title: Integrated application of uniform design and least-squares support vector machines to transfection optimization.
abstract: BACKGROUND
  Transfection in mammalian cells based on liposome presents great challenge for biological professionals. To protect themselves from exogenous insults, mammalian cells tend to manifest poor transfection efficiency. In order to gain high efficiency, we have to optimize several conditions of transfection, such as amount of liposome, amount of plasmid, and cell density at transfection. However, this process may be time-consuming and energy-consuming. Fortunately, several mathematical methods, developed in the past decades, may facilitate the resolution of this issue. This study investigates the possibility of optimizing transfection efficiency by using a method referred to as least-squares support vector machine, which requires only a few experiments and maintains fairly high accuracy.
  
  
  RESULTS
  A protocol consists of 15 experiments was performed according to the principle of uniform design. In this protocol, amount of liposome, amount of plasmid, and the number of seeded cells 24 h before transfection were set as independent variables and transfection efficiency was set as dependent variable. A model was deduced from independent variables and their respective dependent variable. Another protocol made up by 10 experiments was performed to test the accuracy of the model. The model manifested a high accuracy. Compared to traditional method, the integrated application of uniform design and least-squares support vector machine greatly reduced the number of required experiments. What's more, higher transfection efficiency was achieved.
  
  
  CONCLUSIONS
  The integrated application of uniform design and least-squares support vector machine is a simple technique for obtaining high transfection efficiency. Using this novel method, the number of required experiments would be greatly cut down while higher efficiency would be gained. Least-squares support vector machine may be applicable to many other problems that need to be optimized.
authors.affiliation: Division of Gastroenterology, Zhongshan Hospital, Gastroenterology Institute of Xiamen University, Gastroenterology Center of Xiamen, Fujian Province, PR China. panjinshui@yahoo.com.cn
authors.forename: Jin-Shui
authors.initials: JS
authors.lastname: Pan
authors.forename: Mei-Zhu
authors.initials: MZ
authors.lastname: Hong
authors.forename: Qi-Feng
authors.initials: QF
authors.lastname: Zhou
authors.forename: Jia-Yan
authors.initials: JY
authors.lastname: Cai
authors.forename: Hua-Zhen
authors.initials: HZ
authors.lastname: Wang
authors.forename: Lin-Kai
authors.initials: LK
authors.lastname: Luo
authors.forename: De-Qiang
authors.initials: DQ
authors.lastname: Yang
authors.forename: Jing
authors.initials: J
authors.lastname: Dong
authors.forename: Hua-Xiu
authors.initials: HX
authors.lastname: Shi
authors.forename: Jian-Lin
authors.initials: JL
authors.lastname: Ren
mesh_terms: D000465:Algorithms; D002461:Cell Line, Transformed; D005822:Genetic Vectors; D006801:Humans; D016018:Least-Squares Analysis; D008081:Liposomes; D008954:Models, Biological; D012984:Software; D014162:Transfection / Q000379:methods*
chemical_list: D008081:Liposomes