Advertisement

Genome-Wide Essential Gene Identification in Pathogens

  • Budhayash Gautam
  • Kavita Goswami
  • Satendra Singh
  • Gulshan Wadhwa
Chapter

Abstract

Genome-wide, a gene can be designated as indispensable for the survival of a cell or an organism, and its interruption can lead to the malfunctioning or death of the organism. Due to its essentiality for survival, these could be proposed as novel and promising candidates for broad-spectrum drug targets, if these are conserved across a genus. Identification of essential gene has been done in many organisms, and interestingly, most of them were pathogenic in nature. The genome-scale elucidation of essential genes plays an important role in development and complete genome availability. At large scale, gene-inactivation technologies such as targeted gene inactivation, genetic footprinting, and transposon-based mutagenesis are controlled by essential genes. In silico, numerous strategies and tools also have been developed, such as subtractive genomics, essentiality base mapping, and target identification using phylogenetic profiling. Bioinformatic approaches can also be used to analyze experimentally generated data. This chapter is referred to provide an overview of some of these methodologies which are often used to identify essential genes and their functions and discuss advantage and drawbacks of the methods.

Keywords

Essential gene DEG Genome-wide identification Subtractive genomics Essentiality-based mapping In silico drug target identification 

Notes

Acknowledgment

The authors are grateful to the Sam Higginbottom University of Agriculture, Technology and Sciences, Allahabad, for providing the facilities and support to complete the present research work.

References

  1. Akerley BJ et al (1998) Systematic identification of essential genes by in vitro mariner mutagenesis. Proc Natl Acad Sci 95:8927–8932CrossRefGoogle Scholar
  2. Bardarov S et al (2002) Specialized transduction: an efficient method for generating marked and unmarked targeted gene disruptions in Mycobacterium tuberculosis, M. bovis BCG and M. smegmatis. Microbiology 148:3007–3017CrossRefGoogle Scholar
  3. Barrett AD, Stanberry LR (2009) Vaccines for biodefense and emerging and neglected diseases. Academic, AmsterdamGoogle Scholar
  4. Basu MK et al (2011) ProPhylo: partial phylogenetic profiling to guide protein family construction and assignment of biological process. BMC Bioinformatics 12:1CrossRefGoogle Scholar
  5. Cooper I, Duffield M (2011) The in silico prediction of bacterial essential genes. In: Méndez-Vilas A (ed) Science against microbial pathogens: communicating current research and technological advances. FORMATEX Microbiology Series N° 3, vol 1. Formatex Research Center, BadajozGoogle Scholar
  6. Date SV, Marcotte EM (2003) Discovery of uncharacterized cellular systems by genome-wide analysis of functional linkages. Nat Biotechnol 21:1055–1062CrossRefGoogle Scholar
  7. Deng J et al (2010) Investigating the predictability of essential genes across distantly related organisms using an integrative approach. Nucleic Acids Res 39(3):795–807CrossRefGoogle Scholar
  8. Devine SE, Boeke JD (1994) Efficient integration of artificial transposons into plasmid targets in vitro: a useful tool for DNA mapping, sequencing and genetic analysis. Nucleic Acids Res 22:3765–3772CrossRefGoogle Scholar
  9. Fleischmann RD et al (1995) Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 269:496–512CrossRefGoogle Scholar
  10. Forsyth R et al (2002) A genome-wide strategy for the identification of essential genes in Staphylococcus aureus. Mol Microbiol 43:1387–1400CrossRefGoogle Scholar
  11. Freilich S et al (2009) Stratification of co-evolving genomic groups using ranked phylogenetic profiles. BMC Bioinformatics 10:1CrossRefGoogle Scholar
  12. Frøkjær-Jensen C et al (2010) Targeted gene deletions in C. elegans using transposon excision. Nat Methods 7:451–453CrossRefGoogle Scholar
  13. Gaasterland T, Ragan MA (1998) Microbial genescapes: phyletic and functional patterns of ORF distribution among prokaryotes. Microb Comp Genomics 3:199–217CrossRefGoogle Scholar
  14. Gautam B et al (2012) Metabolic pathway analysis and molecular docking analysis for identification of putative drug targets in Toxoplasma gondii: novel approach. Bioinformationtics 8:134–141CrossRefGoogle Scholar
  15. Gil R et al (2004) Determination of the core of a minimal bacterial gene set. Microbiol Mol Biol Rev 68:518–537CrossRefGoogle Scholar
  16. Grünblatt E et al (2014) Imaging genetics in obsessive-compulsive disorder: linking genetic variations to alterations in neuroimaging. Prog Neurobiol 121:114–124CrossRefGoogle Scholar
  17. Hayes F (2003) Transposon-based strategies for microbial functional genomics and proteomics. Annu Rev Genet 37:3–29CrossRefGoogle Scholar
  18. Holman AG et al (2009) Computational prediction of essential genes in an unculturable endosymbiotic bacterium, Wolbachia of Brugia malayi. BMC Microbiol 9:1CrossRefGoogle Scholar
  19. Hosen MI et al (2014) Application of a subtractive genomics approach for in silico identification and characterization of novel drug targets in Mycobacterium tuberculosis F11. Interdiscip Sci Comput Life Sci 6:48–56CrossRefGoogle Scholar
  20. Huynen MA, Bork P (1998) Measuring genome evolution. Proc Natl Acad Sci 95:5849–5856CrossRefGoogle Scholar
  21. Ishikawa M, Hori K (2013) A new simple method for introducing an unmarked mutation into a large gene of non-competent Gram-negative bacteria by FLP/FRT recombination. BMC Microbiol 13:86CrossRefGoogle Scholar
  22. Ivics Z et al (2009) Transposon-mediated genome manipulation in vertebrates. Nat Methods 6:415–422CrossRefGoogle Scholar
  23. Jimenez-Ruiz E et al (2014) Advantages and disadvantages of conditional systems for characterization of essential genes in Toxoplasma gondii. Parasitology 141:1390–1398CrossRefGoogle Scholar
  24. Jordan IK et al (2002) Essential genes are more evolutionarily conserved than are nonessential genes in bacteria. Genome Res 12:962–968CrossRefGoogle Scholar
  25. Joshi PB et al (2002) Targeted gene deletion in Leishmania major identifies leishmanolysin (GP63) as a virulence factor. Mol Biochem Parasitol 120:33–40CrossRefGoogle Scholar
  26. Jothi R et al (2007) Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment. BMC Bioinformatics 8:1CrossRefGoogle Scholar
  27. Judson N, Mekalanos JJ (2000) Transposon-based approaches to identify essential bacterial genes. Trends Microbiol 8:521–526CrossRefGoogle Scholar
  28. Juhas M et al (2012) High confidence prediction of essential genes in Burkholderia cenocepacia. PLoS One 7:e40064CrossRefGoogle Scholar
  29. Kang DC, Fisher PB (2005) Complete open reading frame (C-ORF) technology: simple and efficient technique for cloning full-length protein-coding sequences. Gene 353:1–7CrossRefGoogle Scholar
  30. Kensche PR et al (2008) Practical and theoretical advances in predicting the function of a protein by its phylogenetic distribution. J R Soc Interface 5:151–170CrossRefGoogle Scholar
  31. Kleckner N (1981) Transposable elements in prokaryotes. Annu Rev Genet 15:341–404CrossRefGoogle Scholar
  32. Koonin EV (2000) How many genes can make a cell: the minimal-gene-Set concept 1. Annu Rev Genomics Hum Genet 1:99–116CrossRefGoogle Scholar
  33. Langille MG et al (2013) Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 31:814–821CrossRefGoogle Scholar
  34. Lehoux DE et al (2001) Discovering essential and infection-related genes. Curr Opin Microbiol 4:515–519CrossRefGoogle Scholar
  35. Lin Y, Zhang RR (2011) Putative essential and core-essential genes in Mycoplasma genomes. Sci Rep 1Google Scholar
  36. Luisi PL et al (2002) The notion of a DNA minimal cell: a general discourse and some guidelines for an experimental approach. Helv Chim Acta 85:1759–1777CrossRefGoogle Scholar
  37. Luo H et al (2013) DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements. Nucleic Acids Res 42(Database issue):D574–D580PubMedPubMedCentralGoogle Scholar
  38. Mikkelsen TS et al (2005) Improving genome annotations using phylogenetic profile anomaly detection. Bioinformatics 21:464–470CrossRefGoogle Scholar
  39. O’sullivan GJ et al (2006) Potential and limitations of genetic manipulation in animals. Drug Discov Today Technol 3:173–180CrossRefGoogle Scholar
  40. Pellegrini M (2012) Using phylogenetic profiles to predict functional relationships. Bacterial Mol Netw Methods Protoc 804:167–177Google Scholar
  41. Plaimas K et al (2010) Identifying essential genes in bacterial metabolic networks with machine learning methods. BMC Syst Biol 4:1CrossRefGoogle Scholar
  42. Psomopoulos FE et al (2013) Detection of genomic idiosyncrasies using fuzzy phylogenetic profiles. PLoS One 8:e52854CrossRefGoogle Scholar
  43. Ranea JA et al (2007) Predicting protein function with hierarchical phylogenetic profiles: the Gene3D Phylo-Tuner method applied to eukaryotic genomes. PLoS Comput Biol 3:e237CrossRefGoogle Scholar
  44. Rusmini R et al (2014) A shotgun antisense approach to the identification of novel essential genes in Pseudomonas aeruginosa. BMC Microbiol 14:1CrossRefGoogle Scholar
  45. Sakharkar KR et al (2004) A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa. In Silico Biol 4:355–360PubMedGoogle Scholar
  46. Salama NR et al (2004) Global transposon mutagenesis and essential gene analysis of Helicobacter pylori. J Bacteriol 186:7926–7935CrossRefGoogle Scholar
  47. Sarangi AN et al (2009) Subtractive genomics approach for in silico identification and characterization of novel drug targets in Neisseria meningitidis serogroup B. J Comput Sci Syst Biol 2:255–258Google Scholar
  48. Sassetti CM et al (2003) Genes required for mycobacterial growth defined by high density mutagenesis. Mol Microbiol 48:77–84CrossRefGoogle Scholar
  49. Schmidt M, Oliver D (1989) SecA protein autogenously represses its own translation during normal protein secretion in Escherichia coli. J Bacteriol 171:643–649CrossRefGoogle Scholar
  50. Singh IR et al (1997) High-resolution functional mapping of a cloned gene by genetic footprinting. Proc Natl Acad Sci 94:1304–1309CrossRefGoogle Scholar
  51. Smith V et al (1995) Genetic footprinting: a genomic strategy for determining a gene’s function given its sequence. Proc Natl Acad Sci 92:6479–6483CrossRefGoogle Scholar
  52. Snitkin ES et al (2006) Comparative assessment of performance and genome dependence among phylogenetic profiling methods. BMC Bioinformatics 7:420CrossRefGoogle Scholar
  53. Song JH, Ko KS (2008) Detection of essential genes in Streptococcus pneumoniae using bioinformatics and allelic replacement mutagenesis. Microb Gene Essentiality Protoc Bioinformatics 416:401–408CrossRefGoogle Scholar
  54. Tatusov RL et al (1997) A genomic perspective on protein families. Science 278:631–637CrossRefGoogle Scholar
  55. Touchon M et al (2009) Organised genome dynamics in the Escherichia coli species results in highly diverse adaptive paths. PLoS Genet 5:e1000344CrossRefGoogle Scholar
  56. Wong SM, Mekalanos JJ (2000) Genetic footprinting with mariner-based transposition in Pseudomonas aeruginosa. Proc Natl Acad Sci 97:10191–10196CrossRefGoogle Scholar
  57. Xiong J et al (2006) Genome wide prediction of protein function via a generic knowledge discovery approach based on evidence integration. BMC Bioinformatics 7:268CrossRefGoogle Scholar
  58. Xu P et al (2011) Genome-wide essential gene identification in Streptococcus sanguinis. Sci Rep 1:125CrossRefGoogle Scholar
  59. Yaveroglu ON, Can T (2009) Predicting protein-protein interactions from protein sequences using phylogenetic profiles. Int J Comput Electr Autom Control Inf Eng 3:1971–1977Google Scholar
  60. Zhang Z, Ren Q (2015) Why are essential genes essential? – the essentiality of Saccharomyces genes. Microbial Cell 2:280–287CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Budhayash Gautam
    • 1
  • Kavita Goswami
    • 2
  • Satendra Singh
    • 1
  • Gulshan Wadhwa
    • 3
  1. 1.Department of Computational Biology and BioinformaticsJacob Institute of Biotechnology and Bioengineering, Sam Higginbottom University of Agriculture, Technology and SciencesAllahabadIndia
  2. 2.Plant RNAi Biology GroupInternational Center for Genetic Engineering and BiotechnologyNew DelhiIndia
  3. 3.Department of Biotechnology, Apex Bioinformatics CentreMinistry of Science & TechnologyNew DelhiIndia

Personalised recommendations