Positive interactions are common among culturable bacteria

Abstract

Interspecies interactions shape the structure and function of microbial communities. In particular, positive, growth-promoting interactions can substantially affect the diversity and productivity of natural and engineered communities. However, the prevalence of positive interactions and the conditions in which they occur are not well understood. To address this knowledge gap, we used kChip, an ultrahigh-throughput coculture platform, to measure 180,408 interactions among 20 soil bacteria across 40 carbon environments. We find that positive interactions, often described to be rare, occur commonly and primarily as parasitisms between strains that differ in their carbon consumption profiles. Notably, nongrowing strains are almost always promoted by strongly growing strains (85%), suggesting a simple positive interaction–mediated approach for cultivation, microbiome engineering, and microbial consortium design.

Fig. 1.. High-throughput interaction assay and analysis.

(A) Steps to assay the effect of multiple unlabeled species on a single-label species across carbon sources on each kChip. Color-coded droplets, each containing either a labeled + unlabeled coculture or a single carbon source, were generated (step 1), pooled together (step 2), and loaded onto a kChip (step 3). Each kChip contained an array of microwells that randomly paired coculture droplets with carbon source droplets. After imaging the color codes to identify the inputs per microwell, droplet pairs were merged via exposure to an electric field (step 4), and the growth of the labeled strain was measured at 0, 24, and 72 hours (step 5). (B) Overall size of the kChip screen. (C) Using data across kChips, bidirectional interactions were deduced by combining data where each strain within a given pair was the labeled strain. (D to F) Framework for kChip data analysis. Each bidirectional interaction was described qualitatively (interaction classification) and quantitatively (interaction strength, m; interaction type, ϴ).

Fig. 2.. Positive interactions occurred commonly and depended on strain pair and carbon source.

(A) Left: All bidirectional interactions on 33 distinct carbon sources. Middle: Interaction classification of all data. The inner circle represents one-way interaction classifications; the outer ring represents two-way interaction classifications. Right: Interaction classification excluding cases in which both strains comprising a coculture showed no detectable growth as monocultures on a given carbon source. (B and C) Interactions of two example cocultures on all carbon sources. PAr, Pseudomonas arsenicoxydans; PR1, Pseudomonas rhodesiae #1; SF, Serratia fonticola. (D and E) Interactions of all cocultures on two example carbon sources. Colors indicate interaction classification (legend). All data are at 72 hours.

Fig. 3.. Positive interactions depended strongly on strain properties.

(A) Interaction classification by carbon source organized into biochemical categories. Bar colors indicate interaction classification (legends are provided in Fig. 2A). (B) Average interaction type by number of carbon atoms. The dot color indicates the biochemical class. (C) Interaction classification by phylogenetic relatedness of the taxonomic pairs. En, Enterobacterales. Ps, Pseudomonadales. (D) Interaction type by phylogenetic relatedness of the taxonomic pairs, averaged across all carbon sources. (E) Interaction classification by pairwise Euclidean metabolic distance (binned). Bin 0 represents with self-interactions. Bins 1 to 8 each contain roughly equal numbers of bidirectional interactions. (F) Interaction type by metabolic distance. All data are at 72 hours.

Fig. 4.. Carbon source utilization capabilities shape interactions.

(A) Example interaction networks for two carbon sources, each with different subsets of strains that could use it. The size of the circular nodes represents each strain’s growth in monoculture (normalized to each strain’s maximum monoculture yield across all carbon sources). Edge color represents interaction classification. Edge thickness represents interaction strength (m) (B) Interaction types (color) by the monoculture yields of both strains in each coculture. Gray lines indicate monoculture growth bins. (C) Interaction classification for each pair of monoculture growth bins. (D) Fractions of nongrowers that are obligately facilitated by strains with different monoculture yields. Line colors represent the interaction classifications in which the facilitation occurs (Mut., mutualism; Comm., commensalism; Para., parasitism; Total, total fraction of nongrowers facilitated). (E) The total number of carbon sources on which each strain can grow in monoculture and in at least one coculture. Each line represents one strain. All data are at 72 hours.