1 Large-scale maps of variable infection efficiencies in aquatic Bacteroidetes phage-
2 host model systems
3 Karin Holmfeldt1,2, Natalie Solonenko1,a, Cristina Howard-Varona1,a, Mario Moreno1,
4 Rex R. Malmstrom3, Matthew J. Blow3, Matthew B. Sullivan1,a,b
5 1Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ,
6 USA
7 2Centre for Ecology and Evolution in Microbial Model Systems, Department of Biology
8 and Environmental Sciences, Linnaeus University, Kalmar, Sweden
9 3DOE Joint Genome Institute, Walnut Creek, CA, USA
10 Current affiliation: Departments of aMicrobiology, and bCivil, Environmental and
11 Geodetic Engineering, The Ohio State University, Columbus, OH
12 * corresponding author: Karin Holmfeldt, Center for Ecology and Evolution in Microbial
13 Model Systems, Department of Biology and Environmental Sciences, Linnaeus
14 University, SE-391 82 Kalmar, Sweden. Phone nr +46-480-447310, Fax nr +46-480-
15 447305, email [email protected].
16
17 Running title: Variable phage-host infection interactions
1 18 Summary
19 Microbes drive ecosystem functioning, and their viruses modulate these impacts through
20 mortality, gene transfer, and metabolic reprogramming. Despite the importance of virus-
21 host interactions and likely variable infection efficiencies of individual phages across
22 hosts, such variability is seldom quantified. Here we quantify infection efficiencies of 38
23 phages against 19 host strains in aquatic Cellulophaga (Bacteroidetes) phage-host model
24 systems. Binary data revealed that some phages infected only one strain while others
25 infected 17, whereas quantitative data revealed that efficiency of infection could vary 10
26 orders of magnitude, even among phages within one population. This provides a baseline
27 for understanding and modeling intra-population host range variation. Genera specific
28 host ranges were also informative. For example, the Cellulophaga Microviridae, showed
29 a markedly broader intra-species host range than previously observed in Escherichia coli
30 systems. Further, one phage genus, Cba41, was examined to investigate non-heritable
31 changes in plating efficiency and burst size that depended on which host strain it most
32 recently infected. While consistent with host modification of phage DNA, no differences
33 in nucleotide sequence or DNA modifications were detected, leaving the observation
34 repeatable, but the mechanism unresolved. Overall this study highlights the importance of
35 quantitatively considering replication variations in studies of phage–host interactions.
36
37 Introduction
38 Microbes drive the planet’s biogeochemical cycles (Falkowski et al., 2008) and
39 their viruses (called phages when infecting bacteria) play important roles ranging from
40 mortality and nutrient cycling to gene transfer and metabolic reprograming (Fuhrman,
2 41 1999; Wommack and Colwell, 2000; Weinbauer, 2004; Suttle, 2005, 2007; Rohwer et al.,
42 2009; Breitbart, 2012; Hurwitz et al., 2013; Brum and Sullivan, 2015; Hurwitz et al.,
43 2015). Our knowledge of genome-wide viral diversity, in marine systems in particular, is
44 rapidly expanding through mining microbial datasets (Roux et al., 2014, Labonte et al.,
45 2015) and assembly from large-scale viral metagenomes (Brum et al., 2015). Such
46 advances mean that the field can now look forward to advancing from measuring gene
47 marker based diversity to assessing viral impacts. These impacts ultimately depend upon
48 a virus’ ability to infect a bacterium, which is a function of myriad levels of phage–
49 bacteria interactions from recognition to overcoming bacterial defenses (reviewed in
50 Hyman and Abedon, 2010; Labrie et al., 2010; Samson et al., 2013). The first step for
51 successful infection is recognition and attachment of the phage to the host receptors. This
52 involves a specific interaction between phage receptor-binding proteins, such as tail fiber
53 proteins among tailed phages, and bacterial cell surface receptors, which can include
54 surface proteins, polysaccharides, or lipopolysaccharides (Rakhuba et al., 2010). Through
55 sequence mutations phages can expand the range of hosts that they infect (host range),
56 likely by adopting new surface interaction capabilities and counteracting bacterial
57 defense mechanisms (Pepin et al., 2008; Paterson et al., 2010; Avrani et al., 2011). Once
58 inside the cell, phage DNA must avoid cleavage by restriction endonucleases (Arber,
59 1965a) or the CRISPR-Cas system (Barrangou et al., 2007), which can work together to
60 increase bacterial resistance to phages (Dupuis et al., 2013), as well as avoid abortive
61 infection systems (Snyder, 1995). Phages resist such defenses by altering their DNA to
62 escape restriction endonucleases (e.g. by methylation; Krüger and Bickle, 1983) or to
63 escape the CRISPR-Cas (Deveau et al., 2008) and the abortive infection system (Haaber
3 64 et al., 2009) (e.g., by mutations). Thus, a phage’s realized host range is dictated by the
65 ability to recognize hosts and avoid host defenses.
66 Such host ranges ultimately also dictate how phages impact the diversity of
67 bacterial communities (Weitz et al., 2013). Among cultured phages, most infect only
68 strains from a single or closely-related bacterial species (Wichels et al., 1998; Comeau et
69 al., 2005; Holmfeldt et al., 2007; Stenholm et al., 2008), though as assays are typically
70 constrained to strains of the species used for isolation, in situ host ranges may be broader.
71 Consistent with this, some phages are known to infect across bacterial genera (Sullivan et
72 al., 2003) or classes (Jensen et al., 1998). Our perception of the phage’s host range when
73 measured in the laboratory can also be affected by the choice of assay method, which
74 commonly includes plaque assays, spot tests (small amount of viruses applied on a
75 bacterial lawn), and liquid culture–based methods (Hyman and Abedon, 2010). Host
76 range assays of larger isolated phage–host systems (>10 phages compared to >10
77 bacteria) from natural communities have mainly been investigated using spot-tests
78 (Moebus and Nattkemper, 1981; Comeau et al., 2005; Holmfeldt et al., 2007; Stenholm
79 et al., 2008). However, spot-tests often overestimate phage host ranges (Kutter, 2009;
80 Holmfeldt et al., 2014; Khan Mirzaei and Nilsson, 2015), which leave plaque assays,
81 with their quantitative capability to determine the phage’s efficiency of plating (EOP;
82 Kutter, 2009) as the most compelling estimate of host range. The challenge for EOP
83 measurements is the time consuming nature of many plaque assays, which have left EOP
84 host range estimates limited to small data sets, using few (<10) hosts or phages (Jensen et
85 al., 1998; Holmfeldt et al., 2014; Silva et al., 2014).
4 86 To advance our understanding of phage–host interactions, we sought to
87 empirically evaluate the quantitative host range in the Cellulophaga baltica phage–host
88 system (Holmfeldt et al., 2007) by screening 38 phages against 19 host strains. From
89 these findings, a subset of the isolates was further explored to investigate host-driven
90 variation in phage replication within a single phage genus.
91
92 Results and Discussion
93 Quantitative host range variations among Cellulophaga phages
94 To assess the Cellulophaga phages’ efficiency of infection (EOI) on the different
95 host strains, their infectivity were investigated using plaque assays. All phages replicated
96 lytically with high EOI on at least one host. While some phages (Cba461, as well as
97 Cba401 and Cba183 investigated in Holmfeldt & Howard-Varona et al., 2014) contained
98 genes pointing towards possible lysogenic replication (Holmfeldt et al., 2013), no phages
99 capable of lysogeny have been observed, even though it was investigated in depth for the
100 Cba401 phages (Holmfeldt & Howard-Varona et al., 2014; Dang & Howard-Varona et
101 al., 2015). The number of host strains a phage could infect and the EOI varied greatly
102 across the phages (Fig. 1 and detailed in supp. Table 1). Specific phages (e.g.
103 siphoviruses φ12:1 and φ10:1) infected only one bacterial strain, while non-tailed ssDNA
104 phages within the Cba184 genus infected up to 17 of the 19 bacterial strains tested. When
105 multiple hosts were infected by a single phage, the EOI varied up to 10 orders of
106 magnitude across different hosts (e.g. φ17:1 on hosts #18 versus #17; φ47:1 on hosts
107 NN014873 versus NN014847). Large variations, both within strain specificity and EOI
108 between strains, could be seen among phages both within the same genus (e.g. Cba41)
5 109 and the same populations (e.g. φ48:1, φ18:4, and φ12a:1; Fig. 1 and supp. Table 2) as
110 defined by >95% average nucleotide identity (ANI) on >80% of their genes (Deng et al.,
111 2014; Brum et al., 2015).
112 Combining this host range data with that of the two previously investigated
113 Cellulophaga podophage genera (Cba401 and Cba183, supp. Table 1) (Holmfeldt &
114 Howard-Varona et al., 2014), the possible connection between host range and phage
115 family was examined. A statistical difference in host range was detected when comparing
116 phages with different taxonomic affiliation (Kruskal-Wallis, p-value=0.0003, χ2=21.30,
117 df=4). The difference was seen as a broader host range for phages within Myoviridae,
118 Microviride, and ssDNA phages (genus Cba482) when compared to Siphoviridae (Dunn-
119 test, p-value 0.0307, 0.0002, and 0.0359 respectively) (Fig. 1 and supp. Table 1). The
120 Microviridae phages also had a broader host range than Podoviridae phages (Dunn-test,
121 p-value 0.0220). That phages belonging to Myoviridae in general have a broader host
122 range than other Caudovirales phages has previously been noted among cyanophages
123 (Sullivan et al., 2003). However, the broad host range among the Cellulophaga
124 Microviridae phages contrasts previous findings (Muniesa et al., 2003; Sillankorva et al.,
125 2011) and is discussed below. While this and other studies (Sullivan et al., 2003;
126 Karumidze et al., 2013) have been able to show possible connection between phage
127 taxonomy and host range, the patterns are not universal (Karumidze et al., 2012;
128 Holmfeldt & Howard-Varona et al., 2014) and generalizations regarding host-range
129 breadth within and between phage families are difficult to predict. What patterns are
130 observed are also dependent upon the scale of the host range assay, as seen for the
131 Cellulophaga phages comparing host ranges of the smaller set of podophages previously
6 132 tested (Holmfeldt & Howard-Varona et al., 2014) with this more broad-scale study.
133 Further, there was a significantly broader host-range among phages isolated in 2005
134 compared to 2000 (Welch Two Sample t-test, p=0.0001, t=-4.255), though this might be
135 due to that broad host-range phage families (Myoviridae, Microviridae, and ssDNA
136 phages) mainly were isolated in 2005, while narrow host range phages (Siphoviridae)
137 were isolated in 2000 (Fig. 1). When comparing the possibility for the phages to infect
138 hosts that were isolated from the same water sample, the phages were more prone to
139 infect the hosts originating from the same water sample (i.e. phages from 2000 infecting
140 hosts isolated in 2000 compared to hosts isolated in 1994, Welch Two Sample t-test,
141 p=0.0405, t=-2.159). This differs from previous findings among cyanophages (Waterbury
142 & Valois, 1993), where host community was less susceptible to phages occurring in the
143 same water. The 2005 phages were as likely to infect the 1994 hosts as the 2000 hosts
144 (Welch Two Sample t-test, p=0.5523, t=0.598) and no hosts were isolated from the same
145 year and location as the 2005 phages.
146 From the host perspective, some strains were permissive to phage infection, while
147 others were not (Fig. 1). For example, 26 of the 38 phages tested were capable of
148 infecting host #18. These 26 phages represented 9 out of the 11 phage genera tested here
149 as well as 3 phages within the 2 podophage genera previously investigated (Holmfeldt &
150 Howard-Varona et al., 2014). In contrast, bacterium NN014850 was only infected by six
151 phages from two different genera (Fig. 1), as well as 3 phages among the 2 podophage
152 genera previously investigated (Holmfeldt & Howard-Varona et al., 2014). While
153 findings from other host range assays of closely related aquatic bacteria commonly show
154 strains within a species that are resistant or only infected by a single phage (Waterbury
7 155 and Valois, 1993; Sullivan et al., 2003; Comeau et al., 2005; Comeau et al., 2006;
156 Stenholm et al., 2008), our findings point toward a high susceptibility of these bacteria to
157 the isolated phages as even the least susceptible strain NN014850 can be infected by
158 phages from four different genera.
159 Comparing the 722 phage–host combinations analyzed in this quantitative host
160 range assay to the spot test-based assay performed previously (Holmfeldt et al., 2007),
161 24% of the combinations showed a different result. In 117 cases the spot-test had
162 recorded infectivity but no plaques were seen in this study. Conversely, in 54 cases
163 positive infections were recorded with this study while no infection had been recorded
164 with the spot-test. These contrasting findings of spot-tests versus plaque assays are
165 similar to those observed in other studies (Holmfeldt & Howard-Varona et al., 2014;
166 Khan Mirzaei and Nilsson, 2015). Assuming the differences are not attributable to
167 storage artifacts (the spot tests were performed 9 years ago), then it is probable that the
168 plaque assay method provides the most accurate measurement of phage host range as is
169 the consensus in the literature (Kutter, 2009; Khan Mirzaei and Nilsson, 2015). It is
170 thought that spot assays overestimate infection due to scoring inhibition and lysis from
171 without as viral replication, but may underestimate infection of low titers on low
172 infectivity hosts (Moebus, 1983; Hyman and Abedon, 2010).
173
174 Host range patterns among Cellulophaga Microviridae phages
175 Among the Cellulophaga phages, the small Microviridae phages within genus
176 Cba184 infected a larger number of bacterial strains than phages within Siphoviridae and
177 Podoviridae families as well as some phages within Myoviridae (Fig. 1). These
8 178 Cellulophaga phage findings contrast previous results in Escherichia coli where
179 Microviridae have narrower host ranges than Myoviridae and Siphoviridae (Muniesa et
180 al., 2003; Sillankorva et al., 2011). In φX174, the type Microviridae, the H protein
181 recognizes the host cell and mediates DNA entry (Jazwinski et al., 1975; Sun et al.,
182 2013). Unfortunately, the gene responsible for host recognition has not been identifiable
183 among the Cba184 phages (categorized as Microviridae based upon morphology and
184 distant functional homologs; Holmfeldt et al., 2013), even though 10 encapsidated
185 structural proteins have been experimentally determined.
186 There were also large variations in Cba184 strain EOIs in spite of the fact that the
187 Cba184 phage genomes were highly similar. For example, φ18:4 and φ48:1 vary in host
188 range and EOI within shared hosts (Fig. 1), and yet differ at only 11 synonymous and 1
189 non-synonymous substitutions across their 6.5 kb genomes (supp. Table S3). Single non-
190 synonymous substitutions are known to cause differences in host range, as previously
191 observed in ssDNA phage phiX174, dsRNA phage phi6 and dsDNA phage φΕΦ24Χ
192 (Cox and Putonti, 2010; Uchiyama et al., 2011; Ford et al., 2014). Here the non-
193 synonymous substitution belongs to a protein located in the phage particle, and thus,
194 presumed structural (Holmfeldt et al., 2013), though its specific function is still unknown.
195 Genetic manipulation of this protein, not yet available in this phage or host, could
196 someday test the hypothesis that such a substitution can drive the host range for the
197 Cba184 phages.
198
199 Replication variations among Cba41 phages
9 200 Two Cba41 phages, φ4:1 and φ17:2, had only minor differences in their genomes
201 as well as host range, making them interesting candidates for investigating the factors
202 regulating differences in infection among these Cellulophaga phages. In terms of host
203 ranges, both phages infected the same six host strains but φ17:2 infected two additional
204 strains at a significantly lower EOI (Fig. 1). The genomes of these phages had 98%
205 nucleotide (nt) identity (id) over the 96% of the genome that was shared (Fig. 2A), with
206 most (88%) genes >95% nt id, placing them within the same population (see Fig. 2B for
207 details). Further, 3 genes were shared with 90–95% nt id, 11 genes shared only a fraction
208 (14–92%) of the gene and with 87–100% nt id, and the remaining genes (10 for φ4:1 and
209 11 for φ17:2) lacking detectable similarity (e-value cut off e-3) at either the nt or amino
210 acid level. Despite the high sequence similarity between the phages, their genomes were
211 divergent enough that predictions about genetic determinants for the detected host range
212 and EOI variations were difficult to make.
213 To explore the variation in EOI for φ4:1 and φ17:2, we both ‘purified’ (i.e.
214 plaques had been picked and replicated on the alternative host 3 consecutive times) and
215 conducted ‘shuffling’ experiments by passaging the phages between the alternative host
216 strains #13 (φ4:1) and #18 (φ4:1 and φ17:2) and the original host strains #4 and #17 after
217 each round of plaquing (see Fig. 3A for details). These alternative host strains were
218 chosen given the 1–3 orders of magnitude reduced EOIs of φ4:1 and φ17:2 on these host
219 strains compared to the EOI of the phage on their original hosts (#4 and #17,
220 respectively; Fig. 1 and 3). In all cases, the passaged phages (φ4:1_13, φ4:1_18, and
221 φ17:2_18) had increased EOI on the host they were passaged on (#13 and #18,
222 respectively) compared to the ancestral phages (φ4:1 and φ17:2) infecting the same host
10 223 (t-test, φ4:1_13 versus φ4:1 on host #13: p=0.034; φ4:1_18 versus φ4:1 on host #18:
224 p=0.025; and φ17:2_18 versus φ17:2 on host #18: p=0.001, respectively; Fig. 3A–B). No
225 change in infectivity was seen for φ4:1_13 when infecting host #18 (t-test, p=0.103) or
226 φ4:1_18 when infecting host #13 (t-test, p=0.298) (Fig. 3B). The difference in EOI
227 occurred both immediately when the phage in a newly picked plaque was exposed to a
228 new host (shuffling; Fig. 3) and if the phage had been ‘purified’ (Fig. 3B–C). Thus it
229 appeared that passaging a phage on the low EOI host affected it, leading to increased EOI
230 on that host. However, when the passaged phage (e.g. 4:1_13) was passaged again
231 through the original host (e.g. 4) its EOI returned to the same as the ancestral phage (e.g.
232 4:1) (for example see Fig. 3A), suggesting that the change in EOI was a non-heritable
233 trait.
234 To investigate additional phenotypic differences among the Cba41 ancestral and
235 passaged phages, one-step growth curves were performed for φ4:1 on the three host
236 strains (#4, #13, and #18) (Fig. 4A–C) and for φ4:1_13 and φ4:1_18 on host #4 and the
237 host the phages had been propagated on (#13 and #18, respectively; φ4:1_13: Fig. 4D-E,
238 φ4:1_18: Fig. 4F-G). Concurring with the EOI results, the ancestral phage φ4:1 had a
239 reduced burst size on the alternative hosts #13 (p=0.023) and #18 (p=0.035) compared to
240 when infecting host #4. Further, the curves on the alternative hosts (13 and 18) did not
241 produce a clean step (Fig. 4B–C), pointing towards replication difficulties for φ4:1 on
242 those hosts. For the passaged phages, φ4:1_13 and φ4:1_18, the replication cycle had
243 improved for the infection on the host they had been propagated on (e.g. 4:1_13 on 13).
244 This meant a clearer “step” in the one-step growth curve (Fig. 4E and G) and an
245 increased burst size for φ4:1_13 versus φ4:1 when infecting #13 (27 vs 4, respectively,
11 246 p=0.038). As there was no difference in latent period, the passaged phages had a faster
247 replication rate when infecting the alternative hosts (burst size divided by latent period;
248 Keen, 2014) than when infecting the original host. Given the increased EOI, this contrasts
249 previous findings where extended host range is connected with reduced replication rate
250 (Duffy et al., 2006; Kesik-Szeloch et al., 2013; Keen, 2014). However, it should be noted
251 that these studies looked at host range differences between different host strains, not the
252 difference in EOI on the same host strain and in two cases different phages (Kesik-
253 Szeloch et al., 2013; Keen, 2014) instead of phages evolved from the same ancestor.
254
255 Genetic similarities among Cba41 phages
256 To detect possible genetic differences between the ancestral and passaged phages,
257 the genome of the passaged phages (φ4:1_13, φ4:1_18 and φ17:2_18) were sequenced
258 with Illumina. A first comparison of the assembled passaged phage genomes to the
259 ancestral phages using blastn revealed 100% nt id. Further detailed by recruiting the
260 passaged phage reads to the ancestral phage genomes (average coverage 300–550 fold)
261 revealed two possible indels: a missing T at a 10-T region (φ4:1_13, φ4:1_18, and
262 φ17:2_18) and a missing AT at a 8-AT region (φ4:1_13 and φ4:1_18). However, <4% of
263 the reads at either position had these indels and while it might represent true variation
264 within the phage population it is likely not connected to the noted replication variations
265 which ought to have been noted among the majority of reads. Thus, the difference in EOI
266 could not be connected with sequence mutations in the phages’ genomes. While
267 difference in infection driven by altered phage entry (e.g. Baranowski et al., 2001; Cox
268 and Putonti, 2010; Uchiyama et al., 2011; Ford et al., 2014) or CRISPR system
12 269 (Barrangou et al., 2007) function is explained by nucleotide substitutions, this is not
270 always the case for phages circumventing host restriction-modification systems (Krüger
271 and Bickle, 1983). We therefore hypothesized that the difference in EOI seen between the
272 passaged and ancestral phages could be due to differences in DNA modification. This
273 hypothesis was also strengthened by the non-heritable nature of the change in EOI seen in
274 the shuffling experiment (Fig. 3A), as the phage would only be given the correct
275 modification if it were provided by the last bacteria the phage infected (Luria, 1953;
276 Labrie et al., 2010).
277 Among phages, such non-sequence-derived, functionality changing (epigenetic)
278 switches are commonly caused by host-derived methylation of the phage DNA, which
279 protect progeny phages from the host restriction system during future infections (Arber,
280 1965b; Hattman, 2009). For example, just 1–2 DNA modifications can cause a 100-fold
281 EOI difference (Arber and Kuhnlein, 1967), which is similar to the difference in EOI that
282 is noted between the ancestral and passaged Cba41 phages (Fig. 3). To investigate the
283 possible methylation signals among the phages, they and the bacterial hosts genomes
284 were sequenced with PacBio (Table 1). Using the single-molecule, real time (SMRT)
285 sequencing technique, PacBio sequencing can be used as a high throughput method, with
286 high accuracy to define modified nucleotides (Flusberg et al., 2010; Fang et al., 2012;
287 Burgess, 2013; Schadt et al., 2013) and has previously been used to detect methylation
288 differences among coli- and lactococcal-phages (Fang et al., 2012; Murphy et al., 2014).
289 The bacterial hosts all contained different modifications ranging from no
290 modifications (strain #4) to 2–3 modifications in the remaining strains (Table 1).
291 However, the phage methylomes did not match any of those modifications. Instead,
13 292 among the five Cba41 phages, only one, identical methylation event was detected, a 6-
293 methyladenosine (m6A) in the motif CTYCAG, which is presumably the product of a
294 phage encoded methylase (Table 1). Thus, methylation based evasion of the host
295 restriction system is not the obvious explanation of the observed phenotypic changes.
296 While the SMRT technique is able to detect the methylations that are commonly
297 occurring among bacteria and phages (e.g. m6A and 4- and 5-methylcytosine), as well as
298 glucosylated 5-hydroxymethylcytosine, a common epigenetic driver among T-even
299 phages (Lehman and Pratt, 1960; Hattman and Fukasawa, 1963), sequencing coverage
300 (25–250x per strand depending on modification) does impact detection accuracy of
301 methylation signals (Biosciences, 2012). Here, the mean sequence coverage for bacterial
302 genomes was 30–54 fold, which is at the lower end of acceptable and suggests that some
303 modifications might not have been detected. However, for the phages, sequencing
304 coverage was >500 fold, so we expect that any known modifications present in the
305 majority of the population of sequenced phages would have been detected.
306 While considering both sequential and DNA-modification differences as possible
307 mechanisms for the detected host-interaction changes, no clear evidence could be
308 detected that this would drive the differences in EOI or burst size. For Cellulophaga
309 phage φ38:1, transcriptional differences within different hosts have been seen to regulate
310 replication differences for the phage (Howard-Varona et al., 2016). Thus, potential
311 mechanisms, including DNA modification not detected with PacBio, transcriptional, or
312 translational differences have to be taken into future consideration. Still, these infection
313 and replication measurements across phages and hosts provide important empirical data
314 for drawing the boundaries of host-to-host EOI differences.
14 315
316 Ecological and theoretical implications of variations in phage–host interactions
317 With increasing availability of next-generation sequencing methods, viral ecology
318 is moving further towards a more sequencing-based research field, providing important
319 data regarding functionality, taxonomy, and even host interactions (e.g. Hurwitz et al.,
320 2013; Deng et al., 2014; Hurwitz et al., 2015; Roux et al., 2015). To define ecological
321 perspective to the immense amount of data, metrics for describing e.g. populations, on a
322 nucleotide level have been suggested (Deng et al., 2014) and later been used for powerful
323 ecological inferences (Brum et al., 2015; Brum and Sullivan, 2015). Within this study we
324 use the same described metrics (>95% ANI on >80% of genes) to define populations
325 within the Cellulophaga phage system and evaluate infection variations within the
326 populations (Fig 1, supp. table 2), which provides experimental data for future phage-host
327 studies of sequence derived data. For example, methods have recently been evaluated and
328 shown to be able to predict possible hosts for phage contigs derived from metagenomes
329 (Roux et al., 2015), but it would be important to include computational analyses for
330 quantitative species-specific variations.
331 Further, through reinvestigation of numerous non-quantitative host range datasets,
332 mathematical models recently provided insight into nested and modular phage–host
333 infection networks (Flores et al., 2011; Flores et al., 2013; Weitz et al., 2013). While
334 phage-host systems of closely related taxa showed nested networks, where the least
335 susceptible is infected by the generalist phages and most susceptible host is infected by
336 both specialist and generalist phages (Flores et al., 2011) modularity seem to be the norm
337 when investigating phage-host interactions across larger taxonomic boundaries (Flores et
15 338 al., 2013; Roux et al., 2015). These studies have highlighted the importance of including
339 strain-specificity variations among bacterial species when investigating the impact of
340 phage driven Lotka-Voltera-like oscillations (Jover et al., 2013; Thingstad et al., 2014;
341 Thingstad et al., 2015). Now, with the results from the Cellulophaga phage–host system
342 we posit that the next stage in advancing our understanding will come from developing
343 theory that considers empirical measurements of EOI with particular focus on variation
344 across different bacterial strains. Such theory is likely more critically needed for phage–
345 host systems where “restrictive” hosts are still infected by many phages (e.g.,
346 Cellulophaga, this study) than those that are infected by few or no phages (e.g.,
347 Prochlorococcus and Synechococcus, Sullivan et al 2003). Further, infection efficiency
348 and replication success may also change among the phages depending on which host the
349 phage most recently infected. For example, with the higher infection efficiency and
350 replication rate the passaged Cba41 phages would presumably provide a heightened
351 mortality pressure on the host community than the ancestral phages (Abedon, 2009). This
352 change in viral replication success could be an important fitness aspect for the phages co-
353 occurring with a large number of different host strains, which is the case for the
354 Cellulophaga phages. Regarding this study, the 4 hosts used for the Cba41 experiments
355 were isolated at the same sampling together with 5 additional C. baltica strains
356 (Holmfeldt et al., 2007). Though, it should be noted that the Cba41 phages were isolated
357 5 years later and there is no data regarding the dynamics of the host community at that
358 point of time. Preferably, to understand the implications regarding the impact of these
359 ancestral/passaged phages on their host community, experiments with mixes of both
360 phage types and different host strains would be performed. However, due to their
16 361 identical DNA sequences this would be difficult, as we at this time point do not have any
362 means to separate or enumerate the different phages after they have been mixed.
363 Besides having variations in EOI among genetically identical phages, we posit
364 that the difference in susceptibility among the bacterial hosts will also be difficult to
365 elucidate using common bacterial evolution and clustering genes, like the 16S rRNA
366 gene (Olsen et al., 1986). The C. baltica bacteria varied largely in phage susceptibility
367 (Fig. 1) between strains that were 100% identical on both their 16S rRNA gene and ITS
368 sequences (e.g. MM#3 and NN016046 in Fig. 1; Holmfeldt et al., 2007). This points
369 towards the rapid evolution of the phage susceptibility trait compared to the slow, long-
370 term evolution of 16S and ITS as previously noted among Prochlorococcus and their
371 phages (Coleman and Chisholm, 2007). As host susceptibility further may be connected
372 to substrate utilization, which has previously been seen in the Cellulophaga phage–host
373 system (Middelboe et al., 2009), this difference in host susceptibility may lead to
374 variations in the bacterial strains’ impact on nutrient cycling, neither of which would be
375 noted on the level of 16S or ITS sequence variations.
376
377 Conclusions
378 This study illustrates the intricate interactions occurring among different and
379 genetically identical phages when infecting strains of the same bacterial species (99–
380 100% similar on 16S) and how these interactions change depending on the last host that
381 was infected. It points out the importance of quantitative host range investigations of
382 aquatic phages to fully understanding the impact they will have on the host community.
383 However, investigations are heavily bottlenecked by the time consuming nature of plaque
17 384 assays and the lack of isolated phage–host systems, which is further complicated by
385 cultivation difficulties of aquatic bacteria (Rappé et al., 2002; Simu and Hagström, 2004).
386 While novel methods are underway for host range determination in wild populations with
387 reduced dependence on cultivation (Tadmor et al., 2011; Deng et al., 2012; Ohno et al.,
388 2012; Allers et al., 2013; Deng et al., 2014; Martinez-Garcia et al., 2014; Roux et al.,
389 2014; Lima-Mendez et al. 2015; Roux et al., 2015), this study points out the importance
390 of also bringing the quantitative efficiency of infection into the host range determination
391 of these culture independent methods. It will be important to get large-scale data on these
392 variations to increase our understanding of phage-host interactions and population
393 dynamics within natural environments.
394
395 Experimental procedures
396 Bacterial and phage growth procedures
397 Isolation procedures for the 19 bacterial strains and 38 phage isolates investigated
398 in this study were described previously (Holmfeldt et al., 2007). The Cellulophaga
399 baltica host strains were grown at room temperature (RT) on Zobell agar plates (1 g yeast
400 extract [Becton, Dickinson and Company (BD)], 5 g bacto-peptone [BD], 15 g agarose
401 [BD], and 15 g Sea Salts [Sigma] per liter). Single colonies were inoculated into MLB
402 liquid media (0.5 g yeast extract [BD], 0.5 g bacto-peptone [BD], 0.5 g casaminoacids
403 [Fisher], 3 mL glycerol [Millipore] and 15 g Sea Salts [Sigma] per liter). Cultures were
404 grown without agitation and experiments were performed on cultures that had reached
405 late exponential phase (108 cells mL-1; typically overnight).
18 406 Phages were grown using the top-agar plating technique (plaque assay)
407 (Sambrook et al., 1989). Briefly, phages were diluted in Marine Sodium Magnesium
408 (MSM) buffer (450 mM NaCl, 50 mM MgSO4x7H20, 50mM Tris base, pH8), mixed with
409 0.3 mL of bacterial over night culture and 3.5 mL molten soft agar (MSM containing
410 0.6% low melting point agarose), and dispersed on agar plates. Plates were incubated at
411 RT in the dark and plaques were visible after 1–2 days. For phage lysate, 5 mL of MSM
412 was added to fully lysed plates, the plates were shaken for at least 30 min at RT, and then
413 the lysate was collected, 0.2 µm filtered and stored in the dark at 4ºC.
414
415 Quantitative host range assay
416 Phages for host range assays were harvested from fully lysed plates where the
417 individual phages were grown on their original hosts. 10x serial dilutions of these lysates
418 were made to 10-10 in MSM buffer. 100 µL of undiluted lysate and each dilution were
419 then used for plaque assays (see above) on each of the 19 hosts within 2 weeks of lysate
420 preparation.
421
422 Isolation of mutant phages and shuffling assay
423 Passaged phages for φ4:1 were isolated from host #13 and #18 (new phage name:
424 φ4:1_13 and φ4:1_18) and for φ17:2 from host #18 (new phage name: φ17:2_18). A
425 single plaque was picked with a 100 µL pipet tip, dispersed in 1 mL MSM buffer,
426 incubated for 30 min at RT and 0.2 µm filtered. This was used as a phage stock for new
427 plaque assays as described above. The passaged phages were replicated in the same
428 manner 3 times before their efficiencies of infection were determined as described above.
19 429 Further, for shuffling assays, the newly picked phage was exposed (plaque assay) to a
430 different host each time a new plaque was picked.
431
432 One-step growth curves
433 One-step growth curves measuring properties of the infection were done with
434 MOI of 0.1 to minimize multiple phage infections per cell. For this, 108 cells (late
435 exponential phase) and 107 phages were mixed for a total volume of 1 mL. After 15 min
436 of bacterial–phage adsorption time, new infections were stopped by diluting the bacteria–
437 phage mix 1000-fold in MLB medium. The first sample was immediately obtained and
438 termed “time 0” and from there on, samples were periodically taken from the bacterial–
439 phage mix. Phages were enumerated by plaque assays on the host used for the one-step.
440 Sampling was carried out every 30 or 60 min for a total of 8–10 h depending on the
441 phage–host pair. In order to calculate the burst size, phage samples collected included
442 both free (extracellular) as well as total (intracellular and extracellular) phages. For the
443 former, a 500 µL sample of the diluted infection was centrifuged at 10 000 x g for 5 min
444 to pellet the cells and 100 µL of the supernatant, containing only free phages, was
445 analyzed through plaque assay. For the total phages, the plaque assay was done with 100
446 µL taken directly from the 1000-fold dilution flask containing both intra- and
447 extracellular phages. Plates were left overnight in the dark at RT and plaques from two
448 consecutive dilutions were counted to obtain number of plaque forming units (pfu) per
449 mL. The burst size was calculated using the free phage values at the plateau after the
450 burst and subtracting the free phages before the burst from them, and then dividing that
20 451 number by the number of phages that were able to infect (the difference between the total
452 and free fraction of phages during the latent period).
453
454 DNA extraction, sequencing and downstream genome analyses
455 Large-scale phage concentrates (3–10 fully lysed plates) were precipitated with
456 polyethylene glycol (PEG 8000, Fisher) to use for DNA extraction. Briefly, 6.5 % (w/v)
457 of NaCl was added to the phage lysate, incubated on ice for 1 h–ON at 4ºC, and
458 centrifuged (11 000 x g, 10 min). To the supernatant 10% (w/v) PEG was added,
459 incubated 1 h–ON at 4ºC, and centrifuged (10 000 x g, 10 min). After the pellet had air-
460 dried it was resuspended in 1 mL MSM. DNA from the dsDNA phages was extracted
461 using the Wizard DNA purification kit (Promega) according to the manufacturer’s
462 recommendations. DNA from liquid ON bacterial cultures was extracted using the
463 DNeasy Blood and Tissue kit (Qiagen) according to the manufacturer’s
464 recommendations.
465
466 DNA sequencing and genome analyses
467 The genomes for the Cellulophaga phages were retrieved from GenBank and
468 genes of closely related phages were compared using BLASTn, to identify the number of
469 shared genes with >95% nucleotide identity.
470 Passaged phages for φ4:1 and φ17:2 were sequenced commercially using Illumina
471 HiSeq 2000 (http://uagc. arl.arizona.edu). Phage genomes derived from the Illumina
472 reads were assembled using the Newbler assembly software package (454 Life Sciences,
473 Branford, CT) with all settings set to default. Illumina reads for the passaged phages were
21 474 recruited to the ancestral phage genomes using Bowtie2 (version 2.2.5; Langmead and
475 Salzberg, 2012) with default settings, converted with Samtools (version 1.2; Li et al.,
476 2009) and visualized with Tablet (version 1.14.11.07; Milne et al., 2013). Genomes and
477 proteins were compared using blastn and blastp and genomes were aligned using
478 progressive Mauve (Darling et al., 2010).
479 All φ4:1 and φ17:2 phages (both ancestral and passaged) and the bacteria they had
480 been replicated on were sequenced using PacBio SMRT sequencing. SMRT sequencing
481 was performed at the DOE Joint Genome Institute using the Pacific Biosciences RS
482 instrument with C2 chemistry (Travers et al., 2010). The average SMRT sequence
483 coverage per genome ranged from 32–53X for the host strains and 532–554X for the
484 phages. DNA modification detection and motif analysis was performed using the PacBio
485 SMRT analysis platform (protocol version=2.2.0 method=RS Modification and Motif
486 Analysis.1, http://www.pacb.com/devnet/code.html). Briefly, short reads and sequencing
487 adapters were removed using SFilter. Filtered reads were aligned to the reference genome
488 using BLASR(v1) (Chaisson and Tesler, 2012). Modified sites were then identified
489 through kinetic analysis of the aligned DNA sequence data (Flusberg et al., 2010) and
490 motifs identified using MotifFinder (v1)2.
491
492 Statistics
493 The connection between host range and phage family was tested using a Kruskal-
494 Wallis test with a Dunn-test Post hoc with Bonferroni correction and the connection
495 between phage and host sampling year and location vs. host range was tested using
496 Welch Two Sample t-test using R (version 3.2.1). In these analyses the phages
22 497 investigated in Holmfeldt & Howard-Varona et al., 2014 was included. For host year and
498 location, the 1994 hosts were grouped together and the 2005 host was removed as only
499 one bacterium had been obtained from that location. Students-t tests were performed on
500 triplicates when comparing efficiency of infection and burst size of the passaged phages
501 compared to the ancestral phages using SPSS Statistics (version 22).
502
503 Nucleotide sequence accession numbers
504 The assembled genomes for the passaged phages has been deposited in GenBank
505 and assigned the accession numbers KT962245-962247. Bacterial genomes have
506 GenBank accession numbers NZ_ATLH01000000, NZ_ATLG01000000, and
507 NZ_CP009976.
508
509 Acknowledgments
510 We thank Emelie Nilsson for statistical assistance. We thank reviewers for
511 insightful comments improving the manuscript. The study was sponsored by postdoctoral
512 fellowships from the Swedish Research Council (623-2012-1395 and 623-2010-6548) to
513 KH, and Gordon and Betty Moore Foundation awards (GBMF2631 and GBMF3790) to
514 MBS. Work conducted by the U.S. Department of Energy Joint Genome Institute was
515 supported by the DOE Office of Science (DE-AC02-05CH11231).
516 Conflict of interest
517 The authors declare no conflict of interest.
518
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34 764 Tables
765 Table 1. Methylations detected in the bacterial and phage genomes. Modified base marked bold.
Organis motif string modification # detected # genome Mean Mean Mean Objective m type Score IpdRatio Coverage Score #4 No modifications detected #13 GAGNNNNNRTGT1 m6A 290 315 59.2 7.1 31.9 15936.7 #13 ACAYNNNNNCTC1 m6A 288 315 57.4 6.1 32.1 15248.3 #13 AGGAAT m6A 3686 4071 57.5 5.5 32.4 193870.1 #17 ACAGNNNNNGGA2 m6A 471 479 66.9 8.6 34.2 31052.7 #17 TCCNNNNNCTGT2 m4C 302 479 43.3 3.1 37.9 8640.6 #17 GAAGNNNNNGRTY3 m6A 717 751 59.8 7.8 33.1 41106.7 #17 RAYCNNNNNCTTC3 m6A 707 751 59.3 5.7 33.1 39710.5 #17 CTAGNNNNRTC4 m6A 166 566 41.4 5.0 37.8 2277.2 #17 GAYNNNNCTAG4 m6A 121 566 40.9 3.8 38.7 1235.0 #18 CAGNNNNNRTATT5 m6A 508 511 81.9 7.3 49.9 41391.1 #18 AATAYNNNNNCTG5 m6A 507 511 81.3 6.4 49.8 40923.5 #18 CCAGTV modified_base 608 2935 40.0 2.9 47.4 5898.4 #18 CCTGGDY m4C 175 1014 41.2 2.6 53.6 1482.5 φ 4:1 CTYCAG m6A 169 169 763.9 8.1 554.3 129104.0 φ 4:1_13 CTYCAG m6A 169 169 720.7 7.8 531.6 121791.0 φ4:1_18 CTYCAG m6A 169 169 648.5 7.3 532.8 109595.0 φ17:2 CTYCAG m6A 170 171 654.2 7.5 522.9 110628.5 φ17:2_18 CTYCAG m6A 171 171 686.2 7.5 549.0 117347.0 766 1-5Marks motif pairs.
35 767 Figure legends
768 Figure 1. Efficiency of infection for 38 Cellulophaga phages (rows) against 19 C.
769 baltica strains (columns). Infection is shown as relative number of Plaque forming
770 units (PFU) ml-1 compared to the infection with highest efficiency per phage, where
771 darker color corresponds to higher efficiency of infection. The phages are divided into
772 their respective families and genera according to (Holmfeldt et al., 2013) and
773 (Holmfeldt et al., 2007) for φ39:2, φ40:2, φ50:1, φ73:1, and φ19:4. Phages are
774 arranged with the genus that infects the highest number of bacteria at the top and
775 smallest number of bacteria at the bottom. Bacteria are arranged with the bacterium
776 that can be infected with the highest number of phages to the left and the smallest
777 number of phages to the right. Phage families and genera displayed on the left; M)
778 Myoviridae, P) Podoviridae, S) Siphoviridae, Mi) Microviridae, and ss) unclassified
779 single stranded DNA phage. Sampling location (bacteria only) and year is presented
780 at the bottom and to the left. All phages were sampled at the same location, Öresund.
781 Host location correspond to O) Öresund, S) Svaneke, E) Ellekilde Hage, and B) Baltic
782 Proper. 1-6 represent phages of the same population based on >95% ANI on >80% of
783 genes.
784
785 Figure 2. Genome comparison of ancestral Cba4 phages φ4:1 and φ17:2. A)
786 Alignment using progressive Mauve where a similarity plot gives the degree of
787 similarity between the genomes and the height of the plot is proportional to the
788 average nucleotide identity. Below each similarity plot colored annotated genomes
789 are presented. B) Pie chart showing the proportion of shared genes at different
790 nucleotide identity levels.
791
36 792 Figure 3. Efficiency of infection of the ancestral and passaged phages presented as
793 percentage of the efficiency of infection on the original hosts. A) Example of
794 shuffling experiment of phage φ4:1 infecting hosts #4 and #13 with efficiency of
795 infection given as percentage of efficiency of infection on host #4. Efficiency of
796 infection for B) phages originating from phage φ4:1 and C) phages originating from
797 phage φ17:2. Bar graphs show mean of three replicates of plaque assays of purified
798 phages and two replicates of shuffled phages ± standard deviation.
799
800 Figure 4. One-step growth curves of A) φ4:1 infecting #4, B) φ4:1 infecting #13, C)
801 φ4:1 infecting #18, D) φ4:1_13 infecting #4, E) φ4:1_13 infecting #13, F) φ4:1_18
802 infecting #4, and G) φ4:1_18 infecting #18. Phage abundance is presented as
803 normalized to average total phage abundance before burst. Black squares represent
804 total phage abundance and grey squares represent free phage abundance. Burst size
805 and latent period (in h) ± standard deviation (n=3) is presented in each graph.
806
807 Supplemental information
808 Supplemental Table 1. Efficiency of plating for 44 Cellulophaga phages (rows)
809 against 19 C. baltica strains (columns). Infection is shown as relative number of PFU
810 ml-1 compared to the infection on the host with highest efficiency per phage. The
811 rows and columns are structured as in Figure 1 with the addition of the 6 phages
812 investigated in Holmfeldt and Howard-Varona et al., (2014).
813
814 Supplemental Table 2. Genes shared (%) at >95% average nucleotide identity
815 among closely related Cellulophaga phages divided by genus. A) Cba184, B)
816 Cba131, C) CbaSM, D) Cba41, E) Cba 181.
37 817
818 Supplemental Table 3. Synonymous and non-synonymous DNA changes in the
819 genomes for two phages within the genus Cba481.
38