The nucleotide composition of microbial genomes indicates differential patterns of selection on core and accessory genomes

GC content in core, accessory and whole genomes

To examine differences in nucleotide composition between the coding regions of the core genome, accessory genome and the whole genome (i.e. all genes, including accessory and core genomes) of the 36 species, (Table 1) we fitted a linear mixed-effects model with GC content as the response variable and sequence type (i.e. core, accessory and whole genome) as the explanatory variable (See Additional file 1 for more information regarding the statistical models). The taxonomic ranks of phylum, genus, and species were added as random effects. However, adding phylum as taxonomic level (See Fig. 1) did not result in improved models (p = 0.14, maximum likelihood ratio test) and no association was found between phylum and %GC (p = 0.625, ANOVA) using a phylogenetic regression model adjusting for Brownian motion correlation structure between the branches (See Methods for more details). Including both genus and species as hierarchical random effects resulted in significantly improved models as compared to species only (p = 0.008, maximum likelihood ratio test) therefore all mixed-effects models will henceforth include the two levels genus and species as random effects, but not phylum. The regression model with %GC as the response and intragenic region (i.e. core, accessory or whole genome) as the explanatory variable indicated that GC content was significantly higher (See Figs. 2 and 3 as well as Additional file 2), on average, in the core part of the genome (p < 0.001) than the whole (p < 0.001), and accessory genomes (p < 0.001). The GC content in the accessory part of the genomes was significantly lower than in whole genomes (p < 0.001).

Species	Strains #	Size in mb (full)	Size in mb (accessory)	%GC (code)	%GC (accessory)	%GC (core)
A_baumannii	16	3,9	1,04	40,19	39,67	40,59
A_macleodii	13	4,5	1,03	45,66	44,8	46,05
B_amyloliquefaciens	16	4,01	0,45	47,28	42,39	47,98
B_animalis	12	1,94	0,23	61,36	58,53	61,88
B_cereus	13	5,27	0,81	36,25	34,39	36,77
B_longum	10	2,46	0,61	60,84	59,57	61,61
B_subtilis	12	4,1	0,46	44,71	42,36	45,07
B_thruringiensis	12	5,51	0,88	36,23	34,91	36,59
Brucella_spp	20	3,3	0,16	58,36	56,9	58,45
C_botulinum	10	3,95	0,43	29,48	28,6	29,66
C_diphtheria	13	2,47	0,31	54,15	53,42	54,3
C_jejuni	16	1,67	0,27	31,05	30,22	31,25
C_pseudotuberculosis	15	2,32	0,11	52,93	52,16	52,97
C_psitacci	10	1,16	0,04	39,76	39,47	39,74
C_trachomatis	78	1,04	0,01	41,78	42,34	41,77
E_coli	62	5,01	1,51	51,79	50,35	52,58
F_tularensis	12	1,9	0,14	33,08	31,53	33,21
H_influenza	10	1,9	0,3	38,97	39,4	38,92
H_pylori	53	1,62	0,29	39,64	36,93	40,31
L_lactis	11	2,45	0,53	36,86	35,32	37,14
L_monocytogenes	30	2,93	0,3	38,66	38,84	39,01
L_pneumophila	12	3,33	0,7	39,12	38,03	39,48
M_gallisepticum	12	0,97	0,05	32,65	31,64	32,69
M_tuberculosis	23	4,4	0,36	65,86	68,13	65,49
N_meningitidis	14	2,22	0,26	53,09	47	54,2
P_acnes	10	2,51	0,17	60,30	59,06	60,4
P_aeruginosa	18	6,43	0,89	66,96	66,03	67,26
R_prowazekii	10	1,11	0,01	30,58	27,57	30,61
S_aureus	49	2,82	0,28	33,78	32,08	33,99
S_enterica	42	4,78	0,64	53,34	50,2	53,92
S_islandicus	10	2,65	0,37	35,76	36,43	35,74
S_pneumoniae	27	2,11	0,26	40,73	36,07	41,5
S_pyogenes	19	1,85	0,23	39,38	37,95	39,63
S_suis	18	2,09	0,4	42,11	39,42	42,97
T_pallidum	11	1,14	0,01	52,60	56,63	52,55
Y_pestis	12	4,58	0,28	48,92	49	48,9

Base composition and bias

To further explore whether the base composition of core and corresponding accessory genomes were subjected to different selective pressures we used the concept of relative entropy [9]. This measure indicates whether genomic oligonucleotide patterns, such as codons, are observed more or less often than expected from genomic mononucleotide frequencies (i.e. AT/GC content). High relative entropy indicates a great distance between observed- and expected oligonucleotide frequencies, suggesting that the oligonucleotide frequencies are biased, most likely due to selection or putative selective neutral forces [31, 32]. Loosely speaking, low relative entropy points to more randomly distributed oligonucleotide frequencies, something that would be expected in a DNA sequence that has undergone genetic drift [9]. Examining differences in relative entropy between intragenic core, accessory and whole genomes, using an identical mixed-effects regression model to the one based on GC content discussed above, but with relative entropy as the response rather than GC content, we found significantly higher relative entropy in the core part of the genome as compared to the whole- (p < 0.001) and accessory genomes (p < 0.001). Genome-wide relative entropy was significantly higher than in the accessory part of the genomes (p < 0.001) (Fig. 4 and Additional file 3).

GC content variation differences between genetic regions

Changing the response variable of the mixed-effects regression model described above to within-genome GC content variation, referred to as GCVAR [2], we found that the core genome exhibited significantly lower GCVAR than the corresponding accessory (p < 0.001) and whole genomes (p < 0.001). Genome-wide GCVAR was, in turn, significantly lower than accessory genome GCVAR (p < 0.001). This indicates that, on average, GC content varies significantly less within the core parts of the coding genome than in the rest (Fig. 5 and Additional file 4). Lower GCVAR has also previously been associated with increased selective constraints [37] as a lower variation in GC content may be an indication of purifying selection acting on base composition. Genome-wide GCVAR was significantly lower than for accessory genomes (p < 0.001) [29].

Oligonucleotide- and GC content bias in core, accessory and whole coding genomes

It has been shown that genome homogeneity in prokaryotes, as measured using oligonucleotide frequencies, is associated with genomic %GC [45]. In other words, the more GC rich the genome the more similar the oligonucleotide usage appears to be. As has been previously observed [9], we find a relatively weak correlation, using mixed-effects linear regression models with taxonomy as the random effect, between GC content and relative entropy on the accessory part of the genomes (p = 0.005), but not on the corresponding core (p = 0.19) or whole genome regions (p = 0.45). A positive correlation between relative entropy and GC content in the accessory part of the genomes (See Additional file 5) may support gBGC and/or amelioration as the accessory genome is presumably more mobile than the core genome implying that the accessory genes have, on average, been subjected to considerably more frequent recombination events [12]. In this regard, it is interesting to note that an association between GC content and codon bias is predicted to result from gBGC [31].

Exceptions to the observed trends

The majority of species discussed here did adhere to the tendency that GC content and relative entropy was higher, and GCVAR lower, in the core genomes, compared to the corresponding accessory genomes and whole genomes. There were however some species were such differences were negligible or even reversed in one or all the measures considered. These species were typically pathogens associated with an intracellular lifestyle like Rickettsia prowazekii, Mycobacterium tuberculosis, Chlamydia spp., Treponema pallidum, Mycoplasma gallisepticum and Francisella tularensis [29]. In addition to the intracellular pathogens the free-living pathogens Haemophilus influenzae, Clostridium botulinum as well as the extremophile archaeon Sulfolobus islandicus exhibited some deviance from the common trend of higher core genome GC content and relative entropy in addition to lower GCVAR. These strains possessed large core genomes with a median fraction of 97% of the genome being classified as core versus 83% of the other species (p < 0.001, Wilcoxon rank sum test). Core genome GC content was higher in 608 out of 731 strains, core genome relative entropy was higher in 721 strains and GCVAR was lower in the core genomes of 677 strains, all compared with the respective measures applied on the corresponding genome-wide regions (See Additional file 6 for more information).

Influence of selective pressures on base composition

As mutations in bacteria are AT-biased [22] it has not been obvious how GC rich microbes can exist. The retention of more energetically expensive and nitrogen-heavy guanine and cytosine nucleotides across core genomes suggests that selective pressures are at work, but identifying and classifying these processes is challenging. Our findings seem to indicate that core genome GC content is conserved by purifying selection, as microbial core genomes must over time have been subjected to stronger purifying selection than the rest of the genome and certainly the more mobile genes of the accessory genomes [41, 44]. Contrarily, in recently emerged clonal strains, traces of purifying selection are in fact more dominant in the accessory part of the genomes due to the transfer of mobile genes from other organisms that have already purged them of fitness-decreasing de novo mutations [12]. Thus, in such clonal strains, purifying selection has not had the opportunity to remove recently emerged de novo mutations from the core genome, quite the opposite of what is observed between phylogenetically more diverse strains [12]. The strains included in the present study are predominantly inter-clonal and therefore it is presumed that purifying selection dominates the core genomes and that the accessory genomes are marked by recombination events and having been subjected to vastly different selective pressures than the corresponding core genomes [12, 36]. Our results seem to indicate that this is expressed as greater variance in %GC, lower relative entropy, and higher GCVAR in the accessory genomes of each species’ strains, as compared to the corresponding core genomes and genome-wide, where the variation between strains is remarkably similar, as can be observed in Figs. 2, 3, 4 and 5 (and Additional files 2, 3, 4 and 5).

Since mutations in bacteria are AT-biased, the purging of deleterious mutations in the core genome may act to conserve GC content as compared to the rest of the genome [42]. Moreover, as the accessory genome may be subjected to weaker selective forces than the core genome, one might assume that fitness decreasing mutations are better tolerated in the non-core parts of the genome [42]. Two recent studies [8, 26] may also provide important pieces to the puzzle of how microbial genomes can maintain GC-richness. Chen et al. demonstrated that AT rich codons are translated into more energy requiring amino acids than GC rich codons. Thus, there appears to be a selective trade-off between energy requiring amino acids and nucleotides, respectively, so that genomic GC richness is maintained or, in some circumstances, even increased. Seward and Kelly provided further evidence that increased environmental nitrogen abundance can affect base composition in the direction of higher GC content [8, 46].

The influence of selectively neutral processes on base composition

Apart from selection, selectively neutral processes may also be involved in shaping genomic GC content. One such process, namely gBGC, has been observed in mammals [47] and appears to be widespread in eukaryotes [48]. A recent study now provides evidence of gBGC in bacteria and archaea [31]. Another, putative selective neutral process, referred to as amelioration, was described by Lawrence and Ochman in 1997 [32]. This process could be at work in many prokaryotes having taken up DNA from phylogenetically distant sources. The concept of amelioration, in short, asserts that foreign DNA integrated into a host chromosome, having a substantially different base composition, will eventually attain a progressively more similar base composition to that of the host chromosome. The exact details regarding this process are not completely understood, but the process of amelioration has been noted in several instances [3, 9, 49–53].

Foreign DNA sequences, like phages and plasmids, are often more AT rich than the host chromosome [6, 27]. If the base composition of integrated foreign DNA is becoming progressively more similar to that of the host chromosome, as is hypothesized by the process of amelioration, this would in many instances imply that the foreign DNA is becoming gradually more GC rich. Since gBGC is assumed to increase GC content in recombined DNA it could, in principle, mean that the process of gBGC is related to amelioration (or vice versa). As the effects attributed to these processes are presumed to be weak, they might also be confounded by selection [1, 32, 36, 37]. Indeed, the positive correlation we observed between %GC and relative entropy in the accessory genomes appears to advocate selective neutral processes, such as gBGC or amelioration. However, we would expect the impact of such processes to decrease in influence with progressively more GC-rich genomes, but this is not supported by our findings, which are largely linear, indicating no change (See Additional file 5).

Environment and phylogeny

In summary, our statistical models suggest that genomic base composition in prokaryotes is strongly affected by a phylogenetic “inertia” at the species level, less so at the genus level and significantly not at the phylum level and above (Fig. 1). Population size may mediate selective pressures through this phylogenetic “inertia” in the sense of genome streamlining [54] due to high population density, through Muller’s ratchet [55] if the population density is low, or through other capacities set by the environment [36]. Selection for energetically expensive nucleotides and/or amino acids is, on the other hand, predominantly driven by the environment, affecting both positive and negative selection. Phylogeny and environment will thus both contribute to the effect that recombination has on microbial populations, which in turn will have a spiraling impact on genomic base composition. Following this line of reasoning, the increased %GC we find in the majority of prokaryotic core genomes seems to be maintained by phylogenetic inertia while the more varied and AT rich base composition in the corresponding accessory and non-core parts of the genome may be more influenced by the environment and the base composition of other hosts. Indeed, the species with core genome %GC and relative entropy similar to or lower, and GCVAR higher, than the non-core genome were mostly intracellular suggesting that recombination and genetic exchange with other microbes is less frequent than that of the other species [29], something that was also apparent by the significantly larger core genomes in these species. Deleterious de novo mutations and horizontally acquired defective genes are purged through purifying selection over time, the degree to which may be, amongst other factors, determined by effective population size, which is small for intracellular microbes [29, 56]. As both uptake of phages and mutations are AT-biased, removal or purging of such genetic regions will thus, in most instances, retain genomic %GC. So will homologous recombination, and it is these processes we believe dominate the differences in base composition we observe between core and corresponding accessory genomes. Our results cannot conclude whether neutral selective processes, such as gBGC and/or amelioration, or selection are more pronounced in the accessory genomes. While the strength of both positive and negative selection will vary between species and environments, the effects of selective neutral processes should remain, more or less, constant between environments but vary between species [36]. Hence, the relative strengths of selective and neutral processes on prokaryotic species depend on both phylogenetic and environmental factors and will hopefully be illuminated further in the time to come.