Long-term social dynamics drive loss of function in pathogenic bacteria

Abstract

Laboratory experiments show that social interactions between bacterial cells can drive evolutionary change at the population level, but significant challenges limit attempts to assess the relevance of these findings to natural populations, where selection pressures are unknown. We have increasingly sophisticated methods for monitoring phenotypic and genotypic dynamics in bacteria causing infectious disease, but in contrast, we lack evidence-based adaptive explanations for those changes. Evolutionary change during infection is often interpreted as host adaptation, but this assumption neglects to consider social dynamics shown to drive evolutionary change in vitro. We provide evidence to show that long-term behavioral dynamics observed in a pathogen are driven by selection to outcompete neighboring conspecific cells through social interactions. We find that Pseudomonas aeruginosa bacteria, causing lung infections in patients with cystic fibrosis, lose cooperative iron acquisition by siderophore production during infection. This loss could be caused by changes in iron availability in the lung, but surprisingly, we find that cells retain the ability to take up siderophores produced by conspecifics, even after they have lost the ability to synthesize siderophores. Only when cooperative producers are lost from the population is the receptor for uptake lost. This finding highlights the potential pitfalls of interpreting loss of function in pathogenic bacterial populations as evidence for trait redundancy in the host environment. More generally, we provide an example of how sequence analysis can be used to generate testable hypotheses about selection driving long-term phenotypic changes of pathogenic bacteria in situ.

Keywords: cheating; cooperation; cystic fibrosis; infection; social evolution.

Fig. 1.

The pyoverdine system. (Upper) The pyoverdine receptor FpvA spans the cell wall. In the absence of bound pyoverdine, the anti-σ factor FpvR inhibits the expression of σ-factors FpvI and PvdS. Pyoverdine acquires iron from transferrin. When ferripyoverdine binds to the receptor, FpvR releases FpvI and PvdS. Release of FpvI initiates synthesis of the receptor FpvA, and PvdS initiates synthesis of pyoverdine (illustrated by arrows). (Lower Left) If pyoverdine production is lost as an adaptation to the lung, receptor function also becomes redundant, irrespective of whether pyoverdine produced by neighbors is available. (Lower Right) However, if pyoverdine production is lost because of cheating, we expect to see retention of receptor function in the presence of pyoverdine produced by others and function only lost in the absence of pyoverdine.

Fig. S1.

Pyoverdine production measured as RFUs standardized by OD significantly decreases with length of infection in years. Isolates come from 36 different patients who were longitudinally sampled, covering 54 different clone types and three types of pyoverdine that fluoresce at different strengths. Each dot represents the pyoverdine production of one isolate (n = 451). The line represents the average decrease in pyoverdine production controlling for patient identity and pyoverdine type.

Fig. S2.

Pyoverdine production over the length of infection in years for individual patients (measured as RFUs standardized by OD). Length of infection is given as the time between sampling of an isolate and the first recording of Pseudomonas aeruginosa from the patient, irrespective of whether this isolate was included in the collection (except for patient P36F2, who, after an initial sampling of P. aeruginosa, tested negative for >10 y; therefore, only the later isolates are included). Patients who harbor isolates that do not produce pyoverdine are marked with stars. Colors represent different clone types.

Fig. S3.

Distribution of pyoverdine-producing and -nonproducing isolates over the length of infection in years. The bars show the numbers of isolates (left y axis) cumulated for 6 mo. The distribution of pyoverdine producers (green; n = 397) is left-skewed, in part because some young patients have been followed for fewer years and in part because clone types isolated for the first time in a patient were recorded as from 0 y of infection, irrespective of other clone types harbored by the patient (Materials and Methods). Nonproducing isolates (blue; n = 54) are more evenly distributed over time. The line shows that the proportion of nonproducers to producers (right y axis), therefore, increases over time. Because of low counts for the last years (seven isolates), samples from 6 to 8 y have been cumulated.

Fig. 2.

Distribution of mutations across the pyoverdine genes given as the ratio of observed to expected numbers of nonsynonymous SNPs and indels. Colors follow those used in Fig. 1, and other genes involved in production are light green. There were significantly more mutations than expected by random distribution in the genes pvdS and fpvA and significantly fewer mutations in the large gene pvdL (marked by an asterisk; a value of one indicates no difference). *P < 0.05.

Fig. 3.

Distribution of receptor mutations supports a social adaptation scenario. (A) Presence of receptor mutations predicts function. Nonproducing isolates were grown with and without the addition of pyoverdine. Isolates without mutations (n = 16 lines of 15 clone types) showed greater induction of growth compared with those with mutations (n = 7 lines of 5 clone types; P < 0.05). Box plots of the difference in OD₆₀₀ with and without pyoverdine. The middle band represents the median, the bottom and top boxes represent the 25th and 75th percentiles, respectively, and the lower and upper whiskers represent the 5th and 95th percentiles, respectively. (B) The number of observed mutations in genes affecting receptor synthesis is higher than expected in the absence of pyoverdine producers (colors follow those in Fig. 1) but not in the presence of pyoverdine producers (green bars), shown as mutations observed per mutations expected. *P < 0.05 for fpvR and fpvA. (C) Loss of receptor function is dependent on the social environment. Kaplan–Meier graph showing that the probability of acquiring receptor mutations is significantly higher when cheating on pyoverdine producers is not possible (blue line; n = 6) compared with when it is (green line; n = 4). Ticks show when the samples were censored.

Fig. 4.

Receptor mutations found in the fpvA IIA receptor gene mapped onto the predicted transmembrane β-barrel of FpvA IIA. The β-sheets are represented by gray boxes, and the loops are represented by black lines. The extracellular loops are numbered L1–L11. Yellow stars indicate one nonsynonymous SNP or indel, orange stars represent two nonsynonymous SNPs or indels, and a red star represents four events. In L8, five adjacent amino acids were found to be altered by mutations (one of these amino acids four times, twice in both the DK1 and DK2 clonetype).