Title |
Non-selective Separation of Bacterial Cells with Magnetic Nanoparticles Facilitated by Varying Surface Charge
|
---|---|
Published in |
Frontiers in Microbiology, December 2016
|
DOI | 10.3389/fmicb.2016.01891 |
Pubmed ID | |
Authors |
Xin-Lei Gao, Ming-Fei Shao, Yi-Sheng Xu, Yi Luo, Kai Zhang, Feng Ouyang, Ji Li |
Abstract |
Recovering microorganisms from environmental samples is a crucial primary step for understanding microbial communities using molecular ecological approaches. It is often challenging to harvest microorganisms both efficiently and unselectively, guaranteeing a similar microbial composition between original and separated biomasses. A magnetic nanoparticles (MNPs) based method was developed to effectively separate microbial biomass from glass fiber pulp entrapped bacteria. Buffering pH and nanoparticle silica encapsulation significantly affected both biomass recovery and microbial selectivity. Under optimized conditions (using citric acid coated Fe3O4, buffering pH = 2.2), the method was applied in the pretreatment of total suspended particle sampler collected bioaerosols, the effective volume for DNA extraction was increased 10-folds, and the overall method detection limit of microbial contaminants in bioaerosols significantly decreased. A consistent recovery of the majority of airborne bacterial populations was demonstrated by in-depth comparison of microbial composition using 16S rRNA gene high-throughput sequencing. Surface charge was shown as the deciding factor for the interaction between MNPs and microorganisms, which helps developing materials with high microbial selectivity. To our knowledge, this study is the first report using MNPs to separate diverse microbial community unselectively from a complex environmental matrix. The technique is convenient and sensitive, as well as feasible to apply in monitoring of microbial transport and other related fields. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 10 | 27% |
Student > Ph. D. Student | 10 | 27% |
Student > Master | 4 | 11% |
Student > Bachelor | 1 | 3% |
Professor > Associate Professor | 1 | 3% |
Other | 0 | 0% |
Unknown | 11 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 9 | 24% |
Biochemistry, Genetics and Molecular Biology | 5 | 14% |
Chemistry | 3 | 8% |
Computer Science | 2 | 5% |
Environmental Science | 1 | 3% |
Other | 4 | 11% |
Unknown | 13 | 35% |