Globally occurring pelagiphage infections create ribosome-deprived cells

doi:10.21203/rs.3.rs-4072578/v1

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Globally occurring pelagiphage infections create ribosome-deprived cells

https://doi.org/10.21203/rs.3.rs-4072578/v1

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published 01 May, 2024

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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 five 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 those 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.

General Microbiology

Marine and Freshwater Ecology

Virology

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 described and discussed^3–7, 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 ocean^3,9–12. Despite the ubiquity of pelagiphages, they appear to have low lytic activity within the host population^13,14. 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 five days¹⁵. As this decrease was taxon-specific, 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.

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 globally^3,10 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, Table S1). 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 hours 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 hours 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, Table S1). We named these “zombie” cells as they are probably in a transitional state between living and dead cells. Zombies are different from ‘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 (Table S2).

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 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 studies^13,14,21. 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 species or strains 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 strains fluctuate simultaneously (Fig. 3) and there are little differences in abundance between the three phages, we believe all strains 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 globally^10,11 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 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 SAR11 infection rates were highest (Fig. 2). To exclude that the phages cross-infected other bacteria besides SAR11, we visualized all bacteria with the EUB I-III probe²². We conclude that the assessed phages are SAR11-specific, as no significant differences were observed between zombie cell abundances in all bacteria (mean ± sd: 3.4x10⁴ ± 1.6x10⁴ cells ml^− 1) and SAR11 (4.2 x10⁴ ± 2.9x10⁴) over five time-points from 27th April to 4th May (Fig. S3; F(1,1) = 0.61, p = 0.578, repeated measures ANOVA; Table S3).

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 & Fig. S5). We detected phage-infected SAR11 and zombie cells 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.

In this study, we used direct-geneFISH to visualize and quantify the abundance of phage-infected SAR11 cells. We assessed the impact of phage infection on the SAR11 community during a phytoplankton bloom and showed the global distribution of phage infections by the assessed phages. We additionally discovered ribosome-deprived but phage-infected cells, whose abundance is correlated to the amount of phage-infected SAR11 cells.

During the phytoplankton bloom, up to 19% of SAR11 cells were phage-infected, which cooccurred with a ~ 90% decrease in SAR11 abundances. Assuming in situ phage lysis within 24 hours or faster⁵, our results are in line with global estimates of up to 30% phage-mediated cell lysis within one day^12,26. We interpret this as part of a ‘boom and bust’ cycle, where SAR11 cell abundances reached a critical population density that was subsequently reduced by phage infection. The “kill-the-winner” hypothesis describes the disproportionally higher phage-induced lysis rates of faster-growing bacteria. Further, different bacterial strains from the same species may succeed each other, especially in bloom situations, as the majority of phages are believed to be strain-specific^27,28. As metagenomic data suggest that the SAR11 community was dominated by the same species and potential strains¹⁸ (Fig. 3), our findings of fast-growing SAR11 and high infection rates suggest a ‘kill-the-winner’ behavior²⁸. In addition, the almost equal contribution of phage infection by the three assessed phages suggests that all the abundant strains are susceptible to the assessed phages. The dominance of individual strains succeeding each other would be in accordance with previously reported Red Queen dynamics, describing constantly changing host and viral communities on the fine strain level²⁹.

Zombie cells: Clever persisters or ‘phage puppets’?

Pelagiphage-infection of SAR11 cells results in the formation of zombie cells – cells devoid of any detectable 16S ribosomal RNA. Such a major cell transformation may be caused by a yet-unknown anti-phage defense system. Infected cells may digest their ribosomes to prevent phage proteins from being synthesized and reduce their metabolism – they may become ‘persisters’ as recently proposed³⁰. In fact, we have previously shown the ability of SAR11 to regulate their ribosome content according to growth rates¹⁵. However, no anti-phage defense system targeting rRNA or an abortive infection has been described for SAR11 or any other bacterium yet³¹. Nevertheless, we screened all SAR11 MAGs (n = 14), which could be recovered from the phytoplankton bloom in 2020, none of which contained any anti-phage system (Table S4). We further analyzed 172 publicly available Ca. P. ubique genomes, of which 19 contained putative anti-phage systems. These were all classified as restriction-modification (RM) systems and are involved in epigenetic modifications (i.e., methylation or phosphorothiolation of the ribophosphate) of the host DNA and restrictions of unmodified phage-DNA³² (Table S4). However, a close monitoring of HTVC027P and HTVC031P infections of batch-cultured HTCC1062 over time speak against an anti-phage system. Firstly, if an anti-phage system existed, zombie cells would enrich over time, while the phage would eventually lyse 16S rRNA-containing infected cells. We could not detect abundance differences 18 and 26 h (HTVC027P) or 20 and 28 h (HTVC031P) post-infection for both cell types (t(3.9) = -0.166, p = 0.88 for HTVC027P, t(3.6)=-0.26, p = 0.81 for HTVC031P, Welch’s two sample t-test, Fig. 1). Additionally, we assessed the phage DNA content by measuring the phage FISH fluorescence intensity. The fluorescence intensity in cells infected with HTVC027P increased over time (F(1) = 0.31, p < 0.001) indicative for ongoing phage DNA synthesis, but we could not detect differences between zombie and phage-infected 16S positive cells (F(1) = 0.303, p = 0.582, ANOVA, Fig. S6). For cells infected with HTVC031P, the fluorescence not only increased over time, but was also increased in the zombie cells, compared to the phage-infected 16S positive cells (F(1) = 100.18, p < 0.001). This indicates a continuous production of phage DNA in both, the zombie and the infected 16S rRNA containing cells and speaks against a defense mechanism. Lastly, the host’s DNA content, and consequently their abundance in metagenomes across the 2020 spring bloom, would remain unchanged, if zombies were a result of an anti-phage system. However, SAR11 cell abundances from FISH and metagenomic (MAG and 16S rRNA-based) data do fluctuate synchronously (Figs. 2 & 3), rendering the hypothesis of an anti-phage defense in SAR11 unlikely.

Alternatively, phage infection may result in phage-induced RNA degradation to recycle ribonucleotides for phage genome synthesis. In this case, the phages become the ‘puppet masters’ of the SAR11 host²⁶. The use of host RNA to build new phage genomes has previously been suggested for Prochlorococcus cyanophages³³ and is not limited to rRNA but may also include mRNA, tRNA, or other RNAs. In fact, we detected all intermediate stages between phage-infected with and without a ribosomal signal, suggesting the general use of RNAs (Fig. S7). In the pure cultures of HTVC027P, we assessed the 16S FISH signal areas, which were truncated at the lower detection limit, indicating a continuum of decreasing ribosomal content (Fig. S7). Hence, there is no switch (i.e., “yes” or “no”) whether ribosomal RNA is used during phage infection but rather suggests a continuous use of all available RNA to complement the nucleotide pool.

The annotation of HTVC031P revealed the presence of ribonucleases and deoxyribonucleotide dehydrogenase subunits alpha and beta (Table S5), which are essential for the breakdown of RNA and the subsequent conversion to DNA nucleotides. On the genome, the ribonucleases and dehydrogenases were middle genes, located and transcribed between DNA replication (early) and structural (late) phage proteins encoding genes³⁴. Timing is essential, as nucleotides must be available early in the infection cycle, while phages rely on host ribosomes, which should not be digested too early. In the case of HTVC027P and Greip, the dehydrogenase genes were not found in their genomes. Either host proteins or one of the many uncharacterized proteins (Table S5) may be used. RNA nucleotides are a valuable resource, especially when DNA nucleotides are scarce. Nucleotides are frequently a limiting factor. For example, cyanophages not only enhance their host’s photosynthesis activity but also modify the host’s metabolism to increase nucleotide production³⁵, although the host genomes are much larger than SAR11. SAR11 have amongst the smallest genomes (~ 1.3 million base pairs) of free-living bacteria¹, and they might have epigenetic modifications in their DNA (discussed above), reducing the availability of DNA nucleotides³⁶. At the same time, SAR11 have an estimated 150–700 ribosomes per cell³⁷, which equates to 0.6-3.0 million bases of single-stranded RNA. This could be a valuable resource, almost doubling the number of nucleotides available for double-stranded DNA phage genomes. To summarize, while we cannot entirely exclude an anti-phage system as a cause for zombie cells, we believe phage-induced ribosome digestion is more likely.

We present the first microscopic quantification of phage-infected SAR11 cells in situ, advancing our understanding of SAR11 clade dynamics, and present zombie cells as a new phenomenon. We demonstrate that pelagiphage infections play a critical role in regulating SAR11 populations, especially during phytoplankton spring blooms. The global prevalence, evident by our data from various oceans, highlights their significance in marine microbial ecology. The discovery of the globally occurring zombie cell phenomenon underscored the complexity of phage-host interactions. We provide possible explanations for the formation of zombie cells, which are phage-infected cells without detectable rRNA. We suggest a phage-induced recycling of ribosomal RNA, though this requires further exploration in future studies. As zombie cells are likely not restricted to SAR11 hosts, but widely distributed among other phage-host pairs, our discovery of zombies has implications beyond marine microbial ecology. This research not only sheds new light on the intricate dynamics of SAR11 and their viruses, as well as their turnover rates, but also opens new possibilities for exploring microbial and viral strategies in the ocean’s biogeochemical cycles.

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℃ without shaking and light. Exponentially growing HTCC1062 cultures were infected with HTVC023P, HTVC027P, and HTVC031P independently at a phage-bacteria ratio of approximately 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 hours after infection; approximately 2 hours before cell lysis; approximately 6 hours after cell lysis) and fixed and filtered as described above.

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 (Table S6). 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 Reintjes et al.⁴⁰. During the cruises, samples were collected from surface water and deep-chlorophyll maximum (DCM; Table S6). 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 (Table S6).

Pelagiphage FISH probe design and synthesis

We designed direct-geneFISH⁴¹ 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 nr database using the NCBI BLAST webservice (14 February 2023).

Probes (Table S7) were ordered as “oPools” from integrated DNA Technologies (IDT, Coraville, Iowa, USA) and resuspended in water as directed by the manufacturer. Probes were labelled with the ULYSIS Alexa 594 conjugation kit (Invitrogen, Waltham, Massachusetts, USA) with minor modifications as described in Zeugner et al.⁴³ and subsequently purified using Micro Bio-Spin chromatography columns P-30 (Bio-Rad, Hercules, California, USA). Labelling efficiencies were calculated as described by the manufacturer’s instructions for the ULYSIS kit, using a NanoDrop (Thermo Fisher Scientific, Waltham, Massachusetts, USA).

Fluorescence in situ hybridization

First, CARD-FISH targeting the 16S rRNA of SAR11 (“SAR11-mix”, Table S7) was conducted⁴⁴. Secondly, samples were hybridized with equimolar amounts of the probes targeting HTVC027P, HTVC031P, and Greip, using direct-geneFISH as described earlier^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-geneFISH signals). The microscope was equipped with a multi-Zeiss 62 HE filter cube (Beam splitter FT 395 + 495 + 610). Images were recorded with a custom-built macro^45,46 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 LSM 780 (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-geneFISH).

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 (Table S2). 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-geneFISH) 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 gtdbk-tk (version 1.3.0, 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 \(RPKM= \frac{Reads mapped to SAR11 MAG*{10}^{6}}{total read in a sample*length of MAG in kilobase pairs}\).

For quantifying the abundance of the 16S rRNA gene, we extracted the full-length 16S rRNA sequences from metagenome assemblies using Barrnap (v0.9; 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 the phages HTVC027P, HTVC031P, and Greip, mapping of metagenomic reads to the reference genomes were performed in a 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 \(\frac{Reads mapped to phage genome*{10}^{6}}{\sum read mapped to all SAR11 MAGs*length of phage in kilobase pairs}\).

Identification of defence 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 defence mechanisms. DefenceFinder⁵³ was used with the default database from October 22nd 2023.

Statistics and modelling

Statistical analyses and corresponding visualizations were done in R (v4.2.2; for used packages see supplementary material and methods)⁵⁴. 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 EUB338 I-III and compared to zombies in SAR11 (SAR11-mix, Table S7). 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.

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).
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).
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 8,000 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.

Acknowledgements

We thank Prof. Dr. Rudolf Amann for general support and critical feedback on different stages of the manuscript and Dr. Susanne Erdmann for general discussions. Germinate Science is acknowledged for language editing and Anja Greiser for help with FISH analysis. We would like to acknowledge the captains, crews, and scientific personnel on the R/V Polarstern cruises PS132 and PS133/1, as well as R/V Sonne cruise SO245. PS132 was financed by the grant AWI_PS132_01 and PS133 by grant AWI_PS133/1_06 by the Alfred Wegener Institute. Cruise SO245 was financed by grant 03G0245A of the Federal Ministry of Education and Research of Germany. Funding was provided by the German Research Foundation (DFG) project FOR 2406 ‘Proteogenomics of Marine Polysaccharide Utilization (POMPU)’ by grants to BMF (277249973) and by the Max Planck Society to JDB, LR, CS, LHO, BMF.

Author contributions

JDB conceptualized and designed study, generated and analysed data, interpreted results, created figures, wrote and revised manuscript; CS analysed data; YZ provided samples and interpreted results; AE analysed data; LR helped during sampling and generated data; LHO analysed data; BMF conceptualized study, interpreted results and revised manuscript. All authors reviewed the manuscript and provided feedback.

Competing interests

The authors declare no competing interests.

Data and materials availability

Automatically recorded microscopy images, as well as CLSM microscopy images, have been deposited at Edmond <https://doi.org/10.17617/3.3ZLOAT>. Data and R code to create figures and statistical analyses have been uploaded to GitLab: <https://gitlab.mpi-bremen.de/jbruewer/pelagiphage-abundance>. Metagenomes assessed in this study are publicly available from the European Nucleotide Archive (ENA) with the accession code PRJEB52999.

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Supplementary Figures 1-7 are not available with this version.

Fig. S1 Examples of high-throughput images to determine phage-infected SAR11 cells in control cultures. Ca. P. ubique HTCC1062 were infected with HTVC027P, HTVC031P, and HTVC023P. DNA was stained with DAPI, 16S ribosomal RNA with CARD-FISH (SAR11-mix), and phage genes were stained with direct-geneFISH (phage mix for HTVC027P, HTVC031P, and Greip). HTVC023P served as negative control. Images were cropped to a quarter of original size for visualization purposes and scale bars were inserted using Fiji/ImageJ.

Fig. S2 Microscopy-based vs. bioinformatic estimates of phage-infected cells during the 2020 spring phytoplankton bloom at Helgoland Roads. Upper panel: Abundance of phage-infected SAR11 cells per individual phage, based on microscopy estimates. Lower panel: Relative abundances of respective phages were normalized by the total number of reads mapped to all SAR11 MAGs in the same sample.

Fig. S3 Amount of zombie cells in all bacteria vs. SAR11. All bacteria were targeted with the EUB I-III FISH probe, while SAR11 was targeted with the SAR11-mix (Table S7).

Fig. S4 Distribution of SAR11, phage-infected SAR11, and zombie cells in the Southern Ocean. Complete results for Fig. 4.

Fig. S5 Statistical modelling applying Bayesian beta regression between SAR11 abundance, phage-infected SAR11 cells, and zombie cells. A relative abundance of phage-infected SAR11 cells and Zombie cells, B relative abundance of Zombie and SAR11 cells, and C phage-infected SAR11 cells and frequency of dividing cells (FDC), which is a proxy for cell division activity. Points represent raw data from different sampling campaigns. Line represent data modelled with Bayesian beta regression (back transformed from logit scale).

Fig. S6 Direct-geneFISH (“phage”) signal content from pure cultures. (A) SAR11 infected with HTVC027P. (B) SAR11 infected with HTVC031P. “Infected cells” corresponds to 16S FISH-positive and direct-geneFISH-positive cells, whereas “Zombie cells” do not contain a 16S FISH signal. Boxplots show median and upper and lower quartile. Whiskers show maximum data points within upper/lower quartile range plus 1.5 times the interquartile range. Outliers not shown.

Fig. S7 16S FISH fluorescence intensity of phage-infected SAR11 cells from infection experiments. Boxplots show median and upper and lower quartile. Whiskers show maximum data points within upper/lower quartile range plus 1.5 times the interquartile range. Outliers not shown. Violin plot show data distribution on y-Axis. Red-dashed line represents defined threshold from image analysis.

The authors declare no competing interests.

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Globally occurring pelagiphage infections create ribosome-deprived cells

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Abstract

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Main Text

Results

Quantifying phage-infected SAR11 cells and discovery of zombie cells

Phage-infection regulates SAR11 abundance during phytoplankton bloom

Global distribution of phage-infected and zombie cells

Discussion

Zombie cells: Clever persisters or ‘phage puppets’?

Conclusion

Material and Methods

Environmental sampling

Pelagiphage FISH probe design and synthesis

Microscopy

Image cytometry

Metagenomic abundance estimates for SAR11 MAGs, 16S rRNA gene, and Pelagiphages

Identification of defence systems within SAR11 genomes

Statistics and modelling

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Acknowledgements

Author contributions

Competing interests

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