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. 2022 Jun 28;11:e74819. doi: 10.7554/eLife.74819

Stable antibiotic resistance and rapid human adaptation in livestock-associated MRSA

Marta Matuszewska 1,†, Gemma GR Murray 1,†,✉, Xiaoliang Ba 1, Rhiannon Wood 1, Mark A Holmes 1, Lucy A Weinert 1
Editors: Daniel J Wilson2, Gisela Storz3
PMCID: PMC9239682  PMID: 35762208

Abstract

Mobile genetic elements (MGEs) are agents of horizontal gene transfer in bacteria, but can also be vertically inherited by daughter cells. Establishing the dynamics that led to contemporary patterns of MGEs in bacterial genomes is central to predicting the emergence and evolution of novel and resistant pathogens. Methicillin-resistant Staphylococcus aureus (MRSA) clonal-complex (CC) 398 is the dominant MRSA in European livestock and a growing cause of human infections. Previous studies have identified three categories of MGEs whose presence or absence distinguishes livestock-associated CC398 from a closely related and less antibiotic-resistant human-associated population. Here, we fully characterise the evolutionary dynamics of these MGEs using a collection of 1180 CC398 genomes, sampled from livestock and humans, over 27 years. We find that the emergence of livestock-associated CC398 coincided with the acquisition of a Tn916 transposon carrying a tetracycline resistance gene, which has been stably inherited for 57 years. This was followed by the acquisition of a type V SCCmec that carries methicillin, tetracycline, and heavy metal resistance genes, which has been maintained for 35 years, with occasional truncations and replacements with type IV SCCmec. In contrast, a class of prophages that carry a human immune evasion gene cluster and that are largely absent from livestock-associated CC398 have been repeatedly gained and lost in both human- and livestock-associated CC398. These contrasting dynamics mean that when livestock-associated MRSA is transmitted to humans, adaptation to the human host outpaces loss of antibiotic resistance. In addition, the stable inheritance of resistance-associated MGEs suggests that the impact of ongoing reductions in antibiotic and zinc oxide use in European farms on livestock-associated MRSA will be slow to be realised.

Research organism: Staphylococcus aureus

eLife digest

Antibiotic-resistant infections are a growing threat to human health. In 2019, these hard-to-treat infections resulted in 4.95 million deaths making them the third leading cause of death that year. Excessive use of antibiotics in humans is likely driving the emergence of drug-resistant bacteria. But there is a concern that use of antibiotics on livestock farms is also contributing. A type of bacteria traced back to livestock is a growing cause of human infections that do not respond to treatment with the antibiotic methicillin in Europe. It is called livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA).

Bacteria can share genes that make them drug resistant or more deadly. These genes are often carried on mobile genetic elements that promote their movement from one bacterial cell to another. The most common type of LA-MRSA in Europe is clonal-complex 398 (CC398). It has two mobile genetic elements carrying antibiotic-resistance genes, but generally lacks a mobile genetic element that helps the bacterium escape the human immune system. Learning more about how LA-MRSA acquired these genetic changes may help scientists develop better strategies to protect the public.

Matuszewska, Murray et al. analyzed the genomes of more than 1,000 samples of CC398 collected from humans, pigs and 13 other animal species in 28 countries over 27 years. They used this data to reconstruct the bacteria’s evolutionary history. Matuszewska, Murray et al. show that two mobile elements containing antibiotic resistance genes in CC398 were gained decades ago. One is more than 50 years old and was likely acquired around the time antibiotic use in livestock became common. While most CC398 in livestock do not have a mobile element that helps LA-MRSA evade the human immune system, they often gain it when they infect humans. This leads to highly drug-resistant human MRSA infections.

The results of this study suggest that LA-MRSA is a serious threat to human health. The resistance of this bacterium has persisted for decades, spreading across different livestock species and different countries. These drug-resistant bacteria in livestock readily infect humans. Current efforts to reduce antibiotic use in farms may take decades to mitigate these risks. Additionally, the ban on zinc-oxide use on livestock in the European Union (coming into force June 2022) may not help reduce LA-MRSA, because the genes conferring resistance to bacteria and zinc treatment are not always linked.

Introduction

Mobile genetic elements (MGEs) play an important role in the evolution of bacterial pathogens. They can move rapidly between bacterial genomes, but can also be vertically inherited through stable integration into a host genome. As MGEs often carry genes associated with virulence and antibiotic resistance (Frost et al., 2005; Rankin et al., 2011), an understanding of the drivers and barriers to their acquisition and maintenance is central to predicting the emergence and evolution of novel and resistant pathogens (Brockhurst et al., 2019).

The emergence and evolution of methicillin-resistant Staphylococcus aureus (MRSA) across different ecological niches and host species are associated with the horizontal transfer of MGEs. Methicillin resistance is carried by the staphylococcal cassette chromosome element SCCmec, and additional MGEs carry resistance to other antibiotics, virulence factors, and host-specific adaptations (Hanssen and Ericson Sollid, 2006; Jamrozy et al., 2017; Haag et al., 2019; Turner et al., 2019; Matuszewska et al., 2020). While most MRSA clonal complexes (CCs) show an association with specific MGEs, their dynamics are not widely understood, leading to a gap in our understanding of the adaptive potential of S. aureus CCs.

Intensification combined with high levels of antibiotic use in farming has led to particular concerns about livestock as reservoirs of antibiotic-resistant human infections (World Health Organization, 2015). CC398 has become the dominant MRSA in European livestock. Its rise has been particularly evident in Danish pig farms where the proportion of MRSA-positive herds has increased from <5% in 2008 to 90% in 2018 (Sieber et al., 2018; DANMAP, 2019), but it has also been observed in other European countries, and other livestock species (Lekkerkerk et al., 2015; Islam et al., 2017; Anjum et al., 2019). Livestock-associated (LA) MRSA CC398 has been associated with increasing numbers of human infections, in both people with and without direct contact with livestock (Larsen et al., 2017; van Alen et al., 2017; Sieber et al., 2019). Understanding the emergence and success of CC398 in European livestock and its capacity to infect the human host is integral to managing the risk that it, and other livestock-associated pathogens, pose to public health.

Previous studies have used genome sequences to reconstruct the evolutionary history of CC398 (Price et al., 2012; Ward et al., 2014; Gonçalves da Silva et al., 2017). They identified a largely methicillin-resistant and livestock-associated clade of CC398, that falls as either sister to Ward et al., 2014 or within (Price et al., 2012; Gonçalves da Silva et al., 2017) a largely methicillin-sensitive and human-associated clade. Through comparing the genomes of isolates from livestock- and human-associated CC398, these studies concluded that the emergence of CC398 in livestock was associated with both the acquisition of antibiotic resistance genes and the loss of genes associated with human immune evasion. While these genes are known to be carried on three categories of MGEs (Tn916 conjugative transposons, SCCmec, and φSa3 prophages), little is known about the dynamics of these MGEs within CC398. Here, we undertake a comprehensive reconstruction of the evolutionary dynamics of these MGEs. We find that while their patterns of presence/absence all show a strong association with the transition to livestock, this is the result of contrasting dynamics. These dynamics can inform predictions about the risk posed by LA-MRSA spillover infections in humans, and the resilience of antibiotic resistance in LA-MRSA to ongoing changes in antibiotic use in farming.

Results

Livestock-associated CC398 emerged between 1957 and 1970

We collected and assembled publicly available whole-genome sequence data from CC398, and sequenced five isolates recently sampled from pig farms in the United Kingdom. Our collection includes high-quality whole genome assemblies of 1180 isolates (including 43 complete reference genomes). This collection spans 15 host species (including humans, pigs, cows, chickens, turkeys, and horses), 28 countries (across Europe, America, Asia, and Australasia), and 27 years (1992–2018) (Figure 1—figure supplement 1 and Supplementary file 1).

We constructed a recombination-stripped maximum likelihood phylogeny of CC398 using reference-mapped assemblies of our collection. We rooted the phylogeny with outgroups from four other S. aureus sequence types (STs) in four separate reconstructions. We also constructed a phylogeny from a recombination-stripped concatenated alignment of core genes extracted from de novo assemblies, with a midpoint rooting. These reconstructions consistently returned the same topology, and one that is described in previous studies: a livestock-associated clade of CC398 (704 isolates) that falls within a more diverse, and other largely human-associated clade (476 isolates) (Figure 1a and Figure 1—figure supplement 2; Price et al., 2012; Gonçalves da Silva et al., 2017).

Figure 1. The transition to livestock association in the 1960s was accompanied by changes in the frequencies of three mobile genetic elements (MGEs).

(a) A maximum likelihood phylogeny of 1180 isolates of CC398, rooted using an outgroup from ST291. Grey shading indicates the livestock-associated clade. Outer rings describe (1) the host groups isolates were sampled from, and the presence of three MGEs: (2) a Tn916 transposon carrying tetM, (3) a SCCmec carrying mecA, and (4) a φSa3 prophage carrying a human immune evasion gene cluster. (b) A dated phylogeny of a sample of 250 CC398 isolates that shows livestock-associated CC398 originated around 1964 (95% HPD: 1957–1970).

Figure 1.

Figure 1—figure supplement 1. The temporal, host species, and geographic distribution of our collection of CC398 isolates.

Figure 1—figure supplement 1.

(a) Phylogeny of CC398 with rings showing the host species and countries of origin for each isolate (groups with n < 10 not shown). The blue outline indicates the livestock-associated clade, and the red outline indicates the five most recent isolates in our collection (sampled in 2018), from pigs on UK farms. (b), (c), and (d) show the variation in sampling date, host species, and country across the livestock-associated (blue, lower) and human-associated (red, upper) clades.
Figure 1—figure supplement 2. Different outgroups consistently identify the root of CC398 within human-associated CC398.

Figure 1—figure supplement 2.

We constructed maximum likelihood phylogenies using a reference-mapped alignment of CC398 combined with four outgroups from sequence types (STs) 291, 30, 97, and 5; and using a core genome alignment of our de novo assemblies and a midpoint rooting. The outgroups we used covered a range of distances from the base of CC398: ST291 (ERR2729529) is ~0.005 subs/site, ST30 (ERS1420125) is ~0.012 subs/site, and ST97 and ST5 (ERR2729579 and SRS613151) are ~0.015 subs/site. The reference-mapped phylogenies that were rooted using ST291, ST30, and ST97, and the midpoint-rooted core genome phylogeny all showed a consistent root, which is shown in the figure (and indicated by 1). A different root was obtained when we used the outgroup of ST5 (location indicated by 2). This root is on a neighbouring branch to the root found in the four other reconstructions, and results in CC398 being rooted on the branch leading to a single isolate (ZTA09_03734_9HSA). Livestock-associated CC398 is indicated by a blue box with grey shading.
Figure 1—figure supplement 3. A consistent estimate of the age of the livestock-associated clade.

Figure 1—figure supplement 3.

Results of BEAST dating analyses estimating (A) the origin of a shallower subclade within the livestock-associated clade, (B) the origin of the entire livestock-associated clade, and (C) the origin of CC398. (a) The figure shows a schematic representation of the CC398 phylogeny indicating the nodes of interest (A–C), and our sampling strategy. We randomly sampled our dataset three times to generate samples of 250 isolates (200 from the livestock-associated clade and 50 from the human-associated clade). Samples overlapped by only 30 isolates that represent the most divergent lineages of the livestock-associated clade, to ensure a consistent description of the most recent common ancestor. Each sample had the same range of sampling dates (1993–2018). (a) also describes the results of a regression of root-to-tip distance against sampling date (correlation coefficient and estimate of the date of the most recent common ancestor) for each sample (1–3), and subsamples that include isolates from (A) only the main livestock-associated clade, (B) only the livestock-associated clade, and (C) the entire sample. As we observed stronger temporal signal for A and B, than for C, we estimated dated trees using BEAST for each of these nine subsampled datasets. We observed consistent estimates of evolutionary rate across all these analyses (b). Rates at first/second codon positions are shown as circular points, and at third codon positions as square points. These analyses also returned broadly consistent estimates of dates (c). Although we found that estimates from subsamples that included outgroups of the node being dated returned more precise and marginally more recent estimates of age, likely due to more information about the location of the root.
Figure 1—figure supplement 4. Evidence of temporal signal is present across in our subsampled datasets, but is stronger when isolates from the human-associated group are excluded.

Figure 1—figure supplement 4.

Regressions of root-to-tip distance against sampling date for each of our datasets, rooted to minimise residual mean squares. (a)-(c) show the results for samples 1, 2, and 3 for clade a (described in Figure 1—figure supplement 3), (d)-(f) the results for samples 1, 2, and 3 for clade b, and (g)-(i) samples 1, 2, and 3 for clade c. For all datasets a randomisation test indicated that these correlations were unlikely to have arisen by change (p < 0.01). Correlation coefficients (r) and estimates of the time of the most recent common ancestor (tMRCA) based on the regression are shown for each dataset.
Figure 1—figure supplement 5. Livestock- and human-associated CC398 have divergent accessory genomes, and genes whose presence/absence most clearly distinguish these groups (except one) are associated with a Tn916 transposon, SCCmec, and φSa3 prophages.

Figure 1—figure supplement 5.

(a) A plot of the first and second principal components of accessory genome content, with isolates from human-associated CC398 in red and isolates from livestock-associated CC398 in blue. This was constructed using the package adegenet in R (Jombart, 2008). (b) Comparison of gene frequencies across the human- and livestock-associated groups. Genes present in <20% of human-associated CC398 and >80% of livestock-associated CC398 and genes presence in >80% of human-associated CC398 and <20% livestock-associated CC398 are highlighted, with genes associated with the Tn916 transposon shown in purple (all are overlapping as they have identical frequencies), genes associated with SCCmec shown in turquoise, and genes associated with φSa3 prophages shown in blue. The one gene that distinguishes livestock-associated CC398 from human-associated CC398 that is not associated with one of these three mobile genetic elements (MGEs) is shown as a red circle (tatC).
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We used the temporal structure in our collection to date the origin of the livestock-associated clade. Due to the size of our collection, we constructed dated phylogenies from three subsampled datasets, each of which includes 250 isolates. Our estimates of the evolutionary rate were consistent across all reconstructions (1.1–1.6 × 10−6 subs/site/year), and similar to estimates from previous studies of CC398 (Ward et al., 2014) and other S. aureus CCs (Hsu et al., 2015). This led to an estimate of the origin of the livestock-associated clade of approximately 1964 (95% CI: 1957–1970) (Figure 1b, Figure 1—figure supplement 3, and Figure 1—figure supplement 4).

The transition to livestock association is associated with changes in the frequencies of three MGEs with very different dynamics

Comparisons of the genomes of isolates from human- and livestock-associated CC398 have previously indicated that the transition to livestock was associated with the acquisition of genes associated with both tetracycline and methicillin resistance (tetM and mecA), and the loss of genes associated with human immune evasion (the immune evasion gene cluster) (Price et al., 2012). Our analyses of this larger collection are broadly consistent with this. We find that the genes whose presence most strongly distinguishes isolates from the human- and livestock-associated groups are associated with three categories of MGEs: (1) a Tn916 transposon carrying tetM, (2) SCCmec carrying mecA, and (3) φSa3 prophages carrying a human immune evasion gene cluster (Figure 1a, Figure 1—figure supplement 5, and Supplementary file 2). Genes associated with the Tn916 transposon and SCCmec elements are more common in the livestock-associated clade, while the reverse is true of genes associated with φSa3 prophages.

Stable maintenance of a Tn916 transposon carrying tetM

We identified a contiguous assembly of a Tn916 transposon carrying tetM in 699/704 isolates in our collection of livestock-associated CC398 (Figure 2a, Supplementary files 3 and 4; de Vries et al., 2009; Roberts and Mullany, 2009). Several lines of evidence indicate that the presence of the Tn916 transposon in livestock-associated CC398 is the result of a single acquisition event, followed by stable inheritance. First, the location of the transposon in the genome of livestock-associated CC398 is conserved (Tn916 is always found next to the same core gene; WP_000902814 in the published annotation of S0385). Second, an alignment of the coding regions of this element (extracted from de novo assemblies) shows a similar average nucleotide diversity to core genes (Figure 2d). Third, a phylogeny constructed from the genes in this element is entirely congruent with the phylogeny of livestock-associated CC398 (Figure 2b, c).

Figure 2. A Tn916 transposon carrying tetM has been stably maintained by livestock-associated CC398 since its origin.

(a) A gene map of the Tn916 transposon in CC398 (based on reference genome 1_1439), with annotations based on previous studies (de Vries et al., 2009; Roberts and Mullany, 2009). (b) A minimum-spanning tree of the element based on a concatenated alignment of all genes shown in (a). Points represent groups of identical elements, with point size correlated with number of elements on a log scale, and colours representing well-supported clades (>70 bootstrap support in a maximum likelihood phylogeny) that include >10 elements (smaller clades are incorporated into their basal clade). (c) These clades are annotated onto the CC398 phylogeny as an external ring. (d) Mean pairwise nucleotide distance between isolates carrying the Tn916 transposon based on genes in the Tn916 transposon and core genes, using bootstrapping to estimate error (see Materials and methods for details).

Figure 2.

Figure 2—figure supplement 1. Evidence of repeated excision of Tn916 transposon in the livestock-associated clade.

Figure 2—figure supplement 1.

(a) Purple points indicate which five isolates lack the Tn916 transposon in the livestock-associated clade. (b) Top: a gene map showing the Tn916 transposon from the 1_1429 reference strain and the two flanking genes (dark grey). Bottom: the integration site in the 62,951 strain within which the transposon is absent. The percentage nucleotide identity between the two flanking genes is indicated below the bars connecting the top and bottom gene maps.
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Our analyses indicate that the Tn916 transposon has been maintained in livestock-associated CC398 since its origin, and therefore for around 57 years (Figure 1b). Nevertheless, its absence from 5/704 livestock-associated CC398 isolates in our collection suggests that it remains capable of excision (this is consistent with experimental studies that have shown that Tn916 in CC398 is a functional conjugative transposon; de Vries et al., 2009). None of the genes associated with this element are present in these five isolates, and in two we were able to identify an intact integration site in the assembled genome (Figure 2—figure supplement 1). These five isolates are broadly distributed across the livestock-associated clade, and not linked to a particular host species or geographic location.

More variable maintenance of a SCCmec carrying mecA, tetK, and czrC

Previous studies suggest that LA-MRSA CC398 emerged from human-associated methicillin-sensitive S. aureus (MSSA) (Price et al., 2012). However, the presence of SCCmec elements in recently sampled human-associated CC398 isolates that fall basal to the livestock-associated clade, including clinical isolates from China (He et al., 2018; Zou et al., 2022), Denmark (Moller et al., 2019), and New Zealand (Gonçalves da Silva et al., 2017), makes the association between methicillin resistance and livestock association less clear (Figure 1a).

SCCmec elements in S. aureus are categorised into several types (Hanssen and Ericson Sollid, 2006). Consistent with previous studies of CC398 (e.g. Price et al., 2012), we observe both type V (76%) and type IV (21%) in CC398 (we were unable to confidently type the remaining 3%; Figure 3c, Figure 3—figure supplement 1, and Supplementary files 3 and 5). Most of the type V SCCmec elements belong to the subtype Vc previously described in livestock-associated CC398 (Li et al., 2011; Price et al., 2012; Vandendriessche et al., 2014). This element includes two additional resistance genes: tetK (tetracycline resistance) and czrC (heavy metal resistance) (Figure 3a and Supplementary file 6). We identified a full-length version of this element in 335 genomes (including some of the most recent isolates in our collection, sampled from UK pig farms in 2018) and shorter type V elements in 204 genomes. Full-length versions are only observed in the livestock-associated clade, while shorter versions are found in both livestock- and human-associated groups of CC398. Shorter versions often lacked tetK (n = 90) and czrC (n = 117) genes (Figure 3—figure supplement 2). Type IV elements are only observed in the livestock-associated clade. They include subtypes IVa and IVc, and all only carry a single resistance gene: mecA.

Figure 3. A type V SCCmec has been maintained since the 1980s, with occasional replacements.

(a) A gene map of the type Vc SCCmec element in CC398 (using the 1_1439 reference strain), with annotations from previous studies (Li et al., 2011; Vandendriessche et al., 2014). Genes in white were excluded from analyses of diversity within the element due to difficulties in distinguishing homologues. (b) A minimum-spanning tree of the type Vc SCCmec element based on a concatenated alignment of the genes (grey and red) in (a). Points represent groups of identical elements, point size correlates with group size on a log scale, and colours represent well-supported clades (>70 bootstrap support in a maximum likelihood phylogeny). (c) Well-supported clades and SCCmec type are annotated on the CC398 phylogeny in external rings. (d) Mean pairwise nucleotide distance between isolates carrying the SCCmec type Vc based on genes in the SCCmec type Vc and core genes, with error estimated by bootstrapping (see Materials and methods for details). (e) Acquisition dates for different SCCmec elements and Tn916 inferred from an ancestral state reconstruction over the dated phylogeny in 1 (b). Dates for type Vc are shown for both livestock- and human-associated CC398.

Figure 3.

Figure 3—figure supplement 1. Type V and IV SCCmec elements identified in CC398 through a BLASTn search or representative types.

Figure 3—figure supplement 1.

Initial identification of SCCmec types was carried out by BLASTn search of all SCCmec reference sequences on the SCCmecFinder extended database. As the SCCmec element in our dataset was commonly separated onto multiple contigs, we found that contiguous hits of the entire element were rare. Therefore, to determine the presence of a particular SCCmec type we considered the combined length of high-identity hits (hits that have >95% nucleotide identity and are ≥5% of the length of the element). We categorised elements into SCCmec types based on the overall length of the matched region, and described strains with best match lengths of <50% as unknown. The CC398 phylogeny is annotated with the results of this analysis. The innermost ring shows the presence/absence of mecA, and outer rings show the percentage length match for each type/sub-type (Table S7).
Figure 3—figure supplement 2. Most of the shorter versions of the type Vc SCCmec element in CC398 can be attributed to deletion events.

Figure 3—figure supplement 2.

Of the 540 isolates that carry a type V SCCmec in CC398, 204 have >2 genes absent. There are 3 common forms of gene absence (B, C and D). (a) Gene maps showing common patterns of gene absence. (b) A minimum spanning tree of a concatenated alignment of the 40 genes associated with the full-length SCCmec type V. Points represent groups of elements that differ by a maximum of 1 SNP, with point size correlated with group size on a log-scale, and colours representing categories described in (a). (c) Annotation of the full-length and truncated categories onto the core genome phylogeny. (d) Histograms showing pairwise distances (per shared nucleotide site) between individual elements in each group and the least divergent member of Group A. Histograms are shown on a log(x+1) scale due to the high frequency of low divergence elements. The dashed vertical lines show the average pairwise distance between isolates within the livestock-associated clade based on a core gene alignment, and the dotted lines show 10-times this value. Groups A, B and C are only found in the livestock-associated clade. Due to the low level of diversity in group D, versions from the human-associated and livestock-associated clade are shown together, while for group E they are shown separately (HA/LA). There are 13 isolates from the human-associated clade in group E. Of these 13 isolates, only 3 show sufficiently low divergence to be consistent with a recent common ancestor with the majority of elements from Group A, within CC398 (for these three elements divergence is <1.7 x10-4 /site). The three isolates carrying these elements all fall within the recent Danish hospital outbreak clade, and show 100% identity with the majority of the elements within this clade (that fall within group D).
Figure 3—figure supplement 3. There have been at least four independent acquisitions of type IV SCCmec within livestock-associated CC398.

Figure 3—figure supplement 3.

(a) An minimum-spanning tree based on a concatenated alignment of the 12 genes shared across all type IV SCCmec (n=148 isolates). Clades are distinguished based on nucleotide distances within these shared genes and by differences in the genes present in these elements. Clade A is IVa(1), Clade B is IVc, Clade C is IVa(2), and Clade D is IVa(3). IVa(2) and IVa(3) only differ by one SNP in the alignment of 12 shared genes, but they have different gene contents, suggesting divergent origins. (b) Clades of type IV elements mapped onto the core genome phylogeny.
Figure 3—figure supplement 4. Tn916 was acquired before the current complement of SCCmec elements in livestock-associated CC398, SCCmec type V was acquired before SCCmec type IV, and SCCmec type V was acquired by livestock-associated CC398 before human-associated CC398.

Figure 3—figure supplement 4.

Date estimates based on ancestral state reconstructions with BEAST over dated phylogenies inferred from three subsampled data sets. (A) A dated phylogeny inferred from one subsample (no. 1) with branches coloured by inferred SCCmec element at their descendent node (>95% posterior support), and earliest nodes (>95% posterior support) for each element labelled. (B) Date estimates for the earliest nodes at which each SCCmec type is inferred to be present (>95% posterior support) across the three data sets. Points are median values and bars are 95% confidence intervals. Estimates are shown for three versions of SCCmec type IVa that were distinguished based on the divergence within this element (see Figure 3—figure supplement 3). Only one estimate is provided for SCCmec-IVa(3) because it is only observed in one of the subsampled data sets.
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While type Vc is the most common SCCmec in our collection of livestock-associated CC398, this largely reflects isolates from pigs. Type Vc SCCmec is much more common in pigs (77% of isolates; n = 286) than type IV SCCmec (7% of isolates). In cows (n = 74), the difference is reduced: 45% are type Vc and 32% are type IV. And in isolates from other animal species (n = 94) type IV elements (55%) are more common than type Vc (33%).

Diversity within the type Vc SCCmec element indicates that a full-length type Vc SCCmec was acquired once by livestock-associated CC398, and has been maintained within CC398 largely through vertical transmission. First, low nucleotide diversity within full-length versions of the element is consistent with 329/335 sharing a recent origin common within livestock-associated CC398 (Figure 3d). Second, patterns of diversity are largely congruent with the core genome phylogeny, consistent with vertical inheritance (Figure 3b, c). Third, low nucleotide diversity within genes shared across full- and shorter-length versions of the element are consistent with most shorter-length versions being the result of deletion within livestock-associated CC398 (Figure 3—figure supplement 2). In contrast, diversity in the type IV elements in livestock-associated CC398 supports four independent acquisitions from outside of CC398 (Figure 3—figure supplement 3). Similar to the type Vc element, once acquired, these elements tend to be maintained.

While the SCCmec elements carried by human-associated CC398 are always type V, 70/80 fall within a single clade from a hospital outbreak in Denmark in 2016 (Moller et al., 2019). They show a truncation relative to the full-length type Vc that is also observed in three isolates from livestock-associated CC398 (leading to the absence of czrC, Figure 3—figure supplement 2). Pairwise nucleotide distances between these 70 human-associated CC398 elements and the full-length type Vc in livestock-associated CC398 are consistent with a recent common ancestor within CC398. In contrast, nucleotide diversity within the other 10 type V SCCmec in human-associated CC398 and distances from the livestock-associated CC398 type Vc indicate multiple independent acquisitions from outside of CC398 (Figure 3—figure supplement 2).

Using our dated phylogeny of CC398 and categorisation of SCCmec based on diversity within the elements, we inferred the dynamics of gain and loss within CC398 (Figure 3e and Figure 3—figure supplement 4). These reconstructions consistently estimated that the type Vc SCCmec had been acquired by livestock-associated CC398 by around 1986 (95% CI: 1982–1990), and has therefore been maintained within livestock-associated CC398 for around 35 years. While the diversity within this element indicates a single acquisition by CC398, these reconstructions indicate multiple gains, likely reflecting horizontal transmission within CC398. They also indicate that the acquisition by livestock-associated CC398 predated the acquisition by human-associated CC398, consistent with transmission from livestock-associated CC398 to human-associated CC398. In contrast, type IV elements show evidence of several more recent acquisitions in relatively quick succession between 1997 and 2004 (Figure 3e and Figure 3—figure supplement 4).

Together, our analyses are consistent with LA-MRSA emerging from human-associated MSSA and acquiring the type Vc SCCmec element following its initial diversification. The element has been stably maintained (particularly in pigs), although with several exceptions – including deletions of parts of the element and replacements with smaller type IV SCCmec.

Loss of a φSa3 prophage carrying a human immune evasion gene cluster, but with frequent reacquisition

In contrast to the maintenance of Tn916 and SCCmec type V in the livestock-associated clade, the φSa3 prophage is highly dynamic. φSa3 prophages carry human immune evasion gene clusters that include a variable set of functional genes that encode human-specific virulence factors, including sak, chp, scn, sea, and sep (Gladysheva et al., 2003; Postma et al., 2004; Rooijakkers et al., 2005; van Wamel et al., 2006; Thammavongsa et al., 2015; van Alen et al., 2018). They are temperate prophages that primarily integrate into the hlb gene of S. aureus. While φSa3 prophages are present in 88% of the human-associated CC398 isolates in our collection, we find that this is not a consequence of a stable association between CC398 and one prophage. Nucleotide diversity within genes shared across φSa3 prophages (Figure 4 and Supplementary file 3) suggest at least seven (but likely more) acquisitions of an φSa3 prophage into human-associated CC398 from outside of CC398. The set of functional genes carried by these elements indicate that the elements within human-associated CC398 include types C (n = 285), B (n = 111), E (n = 35), A (n = 4), and D (n = 4), and those carried by livestock-associated CC398 isolates include types B (n = 84), E (n = 8), and A (n = 5) (van Wamel et al., 2006; van Alen et al., 2018).

Figure 4. φSa3 prophages have been lost and acquired multiple times in both human- and livestock-associated CC398.

(a) A maximum likelihood phylogeny based on 12 genes shared across the φSa3 prophages in our collection, with both low-support nodes (<70% bootstrap support) and branches <0.0018 subs/site collapsed. The latter cut-off is a conservative estimate of the maximum distance that could reflect divergence within CC398. It is the maximum pairwise distance between isolates carrying φSa3 prophages across 1000 estimates from random samples of a core gene alignment of the same number of sites as is in our φSa3 prophage alignment. Node size correlates with the number of elements on a log scale. Elements carried by isolates from human-associated CC398 (grey) and livestock-associated CC398 (white) isolates are indicated, and nodes that include multiple elements labelled (A–E). (b) These clades annotated on the CC398 phylogeny as an external ring. The element carried by the poultry-associated subclade of livestock-associated CC398 is indicated by *.

Figure 4.

Figure 4—figure supplement 1. Maintenance of a φSa3 prophage in a poultry-associated clade of livestock-associated CC398 for around 21 years.

Figure 4—figure supplement 1.

(a) A minimum-spanning tree of the type B φSa3 prophage present in the poultry-associated clade of livestock-associated CC398. Fifty-five isolates in our collection of CC398 carry a version of this element. We identified 34 genes shared across these 55 versions of the element. After pruning genes with homologues, and difficult to align regions 29/34 genes were used to construct the tree. Points represent groups of identical elements, with point size correlated with group size on a log scale, and colours representing clades that differ from the basal group by >1 SNP. (b) These clades annotated onto the CC398 phylogeny as an external ring. 51/55 isolates carrying this element fall within the poultry-associated clade and four other isolates are from other clades within livestock-associated CC398 from human hosts. Within the avian clade we see little diversity (maximum pairwise distance is 1 SNP). The elements from outside of this clade show greater divergence, but this could still represent divergence within livestock-associated CC398.
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While φSa3 prophages are rare in livestock-associated CC398 (68/704 isolates), diversity within these elements indicate at least 15 (but likely more) acquisitions of these MGEs by livestock-associated CC398. The majority of these elements (69%) do not share a recent common ancestor with those in human-associated CC398. φSa3 prophages present in livestock-associated CC398 generally show evidence of recent acquisition, with a notable exception being a previously described poultry-associated subclade (n = 51) (Price et al., 2012; Larsen et al., 2016b; Pérez-Moreno et al., 2017; Tang et al., 2017). In our collection, 39% of the isolates in this clade are from poultry (compared to 4% across the rest of the livestock-associated clade). Low nucleotide diversity within the type B φSa3 consistently present in isolates within this clade suggests that it has been maintained since its acquisition approximately 21 years ago (95% CI: 1997–2001; Figure 1b and Figure 4—figure supplement 1).

Distinct route to multi-drug resistance in livestock-associated CC398

Livestock-associated CC398 is frequently multi-drug resistant. We see evidence of this in our dataset where 81% of livestock-associated CC398 isolates carry one or more resistance genes for antibiotic classes other than tetracyclines and β-lactams (Figure 5—figure supplement 1, Figure 5—figure supplement 2, and Supplementary file 7). Sixty-seven percent of livestock-associated CC398 isolates have genes associated with trimethoprim resistance (dfrA, dfrK, or dfrG), 42% have genes associated with macrolide resistance (ermA, ermB, ermC, or ermT), and 26% have genes associated with aminoglycoside resistance (aadA, aphA, or aphD). Not only are resistance genes less common in human-associated CC398 (only 20% of isolates carry tetracycline resistance genes, and 9% carry trimethoprim resistance genes), they also differ in their relative frequencies. In particular, human-associated CC398 isolates more commonly carry genes associated with macrolide resistance (91%).

Spillover of livestock-associated CC398 into humans is associated with the acquisition of φSa3 prophages, but not a loss of resistance genes

φSa3 prophages are more common in human isolates (23%) than in livestock or companion animal isolates (11%) in our collection of livestock-associated CC398. To determine the significance of this association, we identified 70 phylogenetically independent clades that include isolates from both human and livestock or companion animal hosts (Figure 5—figure supplement 3). Comparisons across these groups revealed that isolates from humans are consistently more likely to carry an φSa3 prophage (McNemar’s chi-squared test: p = 1.50 × 10−3; Figure 5).

Figure 5. Spillover of livestock-associated CC398 into humans is associated with acquisition of human immune evasion genes.

Seventy phylogenetically independent clades that include isolates from both humans and other species were identified within the livestock-associated clade. The plot shows the frequency with which these genes were identified within isolates from humans (right, empty bars) and non-human species (left, filled bars) in these groups. An asterisk indicates a significant difference based on McNemar’s chi-squared test (p = 1.50 × 10−3). No resistance genes differed significantly in their frequency across the human and non-human hosts (p > 0.1). The scn gene is always present in the human immune evasion cluster carried by φSa3 prophages, and therefore represents the presence of this element.

Figure 5.

Figure 5—figure supplement 1. Patterns in the presence/absence of antibiotic resistance genes vary across livestock- and human-associated CC398 in addition to the three genes associated with Tn916 and SCCmec.

Figure 5—figure supplement 1.

Variation in presence of antibiotic resistance genes across CC398 mapped onto the core genome phylogeny. All genes that are present above a threshold of 5% are represented, with colours representing different antibiotic classes.
Figure 5—figure supplement 2. Differences in antibiotic resistance gene frequencies across human- and livestock-associated CC398.

Figure 5—figure supplement 2.

(a) Comparison of the frequencies of resistance genes across clades, with the livestock-associated group shown in the filled bar on the left and the human-associated group the empty bar on the right. (b) Comparison of only isolates carrying mecA from the two groups. (c and d) Venn diagrams that show the relationship between the presence of genes associated with different antibiotic classes in methicillin-resistant Staphylococcus aureus (MRSA) isolates from both groups.
Figure 5—figure supplement 3. Phylogeny of the livestock-associated clade showing locations of 70 phylogenetically independent groups of isolates from human (red) and livestock/companion animal (blue) hosts.

Figure 5—figure supplement 3.

The phylogeny is a maximum likelihood phylogeny of the livestock-associated clade, rooted using human-associated CC398, with nodes with <70% bootstrap support collapsed. Seventy well-supported independent clades that contain both isolates from human and livestock/companion animal hosts were identified across the livestock-associated clade, and were used to test for differences in the frequency of genes associated with both antibiotic resistance and adaptation to the human host across these two groups. The small number of isolates from wild or domestic animals (other than livestock and horses) was excluded from the analysis.
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φSa3 prophages are also less common in isolates from pigs than from other non-human species (only 3% of pig isolates carry one). In 42/70 of our phylogenetically independent groups, the only non-human species was a pig, and none of the pig isolates from these groups carried an φSa3 prophage (while 14% of the human isolates did). In the remaining 28 groups (that included isolates from cows, horses, and poultry), φSa3 prophages were observed in non-human hosts in 17% of groups, but still at a higher frequency in humans (39% of groups) (McNemar’s chi-squared test: p = 0.04).

In contrast, we found no evidence that the spillover of livestock-associated CC398 into humans is associated with the loss (or gain) of individual antibiotic resistance genes (Figure 5). This contrasts with the conclusions of a previous study that suggested that the resistance genes carried by livestock-associated CC398 are likely to be lost in human hosts (Sieber et al., 2019). We find that no resistance gene was significantly more or less common in humans than in livestock species (McNemar’s chi-squared tests: p > 0.1), nor was there a consistent shift in the overall number of resistance genes (there were more resistance genes in isolates from human hosts in 22/70 pairs and more in livestock hosts in 34/70 pairs).

Discussion

We have characterised the evolutionary dynamics of the three classes of MGEs that show the greatest changes in frequency across human- and livestock-associated CC398: the Tn916 transposon and the SCCmec element, which are both common in livestock-associated CC398, and the φSa3 prophage, which is common in human-associated CC398. Despite a consistency in the relative frequencies of these elements across CC398, leading to their strong association with the transition to livestock, these three elements show a broad spectrum of dynamics. The Tn916 transposon carrying tetM shows evidence of stable and consistent vertical transmission in livestock-associated CC398 and absence from human-associated CC398. The type Vc SCCmec, carrying not only mecA, but also tetK and czrC, has also been stably maintained by several lineages of livestock-associated CC398, but by a combination of vertical and horizontal transmission, and with occasional replacement with type IV elements. While type V SCCmec elements are also present in human-associated CC398, there is little evidence of their longer-term maintenance. Finally, while φSa3 prophages carrying a human immune evasion gene cluster are rare in livestock-associated CC398 and common in human-associated CC398, there have been frequent gains and losses in both groups. These contrasting dynamics may reflect variation in the selective benefits and costs of the carriage of these MGEs by CC398, their availability in the environments encountered by CC398, and their mechanisms of transfer.

The three classes of MGEs whose dynamics we describe all employ different mechanisms of horizontal transfer, and this may both influence their intrinsic stability in the CC398 genome and their availability for acquisition from outside of CC398. Experimental studies have found that different types of MGEs vary in their rates of transfer between bacterial cells. In particular, in vitro rates of transfer of phage have been found to be several orders of magnitude higher than of transposons (Humphrey et al., 2021). A 16-day in vivo study of MGE dynamics for two strains of CC398 also observed variation in the mobility of MGEs: the Tn916 transposon, the type V SCCmec and an φSa3 prophage were all stably maintained and not horizontally transferred, while other prophages and plasmids were both gained and lost by daughter cells (McCarthy et al., 2014). While variation in the intrinsic stability of MGEs in their host will influence their long-term dynamics, other factors may dominate. For instance, the long-term stability of Tn916 within CC398 could emerge from a broad spectrum of short-term dynamics. It could result from a very low rate of loss, or frequent loss combined with a high selective cost of loss and a low probability of reacquisition from sources other than very closely related cells. Therefore, the long-term dynamics we describe provide a unique insight into the relationship between these MGEs and CC398.

We find that a Tn916 transposon that carries tetM was acquired once by CC398 and this coincided with its origin in European livestock in 1964 (95% CI: 1957–1970). Our observation of the loss of Tn916 on terminal branches of the phylogeny suggests that while losses do occur, lineages that lose Tn916 are either rapidly outcompeted by those that have maintained it, or they rapidly reacquire it from close relatives. Antibiotics, including tetracyclines, were first licensed for use as growth promoters in livestock in European countries in the 1950s, and were in common use by the end of that decade (Lowbury, 1958). While the use of antibiotics as growth promoters was banned by the European Union in 2006, tetracyclines remain the most commonly used antimicrobial class in livestock farming (World Health Organization, 2015; DANMAP, 2019). Carriage of Tn916 is therefore likely to have been associated with a strong selective benefit for livestock-associated CC398 ever since its emergence. However, as CC398’s exposure to tetracyclines will be intermittent, the long-term stability of Tn916 is also likely to reflect a low selective cost in the absence of treatment or a barrier to reacquisition following loss. Tn916-like elements are found across several bacterial genera (Clewell et al., 1995; Roberts and Mullany, 2009), including other opportunistic pathogens in the respiratory microbiome of pigs (Holden et al., 2009; Hoa et al., 2011) and other S. aureus CCs (de Vries et al., 2009). This suggests that the stability of Tn916 in CC398 is not due to the rarity of the element in the environments encountered by CC398, however it may be due to other barriers to successful transfer.

Previous studies have found evidence that the regulatory system of Tn916 promotes its maintenance in a host through ensuring both that excision only occurs in the presence of tetracycline (or other transcription-limiting cell stress) and that any selective burden in the absence of treatment is minimised (Roberts and Mullany, 2009). Nevertheless, Tn916 has been found to have a much more dynamic association with lineages of other bacterial species (e.g. Streptococcus pneumoniae [D’Aeth et al., 2021]). The fitness costs of MGEs can be host (and even insertion locus) specific and can also be mitigated over time (Starikova et al., 2013; Durão et al., 2018), and therefore the stability of Tn916 in livestock-associated CC398 might reflect a low cost that is specific to this lineage. A combination of high selective benefit, low selective cost and inaccessibility for reacquisition following loss could explain the remarkable stability of Tn916 in livestock-associated CC398, and may in part explain the success of this lineage in livestock.

Our results indicate that the acquisition of an SCCmec occurred later in the expansion of livestock-associated CC398. The most common SCCmec in livestock-associated CC398, type Vc, carries tetK and czrC in addition to mecA. These additional resistance genes might be highly advantageous in livestock, and particularly in pigs. While all livestock-associated CC398 carry tetM, there is evidence that carrying tetK in addition to tetM is associated with increased fitness during exposure to sublethal concentrations of tetracycline (Larsen et al., 2016a). czrC is associated with heavy metal resistance (Cavaco et al., 2010), which is likely to be beneficial in the context of the common supplementation of animal feed with zinc oxide, which in pigs is commonly used to prevent diarrhoea in weaners (Nielsen et al., 2021). Additionally, mecA is likely to be beneficial because of the common use of β-lactams in livestock farming, including third generation cephalosporins (Sjölund et al., 2016; Lekagul et al., 2019). The size of the type Vc element, combined with the replacements and truncations we observe suggests that it may come with a selective cost. In addition, SCCmec type Vc appears to be rare (at least in S. aureus). The element has been found in other staphylococci (S. cohhii in Vervet Monkeys [Hoefer et al., 2021]), but has not been reported in other S. aureus CCs.

Loss of the type Vc SCCmec on internal branches within livestock-associated CC398 is associated with replacement with a type IV SCCmec that only carries mecA. While we find evidence of only a single acquisition of the type Vc SCCmec by livestock-associated CC398, we find evidence of at least four acquisitions of type IV SCCmec. The more recent dates of acquisition, and an apparent association with livestock species other than pigs, might reflect a difference in selective pressures across different livestock species, or a loss of the type Vc element during transmission between livestock populations. The long-term maintenance of the type Vc SCCmec is consistent with a high selective benefit (particularly in pigs where this element is most common). However, its repeated loss and replacement with type IV elements are consistent with a low cost of this replacement, at least in certain contexts (perhaps in other livestock hosts), and might also reflect the rarity of the type V element relative to the type IV.

While the loss of the φSa3 prophage that carries a human immune-evasion gene cluster is associated with the transition to livestock, neither the loss nor the gain of these elements is likely to be a substantial hurdle for the adaptation of CC398 to human or non-human hosts. Their ubiquity in human-associated CC398 and frequent acquisition following transmission of livestock-associated CC398 to humans (consistent with Sieber et al., 2019), is consistent with a strong benefit in the human host (Rohmer and Wolz, 2021). On the other hand, as we find that these elements are frequently lost and generally absent in other host species, these elements may carry a selective burden outside of the human host. The diversity of φSa3 prophages in CC398 suggests they form a large pool of elements within human hosts (van Alen et al., 2018), likely reflecting their ubiquity in human carriage populations of S. aureus (Rohmer and Wolz, 2021) and capacity to transfer between S. aureus lineages.

We observe one clear exception to the pattern of recent acquisitions of φSa3 in livestock-associated CC398 in response to spillover events: the acquisition of an φSa3 prophage at the base of a poultry-associated subclade of livestock-associated CC398 (Price et al., 2012; Larsen et al., 2016b; Pérez-Moreno et al., 2017; Tang et al., 2017). This clade was first described as a hybrid LA-MRSA CC9/CC398 lineage (Price et al., 2012), and was subsequently investigated as a lineage associated with human disease (Larsen et al., 2016b). The maintenance of an φSa3 in this lineage may reflect more frequent transmission via a human host, or an adaptation to poultry (a recent study suggested that φSa3 prophages might aid immune evasion in species other than humans [Jung et al., 2017]). Either way, this might make this lineage a greater immediate threat to public health.

While livestock-associated CC398 is found across a broad range of livestock species, it is most commonly associated with pigs. The dynamics of the SCCmec and φSa3 prophages that we have identified are both consistent with livestock-associated CC398 originating in pig farms and later spreading to other livestock species. The lower frequency of the type Vc SCCmec in species other than pigs could reflect random loss during transmission bottlenecks, or a reduced benefit of either tetK or czrC in these species. Similarly, the higher frequency of φSa3 prophages in other species might reflect an increased benefit or reduced cost, or more recent transmission via human hosts.

Our results reveal that LA-MRSA CC398 is a stably antibiotic-resistant pathogen that is capable of dynamic readaptation to humans. We find that Tn916 and SCCmec are both stably maintained in livestock-associated CC398, across different livestock species and countries, and that neither of these MGEs (or other antibiotic resistance genes) tend to be lost when livestock-associated CC398 is transmitted to humans. This suggests that these MGEs are associated with a low selective cost in both livestock and human hosts, and therefore across variable levels and types of antibiotic exposure. The stability of these two MGEs, combined with the capacity of livestock-associated CC398 to rapidly acquire the φSa3 prophage, underlines the threat posed by LA-MRSA to public health. While SCCmec is less stably maintained than Tn916, our identification of several independent acquisitions of type IV SCCmec suggests both a strong selective benefit, not contingent on the carriage of tetK and czrC, and an availability of type IV elements. These dynamics predict that the impact of gradual reductions in antibiotic consumption on LA-MRSA is likely to be slow to be realised and that the forthcoming EU ban on medical zinc supplementation in pig feed may have a limited impact on LA-MRSA (European Medicines Agency, 2017; European Medicines Agency, 2020 DANMAP, 2019). Further work is, however, required to understand the factors that underlie the acquisition and maintenance of resistance genes within LA-MRSA, and how they differ from human-associated MRSA lineages.

Materials and methods

Data collection

All available genome sequence data relating to S. aureus CC398 were downloaded from public databases (https://www.ncbi.nlm.nih.gov/sra and https://www.ebi.ac.uk/ena/browser/; accessed 2019), with metadata in some cases obtained by request (Supplementary file 1). We additionally sequenced five isolates sampled from UK pig farms in 2018. All publicly available complete S. aureus genomes assemblies (https://www.ncbi.nlm.nih.gov/; accessed 2019) were MLST typed using Pathogenwatch (https://pathogen.watch), and the 43 genomes identified as CC398 were added to our collection. After exclusion of low-quality assemblies and isolates mis-characterised as CC398, this led to a collection of 1,180 genomes.

Genomic library preparation and sequencing

For sequencing of the five UK pig farm isolates, genomic DNA was extracted from overnight cultures grown in TSB at 37°C with 200 rpm shaking using the MasterPure Gram Positive DNA Purification Kit (Cambio, UK). Illumina library preparation and Hi-Seq sequencing were carried out as previously described (Harrison et al., 2013).

Genome assembly

We used sequence data from all isolates to generate de novo assemblies with Spades v.3.12.0 (Bankevich et al., 2012). We removed adapters and low-quality reads with Cutadapt v1.16 (Martin, 2011) and Sickle v1.33 (Joshi and Fass, 2011), and screened for contamination using FastQ Screen (Wingett and Andrews, 2018). Optimal k-mers were identified based on average read lengths for each genome. All assemblies were evaluated using QUAST v.5.0.1 (Gurevich et al., 2013) and we mapped reads back to de novo assemblies to investigate polymorphism (indicative of mixed cultures) using Bowtie2 v1.2.2 (Langmead and Salzberg, 2012). Low-quality genome assemblies were excluded from further analysis (i.e. N50 < 10,000, contigs smaller than 1 kb contributing to >15% of the total assembly length, total assembly length outside of the median sequence length ± one standard deviation, or >1500 polymorphic sites). We identified genomes mischaracterised as CC398 via two approaches and excluded them from further analysis. First, we identified STs with MLST-check (Page et al., 2016) and grouped into CCs using the eBURST algorithm with a single locus variant (Francisco et al., 2009). Second, we constructed a neighbour-joining tree based on a concatenated alignment of MLST genes (arcC, aroE, glpF, gmk, pta, tpi, and yqiL) for our collection and 13 additional reference genomes from other CCs, using the ape package in R and a K80 substitution model (Paradis et al., 2004).

We generated reference-mapped assemblies with Bowtie2 using the reference genome S0385 (GenBank accession no. AM990992). For reference genomes, we generated artificial FASTQ files with ArtificialFastqGenerator (Frampton and Houlston, 2012). Average coverage and number of missing sites in these assemblies were used as an additional quality control measure; genomes with average coverage <×50 or with >10% missing sites were excluded.

We identified recombination in the reference-mapped alignment using both Gubbins v2.3.1 (Croucher et al., 2015) and ClonalFrame (Didelot and Wilson, 2015). We masked all the recombinant sites identified from our alignment. We additionally masked a region of ∼123 kb that was identified as horizontally acquired from an ST9 donor in a previous study (Price et al., 2012).

Genome annotation and identification of homologous genes

We annotated de novo assemblies with Prokka v2.8.2 (Seemann, 2014) and identified orthologous genes with Roary (Page et al., 2015) using recommended parameter values. We created a core gene alignment with Roary and identified recombinant sites using Gubbins. We identified antibiotic resistance genes using the Pathogenwatch AMR prediction module (Wellcome Sanger Institute), which uses BLASTn (Altschul et al., 1990) with a cut-off of 75% coverage and 80–90% identity threshold (depending on the gene) against a S. aureus AMR database.

Phylogenetic analyses

We carried out phylogenetic reconstruction for the reference-mapped alignment with RAxML v8.2.4 using the GTR+Γ model and 1000 bootstraps (Stamatakis, 2014). Sites where >0.1% of genomes showed evidence of recombination or had missing data were excluded from the analysis. We constructed dated phylogenies using BEAST v1.10 with a HKY+Γ model, a strict molecular clock, and constant population size coalescent prior, from the coding regions of the reference-mapped alignment (Drummond et al., 2012). We fit separate substitution models and molecular clocks to first/second and third codon positions to reflect differences in selective constraint. We constructed phylogenies for three random subsamples of 250 isolates (200 from livestock-associated CC398 and 50 from human-associated CC398). Subsamples were non-overlapping except for 30 genomes representing the most divergent lineages within the livestock-associated clade, to ensure a consistent description of the origin of this clade. We constructed additional phylogenies from subsamples that included only isolates from the LA clade to establish that consistent rate estimates were returned over different evolutionary depths. We investigated temporal signal in each dataset through a regression of root-to-tip distance against sampling date, and a permutation test of dates over tips (with clustering used to correct for any confounding of temporal and genetic structures) (Murray et al., 2016; Rambaut et al., 2016). Trees are visualised and annotated using ITOL (Letunic and Bork, 2021).

Comparative analyses of MGEs

Genes associated with the transition to livestock were identified through comparing frequencies of homologous genes identified with Roary across human- and livestock-associated CC398. We investigated the association between these genes and MGEs through analysis of (1) physical locations within our de novo assemblies and the reference genomes, (2) correlations in their presence/absence across our collection, and (3) comparison with descriptions in the literature and in online databases of particular MGEs.

We confirmed the identity of the Tn916 transposon by comparison with published descriptions and publicly available annotated sequences. SCCmec elements were initially categorised into types using a BLASTn search of all representative SCCmec types from the SCCmecFinder database in our de novo assemblies (Supplementary file 5; Hanssen and Ericson Sollid, 2006). φSa3 prophages were initially identified and categorised through identification of functional genes associated with the human immune evasion gene cluster. To further characterise diversity within these elements we identified genes associated with each element across our collection. We constructed alignments of genes within MGEs using Clustal Omega v1.2.3 (Sievers and Higgins, 2018) and checked for misalignment by eye.

We analysed variation in both gene content and nucleotide diversity within shared genes for each MGE. We estimated pairwise nucleotide distances in concatenated alignments of shared genes for each type of element using the ape package in R (Paradis et al., 2004), and constructed maximum likelihood trees using RaxML and minimum-spanning trees using GrapeTree (Zhou et al., 2018) to investigate co-phylogeny. We generated confidence intervals for our estimates of mean pairwise nucleotide distances within MGEs by re-estimating the mean distance from 1000 bootstrapped samples of sites. We compared this to sites in the core genome by sampling the same number of sites as were in the MGE alignment from a concatenated alignment of core genes (generated by Roary). For SCCmec we used ancestral state reconstruction in BEAST to infer the evolutionary dynamics of these elements and date their origins within CC398. This involved fitting a discrete traits model to the posterior distributions of trees, with each state representing a version of the element that had been independently acquired by CC398. We used a strict clock model that allowed for asymmetric rates of transitions between states, but we found that the results were robust to use of a symmetric model or a relaxed clock.

Phylogenetically independent groups

To test the association between spillover into the human host and the presence of φSa3 prophages and antibiotic-resistance genes, we identified 70 phylogenetically independent clades of isolates that were sampled from both human and non-human hosts in the livestock-associated clade. We classed a gene as present in a host if it was observed in any of the isolates from that host in that clade.

Acknowledgements

MM was funded by the Medical Research Council, co-funded by the Raymond and Beverly Sackler Fund. GGRM and LAW were supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (109385/Z/15/Z). GGRM was also supported by a ZELS BBSRC award (BB/L018934/1) and a Research Fellowship at Newnham College.

Funding Statement

The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication. For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

Contributor Information

Gemma GR Murray, Email: ggrmurray@gmail.com.

Daniel J Wilson, University of Oxford, United Kingdom.

Gisela Storz, National Institute of Child Health and Human Development, United States.

Funding Information

This paper was supported by the following grants:

  • Wellcome Trust 109385/Z/15/Z to Gemma GR Murray, Lucy A Weinert.

  • Medical Research Council to Marta Matuszewska.

  • Biotechnology and Biological Sciences Research Council BB/L018934/1 to Gemma GR Murray.

  • Newnham College, University of Cambridge to Gemma GR Murray.

Additional information

Competing interests

No competing interests declared.

No competing interests declared.

Author contributions

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

Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review and editing.

Resources, Writing – review and editing.

Resources.

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

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

Additional files

Supplementary file 1. Strain names, country of origin, source (host species), year, accession numbers, and references for all isolates.
elife-74819-supp1.xlsx (65KB, xlsx)
Supplementary file 2. Genes that most strongly distinguish human- and livestock-associated CC398, and their association with mobile genetic elements.

Our gene identifiers and the gene locations and locus tags in published reference genomes are provided.

elife-74819-supp2.xls (36KB, xls)
Supplementary file 3. Description of the presence of mobile genetic elements (MGEs) and annotation of MGE types and clades.

The presence/absence of genes and MGEs is described by 1/0, and types and clades that are presented in the text are described.

elife-74819-supp3.xls (329.5KB, xls)
Supplementary file 4. Description of the genes in the Tn916 element.

The genes in the Tn916 element used in our analyses are described in the reference genome 1_1439.

elife-74819-supp4.xls (27.5KB, xls)
Supplementary file 5. Reference SCCmec elements used in BLAST typing.
elife-74819-supp5.xls (29KB, xls)
Supplementary file 6. Description of the genes in the type V SCCmec element.

The genes in the SCCmec type Vc element used in our analyses are described in the reference genome 12_LA_293.

elife-74819-supp6.xls (32KB, xls)
Supplementary file 7. AMR genes identified by PathogenWatch.

Gene presence/absence is described by 1/0.

elife-74819-supp7.xls (231KB, xls)
Transparent reporting form

Data availability

The Illumina sequences generated in this study have been deposited in the NCBI short read archive under the accession numbers ERR3524650, ERR3524328, ERR3524354, ERR3524446, and ERR3524562. All other sequences used in this study are publicly available and their origins are described in Supplementary file 1.

The following datasets were generated:

Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524650

Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524328

Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524354

Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524446

Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524562

The following previously published datasets were used:

Gonçalves da Silva A. 2017. Emergence of CC398 MRSA in New Zealand. NCBI BioProject. PRJEB12552

Fox et al. 2017. Detection and molecular characterisation of Livestock-Associated MRSA in raw meat on retail sale in North West England. NCBI BioProject. PRJEB18725

He et al. 2018. Staphylococcus aureus CC398 resequencing data. NCBI BioProject. PRJNA347471

Heikinheimo et al. 2016. Studying 3 strains of LA-MRSA from Finland with interesting deletion genotypes. NCBI BioProject. PRJEB14187

Himsworth et al. 2014. MRSA from rats and humans isolated from the Downtown Eastside of Vancouver, BC, Canada. NCBI BioProject. PRJEB5042

Islam et al. 2017. Prevalence and origin of LA-MRSA CC398 in Danish horses. NCBI BioProject. PRJEB19362

Larsen et al. 2016. Staphylococcus aureus . NCBI BioProject. PRJNA226567

Lowder and Fitzgerald 2018. poultry-associated genetic elements in Staphylococcus aureus. NCBI BioProject. PRJNA312437

Makarova et al. 2017. Staphylococcus aureus strain 08S00974 chromosome, complete genome. NCBI GenBank. PRJNA378150

Moller et al. 2019. Unusual MRSA CC398 hospital outbreak. NCBI BioProject. PRJNA508272

Paterson et al. 2013. Diversity_of_MRSA. NCBI BioProject. PRJEB2655

Holmes 2018. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI BioProject. PRJEB21015

Price et al. 2012. Staphylococcus aureus CC398: host adaptation and emergence of methicillin resistance in livestock. NCBI BioProject. PRJNA274898

Ronco et al. 2018. Staphylococcus aureus Raw sequence reads. NCBI BioProject. PRJNA430150

Sharma et al. 2016. LA-MRSA CC398 from UK animals. NCBI BioProject. PRJEB14251

Sieber et al. 2019. Spread of LA-MRSA CC398 in pigs and humans in Denmark. NCBI BioProject. PRJEB25608

Uhlemann et al. 2017. Sequencing of Staphylococcus aureus CC398 from Northern Manhattan. NCBI BioProject. PRJEB12818

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Editor's evaluation

Daniel J Wilson 1

The reviewers recognised the importance of understanding where new strains of microbes come from and how they change over time for infection control and prevention. Staphylococcus aureus CC398 is an important strain that 'spills over' from livestock to humans, carrying with it high levels of resistance to antibiotics commonly used in farming. This paper compares more than 1000 genomes of CC398 and concludes that spillover is likely to carry resistance to tetracyclines and other antibiotics into humans that will persist over time.

Decision letter

Editor: Daniel J Wilson1
Reviewed by: Daniel J Wilson2

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Human readaptation outpaces loss of antibiotic resistance in livestock-associated MRSA" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Daniel J Wilson as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Gisela Storz as the Senior Editor.

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

The reviewers were all impressed by the excellent quality of these comprehensive analyses of an important pathogen strain. Please read the summary below in conjunction with the detailed reviews.

1) Our first main reservation was that the text should distinguish better what is new vs what is known throughout the paper. As an example, line 28-29 of the abstract is particularly ambiguous.

2) The second main reservation was the headline conclusion in the title -- that human re-adaptation (acquisition of human immune evasion genes by livestock-associated CC398s) outpaces loss of antibiotic resistance -- can be argued on first principles. From that perspective, it would appear to lack novelty.

3) A third point of discussion was an apples-and-oranges argument about comparing different MGE types. We felt that since they are fundamentally different and known to come and go at different rates, that this should be acknowledged with references. That is not to say there is no value to empirically quantifying those differences on timescales relevant to the evolution of CC398, and to discussing the implications for the turnover of the different AMR genes they carry.

My inclination is that the new analyses of MGE dynamics (how often known CC398-associated MGEs have come and gone, and the dates of these events) probably add sufficient novelty to warrant publication in eLife, but as currently presented that is not certain. I would welcome a revision that focuses on addressing this point.

Reviewer #2 (Recommendations for the authors):

I find that the comparison made in the title potentially a false equivalence between the evolutionary mechanisms driving gain/loss of pathogenicity genes, and gain/loss of resistance, for a few reasons. One, loss of resistance genes first requires that the 'mutation' leading to loss of resistance occurs, then lineages with that loss are selectively favoured. In contrast, (re)acquisition of the pathogenicity genes, which are already present in the wider population/community of bacteria, is much more likely to occur and then be selectively favoured. It is thus hard to envision a scenario where adaptive evolution for pathogenicity would ever be expected to outpace adaptive loss of resistance, unless the fitness costs of resistance are extremely high. I think the analysis and data stand on their own without having to force this comparison

Two, for an expectation that a 'thing' might be lost, its carriage should be associated with a fitness cost. While this is touched on, I would like to see more discussion about whether Tn916 is likely to carry a cost, otherwise its stable maintenance is the rule rather than the exception. Also, are there estimates about how easily Tn916 can be lost? Does it not drive its own reacquisition if an excision event is to occur?

Three, prophages, plasmids and transposons likely have different rates of gain/loss. This has been experimentally demonstrated by an excellent study from the group of Prof Jodi Lindsey (McCarthy et al., 2014, Genome Biology and Evolution, doi: 10.1093/gbe/evu214). Transfer of some MGEs was observed within 4 hours, whereas transfer of Tn916 was not observed within 16 days. I think it may lead to misleading comparisons to lump different types of MGEs together, as their gain/loss dynamics can differ significantly.

I would thus like to see an expanded discussion (i.e. more than just supposition) about estimated costs of SCCmec and phiSa3, or estimated benefits of (re-)acquiring these when selectively advantageous, and also what might be driving the replacement of Type V with other types. Also on relative rates of gain/loss events for the different categories of MGEs here. I would also recommend altering the title, as I do not find the comparison made there compelling, but that might be excessive.

Reviewer #3 (Recommendations for the authors):

In general, this manuscript is very well done and as mentioned in the public review, of high quality for the reader. It is in my eyes very close to be ready for publication if accepted, and I only have a few comments. Important, however, is the fact that the novelty in the manuscript is very limited because most results have been published earlier in the studies on the original datasets which are used here.

I only have a few comments:

General comments:

– Do you have any hypothesis on why ΦSa3 phages frequently are re-introduced and where from, as compared to other elements?

Specific comments:

– Line 62 and Table S1: Sieber et al., 2019 should be Sieber et al., 2018, mBio.

– Line 110: space missing before "(Ward et al., 2014)”.

– Line 275: “that integrate into the hlb gene of S. aureus”: There is strong evidence that the ΦSa3 phages integrate at other positions in LA-MRSA CC398. See e.g. Leinweber et al., 2021 (mBio) for a recent publication.

– Line 276: change "88% of our human-associated CC398 isolates" to "88% of the human-associated isolates in our collection".

– Lines 356-359: These results differ from what Sieber et al., 2019 found. Can you discuss this?

– Lines 416-418: This should be explained more precisely. Why are these dynamics consistent with these traits?

eLife. 2022 Jun 28;11:e74819. doi: 10.7554/eLife.74819.sa2

Author response

Essential revisions:

The reviewers were all impressed by the excellent quality of these comprehensive analyses of an important pathogen strain. Please read the summary below in conjunction with the detailed reviews.

We would like to thank the editor and the reviewers for their positive assessments of our manuscript and useful suggestions. We have provided point-by-point responses to their comments below. The line numbers refer to the track-changes word document. In particular, we have made substantial additions to our discussion of our results, which we think has made our presentation and interpretation of our results clearer.

1) Our first main reservation was that the text should distinguish better what is new vs what is known throughout the paper. As an example, line 28-29 of the abstract is particularly ambiguous.

We agree that we could have made clearer which aspects of our results are novel, particularly in the abstract. While our study represents the largest comparative genomic study of CC398 isolates to date, allowing for more accurate characterisation of MGE carriage and dating of transitions, the greatest novelty of our study lies in our reconstruction of the evolutionary dynamics of the MGEs associated with the transition to livestock. We have now amended the manuscript in several places (including the abstract) to make this clearer through better referencing of previous work on CC398 and these MGEs (lines 26-30, 100-105, 199-201, 448-453, 482-500, 515-518, 522-533, 598-601).

2) The second main reservation was the headline conclusion in the title -- that human re-adaptation (acquisition of human immune evasion genes by livestock-associated CC398s) outpaces loss of antibiotic resistance -- can be argued on first principles. From that perspective, it would appear to lack novelty.

We agree that our interpretation of our results could have been more nuanced and have included more consideration of the mechanisms and selective pressures that may have led to the dynamics we identify. However, we don’t agree that our finding that adaptation to the human host occurs more rapidly than the loss of resistance can be argued from first principles.

In particular, MGEs carrying resistance genes often have fitness costs (e.g. Starikova et al., 2013 DOI:10.1093/jac/dkt270) (now noted in lines 527-529). Accurate predictions of the costs of MGEs are also difficult. This is in part because most studies of their impact on fitness are based on experimental (and often in vitro) assays, and these cannot fully replicate the selective pressures experienced by natural populations. Fitness costs can also vary across different bacterial hosts. In particular, the fitness costs of MGEs may be mitigated over time (lines 527-529), and therefore our finding that Tn916 and SCCmec types V and IV have been maintained by livestock-associated CC398 over long periods may suggest that CC398 has evolved to mitigate costs associated with carriage of these MGEs.

A recent smaller-scale study (that didn’t fully correct for the impact of phylogenetic structure on their comparisons) came to the opposite conclusion to ours (Sieber et al., 2019; DOI:10.1038/s41598-019-55086-x) (lines 448-450). They concluded that transmission from pigs to humans is both associated with the loss of antibiotic resistance genes and the acquisition of human immune evasion genes. In reference to resistance genes, the authors concluded that ‘the genes are likely lost because they do not provide a fitness advantage in absence of the corresponding antimicrobial compounds in the human hosts’. The fact that this conclusion was drawn by authors who are experts in this field suggests that our findings are indeed novel.

In addition, the degree of selective benefit obtained from acquisition of the Sa3 prophage is not entirely clear. While these prophages are common in human Staphylococcus aureus strains and are associated with increased virulence, they are not essential for human nasal colonisation (Verkaik et al., 2011 DOI:10.1111/j.1469-0691.2010.03227.x).

Despite this, we agree that our title unnecessarily implied an equivalence in the evolutionary trajectories of the MGEs we are describing. We have therefore modified our title and added substantially to our discussion and interpretation of the dynamics we identify.

3) A third point of discussion was an apples-and-oranges argument about comparing different MGE types. We felt that since they are fundamentally different and known to come and go at different rates, that this should be acknowledged with references. That is not to say there is no value to empirically quantifying those differences on timescales relevant to the evolution of CC398, and to discussing the implications for the turnover of the different AMR genes they carry.

My inclination is that the new analyses of MGE dynamics (how often known CC398-associated MGEs have come and gone, and the dates of these events) probably add sufficient novelty to warrant publication in eLife, but as currently presented that is not certain. I would welcome a revision that focuses on addressing this point.

We agree that our interpretation of our results should have included discussion of the different types of MGEs, as type influences short-term rates of acquisition and loss. As suggested, we have now added a paragraph to our discussion that directly addresses this point (lines 482-500), and greater context to our discussion of the dynamics of individual MGEs.

Nevertheless, we consider that there is considerable value in quantifying the long-term dynamics of these MGEs within CC398, independently of their type. Differences between these short-term and our long-term dynamics will reflect MGEs selective benefits/costs/availability. The long-term dynamics are important for understanding and predicting the evolution of the traits associated with the carriage of these MGEs. It is long-term dynamics that can inform predictions of how these traits are likely to be influenced by changes in the environment of CC398, such as host jumps or changes in the use of antibiotics in farming. Our current understanding of the long-term dynamics of MGEs, are how they are gained and lost in natural populations is extremely limited and we think our study develops a creative approach to uncovering these dynamics. Our amended discussion reflects on this point.

Reviewer #2 (Recommendations for the authors):

I find that the comparison made in the title potentially a false equivalence between the evolutionary mechanisms driving gain/loss of pathogenicity genes, and gain/loss of resistance, for a few reasons. One, loss of resistance genes first requires that the 'mutation' leading to loss of resistance occurs, then lineages with that loss are selectively favoured. In contrast, (re)acquisition of the pathogenicity genes, which are already present in the wider population/community of bacteria, is much more likely to occur and then be selectively favoured. It is thus hard to envision a scenario where adaptive evolution for pathogenicity would ever be expected to outpace adaptive loss of resistance, unless the fitness costs of resistance are extremely high. I think the analysis and data stand on their own without having to force this comparison

We agree with the reviewer that our title could be interpreted as suggesting an equivalence in the processes and/or drivers of gain of pathogenicity genes and loss of resistance genes. As the reviewer notes, there are several factors that will influence the dynamics of these MGEs along a bacterial lineage, including those that influence the chance of random gain/loss of the MGE and the selective benefit/cost of this.

While we may expect (based on experiments, theory and observations of nature) that the selective benefit of losing MGEs carrying resistance genes in the absence of treatment is less than the benefit of acquiring MGEs carrying human-adaptive genes when moving into the human host, our results reveal how these predictions relate to the actual dynamics of these MGEs within CC398 as it moves between different host groups.

MGEs carrying resistance genes are often associated with fitness costs, and these costs can be host (and even insertion locus) specific (e.g. Starikova et al., 2013 DOI:10.1093/jac/dkt270) (now noted in lines 527-530). Accurate predictions of the costs of MGEs are made more difficult because most studies of their fitness costs are based on experimental (and often in vitro) assays, and these cannot fully replicate the selective pressures experienced by natural populations. It has also been suggested that the fitness costs of MGEs are likely to be mitigated over time (lines 527-530), and therefore our finding that particular MGEs have been maintained by livestock-associated CC398 over long periods may be informative because they predict that CC398 has evolved to mitigate the costs associated with carriage of these MGEs. Nevertheless, this cost could still vary across host species. For instance, it could be the case that CC398 experiences greater competition with resident populations of Staphylococcus aureus in a human host, and therefore that the cost carriage of MGEs carrying resistance genes may be greater in humans than in livestock.

Sieber et al., (2019; DOI:10.1038/s41598-019-55086-x) compared the genomes of livestock-associated CC398 isolates sampled from human and pigs, and they concluded that transmission from pigs to humans is both associated with the loss of antibiotic resistance genes and the acquisition of human immune evasion genes. In reference to resistance genes, the authors concluded that ‘the genes are likely lost because they do not provide a fitness advantage in absence of the corresponding antimicrobial compounds in the human hosts’. This study had a smaller sample size (256 isolates) than ours, only included human and pig isolates, and compared human and pig isolates using a method that did not fully correct for phylogenetic structure. While our results are therefore not entirely comparable, we consider our results to be more robust than those of this previous study. However, the fact that this conclusion was drawn by authors who are experts in this field suggests that our findings are not entirely anticipated. We have added a reference to the results of this previous study to our manuscript (lines 448-450).

Nevertheless, we agree with the reviewer that the selection for loss of the MGEs carrying resistance genes in the absence of treatment is unlikely to be as strong as selection for acquisition of the MGEs carrying host-adaptive genes, and we have therefore modified our title so that we don’t imply a potentially false equivalence regarding the selective pressures on their carriage.

Two, for an expectation that a 'thing' might be lost, its carriage should be associated with a fitness cost. While this is touched on, I would like to see more discussion about whether Tn916 is likely to carry a cost, otherwise its stable maintenance is the rule rather than the exception. Also, are there estimates about how easily Tn916 can be lost? Does it not drive its own reacquisition if an excision event is to occur?

We have substantially expanded our discussion of the Tn916 element (lines 502-533). In particular, we have added discussion about how its regulation may both mitigate its cost and promote its maintenance. While this may predict the stability of Tn916, this prediction does not hold for all bacterial species (such as Streptococcus pnuemoniae; D’Aeth et al., 2021) and therefore these mechanisms alone cannot explain or predict the maintenance of Tn916 in CC398. We also discuss the likelihood that this element provides a strong selective benefit for CC398 in livestock due to the high levels of usage of tetracyclines, and how this element is observed across a wide range of bacterial species, including other opportunistic pathogens in the respiratory tract of pigs, and other S. aureus CCs. The latter suggests that the stability is not a consequence of the rarity of the element, as the element is likely to be present in other bacteria in the environment of CC398. Although it could instead reflect the rarity of successful interspecies transfers.

We have also added a section that describes the results of experimental studies of the dynamics of the Tn916 transposon (and other MGEs) (lines 482-500). We report how these studies have found that transposons are more stably maintained (and less frequently transferred) than other types of MGEs. In particular, one study found that the Tn916 in CC398 was stably inherited (and not transferred to other cells) over the course of a 16-day in vitro experiment. Nevertheless, the SCCmec and the φSa3 prophage were also stably maintained over the course of this experiment (while other prophages and plasmids were more dynamically gained and lost) (McCarthy et al., 2014). Therefore, while these short-term dynamics will likely influence the long-term dynamics we describe, other factors will also be important, and the long-term dynamics within a particular bacterial lineage cannot be predicted solely by transmission mechanism.

Three, prophages, plasmids and transposons likely have different rates of gain/loss. This has been experimentally demonstrated by an excellent study from the group of Prof Jodi Lindsey (McCarthy et al., 2014, Genome Biology and Evolution, doi: 10.1093/gbe/evu214). Transfer of some MGEs was observed within 4 hours, whereas transfer of Tn916 was not observed within 16 days. I think it may lead to misleading comparisons to lump different types of MGEs together, as their gain/loss dynamics can differ significantly.

We agree that in addition to differences in their selective benefit/cost different types of mobile genetic elements may differ in their dynamics due to differences in their mechanism of transfer. Nevertheless, our understanding of how these differences translate into long-term dynamics in natural populations is lacking in most cases, and studies such as ours can shed light on this. In the study undertaken by McCarthy et al., (2014), the Tn916 element was not transferred during the 16 day experiment, but neither was the type V SCCmec or the Sa3 prophage. This suggests that all three of these elements are more intrinsically stable than other MGEs carried by CC398 isolates. This may, in part, explain the stability of all three of these elements in CC398 compared to other MGEs.

Other studies have, however, found that transposons tend to be more stable and less frequently transferred than prophages, and this difference could influence the long-term dynamics of these MGEs in CC398. These dynamics cannot, however, predict the long-term dynamics we identify. These long-term dynamics in a real population will be strongly influenced by both natural selection (both costs and benefits) and the availability of MGEs for acquisition by CC398. Therefore, despite what is known about short-term transmission dynamics of these MGEs, our study provides a unique insight into the longer-term dynamics these MGEs within CC398.

We agree with the reviewer that we ought to have related our results more to what is known of the dynamics of these elements over shorter time periods, and in laboratory conditions. We have therefore substantially expanded our discussion through the addition of a paragraph addressing this point (lines 482-500), and additions to our discussions of individual MGEs.

I would thus like to see an expanded discussion (i.e. more than just supposition) about estimated costs of SCCmec and phiSa3, or estimated benefits of (re-)acquiring these when selectively advantageous, and also what might be driving the replacement of Type V with other types. Also on relative rates of gain/loss events for the different categories of MGEs here. I would also recommend altering the title, as I do not find the comparison made there compelling, but that might be excessive.

We have provided a significantly expanded discussion which we hope addresses your concerns. We have tried to select the most relevant aspects of the literature on these three categories of elements to put our results in context, as there is a lot to discuss about each of these three elements. We have also amended our title, as you have suggested, so that we don’t suggest an equivalence between the drivers of the dynamics of these MGEs. We hope that we have satisfied you that the dynamics we describe are both interesting and important.

Reviewer #3 (Recommendations for the authors):

In general, this manuscript is very well done and as mentioned in the public review, of high quality for the reader. It is in my eyes very close to be ready for publication if accepted, and I only have a few comments. Important, however, is the fact that the novelty in the manuscript is very limited because most results have been published earlier in the studies on the original datasets which are used here.

We would like to thank the reviewer for their positive assessment of our study and for their useful suggestions. We have provided a point-by-point response to their comments below. Page and line numbers refer to the word document with tracked changes.

We appreciate that we could have made it clearer which aspects of our results are novel. As our study is the largest comparative genomic analysis of CC398 isolates to date, it has allowed us to confirm previous described associations between MGEs and the transition of CC398 to livestock and allowed for more accurate dating of the emergence of CC398 in livestock. Nevertheless, the novelty of our study lies in our reconstruction of the evolutionary dynamics of the MGEs associated with the transition to livestock, which has never been done before. We have amended the manuscript in several places to make this clearer through better referencing of previous work on CC398 and these MGEs (lines 26-30, 100-105, 199-201, 448-453, 482-500, 515-518, 522-533, 598-601).

I only have a few comments:

General comments:

– Do you have any hypothesis on why ΦSa3 phages frequently are re-introduced and where from, as compared to other elements?

ΦSa3 prophages are common in human-associated S. aureus populations, and therefore it seems likely that when livestock-associated CC398 isolates are transmitted to humans they acquire them from other S. aureus CCs within the human host. The loss and reacquisition within human-associated CC398 could also result from occasional transmission between lineages that carry different ΦSa3 prophages when they co-colonise the same host. What is known about these elements suggests that they are only associated with S. aureus, and so their diversity and dynamics may reflect the large and diverse population of S. aureus that colonises human hosts (lines 598-601).

There is evidence that SCCmec has a larger host range, as it has been found more widely across staphylococci species. It is therefore possible that SCCmec acquisitions may originate from either other S. aureus lineages or from other staphylococci species. SCCmec type IV is associated with human community-associated S. aureus populations, and therefore might be acquired by livestock-associated CC398 when it moves through the human population (lines 571-578).

Tn916 has an even larger host range. It has been found across several bacterial genera (lines 515-518). This makes it very difficult to determine where CC398 acquired its Tn916 element from.

Specific comments:

– Line 62 and Table S1: Sieber et al., 2019 should be Sieber et al., 2018, mBio.

Thank you for observing this error. We’ve now corrected this (line 83).

– Line 110: space missing before "(Ward et al., 2014)".

We’ve now corrected this (line 147).

– Line 275: "that integrate into the hlb gene of S. aureus": There is strong evidence that the ΦSa3 phages integrate at other positions in LA-MRSA CC398. See e.g. Leinweber et al., 2021 (mBio) for a recent publication.

Thank you for this correction. We have amended this to note that this is the primary integration site (line 343). In most, but not all, of our isolates carrying the Sa3 prophage we see evidence of insertion into the hlb gene.

– Line 276: change "88% of our human-associated CC398 isolates" to "88% of the human-associated isolates in our collection".

We’ve corrected this (lines 344-345).

– Lines 356-359: These results differ from what Sieber et al., 2019 found. Can you discuss this?

We have now mentioned this difference in our manuscript (lines 448-450). Our analysis differs from the one undertaken by Sieber et al., as it includes a larger number of isolates, isolates from livestock species other than pigs, and isolates from across a wider geographic range. In addition, due to the larger number of isolates in our collection, we were able to use an approach that better corrects for phylogenetic structure (comparing 70 phylogenetically independent pairs of isolates from human and livestock species). This means that our results are likely to be more robust than those of Sieber et al., 2019. While Sieber et al., 2019 considered patterns across three lineages (plus the remainder), they did not always observe consistent patterns of the loss of resistance genes across these independent lineages, and even when a consistent pattern was observed, the small number of independent comparisons means that these patterns may have arisen by chance.

– Lines 416-418: This should be explained more precisely. Why are these dynamics consistent with these traits?

We agree that this statement was unclear. We’ve now expanded on this statement, hopefully answering the reviewer’s question (lines 575-580). In short, the fact that the type V SCCmec has been replaced several times with type IV SCCmec, and that lineages carrying type IV SCCmec have persisted over several years (in parallel with those carrying type V), suggest that this replacement is not associated with a significant reduction in fitness. Multiple acquisitions of the type IV element and only a single acquisition of the type V element also suggests that the type IV element might be more common in the environments encountered by CC398.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524650
    2. Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524328
    3. Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524354
    4. Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524446
    5. Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524562
    6. Gonçalves da Silva A. 2017. Emergence of CC398 MRSA in New Zealand. NCBI BioProject. PRJEB12552
    7. Fox et al. 2017. Detection and molecular characterisation of Livestock-Associated MRSA in raw meat on retail sale in North West England. NCBI BioProject. PRJEB18725 [DOI] [PubMed]
    8. He et al. 2018. Staphylococcus aureus CC398 resequencing data. NCBI BioProject. PRJNA347471
    9. Heikinheimo et al. 2016. Studying 3 strains of LA-MRSA from Finland with interesting deletion genotypes. NCBI BioProject. PRJEB14187
    10. Himsworth et al. 2014. MRSA from rats and humans isolated from the Downtown Eastside of Vancouver, BC, Canada. NCBI BioProject. PRJEB5042
    11. Islam et al. 2017. Prevalence and origin of LA-MRSA CC398 in Danish horses. NCBI BioProject. PRJEB19362
    12. Larsen et al. 2016. Staphylococcus aureus . NCBI BioProject. PRJNA226567
    13. Lowder and Fitzgerald 2018. poultry-associated genetic elements in Staphylococcus aureus. NCBI BioProject. PRJNA312437
    14. Makarova et al. 2017. Staphylococcus aureus strain 08S00974 chromosome, complete genome. NCBI GenBank. PRJNA378150
    15. Moller et al. 2019. Unusual MRSA CC398 hospital outbreak. NCBI BioProject. PRJNA508272
    16. Paterson et al. 2013. Diversity_of_MRSA. NCBI BioProject. PRJEB2655
    17. Holmes 2018. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI BioProject. PRJEB21015
    18. Price et al. 2012. Staphylococcus aureus CC398: host adaptation and emergence of methicillin resistance in livestock. NCBI BioProject. PRJNA274898 [DOI] [PMC free article] [PubMed]
    19. Ronco et al. 2018. Staphylococcus aureus Raw sequence reads. NCBI BioProject. PRJNA430150
    20. Sharma et al. 2016. LA-MRSA CC398 from UK animals. NCBI BioProject. PRJEB14251
    21. Sieber et al. 2019. Spread of LA-MRSA CC398 in pigs and humans in Denmark. NCBI BioProject. PRJEB25608
    22. Uhlemann et al. 2017. Sequencing of Staphylococcus aureus CC398 from Northern Manhattan. NCBI BioProject. PRJEB12818
    23. Ward et al. 2014. Global transmission and antibiotic resistance dynamics of Staphylococcus aureus CC398 in humans and livestock revealed by whole genome sequence analysis. NCBI BioProject. PRJEB7209
    24. Warne et al. 2016. Staphylococcus_aureus__MSSA__study. NCBI BioProject. PRJEB2755
    25. Zou et al. 2021. The Staphylocossus aureus isolates from central China. NCBI BioProject. PRJNA660925

    Supplementary Materials

    Supplementary file 1. Strain names, country of origin, source (host species), year, accession numbers, and references for all isolates.
    elife-74819-supp1.xlsx (65KB, xlsx)
    Supplementary file 2. Genes that most strongly distinguish human- and livestock-associated CC398, and their association with mobile genetic elements.

    Our gene identifiers and the gene locations and locus tags in published reference genomes are provided.

    elife-74819-supp2.xls (36KB, xls)
    Supplementary file 3. Description of the presence of mobile genetic elements (MGEs) and annotation of MGE types and clades.

    The presence/absence of genes and MGEs is described by 1/0, and types and clades that are presented in the text are described.

    elife-74819-supp3.xls (329.5KB, xls)
    Supplementary file 4. Description of the genes in the Tn916 element.

    The genes in the Tn916 element used in our analyses are described in the reference genome 1_1439.

    elife-74819-supp4.xls (27.5KB, xls)
    Supplementary file 5. Reference SCCmec elements used in BLAST typing.
    elife-74819-supp5.xls (29KB, xls)
    Supplementary file 6. Description of the genes in the type V SCCmec element.

    The genes in the SCCmec type Vc element used in our analyses are described in the reference genome 12_LA_293.

    elife-74819-supp6.xls (32KB, xls)
    Supplementary file 7. AMR genes identified by PathogenWatch.

    Gene presence/absence is described by 1/0.

    elife-74819-supp7.xls (231KB, xls)
    Transparent reporting form
    elife-74819-transrepform1.docx (111.7KB, docx)

    Data Availability Statement

    The Illumina sequences generated in this study have been deposited in the NCBI short read archive under the accession numbers ERR3524650, ERR3524328, ERR3524354, ERR3524446, and ERR3524562. All other sequences used in this study are publicly available and their origins are described in Supplementary file 1.

    The following datasets were generated:

    Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524650

    Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524328

    Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524354

    Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524446

    Wellcome Sanger Institute 2019. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI Sequence Read Archive. ERR3524562

    The following previously published datasets were used:

    Gonçalves da Silva A. 2017. Emergence of CC398 MRSA in New Zealand. NCBI BioProject. PRJEB12552

    Fox et al. 2017. Detection and molecular characterisation of Livestock-Associated MRSA in raw meat on retail sale in North West England. NCBI BioProject. PRJEB18725

    He et al. 2018. Staphylococcus aureus CC398 resequencing data. NCBI BioProject. PRJNA347471

    Heikinheimo et al. 2016. Studying 3 strains of LA-MRSA from Finland with interesting deletion genotypes. NCBI BioProject. PRJEB14187

    Himsworth et al. 2014. MRSA from rats and humans isolated from the Downtown Eastside of Vancouver, BC, Canada. NCBI BioProject. PRJEB5042

    Islam et al. 2017. Prevalence and origin of LA-MRSA CC398 in Danish horses. NCBI BioProject. PRJEB19362

    Larsen et al. 2016. Staphylococcus aureus . NCBI BioProject. PRJNA226567

    Lowder and Fitzgerald 2018. poultry-associated genetic elements in Staphylococcus aureus. NCBI BioProject. PRJNA312437

    Makarova et al. 2017. Staphylococcus aureus strain 08S00974 chromosome, complete genome. NCBI GenBank. PRJNA378150

    Moller et al. 2019. Unusual MRSA CC398 hospital outbreak. NCBI BioProject. PRJNA508272

    Paterson et al. 2013. Diversity_of_MRSA. NCBI BioProject. PRJEB2655

    Holmes 2018. Tracking_the_dynamics_of_AMR_genes_within_enteric_bacterial_communities_in_pigs_and_humans. NCBI BioProject. PRJEB21015

    Price et al. 2012. Staphylococcus aureus CC398: host adaptation and emergence of methicillin resistance in livestock. NCBI BioProject. PRJNA274898

    Ronco et al. 2018. Staphylococcus aureus Raw sequence reads. NCBI BioProject. PRJNA430150

    Sharma et al. 2016. LA-MRSA CC398 from UK animals. NCBI BioProject. PRJEB14251

    Sieber et al. 2019. Spread of LA-MRSA CC398 in pigs and humans in Denmark. NCBI BioProject. PRJEB25608

    Uhlemann et al. 2017. Sequencing of Staphylococcus aureus CC398 from Northern Manhattan. NCBI BioProject. PRJEB12818

    Ward et al. 2014. Global transmission and antibiotic resistance dynamics of Staphylococcus aureus CC398 in humans and livestock revealed by whole genome sequence analysis. NCBI BioProject. PRJEB7209

    Warne et al. 2016. Staphylococcus_aureus__MSSA__study. NCBI BioProject. PRJEB2755

    Zou et al. 2021. The Staphylocossus aureus isolates from central China. NCBI BioProject. PRJNA660925

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