Co-cultivation of microbial sub-communities in microfluidic droplets facilitates high-resolution genomic dissection of microbial 'dark matter'

Abstract

While the 'unculturable' majority of the bacterial world is accessible with culture-independent tools, the inability to study these bacteria using culture-dependent approaches has severely limited our understanding of their ecological roles and interactions. To circumvent cultivation barriers, we utilize microfluidic droplets as localized, nanoliter-size bioreactors to co-cultivate subsets of microbial communities. This co-localization can support ecological interactions between a reduced number of encapsulated cells. We demonstrated the utility of this approach in the encapsulation and co-cultivation of droplet sub-communities from a fecal sample collected from a healthy human subject. With the whole genome amplification and metagenomic shotgun sequencing of co-cultivated sub-communities from 22 droplets, we observed that this approach provides accessibility to uncharacterized gut commensals for study. The recovery of metagenome-assembled genomes from one droplet sub-community demonstrated the capability to dissect the sub-communities with high-genomic resolution. In particular, genomic characterization of one novel member of the family Neisseriaceae revealed implications regarding its participation in fatty acid degradation and production of atherogenic intermediates in the human gut. The demonstrated genomic resolution and accessibility to the microbial 'dark matter' with this methodology can be applied to study the interactions of rare or previously uncultivated members of microbial communities.

Keywords: co-cultivation; human gut; metagenomics; microbial communities; microbiome; microdroplet; microfluidics.

Figure 1

Overview of the microfluidic droplet cultivation and processing pipeline. (a) A microbial suspension derived from a human fecal sample is prepared. (b) Using biphasic flows of aqueous and oil phases, random combinations of bacteria are encapsulated in microdroplets at frequencies according to a Poisson distribution. (c) These droplets are incubated anaerobically for a week to allow for co-cultivation of the subcommunities. (d) With a droplet spacing device, microdroplets are isolated and processed individually. (e) Upon droplet destabilization, cells released from individual droplets are lysed and their genomes are amplified with MDA to generate sufficient nucleic acid material for downstream sequencing. (f) 16S amplicon and metagenomic libraries are prepared with amplified DNA and sequenced. 16S profiling of individual droplets is used to determine which droplet to submit for metagenomic shotgun sequencing.

Figure 2

Microbial sub-communities in generated microfluidic droplets before and after co-cultivation. A sample pool of droplets with encapsulated microbial sub-communities before (a, c) and after anaerobic cultivation for a week (b, d). Droplets were cultivated in two rich media: BHI (a, b) and Schadler media (SM) (c, d). Droplets are not tracked over time, so each droplet viewed is distinct. Dashed boxes on the left correspond to the magnified droplets in each subpanel on the right, identified by the numerical marker. Arrows distinguish single cells in the pre-incubation microfluidic droplet. Scale bar is 100 microns.

Figure 3

16S OTU profiles of 22 isolated droplets sub-communities. OTU classification and bootstrap values are provided. Droplet identity nomenclature is based on Schaedler media (S) or BHI media (B) and with the initial λ value [2 or 10] and a numerical identifier. Because MDA introduced significant bias, quantitative information is not shown and OTUs are presented as either present (black) or absent (light gray) in a sample. Hierarchical clustering of the droplet taxonomic profiles provides two distinct clusters. P-values provided by pvclust in R do not signify statistical significance (AU < 95%).

Figure 4

Phylogenetic and metabolic description of a novel member Neisseriaceae observed in droplet B2–2. (a) Phylogenetic tree comparing conserved protein sequences between the recovered genome with other Betaproteobacteria genomes from IMG. (b) Metabolic reconstruction of the most distinctive pathways.