Privatisation rescues function following loss of ...

bioRxiv preprint first posted online May. 22, 2018; doi: http://dx.doi.org/10.1101/326165. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.

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Privatisation rescues function following loss of cooperation

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Authors: Sandra B. Andersen1*F, Melanie Ghoul1, Rasmus L. Marvig2†, Zhuo-Bin Lee1, Søren

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Molin2, Helle Krogh Johansen3,4 & Ashleigh S. Griffin1*

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Affiliations:

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1: Department of Zoology, University of Oxford, Oxford, United Kingdom.

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2: Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark,

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Lyngby, Denmark.

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3: Department of Clinical Microbiology, Rigshospitalet, Copenhagen, Denmark.

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4: Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of

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Copenhagen, Denmark

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Correspondence to:

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Sandra B. Andersen

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[email protected]

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Ashleigh S. Griffin

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[email protected]

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F Current address: Langone Medical Center, New York University, New York, USA

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† Current address: Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark.

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Abstract

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A single cheating mutant can lead to the invasion and eventual eradication of cooperation from a

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population. Consequently, cheat invasion is often considered as “game over” in empirical and

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theoretical studies of cooperator-cheat dynamics, especially when cooperation is necessary for

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fulfilling an essential function. But is cheat invasion necessarily “game over” in nature? By

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following a population of bacteria through loss of cooperation and beyond, we observed that

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individuals evolved to replace cooperation with a selfish, or “private” behaviour. Specifically, we

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show that when cheating caused the loss of cooperative iron acquisition in a collection of

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Pseudomonas aeruginosa isolates from cystic fibrosis patients, a private uptake system that only

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benefits the focal individual was upregulated. This observation highlights the importance of social

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dynamics of natural populations and emphasizes the potential impact of past social interaction on

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the evolution of private traits.

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Introduction

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evolutionary biology (Axelrod & Hamilton, 1981; Hamilton, 1963). We can predict in which

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conditions cooperation will thrive, and where it might pay to exploit cooperative neighbours.

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Evidence of tension between cooperative and cheating strategies are all around us in nature – for

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example, the co-evolution between flowers and their pollinators , the policing and counter-policing

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behaviours of social insects (Foster & Ratnieks, 2000) – and in human society (Mathew & Boyd,

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2011; Rand et al., 2011). Cases where these dynamics have resulted in the loss of cooperation are

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much less well understood, primarily because long-term consequences of cheat invasions are

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unobserved and unreported (Sachs & Simms, 2006). This is for the obvious reason that it is

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inherently difficult to detect a history of something that no longer exists. And also because it is

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generally the case that once cheating has gone to fixation, it is almost impossible for cooperation to

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re-invade (Axelrod & Hamilton, 1981). The cheats won. End of story.

Identifying mechanisms responsible for the maintenance of cooperation is a major achievement of

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Life, however, goes on. Consider a population where cheating has gone to fixation. If cooperation

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fulfilled an important function, this population may now be at risk of extinction (Fiegna & Velicer,

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2003). To escape this fate, selection may favour individuals that can restore function by employing

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a “privatisation” strategy – replacement of a mechanism that was once performed cooperatively as a

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group, with a selfish one that only benefits the actor (Bel, 2006). As such, we use the term

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privatisation as it is normally understood in common language to describe a switch in strategy from

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one that helps a whole group to achieve a goal to one where a goal is achieved by the actor alone.

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This differs from its use for describing the acquisition of property for future benefit by a group or

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an individual (Strassmann & Queller, 2014), the retention of public goods for individual use (Asfahl

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& Schuster, 2017), and for when public goods only are useable to a part of a community (Niehus et

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al., 2017). Privatisation could be a common occurrence in nature that has nevertheless been

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overlooked because there is no reason, a priori, to interpret private function as a result of past social

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interaction. It may also have been missed for the practical reason that we are required to track

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behaviour over many generations post-cheat invasion in a natural population. We overcome these

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difficulties by studying the evolutionary dynamics of a cooperative trait for more than an estimated

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20 million generations (Table S1), in a population of bacterial cells. We report the first observation

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(to our knowledge) of a natural population responding to cheat invasion by adopting a privatisation

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strategy and, therefore, avoiding the possibility of extinction.

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Our study population is comprised of Pseudomonas aeruginosa bacteria causing lung infection in

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patients with cystic fibrosis (CF). CF is a genetic disease that causes the build-up of dehydrated 3


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mucus in lungs and sinuses, which P. aeruginosa infects (Folkesson et al., 2012). The host actively

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withholds iron to limit infection, and, as a counter-measure, P. aeruginosa employ a range of

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different iron acquisition strategies (Poole & McKay, 2003). The primary mechanism relies on

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secretion of the siderophore pyoverdine (Andersen et al., 2015; Haas et al., 1991; Konings et al.,

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2013). This has been demonstrated to be a cooperative trait, where iron-bound pyoverdine

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molecules are available for uptake not only by the producer, but also by neighbouring cells

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(Buckling et al., 2007; West & Buckling, 2003). P. aeruginosa also make a secondary siderophore,

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pyochelin, which is cheaper to produce but has a lower affinity for iron (Dumas et al., 2013). In

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contrast, the Pseudomonas heme uptake system (phu) is private, as the iron-rich compound heme is

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taken up directly without the secretion of exploitable exoproducts (Table 1). Additional

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mechanisms of uptake include the private ferrous iron transport system (feo; Table 1 (Cartron et al.,

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2006)), and the heme assimilation system (has). The has system produces a hemophore that can

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bind to heme, or hemoglobin that contains heme. In the closely related system of Serratia

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marcescens it is conditionally cooperative, as uptake is direct without the hemophore at high

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concentrations (Ghigo et al., 1997; Létoffé et al., 2004).

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P. aeruginosa iron metabolism evolves during long term infection. Pyoverdine production has

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repeatedly been found to be lost during CF infection (Jeukens et al., 2014; Konings et al., 2013;

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Martin et al., 2011), and the phu system has been observed to be upregulated late in infection

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(Marvig et al., 2014; Nguyen et al., 2014). A major challenge is to identify the selective pressures

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experienced in situ that cause such changes. Host adaptation, to accommodate e.g. antibiotic

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pressure and resource limitations, is frequently predicted to be the primary force in pathogen

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evolution (Lieberman et al., 2011; Young et al., 2012). Experimentally recreating host conditions in

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vitro is challenging, given the complex interplay between spatial structure, host immunity and

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nutrient availability (Clevers et al., 2016), which we are only beginning to be able to measure (Koo

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et al., 2011). Clinical measurements may differ from experimental in vivo and in vitro findings

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(Cornforth et al., 2018), and studies using “simple” experimental conditions do not always give

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comparable results to those that use more complex, and potentially more clinically relevant

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conditions (Harrison et al., 2017). In contrast, longitudinal sampling of patients to track in situ

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evolution provides an opportunity to infer selection without making a priori assumptions about the

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experienced environment. Evolutionary theory lets us make testable predictions to distinguish the

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effect of host adaptations and social interactions. With this approach we have shown that cheating is

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a major selective force in the loss of cooperative iron acquisition in the CF lung (Andersen et al.,

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2015).

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Here, we identified changes in iron uptake strategies from genome sequences and correlated these

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with the social environment (the P. aeruginosa clonal lineage infecting a host), and duration of

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infection. The isolate collection covers 546 whole genome sequenced isolates from 61 Danish

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patients, of 55 clone types (Andersen et al., 2015; Markussen et al., 2014; Marvig et al., 2013,

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2015); allowing for the identification of patterns of convergent evolution. While the P. aeruginosa

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populations within patients are remarkably uniform at the clone type level, colonizers diversify

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during infection (Mowat et al., 2011; Winstanley et al., 2016), and lineages may occupy distinct

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niches at late stages (Jorth et al., 2015). The isolate collection has been shown to represent the

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genetic diversity well, with multiple genotypes co-occurring within individual patient samples

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(Sommer et al., 2016). A key step in our analysis is to categorise isolates with respect to their social

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environment, for example, presence vs absence of cooperators (pyoverdine producers). This is

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necessary for testing our hypotheses that iron acquisition strategy is influenced by the social

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environment. While it is likely that we do not capture all co-infecting strains in our sample, the

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effect of mis-classifying isolates will homogenise the sample groups and hence obscure rather than

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amplify any differences, reducing our ability to detect an effect.

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Table 1: Main iron uptake systems of P. aeruginosa. The pyoverdine and pyochelin systems produce

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siderophores which can steal Fe3+ from host carriers. The conditionally cooperative has system

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produces a hemophore that can bind to heme, or hemoglobin that contains heme. The phu and feo

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systems are private. All systems have a specific receptor and uptake feeds back to increase system

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expression. The illustration shows a receptor in the cell membrane taking up an iron source (star).

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In a cooperative system a secreted public good (circle) binds the target and is taken up by the

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receptor, whereas a private system takes up the iron source directly.

137 SYSTEM

MECHANISM

SOCIAL STATUS

TARGET

Pyoverdine

Public good; siderophore and specific receptor

Cooperative

Fe3+, host-bound

Pyochelin

Public good; siderophore and specific receptor

Cooperative

Fe3+, host-bound

has

Public good; hemophore and specific receptor

Conditionally cooperative or private

Heme, hemoglobin

phu

Specific receptor

Private

Heme, hemoglobin

feo

Specific receptor

Private

Fe2+

ILLUSTRATION

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Results and Discussion

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More cooperative populations are more vulnerable to exploitation

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The environmental clones that infect CF patients produce pyoverdine (Andersen et al., 2015) but

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what happens as they transition to life in a host? We compared pyoverdine production between

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strains isolated from different time points of infection in iron-limited media, in which cells must

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produce pyoverdine to avoid iron starvation. In some clonal lineages of P. aeruginosa, pyoverdine

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production was maintained for >30 years of CF infection: e.g. of the eight clonal lineages of the

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transmissible clone type DK1 were followed for >30 years; four maintained pyoverdine production

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(Andersen et al., 2015 and below). Limited diffusion of secreted pyoverdine, as is likely in viscous

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CF sputum, impairs the ability of potential cheats to exploit and may contribute to stabilize

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cooperation in these lineages (Julou et al., 2013; Kümmerli, Griffin, et al., 2009); although there

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may be significant exchange between spatially distinct microcolonies (Weigert & Kümmerli, 2017).

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We found that pyoverdine production increased in 33% of clonal lineages within the first two years

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of infection. Overall, these “super-cooperator” isolates, which had > 30% higher production than

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isolates initiating infection, were detected in 24 of 45 independent clonal lineages (53%; Fig. 1),

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and on average sampled 1.86 years into the infection. This suggests that upregulation is initially

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favoured, likely by iron limitation or inter-species competition. In CF patients, P. aeruginosa

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frequently co-infects with Staphylococcus aureus (Folkesson et al., 2012), and co-culture in vitro

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causes an upregulation of pyoverdine production (Harrison et al., 2008). When in co-infection, iron

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sequestering can have the additional benefit of making it unavailable for S. aureus or other

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competitors (Leinweber et al., 2018; Niehus et al., 2017). Increased production could also be part of

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a general acute infection phenotype (Coggan & Wolfgang, 2012). For six out of the 24 lineages

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with super-cooperators we identified candidate mutations in global regulatory and quorum sensing

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genes that likely cause increased production of pyoverdine as well as other virulence factors, such

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as pyochelin, pyocyanin and alginate (Table S2). For the remainder, super-cooperators produced

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pyoverdine at a consistently higher rate than their ancestors but the genetic basis of upregulation

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was unclear.

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Despite the potential benefits of pyoverdine production, the presence of super-cooperators appears

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to weaken long-term stability of cooperation in the lung. In 12 out of 35 patients, we previously

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observed the appearance of mutants that have lost the ability to synthesise pyoverdine (Andersen et

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al., 2015), sampled on average 2.97 years after infection. Here, we found that the likelihood of these 6


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non-producers arising was significantly higher in the presence of super-cooperators [c2 (2, N = 47)

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= 5.7; p < 0.05; fig. 1]. Non-producers were present in four out of 21 clonal lineages without (19%)

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and in eight out of 24 lineages with super-cooperators (33%).

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Why is upregulation of pyoverdine production associated with the subsequent loss of this trait?

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Non-producers appear to be favoured as a result of exploiting the pyoverdine production of

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neighbouring cells – a strategy referred to as cheating (Ghoul et al., 2013). We have previously

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shown that non-producers in the lung acquire mutations in a pattern consistent with a cheating

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strategy, as opposed to one expected from redundancy, in that they retained the pyoverdine receptor

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only if producers were present (Andersen et al., 2015). In other words, non-producers lose the

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capacity to contribute but retain the ability to benefit from pyoverdine, as long as it is being

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supplied by cooperative neighbours. The relative fitness of cheats is predicted by theory to be

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greater when there are higher levels of cooperation in a population, because their competitors are

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bearing a higher cost (Ross-Gillespie et al., 2007); and this prediction has been shown to hold in

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empirical tests (Ghoul et al., 2014; Harrison et al., 2008; Jiricny et al., 2010). Hence, super-

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cooperators are predicted to be especially vulnerable to exploitation and invasion of cheats. The

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pattern of upregulation, followed by loss, is likely to be applicable to the evolution of other

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exoproducts during infection.

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Figure 1. Kaplan-Meier graph showing that pyoverdine non-producers are found more often in the

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presence of super-cooperators (dotted line, n = 25 representing 24 clonal lineages in patients, one

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of which had two independent losses of pyoverdine production), compared to when super-

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cooperators are absent (solid line, n = 22, representing 21 clonal lineages in patients, one of which

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had two independent losses). Circles indicate when sampling of clonal lineages stopped, without

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the observation of lost pyoverdine production. Insert shows that a transition from wild-type (WT)

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production to super-cooperation (pvd+) was observed in 24 clonal lineages, followed by nine

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independent occurrences of non-producers. Non-producers evolved in the absence of super-

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cooperators five times. In total, 33 clone types infecting 35 patients were followed.

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7

1.0


0.8

9 24 WT

pvd-

0.4

0.6

5

0.2

Presence of non-producers

pvd+

Super-cooperators present

0.0

Super-cooperators absent

0

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1

2

3

4

5

6

7

Years of infection

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Evolution of iron acquisition systems in the lung – the sequence of events

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How do the changes in cooperative pyoverdine production relate to the overall iron metabolism of

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the cells? Comparison of the accumulation of mutations across five different systems (Table 1)

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showed that loss of pyoverdine production is the first change in iron metabolism observed in most

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clonal lineages. When weighed by the high mutation rate of the system, reflecting a strong selection

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pressure, and its large size, this is not unexpected [P(X ≥ 16) ∼ pois (X; 14.69) > 0.05), fig. 2, table

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S3, SI text]. We observe cheats appear 14 times without going to fixation during the sampling

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period, but further record nine cases where no producers are sampled a year prior to, or after

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emergence a non-producer. One of these is in a transmitted clone type that is subsequently sampled

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from 16 patients over 35 years. This is the “game over” scenario of cheat invasion. However,

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because we have continued to sample after this event, we can observe how the population responds

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to this potentially catastrophic situation. And because cheat invasion is not inevitable, we can

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compare dynamics in lungs with and without availability of pyoverdine.

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Cheat invasion is associated with a subsequent switch to private iron uptake mechanism

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After cooperation was lost, and only if it was lost, we observed that iron uptake was privatised (Fig.

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3). This was achieved by upregulation of the private phu system. The phu system targets the iron-

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rich heme molecule, which is taken up directly through a membrane-bound receptor (Table 1)

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(Ochsner et al., 2000). Increased expression of the phu system results from intergenic mutations

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between the phuS gene encoding a heme traffic protein, and the receptor gene phuR (phuS//phuR

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mutations; Marvig et al., 2014). In the isolate collection, a total of 29 SNPs and two indels

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accumulate in the phuS//phuR region. Eight of these mutations in the phuR promoter have been

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found to cause a significant upregulation of promoter activity, and one of these has further been

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shown, in an isogenic pair, to provide a growth benefit to the carrier when heme is available as an

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iron source (Marvig et al., 2014) (see also below and fig. S1). These specific mutations were found

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to occur significantly more frequently than expected by chance following the loss of pyoverdine

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production [P(X ≥ 5) ∼ pois (X; 0.39) < 0.01); fig. 2]. In three patients, non-producing isolates with

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phuS//phuR mutations were found to co-occur with pyoverdine producers, however in two of these

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the producer and non-producers were unlikely to interact (SI text).

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Figure 2: Order of mutations across iron acquisition systems.

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Wild type-like (WT) isolates colonize patients, and subsequent loss of cooperative pyoverdine

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production (pvd-) is the most common change in iron metabolism (n = 25), compared to mutations

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expected to affect the pyochelin, phu and has systems negatively (pch-, phu-, has-). Loss of

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pyoverdine production is followed by intergenic phuS//phuR mutations, predicted to upregulate the

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private phu system, significantly more often than expected by chance (phu+, n = 9). Colour

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indicates iron uptake system (green = pyoverdine, yellow = pyochelin, dark red= intergenic

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phuS//phuR, orange = phu (either a mix of phuS//phuR and other phu mutations, or only ns SNPs),

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blue = has). The occurrence of has mutations may be underestimated due to low sequencing depth

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of two genes. The figure shows only transitions where there was a clear order in which systems

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were affected, see table S3 for all transitions.

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Figure bioRxiv 2 preprint first posted online May. 22, 2018; doi: http://dx.doi.org/10.1101/326165. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.

pch-

pch-

phu-

24%

22%

WT

pvd-

phu+

64% 4% phu-

11%

8% has-

56%

pvd-

has-

11% phu-

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Social interactions are unlikely to be the only selection pressure influencing dynamics in iron

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acquisition strategies. Changes in iron uptake strategy might more readily be expected to reflect

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changes in the lung environment as the availability of iron in different forms increases with disease

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progression (Hunter et al., 2013). And while iron is found to be equally available in its oxidized

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ferric (Fe3+) and reduced ferrous forms (Fe2+) in early infection, there is a slight skew towards the

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reduced form later, which the feo system targets (Hunter et al., 2013). Heme and hemoglobin are

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also present in the sputum (Ghio et al., 2013), and availability has been speculated to increase as the

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lung tissue degrades (Marvig et al., 2014), as evidenced by increased coughing up of blood, termed

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hemoptysis, with age (Thompson et al., 2015). As such, pyoverdine may be most efficient early in

267

infection, and phu only advantageous later as lung tissue degrades and/or alternative sources of iron

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become more or less abundant. However, the patterns we observe are not consistent with this

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explanation. If pyoverdine production is maintained, the phu genotype remains unaltered from

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colonization, even after 35 years of infection. The phuS//phuR mutations, responsible for

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upregulating the private phu system, are only observed in non-producers [c2 (2, N = 64) = 12.1; p
1 and < 5 µM heme) but detrimental at high concentrations (> 5 µM heme). If iron

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availability increases during infection, an initially beneficial upregulation of heme uptake would

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turn toxic. In the phu system we found a significant bias towards mutations of the phu receptor gene

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phuR (P(X ≥ 24) ∼ pois (X; 10.69) < 0.05; table S5, SI). These were not randomly distributed but

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primarily found in the extracellular loops of the phu receptor, that initiate the uptake of heme

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(Noinaj et al., 2010; Smith et al., 2015)[P(X ³ 15) ~ pois (X; 7.28) < 0.05; fig. S2]. If there is

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selection to reduce iron concentration within cells, these may, therefore, represent compensatory

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mutations.

327 328

Figure 5: Effect of phu upregulation depends on the heme concentration. An isogenic pair of

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isolates differing only in a 1 bp phuS//phuR deletion was grown in iron-limited media supplemented

330

with heme at 1-10 µM. The clinical isolate without the mutation, that does not produce pyoverdine

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(WT), had a significant higher maximum OD600 after 48 h growth at 5 and 10 µM, whereas the

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mutant (phu+) grew best at 2.5 µM. There was no significant difference at 1 µM. Boxplots show

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median value, and the interquartile range ± 25%. The * marks a significant difference at p < 0.05.

334

13

0.5

*

*

*

0.2

0.3

0.4

n.s.

0.0

0.1

Max OD600 after 48 h growth

0.6


WT

phu+

1 μM heme

WT

phu+

2.5 μM heme

WT

phu+

5 μM heme

WT

phu+

10 μM heme

Heme concentration

335 336 337 338

Conclusions

339 340

Bacterial cells will be under selection to adapt to the host environment, including antibiotic pressure

341

(Lieberman et al., 2011). The observations we report here, however, demonstrate the errors of

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interpretation that can arise from assuming that bacterial cells are driven entirely by the

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evolutionary imperative to survive in the host. As in all other organisms, fitness is also determined

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by the ability to compete with members of the same species, and these two evolutionary drivers –

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survival and competition – do not always coincide. The effect of the social environment on iron

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acquisition mechanism remains statistically detectable despite the noise from variation in patient

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age, sex, infection and treatment. In a clinical system like this, failure to appreciate these factors can

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lead to misinterpretation of how bacterial cells are influenced by the host environment and,

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therefore, impair necessary understanding for the development of intervention strategies (Leggett et

350

al., 2014).

351 352

Evolutionary theory clearly predicts that any adaptation involving cooperation can be vulnerable to

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exploitation, irrespective of its benefits (Axelrod & Hamilton, 1981). But this is often overlooked

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when it is difficult to characterize the selective environment, as for example, inside a human host. 14


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By longitudinal sampling of bacterial populations, we were able to observe the consequences of

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cheat invasion for an essential trait and show that switching to a private strategy can provide

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bacterial cells with an evolutionary “escape route”. This observation highlights the importance of

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considering potential constraints imposed by social interactions: if a private trait is expressed it may

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not be the most efficient in a given environment, but simply the “last resort” in a population with a

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history of exploitation.

361 362 363

Acknowledgements

364 365

We thank Stuart West, Lars Jelsbak and Rolf Kümmerli for comments on the manuscript. Trine

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Markussen and Lars Jelsbak provided analysed sequences of additional DK1 isolates, and Hossein

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Khademi provided valuable discussion of the phu mutations. This work was supported by grants

368

from Villum Fonden (grant 95-300-13894) and Lundbeckfonden (grant R108-2012-10094) to SBA,

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the European Research Council (grant SESE) to ASG, and Rigshospitalet (grant R88-A3537), Novo

370

Nordisk Fonden (grant NNF12OC1015920) and Lundbeckfonden (grant R167-2013-15229) to

371

HKJ.

372 373 374

Author contributions

375 376

SBA & ASG designed the study, SBA & RLM analysed the data, MG & ZBL performed the

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experimental work, HKJ and SM acquired the isolates and all related information. All authors

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contributed to the interpretation of the data, the writing of the manuscript, and approved the final

379

version.

380 381 382

Ethics statement

383 384

The CF isolates used for sequencing were obtained from the Department of Clinical Microbiology,

385

Rigshospitalet, Copenhagen, where they had been isolated from CF patients treated at the

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Copenhagen CF clinic. The use of isolates was approved by the local ethics committee at the

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Capital Region of Denmark Region Hovedstaden: registration number H-1-2013-032. All patients

15


388

have given informed consent. In patients under 18 years of age, informed consent was obtained

389

from their parents. All patient isolates were anonymized prior to any experimental use or analysis.

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Frangipani, E., Visaggio, D., Heeb, S., Kaever, V., Cámara, M., Visca, P., & Imperi, F. (2014). The Gac/Rsm and cyclic-di-GMP signalling networks coordinately regulate iron uptake in Pseudomonas aeruginosa. Environmental Microbiology, 16(3), 676–688. https://doi.org/10.1111/1462-2920.12164 Ghigo, J., Letoffe, S., & Wandersman, C. (1997). A new type of hemophore-dependent heme acquisition system of Serratia marcescens reconstituted in Escherichia coli. J. Bacteriol., 179(11), 3572–3579. Ghio, A. J., Roggli, V. L., Soukup, J. M., Richards, J. H., Randell, S. H., & Muhlebach, M. S. (2013). Iron accumulates in the lavage and explanted lungs of cystic fibrosis patients. Journal of Cystic Fibrosis : Official Journal of the European Cystic Fibrosis Society, 12(4), 390–398. https://doi.org/10.1016/j.jcf.2012.10.010 Ghoul, M., Griffin, A. S., & West, S. A. (2013). Toward an evolutionary definition of cheating. Evolution, 68, 318–331. https://doi.org/10.1111/evo.12266 Ghoul, M., West, S. A., Diggle, S. P., & Griffin, A. S. (2014). An experimental test of whether cheating is context dependent. Journal of Evolutionary Biology, 27(3), 551–556. https://doi.org/10.1111/jeb.12319 Haas, B., Kraut, J., Marks, J., Zanker, S. C., & Castignetti, D. (1991). Siderophore presence in sputa of cystic fibrosis patients. Infection and Immunity, 59(11), 3997–4000. Hamilton, W. D. (1963). The evolution of altruistic behavior. The American Naturalist, 97(896), 354–356. Harrison, F., McNally, A., da Silva, A. C., Heeb, S., & Diggle, S. P. (2017). Optimised chronic infection models demonstrate that siderophore ‘cheating’ in Pseudomonas aeruginosa is context specific. The ISME Journal, 11(11), 2492–2509. https://doi.org/10.1038/ismej.2017.103 Harrison, F., Paul, J., Massey, R. C., & Buckling, A. (2008). Interspecific competition and siderophore-mediated cooperation in Pseudomonas aeruginosa. The ISME Journal, 2(1), 49– 55. https://doi.org/10.1038/ismej.2007.96 Hunter, R. C., Asfour, F., … Newman, D. K. (2013). Ferrous iron is a significant component of bioavailable iron in cystic fibrosis airways. MBio, 4, e00557-13-. https://doi.org/10.1128/mBio.00557-13 Jelsbak, L., Johansen, H. K., … Molin, S. (2007). Molecular epidemiology and dynamics of Pseudomonas aeruginosa populations in lungs of cystic fibrosis patients. Infection and Immunity, 75(5), 2214–2224. https://doi.org/10.1128/IAI.01282-06 Jeukens, J., Boyle, B., … Levesque, R. C. (2014). Comparative genomics of isolates of a Pseudomonas aeruginosa epidemic strain associated with chronic lung infections of cystic fibrosis patients. PloS One, 9(2), e87611. https://doi.org/10.1371/journal.pone.0087611 Jiricny, N., Diggle, S. P., West, S. A., Evans, B. A., Ballantyne, G., Ross-Gillespie, A., & Griffin, A. S. (2010). Fitness correlates with the extent of cheating in a bacterium. Journal of Evolutionary Biology, 23(4), 738–747. https://doi.org/10.1111/j.1420-9101.2010.01939.x Jorth, P., Staudinger, B. J., … Singh, P. K. (2015). Regional isolation drives bacterial diversification within cystic fibrosis lungs. Cell Host & Microbe, 18(3), 307–319. https://doi.org/10.1016/j.chom.2015.07.006 Julou, T., Mora, T., Guillon, L., Croquette, V., Schalk, I. J., Bensimon, D., & Desprat, N. (2013). Cell-cell contacts confine public goods diffusion inside Pseudomonas aeruginosa clonal microcolonies. Proceedings of the National Academy of Sciences, 110(31), 12577–12582. https://doi.org/10.1073/pnas.1301428110 Konings, A. F., Martin, L. W., Sharples, K. J., Roddam, L. F., Latham, R., Reid, D. W., & Lamont, I. L. (2013). Pseudomonas aeruginosa uses multiple pathways to acquire iron during chronic infection in cystic fibrosis lungs. Infection and Immunity, 81(8), 2697–2704. https://doi.org/10.1128/IAI.00418-13 Koo, H., Huh, M. S., … Kwon, I. C. (2011). Nanoprobes for biomedical imaging in living systems. Nano Today, 6(2), 204–220. https://doi.org/10.1016/J.NANTOD.2011.02.007 17


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Kümmerli, R., Griffin, A., West, S., Buckling, A., & Harrison, F. (2009). Viscous medium promotes cooperation in the pathogenic bacterium Pseudomonas aeruginosa. Proceedings. Biological Sciences, 276(1672), 3531–3538. https://doi.org/10.1098/rspb.2009.0861 Kümmerli, R., Jiricny, N., Clarke, L. S., West, S. A., & Griffin, A. S. (2009). Phenotypic plasticity of a cooperative behaviour in bacteria. Journal of Evolutionary Biology, 22(3), 589–598. https://doi.org/10.1111/j.1420-9101.2008.01666.x Leggett, H. C., Brown, S. P., & Reece, S. E. (2014). War and peace: social interactions in infections. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 369(1642), 20130365. https://doi.org/10.1098/rstb.2013.0365 Leinweber, A., Weigert, M., & Kümmerli, R. (2018). The bacterium Pseudomonas aeruginosa senses and gradually responds to inter-specific competition for iron. Evolution. https://doi.org/10.1111/evo.13491 Létoffé, S., Delepelaire, P., & Wandersman, C. (2004). Free and hemophore-bound heme acquisitions through the outer membrane receptor HasR have different requirements for the TonB-ExbB-ExbD complex. Journal of Bacteriology, 186(13), 4067–4074. https://doi.org/10.1128/JB.186.13.4067-4074.2004 Lieberman, T. D., Michel, J.-B., … Kishony, R. (2011). Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes. Nature Genetics, 43(12), 1275–1280. https://doi.org/10.1038/ng.997 Markussen, T., Marvig, R. L., … Jelsbak, L. (2014). Environmental heterogeneity drives withinhost diversification and evolution of Pseudomonas aeruginosa. MBio, 5(5), e01592-14. https://doi.org/10.1128/mBio.01592-14 Martin, L. W., Reid, D. W., Sharples, K. J., & Lamont, I. L. (2011). Pseudomonas siderophores in the sputum of patients with cystic fibrosis. Biometals : An International Journal on the Role of Metal Ions in Biology, Biochemistry, and Medicine, 24(6), 1059–1067. https://doi.org/10.1007/s10534-011-9464-z Marvig, R. L., Damkiær, S., Khademi, S. M. H., Markussen, T. M., Molin, S., & Jelsbak, L. (2014). Within-host evolution of Pseudomonas aeruginosa reveals adaptation toward iron acquisition from hemoglobin. MBio, 5(3), e00966-14. https://doi.org/10.1128/mBio.00966-14 Marvig, R. L., Johansen, H. K., Molin, S., & Jelsbak, L. (2013). Genome analysis of a transmissible lineage of Pseudomonas aeruginosa reveals pathoadaptive mutations and distinct evolutionary paths of hypermutators. PLoS Genetics, 9(9), e1003741. https://doi.org/10.1371/journal.pgen.1003741 Marvig, R. L., Sommer, L. M., Molin, S., & Johansen, H. K. (2015). Convergent evolution and adaptation of Pseudomonas aeruginosa within patients with cystic fibrosis. Nature Genetics, 47, 57–64. https://doi.org/10.1038/ng.3148 Mathew, S., & Boyd, R. (2011). Punishment sustains large-scale cooperation in prestate warfare. Proceedings of the National Academy of Sciences of the United States of America, 108(28), 11375–11380. https://doi.org/10.1073/pnas.1105604108 Mowat, E., Paterson, S., … Winstanley, C. (2011). Pseudomonas aeruginosa population diversity and turnover in cystic fibrosis chronic infections. American Journal of Respiratory and Critical Care Medicine, 183(12), 1674–1679. https://doi.org/10.1164/rccm.201009-1430OC Nguyen, A. T., O’Neill, M. J., Watts, A. M., Robson, C. L., Lamont, I. L., Wilks, A., & OglesbySherrouse, A. G. (2014). Adaptation of iron homeostasis pathways by a Pseudomonas aeruginosa pyoverdine mutant in the cystic fibrosis lung. Journal of Bacteriology, 196(12), 2265–2276. https://doi.org/10.1128/JB.01491-14 Niehus, R., Picot, A., Oliveira, N. M., Mitri, S., & Foster, K. R. (2017). The evolution of siderophore production as a competitive trait. Evolution. https://doi.org/10.1111/evo.13230 Noinaj, N., Guillier, M., Barnard, T. J., & Buchanan, S. K. (2010). TonB-dependent transporters: regulation, structure, and function. Annual Review of Microbiology, 64, 43–60. https://doi.org/10.1146/annurev.micro.112408.134247 Ochsner, U. A., Johnson, Z., & Vasil, M. L. (2000). Genetics and regulation of two distinct haem18


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uptake systems, phu and has, in Pseudomonas aeruginosa. Microbiology (Reading, England), 146 ( Pt 1(1), 185–198. https://doi.org/10.1099/00221287-146-1-185 Ochsner, U. A., Wilderman, P. J., Vasil, A. I., & Vasil, M. L. (2002). GeneChip® expression analysis of the iron starvation response in Pseudomonas aeruginosa: identification of novel pyoverdine biosynthesis genes. Molecular Microbiology, 45(5), 1277–1287. https://doi.org/10.1046/j.1365-2958.2002.03084.x Poole, K., & McKay, G. A. (2003). Iron acquisition and its control in Pseudomonas aeruginosa: many roads lead to Rome. Frontiers in Bioscience a Journal and Virtual Library, 8, d661– d686. R Core Team. (2013). R: A language and environment for statistical computing. Rand, D. G., Arbesman, S., & Christakis, N. A. (2011). Dynamic social networks promote cooperation in experiments with humans. Proceedings of the National Academy of Sciences, 108(48), 19193–19198. https://doi.org/10.1073/pnas.1108243108 Ross-Gillespie, A., Gardner, A., West, S. A., & Griffin, A. S. (2007). Frequency dependence and cooperation: theory and a test with bacteria. The American Naturalist, 170(3), 331–342. https://doi.org/10.1086/519860 Sachs, J. L., & Simms, E. L. (2006). Pathways to mutualism breakdown. Trends in Ecology & Evolution, 21(10), 585–592. https://doi.org/10.1016/j.tree.2006.06.018 Smith, A. D., Modi, A. R., Sun, S., Dawson, J. H., & Wilks, A. (2015). Spectroscopic determination of distinct heme ligands in outer-membrane receptors PhuR and HasR of Pseudomonas aeruginosa. Biochemistry, 54(16), 2601–2612. https://doi.org/10.1021/acs.biochem.5b00017 Sommer, L. M., Marvig, R. L., Lujan, A., Koza, A., Pressler, T., Molin, S., & Johansen, H. K. (2016). Is genotyping of single isolates sufficient for population structure analysis of Pseudomonas aeruginosa in cystic fibrosis airways? BMC Genomics, 17, 589. https://doi.org/10.1186/s12864-016-2873-1 Stintzi, A., Evans, K., Meyer, J., & Poole, K. (1998). Quorum-sensing and siderophore biosynthesis in Pseudomonas aeruginosa: lasRllasI mutants exhibit reduced pyoverdine biosynthesis. FEMS Microbiology Letters, 166(2), 341–345. https://doi.org/10.1111/j.15746968.1998.tb13910.x Stover, C. K., Pham, X. Q., … Olson, M. V. (2000). Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature, 406(6799), 959–964. https://doi.org/10.1038/35023079 Strassmann, J. E., & Queller, D. C. (2014). Privatization and property in biology. Animal Behaviour, 92, 305–311. https://doi.org/10.1016/J.ANBEHAV.2014.02.011 Therneau, T. (2015). A Package for Survival Analysis in S. Retrieved from http://cran.rproject.org/package=survival Thompson, V., Mayer-Hamblett, N., Kloster, M., Bilton, D., & Flume, P. A. (2015). Risk of hemoptysis in cystic fibrosis clinical trials: A retrospective cohort study. Journal of Cystic Fibrosis, 14(5), 632–638. https://doi.org/10.1016/J.JCF.2015.02.003 Touati, D. (2000). Iron and oxidative stress in bacteria. Archives of Biochemistry and Biophysics, 373(1), 1–6. https://doi.org/10.1006/ABBI.1999.1518 Vasil, M. L., & Ochsner, U. A. (1999). The response of Pseudomonas aeruginosa to iron: genetics, biochemistry and virulence. Molecular Microbiology, 34(3), 399–413. https://doi.org/10.1046/j.1365-2958.1999.01586.x Visaggio, D., Pasqua, M., Bonchi, C., Kaever, V., Visca, P., & Imperi, F. (2015). Cell aggregation promotes pyoverdine-dependent iron uptake and virulence in Pseudomonas aeruginosa. Frontiers in Microbiology, 6, 902. https://doi.org/10.3389/fmicb.2015.00902 Weigert, M., & Kümmerli, R. (2017). The physical boundaries of public goods cooperation between surface-attached bacterial cells. Proceedings. Biological Sciences, 284(1858), 20170631. https://doi.org/10.1098/rspb.2017.0631 West, S. A., & Buckling, A. (2003). Cooperation, virulence and siderophore production in bacterial parasites. Proceedings. Biological Sciences / The Royal Society, 270(1510), 37–44. 19


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20


609

Methods

610 611

Isolate collections

612

Two collections of whole genome sequenced P. aeruginosa isolates were used, as described

613

previously (Andersen et al., 2015). Of the transmissible clonetypes DK1 and DK2, 95 isolates from

614

25 CF patients were sampled between 1973 and 2012. (Jelsbak et al., 2007; Markussen et al., 2014;

615

Yang et al., 2011) An additional 10 DK1 isolates were included compared to Andersen et al.

616

(2015). Further, 451 isolates of 54 clonetypes from 36 young CF patients were used (the “children’s

617

collection” (Andersen et al., 2015; Marvig et al., 2015), of which 10 were of the DK1 clone type).

618

The sampling regime for each patient is described in Table S6. The two collections complement

619

each other as the first covers a long time period, with relatively few samples from each patient and

620

of both early and long-term infection stages, whilst the second covers the first 10 years of infection

621

with more extensive sampling within patients.

622 623

The length of infection of each clone type in each patient was calculated. Clone types sampled only

624

once from a patient were excluded. For the transmissible clone types DK1 and DK2 the total length

625

of infection across patients was used (39 and 35 years, respectively). This is a very conservative

626

estimate of length of infection, as evolution occurs independently in different patients. To calculate

627

the number of generations, a doubling time of 50 min. was used for clonal lineages infecting for less

628

than 10 years, and for the DK1 and DK2 isolates a doubling time of 65 min. based on the

629

measurements of Yang et al. (2011) (Table S1).

630 631

Changes in pyoverdine production during infection

632

We tested if loss of pyoverdine production is correlated with preceding upregulation. Measurement

633

of pyoverdine production was carried out by fluorescence readings at 400/460 nm

634

excitation/emission with a 475 nm cut-off following growth in iron-limited media (Andersen et al.,

635

2015; Kümmerli, Jiricny, et al., 2009). For each clonal lineage the baseline pyoverdine production

636

was determined as that of the first isolate(s) of a clone type from a patient, and the production of all

637

subsequent isolates of this clone type was compared to this. An isolate was classified as an over-

638

producer if its production was > 30% higher than that of the first. This cut-off was chosen as ~95%

639

of the isolates had a lower standard deviation between replicates. Loss of pyoverdine production

640

was defined as sampling of a non-producing isolate from a clonal lineage that produced pyoverdine

641

at the beginning of the infection period. The analysis was performed on longitudinally sampled

642

clone types from the children’s collection only, as the DK1 and DK2 isolates were not sampled

643

frequently within patients. In all but three cases, over-producers were sampled before non21


644

producers. In two cases there was < 5 months between sampling, and we scored non-producers as

645

occurring at the same time as overproducers. In one case the non-producer was sampled 2.95 years

646

prior to the over-producer and scored as having occurred in the absence of an over-producer. In two

647

clone types two independent transitions to non-producers were observed and these were included as

648

independent events.

649 650

We categorized each clone type in individual patients as harbouring over-producers or not. If an

651

over-producer was present, the length of time to a non-producer was observed, or till the last sample

652

was collected from the patient, was noted. Clone types without non-producers were classified as

653

right-censored. The same was done for patients without over-producers. In total, 45 clonal lineages

654

were followed (some clone types occur in multiple patients, and some patients are infected by

655

multiple clone types (Marvig et al., 2015)). Clone types DK1, DK11, DK40 and DK53 were

656

excluded from the analysis, as they were “chronic” clone types with no pyoverdine producers

657

sampled (Andersen et al., 2015). The timing of sampling of non-producers was analysed with the

658

“survival” package in R (R Core Team, 2013; Therneau, 2015).

659 660 661

Identification of mutations in the pyoverdine, pyochelin, phu, has and feo systems

662

Mutations in the pyoverdine (pvdQ-pvdI + pvdS-pvdG + pvcA-ptxR + fpvB), the pyochelin (ampP-

663

pchA), the phu (prrF1-phuR), the has (PA3404-hasI) and the feo operons (PA4357-feoA) were

664

identified previously from Illumina GAIIx or HiSeq2000 reads (Andersen et al., 2015; Markussen

665

et al., 2014; Marvig et al., 2013, 2015; Yang et al., 2011) (Table S5, S7). Mutations of iron systems

666

in the 10 new DK1 isolates were identified as described previously (Andersen et al., 2015).

667

Mapping of reads revealed low sequencing depth of the hasD (required for hemophore secretion)

668

and hasS (the has anti-sigma factor) genes, likely due to repetitive regions. These were

669

unsuccessfully attempted amplified by PCR. Mutations were categorized as synonymous (syn) or

670

non-synonymous (ns) SNPs, insertions or deletions (indels), or intergenic. We tested for a bias in

671

which genes in each operon were mutated with [P(X ≥ changes observed) ~ Poisson distribution (pois)

672

(X; changes expected) < 0.05].

673 674

We identified the order of mutation across the different systems, with a system classified as mutated

675

by the presence of ns SNPs or indels in any gene in the system. For pyoverdine, the presence of

676

mutations was compared to the actual measurements of production; the two measures are highly

677

consistent (Andersen et al., 2015) but when incongruent the phenotype was used. For the phu region

678

intergenic phuS//phuR mutations predicted to cause receptor upregulation were included, and when 22


679

occurring alone these were recorded separately. We calculated the expected order of mutation,

680

equally weighted by the size and number of mutations of the different systems. We tested, as

681

described above, whether this was different from the observed, using only cases where there is a

682

clear order of mutations (Fig. S1).

683 684

For the phu system, we located mutations in the phuR receptor gene to functional regions (the N-

685

terminal-domain, periplasmic turns, transmembrane strands or extracellular loops) using a predicted

686

structure of the receptor (http://bioinformatics.biol.uoa.gr//PRED-TMBB (Bagos et al., 2004)). For

687

each domain in the receptor we calculated the expected number of non-synonymous amino acid

688

changes, as the proportion the domain comprises of the entire protein times the observed number of

689

changes. Whether the observed changes in each domain differed significantly from the expected

690

was calculated as described above.

691 692 693

Transitions between public and private iron uptake

694 695

To test if the appearance of intergenic phuS//phuR mutations was correlated with loss of pyoverdine

696

production we categorized each independent acquisition of these mutations as having occurred in

697

the presence or absence of measured pyoverdine production. In the absence of pyoverdine

698

production the time between loss of production and occurrence of mutations was estimated. The

699

analysis was performed on longitudinally sampled clonal lineages from both collections of isolates,

700

that is lineages with at least two isolates with or without pyoverdine production. Further, three cases

701

where the loss of pyoverdine production and phuS//phuR mutations were observed in the same

702

isolate were also included. Clonal lineages that did not acquire phuS//phuR mutations were

703

classified as right-censored. For DK1 and DK2 we used monophyletic clades with and without

704

mutations as independent clonal lineages. We included isolates of DK53 where no WT pyoverdine

705

producer was sampled, but phuS//phuR mutations were inferred by comparison to PA01 (Table S5).

706

The timing of sampling of mutants was analysed with the “survival” package in R (Therneau,

707

2015). We are likely to over-estimate the length of time to mutation, as patients chronically infected

708

with the transmissible DK1 and DK2 clone types were infrequently sampled (Markussen et al.,

709

2014; Marvig et al., 2013). In these cases, with several years between longitudinal samples, a

710

mutation may only be detected years after occurring.

711 712 713

Uptake of heme following phuS//phuR mutations 23


714 715

We tested if clinical isolates with phuS//phuR mutations have a growth advantage in iron-limited

716

media supplemented with heme, when matched to their closest genetically related isolate without

717

mutations. The phuS//phuR mutations occurred in three different clone types without additional phu

718

mutations (DK1, DK2 and DK32, highlighted in yellow in Table S5). The six isolates with

719

mutations were matched with four close relatives without, because DK2 in two instances had

720

independent phuS//phuR mutations in two closely related isolates. One additional DK2 isolate with

721

a mutation was lost from the collection, and only available as sequence reads (P80F1, table S5). As

722

a positive control we included an isogenic pair of DK2, only differing in the presence of a 1 bp

723

phuS//phuR deletion (Marvig et al., 2014). This pair represents the WT isolate used in two of the

724

clinical pairs, and the mutation of one of the clinical isolates moved to this background (P0M30-

725

1979 and P173-2005; Fig. S2). Three biological replicates of each isolate were cultured in liquid LB

726

media for 24-48 h, so that all cultures reached an OD600 above 0.1. Cultures were subsequently

727

standardised to a starting OD600 of 0.001, in iron-limited CAA media following Kümmerli, Jiricny,

728

et al. (2009), without heme or supplemented with 2.5 or 5 µM heme as an iron source (BioXtra

729

porcine hemin ≥ 97.0%, Sigma-Aldrich). Of each culture 200 µL were inoculated in 96 well plates.

730

Plates were sealed with a breathable membrane to avoid evaporation and incubated in a plate reader

731

measuring OD600 every 30 min for 48h. Growth curves were plotted in Excel and the average

732

maximum OD600 of the three replicates calculated. The difference in max OD600 for a pair of related

733

isolates with and without phuS//phuR mutations was analysed with a t-test in R (R Core Team,

734

2013). The isogenic control pair was also grown supplemented with 1 and 10 µM heme, and the

735

differences in max OD600 were compared in R with a Two-Way ANOVA test with post hoc

736

comparisons with Tukey HSD.

737 738 739 740 741 742 743 744 745 746 747 748 24


749

Supplementary Information

750 751

Supplementary text

752 753

Order of mutations across iron uptake systems

754

Loss-of-function of the cooperative pyoverdine system occurred earliest in 16 out of 25 clonal

755

lineages where the sequence analysis provided a clear order of systems affected (Fig. 2; table S3).

756

These were observed to occur on average 3.21 years after the first sampling of the clone type in the

757

young patients (n = 11 clonal lineages in nine patients), and between 0-39 years after infection for

758

the more rarely sampled transmissible clone types (n = 5 clonal lineages in five patients). Mutation

759

of the pyochelin system first was found not to differ from that expected given a random distribution

760

of mutations [P(X ≥ 6) ∼ pois (X; 5.14) > 0.05), fig. 2; table S3].

761 762

The conditionally private or cooperative has heme uptake system was found to acquire few

763

mutations during infection. It remains to be tested if this is because maintenance of the system is

764

favoured by selection, or if selection for loss is relatively weak. The private feo system is rarely

765

mutated (Table S3) and has been suggested to be of increased importance as conditions turn

766

microanaerobic during infection (Hunter et al., 2013).

767 768

Co-occurrence of isolates with phuS//phuR mutations and pyoverdine producers

769

The phuS//phuR mutations only occurred in isolates that had lost pyoverdine production. In three

770

instances these, however, co-occurred in the patient with isolates that produced pyoverdine. The

771

producers and non-producers with phu upregulation are unlikely to have interacted at the time when

772

the iron metabolism mutations occurred in two of these. In patient P30M0, infected with clone type

773

DK1, the cooperating isolates were sampled from the patient’s sinuses only, while the non-

774

producers with phu upregulation came from lung samples. In patient P28F1, two lineages of clone

775

type DK1 co-occurred. One had been transmitted from another patient, where pyoverdine

776

production was lost, and phu likely upregulated, prior to transmission and establishment of a co-

777

infection. In both cases the non-producers carried mutations in the pyoverdine receptor. In patient

778

P83M2 a pyoverdine producer and an isolate with a phuS//phuR mutation, both of clone type DK32,

779

were found in the same lung sample. The latter harbours the most common phuS//phuR mutation (G

780

146 upstream//35 upstream A, table S5), which is located outside the phuR promoter (Marvig et al.,

781

2014). It is the only isolate to have this phuS//phuR mutation in isolation, all others with it have an

782

additional SNP, and the effect of it is unknown (but see below).

783 25


784

Effect of phuS//phuR mutations in clinical isolates

785

A range of the clinical phuS//phuR mutations have been shown to cause increased promoter activity,

786

increased expression of the phuR gene and a growth benefit in iron-limited media supplemented

787

with heme (Marvig et al., 2014; Yang et al., 2011). We tested if the phuS//phuR mutations are also

788

beneficial in the clinical isolates, using six isolates of three different clone types that had acquired a

789

variety of phuS//phuR mutations, and no additional phu mutations (Table S5). We compared fitness

790

of the mutants with their closest genetically related isolate without phuS//phuR mutations, to control

791

for phylogenetic differences. The isolates in a pair were, however, separated by multiple other

792

mutations as they were sampled up to 26 years apart. The pairs were grown in iron-limited media

793

with 2.5 and 5 µM heme added, which corresponds to medium concentrations observed in CF

794

patients (Ghio et al., 2013). Three mutants with intergenic SNPs had significantly higher (P73F1;

795

26% higher; t = -6.33, df = 3.48, p > 0.01 and P83M2; 16% higher, t = -4.48, df = 2.15, p < 0.05;

796

isolates sampled 0 and 23 years apart) or a tendency towards a higher maximum OD600 in 5 µM

797

heme compared to their closest relative (P66F0; 17% higher, t = -2.85, df = 2.67, p = 0.07; isolates

798

sampled 10 years apart; fig. S2). A mutant with a three bp insertion, and an isolate with a one base

799

pair deletion in phuS//phuR in addition to a SNP, showed no significant difference in growth

800

compared to their closest relative (17% higher, t = -1.78, df = 2.95, p = 0.18; 16% lower, t = - 0.55,

801

df = 2.56, p = 0.10; isolates sampled 3 and 26 years apart; fig. S2). These two isolates have,

802

however, previously been shown to have respectively 25 and 116 fold increased expression of the

803

phu receptor compared to the wild type (Marvig et al., 2014; Yang et al., 2011), and transfer of the

804

one base pair deletion to its ancestor confirms that it infers growth benefits in heme media (Marvig

805

et al., 2014) (fig. 4). This suggest that other mutations across the genome affect the phenotype we

806

are interested in, which is not unexpected given that we are comparing isolates sampled years apart,

807

and the complex genome of P. aeruginosa where almost 10% of the genes are predicted to be

808

regulatory (Stover et al., 2000). There were no significant growth differences with 2.5 µM heme

809

added. Both isolates of the sixth pair, with a SNP, grew very slowly in rich LB media, and not at all

810

in iron-limited media with or without heme. Caution is generally required when interpreting results

811

of behavioural assays in the lab as evidence of the phenotype in situ, as growth conditions are

812

difficult to replicate in vitro. However, this data provides confirmation that the mutations we

813

observe in the lung isolates upregulate the phu iron uptake pathway in vitro.

814 815 816 817 818 26


819

Supplementary figures

820 821

Figure S1: Growth effect of phuS//phuR mutations in clinical isolates.

822

Isolates with phuS//phuR mutations were grown in iron-limited media supplemented with 5 µM

823

heme for 48 h and compared with their closest relative (WT). Two isolates with mutations had a

824

significantly higher maximum OD600 than their closest WT relative, and one showed a trend. Pairs

825

where the same WT isolate is used because of two independent acquisitions of phuS//phuR

826

mutations are highlighted in red and blue. Boxplots show median value, and the interquartile range

827

± 25%. * marks a significant difference.

828

Supplementary Figure 1

830

0.6 0.5 0.4 0.3 0.2 0.1

*

p = 0.07

*

n.s

n.s

0.0

Max OD600 after 48 h growth

829

P30M0 1979 WT

P73F1 2002 phuS//phuR

244 P82M3 244 WT

243 P82M3 243 phuS//phuR

P66F0 2002 WT


P30M0 1979 WT


P66F0 2002 WT


831 832

Fig. S2: Distribution of non-synonymous mutations in the phuR heme receptor. The figure shows

833

the b-barrel structure spanning the cell membrane (horizontal lines) with transmembrane strands

834

(grey bars), extracellular loops (labelled L1-L11) and periplasmic turns (bottom loops). Green

835

circles indicate the location of non-synonymous SNPs, the smallest circles denoting one mutation

836

and the largest four. Mutations were significantly biased towards the extracellular loops.

837 L3 L2

L1

L4

L5 L6

L7

L8

L10

L11

L9

838 27


839

Supplementary Tables

840 841

Table S1: Calculation of estimated generation times of infecting clonal lineages. For each, the

842

patient ID, clone type, length of infection in years and minutes, estimated doubling time and

843

calculated number of generations is given.

844

(Excel sheet)

845 846

Table S2: Mutations identified in pyoverdine over-producers that may contribute to this phenotype.

847

For each mutation, the patient ID, clone type and gene is listed, as well as a reference to previous

848

work showing a link between the gene and pyoverdine production.

849 Patient ID

Clone type

Mutation

Reference

P40M5

DK43

ns SNP in PA2384

(Ochsner et al., 2002)

P67M4

DK41

Mutations in gacA, gacS and retS

(Frangipani et al., 2014)

P82M3

DK32

Insertion in mucA

(Wu et al., 2004)

P98M3

DK36

Deletion in mucA

(Wu et al., 2004) (Stintzi et al., 1998) (negative effect on

P99F4

DK06

ns SNP in lasR

production in knock-out)

P19F5

DK15

ns SNP in mucA

(Wu et al., 2004)

P50F5

DK07

Insertion wspR

(Visaggio et al., 2015)

850 851 852 853 854 855 856 857 858 859 860 861 862

28


863

Table S3: Transitions between iron uptake systems characterized as the order in which mutations

864

accumulate. When a clear order of mutations could be established the observed and expected

865

number of transitions, given a Poisson distribution, is stated and whether the difference between

866

them is statistically significant.

867

1st system(s)

2nd system(s)

Pyoverdine Obs:16, Exp: 14.69, p > 0.05

phuS//phuR Obs: 5, Exp: 0.39, p < 0.01

868 3rd system 869

Pyochelin + has (3)

870

Pyochelin Obs: 2, Exp: 4.01, p > 0.05 Pyochelin + phu (2)

871

phu Obs: 1, Exp: 2.24, p > 0.05

872

has Obs: 1, Exp: 1.41, p > 0.05

873

phuS//phuR + pyochelin (1) phu + has (1)

874 Pyochelin (1)

Pyochelin + phu + has + feo (1)

875 876

Pyochelin Obs: 6, Exp: 5.14, p > 0.05

877

phu (1)

878 has Obs: 2, Exp: 1.78, p > 0.05

879

Pyoverdine (1)

880

phu Obs: 1, Exp: 2.96, p > 0.05 Pyoverdine + pyochelin + phu (1)

has (2)

Pyoverdine + pyochelin (1)

phu (1)

Pyoverdine + phuS//phuR (1)

feo (1)

882

Pyoverdine + pyochelin + feo (1)

phu (1)

883

Pyoverdine + pyochelin + phu + has (1)

feo (1)

Pyoverdine + phu (1)

feo (1)

881

884 885

886

Table S4: Results of Tukey HSD post hoc comparison of a Two-Way ANOVA analyzing the

887

difference in Max OD600 between an isogenic pair of isolates differing in a phuS//phuR mutation at

888

four different heme concentrations.

889

(Excel sheet)

890 891

Table S5: List of mutations in genes associated with iron metabolism. For each isolate, the patient

892

ID, clone type and mutations are listed. A // denotes an intergenic mutation. The isolate names refer

893

to previous descriptions (Andersen et al., 2015; Markussen et al., 2014; Marvig et al., 2015). The

894

ten DK1 isolates that were not included in the previous analysis of pyoverdine mutations had one ns 29


895

SNP in pvdL (A5702G) and one in pvdP (C1508T, patient P55M3, isolate TM50 & TM51). The six

896

isolates used in the phenotypic assay of phuS//phuR mutations are highlighted in yellow.

897

(Excel sheet)

898 899

Table S6: Overview of patients and isolates.

900

(Excel sheet)

901 902

Table S7: Summary of the mutations found in five different iron uptake systems in P. aeruginosa.

903

The size of the respective operons is given in kb, and mutations are listed as non-synonymous (ns)

904

SNPs, synonymous (syn) SNPs, insertions and deletions (indels) and intergenic (IG). The overall

905

mutations, and ns SNPS and indels, per kb are listed. The phu operon experienced the highest

906

mutation rate, dominated by intergenic mutations. Two genes in the has operon were poorly

907

sequenced in the majority of isolates, and this is taken into account in the size and mutations listed

908

in parentheses.

909 Operon Pyoverdine

Size kb

Ns SNPs

Syn SNPs Indels

IG Mutations per kb

Ns SNPs/indels per kb

72.2

173

93

38

8

4.32

2.92

24.937

63

34

12

7

4.61

3.01

phu

7.516

31

10

3

34

10.38

4.52

has

10.8 (8.8)

17

14

2

3.05 (3.75)

1.75 (2.16)

feo

2.19

6

3

4.10

2.74

Pyochelin

910 911 912

30