Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/54658
Title: A microfluidic platform to study pathogen-host interactions at single cell level
Authors: Zhang, Rui
Keywords: DRNTU::Engineering::Bioengineering
Issue Date: 2012
Source: Zhang, R. (2012). A microfluidic platform to study pathogen-host interactions at single cell level. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: In this study, a high throughput poly(dimethylsiloxane) (PDMS) array chip consisting of multiple micro-wells and microfluidic channels was developed to analyze two biological perspectives of pathogen-host interactions – adherence and gene transcription – at single cell level, that current techniques are unable to cater to. The association of a common human pathogen, Pseudomonas aeruginosa, in either single or mixed (with Staphylococcus aureus) infection context, to the host human lung epithelial A549 cells was selected as the in vitro model to evaluate the performance of the chip. Single A549 cells were isolated into the individual micro-wells by one-step vacuum driven microfluidics when cell density was pre-adjusted to less than 0.3 cell/well. On-chip quantitative PCR was carried out with species-specific primer and probe sets to quantify the adhered bacteria. Single bacterium detection with the success rates of 90% for P. aeruginosa and 94% for S. aureus can be achieved with good reproducibility using the optimized DNA isolation protocol. Association profiling of P. aeruginosa and S. aureus in single infection context to A549 cells at three time points revealed different adherence patterns of these two pathogens. The attachment profiling of P. aeruginosa and S. aureus in mixed infection context was also obtained by on-chip multiplex q-PCR assay, from which P. aeruginosa association to the host A549 cells was identified to be significantly inhibited in the presence of S. aureus at 4 hours and 6 hours of infection. This chip was further developed for gene transcriptional regulation analysis by incorporation of a novel microfluidic phase partitioning technology for bacterial nucleic acid purification. DNA or RNA from P. aeruginosa and S. aureus in the range of 5000 down to a single cell in the sample volume of 1 µl or 125 nl, can be selectively recovered and directly put through on-chip quantitative PCR assay. The aqueous phase bacterial lysate was isolated in an array of micro-wells, after which an immiscible organic (phenol-chloroform) phase was introduced in a headspace channel connecting the micro-well array. Continuous flow of the organic phase increases the interfacial contact with the aqueous phase to achieve purification of target nucleic acid through phase partitioning. Significantly enhanced nucleic acid recovery yield, up to 10 fold higher, was achieved using the chip based liquid phase nucleic acid purification technique compared to that obtained by the conventional column based solid phase nucleic acid extraction method. One step vacuum-driven microfluidics allowed an on-chip quantitative PCR assay to be carried out in the same micro-wells within which bacterial nucleic acids were isolated, avoiding sample loss during liquid transfer. Using this nucleic acid purification device set in a two-dimensional (2D) array format of 900 micro-wells, it was demonstrated for the first time that high-throughput extraction of RNA coupled with direct on-chip PCR analysis from single bacterial cells could be achieved. The mRNA transcripts of rmd gene (an important gene involved in O antigen synthesis) of P. aeruginosa attached to single A549 cells were quantified using the 2D nucleic acid purification chip. The up-regulation of this gene in positive correlation with the number of P. aeruginosa adhered was reported. In summary, the proposed microfluidic platform that integrated liquid phase nucleic acid purification and on-chip quantitative PCR presents a simple and effective “all-in-one” solution for high throughput bacterial nucleic acid analysis down to single cell sensitivity and can be applied for both automated bacteria quantification and transcriptional profiling.
URI: https://hdl.handle.net/10356/54658
DOI: 10.32657/10356/54658
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Theses

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