The gut microbiota has attracted broad attention due to its high relevance to human health and disease. Next-generation deep sequencing in combination with bioinformatics is widely used to study the working mechanism of the microbiome. However, these techniques are costly, slow and complex. Collins and co-workers report the extended usage of their paper-based synthetic biology platform, which is much cheaper, more on-demand and simpler, for analysing microbial and host RNAs in complex biological samples.
This sensing platform includes two key steps: nucleic acid sequence-based amplification and RNA toehold switch-mediated sensing. The researchers find that identifying bacterial species via the detection of 16S ribosomal RNAs does not work here due to the significant crosstalk that occurs among related bacterial species, which can be attributed to similarities in their trigger RNA sequences. To address this specificity issue, they perform bioinformatics analysis and identify the species-unique mRNAs of ten bacteria that are relevant to microbiota studies. By normalizing to a single standard, they can measure the target RNAs semi-quantitatively via the above-mentioned two steps. This is validated on stool samples from inflammatory bowel disease patients, with the determined microbial and host mRNA concentrations well correlated with reverse transcription-qPCR.