Globally occurring pelagiphage infections create ribosome-deprived cells

Domain: earth_science
Published: 2024-05-02
Editorial outcome: accept

Abstract
Phages play an essential role in controlling bacterial populations. Those infecting Pelagibacterales (SAR11), the dominant bacteria in surface oceans, have been studied in silico and by cultivation attempts. However, little is known about the quantity of phage-infected cells in the environment. Using fluorescence in situ hybridization techniques, we here show pelagiphage-infected SAR11 cells across multiple global ecosystems and present evidence for tight community control of pelagiphages on the SAR11 hosts in a case study. Up to 19% of SAR11 cells were phage-infected during a phytoplankton bloom, coinciding with a ~90% reduction in SAR11 cell abundance within 5 days. Frequently, a fraction of the infected SAR11 cells were devoid of detectable ribosomes, which appear to be a yet undescribed possible stage during pelagiphage infection. We dubbed such cells zombies and propose, among other possible explanations, a mechanism in which ribosomal RNA is used as a resource for the synthesis of new phage genomes. On a global scale, we detected phage-infected SAR11 and zombie cells in the Atlantic, Pacific, and Southern Oceans. Our findings illuminate the important impact of pelagiphages on SAR11 populations and unveil the presence of ribosome-deprived zombie cells as part of the infection cycle.

Introduction
Pelagibacterales, known as the SAR11 clade, are small free-living marine bacteria that account for 20–50% of planktonic cells in the oceans and are crucial components of marine biogeochemical cycles1. The reasons for their ecological success in the pelagic ocean are still being elucidated1. One proposed explanation was that SAR11 are slow-growing defense specialists, minimally affected by phage predation2. However, several phages infecting SAR11 (pelagiphages) have been described3–7 and studied through cultivation and sequencing efforts with increasing attention in recent years. Metagenomic and -viromic studies not only explored the functional abilities of their genomes8 but also suggest that pelagiphages, including uncultivated representatives, are the most abundant phages in the ocean3,9–12. Despite the ubiquity of pelagiphages, they appear to have low lytic activity within the host population13,14. However, direct quantifications of pelagiphage infected cells, and thus investigations of their role in controlling SAR11 abundance, have not been done so far.

In a recent study, we identified a contrary trend of cell division rates and cell abundances of SAR11 during the 2020 phytoplankton spring bloom at Helgoland Roads, German Bight15. Phytoplankton spring blooms are characterized by high phytoplankton-derived organic matter availability and a recurring succession of fast-growing specialized bacterial taxa16. Due to low abundances during phytoplankton blooms, SAR11 was generally considered to be outcompeted by specialized taxa. However, when growth rates of SAR11 were measured during the 2020 phytoplankton bloom, SAR11 grew at ~1.9 divisions d−1, while cell abundances decreased by ~90% over 5 days15. As this decrease was specific to SAR11 (compared to other abundant bacterioplankton), we hypothesized viral-induced mortality to cause the discrepancy15. Here, we quantified the number of pelagiphage-infected cells using advanced microscopy techniques. We first established the protocol on pure cultures of the pelagiphages and their hosts and subsequently assessed infection dynamics throughout the phytoplankton spring bloom described above. For a global perspective, we analyzed the distribution of pelagiphage-infected SAR11 cells in cruise samples across the Pacific, Atlantic, and Southern Ocean. Our investigation of the pure cultures and environmental samples has led us to discover ribosome-deprived but phage-infected cells, a new phenomenon during phage infection.

Results
Quantifying phage-infected SAR11 cells and discovery of zombie cells
To characterize pelagiphage:SAR11 interactions, we designed fluorescence in situ hybridization (FISH) probes for the three pelagiphages HTVC027P10, HTVC031P4, and Greip (Iscarvirus greipi; EXVC021P; closely related to HTVC010P)11,17, that were isolated on the SAR11 strain Candidatus Pelagibacter ubique HTCC1062. We targeted those pelagiphages, as they are amongst the most abundant phages globally3,10 and could be detected in metagenomes originating from the same phytoplankton bloom as described above18. These phages are lytic, and a temperate infection can be excluded. We tested hybridization conditions and stringency of the newly designed probes on cultures of Ca. P. ubique HTCC1062 infected with either HTVC027P or HTVC031P (Fig. 1). Positive controls with Greip were not available to us. As negative controls, we included samples of pelagiphage HTVC023P, which is phylogenetically closely related to HTVC027P10 but is not targeted by the designed probes (Fig. S1). In a first experiment, we found through FISH and high-throughput image cytometry that 70.0±7.0% (mean±sd; HTVC027P, n=3) and 17.4±10.1% (HTVC031P, n=3) of the cells were infected in non-synchronized cultures. The negative control of HTVC023P (n=3) contained <0.1% of false positive signals (Fig. S1, Supplementary Data 1). In an independent second experiment, 36.3±2.7% (mean±sd) and 32.4±5.0% of cells were infected with HTVC027P (n=3) 18 and 26h after infection, respectively (Fig. 1). Additionally, 14.3±6.6% and 17.2±6.8% of cells were infected with HTVC031P (n=3) 20 and 28h post-infection, respectively (Fig. 1). In all positive controls, we consistently noticed phage-infected cells with no detectable ribosomal RNA signal (22.7±3.1% (t18) and 23.1±3.6% (t26) of total cell counts for HTVC027P; 25.8±17.4% (t20) and 30.4±24.6% (t28) for HTVC031P; Fig. 1, Supplementary Data 1). We named these “zombie” cells as they are probably in a transitional state between living and dead cells. Zombies are different from so-called ghost cells, which were defined as non-living cell envelopes lacking nucleoids19 or any cytoplasmic content including DNA20. In contrast, all zombie cells contained DNA. We excluded the possibility that zombie cells are free phages since they were too large to be individual phages or vesicles according to our image analysis criteria (Supplementary Data 2).

Phage-infection regulates SAR11 abundance during phytoplankton bloom
To investigate the impact of pelagiphages on the SAR11 host population in the environment, we analyzed 67 samples collected over 133 days in spring 2020 at Helgoland Roads, German Bight. Previously, we showed that fast cell division rates in SAR11 coincided with a rapid decrease in cell abundances (at the end of March and in May; Fig. 2)15. We could identify phages as a plausible cause for this unintuitive decrease in cell abundances by quantifying the amount of pelagiphage-infected SAR11 cells in our samples. We found two peaks of phage-infected (i.e., ribosome-containing and pelagiphage positive) SAR11 cells, in late March and in early May, accounting for up to 9% and 19% of SAR11 cells, respectively (Fig. 2C). During the remaining sampling period, the abundances of phage-infected cells were close to the detection limit (Fig. 2C) and cell division rates were low (Fig. 2B). These findings highlight the importance of the timing of sampling, potentially explaining why SAR11 phage infection was considered low in earlier studies13,14,21. We next assessed the SAR11 community composition in metagenomes from the same phytoplankton bloom sampling campaign in 202018. We determined relative abundances of 16S rRNA gene sequences and metagenome-assembled genomes (MAGs), classified as Pelagibacterales, by read mapping. The outcomes from both abundance estimates indicate that the SAR11 community is dominated by the same populations throughout the bloom situation (Fig. 3). Individual assessments of the three pelagiphages HTVC027P, HTVC031P, and Greip, revealed that HTVC031P infected more SAR11 cells than the other two phages during high infection periods. However, differences between the three phages were minor (Fig. S2A), highlighting that infections with each of the three pelagiphages are important in situ. As bioinformatic analyses revealed that the dominating SAR11 species fluctuates simultaneously (Fig. 3) and there are little differences in abundance between the three phages, we believe all species are susceptible to the three assessed phages. Additionally, our findings are in contrast to bioinformatic analyses, that predict HTVC027P to be more abundant than the other two phages both globally10,11 and during our sampling period (Fig. S2B; this study). This stresses the importance of experimental evidence for quantification approaches in phage ecology. Differences in abundance estimates between metagenomic and microscopy-based approaches are well-known for bacteria and similar causes may apply for phage abundances. Primer and assembly biases might skew bioinformatic approaches, while low signal intensities might underestimate microscopy-based abundances.
Zombie cell (i.e., ribosome negative but pelagiphage positive) abundances coincided with the number of phage-infected SAR11 cells during the phytoplankton bloom. They were increased at the end of March (max. 7.1% of total cell counts) and early May (max. 14.4%), when phage-infected (i.e., ribosome and pelagiphage positive) SAR11 abundances were highest (Fig. 2). To exclude that the here-assessed pelagiphages cross-infected other bacteria besides SAR11, we visualized all bacteria with the EUBI-III probe22. We could not observe a significant difference of zombie abundances (i.e., ribosome negative, but pelagiphage positive) between all bacteria (mean±sd: 3.4×104±1.6×104 cells ml−1) and SAR11 (4.2×104±2.9×104) over five time-points from 27th April to 4th May (Fig. S3; F(1,1)=0.61, p=0.578, repeated measures ANOVA; Supplementary Data 3). Hence, we conclude that the assessed phages are SAR11-specific. Consequently, the here-observed zombie cells always derived from SAR11 cells.

Global distribution of phage-infected and zombie cells
To assess the broader relevance of our findings, we next examined the global distribution of phage-infected SAR11 and zombie cells in samples collected from surface and deep-chlorophyll maximum water in the Atlantic (cruise PS13223; 21 samples from 11 stations; Aug–Sept 2022), Southern (cruise PS13324; 22 samples from 11 stations; Oct–Nov 2022), and Pacific Ocean (cruise SO24525; 38 samples from 15 stations; Dec 2015–Jan 2016; Fig. 4 and Fig. S4). We detected phage-infected (i.e., ribosome and pelagiphage positive) SAR11 and zombie cells (i.e., ribosome negative but pelagiphage positive) across all three transects (Fig. 4), indicating their global abundance and importance. Phage infection exhibited the lowest prevalence in the Pacific (mean±sd: 1.3±1.2% of SAR11 cell counts), while the Atlantic (2.9±1.6%) and Southern Ocean (3.3±1.4%) showed higher infection rates. In contrast to phage-infected SAR11 cells, zombie cell abundances were highest in the Pacific (mean±sd: 5.1±5.1% of total cell counts), followed by lower abundances in the Southern (4.3±1.8%) and Atlantic (2.5±1.2%) Oceans. SAR11 phage infection and zombie cell abundances were less prominent in the assessed transects compared to the relatively high infection stages observed in the Helgoland Roads phytoplankton bloom data. This suggests that our cruise samples might not have coincided with periods of intense infection by the assessed phages. Nevertheless, across all samples (transects and time-series data), we found a positive correlation between the relative abundance of phage-infected and zombie cells (Fig. S5A; 0% of posterior distribution ≤0), a negative correlation between the relative abundance of zombie and SAR11 cells (Fig. S5B; 0% of posterior distribution ≥0), and a positive correlation between the relative abundance of phage-infected SAR11 cells and the frequency of dividing cells, which is a proxy for cell division activity (Fig. S5C; 0.000125% of posterior distribution ≤0)15. This indicates higher infection rates in faster-growing hosts. Our microscopic evidence of phage-infected and zombie cells indicates that they are globally distributed and suggests that zombie cells are an integral part of pelagiphage infections.

Methods
Environmental sampling
Samples were collected during the 2020 phytoplankton spring bloom from ~1 m depth at the long-term ecological research station Helgoland Roads (54°11.3′N, 7°54.0′E), German Bight15 (Supplementary Data 6). Samples from the Atlantic and Southern Ocean were collected using a Seabird SBE 911+ CTD in 2022 during the R/V Polarstern cruises PS13223 and PS133/124, respectively39. Samples from the Pacific Ocean were collected with a Seabird SBE 911+ CTD during the R/V Sonne cruise SO24525. SAR11 cell counts from SO245 were retrieved from ref. 40 During the cruises, samples were collected from surface water and deep-chlorophyll maximum (DCM; Supplementary Data 6). Samples were fixed with formaldehyde (1% final concentration) for 1 h at room temperature. Cells were immobilized on 0.2 µm polycarbonate filters (Merck Millipore, Burlington Massachusetts, US), which were stored at −20 °C until further processing. The final sampling volume varied depending on total cell counts in the samples (Supplementary Data 6).

Cultivation of Candidatus Pelagibacter ubique infected with HTVC031P, HTVC027P, and HTVC023P
The SAR11 strain Candidatus Pelagibacter ubique HTCC1062 was kindly provided by Professor Stephen Giovannoni, Oregon State University, USA. HTCC1062 was cultured in artificial seawater-based ASM1 medium supplemented with 1 mM NH4Cl, 100 µM KH2PO4, 1 µM FeCl3, 100 µM pyruvate, 50 µM glycine, and 50 µM methionine38. HTCC1062 cultures were incubated at 17 °C without shaking and light. Exponentially growing HTCC1062 cultures were infected with HTVC023P, HTVC027P, and HTVC031P independently at a phage-bacteria ratio of ~10:1 in triplicates. Cell mortality was monitored using the Guava EasyCyte flow cytometer (Millipore, USA). When cell mortality was detected, samples were fixed with formaldehyde (1% final concentration) for 1 h at room temperature and filtered on 0.2 µm polycarbonate filters (Merck Millipore, Burlington Massachusetts, US). In a repeated experiment, Ca. P. ubique HTCC1062 were infected with HTVC027P and HTVC031P, as described above. Samples were taken from three time-points (2 h after infection; ~2 h before cell lysis; ~6 h after cell lysis) and fixed and filtered as described above. In an independent second experiment, 36.3±2.7% (mean±sd) and 32.4±5.0% of cells were infected in non-synchronized cultures. The negative control of HTVC023P (n=3) contained <0.1% of false positive signals (Fig. S1, Supplementary Data 1). In an independent second experiment, 36.3±2.7% (mean±sd) and 32.4±5.0% of cells were infected with HTVC027P (n=3) 18 and 26 h after infection, respectively (Fig. 1). Additionally, 14.3±6.6% and 17.2±6.8% of cells were infected with HTVC031P (n=3) 20 and 28 h post-infection, respectively (Fig. 1).

Pelagiphage FISH probe design and synthesis
We designed direct-gene FISH41 probes based on alignments between each of the three isolates, namely HTVC027P, HTVC031P, and Greip, and PacBio Sequel II metagenomes from the 2020 spring phytoplankton bloom at Helgoland, North Sea18 (ENA PRJEB52999). Target probe-regions were identified from assembled contigs (Supplementary material and methods). Subsequently, probes were designed manually within Geneious (v2022.1.1)42. We aimed for 10–13 probes per phage of 156–318 bp length and a GC content similar to the phages (22.0–43.2%, mean±sd: 32.9±4.9%). Further, reference genomes and metagenome data from Helgoland Roads needed to share a minimum of 90% nucleotide identity for usability during FISH43. We aimed to target genes encoding terminases, polymerases, or structural proteins, as we expect higher conservancy in these genes. Ambiguous alignment with any other sequence was excluded, against the nt database using the NCBI BLAST web service (February 14th 2023).
Probes (Supplementary Data 7) were ordered as “oPools” from integrated DNA Technologies (IDT, Coraville, Iowa, USA) and resuspended in water as directed by the manufacturer. Probes were labeled with the ULYSIS Alexa 594 conjugation kit (Invitrogen, Waltham, Massachusetts, USA) with double the suggested fluorophore concentration, as this successfully enhances the labeling efficiency43. Labeled probes were subsequently purified using Micro Bio-Spin chromatography columns P-30 (Bio-Rad, Hercules, California, USA). Labeling efficiencies were calculated as described by Invitrogen, using a NanoDrop (Thermo Fisher Scientific, Waltham, Massachusetts, USA).

Fluorescence in situ hybridization
First, CARD-FISH targeting the 16S rRNA of SAR11 (“SAR11-mix”, Supplementary Data 7) was conducted (details see Supplementary Methods)44. Secondly, samples were hybridized with equimolar amounts of the probes targeting HTVC027P, HTVC031P, and Greip, using direct-gene FISH as described earlier (details see Supplementary Methods)41,43 with minor modifications. Hybridization buffer with 25% formamide was used and no ethanol washing was conducted after FISH to prevent any loss of fluorescence signal. Hybridized filters were counter-stained with the DNA stain 4′,6-diamidino-2-phenylindole (DAPI; 1 µg ml−1). Samples were embedded in ProLong Glass Antifade (Invitrogen, Waltham, Massachusetts, USA) for microscopy. As negative controls, samples of HTVC023P were hybridized with the probe mix, targeting all three phages. Additionally, environmental negative controls included samples which were not exposed to the phage-probe mix to account for any autofluorescence within cells.

Microscopy
Samples were imaged on a Zeiss AxioImager.Z2m, equipped with a charged-coupled device (CCD) camera (Zeiss AxioCam MRm, Zeiss, Oberkochen, Germany), and illuminated with a Zeiss Colibri 7 LED (excitation: 385 nm for DNA, 469 nm for 16S rRNA CARD-FISH, and 590 nm for direct-gene FISH signals). The microscope was equipped with a multi-Zeiss 62 HE filter cube (Beamsplitter FT395+495+610). Images were recorded with a custom-built macro45,46 within the Zeiss AxioVision software (Zeiss, Germany). A total of 120 fields of view per sample were recorded with a 63x Plan Apochromat objective (1.4 NA, oil immersion). For high-resolution imaging, we used a Zeiss LSM780 (Zeiss, Oberkochen, Germany), with an ELYRA PS.1 detector upgrade. The microscope was equipped with a 63x plan apochromatic oil immersion objective and the excitation lasers 405 nm (DAPI), 488 nm (16S rRNA CARD-FISH), and 591 nm (direct-gene FISH).

Image cytometry
Quality control and automated cell counting of 8-bit greyscale images was done within the Automated Cell Measuring and Enumeration tool (ACME, available from https://www.mpi-bremen.de/automated-microscopy.html)45,46 with channel-specific settings (Supplementary Data 2). Cells for total cell counts were defined by a DNA (DAPI)-specific signal. SAR11 cells were defined with an overlapping DNA and 16S rRNA (CARD-FISH) signal and phage-infected cells needed an additional phage (direct-gene FISH) signal. Zombies were cells with a phage signal but no 16S rRNA signal. We calculated the frequency of dividing cells—a proxy for cell division rate—as previously described15 using the MicrobeJ plugin47 within Fiji/ImageJ48. In principle, a cell containing two local DNA maxima was counted as a dividing cell.

Metagenomic abundance estimates for SAR11 MAGs, 16S rRNA gene, and Pelagiphages
To determine the relative abundance of SAR11 metagenome-assembled genomes (MAGs) during the 2020 phytoplankton spring bloom, we performed a mapping analysis utilizing PacBio metagenomic reads obtained from the prokaryotic fraction (0.2–3 µm) across all 30 samples. The reference MAGs, classified under the order Pelagibacterales by gtdb-tk (v1.3.0, release 202)49, were initially derived from the same phytoplankton bloom metagenomes, described above18. Raw reads were mapped using the minimap2-pb50 algorithm, executed within the SqueezeMeta pipeline (version 1.3.1)51. The mapping outcomes were normalized using the reads per kilobase per million mapped reads (RPKM) metric, which considers both the length of the MAG and the library size of each sample. The RPKM value was determined using the formula RPKM = (Reads mapped to SAR11 MAG * 10^6) / (total read in a sample * length of MAG in kilobase pairs).
For quantifying the abundance of the 16S rRNA gene, we extracted the full-length 16S rRNA sequences from metagenome assemblies using Barrnap (version 0.9; https://github.com/tseemann/barrnap). Similar to the SAR11 MAGs, these sequences underwent mapping, and their relative abundance was computed using the RPKM method as described earlier.
To assess the relative abundance of phages HTVC027P, HTVC031P, and Greip, mapping of metagenome reads to the reference genomes of these phages were performed in the similar fashion. To facilitate a comprehensive comparison with our microscopy data, and considering the specificity of these phages to SAR11, we calculated the abundance of these Pelagiphages relative to SAR11 community present during spring phytoplankton bloom in 2020. Therefore, phage relative abundance was determined as (Reads mapped to phage genome * 10^6) / (read mapped to all SAR11 MAGs * length of phage in kilobase pairs).

Identification of defense systems within SAR11 genomes
All available Pelagibacter ubique genomes (n=172) available in the RefSeq database (from October 22nd, 2023)52 and MAGs from the 2020 phytoplankton spring bloom (n=14)18 were screened for anti-phage defense mechanisms. DefenceFinder53 was used with the default database from October 22nd, 2023.

Statistics and modeling
Statistical analyses and corresponding visualizations were done in R (v4.2.2)54 (for used packages see supplementary material and methods). Repeated measures ANOVA was used to test for the specificity of pelagiphages to SAR11. Zombies were detected in all bacteria, using the 16S FISH probe EUBI-III, and compared to zombies in SAR11 (SAR11-mix, Supplementary Data 7). Samples originated from the time series and were not independent from each other. Thus, repeated measures ANOVA was chosen.
Bayesian beta regressions were applied to assess the relationship between (a) the abundance of phage-infected and zombie cells, with the model formula rel_infT ~ Zombie_cells and (b) abundance of zombie and SAR11 cells, using the model formula Zombie_cells ~ rel_SAR11_abundance. rel_infT is the relative infection rate, transformed by adding 0.001 because two values of the data (148 data points) originally contained 0 for which the beta distribution is not defined; Zombie_cells is the relative abundance of Zombie cells; rel_SAR11_abundance is the relative SAR11 abundance; and FDC_percent is the frequency of dividing cells. The model predictions were back-transformed from the logit-scale for the plots in Fig. S5.
a. We assumed a positive relationship between phage-infected cells and Zombie cells, as the 95% credible interval [4.083, 9.554] of the slope (on logit-scale) excluded 0 and all values of the posterior distribution for the slope were ≥ 0. The model predicts an intercept of −3.72±0.1 and a slope of 6.92±1.41 (on logit-scale; means±SD).
b. A negative relationship was assumed between the relative abundances of zombie and SAR11 cells, as all values of the posterior distribution for the slope were < 0. The 95% credible interval was [−2.800, −0.953] (on logit-scale). The model predicted an intercept of −2.74±0.1 and a slope of −1.87±0.5 (on logit-scale; mean±SD).
c. We assumed a positive relationship between phage-infected cells and Zombie cells, as the 95% credible interval [0.02, 0.05] of the slope (on logit-scale) excluded 0 and only 1 of the 8000 values of the posterior distribution for the slope was ≤0. The model predicts an intercept of −3.72±0.1 and a slope of 0.04±0.01 (on logit-scale, mean±SD).
In the model, flat priors (brms default) were used and 2000 iterations for 4 chains after a warmup period of 2000 iterations per chain.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "I found the authors' comments and revisions satisfactory and have no additional comments.", "reviewer_3": "This is a much improved version, and the authors have answered the large majority of my questions.\nI still have a few concerns (more minor than before):\nLine 51. The statement that the decrease was taxon-specific needs more explanation. It was not even\nobvious to me after looking at the cited paper. Is this meant to say SAR11 and only SAR11 declined so\nmuch while other similar sized organisms did not, so might imply grazing was an unlikely contributor\nto the loss?\nFig 1. This better supports the authors’ conclusions, but I still wonder what happened to yield the\nprevious images I had commented on that gave a very different impression (see prior review). It\nmakes me worry a bit about “cherry picking” supportive images.\nLines 113-116 and Fig 3 re SAR11 strains staying the same.: It is very hard to use read mapping to\nbe certain that strains do not change, especially when only the average coverage is shown.\nRead mapping cannot show anything about “new” genes present in environmental genomes but\nlacking in the reference genomes. And did a close look at the read maps show consistent coverage\nalong the entire genome, or were there islands (indicative of strain differences) ? It would not show up\nunless you look closely at the coverage maps (e.g. with anvi'o). And 16S data is too phylogenetically\ncoarse to detect strain differences so you can’t really rely on that. Also - MAGs notoriously miss most\nSAR11 organisms because of microdiversity breaking up the contigs. Big marine MAG collections have\na tiny fraction in SAR11 even though the group represents about a third of the organisms, so those\nmaking MAGS are highly atypical.\nFig. 2. Panel D is potentially confusing or even misleading. The same scale is used for % infected\nSAR11 only and for % of all cells being zombies. But SAR11 is only about a third of cells, so putting\nthem on the same graph with the same scale could easily give a false impression. I suggest two\ngraphs with clearly labeled axes (even though the legend explains – easy to miss the nuance).\nLine 151. but by Fig 2 it looks like Zombies exceed infected SAR11, especially given the percentage of\ninfected cells is SAR11 only and Zombies is all cells. Seems to be a discrepancy needing explanation.\nsee below\nLines 162-165. In the Pacific only 1% of SAR11 cells alone were infected, but 5% of all cells (e.g.\nabout 15 times the number of infected SAR11 cells) were zombies. Begs for an explanation here – e.g.\nmany or probably the large majority of zombies are clearly not infected SAR11 cells. Other species\nmaking zombies? If so why report the totals when it is comparing “apples and oranges”? Seems\npotentially misleading without clear explanations.\nLine 194 – Here saying zombies are correlated to phage infected SAR11 again seems misleading when\nin the Pacific there are about 15 X as many zombies as infected SAR11. Really need to be up front\nabout this and what it means.\nLine 216-217. Reporting that these authors previously showed SAR11 regulate RNA content seems to\nbe a stretch of the facts. When I looked at the previous paper it showed ribosome content was indeed\nhigher per cell in some samples, but tellingly in those exact same samples the cells were much larger\n(especially considering biovolume varies as the cube of diameter). So it could just be that ribosomes\nare a particular fraction of cytoplasm and therefore it may not be regulation of RNA at all but simply\nmore cytoplasm having more ribosomes. And faster growing cells are bigger. I think the claim of\nspecific RNA regulation should be removed.\nLines 286-287. While this could explain why there are so many more zombie cells than infected SAR11\nit should be clarified throughout the manuscript when comparing total zombies and fraction of infected\nSAR11. The rest of the manuscript implies it is all about SAR11, by omission of this discussion.\nLines 407-409. defense mechanisms are easily lost in MAG production because they often have\ndifferent tetranuceotide frequencies than the underlying core genome and also not all members of a\nspecies have them.\nShould add a caveat about this."}, "author_response": "We thank the reviewer for their valuable time to evaluate our revised manuscript.\nThank you very much for your valuable feedback. Your previous and current comments have\nhelped us to considerably improve our manuscript.\nLine 51. The statement that the decrease was taxon-specific needs more explanation. It was\nnot even obvious to me after looking at the cited paper. Is this meant to say SAR11 and only\nSAR11 declined so much while other similar sized organisms did not, so might imply grazing\nwas an unlikely contributor to the loss?\nYes. This is correct and this is the fascinating observation: SAR11 declined much more in\nabundance than the other assessed bacterial groups. They also had the smallest cell sizes. It is\ngenerally accepted in microbial ecology that small cell sizes reduces the risk of being preyed\nupon by grazers. Consequently, the most plausible explanation to the SAR11 - specific decline\nis a viral-induced mortality.\nFig 1. This better supports the authors’ conclusions, but I still wonder what happened to yield\nthe previous images I had commented on that gave a very different impression (see prior\nreview). It makes me worry a bit about “cherry picking” supportive images.\nThank you for your comments. We took these very serious. As a consequence, we have\nanalysed 120 908 cells (in 555 field of views; HTVC027P) and 44 818 cells (in 636 field of\nviews; HTVC031P) and quantified the DNA (DAPI) and phage (direct-geneFISH) content. It\nturned out that the differences between phage-infected, ribosome-containing and zombie cells\nwere negligible (Fig. S6). Due to the spread of fluorescence signals it is challenging to\nchoose representative images, but we did our best to find suitable images and hope these will\nbe convincing now in the changed figures. For full transparency, all raw images have been\nprovided in the online repository.\nLines 113-116 and Fig 3 re SAR11 strains staying the same.: It is very hard to use read\nmapping to be certain that strains do not change, especially when only the average coverage\nis shown.\nRead mapping cannot show anything about “new” genes present in environmental genomes\nbut lacking in the reference genomes. And did a close look at the read maps show consistent\ncoverage along the entire genome, or were there islands (indicative of strain differences) ? It\nwould not show up unless you look closely at the coverage maps (e.g. with anvi'o). And 16S\ndata is too phylogenetically coarse to detect strain differences so you can’t really rely on that.\nAlso - MAGs notoriously miss most SAR11 organisms because of microdiversity breaking\nup the contigs. Big marine MAG collections have a tiny fraction in SAR11 even though the\ngroup represents about a third of the organisms, so those making MAGS are highly atypical.\nAll MAGs analyzed in our study were recovered from long-read PacBio HiFi metagenomes.\nLong-read metagenomes can help resolve complex genomic regions, including repetitive\nelements and structural variations, thereby reducing ambiguity associated with strain\nheterogeneity. Additionally, all MAGs were manually refined using anvi’o through visual\ninspection and consideration of coverage across samples, further reducing the uncertainty\nlinked with strain diversity. Our close inspection of coverage values across genes in the\nassessed MAGs suggest that although it's possible to have multiple strains within a single\nMAG, they're unlikely to shift in abundances over time. This suggests that the abundance\npattern we observed for a particular MAG arise from a homogeneous community.\nRegarding the 16S rRNA gene, while acknowledging its limited resolution in discriminating\nclosely related taxa or resolving fine-scale phylogenetic relationships, we emphasize the\nvalue of employing high-quality, full-length sequences. In Figure 3, the inclusion of full-\nlength 16S rRNA gene sequences (1470 bp in length) from PacBio HiFi metagenomes\nenhances the reliability of depicting genetic diversity.\nIn the manuscript, we intended to emphasize that the SAR11 populations and community\ncomposition did not change a lot. Due to the known challenges with SAR11 MAGs, we\nreplaced the word ‘species’ and ‘strains’ by ‘populations’ throughout the manuscript.\nFig. 2. Panel D is potentially confusing or even misleading. The same scale is used for %\ninfected SAR11 only and for % of all cells being zombies. But SAR11 is only about a third of\ncells, so putting them on the same graph with the same scale could easily give a false\nimpression. I suggest two graphs with clearly labeled axes (even though the legend explains –\neasy to miss the nuance).\nWe have changed the figure accordingly.\nLine 151. but by Fig 2 it looks like Zombies exceed infected SAR11, especially given the\npercentage of infected cells is SAR11 only and Zombies is all cells. Seems to be a\ndiscrepancy needing explanation. see below\nWe acknowledge that this might have been confusing. In this experiment we show that\nzombie cells were always derived from SAR11 cells and that no non-SAR11 cells were\ninfected by the assessed pelagiphages (as written in the text, relevant data can be found in\nsupplementary figure S3, not in figure 2). Therefore, there is no discrepancy, as phage-\ninfected cells (pelagiphage containing and ribosome positive) are different from zombie cells\n(pelagiphage positive but ribosome negative). To avoid the confusion, we changed the\nwording throughout the manuscript to make the differentiation clear.\nHere, we changed the text to:\nWe could not observe a significant difference of zombie abundances (i.e., ribosome negative,\nbut pelagiphage positive) between all bacteria (mean ±sd: 3.4x104 ±1.6x104 cells ml-1) and\nSAR11 (4.2 x104 ±2.9x104) over five time-points from 27th April to 4th May (Fig. S3;\nF(1,1)=0.61, p=0.578, repeated measures ANOVA; table S3). Hence, we conclude that the\nassessed phages are SAR11-specific. Consequently, the here-observed zombie cells always\nderived from SAR11 cells.\nLines 162-165. In the Pacific only 1% of SAR11 cells alone were infected, but 5% of all cells\n(e.g. about 15 times the number of infected SAR11 cells) were zombies. Begs for an\nexplanation here – e.g. many or probably the large majority of zombies are clearly not\ninfected SAR11 cells. Other species making zombies? If so why report the totals when it is\ncomparing “apples and oranges”? Seems potentially misleading without clear explanations.\nThank you for this comment. All zombie cells originally derived from ‘healthy’ (i.e.,\nuninfected SAR11) cells. However, they are not identified as SAR11 cells by our 16S rRNA\ntargeted probes anymore due to the lack of their ribosomes. We have rephrased parts of the\nmanuscript to make the differentiation clearer.\nLine 194 – Here saying zombies are correlated to phage infected SAR11 again seems\nmisleading when in the Pacific there are about 15 X as many zombies as infected SAR11.\nReally need to be up front about this and what it means.\nWe do acknowledge that the numbers are not identical, but the relative abundances of\npelagiphage infected SAR11 and zombie cells do correlate, as shown in Fig. S5. This\ncorrelation is apparent over all data (from all sampling campaigns) and also, when focusing\non samples from the Pacific only.\nLine 216-217. Reporting that these authors previously showed SAR11 regulate RNA content\nseems to be a stretch of the facts. When I looked at the previous paper it showed ribosome\ncontent was indeed higher per cell in some samples, but tellingly in those exact same samples\nthe cells were much larger (especially considering biovolume varies as the cube of diameter).\nSo it could just be that ribosomes are a particular fraction of cytoplasm and therefore it may\nnot be regulation of RNA at all but simply more cytoplasm having more ribosomes. And\nfaster growing cells are bigger. I think the claim of specific RNA regulation should be\nremoved.\nThe reviewer is correct in what we have previously observed (ref. 15) and what we have\nwritten here - the growth in cell volume is co-occurring with an increase in ribosome content.\nThe only explanation is that SAR11 regulates their number of ribosomes - the process of\nwhich is unknown. Nevertheless, we rephrased our statement:\nIn fact, we have previously shown the ability of SAR11 to modify their ribosome content\naccording to growth rates.\nLines 286-287. While this could explain why there are so many more zombie cells than\ninfected SAR11 it should be clarified throughout the manuscript when comparing total\nzombies and fraction of infected SAR11. The rest of the manuscript implies it is all about\nSAR11, by omission of this discussion.\nWe fully agree and have updated the manuscript accordingly (please see our comments\nabove). Thank you for the valuable feedback!\nLines 407-409. defense mechanisms are easily lost in MAG production because they often\nhave different tetranuceotide frequencies than the underlying core genome and also not all\nmembers of a species have them.\nShould add a caveat about this.\nFrom the 172 publicly available Ca. Pelagibacter ubique reference genomes (18 putative\ndefense mechanisms), six are derived from MAGs (of which one has a putative defense\nmechanism). The remaining reference genomes are SAGs or genomes of isolates, which are\nnot prone to assembly biases.\nRegarding our environmental MAGs, they originate from long-read metagenomes. As long-\nread metagenomes are expected to be less prone to assembly biases than short-read\nmetagenomes as outlined above, we do not expect a noticeable effect here."}]

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