Whether they live within the human gut, a drop of ocean water or a gram of soil, microbial communities can influence their neighborhood through virulence and keep pesky neighbors from evicting them through resistance factors. The interplay of microbial genes and the nutrient sources within a specific area can stabilize their community as they fight to keep other types of communities away. Any change in these microbial battles can affect the microbes and how they interact with you and each other, causing substantial implications for your health.
As the human host, you can influence the microbial communities through what you eat, how you exercise and what medicines you take. But resident microbes aren’t simply waiting for you to inflict pain or gain upon them – their genetic content is fully adapted to their survival and their metabolism pathways are tuned to local nutrient sources.
How can we study the meaningful interactions between us and our microbes?
One of the most successful approaches scientists adopt to study host-microbiome interactions is metatranscriptomics.
While transcriptomics studies the complete set of RNA molecules in a single species, metatranscriptomics analyzes the transcriptomes of all the microorganisms in a specific environment, such as the human gut, water or soil. By using high-throughput RNA sequencing, researchers can better understand gene expression patterns and, subsequently, the metabolic activities and the functional roles of the various microbial species within that microbiome.
The critical steps in conducting metatranscriptomics include collecting and stabilizing samples, extracting high-quality RNA without inhibitors, depleting microbial ribosomal RNA while preparing RNA sequencing libraries, and then performing bioinformatic analysis to annotate the expressed genes and infer the functional capabilities of the microbial community.
There are two main strategies for monitoring host-microbiome interactions. Which approach is most suitable depends on the amount of sample you have, your sequencing budget and your research goal.
Single sample with parallel library approaches – for comprehensive analysis of the host genes and microbiome interactions
This metatranscriptomic approach involves isolating RNA from both the host organism and the resident microbiome. For the host-derived RNA, the poly(A) tail on mature mRNA molecules allows for selecting the coding transcripts through targeted purification techniques. This results in a highly purified host mRNA library that can be sequenced and aligned to the host genome.
In parallel, the microbial RNA fraction is subjected to rRNA depletion. This crucial step removes the abundant rRNA sequences, which otherwise would dominate the sequencing output and obscure the actively expressed mRNA transcripts from the microbial community.
The end product of this metatranscriptomic workflow is two complementary libraries: One containing the host's mRNA and the other comprising the microbiome's expressed genes. The host mRNA library is exceptionally clean, facilitating robust alignment and analysis of host gene expression.
The rRNA-removed library is slightly more complicated, as it contains a mix of microbial mRNA, host-derived mRNA and non-coding RNA. However, you can employ bioinformatic analysis to separate and annotate the microbial and host-derived transcripts. In the end, you gain information about the active functions of the microbial community and potential host responses.
Single sample with removal of host and microbial rRNA – Dual RNAseq
An alternative metatranscriptomic approach for analyzing host-microbiome interactions involves a single RNA isolation and rRNA depletion of both host and microbes in a single step. In this strategy, you extract total RNA from the sample, including transcripts from both the host and the resident microbiome. Here, removing rRNA from the sample is critical as more than 85% of the total RNA will contain rRNA. A highly efficient rRNA removal step increases the proportion of other important RNA molecules, which are more informative for analysis and decreases the amount of sequencing and cost.
Variations on library preparation techniques for poly-A host gene expression – 3’ RNA-seq
Coding RNA from the human host contains a poly-A tail, which can be used to enrich these RNA molecules or can be used as a priming site for 3’ RNA-seq. Instead of using random primers during RNA library construction, with 3’ RNA-seq, you can construct a 3' end-focused library to take advantage of the natural polyadenylation of mature mRNA transcripts in the host transcriptome.
Often, 3'-RNA-seq only covers part of the transcript, but it requires a lower sequencing budget and is advantageous when working with samples that contain fragmented RNA and low RNA Integrity Numbers (RIN). Using 3’ RNA-seq libraries improves the cost-efficiency of your experiment and yields a gene expression signature that can be used in deciphering activated and repressed signaling pathways.
Now that you’ve got the strategies down, do you want to hone down on each part of the process? How about starting at the sample prep and finding more information on RNA isolation? Take advantage of our guidelines for DNA and RNA extraction from stool samples.
And remember to drink some water, eat yogurt, get a good night's sleep and do something beneficial for the surroundings of your good microbes.