMed HubMed [Posfai2006]
  14. Gibson DG, Glass JI, Lartigue C, Noskov VN, Chuang RY, Algire MA, Benders GA, Montague MG, Ma L, Moodie MM, Merryman C, Vashee S, Krishnakumar R, Assad-Garcia N, Andrews-Pfannkoch C, Denisova EA, Young L, Qi ZQ, Segall-Shapiro TH, Calvey CH, Parmar PP, Hutchison CA 3rd, Smith HO, and Venter JC. . pmid:20488990. PubMed HubMed [Gibson2010]
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All Medline abstracts: PubMed HubMed
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