Guex, I. | bioRxiv Science

bioRxiv2024

Inferring Bacterial Interspecific Interactions from Microcolony Growth Expansion

Interactions between species are thought to be crucial for modulating their growth and behaviour within communities, and determinant for the emergence of community functions. Several different interaction concepts exist, but there is no consensus on how interactions should be quantified and integrated in community growth theory. Here we expand on existing concepts of real-time measurements of pure culture microcolony growth to develop and benchmark coculture microcolony experiments, and show how these can both parametrize growth kinetic and interspecific interaction effects. We follow surface growth by time-lapse microscopy of fluorescently tagged Pseudomonas putida and Pseudomonas veronii under substrate competition with succinate, or under substrate indifference with D-mannitol and putrescine. Monoculture-grown microcolonies showed substrate concentration dependent expansion rates as expected from Monod relations, whereas individual microcolony yields were strongly dependent on densities and spatial positioning of founder cells. Maximum specific growth rates in cocultures under substrate competition were diminished by ca. 15%, which was seeding-density independent. The collective P. putida population dominated growth over that of P. veronii, but with 27% yield loss under competition compared to monoculture growth; and 90% for that of P. veronii. Incidental local reversal of competition was observed where P. veronii microcolonies profited at the detriment of P. putida, and between 9 and 43% of P. veronii microcolonies grew bigger than expected from bulk competition, depending on seeding density. Simulations with a cell-agent Monod surface growth model suggested that colony expansion rate decrease in competitive coculture is caused by metabolite cross-feeding, which was supported by exometabolite analysis during and after growth of the strains on their individual or swapped supernatant. Coculture microcolony growth experiments thus provide a flexible platform for analysis of kinetic and interspecific interactions, expanding from individual microcolony phenotypic effects to averaged behaviour across all microcolony pairs. The system in theory is scalable to follow real-time growth of multiple species simultaneously into communities.

microbiology↗

bioRxiv2024

Fragmented micro-growth habitats present opportunities for alternative competitive outcomes

Bacteria in nature often proliferate in highly patchy environments, such as soil pores, particles, plant roots or leaves. The resulting spatial fragmentation leads to cells being constrained to smaller habitats, shared with potentially fewer other species. The effects of microhabitats on the emergence of bacterial interspecific interactions are poorly understood, but potentially important for the maintenance of diversity at a larger scale. To study this more in-depth, we contrasted paired species-growth in picoliter droplets at low population census with that in large (macro) population liquid suspended cultures. Four interaction scenarios were imposed by using different bacterial strain combinations and media: substrate competition, substrate independence, growth inhibition, and cell killing by tailocins. In contrast to macro-level culturing, we observed that fragmented growth in picoliter droplets in all cases yielded more variable outcomes, and even reversing the macro-level assumed interaction type in a small proportion of droplet habitats. Timelapse imaging and mathematical simulations indicated that the variable and alternative interaction outcomes are a consequence of founder cell phenotypic variation and small founder population sizes. Simulations further suggested that increased growth kinetic variation may be a crucial selectable property for slower-growing bacterial species to survive competition. Our results thus demonstrate how microhabitat fragmentation enables the proliferation of alternative interaction trajectories and contributes to the maintenance of higher species diversity under substrate competition.

microbiology↗

bioRxiv2023

Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding

When bacterial species with the same resource preferences share the same growth environment, it is commonly believed that direct competition will arise. A large variety of competition and more general interaction models have been formulated, but what is currently lacking are models that link mono-culture growth kinetics and community growth under inclusion of emerging biological interactions, such as metabolite cross-feeding. In order to understand and mathematically describe the nature of potential cross-feeding interactions, we design experiments where two bacterial species Pseudomonas putida and Pseudomonas veronii grow in liquid medium either in mono- or as co-culture in a resource-limited environment. We measure population growth under single substrate competition or with double species-specific substrates (substrate indifference), and starting from varying cell ratios of either species. Using experimental data as input, we first consider a mean-field model of resource-based competition, which captures well the empirically observed growth rates for mono-cultures, but fails to correctly predict growth rates in co-culture mixtures, in particular for skewed starting species ratios. Based on this, we extend the model by cross-feeding interactions where the consumption of substrate by one consumer produces metabolites that in turn are resources for the other consumer, thus leading to positive feedback loops in the species system. Two different cross-feeding options were considered, which either lead to constant metabolite cross-feeding, or to a regulated form, where metabolite utilization is activated with rates according to either a threshold or a Hill function, dependent on metabolite concentration. Both mathematical proof and experimental data indicate regulated cross-feeding to be the preferred model over constant metabolite utilization, with best co-culture growth predictions in case of high Hill coefficients, close to binary (on/off) activation states. This suggests that species use the appearing metabolite concentrations only when they are becoming high enough; possibly as a consequence of their lower energetic content than the primary substrate. Metabolite sharing was particularly relevant at unbalanced starting cell ratios, causing the minority partner to proliferate more than expected from the competitive substrate because of metabolite release from the majority partner. This effect thus likely quells immediate substrate competition and may be important in natural communities with typical very skewed relative taxa abundances and slower-growing taxa. In conclusion, the regulated bacterial interaction network correctly describes species substrate growth reactions in mixtures with few kinetic parameters that can be obtained from mono-culture growth experiments. 1 Author summaryCorrectly predicting growth of communities of diverse bacterial taxa remains a challenge, because of the very different growth properties of individual members and their myriads of interactions that can influence growth. Here we tried to improve and empirically validate mathematical models that combine theory of bacterial growth kinetics (i.e., Monod models) with mathematical definition of interaction parameters. We focused in particular on common cases of shared primary substrates (i.e., competition) and independent substrates (i.e., indifference) in an experimental system consisting of one fast-growing and one slower growing Pseudomonas species. Growth kinetic parameters derived from mono-culture experiments included in a Monod-type consumer-resource model explained some 75% of biomass formation of either species in co-culture, but underestimated the observed growth improvement when either of the species started as a minority compared to the other. This suggested an in important role of cross-feeding, whereby released metabolites from one of the partners is utilized by the other. Inclusion of cross-feeding feedback in the two-species Monod growth model largely explained empirical data at all species-starting ratios, in particular when cross-feeding is activated in almost binary manner as a function of metabolite concentration. Our results also indicate the importance of cross-feeding for minority taxa, which can explain their survival despite being poorly competitive.

microbiology↗