The genus Micromonas comprises phytoplankton that show among the widest latitudinal distributions on Earth, and members of this genus are recurrently infected by prasinoviruses in contrasted thermal ecosystems. In this study, we assessed how temperature influences the interplay between the main genetic clades of this prominent microalga and their viruses. The growth of three Micromonas strains (Mic-A, Mic-B, Mic-C) and the stability of their respective lytic viruses (MicV-A, MicV-B, MicV-C) were measured over a thermal range of 4–32.5 °C. Similar growth temperature optima (Topt) were predicted for all three hosts but Mic-B exhibited a broader thermal tolerance than Mic-A and Mic-C, suggesting distinct thermoacclimation strategies. Similarly, the MicV-C virus displayed a remarkable thermal stability compared with MicV-A and MicV-B. Despite these divergences, infection dynamics showed that temperatures below Topt lengthened lytic cycle kinetics and reduced viral yield and, notably, that infection at temperatures above Topt did not usually result in cell lysis. Two mechanisms operated depending on the temperature and the biological system. Hosts either prevented the production of viral progeny or maintained their ability to produce virions with no apparent cell lysis, pointing to a possible switch in the viral life strategy. Hence, temperature changes critically affect the outcome of Micromonas infection and have implications for ocean biogeochemistry and evolution.


Viruses represent the most abundant biological entities known on Earth and they are likely to infect any form of life in the ocean (Suttle, 2005, 2007). Over the past decades, it has become evident that viruses play a pivotal role in marine ecosystems, especially through their profound influence on the structure and the functioning of microbial communities (see Brum and Sullivan, 2015 for a recent review). The ecological impact of viral infection is however largely determined by the different viral life strategies. Lytic viruses replicate and kill their host by cell lysis. This mode of infection influences ocean productivity and biogeochemistry by altering the dynamics, structure and the function of microbial assemblages (Fuhrman, 1999; Suttle, 2005) but also the recycling of organic matter through the viral shunt (Fuhrman, 1999; Wilhelm and Suttle, 1999; Brussaard et al., 2008). Lysogenic viruses affect the microbial evolution by inserting their own nucleic sequence into their host genome, which may provide the host with new functional traits and immunity against superinfection (Jiang and Paul, 1996; Wilson and Mann, 1997). The ecological incidence of chronic infections, by which viruses disseminate by budding or diffusion through host membranes, has been much less documented in marine ecosystems (Thomas et al., 2011, 2012). Despite the global impact of viral infection in the ocean, the regulation of infection dynamics and the relative share among the different infection strategies remain far from understood (Knowles et al., 2016).

Several field studies have evidenced latitudinal variations of virus-induced mortality in marine microbial assemblages. For example, increasing viral lysis rates of phytoplankton were recorded from high to low latitudes across the North Atlantic Ocean and, interestingly, correlated positively with temperature and salinity (Mojica et al., 2015). Consistent with this finding, high incidence of lysogeny and low viral lysis rates were shown to occur in low temperature ecosystems such as polar, mesopelagic and deep-sea waters or during cold periods in temperate systems (McDaniel et al., 2002; Williamson et al., 2002; Weinbauer et al., 2003; McDaniel et al., 2006; Evans et al., 2009). These studies suggest that viral life strategies other than lytic infection might prevail in cold environments or periods of low productivity. However, other field studies reported contradictory trends (Cochran and Paul, 1998; Weinbauer and Suttle, 1999) and it is still unclear whether temperature-driven shifts in viral infection dynamics and strategy represent a global pattern or arise from local processes.

Laboratory studies on virus–host model systems in controlled conditions have proven essential to address such fundamental question. These approaches have shown that temperature may influence the infection process by regulating viral abundance and infectivity. Most marine virus isolates tolerate low temperatures whereas increasing temperatures tend to induce loss in infectivity and ultimately inactivation of the viral particles (Nagasaki and Yamaguchi, 1998; Baudoux and Brussaard, 2005; Tomaru et al., 2005; Martínez-Martínez et al., 2015). Nevertheless, as viruses generally exhibit a broader thermotolerance than their hosts (Mojica and Brussaard, 2014), and because the optimal temperature for lytic replication (i.e. the temperature that generates fast host lysis and/or high viral yield) generally matches the host optimal growth temperature, it is usually assumed that the impact of temperature on viral infection mostly arises from changes in host metabolism. Temperature-driven changes in host physiology were indeed shown to alter the kinetics of viral lysis, possibly inducing the development of viral resistance (Nagasaki and Yamaguchi, 1998; Kendrick et al., 2014; Tomaru et al., 2014) or switches from a lysogenic to lytic lifestyle (Wilson et al., 2001). Altogether, these studies point to important regulatory roles of temperature for viral infection. However, extrapolating results from culture studies to natural ecosystems remains risky given the paucity and the representativeness of the studied virus–host systems.

The cosmopolitan picophytoplankter Micromonas (Mamiellophyceae, Mamiellales) usually dominates the coastal eukaryotic phytoplankton communities from polar to tropical waters (Thomsen and Buck, 1998; Not et al., 2004; Foulon et al., 2008; Balzano et al., 2012; Monier et al., 2015). Members of this prominent genus are distributed in three discrete genetic clades (Guillou et al., 2004; Foulon et al., 2008) that are all susceptible to viral infection (Baudoux et al., 2015; Martínez-Martínez et al., 2015). Previous studies demonstrated that Micromonas viruses (MicVs) are ubiquitous, highly dynamic and induce substantial mortality through cell lysis events in natural and cultured populations (Cottrell and Suttle, 1991, 1995; Sahlsten, 1998; Zingone et al., 1999; Evans et al., 2003; Baudoux et al., 2015). The majority of known MicVs are lytic dsDNA viruses affiliated to the Phycodnaviridae family and the genus Prasinovirus (Mayer and Taylor, 1979; Cottrell and Suttle, 1991; Zingone et al., 2006; Martínez-Martínez et al., 2015), which may represent the most abundant viruses of eukaryotic marine plankton (Hingamp et al., 2013; Yau et al., 2015). Micromonas is among the phytoplankters that shows the widest latitudinal distribution on Earth and thereby inhabits waters with contrasted temperatures. Hence, Micromonas–virus system constitutes a particularly relevant biological model to investigate how temperature impacts host–virus interactions. To address this problem, we examined the thermal responses of three Micromonas strains that belong to the three main clades and three genetically distinct viruses and monitored the dynamics of the viral infection across a large thermal gradient.

Materials and methods

Algal and virus culture conditions

Micromonas sp. strains RCC451, RCC829 and RCC834 (hereafter referred to as Mic-A, Mic-B and Mic-C; Table 1) that belong to the phylogenetic clades A, B and C, respectively, were retrieved from the Roscoff Culture Collection (http://roscoff-culture-collection.org/). Algal cultures were grown in batch conditions in ventilated polystyrene flasks (Nalgene, Rochester, NY, USA) in K-Si medium (Keller et al., 1987). Cultures were maintained under 100 μmol photons m−2 s−1 of white light provided by fluorescent tubes (Mazda 18WJr/865) using a 12:12 light:dark cycle in temperature-controlled chambers at 4, 7.5, 9.5, 12.5, 20, 25, 27.5, 30 and 32.5 °C (Aqualytic, Dortmund, Germany). Cultures were thermo-acclimated for several months by multiple serial transfers of early exponentially growing cells.

Table 1: Micromonas and virus strains used in this study

Viral strains RCC4253, RCC4265 and RCC4229 (hereafter referred to as MicV-A, MicV-B and MicV-C) that are lytic to Micromonas Mic-A, Mic-B and Mic-C, respectively, were chosen based on the characterization conducted in Baudoux et al. (2015) (Table 1). Viral lysates were produced by infecting host cultures grown at 20 °C. The model system Mic-B/MicV-B was explored in detail because of its large thermal range.

Flow cytometry

All flow cytometric analyses were carried out using a flow cytometer FACS Canto II (Becton Dickinson, San Jose, CA, USA) equipped with an air-cooled argon laser at 488 nm. Green fluorescence intensity (530 nm emission), red fluorescence intensity (emission >660nm), side scatter and forward scatter were normalized with standard 0.95 μm fluorescent beads (YG, Polysciences, Warrington, PA, USA).

Micromonas cell abundances (Figure 1a) were determined using the side scatter and the red fluorescence signals. The samples were analysed for 1 min at the appropriate flow speed according to culture concentration in order to avoid coincidence events (Marie et al., 1999). The growth rates of Micromonas Mic-A, Mic-B and Mic-C acclimated from 4 to 30 °C were computed as the slope of ln(Nt) vs time plot, where Nt is the cell number at time t. All measurements were done on at least four replicates.

Figure 1
Figure 1

Flow cytograms representing (a) Micromonas cells discriminated using the red fluorescence and the side scatter channels for total cell enumeration, (b) Micromonas membrane integrity upon SYTOX-Green staining which discriminates dead cells and live cells based on the green fluorescence channel. (c) MicV particles discriminated by their green fluorescence and side scatter channels upon staining with the nucleic acid dye SYBR-Green.

In addition, cell membrane permeability, used as a proxy for viability, was monitored by flow cytometry using SYTOX-Green. This dye is a membrane-permeant nucleic acid probe (Life Technologies, Saint-Aubin, France) that only binds to nucleic acids of cells that have comprised membranes. SYTOX-Green (0.5 μm final concentration) was added to fresh sample, and the mixture was incubated for 5 min in the dark at the corresponding growth temperature (Peperzak and Brussaard, 2011). Cells with compromised membranes were discriminated based on their higher green fluorescence (Figure 1b).

Viral abundances were determined on glutaraldehyde-fixed samples (0.5% final concentration, Grade II; Sigma Aldrich, St Louis, MO, USA) stored at −80 °C until analysis. Flow cytometry analysis was performed as described by Brussaard (2004). Briefly, samples were thawed at 37 °C, diluted in 0.2 μm filtered autoclaved TE buffer (10:1 Tris-EDTA, pH=8) and stained with SYBR-Green I (concentration; Life Technologies, Saint-Aubin, France) for 10 min at 80 °C. Virus particles were discriminated based on their green fluorescence and side scatter during 1 min analyses (Figure 1c). All cytogram analyses were performed with the Flowing Software freeware (Turku Center of Biotechnology, Turku, Finland).

Micromonas growth rate modelling

A Cardinal Temperature Model with Infection relying on experimental growth rates was used to calculate the optimal growth temperature (Topt), for which growth rate is optimal (μopt), and the minimal and maximal growth temperatures (Tmin and Tmax) beyond which growth rate is assumed to be zero (Bernard and Rémond, 2012). The determination of these parameters was essential to select the appropriate temperature for infection experiments. Cardinal temperatures (Tmin, Topt and Tmax) of Micromonas and thermal growth response were predicted using the relation:


The same algorithm was used in Bernard and Rémond (2012) to identify model parameters and the confidence intervals were determined with a jackknife method with a 95% threshold.

Pulse amplitude modulated fluorimetry

The quantum yield of photosystem II of algal cells was determined using a pulse amplitude modulated fluorometer (Phyto-PAM, Walz) connected to a chart recorder (Labpro; Vernier) in order to monitor the impact of temperature and viral infection on host photophysiology. After 5 min relaxation in darkness, the non-actinic modulated light (450 nm) was turned on in order to measure the fluorescence basal level, F0. A saturating red light pulse (655 nm, 4000 μmol quanta m−2 s−1, 400 ms) was applied to determine the maximum fluorescence level in the dark-adapted sample, FM. The maximal photosystem II fluorescence quantum yield of photochemical energy conversion, FV/FM, was calculated using the following formula:

Measuring the effect of temperature on virion infectivity and abundance

Freshly produced 0.2 μm filtered (polyethersulfone membrane) viral lysates of MicV-A, MicV-B and MicV-C were diluted in K-Si culture medium to a final concentration of 106 viral particles ml1. Aliquots of these viral suspensions were incubated in darkness at 4, 7.5, 12.5, 20, 25, 27.5, 30 °C, which corresponds to the global temperature range encountered in the ocean. Samples for total virus abundance and infectivity were taken once a week and once every 2 weeks, respectively, during 6 weeks. Viral abundance was monitored by flow cytometry as described above. Viral infectivity was assessed using end point dilution method (Most Probable Number (MPN) method; Taylor, 1962). To this end, virus suspensions were serially diluted (10-fold increments) in exponentially growing Micromonas cultures in 48-multiwell plates and incubated at 20 °C for 10 days. Each serial dilution was done in triplicate along with a control, non-infected Micromonas culture. After incubation, the cultures that underwent lysis, as seen by the colour change, were counted and the infectious virus concentration was determined with the software Most Probable Number (MPN; version 2.0; Avineon, U.S Environmental Protection Agency).

Particle degradation and decrease in infectivity rates (respectively dS and di) were calculated from viral counts and viral infectivity measurements as follows:

where Vt+1 and Vt are the concentration of viral particles at time t+1 and t, respectively, and

where It+1 and It are the concentrations of infectious viral particles at time t+1 and t, respectively.

Measuring the effect of temperature on the Micromonas–virus interactions

The effects of temperature on virus–host interactions were assessed by infection dynamics experiments. For the model system Mic-B/MicV-B, host cultures acclimated at 9.5, 12.5, 20, 25, 27.5 and 30 °C were prepared at a concentration of 5 × 105 cell ml−1 and split into four subcultures. Three of the subcultures were infected with a fresh, 0.2 -μm-filtered virus lysate of MicV-B at a multiplicity of infection of 10. The fourth culture, uninfected, served as control. Control and infected cultures, incubated at each temperature, were sampled every 3–4 h during 120 h for measurements of host and viral abundances, host cell membrane integrity and photosynthetic capacity (see above).

Three viral parameters, the latent period, the viral production and, when applicable, the burst size, were calculated from viral growth cycle. The latent period was calculated as the lapse-time between inoculation of viruses in host culture and the release of viral particles by host cells. A viral production rate was calculated as the slope of the logarithm curve of viral concentration over time following the equation:

with Vt+1 the viral concentration at time t+1 and Vt the viral concentration at time t for the period .

If complete host lysis occurred, the burst size (BS) was calculated as the number of viral particles produced per infected host cell as

where V0 is the viral concentration and To, Vmax the maximum concentrations of viral particles during the experiment, and Hmax and Hmin the maximal and minimal host abundances during the experiment.

For the model systems Mic-A/MicV-A and Mic-C/MicV-C, a simplified experimental setup and sampling strategy were used. Infection cycles were monitored at only five temperatures: 12.5, 20, 25, 27.5 and 30 °C. Infections at 12.5, 20, 27.5 and 30 °C were sampled every 10–14 h during 120 h for host and virus abundance and photosynthetic capacity measurements. Infections at 25 °C were sampled for host and virus abundance every 3–4 h during 28 h and every 12 h for the remaining 96 h.


Effect of temperature on Micromonas growth

The growth rate of Micromonas sp. strains Mic-A, Mic-B and Mic-C was measured at temperatures ranging from 4 to 32.5 °C (Figure 2; Table 2). The growth responses to temperature followed a typical, asymmetric bell-shaped curve over the selected temperature range with an asymptotic increase at temperatures below Topt and an abrupt decline at temperatures beyond Topt. Cardinal Temperature Model with Infection model fitting resulted in the determination of optimum growth temperature (Topt) values of 25.1, 26.7 and 24.3 °C for Mic-A, Mic-B and Mic-C, respectively. Mic-A and Mic-C showed a similar optimal growth rate (μopt=0.8 day−1), while Mic-B (μopt=1.1 day−1) was higher. Micromonas strain Mic-B exhibited the largest thermal range with a theoretical Tmin of 0.55 °C and Tmax of 32.5 °C. Mic-A and Mic-C appeared slightly more restrictive with a positive growth between 9.6 and 32.5 °C and 5.7–30.1 °C, respectively. Based on these thermal responses, we investigated the stability of the virus particles and the potential changes in the virus–host interactions below or at Topt (7.5 or 9.5, 12.5, 20  and 25 °C) and beyond Topt (27.5 and 30 °C).

Figure 2
Figure 2

Growth response to temperature of Micromonas sp. strains Mic-A (red), Mic-B (green) and Mic-C (blue). Closed circles represent experimental data and solid lines indicate the fit of the Cardinal Temperature Model with Infection model from Bernard and Rémond (2012). Error bars represent the standard deviation of the data (at 95%, at least n=3).

Table 2: Cardinal temperatures (°C), optimal growth rates (day−1) and their respective confidence intervals (CIlow and CIup) for the three Micromonas strains

Thermal stability of Micromonas virions

The thermal stability of the viral particles MicV-A, MicV-B and MicV-C was investigated over a 6–week period, during which viral infectivity and particle integrity were monitored. Rates of decay for these two parameters varied considerably among the three viral strains (Figure 3). MicV-C was the most stable over the range of selected temperature. MicV-C infectivity and particle integrity both declined at similar rates between 7.5 °C (0.08±0.05 day−1) and 27.5 °C (0.1±0.02 day−1), while infectivity decay rates increased considerably only at 30 °C (0.35±0.02 day−1). The infectivity decay rates were globally higher for MicV-A and MicV-B virions, increasing gradually (from 0.17±0.025 to 0.44±0.01 day−1) with increasing temperature. In spite of these considerable losses in infectivity, total counts of viral particles decreased at much lower rates, suggesting that MicV-A and MicV-B had lost the ability to infect their hosts prior to particle destruction.

Figure 3
Figure 3

Decay rates of viral particles (dashed line) and viral infectivity (solid line) for MicV-A (a), MicV-B (b) and MicV-C (c) exposed to a large range in temperatures over a 6–week incubation period. Error bars represent the confidence intervals (at 95%, n=3).

Impact of temperature on virus–host interactions

Infection dynamics experiments revealed that virus–host interactions were strongly affected by temperature, but each virus–host systems displayed distinct responses (Figures 4 and 6).

Figure 4
Figure 4

Viral infection of Micromonas Mic-B by MicV-B at 9.5, 12.5, 20, 25, 27.5 and 30 °C. Dynamics of viral abundance (panels af, data in grey triangles and mean of two replicates in black lines), Micromonas abundance (panels gl) in control (dashed lines and white circles) and infected (solid lines and black circles) cultures, % cells with intact membranes (viable cells, panels mr) in control (dashed lines and white circles) and infected (solid lines and black circles) cultures, and photosynthetic capacity (panels sx) of control (dashed lines and white circles) and infected (solid lines and black circles) cultures are shown. Blues bars represent the light phases. Error bars were computed from triplicate samples for the host parameters. Virus particles were enumerated from duplicate samples, so no error bar is shown.


Both infection kinetics and the fate of the infected Micromonas cells differed between temperature treatments. Below Mic-B Topt (25, 20, 12.5 and 9.5 °C), MicV-B propagated through a typical lytic cycle (Figure 4). The virus latent period increased progressively with decreasing temperature ranging from <3 h at 25 °C to the 7–11 h at 12.5 and 9.5 °C (Figures 4a–d). Similarly, the rates of virus production were substantially faster at 25 and 20 °C (5.76 and 5.52 day−1; Figures 4c and d) compared with that at 9.5 and 12.5 °C (0.48 and 0.96 virus produced day−1, respectively, Figures 4a and b). The virus production at 25 and 20 °C induced host cell lysis, which was accompanied by a disruption of host membranes (Figures 4o and p and Supplementary Figure S1) and a decrease in photosynthetic capacity (Figures 4u and v). The resulting burst size (139 to 142 virions host−1) was comparable for both temperature treatments. At 12.5  and 9.5 °C, the host cell lysis was delayed considerably. At these temperatures, control and infected cultures displayed similar growth rates (Figures 4g and h) and neither the host membrane integrity (Figures 4m and n) nor the photosynthetic capacity (Figures 4s and t) appeared to be altered by the virus production until 70 h post infection. The loss in host abundance recorded 70 h post infection (Figures 4g and h) led to estimate a burst size of 84 virions host−1 at 12.5 °C. At 9.5 °C, the infected host abundance did not decline during the 120 h sampling, precluding calculation of the burst size. Lysis of infected host was nevertheless confirmed by a visual control (the infected culture became transparent) at 140 h post infection.

At temperatures above Topt (27.5 and 30 °C), complete host cell lysis was not observed and viral infections appeared to follow a two-step process. At 27.5 °C, virus infection led to a rapid release of viral progeny (latent period <3 h) at a substantial production rate (6.24 day−1) until a plateau in virus concentration was reached after 20 h (Figure 4e). A second increase in viral abundance with a production rate of 0.48 day−1 was recorded after 70 h, which was maintained until the end of the experiment. Interestingly, viral infection at 27.5 °C did not result in complete collapse of the host culture (Figure 4k and Supplementary Figure S1). A slight decline in infected host cell abundance (Figure 4k), membrane integrity (from 100% to 90%; Figure 4q) and FV/FM (from 0.55 to 0.45; Figure 4w) accompanied the first viral burst (BS of 177 virions host−1). However, the second production of viruses did not induce cell lysis. Indeed, infected host cells grew at slower rates than control cultures (0.62 day−1 compared with 1.11 day−1; Figure 4k), yet they exhibited unaltered membrane integrity (Figure 4q) and FV/FM (Figure 4w) compared with the control. The estimation of the viral BS was not possible in the absence of a host cell lysis; instead we calculated a viral release of 5 virions cell−1 day−1.

Last, virus infection at 30 °C resulted in a reduced production rate of viral progeny (3.6 day−1) after a latent period of 3–7 h and a gradual decay in viral abundance from 35 h until the end of the experiment (Figure 4f). As observed at 27.5 °C, the viral production was accompanied by an incomplete host cell lysis (Figure 4l and Supplementary Figure S1). The production of viral progeny and subsequent cell lysis induced slight declines in infected host cell abundance, membrane integrity (from 100% to 90%; Figure 4r) and FV/FM (from 0.55 to 0.45; Figure 4x). The resulting viral BS reached 49 virions host−1. Yet, we observed a regrowth of infected host at a rate of 0.81 day−1 (compared with 0.69 day−1 for the control) after 80 h (Figure 4l) and restoration of membrane integrity and photosynthetic capacity after 27 h until the end of the experiment (Figures 4r and x).

Altogether, these results indicate that rates of viral production were positively related to host growth rate whereas viral latent period was inversely related to the host growth rates (Figure 5). Optimal viral replication (shortest latent period and fastest viral production) occurred at a temperature between 25 and 27.5 °C, which correspond to the optimal growth of Micromonas Mic-B.

Figure 5
Figure 5

Relationship between viral latent period (dashed line and white circle), viral production (solid line and black circle) and host growth rate for the system Mic-B/MicV-B. Linear regressions were statistically robust with an adjusted R2 >0.85 and a P-value <0.05.

Mic-A/MicV-A and Mic-C/MicV-C

As observed for MicV-B, MicV-A and MicV-C replicated through a typical lytic cycle only below host Topt (20 and 12.5 °C; Figure 6). At 20 °C, viruses were released after latent periods lower than 14 h  and 14–24 h for MicV-A and MicV-C, respectively, with virion production rates of 2.64 day−1 and 1.44 day−1, respectively. The strong decrease in cell abundance in the infected cultures indicates that viral production induced complete collapse of the corresponding host culture (Figure 6g and Supplementary Figure S2). The resulting BS reached values of 130–158 virions host−1 and 177–197 virions host−1 for MicV-A and MicV-C, respectively (Figure 6b). At 12.5 °C, MicV-A and MicV-C readily propagated in their respective host; yet the duration of virus latent periods were prolonged (19–29 h) compared with the 20 °C treatment with virion production rates of 1.2 and 0.96 day−1, respectively (Figure 6a). The release of viral progeny was accompanied by immediate host lysis and the resulting burst size was reduced for MicV-A and MicV-C (57–69 and 80–96 virions host−1, respectively) compared with infection at 20 °C (Figure 6f and Supplementary Figure S2).

Figure 6
Figure 6

Viral infection of Micromonas Mic-A by MicV-A (black symbols and lines) and Micromonas Mic-C by MicV-C (grey symbols and lines) at 12.5, 20, 27.5 and 30 °C. Dynamics of virus abundance (ae) for MicV-A (black triangles) and MicV-C (grey triangles) are shown in the upper panels. Dynamics of Micromonas abundance (fj) for Mic-A in control (black open circles and dashed lines) and infected cultures (black circles and solid lines) and Mic-C in control (grey open circles and dashed lines) and infected cultures (grey circles and solid lines) are shown in the bottom panels.

At temperatures close to Topt (25 °C), infection by MicV-A and MicV-C did not result in cell lysis while viruses were still produced (Figures 6c and h and Supplementary Figure S2). The duration of the virus latent periods was similar (7–11 and 27–31 h) compared with the 20 °C treatment with virion production rates of 0.48 and 0.84 day−1, respectively. The resulting growth rate of infected Mic-A cells was not different to the control (0.8 day−1) whereas infected Mic-C grew at a lower rate than the control (0.36 vs 1.02 day−1).

At temperatures beyond host Topt (27.5 and 30 °C), infection by MicV-A and MicV-C did not result in any production of viruses. Infected Micromonas cells were apparently not altered by the presence of viruses, growing at rates similar to control cultures (Figures 6d, e, i and j) with unaffected photosynthetic yields (data not shown).


The response of Micromonas strains to temperature is typical for a eurythermal mesophilic species, characterized by a wide range of thermal tolerance with an optimal growth temperature (Topt) between 20 and 25 °C. Deviation from the optimal growth temperature is thought to induce modifications of intrinsic biochemical and physiological functions in order to optimize resource allocation for growth on the one hand, and to maintain cell integrity on the other hand (Behrenfeld et al., 2008; Ras et al., 2013). As a result, Micromonas growth response below Topt reflects cold acclimation whereas the abrupt decline of growth rates beyond Topt suggests dramatic deleterious effects of heat on cellular components (Raven and Geider, 1988; Dill et al., 2011; Ras et al., 2013). Although the three Micromonas strains exhibited broad temperature tolerances, the strain belonging to clade B (Mic-B) showed the largest thermal tolerance range (from 0.55 to 32.5 °C) while strains belonging to clades A and C were more restrictive with thermal tolerance ranging from 9.6 to 32.5 °C and from 5.7 to 30.1 °C, respectively. Whether these differences are generally the case for all of the members of these clades remains to be investigated. To the best of our knowledge, no study has explored the existence of thermotypes in Micromonas species. Nonetheless, our results suggest that the selected Micromonas strains might have evolved divergent acclimation strategies, which may, in turn, influence virus–host interactions.

The detailed study of the model system Mic-B/MicV-B unequivocally demonstrated that viral infection is altered by temperature. At temperatures lower than Topt, MicV-B propagated and killed their hosts through cell lysis as classically reported in the literature (Mayer and Taylor, 1979; Zingone et al., 2006; Baudoux et al., 2015; Martínez-Martínez et al., 2015). Yet the kinetics and the intensity of viral replication slowed down with decreasing temperatures. MicV-B propagated the most efficiently at 25 °C, which corresponded to a temperature close to the optimal growth temperature of Micromonas sp. Mic-B. Under these growth conditions, MicV-B readily adsorbed on host membranes and rapidly hijacked host cellular machinery for viral DNA replication as well as virion protein synthesis and assembly, as indicated by the short latent period (<3 h), the high burst size (140 virions per infected cell) and the fast viral production rate (5.5 day−1). The observed viral parameters fall within the range of reported values for other Micromonas viral isolates (Mayer and Taylor, 1979; Baudoux and Brussaard, 2008; Baudoux et al., 2015). Decrease in temperature led to increased latent periods and the coldest temperatures (12.5 and 9.5 °C) also induced a reduction of viral production rates and a substantial delay in host cell lysis. The relatively low viral decay rates recorded across this thermal range indicated that MicV-B particles did remain infectious under these conditions. It is thus likely that the acclimation strategy evolved by Mic-B to grow at temperatures below Topt was responsible for the alteration of the viral infection process. The decrease in auto-fluorescence intensity of cold-adapted Micromonas (Supplementary Figure S3) suggests a reduction in chlorophyll content with decreasing temperatures as previously reported (Claquin et al., 2008). Several studies pointed out the similarity of photoacclimation trends at low temperatures to those at high irradiance (Anning et al., 2001; El-Sabaawi and Harrison, 2006; Claquin et al., 2008). Reports on the effect of light intensity evidenced the importance of this factor in regulating algal host–virus interactions (Waters and Chan, 1982; Bratbak et al., 1998; Brown et al., 2007; Baudoux and Brussaard, 2008). However, elevated irradiance per se did not appear to alter viral infection of Micromonas (Baudoux and Brussaard, 2008). Several other reasons might explain changes in viral infection of Mic-B at low temperatures. For example, low temperatures were shown to slow down the rates of translation initiation at the ribosome site in phytoplankton (Toseland et al., 2013). The globally reduced metabolic activities and protein biosynthesis may thus result in a slower synthesis and assembly of virions proteins, which, in turn, could explain the decrease in viral progeny production. Another known impact of low temperatures is the stiffening of phytoplankton membranes through the activation of lipid desaturases (Los and Murata, 2004; D’Amico et al., 2006). Interestingly, the monitoring of Micromonas membrane integrity indicated a modification of their membrane properties. While cell division enhanced membrane permeability at 25 and 20 °C, host membranes remained impermeable to the dye throughout their cell cycle at the coldest temperatures (9.5 and 12 °C), supporting the idea that Mic-B membranes became more rigid. Such modification might not only impact viral adsorption on host cell, which would result in a prolonged latent period, but it may also delay the release of viral progeny and, thereby, the timing of host lysis.

Notably, temperatures above Topt altered the algicidal activity of Micromonas viruses considerably. A 1 °C temperature increase beyond Topt induced host tolerance to viral infection. At 27.5 °C, we indeed observed a rapid transition from a classical lytic infection mode to a viral life strategy reminiscent of chronic infection, by which viruses are released with no apparent sign of host lysis. This infection mode has never been reported in MicV. Yet, one of the few examples of chronic infection in marine systems has interestingly been described for another prasinovirus that infects the green alga Ostreococcus tauri, a close relative of Micromonas sp. (Thomas et al., 2011). Ostreococcus virus OtV-5 switched from a lytic to a chronic lifestyle within a few days of incubation, after lysis of most of the host cells remaining host cells were resistant but produced viruses chronically. The viral yield of chronically infected cells is within the same range for both model systems with 1–3 and 5 viruses host−1 day−1 in Ostreococcus and Micromonas, respectively. Yet, the growth rate of chronically infected Micromonas cells was considerably reduced while no reduction in growth rate was evidenced in Ostreococcus species (Thomas et al., 2011). As argued for lysogeny, chronic infection ensures a coexistence between host and virus in unfavourable conditions (e.g. low host density, suboptimal growth environments, Mackinder et al., 2009; Thomas et al., 2012). Being in the vicinity of their host may directly benefit the virus if growth conditions improved. The mechanisms that trigger a lytic–chronic decision remain to be established. Our results however suggest that this switch in life strategy did not operate when temperatures deviated excessively from the growth optimum. At 30 °C, MicV-B rapidly replicated through cell lysis and regrowth of infected Micromonas cells was recorded following this lytic event as observed at 27.5 °C. A number of interpretations could explain the findings of low viral production and continued host growth at 30 °C. The observed loss of viral infectivity at this temperature suggests that viruses could become inactive during the period of the experiment. However, we cannot rule out that alterations of host phenotype modify their susceptibility to viral infection as demonstrated recently in Kendrick et al. (2014). Hence, temperatures above Topt induced complex outcomes after viral infection in Mic-B. Importantly, chronic infections might arise more frequently than previously thought, at least among marine prasinophytes.

The investigation of two additional Micromonas–virus systems suggests that the previously observed temperature effects on the viral infection process are not specific to the model system Mic-B/MicV-B. Despite the variable thermal tolerance of the studied Micromonas hosts and their respective viruses, temperature affected the outcome of viral infections similarly. Infection dynamics experiments demonstrated that temperatures below Topt slowed down the kinetics and intensity of the lytic cycle while temperatures close to and higher than Topt induced complex outcomes in viral infections. Infections at 25 °C might correspond to temperature slightly above Topt as the averaged predicted Topt were 25.1 °C (24.5–25.8) and 24.3 °C (23.4–25.2) for Mic-A and Mic-C, respectively. As observed previously, a slight increase beyond Topt induced a viral life strategy reminiscent of chronic infection while excessive deviation from Topt inhibited viral production, although hosts maintained their ability to grow. Hence, the thermal environment of Micromonas determines the outcome of viral infection, leading to drastic changes in the lytic cycle and a possible switch in viral life strategy. Similar thermal responses to viral infection were reported for the raphidophyte Heterosigma akashiwo (Nagasaki and Yamaguchi, 1998) and the haptophyte Emiliania huxleyi (Kendrick et al., 2014). An alteration of the algicidal activity of viruses at high temperatures and a reduced intensity of viral lysis at low temperatures seem to represent a global pattern, which may have important consequences for the regulation of phytoplankton population in the ocean.

Because of their worldwide distribution and persistence in marine systems, Micromonas and their viruses are exposed to important changes in environmental parameters, including temperature. Results of this study clearly demonstrated that a 1 °C change can profoundly affect the outcome of viral infection and can even lead to development of complex outcomes of viral lysis. It is thus very likely that temperature contributes to the control of viral induced mortality in Micromonas populations both at a temporal and a geographical scale. There is, to our knowledge, no report of actual viral lysis rates in Micromonas natural populations to support our speculation. Nonetheless, a recent study observed a latitudinal variation in virus–mediated mortality of phytoplankton across the North Atlantic Ocean and pointed out a correlation between the velocity of viral lysis and in situ temperature that varied between 10 and 25 °C (Mojica et al., 2015). Such geographic partitioning of viral lysis processes could have important consequences for the ecology and the biogeochemistry of the global ocean. Viral lysis diverts phytoplankton biomass away from the higher trophic level towards the microbial loop through the release of cellular compounds upon host cell lysis. Temperature-driven changes in the amount of viral-mediated mortality and in host cell stoichiometry (due to changes in biochemical functions) could thereby alter the structure of marine food webs and the capacity of pelagic systems to sequester carbon. Given the anticipated increase of sea surface temperature due to global warming, it is essential to gain a better understanding of the thermal response and life strategy in other prominent virus–phytoplankton model systems. Such studies are necessary for improving ecosystem models in ecosystem-based considerations of climate change.


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We are grateful to the MICROBIOL Master students 2015–2016 for repeating infection dynamics experiments and to Nigel Grimsley, Hervé Moreau and Evelyne Derelle for stimulating discussions. We thank the three anonymous reviewers for their constructive comments on a previous version of this manuscript. This research was funded by the ANR funding agency REVIREC; grant no. 12-BSV7-0006-01.

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  1. Sorbonne Universités, UPMC Univ Paris 06, CNRS, Villefranche/mer, France

    • David Demory
    • , Antoine Sciandra
    •  & Sophie Rabouille
  2. BIOCORE-INRIA, BP93, Sophia-Antipolis Cedex, France

    • David Demory
    •  & Olivier Bernard
  3. Sorbonne Universités, UPMC Univ Pierre et Marie Curie (Paris 06), CNRS, Adaptation et Diversité en Milieu Marin UMR7144, Station Biologique de Roscoff, Roscoff, France

    • Laure Arsenieff
    • , Nathalie Simon
    • , Christophe Six
    • , Dominique Marie
    • , Pei Ge
    • , Estelle Bigeard
    •  & Anne-Claire Baudoux
  4. Sorbonne Universités, UPMC Univ Pierre et Marie Curie (Paris 06), CNRS, Fédération de Recherche FR2424, Station Biologique de Roscoff, Roscoff, France

    • Fabienne Rigaut-Jalabert
  5. INRA, UMR CARRTEL, Thonon-les-Bains Cedex, France

    • Stéphan Jacquet


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