The bacterium Staphylococcus aureus lives harmlessly on our skin and noses. However, occasionally, it gets into our blood and internal organs, such as our bones and joints, where it causes severe, long-lasting infections that are difficult to treat.

Over time, S. aureus acquire characteristics that help them to adapt to different locations, such as transitioning from the nose to the blood, and avoid being killed by antibiotics. Previous studies have identified changes, or ‘mutations’, in genes that are likely to play an important role in this evolutionary process. One of these genes, called accessory gene regulator (or agr for short), has been shown to control the mechanisms S. aureus use to infect cells and disseminate in the body. However, it is unclear if there are changes in other genes that also help S. aureus adapt to life inside the human body.

To help resolve this mystery, Giulieri et al. collected 2,500 samples of S. aureus from almost 400 people. This included bacteria harmlessly living on the skin or in the nose, as well as strains that caused an infection. Gene sequencing revealed a small number of genes, referred to as ‘adaptive genes’, that often acquire mutations during infection. Of these, agr was the most commonly altered. However, mutations in less well-known genes were also identified: some of these genes are related to resistance to antibiotics, while others are involved in chemical processes that help the bacteria to process nutrients.

Most mutations were caused by random errors being introduced in to the bacteria’s genetic code which stopped genes from working. However, in some cases, genes were turned off by small fragments of DNA moving around and inserting themselves into different parts of the genome.

This study highlights a group of genes that help S. aureus to thrive inside the body and cause severe and prolonged infections. If these results can be confirmed, it may help to guide which antibiotics are used to treat different infections. Furthermore, understanding which genes are important for infection could lead to new strategies for eliminating this dangerous bacterium.

While Staphylococcus aureus is one of the most important human pathogens (Tong et al., 2015), its common interaction with the human host is colonisation, usually of the anterior nares (Wertheim et al., 2005). Comparatively, severe, life-threatening infections such as bacteraemia or osteomyelitis occur very rarely. This suggests that at the macro-evolutionary level, S. aureus is primarily adapted to its natural ecological niche (the nasal cavity) and to specific selective pressures arising in this environment, such as competition with the resident microbiota (Krismer et al., 2017). By contrast, during invasive infection, a new fitness trade-off needs to be achieved to adjust to environmental challenges that include innate and acquired immune responses (Proctor, 2019), high-dose antibiotics (Kuehl et al., 2020), and nutrient starvation (Hood and Skaar, 2012). These trade-offs could occur across three potentially distinctive dynamics of micro-evolution during colonisation and infection (within the colonising population, from colonising to invasive, and within the invasive population), leading to nose-adapted, early infection-adapted, and late infection-adapted strains. Identifying infection-adapted strains might assist precision medicine strategies for infection prevention and management and refine the understanding of S. aureus pathogenesis versatility, as mutational footprints of selection mirror functions that are critically important for bacterial survival during invasion.

Emerging genomic approaches for analysis of within-host evolution are among the most powerful means to study bacterial host adaptation (Marvig et al., 2015; Kennemann et al., 2011; Lieberman et al., 2016). Studies have shown the remarkable diversity and evolution of colonising populations of Streptococcus pneumoniae (Chaguza et al., 2020) and S. aureus (Paterson et al., 2015). In S. aureus, Enterococcus faecalis and Enterococcus faecium it has been shown that transition from colonisation to invasion favours strains with specific adaptive signatures (Young et al., 2017; Van Tyne et al., 2019; Chilambi et al., 2020), while evidence of niche adaptation was noted in a within-host study of bacterial meningitis due to S. pneumoniae (Lees et al., 2017b). Furthermore, phenotypic and genomic adaptation (often in response to antibiotic pressure) has been investigated during selected episodes of persistent invasive infections due to S. aureus (Giulieri et al., 2020; Howden et al., 2006; Giulieri et al., 2018), Pseudomonas aeruginosa (Wheatley et al., 2021), Salmonella enterica (Klemm et al., 2016), and Mycobacterium tuberculosis (Vargas et al., 2021). To increase power, bacterial within-host evolution studies have leveraged on large collections of paired samples coupled with statistical models of genome-wide mutation rates (Marvig et al., 2015; Lees et al., 2017b; Gatt and Margalit, 2021) and extended the analysis to include chromosomal structural variation (Giulieri et al., 2018; Lees et al., 2017a; Gao et al., 2015) as well as intergenic mutations (Lees et al., 2017a; Khademi et al., 2019).

Convergent evolution among separated (independent) episode of colonisation or infection is a key indication of adaptation in evolution analyses. However, with the notable exception of one study of cystic fibrosis (Long et al., 2020), the convergence has generally been weak in within-host studies of S. aureus infections, with no convergence at all (Giulieri et al., 2018) or significant enrichment limited to the S. aureus master regulator agr (Young et al., 2017). We hypothesised that in addition to the small sample size, the extended range of bacterial functions potentially under selective pressure (each function being potentially targeted by diverse pathoadaptive mutations) has hampered the identification of important adaptation mechanisms. To overcome the limitations of studies to date, we have pooled all publicly available S. aureus within-host evolution studies, and complemented this with a new dataset from a recent S. aureus clinical trial (Tong et al., 2020), in a single large-scale analysis. Rather than focussing on point mutations and small insertions/deletions alone, we leveraged multiple layers of genome annotation (encompassing coding regions, operons, intergenic regions, and functional categories) and included chromosome structural variants to compile a comprehensive catalogue of bacterial genetic variation arising during host infection. This strategy enabled the detection of convergent adaptation patterns at an unprecedented resolution. We also outline distinctive signatures of adaptation during colonisation, upon transition from colonisation to infection and during invasive infection.

Within-host evolution of bacterial pathogens such as S. aureus is thought to be governed by a combination of positive selection for variants that confers an advantage within the host and random fixation of mutations (genetic drift) (Klemm et al., 2016; Didelot et al., 2016). Sudden changes in the effective population size (bottlenecks) can cause genetic drift, for example, when a single or few bacterial cells invade the bloodstream or when a secondary infection foci is established in tissues and organs. Consistent with this view, animal studies have shown that after infecting the blood with a polyclonal population, bacteraemic infection is established stochastically by a single clone (McVicker et al., 2014; Guerillot et al., 2018), although estimating the bottleneck size at invasion from clinical sequences has been more challenging (Abel et al., 2015). On the other hand, several lines of evidence support the role of positive selection and adaptive evolution during S. aureus infection. First, adaptive phenotypic features appear to be acquired during infection. The most obvious adaptative phenotype is secondary resistance to antistaphylococcal antibiotics such as rifampicin, vancomycin (Howden et al., 2006), daptomycin (Peleg et al., 2012), and oxacillin (Giulieri et al., 2020). Crucially, these resistance phenotypes can be associated with pleiotropic, pathoadaptative phenotypes such as small colony variant and immune evasion (Guérillot et al., 2018; Jiang et al., 2019; Guérillot et al., 2019). Furthermore, phenotypic adaptation (e.g. loss of toxicity) has been observed upon transition from colonisation to infection (Laabei et al., 2015), supporting the concept that invasive infection is linked to pathoadapted strains. At the molecular level, an excess of protein-truncating mutations in invasive strains (Giulieri et al., 2018) and in late colonising strains leading to infection (Young et al., 2012) have been noted. While this observation alone could be explained by relaxed constraint resulting from reduced population size (Didelot et al., 2016), it has been suggested that loss of gene function might be a common adaptation mechanism of within-host evolution (Gatt and Margalit, 2021), as supported by evidence of gene- or pathway-specific enrichment of mutations across independent infection episodes (Young et al., 2017).

Despite support for adaptive evolution from previous studies, it has been difficult to identify specific molecular signatures of adaptation during infection, due to the limited power of previous within-host studies of bacteraemia and other serious S. aureus infections that were often limited to a restricted number of episodes. To increase our ability to identify signatures of adaptation and find significantly enriched loci, we analysed multiple sources of genetic variation (point mutations, large deletions, IS insertions, and copy number variants) in a large collection of independent episodes of S. aureus colonisation and infection from 25 studies. We predicted that the main advantage of our approach would be to increase the ability of detecting convergence of genetic variants arising during invasive infections as opposed to those detected during the colonisation and upon transition from colonisation to infection. To test this hypothesis, we classified within-host variants based on their likely position in the within-host phylogeny (Figure 1D).

Bacterial adaptation is promoted by genomic plasticity; however, within-host evolution is characterised by low genetic variation (Giulieri et al., 2018). Based on our previous genomic studies of S. aureus bacteraemia, we reasoned that chromosome structural variants may provide an additional mechanism to increase genetic variation during infection. Here, we found that new insertions of IS are strongly enriched during invasive infection. However, despite this 20-fold enrichment, IS insertions remained a rare source of variation even within invasive strains and appeared to have a selective contribution to adaptation (i.e. limited to specific loci such as agrC). Similarly, large deletions and copy number variants appeared to play a less prominent role in adaptation, although we did not include them in our enrichment analysis.

Together with the enrichment for LOF mutations, which is another feature of evolution within the invasive population in our analysis, these IS movements suggest that a pattern of reductive evolution (genome degradation through loss of genes or accumulation of LOF mutations) emerges during within-host evolution of invasive S. aureus. This genome degradation might be related to less effective purifying selection (loss of deleterious alleles) in the invasive population due to a decrease in effective population size and a shorter evolutionary timescale (Didelot et al., 2016). However, our data indicate that these changes converge to specific genes, operons, and pathways, suggesting an adaptative benefit. Reductive evolution has been described in several ‘commensal-to-pathogen’ settings (Toft and Andersson, 2010). Although niche adaptation through reductive evolution has been described in extracellular pathogens (Stinear et al., 2007), a smaller (reduced) genome is a hallmark of obligate intracellular endosymbiotic bacteria (Batut et al., 2014). Since it appears that invasive S. aureus is able to reside intracellularly (promoting dissemination through mobile phagocytes during S. aureus sepsis [Thwaites and Gant, 2011; Surewaard et al., 2016], and immune evasion), it is plausible that this pattern of reductive evolution reflects an adaptation of invasive S. aureus to an invasive and intracellular lifestyle, as it has been shown for other facultative intracellular pathogens such as non-typhoidal Salmonella (Klemm et al., 2016). However, it is possible that these signatures of reductive evolution might be only temporary, as genome degradation might be present only in a minority of strains or be reversible; moreover, LOF mutations are expected to be more likely than gain of function mutations.

Beside reductive evolution, another distinctive feature of within-host evolution during invasive infection was intergenic mutations (both point mutations and IS insertions). In a within-host evolution study of S. pneumoniae colonisation, it was shown that intergenic sites were under convergent evolution (Chaguza et al., 2020). Mutations in promoter sequences of some core genes can play an important role in antibiotic resistance as it was repeatedly shown for pbp4 and resistance to beta-lactam antibiotics (Basuino et al., 2018). The role of intergenic mutations in within-host evolution was shown in a study of P. aeruginosa infection, where convergent evolution targeted several intergenic regulatory regions including upstream of antibiotic resistance genes (Khademi et al., 2019).

Previous work on within-host evolution by our group (included in this analysis) has established that agrA mutations are significantly enriched upon transition from colonisation to infection (Young et al., 2017). In addition, we have shown through genomics and targeted mutagenesis that mutations in key genes such as walKR (Howden et al., 2011) and rpoB (Gao et al., 2013) play a key pathoadaptive role in selected cases of persistent S. aureus infections. In this study, we increased our ability to discover potential targets of adaptation by analysing several mechanisms of genetic variation and applying several layers of annotation. As compared to previous work on S. aureus, this approach provides a higher-resolution picture of within-host evolution and adaptation. Importantly, this analysis remains robust after removing more than 1000 sequences from the largest within-host study included (Figure 3—figure supplement 7). We increase here the generalisability of our findings. We expand the list of genes targeted by convergent evolution and show that there are distinctive adaptation pathways in colonising and invasive populations. We confirm that the dominantly mutated loci belonged to the agr locus, in particular agrA and agrC. This finding is consistent with a large body of literature that predated the genomic era (Novick and Geisinger, 2008) that supports the role of the agr locus as the master regulator of gene expression in S. aureus. Agr-mediated adaptation was so important that we found a highly significant enrichment of agr mutations arros all type variants, including within colonising strains (type C>C variants). Shopsin et al. showed that ~10% of healthy S. aureus carriers held an agr-defective strain and that prior hospitalisation was significantly associated with agr-defective status, suggesting prior adaptive pressures (Shopsin et al., 2008).

Consistent with the distinctive general patterns of evolution displayed during invasive infection, some genes and loci were specifically mutated within invasive strains. Some of these genes were emerging targets of S. aureus pathogenesis in vivo, such as purR and yjbH that were not singled out in previous within-host evolution investigations. Others were known determinants of antibiotic resistance, including mprF, rpoB, and the walKR operon. This underscores the crucial role of antibiotic exposure in shaping adaptive evolution during invasive infection. A recent study of within-host evolution during cystic fibrosis found that resistance genes were hotspots of convergent evolution in this population, which is frequently treated with antibiotics and shows features of phenotypic adaptation (Long et al., 2020).

While most mutations in adaptive loci were substitutions within the coding sequence, about 40% of walKR operon mutations were located outside of the coding regions of walR and walk, emphasising the need to study intergenic mutations and mutations throughout an operon to capture adaptive signatures. This observation highlights the importance of expanding the analysis of intergenic mutations for the detection of adaptive mutations, in particular those linked to antibiotic resistance.

If within-host evolution represents adaptative evolution, it is possible that adaptation involved an accumulation of mutations and possibly epistatic mechanisms. Our data show that some mutations are specific for invasive strains; these mutations may reflect late adaptation, occurring after evolution during colonisation in the nose and upon transition from colonisation to infection, and thus occurring after adaptive mutations were acquired during earlier stages. This evolutionary pattern of stepwise adaptation (or adaptive continuum) encompassing the entire within-host evolutionary arch has been well described for cancer (Abbosh et al., 2017) and has been also investigated in a study of transition from colonisation to infection (Young et al., 2012). One way to capture this is mutation co-occurrence analysis. Here, we show mutation co-occurrence within the agr operon but also co-occurrence of the same mutations in two uncharacterised proteins in S. aureus. Our network of mutation co-occurrence linked to agrAC mutations might suggest a potential pathway of stepwise adaptation following initial mutations acquisition in the agr locus, an hypothesis that has been explored in one of studies included in our analysis (Altman et al., 2018).

While combining multiple studies allowed us to increase statistical power in order to detect genome-wide convergent signals of adaptation, this approach has some limitations. The quality of the publicly available sequences and metadata can be heterogeneous, despite performing quality control assessment, for example, due to different read coverage across studies. Lack of consistent metadata might have impacted the clinical categorisations used here, including the distinction between colonising and invasive strains (however, 83% of the strains could be classified unambiguously based on the site of collection). In addition, detection of structural variants from short reads is not as accurate as from long reads; for example, chromosomal inversions can be missed if their inversion site span is larger than the insert site of the paired-end reads (Guérillot et al., 2019). Furthermore, the majority of the episodes included had low sampling density. More contemporary strategies leverage a multiplicity of samples and deep sequencing strategies to capture within-host diversity, allowing to detect minority variants that could be relevant for adaptation and to obtain a more accurate understanding of evolutionary dynamics within the host, including estimating bottlenecks (Hall et al., 2019) and tracking the fall and rise of within-host lineages (Bryant et al., 2021). Finally, while several adaptive loci identified here have been previously assessed experimentally, the functional impact of adaptive variants in less characterised genes and intergenic mutations warrants further exploration using targeted mutagenesis (Monk et al., 2015).

Ultimately, the goal of detecting adaptive signals is to identify new mechanisms of pathogenesis or resistance to therapeutic targets and to inform prediction of clinical outcomes. So far, studies have failed to show consistent associations between specific clinical outcomes and genetic features of infecting (or colonising) S. aureus strains. This might be related to the dominance of host/environmental factors, but it could also be linked to the limited power of studies performed so far. By contrast, within-host evolution studies are an elegant approach to identify signatures of adaptation that might be candidate markers of important clinical outcomes, such as infection risk in case of colonisation or treatment failure in case of infection. Here, we show that adaptation signatures are at least partially specific to colonisation, infection, and upon transition from colonisation to infection and that adaptive changes are more frequent in distinctive infection episodes (complicated bacteraemia and endocarditis). These findings suggest that adaptive signatures might be indicative of important clinical outcomes. In the future, precision medicine in infectious diseases could follow the lead of cancer genomics, where within-host evolution studies have tracked the evolution of cancer clones and enabled the detection of high risk mutations early.

All data generated or analysed during this study are included in the manuscript and supporting file 1-6. The code to call, filter and annotated within-host variants and to perform the enrichment analysis is available on github at https://github.com/stefanogg/staph_adaptation_paper, (copy archived at swh:1:rev:6ec5132855405e1c759fedadb4c70e295c1c1974).

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Author details

1. Stefano G Giulieri

   1. Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia
   2. Department of Infectious Diseases, Austin Health, Heidelberg, Australia
   3. Victorian Infectious Diseases Service, Royal Melbourne Hospital, Melbourne, Australia

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

2. Romain Guérillot

   Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

   Contribution

   Conceptualization, Formal analysis, Methodology, Software, Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

3. Sebastian Duchene

   Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

   Contribution

   Resources, Software, Writing – review and editing

   Competing interests

   No competing interests declared

4. Abderrahman Hachani

   Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

   Contribution

   Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8032-2154

5. Diane Daniel

   1. Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia
   2. Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne at the Doherty Institute for Infection and Immunity, Melbourne, Australia

   Contribution

   Data curation, Investigation, Project administration

   Competing interests

   No competing interests declared

6. Torsten Seemann

   Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne at the Doherty Institute for Infection and Immunity, Melbourne, Australia

   Contribution

   Methodology, Software, Supervision

   Competing interests

   No competing interests declared

7. Joshua S Davis

   1. Department of Infectious Diseases, John Hunter Hospital, Newcastle, New South Wales, Australia
   2. Menzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia

   Contribution

   Investigation, Resources, Writing – review and editing

   Competing interests

   No competing interests declared

8. Steven YC Tong

   1. Menzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia
   2. Victorian Infectious Disease Service, Royal Melbourne Hospital, and University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia

   Contribution

   Conceptualization, Investigation, Resources

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1368-8356

9. Bernadette C Young

   Nuffield Department of medicine, Oxford, United Kingdom

   Contribution

   Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6071-6770

10. Daniel J Wilson

    Big Data Institute, Nuffield Department of Population Health, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, University of Oxford, Oxford, United Kingdom

    Contribution

    Methodology, Software, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-0940-3311

11. Timothy P Stinear

    Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

    Contribution

    Conceptualization, Methodology, Supervision, Writing – review and editing

    For correspondence

    tstinear@unimelb.edu.au

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-0150-123X

12. Benjamin P Howden

    1. Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia
    2. Department of Infectious Diseases, Austin Health, Heidelberg, Australia
    3. Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne at the Doherty Institute for Infection and Immunity, Melbourne, Australia

    Contribution

    Conceptualization, Funding acquisition, Supervision, Writing – review and editing

    For correspondence

    bhowden@unimelb.edu.au

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-0237-1473

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