Literature DB >> 10508639

Genomics for food biotechnology: prospects of the use of high-throughput technologies for the improvement of food microorganisms.

O P Kuipers1.   

Abstract

Functional genomics is currently the most effective approach for increasing the knowledge at the molecular level of metabolic and adaptive processes in whole cells. High-throughput technologies, such as DNA microarrays, and improved two-dimensional electrophoresis methods combined with tandem mass-spectroscopy, supported by bioinformatics, are useful tools for food biotechnology, which depends on detailed knowledge of the properties of food microbes (and pathogens) in their industrial, food and consumer environments. Genomics of food microbes, based on rapidly emerging genome sequence information, generates valuable knowledge that can be used for metabolic engineering, improving cell factories and development of novel preservation methods. Furthermore, pre- and probiotic studies, characterization of stress responses, studies of microbial ecology and, last but not least, development of novel risk assessment procedures will be facilitated.

Mesh:

Substances:

Year:  1999        PMID: 10508639     DOI: 10.1016/s0958-1669(99)00019-1

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  3 in total

1.  Generation of subspecies level-specific microbial diagnostic microarrays using genes amplified from subtractive suppression hybridization as microarray probes.

Authors:  Jin-Woo Bae; Sung-Keun Rhee; Young-Do Nam; Yong-Ha Park
Journal:  Nucleic Acids Res       Date:  2005-07-19       Impact factor: 16.971

2.  Unrestrained markerless trait stacking in Nannochloropsis gaditana through combined genome editing and marker recycling technologies.

Authors:  John Verruto; Kristie Francis; Yingjun Wang; Melisa C Low; Jessica Greiner; Sarah Tacke; Fedor Kuzminov; William Lambert; Jay McCarren; Imad Ajjawi; Nicholas Bauman; Ryan Kalb; Gregory Hannum; Eric R Moellering
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-09       Impact factor: 11.205

3.  A Parallel Software Pipeline for DMET Microarray Genotyping Data Analysis.

Authors:  Giuseppe Agapito; Pietro Hiram Guzzi; Mario Cannataro
Journal:  High Throughput       Date:  2018-06-14
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.