Bacteriophage possess a variety of auxiliary metabolic genes of bacterial origin. These proteins enable them to maximize infection efficiency, subverting bacterial metabolic processes for the purpose of viral genome replication and synthesis of the next generation of virion progeny. Here, we examined the enzymatic activity of a cyanophage MazG protein - a putative pyrophosphohydrolase previously implicated in regulation of the stringent response via reducing levels of the central alarmone molecule (p)ppGpp. We demonstrate, however, that the purified viral MazG shows no binding or hydrolysis activity against (p)ppGpp. Instead, dGTP and dCTP appear to be the preferred substrates of this protein, consistent with a role preferentially hydrolysing deoxyribonucleotides from the high GC content host Synechococcus genome. This showcases a new example of the fine-tuned nature of viral metabolic processes.
Bacteriophage possess a variety of auxiliary metabolic genes of bacterial origin. These proteins enable them to maximize infection efficiency, subverting bacterial metabolic processes for the purpose of viral genome replication and synthesis of the next generation of virion progeny. Here, we examined the enzymatic activity of a cyanophageMazG protein - a putative pyrophosphohydrolase previously implicated in regulation of the stringent response via reducing levels of the central alarmone molecule (p)ppGpp. We demonstrate, however, that the purified viral MazG shows no binding or hydrolysis activity against (p)ppGpp. Instead, dGTP and dCTP appear to be the preferred substrates of this protein, consistent with a role preferentially hydrolysing deoxyribonucleotides from the high GC content host Synechococcus genome. This showcases a new example of the fine-tuned nature of viral metabolic processes.
Cyanophage that infect the marine cyanobacterial genera Synechococcus and Prochlorococcus are widespread and abundant in oceanic systems (Suttle and Chan, 1994; Sullivan et al.,
2003; Baran et al.,
2018) where they play important ecosystem roles including releasing organic matter through cell lysis (Suttle, 2007), transferring genes horizontally between hosts (Zeidner et al.,
2005) and structuring host communities (Mühling et al.,
2005). Cyanophage can also influence ocean biogeochemistry by modifying host metabolism during the infection process, such as the shutdown of CO2 fixation whilst maintaining photosynthetic electron transport (Puxty et al.,
2016). This subversion of host metabolism is facilitated by the expression of cyanophage genes that appear to have a bacterial origin, so‐called auxiliary metabolic genes (AMGs) (Breitbart et al.,
2007). These include genes involved in photosynthesis (Mann et al.,
2003; Lindell et al.,
2005; Fridman et al.,
2017) and photoprotection (Lindell et al.,
2004; Millard et al.,
2004; Sullivan et al.,
2005; Roitman et al.,
2018), pigment biosynthesis (Dammeyer et al.,
2008), central carbon metabolism (Millard et al.,
2009; Thompson et al.,
2011), nucleotide biosynthesis (Enav et al.,
2014), phosphorus metabolism (Sullivan et al.,
2010; Zeng and Chisholm, 2012; Lin et al.,
2016) and other stress responses (Sullivan et al.,
2010; Crummett et al.,
2016).Amongst the cyanophage AMGs MazG is a core gene in cyanomyoviruses (Millard et al.,
2009; Sullivan et al.,
2010) and of particular interest since it has been proposed to play a more general role in regulating host metabolism (Clokie and Mann, 2006; Clokie et al.,
2010). In Escherichia coli, MazG has been implicated in regulating programmed cell death by interfering with the function of the MazEF toxin‐antitoxin system, through lowering of cellular (p)ppGpp levels (Gross et al.,
2006). This latter molecule guanosine 3′,5′ bispyrophosphate, together with guanosine pentaphosphate also known as magic spot nucleotides, is a global regulator of gene expression in bacteria (Traxler et al.,
2008) synthesized by RelA under amino acid starvation. Since MazG can potentially regulate levels of (p)ppGpp in E. coli, a similar role has been proposed for the cyanophage encoded MazG (Clokie and Mann, 2006). This is pertinent given that picocyanobacterial hosts like Synechococcus and Prochlorococcus occupy oligotrophic conditions (see Scanlan et al.,
2009; Biller et al.,
2015) where nutrient starvation is likely and (p)ppGpp may be involved in adapting to this stressed state. By regulating (p)ppGpp levels the cyanophage encoded MazG may trick the host into mimicking a nutrient replete cellular state so that host cell physiology is optimized for macromolecular synthesis and hence cyanophage replication. The MazG protein belongs to the all‐nucleoside triphosphate pyrophosphohydrolase (NTP‐PPase, EC 3.6.1.8) superfamily that hydrolyzes in vitro all canonical nucleoside triphosphates into monophosphate derivatives and pyrophosphate (PPi) (Moroz et al.,
2005; Galperin et al.,
2006; Lu et al.,
2010). Here, we set out to purify the cyanophage S‐PM2MazG protein as well as a Synechococcus host MazG to assess their activity and ability to hydrolyse (p)ppGpp, canonical and noncanonical nucleotides.
Results
Picocyanobacterial host and cyanophageMazG proteins are phylogenetically distinct (Fig. 1) and with an origin of the cyanophageMazG outside the cyanobacteria since the closest proposed homologue to date is a Chloroflexus protein (Bryan et al.,
2008; Sullivan et al.,
2010). Picocyanobacteria encode two genes annotated as MazG, a ‘large’ MazG version similar to that found in most bacteria, and a ‘small’ version which is similar in size to the cyanophage gene (Fig. 2). The ‘large’ MazG version has two predicted catalytic regions functionally annotated as MazG family domains (IPR004518) whilst the ‘small’ MazG and cyanophage proteins have only one (Fig. 2). In order to assess the hydrolytic activity of the host and cyanophageMazG proteins we cloned into E. coli, over‐expressed and purified the host Synechococcus sp. WH7803MazG, using the ‘large’ MazG version (Syn_WH7803_02449) as a proxy for other host bacterial MazG proteins, and the cyanophage S‐PM2MazG (Fig. 3; for experimental details see Supporting Information). The activity of the cyanophage and Synechococcus host MazG proteins was assessed using increasing concentrations of a range of nucleotide and deoxyribonucleotide substrates using 1 μg of the purified protein, and the amount of free phosphate resulting from enzyme activity measured using the PiPER pyrophosphate assay kit (ThermoFisher Scientific; see Supporting Information). This allowed determination of K
m, V
max and K
cat values for each protein across a range of substrates (Table 1). K
m values of the Synechococccus sp. WH7803 ‘large’ MazG and cyanophage S‐PM2MazG proteins were generally in the low mM range for a range of nucleotides and deoxyribonucleotides, similar to MazG K
m values reported from other bacteria for these substrates (Lu et al.,
2010). The measured V
max of the Synechococcus host MazG was highest when incubated with dTTP, whilst the viral MazG exhibited highest activity when incubated with the deoxyribonucleotidesdGTP and dCTP (Fig. 4). In addition to these standard nucleotides, the viral MazG protein was also incubated with the ‘aberrant’ nucleotides dUTP, 2‐hydroxy‐dATP and 8‐oxo‐dGTP. dUTP is one of the most common of these mutagenic nucleotides, produced as a by‐product of thymine biosynthesis (Galperin et al.,
2006), whilst 2‐hydroxy‐dATP and 8‐oxo‐dGTP are mutagenic nucleotides produced as a result of intracellular oxidative stress (Kamiya and Kasai, 2000; Galperin et al.,
2006). Interestingly, the V
max values of the viral MazG when incubated with dUTP, 2‐hydroxy‐dATP and 8‐oxo‐dGTP were not significantly different to those of the canonical nucleotides (Table 1; Fig. 4), whilst the Km values for these substrates were higher (Table 1), suggesting that dGTP and dCTP are the preferred substrates of the cyanophageMazG protein.
Figure 1
Maximum likelihood phylogenetic tree comprising 44 bacterial and 38 viral MazG sequences.
The tree was generated using the LG + G4 substitution model, automatically chosen by the Iqtree script (Nguyen et al.,
2015), with ultrafast bootstrap (Minh et al.,
2013). Bootstrap values of >70% are shown as closed circles (of 1000 iterations). The scale bar represents 0.5 substitutions/amino acid position. Syn: Synechococcus; Pro: Prochlorococcus. The red asterisks indicate the Synechococcus and cyanophage proteins used here.
Figure 2
A. InterProScan5‐predicted (Jones et al.,
2014) pyrophosphatase catalytic domains in cyanophage S‐PM2 MazG, ‘small’ Synechococcus sp. WH7803 MazG (Syn_WH7803_01219), ‘large’ Synechococcus sp. WH7803 MazG (Syn_WH7803_02449) and MazG orthologues. Numbers above each domain represent the position of amino acids in each of the domains.
B. ClustalW pairwise alignment of , ‘large’ Synechococcus sp. WH7803, ‘small’ Synechococcus sp. WH7803 and cyanophage S‐PM2 MazG orthologues.
Figure 3
A. SDS‐PAGE analysis of whole cell lysates expressing Synechococcus sp. WH7803 ‘large’ MazG (lanes 1 and 3) and cyanophage S‐PM2 MazG proteins (lanes 2 and 4). L: Protein molecular weight marker ladder. Lanes 1 and 2 un‐induced, lanes 3 and 4 IPTG‐induced. Arrows indicate the positions of the overexpressed proteins.
B. SDS‐PAGE analysis showing purification of the cyanophage S‐PM2 MazG protein from . L: Protein molecular weight marker ladder. UB: The unbound fraction (proteins that did not bind to the column). W1–W5: fractions washed off the column with binding buffer. E1–E6: Fractions eluted with increasing concentrations of imidazole (30 mM, 50 mM, 100 mM, 150 mM, 200 mM and 300 mM respectively). SB – stripping buffer. The arrow indicates the position of the over‐expressed cyanophage S‐PM2 MazG protein.
Table 1
Kinetic parameters of enzymatic activity of Synechococcus WH7803 and cyanophage S‐PM2 MazG protein.
Vmax (nmol/μg/min)
Km (mM)
Kcat (min−1)
Synechococcus sp. WH7803
Cyanophage S‐PM2
Synechococcus sp. WH7803
Cyanophage S‐PM2
Synechococcus sp. WH7803
Cyanophage S‐PM2
dATP
1.8 (±0.28)
1.62 (±0.19)
0.3 (±0.09)
1.2 (±0.21)
126.12 (±19.35)
62.97 (±7.44)
dCTP
3.81 (±0.36)
8.86 (±0.2)
0.14 (±0.03)
1.16 (±0.04)
267.68 (±25.02)
344.68 (±7.72)
dTTP
6.57 (±0.19)
5.68 (±0.2)
ND
1.23 (±0.06)
461.04 (±13.43)
221.00 (±7.78)
dGTP
0.64 (±0.25)
10.29 (±0.25)
0.85 (±0.07)
0.14 (±0.01)
45.16 (±17.6)
400.35 (±9.91)
ATP
2.55 (±0.35)
2.28 (±0.24)
0.63 (±0.23)
1.43 (±0.36)
179.27 (±24.4)
88.7 (±9.41)
CTP
1.96 (±0.14)
2.51 (±0.17)
1.2 (±0.21)
0.85 (±0.11)
137.81 (±9.81)
97.48 (±6.68)
GTP
0.7 (±0.13)
0.3 (±0.02)
0.26 (±0.02)
ND
49.46 (±9.19)
11.67 (±0.6)
UTP
3.02 (±0.2)
3.31 (±0.18)
1.33 (±0.3)
0.6 (±0.37)
221.07 (±6)
128.75 (±7.12)
dUTP
‐
4.22 (±0.34)
‐
3.24 (±1.55)
‐
296.42 (±23.72)
2‐hydroxy d‐ATP
‐
1.65 (±0.06)
‐
4.86 (±1.13)
‐
115.65 (±3.95)
8‐oxo‐dGTP
‐
ND
‐
ND
‐
ND
The values in brackets represent SE based on three replicates. ND – not detected; − not measured.
Figure 4
Relative maximal activity (Vmax) of the Synechococcus sp. WH7803 ‘large’ MazG and cyanophage S‐PM2 MazG proteins against a range of canonical and noncanonical nucleotide and deoxyribonucleotide substrates, normalized to the activity of the cyanophage S‐PM2 MazG using dGTP as a substrate.
Error bars represent the standard error based on three replicate experiments.
Maximum likelihood phylogenetic tree comprising 44 bacterial and 38 viral MazG sequences.The tree was generated using the LG + G4 substitution model, automatically chosen by the Iqtree script (Nguyen et al.,
2015), with ultrafast bootstrap (Minh et al.,
2013). Bootstrap values of >70% are shown as closed circles (of 1000 iterations). The scale bar represents 0.5 substitutions/amino acid position. Syn: Synechococcus; Pro: Prochlorococcus. The red asterisks indicate the Synechococcus and cyanophage proteins used here.A. InterProScan5‐predicted (Jones et al.,
2014) pyrophosphatase catalytic domains in cyanophage S‐PM2MazG, ‘small’ Synechococcus sp. WH7803MazG (Syn_WH7803_01219), ‘large’ Synechococcus sp. WH7803MazG (Syn_WH7803_02449) and MazG orthologues. Numbers above each domain represent the position of amino acids in each of the domains.B. ClustalW pairwise alignment of , ‘large’ Synechococcus sp. WH7803, ‘small’ Synechococcus sp. WH7803 and cyanophage S‐PM2MazG orthologues.A. SDS‐PAGE analysis of whole cell lysates expressing Synechococcus sp. WH7803 ‘large’ MazG (lanes 1 and 3) and cyanophage S‐PM2MazG proteins (lanes 2 and 4). L: Protein molecular weight marker ladder. Lanes 1 and 2 un‐induced, lanes 3 and 4 IPTG‐induced. Arrows indicate the positions of the overexpressed proteins.B. SDS‐PAGE analysis showing purification of the cyanophage S‐PM2MazG protein from . L: Protein molecular weight marker ladder. UB: The unbound fraction (proteins that did not bind to the column). W1–W5: fractions washed off the column with binding buffer. E1–E6: Fractions eluted with increasing concentrations of imidazole (30 mM, 50 mM, 100 mM, 150 mM, 200 mM and 300 mM respectively). SB – stripping buffer. The arrow indicates the position of the over‐expressed cyanophage S‐PM2MazG protein.Kinetic parameters of enzymatic activity of Synechococcus WH7803 and cyanophage S‐PM2MazG protein.The values in brackets represent SE based on three replicates. ND – not detected; − not measured.Relative maximal activity (Vmax) of the Synechococcus sp. WH7803 ‘large’ MazG and cyanophage S‐PM2MazG proteins against a range of canonical and noncanonical nucleotide and deoxyribonucleotide substrates, normalized to the activity of the cyanophage S‐PM2MazG using dGTP as a substrate.Error bars represent the standard error based on three replicate experiments.In order to directly assess whether the Synechococcus and cyanophageMazG proteins play a role in (p)ppGpp metabolism we performed both hydrolysis and DRaCALA binding assays (Corrigan et al.,
2016), using 32P‐labelled GTP, ppGpp and pppGpp. In both assays, neither the Synechococcus nor cyanophageMazG showed any binding or hydrolysis activity against (p)ppGpp (Fig. 5A), whilst hydrolysis activity was confirmed for both orthologues against 32P‐labelled GTP (Fig. 5B).
Figure 5
A. Upper panel: DRaCALA binding assays, using 32P‐labelled GTP, ppGpp and pppGpp incubated with purified Synechococcus sp. WH7803 ‘large’ MazG and cyanophage S‐PM2 MazG proteins. MBP – maltose binding protein, used as a negative control. RsgA –purified RsgA protein from , used as a positive control. Syn MazG: Synechococcus sp. WH7803 ‘large’ MazG. Viral MazG: cyanophage S‐PM2 MazG. Lower panel: Bar chart representation of the fraction of substrate bound to each protein, as measured by densitometry. Syn. MazG: Synechococcus sp. WH7803 ‘large’ MazG. Viral MazG: cyanophage S‐PM2 MazG. Error bars represent the standard deviation of three experimental replicates.
B. Hydrolysis assay using purified Synechococcus sp. WH7803 ‘large’ MazG (Syn MazG), cyanophage S‐PM2 MazG (Viral MazG), MBP and RsgA proteins with 32P‐labelled GTP, ppGpp and pppGpp. The arrow highlights the absence of hydrolysis of 32P‐labelled ppGpp and pppGpp substrates.
A. Upper panel: DRaCALA binding assays, using 32P‐labelled GTP, ppGpp and pppGpp incubated with purified Synechococcus sp. WH7803 ‘large’ MazG and cyanophage S‐PM2MazG proteins. MBP – maltose binding protein, used as a negative control. RsgA –purified RsgA protein from , used as a positive control. Syn MazG: Synechococcus sp. WH7803 ‘large’ MazG. Viral MazG: cyanophage S‐PM2MazG. Lower panel: Bar chart representation of the fraction of substrate bound to each protein, as measured by densitometry. Syn. MazG: Synechococcus sp. WH7803 ‘large’ MazG. Viral MazG: cyanophage S‐PM2MazG. Error bars represent the standard deviation of three experimental replicates.B. Hydrolysis assay using purified Synechococcus sp. WH7803 ‘large’ MazG (Syn MazG), cyanophage S‐PM2MazG (Viral MazG), MBP and RsgA proteins with 32P‐labelled GTP, ppGpp and pppGpp. The arrow highlights the absence of hydrolysis of 32P‐labelled ppGpp and pppGpp substrates.
Discussion
Although, the presence and identity of AMGs in bacteriophage genomes is widely appreciated (Millard et al.,
2009; Sullivan et al.,
2010; Crummett et al., 2016) the specific role of many of these genes has not been resolved. Here, we sought to elucidate the activity of the cyanophageMazG protein given its hypothesized role as a more general modulator of the host stringent response, and with previous data suggesting cyanophage can modulate intracellular levels of (p)ppGpp in infected freshwater cyanobacteria (Borbély et al.,
1980).Our results showed, however, that neither the Synechococcus nor cyanophageMazG protein demonstrated detectable hydrolytic activity towards ppGpp or pppGpp (Fig. 5), suggesting these two proteins do not actively modulate the stringent response via direct hydrolysis of magic spot nucleotides. Nevertheless, we cannot rule out a role for these proteins in regulating the stringent response indirectly through hydrolysis of other nucleotide substrates, for example GTP. Whilst the role of the ‘small’ Synechococcus host MazG also requires clarification in this respect, it is potentially the predicted bifunctional Synechococcus sp. WH7803 SpoT orthologue (SynWH7803_2342) that serves the role of regulating alarmone levels during the stringent response in these organisms, a protein known to both synthesize and hydrolyse (p)ppGpp in other bacteria (see, e.g. Murray and Bremer, 1996; Hogg et al.,
2004). Interestingly, there were distinct differences in the hydrolytic activities of the Synechococcus host and cyanophage S‐PM2MazG proteins towards other canonical and noncanonical nucleotides (Fig. 4 and Table 1) with much higher V
max values of the viral MazG towards dGTP and dCTP coupled with a much higher affinity of the viral MazG for dGTP compared to its host counterpart. Such different kinetic parameters mirror differences in %GC content between the cyanophage and Synechococcus host genomes, with the former possessing a GC content of 37.7% (Mann et al.,
2005) and the latter a GC content of 60.2% (Dufresne et al.,
2008). With this in mind, we suggest that the substrate specificity of the viral MazG allows it to preferentially hydrolyse dGTP and dCTP deoxyribonucleotides from the high GC content host Synechococcus genome allowing for their recycling and ultimately facilitating replication of the AT‐rich cyanophage genome. Whether such a mechanism is applicable to, or modified in, Prochlorococcus infecting cyanophage whose genomes generally possess a similar %GC content (Sullivan et al.,
2005; Limor‐Waisberg et al.,
2011) remains to be determined. Certainly, it is well known that following infection with cyanophage, the host genome is rapidly degraded (Doron et al.,
2016). Moreover, analysis of viral metagenomes has shown an enrichment of metabolic pathways involved in pyrimidine and purine metabolism as well as in DNA replication (Enav et al.,
2014), emphasizing the importance of these pathways during viral infection.Our work with the viral MazG thus highlights that cyanophage genomes appear exquisitely suited to promote degradation of the host genome in order to reuse its building blocks to replicate the viral genome.Appendix S1: Supplementary InformationClick here for additional data file.
Authors: Debbie Lindell; Matthew B Sullivan; Zackary I Johnson; Andrew C Tolonen; Forest Rohwer; Sallie W Chisholm Journal: Proc Natl Acad Sci U S A Date: 2004-07-15 Impact factor: 11.205
Authors: Gil Zeidner; Joseph P Bielawski; Michael Shmoish; David J Scanlan; Gazalah Sabehi; Oded Béjà Journal: Environ Microbiol Date: 2005-10 Impact factor: 5.491
Authors: Andrew D Millard; Katrin Zwirglmaier; Mike J Downey; Nicholas H Mann; Dave J Scanlan Journal: Environ Microbiol Date: 2009-06-07 Impact factor: 5.491
Authors: Rebecca M Corrigan; Lauren E Bellows; Alison Wood; Angelika Gründling Journal: Proc Natl Acad Sci U S A Date: 2016-03-07 Impact factor: 11.205
Authors: Michael J Bryan; Nigel J Burroughs; Edward M Spence; Martha R J Clokie; Nicholas H Mann; Samantha J Bryan Journal: PLoS One Date: 2008-04-23 Impact factor: 3.240
Authors: Holger H Buchholz; Luis M Bolaños; Ashley G Bell; Michelle L Michelsen; Michael J Allen; Ben Temperton Journal: Appl Environ Microbiol Date: 2022-03-21 Impact factor: 4.792
Authors: Ryan Cook; Steve Hooton; Urmi Trivedi; Liz King; Christine E R Dodd; Jon L Hobman; Dov J Stekel; Michael A Jones; Andrew D Millard Journal: Microbiome Date: 2021-03-20 Impact factor: 16.837
Authors: Dror Shitrit; Thomas Hackl; Raphael Laurenceau; Nicolas Raho; Michael C G Carlson; Gazalah Sabehi; Daniel A Schwartz; Sallie W Chisholm; Debbie Lindell Journal: ISME J Date: 2021-08-24 Impact factor: 10.302