Enrichment of gut microbiome strains for cultivation-free genome sequencing using droplet microfluidics
Posted on: 24 June 2021
Preprint posted on 2 June 2021
A microfluidics chip enables single-cell and cultivation-free genome sequencing of gut microbiome bacteria
Selected by Afonso Mendes
Categories: biochemistry, bioengineering, bioinformatics, cell biology, genetics, genomics, microbiology, molecular biology
Figure 1 – Overview of the framework developed. A microfluidic chip (top-left) was designed to generate droplets of an emulsion created from oil and an aqueous cell suspension. Droplet PCR using biotinylated primers is performed “off-chip” to detect the presence of the target DNA sequence; a positive result yields a fluorescent signal (top-center) and biotinylated amplicons. The droplets are then reinjected into a sorting chip designed to generate a sample enriched in positive droplets (top-right). Finally, the sample is cleared of amplicons using streptavidin-conjugated magnetic beads and used for whole-genome amplification and sequencing. Adapted from Figure 1 of the preprint.
Background
The gut microbiome contains at least several thousand species [1] and is linked to over 100 human diseases or syndromes [2-5]. Furthermore, it impacts the success of pharmacological intervention by influencing drug metabolism [6,7]. Microbiome studies often involve the reconstruction of metagenomically-assembled genomes (MAGs) of abundant taxa, which are prone to chimeric assemblies. Microfluidic droplet screens can overcome this problem by enabling single-cell analysis. However, this approach is severely limited by the inability to culture natural isolates required to obtain suitable samples. Cultivation-free methods using microfluidic droplets that can generate single amplified genomes (SAGs) are available [8,9] but lack the specificity required to map particular genes of interest. Droplet digital PCR can be implemented to improve the assays’ specificity but so far has never been used to study complex microbiomes in stool samples. This preprint reports the development of a framework that enables cultivation-free sequencing of genome fragments in stool samples to recover high-quality genomes.
Key findings
1- Development of a cultivation-free assay that enables the retrieval of high-quality genomes from complex samples
The first step in the framework developed is the generation of droplets containing single bacterial cells (Figure 1, top-left). This is achieved using a microchip designed to generate oil droplets encapsulating single cells from an aqueous cell suspension. An “off-chip” droplet PCR is performed to detect the presence of a particular bacterial species or strain using biotinylated primers; a positive droplet becomes fluorescent due to the presence of sequence-specific TaqMan probes (Figure 1, top-center). The droplets are then injected into a second microchip designed to sort the positive droplets into a bulk sample enriched in genomic DNA for the target sequence (Figure 1, top-right). The bulk samples are cleared of amplicons using streptavidin-conjugated magnetic beads (Figure 1, bottom) and used for sequencing-based genome reconstruction.
2 – Assay optimization and validation using controlled samples
The density of bacterial cells in stool samples was quantified with flow cytometry using a non-specific DNA stain (Syto-BC). Single-copy non-16S ribosomal RNA marker gene sequences were obtained directly from shotgun metagenomic data to quantitatively determine the relative abundance of taxa in the samples. Then, primer pairs and TaqMan probes against marker sequences were designed to target different microbial strains. The specificity of the TaqMan probe signal was validated using stool samples and culture mixes of several taxa. Several alternative sequences for each target organism were tested, and the best performing are provided in Table 1 of the preprint.
The cell density determined previously was then diluted to a ratio that maximizes the generation of droplets hosting single cells, estimated to be 1 cell for every 4 droplets. The results were confirmed using fluorescence microscopy and a custom ImageJ macro. This assay produced fluorescence-positive single-cell droplets with an efficiency of 80% relative to the theoretical maximum values considering a Poisson model for the number of cells per droplet generated.
A fluorescence threshold that resulted exclusively in positive droplets observable by PCR or microscopy was empirically determined using stool samples spiked with a lab isolate of B. subtilis at different ratios.
As a consequence of the PCR-based detection approach, the samples are enriched in amplicons, which become the most abundant DNA fragments in droplets containing a single genome copy. This caveat is circumvented using biotinylated PCR primers, which can be used to remove the amplicons from a pool of droplets using streptavidin-conjugated magnetic beads. Using this method, the levels of amplicons became undetectable after three rounds of bead purification and remained as such after DNA amplification during Illumina sequencing library preparation. Thermocycling in droplets resulted in genomic DNA fragments with sizes (300 to 3000 bp) suitable for preparing the sequencing library, not requiring additional fragmentation steps. Importantly, the authors determined that high-quality genomes could be retrieved from only 4000 cells using the framework developed.
3- Retrieval of high-quality de-novo genomes of endogenous bacteria from clinical samples
After the benchmarking steps described previously, the framework was applied to the endogenous stool bacterium B. vulgatus in two aliquots of the same stool sample.
The samples were sorted for the target bacterium, and the corresponding sequencing data was assembled (Figures 2A and 2B).
A high-quality genome was retrieved from each aliquot. CheckM [10] was used to calculate genome “completeness” with scores of 89% and 99% for each genome and contamination levels below 1%. The high quality of the data collected was further demonstrated comparing to reference genomes (Figure 2C).
Why I think this work is important
In the past years, a large number of studies provided insight into the influence of the gut microbiome on the health of individuals. The species composition of the gut microbiome is often associated with its functional properties. Thus, understanding how this composition can be modulated as a consequence of certain conditions or through medical interventions is important to improve populations’ health. However, given the taxonomic complexity of the microbiome and the inability to culture most endogenous strains, determining the relative abundance of taxa and recovering high-quality genomes of species of interest from clinical samples in a precise and reproducible manner is difficult using current approaches.
In this preprint, the authors develop an assay that overcomes these limitations by combining the advantages of several cutting-edge techniques. Importantly, they provide a detailed description of the framework developed and instructions for its correct implementation.
Questions for the authors
1 – Your new method enables cultivation-free work with gut microbiota, while clinical tests routinely involve cultivation. How do you envision the role of cultivation-free methods like this for targeted analysis of the microbiota of interest, versus cultivation-based alternatives?
2 – A feasible method to characterize an individual’s microbiome is an important step for Precision Medicine. How far do you think we are from implementing frameworks like yours in clinical settings?
References
[1] Almeida, A. et al. A new genomic blueprint of the human gut microbiota. Nature 568, 499–504 (2019).
[2] Nobu, M. K. et al. Microbial dark matter ecogenomics reveals complex synergistic networks in a methanogenic bioreactor. Isme J 9, 1710–1722 (2015).
[3] Gupta, S., Allen-Vercoe, E. & Petrof, E. O. Fecal microbiota transplantation: in perspective. Ther Adv Gastroenter 9, 229–239 (2016).
[4] Louis, P., Hold, G. L. & Flint, H. J. The gut microbiota, bacterial metabolites, and colorectal cancer. Nat Rev Microbiol 12, 661–672 (2014).
[5] Vos, W. M. de & Vos, E. A. de. Role of the intestinal microbiome in health and disease: from correlation to causation. Nutr Rev 70, S45–S56 (2012).
[6] Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature 570, 462–467 (2019).
[7] Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Separating host and microbiome contributions to drug pharmacokinetics and toxicity. Science 363, eaat9931 (2019).
[8] Chijiiwa, R. et al. Single-cell genomics of uncultured bacteria reveals dietary fiber responders in the mouse gut microbiota. Microbiome 8, (2020).
[9] Lan, F., Demaree, B., Ahmed, N. & Abate, A. R. Single-cell genome sequencing at ultra-high-throughput with microfluidic droplet barcoding. Nat Biotechnol 35, 640–646 (2017).
[10] Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 25, 1043–1055 (2015).
doi: https://doi.org/10.1242/prelights.29645
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