Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections

Abstract

Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. microbiology | systems biology | antibiotics | infection

A rare opportunist,Morganella morganii, decreases severity of polymicrobial catheter-associated urinary tract infection

“…Furthermore, there are increasing reports of isolates producing extended-spectrum β-lactamases (ESBL) and carbapenemases (25–29), which threatens the utility of last-resort antibiotics and increases the mortality rate for P. mirabilis infection (30–32). P. mirabilis also acts as a “hub” species in catheterized nursing home residents, promoting colonization by additional multidrug resistance organisms (33) and providing protection from antibiotic treatment (34). Furthermore, P. mirabilis produces a potent urease enzyme that hydrolyzes the urea in urine to carbon dioxide and ammonia, thereby increasing urine pH and facilitating the precipitation of polyvalent ions and resulting in struvite crystals, catheter encrustation, blockage, and formation of urinary stones (urolithiasis) (35–37).…”

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a synthetic gut community

“…Mono-and bi-cultures are increasingly carried out in batch in a high-throughput fashion to determine ecological interactions and to quantify their strengths (de Vos et al, 2017, Sher, Thompson et al, 2011. Such systematic quantification is an important step forward, but there are challenges to tackle.…”

“…Since Gause's early work on competition between yeast and Paramecium species (Gause, 1932, Gause, 1934, growth rates in mono-and bi-culture experiments have been compared to determine ecological interactions (e.g. (de Vos, Zagorski et al, 2017, Freilich, Zarecki et al, 2011, Wang, Wei et al, 2017). The rationale is that growth rates in bi-culture should increase for mutualistic organisms as compared to mono-culture growth rates, whereas bi-culture growth rates should decrease for competitors.…”

Building clone-consistent ecosystem models

“…In particular for microbial ecosystems, recent advances in automatising experiments have made it feasible to determine interaction parameters for richer ecosystems [15, 17–19], to quantify the interaction between two populations with more than one parameter [15], or to measure higher-order interactions [14, 20]. These new experimental scenarios often demand new models that can incorporate the respective data, in particular as there is no single answer as to how multiparameter or higher-order interactions should be measured [2, 6, 15, 18, 21].…”

“…This difference cannot be explained by numerical noise and sensitivity to initial conditions, as demonstrated by simulations with perturbed initial conditions (dotted lines) exhibiting a much smaller difference. This model was taken from a study [15] that featured communities containing two strains of the same species; therefore the case of populations with very similar properties is relevant here.…”