Oscillatory dynamics in a bacterial cross-protection mutualism.

Cooperation between microbes can enable microbial communities to survive in harsh environments. Enzymatic deactivation of antibiotics, a common mechanism of antibiotic resistance in bacteria, is a cooperative behavior that can allow resistant cells to protect sensitive cells from antibiotics. Understanding how bacterial populations survive antibiotic exposure is important both clinically and ecologically, yet the implications of cooperative antibiotic deactivation on the population and evolutionary dynamics remain poorly understood, particularly in the presence of more than one antibiotic. Here, we show that two Escherichia coli strains can form an effective cross-protection mutualism, protecting each other in the presence of two antibiotics (ampicillin and chloramphenicol) so that the coculture can survive in antibiotic concentrations that inhibit growth of either strain alone. Moreover, we find that daily dilutions of the coculture lead to large oscillations in the relative abundance of the two strains, with the ratio of abundances varying by nearly four orders of magnitude over the course of the 3-day period of the oscillation. At modest antibiotic concentrations, the mutualistic behavior enables long-term survival of the oscillating populations; however, at higher antibiotic concentrations, the oscillations destabilize the population, eventually leading to collapse. The two strains form a successful cross-protection mutualism without a period of coevolution, suggesting that similar mutualisms may arise during antibiotic treatment and in natural environments such as the soil.

Highly-resolved within-species dynamics in the human facial skin microbiome.

Human facial skin microbiomes (FSMs) on adults are dominated by just two bacterial species, Cutibacterium acnes and Staphylococcus epidermidis. Underlying this apparent simplicity, each FSM harbors multiple strains of both species whose assembly dynamics on individuals are unknown. Here, we use 4,055 isolate genomes and 360 metagenomes to trace the dynamics of strains on individuals and their transmission. Strains are shared amongst family members of all ages, but each individual harbors unique strain consortia. Strain stability changes upon formation of the adult-type FSM: S. epidermidis lineage turnover slows, and the rate of C. acnes colonization increases before stabilizing, suggesting this transitional window could facilitate engraftment of therapeutic strains. Our work reveals previously undetectable community dynamics and informs the design of therapeutic interventions.

Anatomy promotes neutral coexistence of strains in the human skin microbiome.

What enables strains of the same species to coexist in a microbiome? Here, we investigate whether host anatomy can explain strain co-residence of Cutibacterium acnes, the most abundant species on human skin. We reconstruct on-person evolution and migration using whole-genome sequencing of C. acnes colonies acquired from healthy subjects, including from individual skin pores, and find considerable spatial structure at the level of pores. Although lineages (sets of colonies separated by <100 mutations) with in vitro fitness differences coexist within centimeter-scale regions, each pore is dominated by a single lineage. Moreover, colonies from a pore typically have identical genomes. An absence of adaptive signatures suggests a genotype-independent source of low within-pore diversity. We therefore propose that pore anatomy imposes random single-cell bottlenecks; the resulting population fragmentation reduces competition and promotes coexistence. Our findings suggest that therapeutic interventions involving pore-dwelling species might focus on removing resident populations over optimizing probiotic fitness.

Rapid, Inexpensive Measurement of Synthetic Bacterial Community Composition by Sanger Sequencing of Amplicon Mixtures.

Synthetic bacterial communities are powerful tools for studying microbial ecology and evolution, as they enable rapid iteration between controlled laboratory experiments and theoretical modeling. However, their utility is hampered by the lack of fast, inexpensive, and accurate methods for quantifying bacterial community composition. Although next-generation amplicon sequencing can be very accurate, high costs (>$30 per sample) and turnaround times (>1 month) limit the nature and pace of experiments. Here, we quantify amplicon composition in synthetic bacterial communities through Sanger sequencing. We PCR amplify a universal marker gene, then we sequence this amplicon mixture in a single Sanger sequencing reaction. We then fit the "mixed" electropherogram with contributions from each community member as a linear combination of time-warped single-strain electropherograms, allowing us to estimate the fractional amplicon abundance of each strain within the community. This approach can provide results within one day and costs ∼$5 per sample.

Publisher Correction: Migration alters oscillatory dynamics and promotes survival in connected bacterial populations.

In the original version of this Article, an additional double-headed arrow was inadvertently included within Fig. 3e. This error has been corrected in both the PDF and HTML versions of the Article.

Migration alters oscillatory dynamics and promotes survival in connected bacterial populations.

Migration influences population dynamics on networks, thereby playing a vital role in scenarios ranging from species extinction to epidemic propagation. While low migration rates prevent local populations from becoming extinct, high migration rates enhance the risk of global extinction by synchronizing the dynamics of connected populations. Here, we investigate this trade-off using two mutualistic strains of E. coli that exhibit population oscillations when co-cultured. In experiments, as well as in simulations using a mechanistic model, we observe that high migration rates lead to synchronization whereas intermediate migration rates perturb the oscillations and change their period. Further, our simulations predict, and experiments show, that connected populations subjected to more challenging antibiotic concentrations have the highest probability of survival at intermediate migration rates. Finally, we identify altered population dynamics, rather than recolonization, as the primary cause of extended survival.