Laura Alonso-Sáez

Antonio S Palacio

Ana M Cabello

Semidán Robaina- Estévez

Jose M González

Laurence Garczarek

Angel López-Urrutia

Transcriptional mechanisms of thermal acclimation in Prochlorococcus

Low temperature limits the growth and the distribution of the key oceanic primary producer Prochlorococcus, which does not proliferate above ca. 40 degrees latitude. Yet, the molecular basis of thermal acclimation in this cyanobacterium remains unexplored.

We analyzed the transcriptional response of the strain Prochlorococcus marinus MIT9301 in long-term acclimations and in natural Prochlorococcus populations along a temperature range enabling its growth (17 to 30ºC). MIT9301 upregulated mechanisms of the global stress response at the temperature minimum (17ºC) but maintained the expression levels of genes involved in essential metabolic pathways (e.g., ATP synthesis, carbon fixation) along the whole thermal niche. Notably, their declining growth from the optimum to the minimum temperature was coincident with a transcriptional suppression of their photosynthetic apparatus and a dampening of its circadian expression patterns, indicating a loss in their regulatory capacity under cold conditions. Under warm conditions, the cellular transcript inventory of MIT9301 was strongly streamlined, which may also induce regulatory imbalances due to stochasticity in gene expression. The daytime transcriptional suppression of photosynthetic genes at low temperature was also observed in MIT9301-like populations across the global ocean, implying that this molecular mechanism may be associated with the restricted distribution of Prochlorococcus to temperate zones.

Importance

Prochlorococcus is a major marine primary producer with a global impact on atmospheric CO2 fixation. This cyanobacterium is widely distributed across the temperate ocean, but virtually absent at latitudes above 40º for yet unknown reasons. Temperature has been suggested as a major limiting factor, but the exact mechanisms behind Prochlorococcus thermal growth restriction remain unexplored. This study brings us closer to understanding how Prochlorococcus functions under temperature challenging conditions, by focusing on its transcriptional response after long-term acclimation from its optimum to its thermal thresholds. Our results indicate a detrimental role of oxidative stress on Prochlorococcus fitness under cold conditions, as the drop in its growth rate was paralleled by a transcriptional suppression of the photosynthetic machinery during daytime, likely to mitigate the generation of ROS. Notably, warm temperature induced a marked shrinkage of its cellular transcript inventory, which may induce regulatory imbalances in the future functioning of this cyanobacterium.

Introduction

Prochlorococcus is the most abundant photosynthetic organism on Earth [START_REF] Partensky | Prochlorococcus, a Marine Photosynthetic Prokaryote of Global Significance[END_REF], and a major contributor to the oceanic primary production [START_REF] Li | Primary production of prochlorophytes, cyanobacteria, and eucaryotic ultraphytoplankton: Measurements from flow cytometric sorting[END_REF]. Despite sustaining vast populations at the global scale, Prochlorococcus exhibits an enigmatic distribution in the ocean, with a sharp latitudinal barrier at ca. 45°N and 40°S [START_REF] Johnson | Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental gradients[END_REF][START_REF] Flombaum | Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus[END_REF]. While the ultimate reasons for such restricted distribution are still unknown and may involve biotic interactions [START_REF] Follett | Trophic interactions with heterotrophic bacteria limit the range of Prochlorococcus[END_REF], temperatures in the range of 12º-15ºC typically limit the growth of Prochlorococcus in culture [START_REF] Johnson | Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental gradients[END_REF][START_REF] Zinser | Influence of light and temperature on Prochlorococcus ecotype distributions in the Atlantic Ocean[END_REF][START_REF] Moore | Comparative physiology of Synechococcus and Prochlorococcus: Influence of light and temperature on growth, pigments, fluorescence and absorptive properties[END_REF] and in situ [START_REF] Johnson | Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental gradients[END_REF], potentially representing critical thresholds for their metabolism.

Due to genome streamlining, Prochlorococcus is assumed to have a lower regulatory capacity than other phytoplankton groups, and a limited metabolic flexibility to adapt to environmental disturbance, including temperature changes [START_REF] Scanlan | Ecological Genomics of Marine Picocyanobacteria[END_REF][START_REF] Partensky | Prochlorococcus: Advantages and limits of minimalism[END_REF][START_REF] Mary | Two-component systems in Prochlorococcus MED4: Genomic analysis and differential expression under stress[END_REF]. However, a mechanistic understanding of their temperature sensitivity at the molecular level is still lacking.

In general, addressing the impact of temperature on the functioning of any organism is complex, as this parameter has overriding effects on virtually every aspect of cell physiology. Temperature notably impacts the cellular size, the stability and conformation of macromolecules, and the kinetics of biochemical reactions, altogether leading to differences in cell growth [START_REF] Kingsolver | The well-temperatured biologist[END_REF]. In the case of photosynthetic organisms such as Prochlorococcus, growth is closely linked to their photosynthetic capacity, which is also impacted by temperature [START_REF] Mackey | Effect of temperature on photosynthesis and growth in marine Synechococcus spp[END_REF][START_REF] Pittera | Connecting thermal physiology and latitudinal niche partitioning in marine Synechococcus[END_REF][START_REF] Pittera | Adaptive thermostability of light-harvesting complexes in marine picocyanobacteria[END_REF]. Under temperature conditions below the optimum, the slow-down in carbon fixation rates constrains the replenishment of final acceptors of the photosynthetic electron flow, producing an imbalance between photochemistry and metabolism. Under these conditions, the excess of light energy absorbed can generate cell-damaging reactive oxygen species (ROS), which need to be counterbalanced by photoprotective mechanisms [START_REF] Bailey | Photoprotection in Cyanobacteria: Regulation of Light Harvesting[END_REF]. Under heat-stress conditions (35-50ºC) ROS are also typically produced likely not as a result of an excess of energy absorbed, but of heatinduced structural and functional changes in the photosystems and thylakoid membranes [START_REF] Yamamoto | Quality control of photosystem II: The mechanisms for avoidance and tolerance of light and heat stresses are closely linked to membrane fluidity of the thylakoids[END_REF]. The decline in photosynthetic activity in phototrophs under moderate warm stress has been associated with different processes, including the inhibition of de novo synthesis of the photosystem II D1 protein by ROS [START_REF] Murata | Photoinhibition of photosystem II under environmental stress[END_REF], the inactivation of the oxygen-evolving complex [START_REF] Pospíšil | Molecular mechanism of high-temperatureinduced inhibition of acceptor side of Photosystem II[END_REF] and declines in electron transport [START_REF] Mathur | Photosynthesis: Response to high temperature stress[END_REF].

At the expression level, a variety of compensatory mechanisms have been found to be activated in several phytoplankton groups (i.e., Synechococcus and eukaryotic phytoplankton) to preserve cell functioning under thermal stress conditions [START_REF] Mackey | Effect of temperature on photosynthesis and growth in marine Synechococcus spp[END_REF][START_REF] Pittera | Connecting thermal physiology and latitudinal niche partitioning in marine Synechococcus[END_REF][START_REF] Pittera | Adaptive thermostability of light-harvesting complexes in marine picocyanobacteria[END_REF][START_REF] Varkey | Effects of low temperature on tropical and temperate isolates of marine Synechococcus[END_REF][START_REF] Toseland | The impact of temperature on marine phytoplankton resource allocation and metabolism[END_REF][START_REF] Guyet | Synergic Effects of Temperature and Irradiance on the Physiology of the Marine Synechococcus Strain WH7803[END_REF][START_REF] Rosenberg | Particle-associated and freeliving bacterial communities in an oligotrophic sea are affected by different environmental factors[END_REF].

The cold-stress response network involves the upregulation of fatty acid desaturases to offset decreases in membrane fluidity at low temperature, and RNA helicases and cellular chaperones to facilitate proper folding of nucleic acids and proteins [START_REF] Toseland | The impact of temperature on marine phytoplankton resource allocation and metabolism[END_REF][START_REF] Guyet | Synergic Effects of Temperature and Irradiance on the Physiology of the Marine Synechococcus Strain WH7803[END_REF][START_REF] Mikami | Membrane fluidity and the perception of environmental signals in cyanobacteria and plants[END_REF][START_REF] Los | Responses to cold shock in cyanobacteria[END_REF]. Low temperature can also impact the expression of central components of the transcriptional and translational machinery in eukaryotic phytoplankton, which are upregulated to compensate for their reduced efficiency [START_REF] Toseland | The impact of temperature on marine phytoplankton resource allocation and metabolism[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF], and even impact global regulatory networks such as circadian rhythms in cyanobacteria [START_REF] Murayama | Low temperature nullifies the circadian clock in cyanobacteria through Hopf bifurcation[END_REF]. At elevated temperatures, a nearly universal response induces the expression of heat-shock proteins, which degrade or restructure denatured proteins and nucleic acids [START_REF] Rajaram | Cyanobacterial heat-shock response: Role and regulation of molecular chaperones[END_REF].

Some of the temperature compensatory mechanisms involve only short-term transcriptional responses until cell functioning is restored [START_REF] Los | Responses to cold shock in cyanobacteria[END_REF]. In other cases, the baseline expression of key enzymes is upregulated under long-term cold acclimations [START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. Beyond short-term temperature manipulation experiments, where cells are suddenly exposed to a "thermal shock", understanding mechanisms of long-term acclimation is particularly relevant as they more accurately reflect responses to gradually changing thermal conditions.

Here, we performed a series of experiments on Prochlorococcus marinus MIT9301, where cells were progressively exposed from a temperature close to their optimum to their upper and lower thresholds of growth. This strain, which is a representative of the Prochlorococcus dominant clade in situ (HLII, [START_REF] Farrant | Delineating ecologically significant taxonomic units from global patterns of marine picocyanobacteria[END_REF][START_REF] Huang | Novel lineages of Prochlorococcus and Synechococcus in the global oceans[END_REF]), was selected because it shares the highest sequence similarity with environmental sequences [START_REF] Kettler | Patterns and implications of gene gain and loss in the evolution of Prochlorococcus[END_REF] and enabled the identification of closely related transcripts in natural Prochlorococcus populations. We first used a quantitative RNA-Seq approach [START_REF] Moran | Sizing up metatranscriptomics[END_REF][START_REF] Gifford | Quantitative transcriptomics reveals the growth-and nutrient-dependent response of a streamlined marine methylotroph to methanol and naturally occurring dissolved organic matter[END_REF] to decipher the transcriptional response of MIT9301 to temperature acclimations. Then, we addressed the environmental relevance of one of the most conspicuous transcriptional responses observed in MIT9301, involving highly expressed photosynthetic genes, in oceanic metatranscriptomes collected along a comparable thermal gradient. Our objective was to analyse how sustained growth at sub-optimal temperature reprograms the transcriptome of Prochlorococcus and significantly advance in our understanding of which mechanisms underlie their growth restriction under cold and warm conditions.

Results

Thermal acclimation experiments with Prochlorococcus marinus MIT9301: growth rates and mRNA content.

MIT9301 cultures were synchronized to a diel 12:12 light/dark cycle and long-term acclimated to six temperatures along their thermal range (Figure 1, Figure S1). MIT9301 could not survive single-generation transfers below 17ºC or above 30ºC degrees and, thus, these were considered thermal thresholds for this strain (Tmin and Tmax, hereinafter). The growth rate of MIT9301 increased from 0.17 day -1 at Tmin to ca. 0.61 day -1 at 25ºC (hereinafter referred to as optimum growth temperature, Topt) and, thereafter, entered a warm-stress zone up to 30ºC, where no further increases in growth rate were observed (Figure 1A). The average size of MIT9301 cells also changed along the thermal gradient, with maximum and minimum values at the Tmin and Tmax, respectively (Figure 1A).

After the acclimation period, RNA samples were collected at different temperature conditions 3 hours after subjective sunrise and sunset (day-and night-time, respectively, hereinafter). Large variations in the number of mRNA transcripts per cell were found in replicate cultures acclimated to 17 and 20ºC during day-time, while values were highly constrained in temperatures close to the optimum (22 and 25ºC, Figure 1B). A pattern of decrease of mRNA transcripts with increasing temperature was found, with the average number of mRNA transcripts per cell being positively correlated with cellular size in night-time samples (Spearman Rho = 0.89, p < 0.001, Supplementary Figure S2).

Quantitative global transcriptomic analysis of MIT9301 in experimental long-term acclimations

Top-expressed genes in MIT9301 were associated with photosynthetic components (e.g., psbA, psbC), the RuBisCO enzyme (rbcL) or an ammonium transporter (amt), which reached average values above two mRNA transcripts per cell (Table S3). However, the average abundance of most mRNA transcripts was at least one order of magnitude below that value, which indicates that only a fraction of the population was actively expressing them at any given time. Estimates of mRNA transcript abundance were normalized by cell biovolume (i.e., transcripts per µm 3 or [mRNA], Table S4), to discard potential indirect effects of cell size on transcript abundance in further analyses.

A substantial fraction of MIT9301 genes were differentially expressed along the temperature gradient (i.e., exhibited significant variations in cellular [mRNA] estimates at different temperatures). In total, 61% of protein-coding MIT9301 genes were differentially expressed at night-time, while this number was reduced to 30% during day-time (Kruskal-Wallis test, p < 0.05), in association with an increase in the variability of gene expression levels; while [mRNA] values of individual genes in different biological replicates were highly constrained at the Topt, a large variation was found during day-time at both thresholds of growth, and particularly at the Tmin (Figures 2 and3, Table S4). This suggests a reduced ability of MIT9301 cells to maintain a tight transcriptional control under challenging temperature conditions when cells are exposed to light. Notably, the expression of some sigma factors and key regulatory proteins from different families also showed this pattern (Figures 3A and3B).

We identified five clusters of genes according to their patterns of day and night-time expression at different temperatures (Figure 2, Table S5). More than 90% of MIT9301 protein-coding genes were assigned to one of these clusters with a probability score > 0.5), which indicates that these clusters were highly representative of the main thermal gene expression responses in this strain. Clusters A and E were represented by genes involved in core cellular and metabolic processes typically expressed in Prochlorococcus during day-and night-time, respectively [START_REF] Zinser | Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, Prochlorococcus[END_REF]. Clusters C and D were associated with mechanisms of cold-stress response, as they were characterized by a strong upregulation at the Tmin either during day-time or both day-and nigh-time, respectively. Finally, the expression of genes in Cluster B showed a decreasing trend from the Topt towards the Tmin during day-time (Figure 2), paralleling the pattern observed in growth rates along the thermal niche (Figure 1A). Therefore, we hypothesize that the expression of Cluster B genes is associated with metabolic processes limiting the growth of Prochlorococcus when exposed to cold conditions.

Cluster A included genes related with C fixation and assimilation such as the RuBisCO (rbcLS), CO2 transporters (csoS2), carboxysome shell proteins (ccmK), the Calvin cycle (e.g., gap2, tktA, glpX, pgk, cbbA) and glycogen synthesis (glgABC), consistently expressed during day-time along the thermal gradient (Figure 2, Tables S4-S5). This cluster also included ATP synthesis genes (atpADE) and a few components of the PS II (psbA, psbC and psbD). Cluster E included genes related to catabolic consumption (cyoB, ndhD), DNA replication (dnaA, nrdJ, gyrB), cell division (ftsZYQ) and the pentose phosphate pathway (tal, gnd, zwf), all of them upregulated at night-time. Altogether, these essential pathways likely represent a transcriptional core, which Prochlorococcus marinus MIT9301 maintains at all temperature conditions. Clusters C and D genes included different elements of the global stress response (e.g., cellular chaperones such as groES/groES, dnaK, clpBCP [START_REF] Bae | Escherichia coli CspA-family RNA chaperones are transcription antiterminators[END_REF][START_REF] Watanabe | Protection of psbAII transcript from ribonuclease degradation in vitro by DnaK2 and DnaJ2 chaperones of the cyanobacterium Synechococcus elongatus PCC 7942[END_REF]), mechanisms of DNA repair (recA, ruvB [START_REF] Bagby | Response of Prochlorococcus to varying CO 2 :O 2 ratios[END_REF][START_REF] Six | Prochlorococcus and Synechococcus have evolved different adaptive mechanisms to cope with light and uv stress[END_REF]), and the synthesis of antioxidant compounds such as carotenoids (pds, crtBH) and rubredoxin (rub) (Table S5). Notably, the expression of the chaperones groEL/groES, grpE and htpG were strongly upregulated at the Tmin only during day-time, suggesting a prioritization of their expression during the light-exposed period (Figure 3C). Other metabolic processes upregulated at the Tmin were the mobilization of energy storage (i.e., glycogen degradation, glgP), and the synthesis of proteins, as reflected by the increase in the [mRNA] of amino-acid synthesis genes (glyA, serA, leuA), translation initiation factors (infABC) and N acquisition genes (Figures 2 and3, Table S4).

The strong upregulation of N acquisition mechanisms at the Tmin under light conditions was observed not only for genes predominately expressed during day-time at the Topt (i.e., the global nitrogen regulatory protein ntcA, glnA, and urea transporters), but also for genes typically expressed at night-time in Prochlorococcus, such as the ammonium transporter (amt) and urease genes (ureABC.) This likely reflects the large cellular demand of N for protein synthesis during day-time under cold stress conditions. In the case of phosphate uptake, the high affinity ABC transporter pstABC genes were upregulated under cold conditions at night, following the pattern of cluster E genes, possibly related to the cellular demand of P for DNA replication. By contrast, both copies of the periplasmic phosphate binding protein (pstS) showed maximum expression values around the Topt during day-time following the pattern of most photosynthetic genes (cluster B), which highlights the complexity in the thermal response of nutrient acquisition genes (Figure 3D).

Finally, the expression of all components of the PS I complex (psaABDEFKL) and some of the PS II (including psbBJH and the oxygen evolving complex protein psbO) showed a gradual decrease in expression from a temperature close to the optimum to the Tmin, (Figure 2) in correlation with MIT9301 growth rates (Figure 1). This expression pattern was different from other PSII components (psbACD, see above), which were not differentially expressed during day-time along the thermal niche (Kruskall-Wallis, p > 0.05, Figure 2). Similarly, many components of the photosynthetic electron transport genes were assigned to either Cluster B (petACGNM) or Cluster A (petBEDH), implying a non-uniform transcriptional thermal response of all components of the photosynthetic apparatus (Figure 4). Yet, a general pattern of upregulation of photosynthetic genes during night-time under cold conditions, inducing changes in their day-night log2fold expression ratio was observed (Figure 2), suggesting a loss in the capacity of the cells to regulate their circadian expression.

Transcriptional response of photosynthetic genes in naturally occurring

Prochlorococcus populations

With the aim of testing whether the transcriptional suppression of photosynthetic genes at cold temperature observed in MIT931 was also found in natural Prochlorococcus populations in situ, we identified reads closely related to MIT9301 in the Tara Oceans metatranscriptome dataset [START_REF] Salazar | Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome[END_REF] including samples distributed across different ocean basins along a comparable thermal gradient (Table S6). The number of MIT9301-like reads ranged from 6379 to 9.62 million in the different environmental samples (Table S7). The DESeq2 normalized abundance of transcript counts from some of the most actively expressed genes of the PSII (psbA, psbD) did not show any significant trend along the in situ thermal gradient from 17 to 30ºC (Spearman correlation, p > 0.05), mirroring the response observed under culture conditions (Figure 5, Supplementary Figure S3). By contrast, other PSII components (psbJ) were positively correlated with temperature both in the experimental and in situ datasets (Spearman R = 0.6, p < 0.01), indicating a downregulation at cold temperature (Figure 5). Similarly, the downregulation of PS I genes at cold temperature was clearly observed both in the experimental and in situ dataset (Figure 5), reinforcing the environmental relevance of this response.

Temperature had the strongest correlation to photosynthetic transcript counts in comparison with all other tested environmental variables (Supplementary Figure S4), excluding the possibility that these correlations were driven by co-varying environmental parameters.

Discussion

There is a remarkable gap of fundamental knowledge on the molecular mechanisms of thermal acclimation in Prochlorococcus, as previous studies have concentrated on their cyanobacterial sister clade Synechococcus and eukaryotic phytoplankton (12-14, 20-22, 40, 41). Acquiring this knowledge would be crucial towards answering a long-standing question: what limits the ability of Prochlorococcus to expand to high-latitude environments? The decrease in the light-harvesting capacity of phytoplankton under cold conditions has been typically attributed to changes in the conformation of membrane lipids and proteins of their photosynthetic apparatus [START_REF] Pittera | Adaptive thermostability of light-harvesting complexes in marine picocyanobacteria[END_REF][START_REF] Pittera | Thermoacclimation and genome adaptation of the membrane lipidome in marine Synechococcus[END_REF]. Our quantitative gene expression analysis shows that, in the case of Prochlorococcus, the inability to maintain their photosynthetic capacity under cold conditions is already critically compromised at the transcriptional level, as we found a clear suppression of the expression of most photosynthetic genes towards cold conditions. The same pattern was found for MIT9301-like reads in in situ metatranscriptomes across the global ocean, suggesting that this molecular mechanism may be relevant to explain the restricted distribution of Prochlorococcus to temperate zones. Notably, this response differs from previous studies targeting diatom cultures [START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF], or phytoplankton communities in situ [START_REF] Toseland | The impact of temperature on marine phytoplankton resource allocation and metabolism[END_REF][START_REF] Salazar | Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome[END_REF] , indicating fundamental differences in the ability of Prochlorococcus to respond to cold temperature, which may be related to their exceptional high sensitivity to oxidative stress [START_REF] Six | Prochlorococcus and Synechococcus have evolved different adaptive mechanisms to cope with light and uv stress[END_REF][START_REF] Ma | Degradation of hydrogen peroxide at the ocean's surface: The influence of the microbial community on the realized thermal niche of Prochlorococcus[END_REF].

Photosystems are naturally sensitive to light damage, which is exacerbated under low temperature [START_REF] Guyet | Synergic Effects of Temperature and Irradiance on the Physiology of the Marine Synechococcus Strain WH7803[END_REF]. The cellular decision of shutting down their sunlight energy conversion system at cold conditions likely arises from the inability of Prochlorococcus to cope with uncontrolled redox chemistry when there is an imbalance between the production of excited electrons by light and their metabolic consumption. The downregulation of photosystems would represent an emergency mechanism to slow-down the electron flow and prevent the production of cell-damaging ROS. Notably, the response was not equal for all photosystem components, as previously observed in cultured Prochlorococcus strains undergoing other types of stress, such as iron starvation [START_REF] Thompson | Transcriptome response of high-and low-light-adapted Prochlorococcus strains to changing iron availability[END_REF], phage infection [START_REF] Thompson | Gene expression patterns during light and dark infection of Prochlorococcus by cyanophage[END_REF], or high-light exposure [START_REF] Steglich | Genome-wide analysis of light sensing in Prochlorococcus[END_REF]. On the one hand, the high expression of psbA transcripts at all temperature conditions is likely related to the need to maintain an exceptionally high turnover rate of this protein [START_REF] Mattoo | Dynamic metabolism of photosystem II reaction center proteins and pigments[END_REF], being differentially regulated than other PS components [START_REF] Zinser | Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, Prochlorococcus[END_REF][START_REF] Garczarek | Differential expression of antenna and core genes in Prochlorococcus PCC 9511 (Oxyphotobacteria) grown under a modulated lightdark cycle[END_REF][START_REF] Holtzendorff | Genome streamlining results in loss of robustness of the circadian clock in the marine cyanobacterium Prochlorococcus marinus PCC 9511[END_REF]. On the other hand, the selective downregulation of PSI probably arises from the strong need to protect PSI from oxidative stress, as this photosystem typically lacks efficient repair machinery, and therefore its damage may be practically irreversible [START_REF] Sonoike | Photoinhibition of photosystem I[END_REF].

Interestingly, MIT9301 also upregulated the plastoquinol terminal oxidase (PTOX) at the Tmin (Figure 2), which is thought to function as a safety valve in cyanobacteria to avoid electron flow towards PSI [START_REF] Bailey | Alternative photosynthetic electron flow to oxygen in marine Synechococcus[END_REF].

In addition to the transcriptional suppression of photosynthetic genes, we found that under light conditions, cold temperature induced a loss in the regulatory capacity of MIT9301 cells. This was reflected in the loss of the circadian day/night gene expression ratio and the increased variability in the concentration of cellular mRNA transcripts among biological replicates. In a previous study, it has been suggested that higher levels of stochasticity in Prochlorococcus' gene expression during the transition from photosynthesis to the use of internal energy is related to the accumulation of ROS [START_REF] Biller | Heterotroph Interactions Alter Prochlorococcus Transcriptome[END_REF].

Our transcriptomic results are consistent with the idea of oxidative stress impacting the regulatory capacity of Prochlorococcus. Notably, at the Tmin we observed a high variability in the expression of regulatory proteins that modulate the cellular response to daily light fluctuations in cyanobacteria, including sigma factors (rpoD) [START_REF] Imamura | Sigma Factors for Cyanobacterial Transcription[END_REF][START_REF] Summerfield | Role of sigma factors in controlling global gene expression in light/dark transitions in the cyanobacterium Synechocystis sp. strain PCC 6803[END_REF], the NblS-RpaB two-component system [START_REF] Van Waasbergen | nblS, a gene involved in controlling photosynthesis-related gene expression during high light and nutrient stress in Synechococcus elongatus pcc 7942[END_REF] and the SasA-RpaA clock output system [START_REF] Espinosa | Crosstalk and regulatory interactions between the essential response regulator RpaB and cyanobacterial circadian clock output[END_REF][START_REF] Takai | A KaiC-associating SasA-RpaA two-component regulatory system as a major circadian timing mediator in cyanobacteria[END_REF].

Assuming that mRNA transcript levels reflect the protein levels of these regulators, our results would imply a critical impairment of their co-regulated networks. Other mechanisms of transcriptional regulation in Prochlorococcus (i.e., RNA-based regulatory strategies (58)), were likely also compromised at low temperature, as evidenced by the upregulation of the ribonuclease rne gene at the Tmin (Table S4).

Marked changes in the day/night gene expression ratio of some of Prochlorococcus key functional genes along the thermal niche imply a deregulation of one of their fundamental features, i.e., the coordination of transcriptional oscillations with the daily light/dark cycle. This feature is key to optimize cellular processes through anticipating and synchronizing transcription of photosynthetic genes with daylight hours [START_REF] Zinser | Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, Prochlorococcus[END_REF][START_REF] Jacquet | Cell cycle regulation by light in Prochlorococcus strains[END_REF][START_REF] Shalapyonok | Ultradian growth in Prochlorococcus spp[END_REF]. At Topt, the day/night expression preferenda of most key functional genes of MIT9301 matched those previously observed in the model strain MED4 [START_REF] Zinser | Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, Prochlorococcus[END_REF], reinforcing the idea that maintaining this transcriptional choreography is a highly conserved and critical trait. The deregulation observed at cold temperature led to the paradoxical situation where, after subjective sunrise, chilled Prochlorococcus MIT9301 cells contained several-fold less PSI transcripts than after subjective sunset, which supports the idea of a malfunctioning regulatory network. With only two samplings over the daily cycle, we cannot ensure whether the observed changes were due to random misregulations or variations in the phasing or amplitude of their diel gene expression patterns. Yet, considering that we were sampling the two daily periods when most Prochlorococcus genes show maxima in expression [START_REF] Zinser | Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, Prochlorococcus[END_REF], the inversion of their day/night preferenda is remarkable and likely has an important impact on its fitness. By contrast to the pattern observed in day-time samples, genes related to Prochlorococcus cell division cycle, typically expressed during night-time, showed rather constrained

[mRNA] values between replicates. We observed an increase in [mRNA] of those genes towards cold conditions, which may be related to the predominant cell cycle phase of the cells. As the timing of cell division is delayed in Prochlorococcus marinus MIT9301 when acclimated to cold temperature (61), our results likely reflect a situation where a higher proportion of cells were still undergoing the S phase at 17ºC and 20ºC at the time of sampling (i.e., 3 hours after subjective dusk), as compared to other acclimation temperatures.

At the warm temperature threshold, the upregulation of a variety of cellular chaperones (e.g., groEL/groES, htpG, grpE) reflected that cells were undergoing substantial stress. However, no drastic changes were generally observed in the expression of most proteincoding genes at the Tmax. Accordingly, a previous study on the short-term response of MED4 to warm stress found that the synthesis of new polypeptides was not induced [START_REF] Ting | Photosynthetic Response to Environmental Stress in Prochlorococcus[END_REF].

We had previously shown that Prochlorococcus MIT9301 cells decrease in size after long-term warm acclimation, in accordance with the temperature-size rule [START_REF] Palacio | Changes in Population Age-Structure Obscure the Temperature-Size Rule in Marine Cyanobacteria[END_REF]. Interestingly, here, our quantitative transcriptomic approach showed a conspicuous streamlining in the transcript inventory in the cells in parallel with the progressive reduction in cell size. While at non-restricting growth temperature the average estimate of mRNA transcript abundance per cell was within the range reported for environmental marine bacteria (i.e., ca. 85-255 transcripts per cell (32)), under warm conditions this average dropped down to 30 mRNA transcripts of protein-coding genes per cell at night-time. Cellular reactions involving small numbers of molecules are intrinsically noisy, being dominated by fluctuations in concentration and stochasticity [START_REF] Swain | Intrinsic and extrinsic contributions to stochasticity in gene expression[END_REF][START_REF] Thattai | Intrinsic noise in gene regulatory networks[END_REF]. Thus, the decline in the transcript inventory under warm conditions invites the hypothesis that there is a critical threshold in the number of mRNA copies beyond which cells lose regulatory capacity, contributing to the growth arrest.

In summary, previous studies on phytoplankton have identified the cellular membrane and translational apparatus as central elements associated with the thermal adaptation at the transcriptional level [START_REF] Toseland | The impact of temperature on marine phytoplankton resource allocation and metabolism[END_REF][START_REF] Liang | Molecular mechanisms of temperature acclimation and adaptation in marine diatoms[END_REF]. Some of these mechanisms were also observed in MIT9301, such as the upregulation of the translational machinery, likely to compensate the general slow-down in protein synthesis rates under cold conditions [START_REF] Mikami | Membrane fluidity and the perception of environmental signals in cyanobacteria and plants[END_REF]. Yet, we found that in the case of Prochlorococcus, oxidative stress emerged as a major factor impacting its physiology when approaching cold temperature, as this source of stress relates to both the need to protect the photosynthetic machinery and the ability of Prochlorococcus to "reset" their daily cycles in the morning hours [START_REF] Axmann | Biochemical evidence for a timing mechanism in Prochlorococcus[END_REF]. Cold temperature has been previously shown to nullify the circadian rhythm in different organisms, including plants and different phytoplankton species, moving the circadian oscillation to a damped oscillation (see references in [START_REF] Murayama | Low temperature nullifies the circadian clock in cyanobacteria through Hopf bifurcation[END_REF]). As Prochlorococcus contains only a minimalist circadian system, their cell cycle is likely more easily perturbated than that from organisms containing a complete kaiABC gene set.

The disruption of the transcriptional choreography in Prochlorococcus may be a differentiating factor as compared to Synechococcus and eukaryotic phytoplankton, which do not require maintaining such a finely tuned daily expression rhythm to maintain their metabolism. The higher tolerance of Synechococcus to oxidative stress(38) may also imply a more resilient photochemistry when exposed to cold conditions, enabling them to colonize higher latitudes. Additionally, we postulate that increased levels of stochasticity in gene expression at temperature challenging conditions may contribute to a decrease in Prochlorococcus fitness. These remains as an interesting hypotheses to test in future studies, with implications for the functioning of this global primary producer and, thus, the marine carbon biogeochemistry in future oceanic conditions.

Materials and Methods

Growth of cultures and temperature acclimation

We grew non-axenic cultures of Prochlorococcus marinus MIT9301 obtained from the Roscoff Culture Collection (RCC) in PCR-S11 culture medium (66) based on Red Sea Salt (Houston, TX, USA). Cultures were grown under a 12:12 hour photoperiod and irradiance of 120 µmol quanta m -2 s -1 in polycarbonate flasks with vented caps. During the acclimation, we maintained the cultures in exponential growth by performing serial transfers before cell density reached 30% of the maximum yield. The acclimation started from 22ºC (i.e., temperature of maintenance in RCC) and temperature was progressively changed towards the upper and lower thermal thresholds. At each acclimation step, temperature was changed by a maximum of 2ºC and down to 0.2ºC when approaching the temperature thresholds, to avoid lethal thermal stress (Figure S1). We considered that the culture had been fully acclimated to a temperature treatment when growth rate stayed stable in at least two consecutive growth curves after at least 8 generations. Flow cytometry was used for sustained monitoring of the culture growth during the acclimation process. Samples were fixed with glutaraldehyde (final concentration of 0.025%) for 10 minutes at room temperature and dark conditions, and frozen at -80°C until analysis in a FACSCalibur flow cytometer (Becton Dickinson). Estimates of cell size were obtained based on the natural logarithmic-transformed side scatter (SSC) using the calibration provided in [START_REF] Calvo-Díaz | Seasonal dynamics of picoplankton in shelf waters of the southern Bay of Biscay[END_REF] and assuming a spherical cellular shape.

RNA samples collection and extraction

Once the cultures reached full acclimation to the temperatures selected [START_REF] Murata | Photoinhibition of photosystem II under environmental stress[END_REF][START_REF] Varkey | Effects of low temperature on tropical and temperate isolates of marine Synechococcus[END_REF][START_REF] Guyet | Synergic Effects of Temperature and Irradiance on the Physiology of the Marine Synechococcus Strain WH7803[END_REF][START_REF] Los | Responses to cold shock in cyanobacteria[END_REF] and 30°C), we re-inoculated biological replicate batch cultures into fresh medium (160 mL) and collected samples for RNA-Seq analysis during exponential growth (with cell density values ranging between 6 to 17 10 7 cells mL -1 , Table S1). For each temperature and biological replicate (ranging from 3 to 7, depending on the experimental treatment, Table S1), samples for RNA extraction were collected 3 hours after the onset and offset of the photoperiod (day-and night-time, respectively). Exceptionally, for the acclimation temperature 22ºC, only day-time RNA samples were available. Samples were filtered on 0.22-µm pore-size PES filters using a vacuum pump at a pressure of 5 psi. Immediately after filtration, filters were snap frozen in liquid nitrogen and stored at -80°C. The time elapsed from the start of the filtration until freezing was always lower than 2 minutes.

Quantitative benchmarked RNA extraction was performed following (33) using five RNA standards from Saccharolobus (Sulfolobus) solfataricus P2 (NCBI Taxon ID 273057) obtained by in vitro transcription of genomic templates of the isolate (standards 3, 6, 7, 13 and 14, as described in [START_REF] Gifford | Quantitative transcriptomics reveals the growth-and nutrient-dependent response of a streamlined marine methylotroph to methanol and naturally occurring dissolved organic matter[END_REF]). The RNA standards were individually spiked (10 to 28 µL) at a concentration of ca. 20 pg µL -1 to the filters prior to the initiation of the RNA extraction. Subsequently, RNA samples were extracted with the mirVana kit (Ambion), and DNA was removed using the TURBO DNase (Ambion). Samples were depleted from ribosomal RNA using the Ribo-Zero rRNA removal kit (Bacteria, Illumina) and quality check was performed using a Bioanalyzer (Agilent). mRNA samples were concentrated using the Zimo Clean & Concentrator kit, and cDNA libraries were constructed using the TruSeq Stranded mRNA Sample Preparation Kit (Illumina). cDNA libraries were sequenced as 75bp paired-end reads on an Illumina HiSeq v4 platform (CNAG, Spain).

Raw reads have been submitted to ENA under project accession number PRJEB54738.

Quantitative gene expression analysis of Prochlorococcus MIT9301 under culturing conditions

Sequence read quality check was performed with the FastQC tool [START_REF] Andrews | FastQC: A quality control tool for high throughput sequence data[END_REF], and Trimmomatic protein-coding gene, Ts corresponds to the number of reads assigned to the corresponding MIT9301 protein-coding gene, Sa corresponds to the molecules of internal RNA standards spiked to the RNA sample, and Ss corresponds to the number of reads assigned to S. solfataricus internal standards. In this calculation, one of the standards (standard 14) was removed from the analysis because it was consistently recovered in higher proportion than other standards. Ta values were divided by total cell abundance or estimates of total cell biovolume collected in the corresponding RNA filter to obtain estimates of transcript abundance per cell and per volume (i.e., transcript concentration), respectively (Tables S1-S3). This normalization is relevant because cell size, which varies over the thermal gradient in this strain (see Figure 1A), can impact the number of cellular transcripts [START_REF] Kempe | The volumes and transcript counts of single cells reveal concentration homeostasis and capture biological noise[END_REF][START_REF] Zhurinsky | A coordinated global control over cellular transcription[END_REF].

Bioinformatic analysis of transcriptional patterns of Prochlorococcus photosynthetic genes in oceanic samples and culture conditions

For comparing the expression patterns of Prochlorococcus photosynthetic genes along the same thermal gradient under environmental and culturing conditions, two datasets were produced using a common normalization method (DESeq2 (76)). The experimental dataset was obtained from the raw read counts obtained by HTSeq2 in the long-term thermal acclimation experiments, as explained above. For obtaining the environmental database, a dataset of Tara Oceans metatranscriptomes (39) was initially selected based on the latitude range where Prochlorococcus is found in the ocean (i.e., between 45º N and S), the thermal range of MIT9301 (17ºC to 30ºC), and the time of sample collection (between 6 and 12 am, when the expression of photosynthetic genes should be close to their maximum). Fastq sequence files were quality filtered with fastp (77) using default parameters, and rRNA sequences were removed with RiboDetector (78) with the option "--ensure" selected. The remaining reads were filtered to remove reads not affiliated with Prochlorococcus, using a custom made database with the complete genome sequences in the MarRef database, which included 16 Prochlorococcus genomes (79), and eukaryotic genes of interest extracted from Refseq (80) (i.e., psaA, psaB, psaD, psaF, psaL, psbA, psbD, and psbO, searched with Entrez filter [Gene Name] AND ((protists[filter] OR

plants[filter]) AND refseq[filter]). Metatranscriptome sequences closest to

Prochlorococcus were identified based on Blastn v.2.12.0+ searches (identity ≥ 98% and bitscore ≥ 30), and only those with highest bitscore to Prochlorococcus sequences were considered further. Subsequently, we applied a two-step filtering strategy to obtain read counts closely related to MIT9301. First, we aligned each metatranscriptome sample against MIT9301 genome using BWA mem version 0.7.17-r1188 with default parameters [START_REF] Li | Fast and accurate short read alignment with Burrows-Wheeler transform[END_REF]. Next, we discarded alignments which had a percent identity lower than 98%, a read length lower than 50 bases, and a number of matches lower than 50% of the total length of each aligned sequence. Percent identity was computed as 100 × (N_m / (N_m + N_i)), where N_m corresponds to the number of matches in the alignment and N_i to the number of mismatches. The number of matches was obtained by parsing the MD tag of the alignment record, while the number of matches and mismatches was obtained from the CIGAR string in the SAM file. Once alignments were filtered, we proceeded to count aligned reads with HTSeq v.2.0. with default parameters [START_REF] Putri | Analysing highthroughput sequencing data in Python with HTSeq 2.0[END_REF]. Next, we removed noncoding genes from the count matrices as well as genes which had no counts across all conditions, to facilitate the consequent normalization. We also discarded samples which had counts in less than 10 genes other than the psbA gene. Finally, we normalized count data using the default DESeq2 v.3.15 count normalization workflow [START_REF] Love | Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[END_REF]

Softclustering and statistical analyses

Clusters of differentially expressed genes that responded similarly over the thermal gradient were identified using softclustering, following [START_REF] Kumar | Mfuzz: A software package for soft clustering of microarray data[END_REF]. A matrix of N genes x 9 treatments (4 temperatures at night-time and 5 temperatures at day-time) was used as input data. Data for each gene was standardized to zero mean and unit variance. The optimal value of the parameter m in the Mfuzz algorithm was estimated through randomization following [START_REF] Schwämmle | A simple and fast method to determine the parameters for fuzzy c-means cluster analysis[END_REF]. The number of clusters was chosen to maximize the functional enrichment of gene clusters (COGs) and the ClusterJudge method [START_REF] Package | Package ' ClusterJudge[END_REF]. The standardized data was clustered by a generalized version of the fuzzy c-means algorithm.

Finally, statistically significant differences in cellular transcript concentration among temperature regimes were determined by the Kruskall-Wallis test using R.

( 69 )

 69 was used to trim raw sequences (SLIDINGWINDOW:50:35 and MINLEN:50) and pair those passing quality thresholds. rRNA sequences were removed using SortMeRNA (70) and the remaining reads were mapped with Bowtie2 (71) (using the '-non-deterministic' parameter) against the Prochlorococcus marinus MIT9301 genome (NCBI Taxon ID 167546). The same procedure was done with the S. solfataricus genome to identify RNA internal standard reads. Read count tables were obtained using HTSeq (72) with the following parameters: '-stranded = reverse -a 10 -m intersection-nonempty'. Quantitative estimates of individual transcript abundance (Ta) of MIT9301 protein-coding genes in each RNA sample were obtained following the calculations described in (73): Ta = (Ts x Sa)/Ss where Ta corresponds to the estimated number of transcripts of an individual MIT9301

Figure 1 .

 1 Figure 1. Growth rates, cell size and number of mRNA transcripts per cell in samples of

Figure 2 .

 2 Figure 2. Clusters of Prochlorococcus marinus MIT9301 genes according to their pattern

Figure 3 .

 3 Figure 3. Cellular expression levels (measured as [mRNA]) in Prochlorococcus marinus

Figure 4 .

 4 Figure 4. Schematic diagram showing some of the main components of the

Figure 5 .

 5 Figure 5. Expression patterns of a selection of Prochlorococcus photosynthetic genes of

Acknowledgements: We are grateful to the Spanish Ministry of Economy and Competitiveness (MINECO) for supporting LA-S's Ramón y Cajal research contract (RYC-2012-11404), AP's FPI Ph.D. fellowship (BES2015076149) and the project TECCAM (CTM2014-58564-R) and the Spanish Ministry of Science and Innovation for supporting the project CYADES (RTI2018-100690-B-I00). SRE and JMG were supported by project PID2019-110011RB-C32 (Spanish Ministry of Science and Innovation, Spanish State Research Agency, doi: 10.13039/501100011033). L.G acknowledges funding from the Agence Nationale de la Recherche project CINNAMON (ANR-17-CE2-0014-01). This paper is contribution number (to be updated) from AZTI (Marine Research Division).

regression lines are shown for all genes with significant Spearman correlation coefficients 848 at a p-value < 0.05 (indicated in the plots).