Skip to main content

Strain Improvement of Microbes

  • Chapter
  • First Online:
Industrial Microbiology and Biotechnology

Abstract

Strain improvement is an advanced biotechnological strategy where various cellular pathways are modified by recombinant DNA technology to improve the yield of metabolic products that are beneficial to humanity. Strain improvements are directed toward improving product quality and yield by enhancing substrate utilization, regulating enzyme activity, resistance to phage infection, etc. The primary genetic routes to strain improvement include (1) mutagenesis for the creation of genetic variants, (2) screening to select improved strains, (3) identification of improved strains, and (4) mass culture optimization of operational and cellular responses and downstream processing. This chapter details the various strain improvement strategies and the respective computational and biotechnological methods that are used.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

asRNA:

Antisense RNA

BWA:

Burrows-Wheeler Aligner

CCDS:

Consensus Coding Sequence

cDNA:

Complementary DNA

CRISPR:

Clustered regularly interspaced short palindromic repeats

DDBJ:

DNA Data Bank of Japan

EMBL:

European Molecular Biology Laboratory

EMS:

Ethyl methanesulfonate

EST:

Expressed Sequence Tags

ExPASy:

Expert Protein Analysis System

GATK:

Genome Analysis Toolkit

GI:

GenInfo

GO:

Gene Ontology

GSS:

Genome Survey Sequences

HA:

Hydroxylamine

HTGS:

High-Throughput Genomic Sequence

indels:

Insertions/deletions

MALDI-ToF:

Matrix-assisted laser desorption/ionization time-of-flight spectroscopy

MMS:

Methyl methanesulfonate

MPSS:

Massive parallel signature sequencing

NGS:

Next-generation sequencing

NTG:

Nitrosoguanidine

PRIDE:

PRoteomics IDEntifications

RDT:

Recombinant DNA technology

RefSeq:

Reference sequences

RISC:

RNA-induced silencing complex

RNAi:

RNA interference

siRNAs:

Small interfering RNAs

SNPs:

Single-nucleotide polymorphisms

STS:

Sequence-Tagged Sites

SVs:

Structural variants

TALENs:

Transcription activator-like effector nucleases

UV:

Ultraviolet

ZFN:

Zinc finger nucleases

References

  • Adrio JL, Demain AL (2006) Genetic improvement of processes yielding microbial products. FEMS Microbiol Rev 30(2):187–214

    CAS  PubMed  Google Scholar 

  • Agrawal K, Verma P (2020) Multicopper oxidase laccases with distinguished spectral properties: a new outlook. Heliyon 6(5):E03972. https://doi.org/10.1016/j.heliyon.2020.e03972

    Article  PubMed  PubMed Central  Google Scholar 

  • Agrawal N, Dasaradhi PVN, Mohmmed A, Malhotra P, Bhatnagar RK, Mukherjee SK (2003) RNA interference: biology, mechanism, and applications. Microbiol Mol Biol Rev 67(4):657–685

    CAS  PubMed  PubMed Central  Google Scholar 

  • Agrawal K, Shankar J, Verma P (2020a) Multicopper oxidase (MCO) laccase from Stropharia sp. ITCC-8422: an apparent authentication using integrated experimental and in silico analysis. 3 Biotech 10:413. https://doi.org/10.1007/s13205-020-02399-8

    Article  PubMed  PubMed Central  Google Scholar 

  • Agrawal K, Shankar J, Kumar R, Verma P (2020b) Insight into multicopper oxidase laccase from Myrothecium verrucaria ITCC-8447: a case study using in silico and experimental analysis. J Environ Sci Health B 55(12):1048–1060. https://doi.org/10.1080/03601234.2020.1812334

    Article  CAS  PubMed  Google Scholar 

  • Alm EW, Oerther DB, Larsen N, Stahl DA, Raskin L (1996) The oligonucleotide probe database. Appl Environ Microbiol 62(10):3557–3559

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bairoch A, Apweiler R (1996) The SWISS-PROT protein sequence data bank and its new supplement TREMBL. Nucleic Acids Res 24(1):21–25

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bairoch A, Apweiler R (1997) The SWISS-PROT protein sequence data bank and its supplement TrEMBL. Nucleic Acids Res 25(1):31–36

    CAS  PubMed  PubMed Central  Google Scholar 

  • Baker W, van den Broek A, Camon E, Hingamp P, Sterk P, Stoesser G, Tuli MA (2000) The EMBL nucleotide sequence database. Nucleic Acids Res 28(1):19–23

    CAS  PubMed  PubMed Central  Google Scholar 

  • Behjati S, Tarpey PS (2013) What is next generation sequencing? Arch Dis Child Educ Pract Ed 98(6):236–238

    PubMed  PubMed Central  Google Scholar 

  • Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW (2010) GenBank. Nucleic Acids Res 38(Database issue):D46–D51

    CAS  PubMed  Google Scholar 

  • Bhardwaj N, Verma V, Chaturvedi V, Verma P (2018) GH10 XynF1 and Xyn11A: the predominant xylanase identified in the profiling of extracellular proteome of Aspergillus oryzae LC1. Ann Microbiol 68:731–742. https://doi.org/10.1007/s13213-018-1378-3

    Article  Google Scholar 

  • Bhardwaj N, Kumar B, Verma P (2019) A detailed overview of xylanases: an emerging biomolecule for current and future prospective. Bioresour Bioprocess 6:40. https://doi.org/10.1186/s40643-019-0276-2

    Article  Google Scholar 

  • Bhardwaj N, Verma V, Chaturvedi V, Verma P (2020) Cloning, expression and characterization of a thermo-alkali-stable xylanase from Aspergillus oryzae LC1 in Escherichia coli BL21 (DE3). Protein Expr Purif 168:105551. https://doi.org/10.1016/j.pep.2019.105551

    Article  CAS  PubMed  Google Scholar 

  • Binnie C, Warren M, Butler MJ (1989) Cloning and heterologous expression in Streptomyces lividans of Streptomyces rimosus genes involved in oxytetracycline biosynthesis. J Bacteriol 171(2):887

    CAS  PubMed  PubMed Central  Google Scholar 

  • Brouard JS, Schenkel F, Marete A, Bissonnette N (2019) The GATK joint genotyping workflow is appropriate for calling variants in RNA-seq experiments. J Anim Sci Biotechnol 10:44

    PubMed  PubMed Central  Google Scholar 

  • Carroll D (2011) Genome engineering with zinc-finger nucleases. Genetics 188(4):773–782

    CAS  PubMed  PubMed Central  Google Scholar 

  • Chaurasia AK, Parasnis A, Apte SK (2008) An integrative expression vector for strain improvement and environmental applications of the nitrogen fixing cyanobacterium, Anabaena sp. strain PCC7120. J Microbiol Methods 73(2):133–141

    CAS  PubMed  Google Scholar 

  • Consortium GO (2008a) The Gene Ontology project in 2008. Nucleic Acids Res 36(Database issue):D440–D444

    Google Scholar 

  • Consortium U (2008b) The universal protein resource (UniProt). Nucleic Acids Res 36(Database issue):D190–D195

    Google Scholar 

  • Derkx PMF, Janzen T, Sørensen KI, Christensen JE, Stuer-Lauridsen B, Johansen E (2014) The art of strain improvement of industrial lactic acid bacteria without the use of recombinant DNA technology. Microb Cell Factories 13(1):S5

    Google Scholar 

  • Dong H, Zhang Y, Zhu Y, Luan G, Wang R, Tao W, Li Y (2011) 3.08—Biofuels and bioenergy: acetone and butanol. In: Moo-Young M (ed) Comprehensive biotechnology, 2nd edn. Academic Press, Burlington, pp 71–85

    Google Scholar 

  • Donohoue PD, Barrangou R, May AP (2018) Advances in industrial biotechnology using CRISPR-Cas Systems. Trends Biotechnol 36(2):134–146

    CAS  PubMed  Google Scholar 

  • Drmanac R, Sparks AB, Callow MJ, Halpern AL, Burns NL, Kermani BG, Carnevali P, Nazarenko I, Nilsen GB, Yeung G, Dahl F, Fernandez A, Staker B, Pant KP, Baccash J, Borcherding AP, Brownley A, Cedeno R, Chen L, Chernikoff D, Cheung A, Chirita R, Curson B, Ebert JC, Hacker CR, Hartlage R, Hauser B, Huang S, Jiang Y, Karpinchyk V, Koenig M, Kong C, Landers T, Le C, Liu J, McBride CE, Morenzoni M, Morey RE, Mutch K, Perazich H, Perry K, Peters BA, Peterson J, Pethiyagoda CL, Pothuraju K, Richter C, Rosenbaum AM, Roy S, Shafto J, Sharanhovich U, Shannon KW, Sheppy CG, Sun M, Thakuria JV, Tran A, Vu D, Zaranek AW, Wu X, Drmanac S, Oliphant AR, Banyai WC, Martin B, Ballinger DG, Church GM, Reid CA (2010) Human genome sequencing using unchained base reads on self-assembling DNA nanoarrays. Science 327(5961):78

    CAS  PubMed  Google Scholar 

  • Edwards JS, Palsson BO (1998) How will bioinformatics influence metabolic engineering? Biotechnol Bioeng 58(2–3):162–169

    CAS  PubMed  Google Scholar 

  • Eness J, Del Cardayré SB, Minshull J, Stemmer WPC (2001) Molecular breeding: the natural approach to protein design, Advances in protein chemistry, vol 55. Academic, New York, pp 261–292

    Google Scholar 

  • Fiedurek J, Trytek M, Szczodrak J (2017) Strain improvement of industrially important microorganisms based on resistance to toxic metabolites and abiotic stress. J Basic Microbiol 57(6):445–459

    CAS  PubMed  Google Scholar 

  • Freese E, Bautz E, Freese EB (1961) The chemical and mutagenic specificity of hydroxylamine. Proc Natl Acad Sci U S A 47(6):845–855

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel RD, Bairoch A (2003) ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res 31(13):3784–3788

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gizzatkulov NM, Goryanin II, Metelkin EA, Mogilevskaya EA, Peskov KV, Demin OV (2010) DBSolve Optimum: a software package for kinetic modeling which allows dynamic visualization of simulation results. BMC Syst Biol 4(1):109

    PubMed  PubMed Central  Google Scholar 

  • Grigg GW (1965) Prevention of competitive suppression in microbial plating experiments. Nature 207(4992):105–106

    CAS  PubMed  Google Scholar 

  • Gutierrez-Guerrero A, Sanchez-Hernandez S, Galvani G, Pinedo-Gomez J, Martin-Guerra R, Sanchez-Gilabert A, Aguilar-González A, Cobo M, Gregory P, Holmes M, Benabdellah K, Martin F (2018) Comparison of zinc finger nucleases versus CRISPR-specific nucleases for genome editing of the Wiskott-Aldrich Syndrome Locus. Hum Gene Ther 29(3):366–380

    CAS  PubMed  Google Scholar 

  • Harlander SK (1992) Genetic improvement of microbial starter cultures applications of biotechnology to fermented foods: report of an Ad Hoc Panel of the Board on Science and Technology for International Development. National Academies Press (US), Washington, DC

    Google Scholar 

  • Karos M, Vilariño C, Bollschweiler C, Revuelta JL (2004) A genome-wide transcription analysis of a fungal riboflavin overproducer. J Biotechnol 113(1):69–76

    CAS  PubMed  Google Scholar 

  • Katsumata R, Ozaki A, Oka T, Furuya A (1984) Protoplast transformation of glutamate-producing bacteria with plasmid DNA. J Bacteriol 159(1):306–311

    CAS  PubMed  PubMed Central  Google Scholar 

  • Koenig T, Menze BH, Kirchner M, Monigatti F, Parker KC, Patterson T, Steen JJ, Hamprecht FA, Steen H (2008) Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics. J Proteome Res 7(9):3708–3717

    CAS  PubMed  Google Scholar 

  • Kumar B, Verma P (2020) Enzyme mediated multi-product process: a concept of bio-based refinery. Ind Crop Prod 154(2020):112607. https://doi.org/10.1016/j.indcrop.2020.112607

    Article  CAS  Google Scholar 

  • Kumar B, Verma P (2021) Biomass-based biorefineries: an important architype towards a circular economy. Fuel 288:119622

    CAS  Google Scholar 

  • Lancini G, Lorenzetti R (1993) Strain improvement and process development. In: Lancini G, Lorenzetti R (eds) Biotechnology of antibiotics and other bioactive microbial metabolites. Springer US, Boston, pp 175–190

    Google Scholar 

  • Langmead B (2010) Aligning short sequencing reads with Bowtie. Curr Protoc Bioinform Chapter 11:Unit 11.7

    Google Scholar 

  • Lee JH, Lee DE, Lee BU, Kim HS (2003) Global analyses of transcriptomes and proteomes of a parent strain and an L-threonine-overproducing mutant strain. J Bacteriol 185(18):5442–5451

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lee SY, Lee D-Y, Kim TY (2005) Systems biotechnology for strain improvement. Trends Biotechnol 23(7):349–358

    CAS  PubMed  Google Scholar 

  • Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754–1760

    CAS  PubMed  PubMed Central  Google Scholar 

  • Liu L, Li Y, Li S, Hu N, He Y, Pong R, Lin D, Lu L, Law M (2012) Comparison of next-generation sequencing systems. J Biomed Biotechnol 2012:251364

    PubMed  PubMed Central  Google Scholar 

  • Magasanik B (1961) Catabolite repression. Cold Spring Harb Symp Quant Biol 26:249–256

    CAS  PubMed  Google Scholar 

  • Mashima J, Kodama Y, Fujisawa T, Katayama T, Okuda Y, Kaminuma E, Ogasawara O, Okubo K, Nakamura Y, Takagi T (2017) DNA Data Bank of Japan. Nucleic Acids Res 45(D1):D25–D31

    CAS  PubMed  Google Scholar 

  • Masurekar PS, Demain AL (1974) Impaired penicillin production in lysine regulatory mutants of Penicillium chrysogenum. Antimicrob Agents Chemother 6(3):366–368

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mendes P (1993) GEPASI: a software package for modelling the dynamics, steady states and control of biochemical and other systems. Comput Appl Biosci 9(5):563–571

    CAS  PubMed  Google Scholar 

  • Mills DR, Peterson RL, Spiegelman S (1967) An extracellular Darwinian experiment with a self-duplicating nucleic acid molecule. Proc Natl Acad Sci 58(1):217

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mount DW (2009) Using hidden Markov models to align multiple sequences. Cold Spring Harb Protoc 2009(7):1–7

    Google Scholar 

  • Murphy KC (2016) λ recombination and recombineering. EcoSal Plus 7(1)

    Google Scholar 

  • Ohnishi J, Mitsuhashi S, Hayashi M, Ando S, Yokoi H, Ochiai K, Ikeda M (2002) A novel methodology employing Corynebacterium glutamicum genome information to generate a new L-lysine-producing mutant. Appl Microbiol Biotechnol 58(2):217–223

    CAS  PubMed  Google Scholar 

  • Ondov BD, Varadarajan A, Passalacqua KD, Bergman NH (2008) Efficient mapping of Applied Biosystems SOLiD sequence data to a reference genome for functional genomic applications. Bioinformatics 24(23):2776–2777

    CAS  PubMed  PubMed Central  Google Scholar 

  • Parekh S, Vinci VA, Strobel RJ (2000) Improvement of microbial strains and fermentation processes. Appl Microbiol Biotechnol 54(3):287–301

    CAS  PubMed  Google Scholar 

  • Preston A (2003) Choosing a cloning vector. Methods Mol Biol 235:19–26

    CAS  PubMed  Google Scholar 

  • Pruitt KD, Tatusova T, Maglott DR (2007) NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 35(Database issue):D61–D65

    CAS  PubMed  Google Scholar 

  • Pujar S, O’Leary NA, Farrell CM, Loveland JE, Mudge JM, Wallin C, Girón CG, Diekhans M, Barnes I, Bennett R, Berry AE, Cox E, Davidson C, Goldfarb T, Gonzalez JM, Hunt T, Jackson J, Joardar V, Kay MP, Kodali VK, Martin FJ, McAndrews M, McGarvey KM, Murphy M, Rajput B, Rangwala SH, Riddick LD, Seal RL, Suner MM, Webb D, Zhu S, Aken BL, Bruford EA, Bult CJ, Frankish A, Murphy T, Pruitt KD (2018) Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation. Nucleic Acids Res 46(D1):D221–D228

    CAS  PubMed  Google Scholar 

  • Raychaudhuri S (2006) Computational text analysis: for functional genomics and bioinformatics. Oxford University Press, Oxford

    Google Scholar 

  • Rossouw D, van den Dool AH, Jacobson D, Bauer FF (2010) Comparative transcriptomic and proteomic profiling of industrial wine yeast strains. Appl Environ Microbiol 76(12):3911

    CAS  PubMed  PubMed Central  Google Scholar 

  • Rowlands RT (1984) Industrial strain improvement: mutagenesis and random screening procedures. Enzym Microb Technol 6(1):3–10

    CAS  Google Scholar 

  • Saghizadeh M, Brown DJ, Tajbakhsh J, Chen Z, Kenney MC, Farber DB, Nelson SF (2003) Evaluation of techniques using amplified nucleic acid probes for gene expression profiling. Biomol Eng 20(3):97–106

    CAS  PubMed  Google Scholar 

  • Salo OV, Ries M, Medema MH, Lankhorst PP, Vreeken RJ, Bovenberg RAL, Driessen AJM (2015) Genomic mutational analysis of the impact of the classical strain improvement program on β–lactam producing Penicillium chrysogenum. BMC Genomics 16(1):937

    PubMed  PubMed Central  Google Scholar 

  • Sauro HM, Hucka M, Finney A, Wellock C, Bolouri H, Doyle J, Kitano H (2003) Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration. OMICS 7(4):355–372

    CAS  PubMed  Google Scholar 

  • Schaeffer P, Cami B, Hotchkiss RD (1976) Fusion of bacterial protoplasts. Proc Natl Acad Sci U S A 73(6):2151–2155

    CAS  PubMed  PubMed Central  Google Scholar 

  • Sikora A, Mielecki D, Chojnacka A, Nieminuszczy J, Wrzesinski M, Grzesiuk E (2010) Lethal and mutagenic properties of MMS-generated DNA lesions in Escherichia coli cells deficient in BER and AlkB-directed DNA repair. Mutagenesis 25(2):139–147

    CAS  PubMed  Google Scholar 

  • Tarca AL, Romero R, Draghici S (2006) Analysis of microarray experiments of gene expression profiling. Am J Obstet Gynecol 195(2):373–388

    CAS  PubMed  PubMed Central  Google Scholar 

  • Thomas L, Joseph A, Gottumukkala LD (2014) Xylanase and cellulase systems of Clostridium sp.: an insight on molecular approaches for strain improvement. Bioresour Technol 158:343–350

    CAS  PubMed  Google Scholar 

  • Thorvaldsdóttir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14(2):178–192

    PubMed  Google Scholar 

  • Thykaer J, Nielsen J (2003) Metabolic engineering of β-lactam production. Metab Eng 5(1):56–69

    CAS  PubMed  Google Scholar 

  • Tomita M, Hashimoto K, Takahashi K, Shimizu TS, Matsuzaki Y, Miyoshi F, Saito K, Tanida S, Yugi K, Venter JC, Hutchison CA III (1999) E-CELL: software environment for whole-cell simulation. Bioinformatics 15(1):72–84

    CAS  PubMed  Google Scholar 

  • Tripathi KK (2000) Bioinformatics: the foundation of present and future biotechnology. Curr Sci 79(5):570–575

    CAS  Google Scholar 

Download references

Acknowledgments

This work was supported in part by SERB Core Research Grant, EMR/2016/003705 (SD), and MoE-STARS/STARS-1/ 643 (SD). AK is supported by a Junior Research Fellowship from CSIR, Government of India.

Conflicts of Interest

The authors do not have any conflict of interest to declare.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Supratim Datta .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Konar, A., Datta, S. (2022). Strain Improvement of Microbes. In: Verma, P. (eds) Industrial Microbiology and Biotechnology. Springer, Singapore. https://doi.org/10.1007/978-981-16-5214-1_6

Download citation

Publish with us

Policies and ethics