Diel dynamics of bacterial and picophytoplankton growth, grazing and viral lysis at different depths in the tropical South China Sea in spring

Diel dynamics of bacterial and picophytoplankton growth, grazing and viral lysis at different depths in the tropical South China Sea in spring | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diel dynamics of bacterial and picophytoplankton growth, grazing and viral lysis at different depths in the tropical South China Sea in spring Clara Natalie Annabel, Fuh-Kwo Shiah, Patrichka Wei-Yi Chen, Madeline Olivia, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7350023/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To examine the relative importance of nanoflagellate grazing and viral lysis on prokaryote abundance—including heterotrophic bacteria, Synechococcus spp., and Prochlorococcus spp.—in the tropical ocean, a modified dilution technique combined with light-dark experiments was used during a South China Sea cruise in late April 2025. Results show that during the daytime, the combined carbon loss from viral lysis and nanoflagellate grazing (0.40 and 0.20 µgC L⁻¹ h⁻¹, respectively) accounted for nearly 100% of bacterial production in surface waters. In the deep chlorophyll maximum layer, viral lysis alone removes almost 80% of the bacterial production during the daytime. The carbon losses of Synechococcus spp. to nanoflagellate grazing were approximately 0.06 µgC L⁻¹ h⁻¹ in the daytime and 0.04 µgC L⁻¹ h⁻¹ at night, which represent 55% and 33% of total Synechococcus spp. production, respectively. These results strongly suggest that nanoflagellate grazing is the primary factor controlling the daily fluctuations in Synechococcus spp. abundance. The carbon flows among the components of target organisms and the two top-down forces constructed by this research can be indicative for future studies in this and other tropical seas. South China Sea picoplankton microbial loop modified dilution technique viral lysis nanoflagellate grazing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction The picophytoplankton (< 2 µm) dominate phytoplankton abundance and biomass in oligotrophic ocean and play a major role in the dynamics of the food webs (Li et al. 1992 ; Legendre and Rassoulzadegan 1995 ; Patten et al. 2018 ). Among the picophytoplankton, Prochlorococcus (PRO) typically dominates the picophytoplankton in offshore oligotrophic oceanic waters (between latitudes 40°N and 40°S). A wider geographic distribution than PRO has been reported for Synechococcus spp. (SYN), which can be found in oligotrophic through to mesotrophic ecosystems and in tropical as well as polar waters. A significant amount of primary production is attributed to PRO and SYN in oligotrophic oceanic systems (Li et al. 1992 ), and these populations are considered vital components of marine pelagic food webs. Despite considerable information on their distribution, abundance, and biology (Chen et al. 2011 ; Wei et al. 2020 ; Wang et al. 2023 ), little is known about the factors governing their populations, such as biological factors and environmental factors. Particularly, in the open ocean, the relative importance of grazing versus viral lysis controls remains poorly documented (Baudoux et al. 2008 ; Evans and Brussaard 2012 ; Pasulka et al. 2015 ; Tsai et al. 2016 ). A variety of factors influence the dynamics of picophytoplankton in aquatic ecosystems, including trophic levels, temperature, nutrient limitations, and light limitations, but they are also regulated by grazing and viral lysis. Furthermore, it remains unclear how grazing versus viral lysis controls different picophytoplankton groups during a diel variation. Primary producers must respond to changes in the availability of light during the day. Diel cycles of bacterial activity therefore suggest that dissolved organic matter (DOM) is produced by photosynthetic processes and consumed by bacteria (BAC) (Gasol et al. 1998 ). It is not only possible to observe variations in bacterial production over a seasonal period, but also on a diel scale in the surface layer of the ocean. The short-term variations between production of BAC and DOM are more intense in oligotrophic environments, where substrate supply is limited, and we may expect tightly coupled covariation between the two processes (Gasol et al. 1998 ). Furthermore, the diel patterns of bacterial activity, however, may also be affected by other factors varying daily, including ultraviolet radiation (Jeffrey et al. 1996 ), grazing (Connell et al. 2020 ), and viral lysis (Ho et al. 2021 ) There is no doubt that the South China Sea (SCS) is one of the world's largest marginal seas, which is characterized by warm and oligotrophic conditions, like other subtropical oceans. Despite the large amount of nutrients supplied by several large rivers, including Pearl River and Mekong River, the upper water column of SCS is often stratified and remains oligotrophic, particularly during summer, which limits primary production due to inorganic nutrients (Wong et al. 2007 ). In the SCS, the East Asian monsoon controls most of the changes in the atmosphere and upper ocean. The equatorial and central Pacific monsoons closely follow the climatic variations in these regions. Additionally, typhoons and strong internal waves frequently pass through SCS. The magnitude of vertical mixing and the stability of the water column could be affected by all these physical disturbances on different time and spatial scales. Thus, the SCS is an excellent location for observing how the oceanic ecosystem responds to climate change across different time frames, ranging from short-term events to seasonal, yearly, and decade-long periods. According to the consensus mentioned above, scientists in Taiwan (Republic of China) established the Southeast Asia Time-series Station (SEATs) in 1999, located at 18°N, 116°E in the SCS. Previous research has demonstrated that picophytoplankton constitute the majority of phytoplankton biomass and primary production in the central South China Sea (Ning et al. 2005 ; Liu et al. 2007 ). Due to its warm, oligotrophic conditions and the dominance of picoplankton in this region, it is expected that the microbial loop serves as the principal pathway for carbon cycling and energy transfer. This study presents a flow cytometric analysis of picoplankton collected from the SEATs site, alongside two diel surveys conducted in April 2025 to assess picoplankton abundance and associated environmental variables across varying depths. Utilizing these sampling methodologies, we characterized the vertical distribution and diel variability of picoplankton populations. Furthermore, we investigated diel fluctuations in growth and mortality rates, including grazing and viral infection, affecting both BAC and picophytoplankton within the surface and deep chlorophyll maximum (DCM) layers of the tropical SCS. We hypothesized that growth and mortality rates of BAC and picophytoplankton exhibit diel variations between the surface and DCM layers. 2 Materials and methods 2.1 Study sites, sampling and measurement of physic-chemical parameters Samples were collected at the SEATs station (18°N, 116°E) in the SCS during a cruise from April 26 to May 5, 2025 (Fig. 1 ). Seawater samples were obtained from different depths within the upper 200 meters of the water column using Go-Flo bottles connected to a CTD rosette system. A CTD profiler was employed to assess the vertical distribution of temperature, salinity, conductivity, fluorescence, turbidity, and dissolved oxygen. Fluorescence measurements obtained from the CTD facilitated the characterization of the DCM structure throughout the water column. Based on this characterization, samples were collected at the surface (fixed at a depth of 5 meters) and at the DCM depth, for use in the modified dilution experiment. Seawater samples (1 mL, collected in triplicate) from each depth were preserved using glutaraldehyde at a final concentration of 0.5% for the subsequent analysis of BAC, picophytoplankton, and viruses (VIR). The samples were incubated in the dark for 15 minutes, rapidly frozen in liquid nitrogen, and stored at − 80°C until analysis (Brussaard 2004 ). Quantification of picophytoplankton, BAC, and VIR was performed using flow cytometry. Nutrients and Chl a were measured as described by Gong et al. ( 1995 ). 2.2 Calculation of BAC, SYN and PRO growth and mortality rates One limitation of the dilution method is that the starting cell concentration needs to be high enough to permit a three- to fourfold dilution while still retaining enough cells for precise counting. In the current cruise, the cell densities of picoeukaryotes (PPE) in surface and DCM waters were very low (< 0.5 × 10 3 cells mL − 1 ), failing to meet this requirement. Consequently, the current investigation was limited to examining the growth and mortality of BAC, SYN, and PRO. The objective was to assess the variations between daytime and nighttime in prokaryotic growth and mortality resulting from grazing and viral infection in both surface and DCM waters throughout the study period. To accomplish this, we took water samples at 0600 and 1800 a day on 29 April (EXP. I) and 30 April (EXP. II), and determined the growth, grazing, and viral lysis rates of BAC, SYN, and PRO using the modified dilution method (Evans et al. 2003 ). Initially, the subsamples from the incubated 5 L bottles were filtered through a 10 µm mesh, followed by filtration using 47 mm Nuclepore polycarbonate filters with a pore size of 0.2 µm, in order to prepare the 'standard' diluent. The size fractionation method employed for grazers (< 10 µm) was specifically chosen to exclude ciliates while preserving nanoflagellates (Tsai et al. 2013 ). A filtered seawater sample (< 10 µm) was diluted with 0.2 µm filtered seawater in a 4-point dilution series, resulting in final concentrations of 25%, 50%, 75%, and 100% of the original seawater (< 10 µm). In dilution experiments, the diluent is generally filtered using filters with a pore size of 0.2 µm, permitting the passage of nearly all free viral particles. Furthermore, an alternative dilution series was performed in which both grazing and viral mortality were evaluated employing seawater filtered through a 30 kDa membrane, rather than the standard 0.2 µm filtration. The net growth rates (Net µ, h –1 ) for BAC, SYN, and PRO were determined using Equation: Net µ = ln (Nt2/Nt1)/(t2-t1) Here, Nt1 and Nt2 denote the initial and final cell abundances in the experiment (cells ml⁻¹), respectively, while t1 and t2 represent the starting and ending time points of the experimental duration (hour). Incubations were conducted on the deck in triplicate using 50-mL polycarbonate incubation tubes, maintained at in situ temperatures for a duration of 8 to 9 hours during both daytime and nighttime periods. A neutral-density plastic sheet (Lee Filters, Hampshire, UK) was employed to cover the seawater surface, and DCM was incubated under ambient light conditions to replicate the light intensity corresponding to the sampling depth. Specific growth rates (µ, d⁻¹) were determined as the y-intercept obtained from a simplified linear regression analysis of net growth rate plotted against the dilution factor of 30 kDa filtered seawater. The slope derived from the regression equation of the 0.2 µm dilution series corresponded to the grazing rate (mg), whereas the slope obtained from the 30 kDa dilution series represented the combined rates of grazing and viral lysis (mg + mv). The significance of each regression analysis was assessed to determine whether the slopes differed significantly from zero (p < 0.05). In cases where the regression analysis of the 0.2 µm dilution series did not yield statistically significant results, the value of mg was assigned as 0. Moreover, an F-test was conducted to evaluate the statistical significance of the differences observed between the regression models derived from each experiment (p < 0.05). The computations of mv were conducted in accordance with the criteria outlined by Staniewski and Short ( 2018 ). (1) In the case where both regression analyses yielded statistically significant results and were found to differ significantly from one another, the relationship can be expressed as: mv = (mg + mv) – mg. (2) if both regressions were significant but not significantly different from each other: mv = 0; (3) if both regressions were not significant: mv = 0; 2.3 Flow cytometric analysis Flow cytometry (FCM) analysis was performed utilizing a BD FACSCalibur™ instrument to detect and quantify the abundance of picoplankton groups, including BAC, SYN, PRO, and PPE. FCM was performed on triplicates of bacteria by thawing, diluting 1:10 in 0.2 µm filtered TE buffer (10 mM Tris, 1 mM EDTA), staining with SYBR Green I (1:500 dilution; Molecular Probes) at 80°C for 10 min (Brussaard 2004 ). A phosphate-buffered saline (PBS) solution served as the sheath fluid, and forward-angle light scatter (FSC), side-angle light scatter (SSC), and green fluorescence (SYBR Green-I) were recorded for each sample. SYN, PRO, and PPE were identified based on pigment autofluorescence and FSC. 2.4 Statistical analysis A least-squares regression analysis was performed to investigate the relationship between the net growth rates of BAC and picophytoplankton and the fractions derived from 30 kDa or 0.2 µm dilution series. The analysis of variance (ANOVA) conducted on the regression lines confirmed their statistical significance. Furthermore, an F-test was conducted to evaluate the statistical significance of the slope between the 0.2µm and the 30 kDa dilution series. All statistical analyses were conducted utilizing STATISTICA version 7.0 software. A p-value < 0.05 was regarded as indicative of statistical significance. 3 Results 3.1 Study site environmental characteristics and microbial abundance Figure 2 presents the main vertical dynamics of the physicochemical and biological characteristics observed at the stations sampled during this cruise. During the sampling period, seawater temperatures in the upper approximately 10 m of the water column consistently exceeded 25°C, with marginally lower temperatures observed during daytime compared to nighttime (Fig. 2A, B). Salinity exhibited a pattern analogous to that of temperature, characterized by a marginally lower salinity level (approximately 33.5 psu), which decreased by approximately 0.5 psu within the upper ~10 m of the water column during nighttime (Fig. 2C, D). At the SEATS site, the deep chlorophyll a maximum (DCM) demonstrated distinct diel oscillations, occurring at depths of 75 m during the daytime and 64 m at nighttime in Exp. I (Fig. 2E). In Exp. II, the DCM was detected at 54 m during the daytime and at 74 m during the nighttime (Fig. 2F). NO 3 concentrations presented uniformly low concentrations between the surface and 50 m depth (0.1 µM) but reached 16 µM at depths of 200 m at daytime and night (Fig. 3A, B). Chlorophyll a concentrations were generally low (<0.2 mg m⁻³), with the highest value observed in the surface layer during daytime in Exp. I (Fig. 3C). The other vertical variations in chlorophyll a closely followed the fluorescence patterns (Fig. 3D). 3.2 Diel variations in growth and mortality Table 1. Initial conditions of the EXP. I and EXP. II. Temperature and salinity were measured in situ. Abundance of viruses (VIR), bacteria (BAC), Synechococcus spp. (SYN), Prochlorococcus spp. (PRO), photosynthetic picoeukaryotes (PPE) were measured from the experimental bottles. In four out of the twelve dilution experiments conducted in surface waters, a statistically significant negative correlation ( p < 0.05) was observed between the net growth rate and the degree of dilution within the 0.2 μm dilution series (see Fig. 4A, B, E, H). Moreover, irrespective of the 30 kDa dilution series, a significant negative correlation ( p < 0.05) between net growth rate and dilution factors was observed in two out of twelve dilution experiments conducted in surface waters (Fig. 4A, B). In Exp. I, the regression lines for the 30 kDa dilution series in surface waters were statistically significant for BAC and differed significantly from those of the 0.2 μm dilution series (p < 0.05) during daytime conditions (Fig. 4A). Conversely, no significant differences between the regression lines were detected during nighttime (Fig. 4G). Comparable findings were observed in SYN, where a significant correlation between dilution and net growth was detected exclusively for the 0.2 μm and 30 kDa dilution series during the daytime (Fig. 4B). Regarding PRO, all estimates of mg and mv yielded negative values, which can be attributed to the positive correlation observed between the net growth rate and the dilution level (see Fig. 4C, F, I, L). Within the DCM layer, a significant negative linear correlation between the net growth rate and the 0.2 μm dilution series was observed in six out of twelve analyses (Fig. 5D, E, F, G, J, K). In two instances, a significant regression was identified exclusively for the 30 kDa dilution series at the DCM layer (Fig. 5A, J). The growth rates of BAC in surface waters ranged from -0.01 to 0.18 h⁻¹, with no distinct diel variation observed (Table 2). The mean growth rate of BAC in surface waters was 0.09 h⁻¹ during the daytime and 0.02 h⁻¹ during the nighttime (Table 2). Within the DCM, the mean growth rate of BAC was observed to be 0.05 h⁻¹ during the daytime and 0.05 h⁻¹ during the nighttime, as detailed in Table 2. Moreover, SYN exhibited the highest growth rates during daytime, reaching 0.17 h⁻¹, while at the surface waters during nighttime, growth rates varied between 0.05 and 0.1 h⁻¹ (see Table 2). At the DCM, growth rates of SYN have similar values at daytime and nighttime, showing no distinct diel variation (Table 2). Moreover, the mean growth rate of PRO in surface waters was 0.04 h⁻¹ during the daytime and 0.07 h⁻¹ at nighttime (Table 2). A comparable pattern was observed at DCM, where PRO exhibited a higher growth rate at night, recorded at 0.07 h⁻¹ (Table 2). The mortality rate of BAC attributable to nanoflagellate grazing, as estimated from the 0.2 μm dilution series, was observed exclusively at the surface during daytime, with a grazing rate of 0.06 h⁻¹ (Table 2). Viral lysis emerged as the primary mechanism responsible for the removal of BAC in surface waters during daytime, exhibiting a higher rate of 0.09 h⁻¹ (Table 2). Regarding SYN, viral lysis was observed exclusively in surface waters during daytime, with a rate of 0.09 h⁻¹ (Table 2). In all other instances, this study did not detect a significant effect of viral lysis. Moreover, in certain instances, the grazing rates of SYN in both surface waters and DCM were considerable and statistically significant during daytime and nighttime (Table 2). As for PRO, in most cases (15 analyses), neither grazing nor viral lysis was detected. Table 2. Growth (μ), microzooplankton grazing (mg), and viral lysis rates (mv) for the bacteria (BAC), Synechococcus spp. (SYN), and Prochlorococcus spp. (PRO). 4 Discussion This research investigated the diel fluctuations in the growth rates of bacteria and picophytoplankton, as well as their losses attributable to nanoflagellate grazing and viral lysis, within the tropical South China Sea during the spring of 2025. The magnitude of losses attributable to viral lysis and nanoflagellate grazing exhibited considerable variability across different bacterial and picophytoplankton groups as well as over the course of daily time intervals. The primary finding of this study was the alteration in the regulatory mechanisms governing bacterial and picophytoplankton communities throughout the depth gradient. Our findings suggest that viral lysis constituted the primary mechanism of bacterial mortality in surface waters during daytime, while grazing was the dominant factor influencing bacterial mortality within DCM zone during nighttime. Moreover, nanoflagellate grazing exerts significant regulatory influence on SYN populations during both daytime and nighttime periods. This dynamic shift could have substantial implications for the fate and biogeochemical cycling of organic matter within the study area. 4.1 Methodological aspects The size fractionation for grazers (< 10 µm) was selected according to earlier research to exclude microzooplankton (Tsai et al. 2011 ). Trophic cascades may have occurred in the dilution grazing experiments, potentially leading to an overestimation of the effects of nanoflagellates on BAC or picophytoplankton in this study. For example, Calbet et al. ( 2008 ) observed that between March and June, the exclusion of the > 10 µm size fraction from incubation experiments resulted in a 20–100% increase in primary production by < 10 µm that was consumed by microbial grazers, suggesting the presence of a trophic cascade effect. Moreover, the interactions between viruses and grazers, as well as their impacts on picoplankton, are likely to be highly complex (Mike and Jacquet 2008) and may encompass a range of antagonistic and synergistic effects (Jacquet et al. 2007 ). For instance, nanoflagellates have the capacity to directly diminish viral abundance and infectivity either by consuming viruses themselves or by selectively grazing on cells infected by viruses (Bettarel et al. 2005 ). However, selective grazing was not evaluated in this study, so it remains unclear whether it took place during the dilution experiments and, if it did, whether it would lead to an underestimation of viral-induced bacterial mortality. One advantage of employing the dilution method, as opposed to alternative approaches for estimating viral effects on host mortality, is that it enables the direct quantification of the relative contributions of both grazing and viral lysis without requiring the application of conversion factors. For example, burst size and the proportion of visibly infected cells were quantified through transmission electron microscopy and subsequently transformed into the frequency of infected bacteria utilizing the equation presented by Weinbauer et al. ( 2002 ). However, in certain instances throughout this study, the dilution method was not effectively used to determine growth and mortality rates. The dilution method relies on three key assumptions, two of which are that plankton growth is exponential and unaffected by the dilution level (Landry and Hassett 1982 ). Consequently, plankton growth should not be constrained by nutrient availability or other environmental conditions. In this study, we found that BAC and picophytoplankton growth rates were similar or lower in the 30 kDa (free of grazers and viruses) series compared to the 0.2 µm (free of grazers) series (e.g., Fig. 4 F, H, K). Previous research has reported comparable observations wherein dilution with virus-free water led to a reduction in the growth rates of picophytoplankton, including SYN (Suttle et al. 1996 ; Kimmance et al. 2007 ). Other studies have also observed comparable reductions in apparent growth rate after dilution when filtered water was contaminated with substances that limit phytoplankton growth (Middelboe and Lyck 2002 ; Weinbauer et al. 2011 ; Tsai et al. 2018 ). Regarding SYN in surface waters, SYN growth rates were noticeably lower in treatments where viral abundance was decreased during the night (Fig. 4 H), indicating that active viruses promoted SYN growth. Our research indicates that diluting with virus-free water may have hindered nutrient recycling via viral lysis, and this absence of viruses adversely affected growth rates. This aligns with the findings of Weinbauer et al. ( 2011 ), who proposed that nutrient cycling driven by viral lysis of bacteria can regulate phytoplankton growth. This study aims to estimate the differences in growth and mortality of BAC and picophytoplankton between daytime and nighttime at various depths. Therefore, the duration of incubation employed in dilution experiments appears to be a crucial factor to consider. The length of the viral lytic cycle determines whether detectable cell lysis transpires within the incubation period (Evans et al. 2003 ; Jacquet et al. 2005 ). This suggests that a single cycle of infection can be identified, indicating that host cell lysis transpires later than 12 hours post-infection but within a 24-hour incubation period. Most research on algal host–virus model systems, including those involving prokaryotic algal hosts, demonstrates that the duration until cell lysis following viral infection typically occurs within 24 hours (Mann 2003 ). Evans et al. ( 2003 ) emphasize that since dilution experiments usually last 24 hours, the timing of the lytic cycle may correspond with that of the host growth rates. In the current study, viral lysis rates for SYN and PRO were generally not estimable during both daytime and nighttime periods. We propose that viral lysis rates may have been underestimated due to the incubation duration of approximately 8–9 hours employed in our experiments (see Table 2 ). 4.2 Nanoflagellate grazing and viral lysis Previous research has documented that daily maxima in bacterial production tend to occur either in the early morning or around midday, exhibiting a diel pattern that appears to be regulated by phytoplankton activity (Kuipers et al. 2000 ). Irregular fluctuations in production throughout the day have also been documented (Gasol et al. 1998 ). Regarding mortality, bacterial mortality rates have been observed to be significantly elevated during specific times of the day (Weisse 1999 ). This pattern may be attributed to variations in protozoan feeding rates influenced by light intensity (Chen and Chang 1999 ) or alterations in bacterial size affecting nanoflagellate grazing (González et al. 1990). Current understanding indicates that viral activity is modulated by host conditions associated with light–dark cycles. Furthermore, given that viruses are known to be susceptible to inactivation by ultraviolet (UV) radiation (Jacquet and Bratbak 2003 ), it is inferred that elevated rates of viral lysis and infectivity are more likely to occur during the late afternoon and nighttime periods, when free viral particles experience reduced exposure to UV radiation (Suttle 2000 ; Winter et al. 2004 ). Moreover, in the current study, viral lysis accounted for an average of 66.7% of bacterial mortality in both surface and deep chlorophyll maximum (DCM) waters during daytime experiments, as indicated by the ratios (0.06/0.09) × 100% and (0.04/0.06) × 100%, respectively. In contrast, viral lysis was not detected during nighttime conditions (see Table 2 ). Previous studies had demonstrated that bacterial mortality due to viral lysis frequently exhibits a diel pattern. Winter et al. ( 2004 ) reported that the abundance of virus-infected bacterial cells increases following the peak of bacterial activity observed at midday, with a subsequent rise in viral release occurring in the late afternoon in the North Sea. Moreover, Ho et al. ( 2021 ) conducted two diel dilution incubation experiments in a semi-enclosed coastal area of northeastern Taiwan and observed that bacterial mortality due to viral lysis was greater during daytime compared to nighttime. Given that viral lysis and nanoflagellate grazing exert distinct effects on the aquatic food web, it is essential to evaluate the relative significance of these two mortality factors. The fate of viral lysates in aquatic environments is determined by their ability to be assimilated by BAC. Unlike most of the ambient DOM present in seawater, DOM that is freshly released from lysed cells is readily labile and available for bacterial uptake (Middelboe and Jørgensen 2006 ). Under these conditions, viral lysis is expected to enhance bacterial activity, as evidenced by the observed elevated bacterial growth rates during daytime experiments conducted in the surface layer of oligotrophic waters (Table 2 ). Variations in the temporal and spatial significance of viruses as contributors to bacterial mortality, as demonstrated in multiple studies (e.g., Weinbauer et al. 1993 ; Guixa-Boixareu et al. 1996 ; Shiah et al. 2022 ), may substantially impact the role of bacterial-mediated organic carbon processing within pelagic marine ecosystems. Moreover, an additional explanation is that diel fluctuations in substrate availability, primarily driven by changes in phytoplankton production, may result in significant diel patterns of bacterial activity within the euphotic zone. Previous research has indicated that SYN predominantly inhabits the surface layers of the ocean, with growth rates generally observed to be lower at the depths corresponding to the DCM (Partensky et al. 1996 ; Liu et al. 1998 ). In contrast, PRO cells are found to extend into deeper aquatic zones, where they typically exhibit higher growth rates compared to SYN (Partensky et al. 1999). Our findings are consistent with these studies, showing that SYN growth was greater in surface waters compared to the DCM layer (Table 2 ). Furthermore, this study indicates that nanoflagellate grazing may be a significant cause of SYN loss in the oligotrophic waters of the tropical Pacific Ocean (Table 2 ). Regarding the mortality of SYN or PRO, cyanobacteria are present in comparatively high concentrations; however, infectious phages targeting SYN and PRO are observed at low abundances in offshore oligotrophic marine environments (Sullivan et al. 2003 ). Sullivan et al. ( 2003 ) even suggested that low cyanophage concentrations in regions with a high abundance of hosts appear to be typical characteristics of the open ocean. Other studies also indicated that the typically high genetic diversity within SYN and PRO populations, along with capacity of cyanobacteria to develop resistance to cyanophages (Scanlan and West 2002 ), might have contributed to diminishing the impact of cyanophages as causes of mortality. Moreover, grazing on PRO was significantly lower compared to SYN in surface waters (Table 2 ), suggesting that the two prokaryotic groups experienced different loss processes. Additionally, since no significant effects of viral lysis or nanoflagellate grazing on PRO were observed in surface waters, PRO showed a higher abundance than SYN in this study. 4.3 Diel variation of carbon production and losses Differentiating and measuring the losses of BAC and picophytoplankton caused by nanoflagellate grazing and viral lysis is crucial for a comprehensive understanding of the carbon cycle in marine ecosystems. In assessing the interactions among BAC, picophytoplankton, VIR, and nanoflagellates and their influence on energy transfer within microbial food webs, this study concentrated on the relationships between BAC and picophytoplankton growth, grazing, viral lysis, and the associated carbon flux. In this context, the rates of production (BP, SP, PP), grazing (BG, SG, PG), and viral lysis (BL, SL, PL) for BAC, SYN, and PRO, expressed in µg C L⁻¹ h⁻¹, were determined by applying carbon conversion factors of 20, 46, and 213 fg C cell⁻¹ to BAC, PRO, and SYN, respectively, as established by Lee and Fuhrman (1987) and Bertilsson et al. ( 2003 ). According to the estimates, the combined carbon losses of BAC caused by viral lysis and nanoflagellate grazing (0.40 and 0.20 µg C L –1 h –1 , respectively) collectively accounted for an average of 100% of BP (0.60 µg C L –1 h –1 ) at surface water during daylight hours (Fig. 6 ). Regarding the DCM layer, viral lysis was determined to be the primary cause of BAC mortality during daytime experiments, seemingly accounting for the removal of approximately 79% of BP (Fig. 6 ). Our results indicate that nanoflagellate grazing exerted a significant influence on SYN populations during both daytime and nighttime experiments conducted at the surface and DCM layers (Fig. 6 ). Specifically, carbon losses from SYN attributable to nanoflagellate grazing were approximately 0.06 and 0.04 µgC L⁻¹ h⁻¹ during the day and night, respectively, accounting for 55% and 33% of the total SYN production (SP) in these periods (Fig. 6 ). Our findings strongly indicate that nanoflagellate grazing was the primary biological factor controlling daily fluctuations in SYN abundance. Moreover, when considering the relative importance of food sources for nanoflagellates, the results further imply that BAC play a significant role in transferring carbon to higher trophic levels in the oligotrophic waters of the SCS (Fig. 6 ). 5 Conclusion In summary, our research makes an important contribution to understanding how depth and daily changes influence the interaction of key factors regulating BAC and picophytoplankton abundance in the South China Sea. Our findings demonstrate that both bottom-up and top-down controls work together to regulate the populations of all studied groups. The measured overall growth and mortality rates could provide useful data for ocean models that include microbial carbon fluxes in the South China Sea. Declarations Acknowledgements We appreciate the language editing and helpful comments related to this manuscript from Choice Language Service. Author contributions CAN: Formal analysis, Investigation, Methodology, Writing – review & editing. FKS: Resources, Writing – review & editing. PWYC: Formal analysis, Investigation, Methodology. MO: Formal analysis, Investigation, Methodology. TYC: Investigation, Writing – review & editing. A-YT: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Validation, Writing – original draft, Writing – review & editing. Funding This research was supported by the National Science and Technology Council, ROC (Taiwan), grant number NSTC 114-2740-M-001-003 - Competing interests The authors declare no conflict of interest References Baudoux AC, Veldhuis MJW, Noordeloos AAM, Van Noort G, Brussaard CPD (2008) Estimates of virus-vs. grazing induced mortality of picophytoplankton in the North Sea during summer. 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Aquat Microb Ecol 30:207-219. http://dx.doi.org/10.3354/ame030207 Evans C, Brussaard CP (2012) Viral lysis and microzooplankton grazing of phytoplankton throughout the Southern Ocean. Limnol Oceanogr 57 1826-1837. https://doi.org/10.4319/lo.2012.57.6.1826 Gasol JM, Doval MD, Pinhassi J, Calderón-Paz JI, Guixa-Boixareu N, Vaqué D, Pedrós-Alió C (1998) Diel variations in bacterial heterotrophic activity and growth in the northwestern Mediterranean Sea. Mar Ecol Prog Ser 164:107-124. https://doi.org/10.3354/meps164107 Gong GC, Liu KK, Pai SC (1995) Prediction of nitrate concentration from two end member mixing in the southern East China Sea. Cont Shelf Res 15:827-842. https://doi.org/10.1016/0278-4343(94)00039-P Gonzalez JM, Sherr EB, Sherr BF (1990) Size-selective grazing on bacteria by natural assemblages of estuarine flagellates and ciliates. Appl Environ Microbiol 56:583-589. https://doi.org/10.1128/aem.56.3.583-589.1990 Guixa-Boixareu N, Calderón-Paz JI, Heldal M, Bratbak G, Pedrós-Alió C (1996) Viral lysis and bacterivory as prokaryotic loss factors along a salinity gradient. Aquat Microb Ecol 11:215–227. https://doi.org/10.3354/ame011215 Ho PC, Gong GC, Hsieh CH, Chen PWY, Tsai AY (2021) Diel variation of viral production in a coastal subtropical marine system. Diversity, 13:426. https://doi.org/10.3390/d13090426 Jacquet S, Bratbak G (2003) Effects of ultraviolet radiation on marine virus–phytoplankton interactions. FEMS Microbiol Ecol 44:279–289. https://doi.org/10.1016/S0168-6496(03)00075-8 Jacquet S, Domaizon I, Personnic S, Ram ASP, Hedal M, Duhamel S, Sime‐Ngando T. (2005) Estimates of protozoan‐and viral‐mediated mortality of bacterioplankton in Lake Bourget (France). Freshw Biol 50:627-645. https://doi.org/10.1111/j.1365-2427.2005.01349.x Jacquet S, Domaizon I, Personnic S, Sime-Ngando T (2007) Do small grazers influence virus-induced mortality of bacteria in Lake Bourget (France)?. Fundam Appl Limnol 170:125-132. DOI: 10.1127/1863-9135/2007/0170-0125 Jeffrey WH, Pledger RJ, Aas P, Hager S, Coffin RB, Von Haven R, Mitchell D L (1996) Diel and depth profiles of DNA photodamage in bacterioplankton exposed to ambient solar ultraviolet radiation. Mar Ecol Prog Ser 137: 283-291. https://doi.org/10.3354/meps137283 Kimmance SA, Wilson WH, Archer SD (2007) Modified dilution technique to estimate viral virus grazing mortality of phytoplankton: limitations associated with method sensitivity in natural waters. Aquat Microb Ecol 49:207–222. https://doi.org/10.3354/ame01136 Kuipers B, Van Noort GJ, Vosjan J, Herndl GJ (2000) Diel periodicity of bacterioplankton in the euphotic zone of the subtropical Atlantic Ocean. Mar Ecol Prog Ser 201:13-25. https://doi.org/10.3354/meps201013 Landry MR, Hassett RP (1982) Estimating the grazing impact of marine micro-zooplankton. Mar Biol 67:283-288. http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=PASCAL82X0333678 Lee S, Furhman JA (1987) Relationship between bio-volume and biomass of naturally derived marine bacterio-plankton. Appl Environ Microbiol 53:1298-1303. https://doi.org/10.1128/aem.53.6.1298-1303.1987 Legendre L, Rassoulzadegan F (1995) Plankton and nutrient dynamics in marine waters. Ophelia 41:153-172. https://doi.org/10.1080/00785236.1995.10422042 Li WKW, Dickie PM, Irwin BD, Wood AM (1992) Biomass of bacteria, cyanobacteria, prochlorophytes and photosynthetic eukaryotes in the Sargasso Sea. Deep-Sea Res 39:501–519. https://doi.org/10.1016/0198-0149(92)90085-8 Liu H, Campbell L, Landry MR, Nolla HA, Brown SL, Constantinou J (1998) Prochlorococcus and Synechococcus growth rates and contributions to production in the Arabian Sea during the 1995 Southwest and Northeast Monsoons. Deep-Sea Res. II: Top Stud Oceanogr 45:2327-2352. https://doi.org/10.1016/S0967-0645(98)00073-3 Liu H, Chang J, Tseng C-M, Wen L-S, Liu KK (2007) Seasonal variability of picoplankton in the Northern South China Sea at the SEATS station. Deep-Sea Res. II: Top Stud Oceanogr 54:1602–1616. https://doi.org/10.1016/j.dsr2.2007.05.004 Mann NH (2003) Phages of the marine cyanobacterialpicophytoplankton. FEMS Microbiol Rev 27:17–34. https://doi.org/10.1016/S0168-6445(03)00016-0 Middelboe M, Jørgensen NO (2006) Viral lysis of bacteria: an important source of dissolved amino acids and cell wall compounds. Journal of the Mar Biol Assoc UK 86:605-612. https://doi.org/10.1017/S0025315406013518 Middelboe M, Lyck PG (2002) Regeneration of dissolved organic matter by viral lysis in marine microbial communities. Aquat Microb Ecol 27:187-194. https://doi.org/10.3354/ame027187 Miki T, Jacquet S (2008) Complex interactions in the microbial world: underexplored key links between viruses, bacteria and protozoan grazers in aquatic environments. Aquat Microb Ecol 51:195-208. https://doi.org/10.3354/ame01190 Ning X, Li WKW, Cai Y, Shi J (2005) Comparative analysis of bacterioplankton and phytoplankton in three ecological provinces of the northern South China Sea. Mar Ecol Prog Ser 293:17–28. https://doi.org/10.3354/meps293017 Partensky F, Blanchot J, Lantoine F, Neveux J, Marie D (1996) Vertical structure of picophytoplankton at different trophic sites of the tropical northeastern Atlantic Ocean. Deep-Sea Res I: Oceanogr Res Pap 43:1191-1213. https://doi.org/10.1016/0967-0637(96)00056-8 Pasulka AL, Samo TJ, Landry MR (2015) Grazer and viral impacts on microbial growth and mortality in the southern California Current Ecosystem. J Plankton Res 37:320-336. https://doi.org/10.1093/plankt/fbv011 Patten NL, van Ruth PD, Rodriguez AR (2018) Spatial variability in picophytoplankton, bacteria and viruses in waters of the Great Australian Bight (southern Australia). Deep-Sea Res. II: Top Stud Oceanogr 157:46-57. https://doi.org/10.1016/j.dsr2.2018.04.009 Scanlan DJ, West NJ (2002) Molecular ecology of the marine cyanobacterial genera Prochlorococcus and Synechococcus. FEMS Microbiol Ecol 40: 1-12. https://doi.org/10.1111/j.1574-6941.2002.tb00930.x Shiah FK, Lai CC, Chen TY, Ko CY, Tai JH, Chang CW (2022) Viral shunt in tropical oligotrophic ocean. Science Advances, 8:eabo2829. DOI: 10.1126/sciadv.abo2829 Staniewski MA, Short SM (2018) Methodological review and meta-analysis of dilution assays for estimates of virusand grazer-mediated phytoplankton mortality. Limnol Oceanogr Methods 16:649– 668. https://doi.org/10.1002/lom3.10273 Sullivan MB, Waterbury JB, Chisholm SW (2003) Cyanophages infecting the oceanic cyanobacterium Prochlorococcus. Nature 424:1047-1051. Suttle CA (2000) The ecological, evolutionary and geochemical consequences of viral infection of cyanobacteria and eukaryotic algae. In Viral Ecology. Hurst, C.J. (ed.). London, UK: Academic Press, 248–286. Suttle CA, Chan AM, Rodda KM, Short SM, Weinbauer MG, Garza DR, Wilhelm SW (1996) The effect of cyanophages on Synechococcus spp. during a bloom in the western Gulf of Mexico. EOS J Immunol Immunofarmacol 76:OS207–OS208. Tsai AY, Gong GC, Sanders RW, Chen WH, Chao CF, Chiang KP (2011) Importance of bacterivory by pigmented and heterotrophic nanoflagellates during the warm season in a subtropical western Pacific coastal ecosystem. Aquat Microb Ecol 63:9-18. https://doi.org/10.3354/ame01470 Tsai AY, Gong GC, Hung J (2013) Seasonal variations of virus-and nanoflagellate-mediated mortality of heterotrophic bacteria in the coastal ecosystem of subtropical western Pacific. Biogeosciences 10:3055-3065. https://doi.org/10.5194/bg-10-3055-2013 Tsai AY, Gong GC, Chao CF (2016) Contribution of viral lysis and nanoflagellate grazing to bacterial mortality at surface waters and deeper depths in the coastal ecosystem of subtropical Western Pacific. Estuar Coast 39:1357-1366. DOI 10.1007/s12237-016-0098-9 Tsai AY, Gong GC, Chung CC, Huang YT (2018) Different impact of nanoflagellate grazing and viral lysis on Synechococcus spp. and picoeukaryotic mortality in coastal waters. Estuar Coast Shelf Sci 209:1-6. https://doi.org/10.1016/j.ecss.2018.05.012 Wang F, Guo S, Liang J, Sun X (2023) Water column stratification governs picophytoplankton community structure in the oligotrophic eastern Indian ocean. Mar Environ Res 189:106074. https://doi.org/10.1016/j.marenvres.2023.106074 Wei Y, Huang D, Zhang G, Zhao Y, Sun J (2020) Biogeographic variations of picophytoplankton in three contrasting seas: the Bay of Bengal, South China Sea and Western Pacific Ocean. Aquat Microb Ecol 84:91-103. https://doi.org/10.3354/ame01928 Weinbauer MG, Fuks D, Peduzzi P (1993) Distribution of viruses and dissolved DNA along a coastal trophic gradient in the northern Adriatic Sea. Appl Environ Microbiol 59:4074–4082. https://doi.org/10.1128/aem.59.12.4074-4082.1993 Weinbauer MG, Winter C, Höfle MG (2002) Reconsidering transmission electron microscopy based estimates of viral infection of bacterio-plankton using conversion factors derived from natural communities. Aquat Microb Ecol 27:103-110. https://doi.org/10.3354/ame027103 Weinbauer MG, Bonilla-Findji O, Chan AM, Dolan JR, Short SM, Šimek K, et al. (2011) Synechococcus growth in the ocean may depend on the lysis of heterotrophic bacteria. J Plankton Res 33:1465-1476. https://doi.org/10.1093/plankt/fbr041 Weisse T (1999) Bactivory in the north-western Indian Ocean dur-ing the intermonsoon-northeastern monsoon period. Deep-SeaRes II 46:795–814. https://doi.org/10.1016/S0967-0645(98)00128-3 Winter C, Herndl GJ, Weinbauer MG (2004) Diel cycles in viral infection of bacterioplankton in the North Sea. Aquat Microb Ecol 35:207–216. https://doi.org/10.3354/ame035207 Wong GTF, Ku TL, Mulholland M, Tseng CM, Wang DP (2007) The South East Asian time-series study (SEATS) and the biogeochemistry of the South China Sea – An overview. Deep-Sea Res. II 54:1434–1447. https://doi.org/10.1016/j.dsr2.2007.05.012 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7350023","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":505569489,"identity":"4febdccb-51a0-4be7-a9ae-5e2af518279a","order_by":0,"name":"Clara Natalie Annabel","email":"","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Clara","middleName":"Natalie","lastName":"Annabel","suffix":""},{"id":505569490,"identity":"67402528-bc75-4ea5-acfc-220608b5d75a","order_by":1,"name":"Fuh-Kwo Shiah","email":"","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Fuh-Kwo","middleName":"","lastName":"Shiah","suffix":""},{"id":505569494,"identity":"c32111d4-94b3-4af1-b7f3-b3008d7ea2d8","order_by":2,"name":"Patrichka Wei-Yi Chen","email":"","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Patrichka","middleName":"Wei-Yi","lastName":"Chen","suffix":""},{"id":505569495,"identity":"3c554e1c-bde1-483f-a858-a2a049188a18","order_by":3,"name":"Madeline Olivia","email":"","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Madeline","middleName":"","lastName":"Olivia","suffix":""},{"id":505569498,"identity":"1e58d4da-9308-4435-a24b-e38d0e798ca0","order_by":4,"name":"Tzong-Yueh Chen","email":"","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Tzong-Yueh","middleName":"","lastName":"Chen","suffix":""},{"id":505569499,"identity":"5bd2858a-0b08-42f0-8fe7-d00489595a42","order_by":5,"name":"An-Yi Tsai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYJCCA0DMww9iPIAJ8RDSAtTDI9kAZCQwMEjAtEgQtMYARBClhX92j+HhD3/sZIyvHX4ItOVOHb9EAuODt20MdWBDsACJO2cMDhxsS+Yxu51mANTyTEJyRgKz4dw2BglcWhhu5AC1NDADtSSAtByWMLiRwCbNC9RihkOLPEjLgT/1PMaz0z/AtLD/xqfFAKyF7TCPgXQOwhZmfFoMb6QVHDjbdpxH4nZOwYEEg8OSM3seNkvOOSchuR+HFrkbyZs/VPyptuefnb75w4eKw/z87MkHP7wps+EHxRR2wGGA7E4QwQhSiy8m2R/gkRwFo2AUjIJRAAQANghhuBENNv8AAAAASUVORK5CYII=","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":true,"prefix":"","firstName":"An-Yi","middleName":"","lastName":"Tsai","suffix":""}],"badges":[],"createdAt":"2025-08-12 00:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7350023/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7350023/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90103855,"identity":"68a73d78-5ee5-4686-975c-39b157559234","added_by":"auto","created_at":"2025-08-28 13:44:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114185,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the sampling station (SEATs station) where modified dilution experiments were performed.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/f2e1d53524451be156cbfffb.png"},{"id":90104277,"identity":"38575852-3f49-4918-b858-12d46ed13c51","added_by":"auto","created_at":"2025-08-28 13:52:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":115243,"visible":true,"origin":"","legend":"\u003cp\u003eVertical distribution of temperature, salinity and fluorescence of SEATs station in April. The red line denotes the daytime samples, while the black line indicates the nighttime samples. The dynamics of environmental factors in Exp. I are illustrated in panels A, C, and E, whereas those in Exp. II are presented in panels B, D, and F.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/4eb27be24c8cd6b18177e457.png"},{"id":90103857,"identity":"9c196b80-5d46-46d4-a5ae-84c1b1f4c17d","added_by":"auto","created_at":"2025-08-28 13:44:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72122,"visible":true,"origin":"","legend":"\u003cp\u003eVertical distribution of NO\u003csub\u003e3\u003c/sub\u003e (µM) and Chl \u003cem\u003ea\u003c/em\u003e (mg m\u003csup\u003e-3\u003c/sup\u003e) concentrations of SEATs station in April. The red line denotes the daytime samples, while the black line indicates the nighttime samples. The dynamics of environmental factors in Exp. I are illustrated in panels A and C, whereas those in Exp. II are presented in panels B and D.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/1568379131984bc4c1830c6d.png"},{"id":90105006,"identity":"418d1678-3397-4901-a2a7-6ede880a6db1","added_by":"auto","created_at":"2025-08-28 14:00:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":153176,"visible":true,"origin":"","legend":"\u003cp\u003eDilution plots of net BAC, SYN, and PRO growth rate (h\u003csup\u003e−1\u003c/sup\u003e) versus the seawater fraction in parallel experiments were performed at surface waters. Open squares and closed squares represent growth rates from the 30 kDa and 0.2 μm dilution series, respectively. Plots A, B, C, D, E and F represent results from daytime experiments and G, H, I, J, K and L for nighttime experiments in EXP. I and EXP. II, respectively.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/0958bfe9ff7a3175176e2dd5.png"},{"id":90103865,"identity":"7a2a3df9-4686-4de4-aba6-40972bd4f522","added_by":"auto","created_at":"2025-08-28 13:44:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":164476,"visible":true,"origin":"","legend":"\u003cp\u003eDilution plots of net BAC, SYN, and PRO growth rate (h\u003csup\u003e−1\u003c/sup\u003e) versus the seawater fraction in parallel experiments were performed at DCM. Open squares and closed squares represent growth rates from the 30 kDa and 0.2 μm dilution series, respectively. Plots A, B, C, D, E and F represent results from daytime experiments and G, H, I, J, K and L for nighttime experiments in EXP. I and EXP. II, respectively.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/b4d6322d3af7574c1a7a57f8.png"},{"id":90104278,"identity":"fc211951-2eeb-4d2f-aa39-7e1137009125","added_by":"auto","created_at":"2025-08-28 13:52:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":145501,"visible":true,"origin":"","legend":"\u003cp\u003eHourly bacterial, \u003cem\u003eSynechococcus\u003c/em\u003e spp. and \u003cem\u003eProchlorococcus\u003c/em\u003espp. carbon production (BP, SP, PP) and the carbon consumed by nanoflagellates (BG, SG, PG) and viruses (BL, SL, PL) was calculated for each experiment at surface (above) and DCM layer (below). Unit: µg C L-1 h-1. White and gray box represent daytime and nighttime of microbial biomass (µg C L-1), respectively.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/ce3127473b2559f47b0e34d4.png"},{"id":97135362,"identity":"1b5e39e4-a0fc-4dee-a4a1-c8d216108a63","added_by":"auto","created_at":"2025-12-01 09:39:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1367758,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7350023/v1/a3e36399-134b-4ded-bd37-0dd378e27c4f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diel dynamics of bacterial and picophytoplankton growth, grazing and viral lysis at different depths in the tropical South China Sea in spring","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe picophytoplankton (\u0026lt;\u0026thinsp;2 \u0026micro;m) dominate phytoplankton abundance and biomass in oligotrophic ocean and play a major role in the dynamics of the food webs (Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Legendre and Rassoulzadegan \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Patten et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Among the picophytoplankton, \u003cem\u003eProchlorococcus\u003c/em\u003e (PRO) typically dominates the picophytoplankton in offshore oligotrophic oceanic waters (between latitudes 40\u0026deg;N and 40\u0026deg;S). A wider geographic distribution than PRO has been reported for \u003cem\u003eSynechococcus\u003c/em\u003e spp. (SYN), which can be found in oligotrophic through to mesotrophic ecosystems and in tropical as well as polar waters. A significant amount of primary production is attributed to PRO and SYN in oligotrophic oceanic systems (Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), and these populations are considered vital components of marine pelagic food webs. Despite considerable information on their distribution, abundance, and biology (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wei et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), little is known about the factors governing their populations, such as biological factors and environmental factors. Particularly, in the open ocean, the relative importance of grazing versus viral lysis controls remains poorly documented (Baudoux et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Evans and Brussaard \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pasulka et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Tsai et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). A variety of factors influence the dynamics of picophytoplankton in aquatic ecosystems, including trophic levels, temperature, nutrient limitations, and light limitations, but they are also regulated by grazing and viral lysis. Furthermore, it remains unclear how grazing versus viral lysis controls different picophytoplankton groups during a diel variation.\u003c/p\u003e\u003cp\u003ePrimary producers must respond to changes in the availability of light during the day. Diel cycles of bacterial activity therefore suggest that dissolved organic matter (DOM) is produced by photosynthetic processes and consumed by bacteria (BAC) (Gasol et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). It is not only possible to observe variations in bacterial production over a seasonal period, but also on a diel scale in the surface layer of the ocean. The short-term variations between production of BAC and DOM are more intense in oligotrophic environments, where substrate supply is limited, and we may expect tightly coupled covariation between the two processes (Gasol et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Furthermore, the diel patterns of bacterial activity, however, may also be affected by other factors varying daily, including ultraviolet radiation (Jeffrey et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), grazing (Connell et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and viral lysis (Ho et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThere is no doubt that the South China Sea (SCS) is one of the world's largest marginal seas, which is characterized by warm and oligotrophic conditions, like other subtropical oceans. Despite the large amount of nutrients supplied by several large rivers, including Pearl River and Mekong River, the upper water column of SCS is often stratified and remains oligotrophic, particularly during summer, which limits primary production due to inorganic nutrients (Wong et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In the SCS, the East Asian monsoon controls most of the changes in the atmosphere and upper ocean. The equatorial and central Pacific monsoons closely follow the climatic variations in these regions. Additionally, typhoons and strong internal waves frequently pass through SCS. The magnitude of vertical mixing and the stability of the water column could be affected by all these physical disturbances on different time and spatial scales. Thus, the SCS is an excellent location for observing how the oceanic ecosystem responds to climate change across different time frames, ranging from short-term events to seasonal, yearly, and decade-long periods. According to the consensus mentioned above, scientists in Taiwan (Republic of China) established the Southeast Asia Time-series Station (SEATs) in 1999, located at 18\u0026deg;N, 116\u0026deg;E in the SCS. Previous research has demonstrated that picophytoplankton constitute the majority of phytoplankton biomass and primary production in the central South China Sea (Ning et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Due to its warm, oligotrophic conditions and the dominance of picoplankton in this region, it is expected that the microbial loop serves as the principal pathway for carbon cycling and energy transfer. This study presents a flow cytometric analysis of picoplankton collected from the SEATs site, alongside two diel surveys conducted in April 2025 to assess picoplankton abundance and associated environmental variables across varying depths. Utilizing these sampling methodologies, we characterized the vertical distribution and diel variability of picoplankton populations. Furthermore, we investigated diel fluctuations in growth and mortality rates, including grazing and viral infection, affecting both BAC and picophytoplankton within the surface and deep chlorophyll maximum (DCM) layers of the tropical SCS. We hypothesized that growth and mortality rates of BAC and picophytoplankton exhibit diel variations between the surface and DCM layers.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study sites, sampling and measurement of physic-chemical parameters\u003c/h2\u003e\u003cp\u003eSamples were collected at the SEATs station (18\u0026deg;N, 116\u0026deg;E) in the SCS during a cruise from April 26 to May 5, 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Seawater samples were obtained from different depths within the upper 200 meters of the water column using Go-Flo bottles connected to a CTD rosette system. A CTD profiler was employed to assess the vertical distribution of temperature, salinity, conductivity, fluorescence, turbidity, and dissolved oxygen. Fluorescence measurements obtained from the CTD facilitated the characterization of the DCM structure throughout the water column. Based on this characterization, samples were collected at the surface (fixed at a depth of 5 meters) and at the DCM depth, for use in the modified dilution experiment. Seawater samples (1 mL, collected in triplicate) from each depth were preserved using glutaraldehyde at a final concentration of 0.5% for the subsequent analysis of BAC, picophytoplankton, and viruses (VIR). The samples were incubated in the dark for 15 minutes, rapidly frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis (Brussaard \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Quantification of picophytoplankton, BAC, and VIR was performed using flow cytometry. Nutrients and Chl \u003cem\u003ea\u003c/em\u003e were measured as described by Gong et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Calculation of BAC, SYN and PRO growth and mortality rates\u003c/h2\u003e\u003cp\u003eOne limitation of the dilution method is that the starting cell concentration needs to be high enough to permit a three- to fourfold dilution while still retaining enough cells for precise counting. In the current cruise, the cell densities of picoeukaryotes (PPE) in surface and DCM waters were very low (\u0026lt;\u0026thinsp;0.5 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), failing to meet this requirement. Consequently, the current investigation was limited to examining the growth and mortality of BAC, SYN, and PRO. The objective was to assess the variations between daytime and nighttime in prokaryotic growth and mortality resulting from grazing and viral infection in both surface and DCM waters throughout the study period. To accomplish this, we took water samples at 0600 and 1800 a day on 29 April (EXP. I) and 30 April (EXP. II), and determined the growth, grazing, and viral lysis rates of BAC, SYN, and PRO using the modified dilution method (Evans et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInitially, the subsamples from the incubated 5 L bottles were filtered through a 10 \u0026micro;m mesh, followed by filtration using 47 mm Nuclepore polycarbonate filters with a pore size of 0.2 \u0026micro;m, in order to prepare the 'standard' diluent. The size fractionation method employed for grazers (\u0026lt;\u0026thinsp;10 \u0026micro;m) was specifically chosen to exclude ciliates while preserving nanoflagellates (Tsai et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). A filtered seawater sample (\u0026lt;\u0026thinsp;10 \u0026micro;m) was diluted with 0.2 \u0026micro;m filtered seawater in a 4-point dilution series, resulting in final concentrations of 25%, 50%, 75%, and 100% of the original seawater (\u0026lt;\u0026thinsp;10 \u0026micro;m). In dilution experiments, the diluent is generally filtered using filters with a pore size of 0.2 \u0026micro;m, permitting the passage of nearly all free viral particles. Furthermore, an alternative dilution series was performed in which both grazing and viral mortality were evaluated employing seawater filtered through a 30 kDa membrane, rather than the standard 0.2 \u0026micro;m filtration.\u003c/p\u003e\u003cp\u003eThe net growth rates (Net \u0026micro;, h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e) for BAC, SYN, and PRO were determined using Equation: Net \u0026micro;\u0026thinsp;=\u0026thinsp;ln (Nt2/Nt1)/(t2-t1)\u003c/p\u003e\u003cp\u003eHere, Nt1 and Nt2 denote the initial and final cell abundances in the experiment (cells ml⁻\u0026sup1;), respectively, while t1 and t2 represent the starting and ending time points of the experimental duration (hour). Incubations were conducted on the deck in triplicate using 50-mL polycarbonate incubation tubes, maintained at in situ temperatures for a duration of 8 to 9 hours during both daytime and nighttime periods. A neutral-density plastic sheet (Lee Filters, Hampshire, UK) was employed to cover the seawater surface, and DCM was incubated under ambient light conditions to replicate the light intensity corresponding to the sampling depth.\u003c/p\u003e\u003cp\u003eSpecific growth rates (\u0026micro;, d⁻\u0026sup1;) were determined as the y-intercept obtained from a simplified linear regression analysis of net growth rate plotted against the dilution factor of 30 kDa filtered seawater. The slope derived from the regression equation of the 0.2 \u0026micro;m dilution series corresponded to the grazing rate (mg), whereas the slope obtained from the 30 kDa dilution series represented the combined rates of grazing and viral lysis (mg\u0026thinsp;+\u0026thinsp;mv). The significance of each regression analysis was assessed to determine whether the slopes differed significantly from zero (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In cases where the regression analysis of the 0.2 \u0026micro;m dilution series did not yield statistically significant results, the value of mg was assigned as 0. Moreover, an F-test was conducted to evaluate the statistical significance of the differences observed between the regression models derived from each experiment (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The computations of mv were conducted in accordance with the criteria outlined by Staniewski and Short (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e(1) In the case where both regression analyses yielded statistically significant results and were found to differ significantly from one another, the relationship can be expressed as: mv = (mg\u0026thinsp;+\u0026thinsp;mv) \u0026ndash; mg. (2) if both regressions were significant but not significantly different from each other: mv\u0026thinsp;=\u0026thinsp;0; (3) if both regressions were not significant: mv\u0026thinsp;=\u0026thinsp;0;\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Flow cytometric analysis\u003c/h2\u003e\u003cp\u003eFlow cytometry (FCM) analysis was performed utilizing a BD FACSCalibur\u0026trade; instrument to detect and quantify the abundance of picoplankton groups, including BAC, SYN, PRO, and PPE. FCM was performed on triplicates of bacteria by thawing, diluting 1:10 in 0.2 \u0026micro;m filtered TE buffer (10 mM Tris, 1 mM EDTA), staining with SYBR Green I (1:500 dilution; Molecular Probes) at 80\u0026deg;C for 10 min (Brussaard \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). A phosphate-buffered saline (PBS) solution served as the sheath fluid, and forward-angle light scatter (FSC), side-angle light scatter (SSC), and green fluorescence (SYBR Green-I) were recorded for each sample. SYN, PRO, and PPE were identified based on pigment autofluorescence and FSC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\u003cp\u003eA least-squares regression analysis was performed to investigate the relationship between the net growth rates of BAC and picophytoplankton and the fractions derived from 30 kDa or 0.2 \u0026micro;m dilution series. The analysis of variance (ANOVA) conducted on the regression lines confirmed their statistical significance. Furthermore, an F-test was conducted to evaluate the statistical significance of the slope between the 0.2\u0026micro;m and the 30 kDa dilution series. All statistical analyses were conducted utilizing STATISTICA version 7.0 software. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was regarded as indicative of statistical significance.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Study site environmental characteristics and microbial abundance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 2 presents the main vertical dynamics of the physicochemical and biological characteristics observed at the stations sampled during this cruise. During the sampling period, seawater temperatures in the upper approximately 10 m of the water column consistently exceeded 25\u0026deg;C, with marginally lower temperatures observed during daytime compared to nighttime (Fig. 2A, B). Salinity exhibited a pattern analogous to that of temperature, characterized by a marginally lower salinity level (approximately 33.5 psu), which decreased by approximately 0.5 psu within the upper ~10 m of the water column during nighttime (Fig. 2C, D). At the SEATS site, the deep chlorophyll a maximum (DCM) demonstrated distinct diel oscillations, occurring at depths of 75 m during the daytime and 64 m at nighttime in Exp. I (Fig. 2E). In Exp. II, the DCM was detected at 54 m during the daytime and at 74 m during the nighttime (Fig. 2F). \u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e concentrations presented uniformly low concentrations between the surface and 50 m depth (0.1 \u0026micro;M) but reached 16 \u0026micro;M at depths of 200 m at daytime and night (Fig. 3A, B). Chlorophyll \u003cem\u003ea\u003c/em\u003e concentrations were generally low (\u0026lt;0.2 mg m⁻\u0026sup3;), with the highest value observed in the surface layer during daytime in Exp. I (Fig. 3C). The other vertical variations in chlorophyll \u003cem\u003ea\u0026nbsp;\u003c/em\u003eclosely followed the fluorescence patterns (Fig. 3D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Diel variations in growth and mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1. Initial conditions of the EXP. I and EXP. II. Temperature and salinity were measured in situ. Abundance of viruses (VIR), bacteria (BAC), \u003cem\u003eSynechococcus\u0026nbsp;\u003c/em\u003espp. (SYN), \u003cem\u003eProchlorococcus\u0026nbsp;\u003c/em\u003espp. (PRO), photosynthetic picoeukaryotes (PPE) were measured from the experimental bottles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"746\" height=\"336\"\u003e\u003c/p\u003e\n\u003cp\u003eIn four out of the twelve dilution experiments conducted in surface waters, a statistically significant negative correlation (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) was observed between the net growth rate and the degree of dilution within the 0.2 \u0026mu;m dilution series (see Fig. 4A, B, E, H). Moreover, irrespective of the 30 kDa dilution series, a significant negative correlation (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) between net growth rate and dilution factors was observed in two out of twelve dilution experiments conducted in surface waters (Fig. 4A, B). In Exp. I, the regression lines for the 30 kDa dilution series in surface waters were statistically significant for BAC and differed significantly from those of the 0.2 \u0026mu;m dilution series (p \u0026lt; 0.05) during daytime conditions (Fig. 4A). Conversely, no significant differences between the regression lines were detected during nighttime (Fig. 4G). Comparable findings were observed in SYN, where a significant correlation between dilution and net growth was detected exclusively for the 0.2 \u0026mu;m and 30 kDa dilution series during the daytime (Fig. 4B). Regarding PRO, all estimates of mg and mv yielded negative values, which can be attributed to the positive correlation observed between the net growth rate and the dilution level (see Fig. 4C, F, I, L).\u003c/p\u003e\n\u003cp\u003eWithin the DCM layer, a significant negative linear correlation between the net growth rate and the 0.2 \u0026mu;m dilution series was observed in six out of twelve analyses (Fig. 5D, E, F, G, J, K). In two instances, a significant regression was identified exclusively for the 30 kDa dilution series at the DCM layer (Fig. 5A, J).\u003c/p\u003e\n\u003cp\u003eThe growth rates of BAC in surface waters ranged from -0.01 to 0.18 h⁻\u0026sup1;, with no distinct diel variation observed (Table 2). The mean growth rate of BAC in surface waters was 0.09 h⁻\u0026sup1; during the daytime and 0.02 h⁻\u0026sup1; during the nighttime (Table 2). Within the DCM, the mean growth rate of BAC was observed to be 0.05 h⁻\u0026sup1; during the daytime and 0.05 h⁻\u0026sup1; during the nighttime, as detailed in Table 2. Moreover, SYN exhibited the highest growth rates during daytime, reaching 0.17 h⁻\u0026sup1;, while at the surface waters during nighttime, growth rates varied between 0.05 and 0.1 h⁻\u0026sup1; (see Table 2). At the DCM, growth rates of SYN have similar values at daytime and nighttime, showing no distinct diel variation (Table 2). Moreover, the mean growth rate of PRO in surface waters was 0.04 h⁻\u0026sup1; during the daytime and 0.07 h⁻\u0026sup1; at nighttime (Table 2). A comparable pattern was observed at DCM, where PRO exhibited a higher growth rate at night, recorded at 0.07 h⁻\u0026sup1; (Table 2).\u003c/p\u003e\n\u003cp\u003eThe mortality rate of BAC attributable to nanoflagellate grazing, as estimated from the 0.2 \u0026mu;m dilution series, was observed exclusively at the surface during daytime, with a grazing rate of 0.06 h⁻\u0026sup1; (Table 2). Viral lysis emerged as the primary mechanism responsible for the removal of BAC in surface waters during daytime, exhibiting a higher rate of 0.09 h⁻\u0026sup1; (Table 2). Regarding SYN, viral lysis was observed exclusively in surface waters during daytime, with a rate of 0.09 h⁻\u0026sup1; (Table 2). In all other instances, this study did not detect a significant effect of viral lysis. Moreover, in certain instances, the grazing rates of SYN in both surface waters and DCM were considerable and statistically significant during daytime and nighttime (Table 2). As for PRO, in most cases (15 analyses), neither grazing nor viral lysis was detected.\u003c/p\u003e\n\u003cp\u003eTable 2. Growth (\u0026mu;), microzooplankton grazing (mg), and viral lysis rates (mv) for the bacteria (BAC), \u003cem\u003eSynechococcus\u003c/em\u003e spp. (SYN), and \u003cem\u003eProchlorococcus\u003c/em\u003e spp. (PRO).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"740\" height=\"474\"\u003e\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis research investigated the diel fluctuations in the growth rates of bacteria and picophytoplankton, as well as their losses attributable to nanoflagellate grazing and viral lysis, within the tropical South China Sea during the spring of 2025. The magnitude of losses attributable to viral lysis and nanoflagellate grazing exhibited considerable variability across different bacterial and picophytoplankton groups as well as over the course of daily time intervals. The primary finding of this study was the alteration in the regulatory mechanisms governing bacterial and picophytoplankton communities throughout the depth gradient. Our findings suggest that viral lysis constituted the primary mechanism of bacterial mortality in surface waters during daytime, while grazing was the dominant factor influencing bacterial mortality within DCM zone during nighttime. Moreover, nanoflagellate grazing exerts significant regulatory influence on SYN populations during both daytime and nighttime periods. This dynamic shift could have substantial implications for the fate and biogeochemical cycling of organic matter within the study area.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Methodological aspects\u003c/h2\u003e\u003cp\u003eThe size fractionation for grazers (\u0026lt;\u0026thinsp;10 \u0026micro;m) was selected according to earlier research to exclude microzooplankton (Tsai et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Trophic cascades may have occurred in the dilution grazing experiments, potentially leading to an overestimation of the effects of nanoflagellates on BAC or picophytoplankton in this study. For example, Calbet et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) observed that between March and June, the exclusion of the \u0026gt;\u0026thinsp;10 \u0026micro;m size fraction from incubation experiments resulted in a 20\u0026ndash;100% increase in primary production by \u0026lt;\u0026thinsp;10 \u0026micro;m that was consumed by microbial grazers, suggesting the presence of a trophic cascade effect. Moreover, the interactions between viruses and grazers, as well as their impacts on picoplankton, are likely to be highly complex (Mike and Jacquet 2008) and may encompass a range of antagonistic and synergistic effects (Jacquet et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For instance, nanoflagellates have the capacity to directly diminish viral abundance and infectivity either by consuming viruses themselves or by selectively grazing on cells infected by viruses (Bettarel et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). However, selective grazing was not evaluated in this study, so it remains unclear whether it took place during the dilution experiments and, if it did, whether it would lead to an underestimation of viral-induced bacterial mortality.\u003c/p\u003e\u003cp\u003eOne advantage of employing the dilution method, as opposed to alternative approaches for estimating viral effects on host mortality, is that it enables the direct quantification of the relative contributions of both grazing and viral lysis without requiring the application of conversion factors. For example, burst size and the proportion of visibly infected cells were quantified through transmission electron microscopy and subsequently transformed into the frequency of infected bacteria utilizing the equation presented by Weinbauer et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, in certain instances throughout this study, the dilution method was not effectively used to determine growth and mortality rates. The dilution method relies on three key assumptions, two of which are that plankton growth is exponential and unaffected by the dilution level (Landry and Hassett \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Consequently, plankton growth should not be constrained by nutrient availability or other environmental conditions. In this study, we found that BAC and picophytoplankton growth rates were similar or lower in the 30 kDa (free of grazers and viruses) series compared to the 0.2 \u0026micro;m (free of grazers) series (e.g., Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, H, K). Previous research has reported comparable observations wherein dilution with virus-free water led to a reduction in the growth rates of picophytoplankton, including SYN (Suttle et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Kimmance et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Other studies have also observed comparable reductions in apparent growth rate after dilution when filtered water was contaminated with substances that limit phytoplankton growth (Middelboe and Lyck \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Weinbauer et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Tsai et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Regarding SYN in surface waters, SYN growth rates were noticeably lower in treatments where viral abundance was decreased during the night (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH), indicating that active viruses promoted SYN growth. Our research indicates that diluting with virus-free water may have hindered nutrient recycling via viral lysis, and this absence of viruses adversely affected growth rates. This aligns with the findings of Weinbauer et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), who proposed that nutrient cycling driven by viral lysis of bacteria can regulate phytoplankton growth.\u003c/p\u003e\u003cp\u003eThis study aims to estimate the differences in growth and mortality of BAC and picophytoplankton between daytime and nighttime at various depths. Therefore, the duration of incubation employed in dilution experiments appears to be a crucial factor to consider. The length of the viral lytic cycle determines whether detectable cell lysis transpires within the incubation period (Evans et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Jacquet et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). This suggests that a single cycle of infection can be identified, indicating that host cell lysis transpires later than 12 hours post-infection but within a 24-hour incubation period. Most research on algal host\u0026ndash;virus model systems, including those involving prokaryotic algal hosts, demonstrates that the duration until cell lysis following viral infection typically occurs within 24 hours (Mann \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Evans et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) emphasize that since dilution experiments usually last 24 hours, the timing of the lytic cycle may correspond with that of the host growth rates. In the current study, viral lysis rates for SYN and PRO were generally not estimable during both daytime and nighttime periods. We propose that viral lysis rates may have been underestimated due to the incubation duration of approximately 8\u0026ndash;9 hours employed in our experiments (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Nanoflagellate grazing and viral lysis\u003c/h2\u003e\u003cp\u003ePrevious research has documented that daily maxima in bacterial production tend to occur either in the early morning or around midday, exhibiting a diel pattern that appears to be regulated by phytoplankton activity (Kuipers et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Irregular fluctuations in production throughout the day have also been documented (Gasol et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Regarding mortality, bacterial mortality rates have been observed to be significantly elevated during specific times of the day (Weisse \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). This pattern may be attributed to variations in protozoan feeding rates influenced by light intensity (Chen and Chang \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) or alterations in bacterial size affecting nanoflagellate grazing (Gonz\u0026aacute;lez et al. 1990). Current understanding indicates that viral activity is modulated by host conditions associated with light\u0026ndash;dark cycles. Furthermore, given that viruses are known to be susceptible to inactivation by ultraviolet (UV) radiation (Jacquet and Bratbak \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), it is inferred that elevated rates of viral lysis and infectivity are more likely to occur during the late afternoon and nighttime periods, when free viral particles experience reduced exposure to UV radiation (Suttle \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Winter et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Moreover, in the current study, viral lysis accounted for an average of 66.7% of bacterial mortality in both surface and deep chlorophyll maximum (DCM) waters during daytime experiments, as indicated by the ratios (0.06/0.09) \u0026times; 100% and (0.04/0.06) \u0026times; 100%, respectively. In contrast, viral lysis was not detected during nighttime conditions (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Previous studies had demonstrated that bacterial mortality due to viral lysis frequently exhibits a diel pattern. Winter et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) reported that the abundance of virus-infected bacterial cells increases following the peak of bacterial activity observed at midday, with a subsequent rise in viral release occurring in the late afternoon in the North Sea. Moreover, Ho et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) conducted two diel dilution incubation experiments in a semi-enclosed coastal area of northeastern Taiwan and observed that bacterial mortality due to viral lysis was greater during daytime compared to nighttime.\u003c/p\u003e\u003cp\u003eGiven that viral lysis and nanoflagellate grazing exert distinct effects on the aquatic food web, it is essential to evaluate the relative significance of these two mortality factors. The fate of viral lysates in aquatic environments is determined by their ability to be assimilated by BAC. Unlike most of the ambient DOM present in seawater, DOM that is freshly released from lysed cells is readily labile and available for bacterial uptake (Middelboe and J\u0026oslash;rgensen \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Under these conditions, viral lysis is expected to enhance bacterial activity, as evidenced by the observed elevated bacterial growth rates during daytime experiments conducted in the surface layer of oligotrophic waters (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Variations in the temporal and spatial significance of viruses as contributors to bacterial mortality, as demonstrated in multiple studies (e.g., Weinbauer et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Guixa-Boixareu et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Shiah et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), may substantially impact the role of bacterial-mediated organic carbon processing within pelagic marine ecosystems. Moreover, an additional explanation is that diel fluctuations in substrate availability, primarily driven by changes in phytoplankton production, may result in significant diel patterns of bacterial activity within the euphotic zone.\u003c/p\u003e\u003cp\u003ePrevious research has indicated that SYN predominantly inhabits the surface layers of the ocean, with growth rates generally observed to be lower at the depths corresponding to the DCM (Partensky et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). In contrast, PRO cells are found to extend into deeper aquatic zones, where they typically exhibit higher growth rates compared to SYN (Partensky et al. 1999). Our findings are consistent with these studies, showing that SYN growth was greater in surface waters compared to the DCM layer (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, this study indicates that nanoflagellate grazing may be a significant cause of SYN loss in the oligotrophic waters of the tropical Pacific Ocean (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Regarding the mortality of SYN or PRO, cyanobacteria are present in comparatively high concentrations; however, infectious phages targeting SYN and PRO are observed at low abundances in offshore oligotrophic marine environments (Sullivan et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Sullivan et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) even suggested that low cyanophage concentrations in regions with a high abundance of hosts appear to be typical characteristics of the open ocean. Other studies also indicated that the typically high genetic diversity within SYN and PRO populations, along with capacity of cyanobacteria to develop resistance to cyanophages (Scanlan and West \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), might have contributed to diminishing the impact of cyanophages as causes of mortality. Moreover, grazing on PRO was significantly lower compared to SYN in surface waters (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), suggesting that the two prokaryotic groups experienced different loss processes. Additionally, since no significant effects of viral lysis or nanoflagellate grazing on PRO were observed in surface waters, PRO showed a higher abundance than SYN in this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Diel variation of carbon production and losses\u003c/h2\u003e\u003cp\u003eDifferentiating and measuring the losses of BAC and picophytoplankton caused by nanoflagellate grazing and viral lysis is crucial for a comprehensive understanding of the carbon cycle in marine ecosystems. In assessing the interactions among BAC, picophytoplankton, VIR, and nanoflagellates and their influence on energy transfer within microbial food webs, this study concentrated on the relationships between BAC and picophytoplankton growth, grazing, viral lysis, and the associated carbon flux. In this context, the rates of production (BP, SP, PP), grazing (BG, SG, PG), and viral lysis (BL, SL, PL) for BAC, SYN, and PRO, expressed in \u0026micro;g C L⁻\u0026sup1; h⁻\u0026sup1;, were determined by applying carbon conversion factors of 20, 46, and 213 fg C cell⁻\u0026sup1; to BAC, PRO, and SYN, respectively, as established by Lee and Fuhrman (1987) and Bertilsson et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the estimates, the combined carbon losses of BAC caused by viral lysis and nanoflagellate grazing (0.40 and 0.20 \u0026micro;g C L\u003csup\u003e\u0026ndash;1\u003c/sup\u003e h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e, respectively) collectively accounted for an average of 100% of BP (0.60 \u0026micro;g C L\u003csup\u003e\u0026ndash;1\u003c/sup\u003e h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e) at surface water during daylight hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Regarding the DCM layer, viral lysis was determined to be the primary cause of BAC mortality during daytime experiments, seemingly accounting for the removal of approximately 79% of BP (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur results indicate that nanoflagellate grazing exerted a significant influence on SYN populations during both daytime and nighttime experiments conducted at the surface and DCM layers (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Specifically, carbon losses from SYN attributable to nanoflagellate grazing were approximately 0.06 and 0.04 \u0026micro;gC L⁻\u0026sup1; h⁻\u0026sup1; during the day and night, respectively, accounting for 55% and 33% of the total SYN production (SP) in these periods (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Our findings strongly indicate that nanoflagellate grazing was the primary biological factor controlling daily fluctuations in SYN abundance. Moreover, when considering the relative importance of food sources for nanoflagellates, the results further imply that BAC play a significant role in transferring carbon to higher trophic levels in the oligotrophic waters of the SCS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn summary, our research makes an important contribution to understanding how depth and daily changes influence the interaction of key factors regulating BAC and picophytoplankton abundance in the South China Sea. Our findings demonstrate that both bottom-up and top-down controls work together to regulate the populations of all studied groups. The measured overall growth and mortality rates could provide useful data for ocean models that include microbial carbon fluxes in the South China Sea.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciate the language editing and helpful comments related to this manuscript from Choice Language Service.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCAN: Formal analysis, Investigation, Methodology, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFKS: Resources, Writing \u0026ndash; review \u0026amp; editing. PWYC: Formal analysis, Investigation, Methodology. \u0026nbsp;MO: Formal analysis, Investigation, Methodology. TYC: Investigation, Writing \u0026ndash; review \u0026amp; editing. A-YT: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Science and Technology Council, ROC (Taiwan), grant number NSTC 114-2740-M-001-003 -\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBaudoux AC, Veldhuis MJW, Noordeloos AAM, Van Noort G, Brussaard CPD (2008) Estimates of virus-vs. grazing induced mortality of picophytoplankton in the North Sea during summer. 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Deep-SeaRes II 46:795\u0026ndash;814. https://doi.org/10.1016/S0967-0645(98)00128-3\u003c/li\u003e\n\u003cli\u003eWinter C, Herndl GJ, Weinbauer MG (2004) Diel cycles in viral infection of bacterioplankton in the North Sea. Aquat Microb Ecol 35:207\u0026ndash;216. https://doi.org/10.3354/ame035207\u003c/li\u003e\n\u003cli\u003eWong GTF, Ku TL, Mulholland M, Tseng CM, Wang DP (2007) The South East Asian time-series study (SEATS) and the biogeochemistry of the South China Sea \u0026ndash; An overview. Deep-Sea Res. II 54:1434\u0026ndash;1447. https://doi.org/10.1016/j.dsr2.2007.05.012\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"South China Sea, picoplankton, microbial loop, modified dilution technique, viral lysis, nanoflagellate grazing","lastPublishedDoi":"10.21203/rs.3.rs-7350023/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7350023/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo examine the relative importance of nanoflagellate grazing and viral lysis on prokaryote abundance—including heterotrophic bacteria, \u003cem\u003eSynechococcus\u003c/em\u003espp., and \u003cem\u003eProchlorococcus \u003c/em\u003espp.—in the tropical ocean, a modified dilution technique combined with light-dark experiments was used during a South China Sea cruise in late April 2025. Results show that during the daytime, the combined carbon loss from viral lysis and nanoflagellate grazing (0.40 and 0.20 µgC L⁻¹ h⁻¹, respectively) accounted for nearly 100% of bacterial production in surface waters. In the deep chlorophyll maximum layer, viral lysis alone removes almost 80% of the bacterial production during the daytime. The carbon losses of\u003cem\u003e Synechococcus \u003c/em\u003espp. to nanoflagellate grazing were approximately 0.06 µgC L⁻¹ h⁻¹ in the daytime and 0.04 µgC L⁻¹ h⁻¹ at night, which represent 55% and 33% of total \u003cem\u003eSynechococcus\u003c/em\u003e spp. production, respectively. These results strongly suggest that nanoflagellate grazing is the primary factor controlling the daily fluctuations in \u003cem\u003eSynechococcus\u003c/em\u003e spp. abundance. The carbon flows among the components of target organisms and the two top-down forces constructed by this research can be indicative for future studies in this and other tropical seas.\u003c/p\u003e","manuscriptTitle":"Diel dynamics of bacterial and picophytoplankton growth, grazing and viral lysis at different depths in the tropical South China Sea in spring","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-28 13:44:53","doi":"10.21203/rs.3.rs-7350023/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"774b647d-9c79-4f6d-a440-a49e21fb2191","owner":[],"postedDate":"August 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-25T07:09:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-28 13:44:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7350023","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7350023","identity":"rs-7350023","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}