DNA Repair Is Associated with Information Content in Bacteria, Archaea, and DNA Viruses

16 Pages·2015·3.71 MB·English

Journal of Heredity, 2015, 644–659
doi:10.1093/jhered/esv055
Original Article
Advance Access publication August 29, 2015
Original Article
DNA Repair Is Associated with Information
Content in Bacteria, Archaea, and DNA Viruses
Sharlene Acosta, Miguelina Carela, Aurian Garcia-Gonzalez,
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Mariela Gines, Luis Vicens, Ricardo Cruet, and Steven E. Massey w
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From the Department of Biology, University of Puerto Rico—Rio Piedras, PO Box 23360, San Juan 00931, Puerto Rico d
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(Acosta, Carela, Garcia-Gonzalez, Gines, Vicens, Cruet, and Massey). fro
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Address correspondence to Steven E. Massey at the address above, or e-mail: [email protected]. h
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Received February 23, 2015; First decision May 6, 2015; Accepted July 7, 2015. s://a
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Corresponding Editor: Jose Lopez a
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Abstract .o
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The concept of a “proteomic constraint” proposes that DNA repair capacity is positively correlated .c
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with the information content of a genome, which can be approximated to the size of the proteome m
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(P). This in turn implies that DNA repair genes are more likely to be present in genomes with larger e
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values of P. This stands in contrast to the common assumption that informational genes have a d
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core function and so are evenly distributed across organisms. We examined the presence/absence rtic
of 18 DNA repair genes in bacterial genomes. A positive relationship between gene presence and le
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P was observed for 17 genes in the total dataset, and 16 genes when only nonintracellular bacteria b
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were examined. A marked reduction of DNA repair genes was observed in intracellular bacteria, tra
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consistent with their reduced value of P. We also examined archaeal and DNA virus genomes, t/1
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and show that the presence of DNA repair genes is likewise related to a larger value of P. In 6
/5
addition, the products of the bacterial genes mutY, vsr, and ndk, involved in the correction of GC/ /6
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AT mutations, are strongly associated with reduced genome GC content. We therefore propose 4/2
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that a reduction in information content leads to a loss of DNA repair genes and indirectly to a 6
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reduction in genome GC content in bacteria by exposure to the underlying AT mutation bias. The 03
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reduction in P may also indirectly lead to the increase in substitution rates observed in intracellular b
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bacteria via loss of DNA repair genes. g
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Subject areas: Genomics and gene mapping; Bioinformatics and computational genetics t on
Key words: DNA repair, GC content, genome size, information content, proteomic constraint 04
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ril 2
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The concept of a “proteomic constraint” proposes that modulators pressure should be reflected in a greater number and complexity of 9
of mutation rates such as DNA repair genes are subject to a selection DNA repair genes and mechanisms. The presence of a selection pres-
pressure proportional to the amount of information in a genome, sure to reduce mutation rates can be observed in the suppression of
which can be approximated to the size of the proteome (total num- elevated mutation rates in mutator strains of bacteria (Tröbner and
ber of codons/amino acids, P; Massey 2008, 2013; Garcia-Gonzalez Piechocki 1984) and yeast (Herr et al. 2011; Raynes et al. 2011;
et al. 2012, 2013). Essentially, the more sequence specific informa- McDonald et al. 2012). In yeast, this selection pressure has been
tion present in a genome, the greater the size of the mutational target, linked to the mutational load, a product of the number of genes in
which means a greater mutational load, leading to a greater selection the genome (Herr et al. 2011), which is proportional to P. In these
pressure to evolve and maintain DNA repair. This increased selection examples, selection operates indirectly as a second order effect via
© The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: [email protected]
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Journal of Heredity, 2015, Vol. 106, No. 5 645
the increased mutational load to refine enzymes involved in DNA of DNA repair genes across genomes are little understood in either
repair and fidelity. However, there is no known mechanism for selec- multicellular organisms or microbes. Previous work has shown
tion to directly operate on to modulate the size of P, in order to that the presence of mutL, mutS (mismatch repair), mutM, mutY
indirectly refine the properties of these enzymes. (base excision repair) (Garcia-Gonzalez et al. 2012) and recombina-
While selection generally acts to reduce mutation rates there is tion repair genes (Garcia-Gonzalez et al. 2013) are associated with
some evidence of a selective benefit to higher mutation rates in terms increased P in bacteria, consistent with the operation of a proteomic
of increased adaptability in bacteria under specialized scenarios such constraint on replicational fidelity. Here, we examine the distribu-
as antagonistic coevolution between microbes (Chao and Cox 1982; tion of a range of DNA repair genes across the genomes of bacteria,
Pal et al. 2007), pathogenic interaction with a host (Giraud et al. DNA viruses and archaea, and show that a positive relationship with
2001; Denamur et al. 2002; Labat et al. 2005) and long term adapta- P is widespread in microbes.
tion to a new environment (Sniegowski et al. 1997). While the long
term prognosis for the survival of mutator strains is poor (Arjan and
Methods
de Visser 2002), this does not preclude influence on the generation
of beneficial mutations in the short term (Desai and Fisher 2011). Bacteria D
Lastly, Cairns et al. (1988) proposed that organisms might raise their For the analysis, 900 complete bacterial genomes obtained from ow
n
mutation rates in response to selection pressures in order to better the Integrated Microbial Genomes (IMG) database (Joint Genomes lo
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increase adaptability (“adaptive mutagenesis”), however evidence Institute). The following bacterial DNA repair genes were examined, d
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for this is controversial (Brisson 2003). Thus, selection is generally and biases in the types of mutations repaired are noted. These genes d
considered to act to reduce the occurrence of mutations and this can were selected given that they are relatively well characterized experi- fro
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be seen in the diversity of DNA repair, proofreading, and mutation mentally (which allows insights into their mutational biases), and are h
avoidance mechanisms across the 3 domains of life. present in the annotation. Of the base excision repair pathway: mutM ttp
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The idea of a proteomic constraint proposes a fundamental role (8-oxoguanine DNA glycosylase; removes oxidized G, Michaels et al. ://a
for the genomic information quantity in molecular evolution, and 1991), mutY (adenine DNA glycosylase; conversion of A paired to ca
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provides a potential explanation, variously, for the occurrence of oxidized G to a C, Noll et al. 1999), ung (uracil DNA glycosylase; e
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codon reassignments in small genomes (Massey and Garey 2007), removes uracil, Lindahl et al. 1977), nth (endonuclease III; removes ic
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for the inverse relationship between P and mutation rates in a range oxidized T, Demple and Linn 1980), mug (mismatched uracil glycosy- u
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of DNA genomes from viruses to vertebrates (Massey 2008, 2013), lase; excises U from U-G mismatches, Lutsenko and Bhagwat 1999), .c
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for differences in genome wide recombination rates (Massey 2008), nei (endonuclease VIII; removes oxidized pyrimidines, Jiang et al. m
and indirectly for the relationship between elevated genome AT con- 1997). Of the nucleotide excision repair pathway: uvrA, uvrB, and /jhe
tent and a reduction in P in bacteria (Massey 2008; Garcia-Gonzalez uvrC (ultraviolet resistance genes A–C; remove pyrimidine dimers, red
eat  caoln. s2i0d1er2a, t2io0n1 3o)f. Tthhee efvaocltuotri oonf Pof hmasu taalstioo nb ereant eisn cino rmpourlatitceedl liunltaor SmauntcLa,r aanndd m RuutHpp ( t1h9er8e3 i)s. nOoft ath set romnigsm baiatcs hin r tehpea itry ppeast howf mayu:t amtiuotnSs, /article
eukaryotes (Sung et al. 2012, 2013), where it has been proposed repaired; Lahue et al. 1989). Other genes involved in DNA repair -a
b
that effective population size (Ne) is the major factor determining and maintaining DNA fidelity are: vsr (DNA mismatch endonucle- stra
mutation rates, but that P is a cofactor as it constitutes a mutational ase of very short repair; repairs T/G mismatches converting T to C, c
target; this latter prediction is identical to our own earlier proposi- Hennecke et al. 1991), mutT (dGTP pyrophosphohydrolase; removes t/10
6
tion of the role of P in determining mutation rates (Massey 2008). oxidized dGTP, Maki and Sekiguchi 1992), ogt (O6-alkylguanine /5
Intracellular bacteria present an interesting case where the loss DNA alkyl transferase; repairs alkylated G, Vidal et al. 1997), dnaQ /64
4
of DNA repair genes has accompanied a decrease in P (McCutcheon (proofreading epsilon subunit of DNA polymerase III; 3′ → 5′ /2
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and Moran 2012). The reduction in size of P is the result of genomic proofreading, Perrino and Loeb 1989), ndk (nucleoside diphosphate 6
0
simplification due to the intracellular habitat. While a reduced pro- kinase; maintains levels of dNTPs, Almaula et al. 1995, and removes 0
3
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teomic constraint can provide a simple explanation for the loss uracil from U-G and U-A mismatches, Goswami et al. 2006), and ada b
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of DNA repair genes, other explanations such as the operation of (O6-mG-DNA methyltransferase; demethylates methylated G and T, g
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Muller’s ratchet resulting from lack of recombination (Lynch 1996; Demple et al. 1985). e
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Moran 1996) and reduced population sizes (Wernegreen and Moran The presence of each gene in a bacterial genome was deter- t o
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1999) imply a genome wide reduction in selection pressure, which mined manually, initially by use of the IMG compare genomes tool 0
4
may at least partially explain the loss. A more appropriate descrip- (Markowitz et al. 2011), utilizing the genome annotations. Imprecise A
tbiionna tfioorn t hise trhedatu cotfio tnh ein Hseillel–cRtioonb esrttrseonng tehf fdeucte t(oH tilhl ea lnadck R oof breerctosmon- agnennoomtaet ioinn qoure sntaiomne uvsainriga nat sg ewneer ese qreuseonlvcee do bbtya iBnleads tf rsoemar cah irnegla tthede pril 2
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1966), resulting in a reduction in N, and will be used here. An eleva- bacterial genome, using the NCBI taxonomy, utilizing tblastn and 19
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tion in genome AT content is strikingly associated with an intracel- an E value cutoff of e-15. Values of P were determined for each
lular mode of existence and might be explained by the loss of DNA genome, by analysis of the respective Genbank entry, and summa-
repair genes, leading both to a change in mutation bias and an eleva- tion of translation products present on the page. Those genomes that
tion in substitution rates (Burger and Lang 2003; Wernegreen 2005). lacked an annotated gene were also Blast searched. Total genome GC
Previously, we have proposed that the ultimate cause of AT bias and contents were obtained from the NCBI genome reports.
the elevation in substitution rates in these genomes is a reduction The definitions of the different bacterial lifestyles were as follows.
in P, leading to loss of DNA repair genes (Massey 2008; Garcia- “Intracellular” bacteria are bacteria with an obligate intracellular
Gonzalez et al. 2012, 2013). existence within a host cell. “Nonintracellular” are all other bacteria;
The DNA repair capacity (DRC) of a genome is related to the they may live outside a host cell inside host tissue (“extracellular”),
number and efficiency of the DNA repair genes present (Berwick and or without a close association with another organism (“freeliving”).
Vineis 2005), however differences in the distribution and complexity “Pathogenic” bacteria have the ability to act as a pathogen and may
646 Journal of Heredity, 2015, Vol. 106, No. 5
be “host associated” or “opportunistic.” Host associated pathogenic was used and data were of binary form; gene present (1) or absent
bacteria reside within or on a host for at least part of their life- (0). Codistribution patterns of the DNA repair genes across genomes
cycle and typically cause disease, while opportunistic extracellular were analyzed using the Φ coefficient, which calculates the corre-
pathogens may or may not reside in or on a host; in their typical lation in presence between pairs of genes (Garcia-Gonzalez et al.
existence they do not cause disease. “Cyanobacteria” refers to the 2012). Pairwise values were plotted as a heatmap, with codistribu-
bacterial phylum that includes the Prochlorococcus, Synechococcus, tion of genes across genomes indicated by red and antidistribution
Gloeobacter, and Synechocystis genuses. indicated by blue.
Archaea
Results and Discussion
For the analysis, 100 archaeal genomes were obtained from the IMG
database. Archaeal DNA repair is relatively poorly characterized Bacteria
compared with bacteria, the following genes have a role in DNA Correlation of DNA Repair Genes with P
repair in the archaea. Of the base excision repair pathway: mutM, Intracellular bacteria are strongly AT biased (37% AT, Table 1) and
mutY, endonuclease IV (incises DNA strand next to AP sites and have markedly reduced values of P (450 816 amino acids on aver- D
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some oxidized nucleotides, Ljungquist 1977) and endonuclease V age vs. 1 179 835 amino acids for nonintracellular bacteria, Table 1), wn
(incises DNA strand next to deaminated adenines and guanines, and thus their inclusion in the analysis may skew the interpretation loa
Huang et al. 2001). Of the nucleotide excision repair pathway: uvrA, of results. For this reason both the total dataset of 900 bacterial de
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uvrB, uvrC, XPB (Xeroderma pigmentosum factor B, DNA helicase, genomes including intracellular bacteria, and 782 nonintracellular fro
Rouillon and White 2010), XPD (Xeroderma pigmentosum factor bacteria only were examined. Of the total dataset, the presence of m
D, DNA helicase, Rudolf et al. 2010). Of the mismatch repair path- 17 of the 18 DNA repair genes examined was associated with a http
mwarey1: 1m, uatnLd, mhujct.S ,O anthde rm ugetHne. sO ifn rveoclovmedb iinna tDioNn Are preapira: irra dwAe,r era: do5g0t,, gar leaartgeerr avvaelruaeg oef PP (wTaerbel es t1a)t.i sOtifc athlleys sei g1n7i,fi 1c4an otf u tshine ga sthsoec cioatnisoenrsv awtiivthe s://ac
mutT, vsr, and ndk. The presence or absence of DNA repair genes 2-tailed Mann–Whitney test. When nonintracellular bacteria were ad
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was determined as for the bacteria. In the case of imprecise annota- examined, the presence of 16 genes was associated with a larger m
tion, name variants or lack of an annotated gene, Blast searching value of P, 11 of these associations were statistically significant. ic.o
was conducted to establish presence or absence using a sequence Only one gene, nei, was associated with a smaller value of P, in up
obtained from a related archaeal genome, based on the topology of the nonintracellular dataset. Consistent with these observations of .co
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a phylogenetic tree of the archaea (described below). individual genes, a correlation to a power function between P and /jh
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the total number of DNA repair genes present is observed for the re
Nucleocytoplasmic Large DNA Viruses total dataset (Figure 1a, y = 1.03x0.18, r2 = 0.32, p < 2.2e-16). When d/a
For the analysis, 58 nucleocytoplasmic large DNA viruses (NCLDV) 21 recombination repair genes (Garcia-Gonzalez et al. 2013) were rtic
genomes were obtained from Genbank. The number of DNA repair added to the analysis the correlation was strengthened (Figure 1b, le-a
genes in each genome was determined from the genome annotation. y = 0.75x0.25, r2 = 0.46, p < 1e-15). Importantly, when only intracel- b
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For each of these, the closest homolog and its taxonomic affiliation lular bacteria are examined a correlation to a power function is also tra
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was determined by Blast searching the Genbank database using observed (Figure 1c, y = 0.08x0.42, r2 = 0.50, p < 1e-15). The power t/1
tblastn, using an E value cutoff of e-15. functions observed are consistent with that observed between P and 06
mutation rates (μ) in diverse genomes (Massey 2008, 2013), where /5/6
Phylogenetic Inference μ α P−1. Mutation rates may thus be related to proteome size by the 44
Phylogenetic trees were constructed for NCLDVs and archaea, following equation (Massey 2008, 2013): /296
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using Bayesian inference, as follows. The16S rRNA gene was used 0
3
for archaea and the DNA polymerase amino acid sequence for the µ=CP−1 (1) 3 b
NCLDVs. Multiple alignments were constructed using the Muscle y g
program (Edgar 2004) and default parameters. These were used as where C incorporates additional potential factors such as mutational ue
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input to the JModelTest program for DNA sequences (Posada 2008) robustness, recombination rate and N. A refined expression incor- t o
and ProtTest (Guindon and Gascuel 2003, Darriba et al. 2011) for porating these factors is (Massey 2015)e: n 0
amino acid sequences, to identify an appropriate model for the phy- 4 A
logenetic analysis. The best models were selected using the Akaike p
Information Criterion. In the case of the archaea the best model was µ=k(2NeSπP)−1 (2) ril 2
0
GTR + I + Г with values of I = 0.25 and Г = 0.68. In the case of the 1
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NCLDVs the best model was GTR + I + Г with values of I = 0.018 where S is the average selection coefficient of a deleterious mutation,
and Г = 1.32. Bayesian phylogenetic inference was conducted using π is the genomic heterozygosity (per bp), and k is a proportionality
the MrBayes 3.2 program (Ronquist et al. 2012), running the analy- constant. The mutational robustness of a genome is equivalent to the
sis for 5 000 000 generations for the archaea and 1 000 000 for the average deleterious effect of a mutation on an organism (S), which
NCLDVs. In both cases, the first 25% of samples were discarded as has only been calculated for a limited number of organisms (humans,
burn-in, and the last 25% used to construct the consensus tree. Eyre-Walker et al. 2006 and fruit fly, Loewe et al. 2006). The effect
of recombination rate on the strength of selection is described by the
Statistical Analysis Hill–Robertson effect, and may be factored into N. While there is
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Hierarchical cluster analysis was conducted to analyze the distribu- a possibility that P is related to N, and so these 2 factors may not
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tion across genomes of the bacterial and archaeal genes examined be independent, the existing evidence is not supportive, discussed
in the study using the R statistical package. The heatmap.2 package below. In addition, N is not likely to be important, given that N
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Journal of Heredity, 2015, Vol. 106, No. 5 647
Table 1. Relationship of the presence/absence of DNA repair genes with proteome size and GC content in the bacteria
Gene Number of genes absent Mean proteome Mean proteome p Value Mean genome Mean genome p Value
from 900 total genomes size if gene size if gene GC content if GC content if
or 782 genomes from absent present gene absent gene present
nonintracellular bacteria
mutM Total dataset (278) 923 508 1 156 097 1.363e-09 0.45 0.50 1.808e-07
Nonintracellular (217) 1 056 698 1 227 128 9e-06 0.47 0.51 1.4e-05
mutY Total dataset (221) 770 482 1 186 378 <2.2e-16 0.40 0.51 <2.2e-16
Nonintracellular (153) 953 479 1 233 590 1.1e-9 0.43 0.52 <1.6e-13
ung Total dataset (186) 1 019 373 1 101 154 NS 0.51 0.48 0.003
Nonintracellular (161) 1 110 807 1 197 731 NS 0.53 0.49 0.0017
nth Total dataset (158) 1 023 983 1 097 086 NS 0.48 0.48 NS
Nonintracellular (123) 1 177 452 1 192 606 NS 0.52 0.50 NS
vsr Total dataset (696) 997 540 1 380 095 <2.2e-16 0.46 0.56 <2.2e-16 D
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Nonintracellular (583) 1 108 728 1 388 153 2.6e-10 0.48 0.56 3.4e-13 w
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mug Total dataset (696) 1 001 316 1 367 214 3.826e-13 0.47 0.54 2.039e-13 lo
Nonintracellular (584) 1 111 933 1 380 111 1.7e-07 0.49 0.55 7.8e-9 ad
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nei Total dataset (570) 1 092 651 1 069 746 NS 0.49 0.48 NS d
Nonintracellular (473) 1 220 008 1 118 341 0.004 0.51 0.49 NS fro
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mutL Total dataset (151) 948 113 1 111 699 7.884e-06 0.50 0.48 NS
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Nonintracellular (126) 1 083 306 1 197 505 0.0003 0.54 0.49 0.0009 ttp
mutS TNootnailn dtaratacseelltu (l1a1r 4(8)0) 1 918710 393409 11 029597 188009 0N.S00314 00..5508 00..4489 N1.S7e-08 s://a
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MutH Total dataset (751) 1 053 789 1 237 798 4.865e-06 0.49 0.48 NS ad
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Nonintracellular (638) 1 161 979 1 258 947 0.004 0.51 0.48 NS m
uvrA Total dataset (18) 330 821 1 099 629 2.707e-09 0.33 0.49 7.576e-06 ic
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Nonintracellular (3) 1 034 361 1 180 395 NS 0.51 0.50 NS u
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uvrB Total dataset (28) 576 180 1 100 567 4.24e-08 0.34 0.49 4.519e-08 .c
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Nonintracellular (10) 1 173 336 1 179 919 NS 0.47 0.50 NS m
uvrC Total dataset (22) 325 873 1 103 255 4.343e-11 0.31 0.49 1.135e-08 /jh
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Nonintracellular (2) 1 278 328 1 179 583 NS 0.55 0.50 NS re
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mutT Total dataset (327) 930 842 1 171 801 4.188e-11 0.46 0.50 4.515e-05 /a
Nonintracellular (256) 1 079 299 1 228 765 7.3e-05 0.49 0.51 NS rtic
dnaQ Total dataset (254) 1 053 498 1 096 345 NS 0.48 0.48 NS le
Nonintracellular (223) 1 128 086 1 200 479 NS 0.50 0.50 NS -ab
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ndk Total dataset (98) 705 937 1 130 481 6.534e-13 0.39 0.50 6.446e-14 tra
Nonintracellular (68) 886 320 1 207 789 5.6e-7 0.43 0.51 9.4e-07 c
ada Total dataset (260) 726 328 1 229 660 <2.2e-16 0.44 0.50 2.149e-12 t/10
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Nonintracellular (197) 841 678 1 293 710 <2.2e-16 0.47 0.51 1.6e-05 /5
ogt Total dataset (308) 904 149 1 177 955 2.275e-12 0.46 0.49 0.0003082 /6
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Nonintracellular (225) 1 077 604 1 221 131 0.0012 0.50 0.50 NS 4
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NS, not significant. The total dataset of 900 bacterial genomes were examined, of which 782 were nonintracellular bacteria. Proteome size was calculated as 00
described in Methods, and genome GC contents were obtained from the NCBI annotation. The number of genomes that lack each gene are indicated in brackets 33
in the second column. Significance (P) values were generated using a 2-tailed Mann–Whitney test. Shading indicates larger mean proteome size or higher mean by
genome GC content, for a particular gene. g
u
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and S are expected to be inversely related due to the reduction in 666 378, r2 = 0.39, p < 0.006). A similar relationship is also observed t on
the strength of purifying selection resulting from a decrease in N; a with recombination repair genes (Garcia-Gonzalez et al. 2013). The 04
reduction in N therefore would be accompanied by an increasee in relationship is also observed when only intracellular bacteria are Ap
the average deleeteriousness of a mutation (Lynch and Gabriel 1990), examined (Figure 3b, y = 1711x + 317 516, r2 = 0.38, p < 0.007). ril 2
which would be reflected by an increase in S (Massey 2015). This These data imply that more evolutionary conserved genes are more 01
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further weakens the argument made by Sung et al. (2012, 2013) for likely to be absent from smaller proteomes, which can be explained
the primary role of N in determining mutation rates. by the proposed proteomic constraint not being large enough to
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The degree of evolutionary conservation and thus functional exert a sufficient selective constraint to maintain them.
importance of a gene is reflected in the number of genomes in which Hierarchical cluster analysis shows a group of bacterial
it is present. The median number of DNA repair and recombination genomes where many DNA repair genes are absent (Figure 4,
genes in the genomes examined is 25 (Figure 2a), while the numbers indicated). Strikingly, these bacteria are all intracellular and are
of DNA and recombination repair genes present follows a normal comprised of Candidatus Sulcia muelleri GWSS and SMDSEM,
distribution. Most genes are present in the majority of genomes Candidatus Hodgkinia cicadicola, Candidatus Carsonella ruddii,
(Figure 2b), indicating the widespread utility of the majority of the Baumannia cicadellinicola, Wigglesworthia glossinidia, Candidatus
genes in bacteria. When the number of genomes in which a DNA Blochmannia pennsylvanicus, Candidatus Blochmannia floridanus,
repair gene is absent is plotted against the average P when the gene Buchnera aphidicola strains Bp, APS, Sg, Tuc7, 5A and Cc. Notably
is absent, a positive correlation is observed (Figure 3a, y = 634x + Hodgkinia cicadicola possesses the smallest of all values of P in
648 Journal of Heredity, 2015, Vol. 106, No. 5
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Figure 1. The number of DNA repair genes present in a genome versus P. The presence/absence of a DNA repair gene in a genome was plotted against P. tra
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The plots show (a) 18 DNA repair genes in bacteria; (b) 18 DNA repair genes and 21 recombination repair genes in bacteria; (c) 18 DNA repair genes and 21 t/1
recombination genes in intracellular bacteria; (d) 21 DNA repair genes in archaea. The best fit lines were calculated using least squares regression. Intracellular 06
bacteria are highlighted in red. /5
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the dataset (44 467 amino acids), while the other species also have content and of these, 3 associations were statistically significant /2
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extremely reduced values of P (50 921–206 996 amino acids). (ung, mutL, and mutS). The greater number of genes whose absence 0
0
is associated with a higher average genome GC content in the non- 3
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Relationship of DNA Repair Genes with Bacterial GC Content intracellular dataset (7) compared with the total dataset (5) can be by
and Mutation Rates explained by the absence of AT-biased intracellular bacteria in the gu
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The absence of 10 DNA repair genes from the total dataset was nonintracellular dataset. The gene products of mutL and mutS are s
associated with a higher average genome AT content, 8 of these components of the mismatch repair pathway, described as unbiased t on
associations were statistically significant (Table 1). The absence in the literature in terms of the mutations it recognizes (Lahue et al. 04
of 8 genes from the nonintracellular bacteria was associated with 1989). Interestingly, there is evidence that the deletion of MMR can Ap
a higher average genome AT content, 6 of these associations were lead to a GC mutational bias (Lee et al. 2012, Akashi and Yoshikawa ril 2
statistically significant (Table 1). The lower number of genes whose 2013). The deletion of ung is associated with an increase in GC/AT 01
absence is associated with lower average genome GC content in the transitions, however previous work has shown no clear relationship 9
nonintracellular dataset (6) compared with the total dataset (8) can between gene absence and genome GC content (Lucas-Lledó et al.
be explained by the absence of AT-biased intracellular bacteria in the 2011).
total dataset. Most of the differences in average genome GC content Figure 5a shows a weak positive correlation between the pres-
between genomes that possess or lack a gene were <5%, with the ence of both DNA repair and recombination repair genes and
exception of mutY, vsr, mug, and ndk, which were >5% for both genome GC content (r2 = 0.20, p < 1e-15). Interestingly, when
datasets. intracellular bacteria are examined alone the correlation is stronger
In contrast, 5 repair genes from the total dataset were associ- (Figure 5b, r2 = 0.36, p < 6.1e-13). The possibility exists that the
ated with a higher average genome GC content, of which 1 associa- presence/absence of individual genes may only have small individ-
tion was statistically significant (ung). In nonintracellular bacteria, ual effects on genome GC content, and that the cumulative absence
7 repair genes were associated with a higher average genome GC of DNA repair genes may have a cumulative effect. Several studies
Journal of Heredity, 2015, Vol. 106, No. 5 649
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Figure 2. Numbers of DNA and recombination repair genes present in bacterial genomes. Eighteen DNA repair and 21 recombination repair genes were n
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examined. The total numbers of genes present in the bacterial genomes were binned by frequency (a). In addition, the numbers of genomes that possess a a
d
particular gene were binned (b). The best fit lines were calculated using least squares regression. e
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Figure 3. DNA repair gene conservation in bacterial genomes versus average P when gene is absent. The conservation of DNA repair genes was defined as the
number of genomes in which the gene was present, a conserved gene being widely distributed. (a) 18 DNA repair genes in all bacterial genomes; (b) 18 DNA
repair genes in intracellular bacterial genomes; (c) 21 DNA repair genes in archaeal genomes. The best fit lines were calculated using least squares regression.
show an underlying mutational bias towards AT in bacteria (Lind scenario assumes that genome GC content arises largely neutrally,
and Andersson 2008; Hershberg and Petrov 2010; Hildebrand et al. but it is important to note recent evidence that GC content may
2010; Denver et al. 2012; van Leuven and McCutcheon 2012). Thus, have been selected (Hershberg and Petrov 2010; Hildebrand et al.
the fewer genes involved in biased DNA repair that are present in 2010; Raghavan et al. 2012; van Leuven and McCutcheon 2012).
a genome, the more likely that the underlying mutational bias will Neutralist or selectionist ideas of how differences in genome GC
be exposed and reflected in an elevated genome AT content. This content arise are not mutually exclusive. In addition, biased gene
650 Journal of Heredity, 2015, Vol. 106, No. 5
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Figure 4. Hierarchical cluster analysis showing the distribution of DNA repair genes across bacterial genomes. Rows represent genomes, and columns represent ic
genes. Black denotes the absence of a gene in a genome, and gray indicates presence. The clustering of columns uses the complete linkage method. The dots .o
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on the right hand side of the figure shows if a genome belongs to an intracellular bacterium. Red (gray) highlight indicates a subset of bacteria that are missing p
a large proportion of DNA repair genes. .co
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Figure 5. Relationship of the numbers of DNA and recombination repair genes present in bacterial genomes to genome GC content. Eighteen DNA repair and 21 t o
recombination repair genes are plotted against P in (a) bacteria, intracellular bacteria are indicated in red (gray); (b) intracellular bacteria only. The best fit lines n
0
were calculated using least squares regression. 4
A
p
conversion has been proposed to influence genome GC content in that are treated as independent data points, due to “phylogenetic iner- ril 2
0
eukaryotes (Marais 2003), but a potential role in prokaryotic genome tia” or “phylogenetic effects,” the influence of a common ancestor on 19
GC content has not been explored. While loss of DNA repair genes related species (Cheverud et al. 1985; Felsenstein 1985). However,
has been proposed as the proximate cause of increases in substitu- the concept was developed for comparisons between eukaryotic spe-
tion rates and genome AT content in organelle or endosymbiont pro- cies, and the concomitant assumption of vertical inheritance and
teomes (Burger and Lang 2003), we propose that the ultimate cause genetic isolation. Gene flow within eukaryotic species violates the
for these phenotypes is a reduced proteomic constraint, illustrated assumption of a tree-like phylogeny required by techniques designed
in Figure 6, and thus changes to genome GC content resulting from to reduce the effects of phylogenetic nonindependence, and so the
loss of DNA repair genes is a second order effect due to changes in P. use of these methods in the absence of genetic isolation is inappro-
priate (Stone et al. 2011). Its applicability to bacteria is problematic
Accounting for Phylogenetic Effects in Bacteria due to the occurrence of lateral gene transfer (LGT) (Touchon et al.
The factor of phylogenetic nonindependence has been viewed as 2011; Gama et al. 2012; Zimmerman et al. 2013). While the distri-
problematic in considerations of trait distributions between species bution of complex traits are constrained by genetic background and
Journal of Heredity, 2015, Vol. 106, No. 5 651
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Figure 6. The effect of a reduced proteomic constraint on the loss of DNA repair genes, elevated substitution/mutation rates, and genome AT bias in bacteria. ed
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vertical inheritance in eukaryotes, in bacteria this is less likely to link between absence of these DNA repair genes and genome AT h
be the case, given that many bacterial genes, including DNA repair bias. uvrABC are only absent in a handful of genomes with very ttp
s
genes, are easily transferable into novel genetic backgrounds (Sorek small values of P. No gene was more likely to be present in an AT ://a
et al. 2007). The DNA repair genes examined in this work are not rich genome with statistical significance. Overall, the results are con- c
a
involved in large protein complexes, and have been observed to be sistent with those reported above. Collapsing to the genus level is de
m
readily transferable (Aravind et al. 1998; Denamur et al. 2000; Lin overly conservative for simple traits such as DNA repair gene pres- ic
et al. 2007), so they are likely to violate the assumption of vertical ence or absence, given that such traits do not show phylogenetic .o
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inheritance. In contrast, genome GC content is a complex trait that effects above the level of bacterial species. However, this does not p.c
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may be slow to change, and so potentially more subject to phyloge- necessarily apply for a more “complex” trait such as genome GC m
netic inertia in bacteria. content, and the analysis indicates that while there is a clear asso- /jh
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The combination of LGT and the lack of a robust phylogeny for ciation between the presence of a number of genes and increased re
d
our dataset, means that many commonly used tests of phylogenetic genome GC content, the few examples of genes that are associated /a
effects are inappropriate. A solution is to collapse to the species/genus with increased genome AT content are not significantly associated rtic
le
levels, using taxonomic rank as a grouping variable. This is a more when genus level correction is applied; loss of statistical significance -a
appropriate approach where potential phylogenetic inertia effects is often due to a reduction in sample size, an inherent problem with bs
are likely to be weak, as in bacteria (Touchon et al. 2011; Gama methods to correct for phylogenetic effects. tra
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et al. 2012; Zimmerman et al. 2013), as opposed to methods such t/1
0
as phylogenetic independent contrasts, which assume strong phylo- Distribution of DNA Repair Genes across Genomes with 6
/5
genetic effects (Capellini et al. 2010). The results were as follows. Bacterial Lifestyle /6
4
The dataset was collapsed to the species level (see Supplementary Additional features of bacterial lifestyle were examined to assess pos- 4
/2
Table 1a online), the level at which phylogenetic effects operate on sible influences on the distribution of DNA repair genes across bac- 9
6
simple traits in bacteria, presumably due to the ameliorating effect of terial genomes. Intracellular bacteria have a marked absence of DNA 00
3
LGT (Martiny et al. 2012; Zimmerman et al. 2013; species defined repair genes, in comparison to nonintracellular bacteria (Table 2a). 3
b
as >97% identity of the 16S rRNA gene). Of the 18 genes examined, This is consistent with earlier work that has shown the loss of y
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17 were more likely to be present in bacteria with a larger P, and DNA repair genes in intracellular bacteria, discussed above. While u
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14 of these comparisons were statistically significant. In addition, a reduction in size of the proposed proteomic constraint provides a st o
15 of the genes were more likely to be present in GC rich genomes, potential explanation for the loss of DNA repair genes, if bacterial n
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11 of these comparisons were statistically significant. ung was sta- symbionts have reduced N, the alternative explanation of relaxed 4
e A
tistically more likely to be present in AT rich genomes. These results selection pressure and a general deletion bias might also lead to gene p
are largely consistent with those generated without phylogenetic loss (Moran 2003; Kuo et al. 2009). However, it is unlikely that this ril 2
0
correction. is a major factor given that only a small proportion of mutations 1
9
When the dataset was collapsed to the genus level (see are slightly deleterious (Fay et al. 2001; Eyre-Walker et al. 2002),
Supplementary Table 1b online), 15 of the genes were more likely defined as mutations that are affected by population size according
to be present in bacteria with a larger P, and of these comparisons 9 to the nearly neutral theory (Ohta 1974). In addition, deletion of an
were statistically significant. None were likely to be present in bacte- entire gene would be equivalent to summing the deleterious effects of
ria with smaller P. The presence of DNA repair genes was associated all the potential point mutations that the gene might undergo, mean-
with genome GC bias, with 12 of the genes more likely to be present ing that its loss is unlikely to be slightly deleterious and so affected
in GC rich genomes, of these comparisons 9 were statistically sig- by a reduction in N, consistent with the small number of genes in
e
nificant. A number of genes were associated an average genome GC intracellular bacterial genomes that are under weak selection (Ka/
content >5%; these were mutY, vsr, uvrABC, and ndk. The protein Ks > 0.8; Kuo et al. 2009). Crucially, P does not vary substantially
products of the mutY, vsr, and ndk genes are responsible for repair- in metazoa, despite large differences in population densities (White
ing GC → AT mutations (see Methods), this provides a mechanistic et al. 2007), implying that populational differences are unlikely to
652 Journal of Heredity, 2015, Vol. 106, No. 5
Table 2. DNA repair gene contents of different categories of bacteria
a) Intracellular bacteria were compared with nonintracellular bacteria
Intracellular Nonintracellular p Value
bacteria (118 genomes) bacteria (782 genomes)
Mean proteome size (amino acids) 450 816 1 179 835 <0.01
Mean GC content 0.37 0.50 <0.01
Percentage that lack ada 53.4 25.2 <0.001
Percentage that lack dnaQ 26.3 28.5 NS
Percentage that lack mug 94.9 74.7 <0.001
Percentage that lack mutH 95.8 81.6 <0.001
Percentage that lack mutL 22.0 16.1 NS
Percentage that lack mutS 28.8 10.0 <0.001
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Percentage that lack mutT 60.2 32.7 <0.001 o
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Percentage that lack mutM 51.7 27.7 <0.001 n
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Percentage that lack mutY 57.6 19.6 <0.001 a
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Percentage that lack ndk 25.4 8.70 <0.001 e
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Percentage that lack nei 82.2 60.5 <0.001 fro
Percentage that lack nth 29.7 15.7 <0.001 m
PPeerrcceennttaaggee tthhaatt llaacckk ougntg 2710..23 2208..68 N<0S.001 https
Percentage that lack uvrA 12.7 0.38 <0.001 ://a
c
Percentage that lack uvrB 15.3 1.28 <0.001 a
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Percentage that lack uvrC 16.9 0.26 <0.001 e
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Percentage that lack vsr 95.8 74.6 <0.001 ic
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b) Pathogenic (host associated and opportunistic) nonintracellular bacteria were compared with nonpathogenic nonintracellular bacteria .c
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Nonintracellular Nonintracellular p Value /jh
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pathogens (334 genomes) nonpathogens (448 genomes) re
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MMeeaann GprCo tceoonmtee nstize (amino acids) 10 1.0457 439 10 2.3552 300 <<00..0011 rticle
Percentage that lack ada 22.8 27.0 NS -a
b
PPeerrcceennttaaggee tthhaatt llaacckk dmnuagQ 1687..91 3850..74 <<00..000011 strac
Percentage that lack mutH 74.6 86.8 <0.001 t/1
0
Percentage that lack mutL 14.4 16.3 NS 6
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Percentage that lack mutS 8.11 11.4 NS /6
Percentage that lack mutT 28.7 35.7 0.01< p ≤0.05 44
Percentage that lack mutM 27.5 27.9 NS /29
Percentage that lack mutY 15.0 23.0 <0.001 60
0
Percentage that lack ndk 7.78 9.38 NS 3
3
Percentage that lack nei 56.3 63.6 0.01< p ≤0.05 b
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Percentage that lack nth 0.21 19.9 <0.001 g
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Percentage that lack ogt 35.3 23.9 <0.001 e
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Percentage that lack ung 4.79 32.4 <0.001 t o
Percentage that lack uvrA 0.60 0.22 NS n
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Percentage that lack uvrB 0.90 1.56 NS 4
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Percentage that lack uvrC 0 0 NS p
Percentage that lack vsr 79.3 71.0 0.005< p ≤0.05 ril 2
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c) Host associated nonintracellular pathogenic bacteria were compared with all other nonintracellular bacteria (including opportunistic pathogens)
Host-associated nonintracellular All other nonintracellular p Value
pathogens (96 genomes) bacteria (686 genomes)
Mean proteome size (amino acids) 1 117 947 1 188 496 NS
Mean GC content 0.49 0.50 NS
Percentage that lack ada 15.6 26.5 0.005 < P ≤ 0.05
Percentage that lack dnaQ 18.8 29.9 0.01 < P ≤ 0.05
Percentage that lack mug 71.9 75.1 NS
Percentage that lack mutH 65.6 83.8 <0.001
Journal of Heredity, 2015, Vol. 106, No. 5 653
Table 2. Continued
c) Host associated nonintracellular pathogenic bacteria were compared with all other nonintracellular bacteria (including opportunistic pathogens)
Host-associated nonintracellular All other nonintracellular p Value
pathogens (96 genomes) bacteria (686 genomes)
Percentage that lack mutL 7.29 16.6 <0.001
Percentage that lack mutS 2.08 11.1 <0.001
Percentage that lack mutT 26.0 33.7 NS
Percentage that lack mutM 20.8 28.7 NS
Percentage that lack mutY 14.6 20.3 NS
Percentage that lack ndk 1.04 9.77 <0.001
Percentage that lack nei 72.9 58.7 <0.001
Percentage that lack nth 7.29 16.9 <0.001
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Percentage that lack ogt 32.3 28.3 NS o
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Percentage that lack ung 3.13 23.0 <0.001 n
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Percentage that lack uvrA 2.08 0.15 NS a
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Percentage that lack uvrB 1.04 1.31 NS e
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Percentage that lack uvrC 0 0 NS fro
Percentage that lack vsr 78.1 74.1 NS m
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NS, not significant. Definitions of the different types of pathogenic bacteria are contained in Methods. Significance (p) values were calculated using a 2-propor- ttps
tion Z test. Shading indicates a larger percentage that lack the gene. ://a
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affect P. Lastly, there is no suggestion that a reduction in N has led of host-associated nonintracellular pathogens (1 117 947 amino acids) em
to a reduction in P in open ocean bacteria of reduced genoeme size is not significantly larger than all other nonintracellular bacteria ic.o
(Batut et al. 2014), including Prochlorococcus species which possess (1 188 496 amino acids; Table 2c), which implies that the host-associ- u
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very large values of Ne (Kashtan et al. 2014). These considerations ated lifestyle may be a factor in influencing the distribution of the DNA .com
imply that a reduction in Ne will have a limited effect on P and the repair genes across genomes. In contrast, recombination repair genes /jh
presence or absence of DNA repair genes. are not clearly associated with pathogenicity (Garcia-Gonzalez et al. e
An additional explanation for the loss of DNA repair genes in 2013); this could be explained by a lack of a role for recombination red
iennthraacneclelu rleapr lbicaacttieornia r aist etsh a(At tnhdee rresssounlt ianngd g eKnuormlainc ds t1re9a9m5)li, nhinogw mevaeyr rweiptahi rp ihno dtoesfeynncthe easgisa iannsdt taheer hoobsict.i tTyh we erreela atiloson sehxipam ofin DedN, Ab urte pnaoi rs gtreonnegs /article
the rate of cell division is unknown in intracellular bacteria and there association was observed (see Supplementary Tables 2a and 2b online). -ab
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is little evidence for a relationship between genome size and rep- tra
lication rate (Bergthorsson and Ochman 1998; Mira et al. 2001). Co- and Antidistribution of DNA Repair Genes across Genomes ct/1
There is also some evidence that loss of auxiliary genes can provide A codistribution analysis reveals that the majority of DNA repair 0
6
a selective advantage (Lee and Marx 2012). Interestingly, the freel- genes are not strongly co- or antidistributed (Figure 7), consistent /5
/6
iving nonphotosynthetic marine bacterium Candidatus Pelagibacter with a previous analysis of recombination repair genes, indicating 4
4
ubique is one of the smallest organisms on earth, and has undergone that only those genes whose protein products are components of /2
9
a reduction in P (it is one of the smallest known organisms, cell size protein complexes are likely to be strongly codistributed (Garcia- 60
0
0.12–0.20 μm, Giovannoni et al. 2002) and a concomitant loss of Gonzalez et al. 2013). Notably, mutL and mutS are codistributed, 3
3
DNA repair (Viklund et al. 2012; P = 424 765 amino acids). Of the indicated by red on the heatmap, as are uvrABC. The gene prod- b
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18 DNA repair genes examined here, Candidatus P.ubique has only ucts of these genes are known to physically interact, indicating the g
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10 DNA repair genes present in the genome, less than the average of efficacy of this statistical approach to detect protein complexes. es
12.7 (SD = 2.25) for nonintracellular bacteria. Notably, nei is antidistributed with mutLS, ogt, and ndk. This could t o
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The potential influence of pathogenicity was examined as DNA indicate a redundant or antagonistic function between the genes. In 0
4
repair in pathogens has been linked to increased resistance to oxida- addition, dnaQ is anti-distributed with uvrABC, again indicating A
p
tSiuvve adranmapaugne yrae saunltdin Sgt efrino m2 0th0e5 )i,m omr uton ea s ysestleecmti o(Kn opbraeyssaushrei etto  ailn. c2r0e0a5se; antagonistic or redundant function. ril 20
1
mutation rates (e.g., adaptive mutagenesis). In nonintracellular patho- 9
gens, 8 DNA repair genes are more common, compared with 3 genes Archaea
that are more common in nonintracellular nonpathogens (Table 2b). Out of the 21 archaeal DNA repair genes examined, 16 were asso-
The average value of P of nonintracellular pathogens (1 105 439 amino ciated with a larger average value of P (Table 3). Of these, 5 asso-
acids) is significantly smaller than nonintracellular nonpathogens ciations were statistically significant. These genes were mutY, mutL,
(1 235 300 amino acids; Table 2b), and so this finding suggests that fac- uvrA, ung, and XPD. Interestingly, the average P is smaller for those
tors in addition to P may be operating. The category of “nonintracel- genomes lacking uvrA, while it is larger for those genomes lacking
lular pathogens” includes opportunistic pathogens, which do not show uvrB and uvrC (Table 3). This discrepancy may be accounted by the
adaptation to the host, so the category of “host-associated pathogens” uncoupled action of these components of nucleotide excision repair
was examined. Of the total genes examined, 8 genes are more com- (Lage et al. 2010). There is a positive correlation between the total
mon in host-associated nonintracellular pathogens, compared with 1 number of DNA repair genes present in a genome and P (Figure 1d,
gene in all other nonintracellular bacteria (Table 2c). The average P y = 0.0029x0.62, r2 = 0.29, p < 6.2e-9), and as for bacteria. Also,