Virophages are small double-stranded DNA (dsDNA) viruses that parasitize the replication machinery of giant viruses, adding a new layer of complexity to virus–host interactions (Duponchel and Fischer, 2019, Fischer, 2021, Fischer and Suttle, 2011, La Scola et al., 2008, Roux et al., 2023). In these cell–virus–virophage (CVv) systems, eukaryotic hosts are co-infected—either simultaneously or sequentially—by both giant viruses and virophages. Virophages replicate within the viral factories (VFs) formed by giant viruses, often suppressing giant virus replication (Azevedo et al., 2022, Fischer and Hackl, 2016, Fischer and Suttle, 2011, Gaia et al., 2014, Jeudy et al., 2020, Koonin and Krupovic, 2016, La Scola et al., 2008, Mougari et al., 2019). This hyperparasitism can indirectly benefit the host by alleviating damage caused by giant virus infection, thereby enhancing host survival (Fischer and Hackl, 2016, Koonin and Krupovic, 2016, La Scola et al., 2008). Depending on the ecological context, CVv interactions can range from antagonistic to mutualistic (Fischer and Hackl, 2016, Koslová et al., 2024, Wodarz, 2013).

CVv systems have been identified in diverse eukaryotic hosts, including amoebae, marine flagellates, and photosynthetic algae, through co-culture experiments and metagenomic surveys (Azevedo et al., 2022, Fischer and Hackl, 2016, Fischer and Suttle, 2011, Gaia et al., 2014, Gong et al., 2016, Jeudy et al., 2020, Koonin and Krupovic, 2016, La Scola et al., 2008, Mougari et al., 2019, Potapov and Belykh, 2023, Roux et al., 2017, Sheng et al., 2022, Wu et al., 2023, Xu et al., 2020, Yau et al., 2011, Zhou et al., 2015). Model systems such as Acanthamoeba castellanii–Mamavirus–Sputnik and Cafeteria roenbergensis–CroV–Mavirus have provided important mechanistic insights (Fischer and Hackl, 2016, Koonin and Krupovic, 2016, La Scola et al., 2008). However, despite increasing metagenomic evidence revealing widespread giant viruses and virophages, quantitative understanding of their interaction dynamics and ecological roles remains limited (Chen et al., 2018, Gong et al., 2016, Paez-Espino et al., 2019, Potapov and Belykh, 2023, Roux et al., 2017, Sheng et al., 2022, Wu et al., 2023, Xu et al., 2020, Yau et al., 2011, Zhang et al., 2015, Zhou et al., 2015, Zhou et al., 2013). This knowledge gap is especially pronounced in algal systems (Chen et al., 2018, Gong et al., 2016, Sheng et al., 2022, Wu et al., 2023, Xu et al., 2020, Zhang et al., 2015, Zhou et al., 2015, Zhou et al., 2013), where cultivable models are scarce and obtaining sufficient purified viral particles is challenging. Yet microalgae are critical primary producers in aquatic ecosystems and frequent viral hosts that influence community structure and biogeochemical cycles (Falkowski et al., 1998, Suttle, 2007).

Metagenomic analyses of Dishui Lake, a freshwater ecosystem in Shanghai, China, uncovered diverse algal-associated CVv systems (Chen et al., 2018, Gong et al., 2016, Sheng et al., 2022, Xu et al., 2020). For example, Dishui Lake Large Alga Virus 1 (DSLLAV1) and Dishui Lake Virophage 8 (DSLV8) form a putative natural pair (Xu et al., 2020). DSLLAV1 is a ∼392 kbp Mimiviridae-related giant virus with genomic signatures indicative of green algal hosts, while DSLV8 is 26.6 kbp virophages exhibiting strong codon usage similarity to DSLLAV1, suggesting close ecological coupling (Xu et al., 2020). Intriguingly, DSLLAV1 encodes a CRISPR-Cas-like system with spacers perfectly matching DSLV8, implying targeted antagonism and potential coevolution (Xu et al., 2020).

Despite their ecological and evolutionary significance, quantitative study of CVv dynamics in algal systems remains hindered by methodological limitations. Traditional culture-based isolation and electron microscopy are time-consuming and morphology-dependent, while quantitative PCR (qPCR) requires target-specific standard curves and is sensitive to inhibitors in environmental samples (Dingle et al., 2013, Rački et al., 2014, Smith and Osborn, 2009). In our preliminary qPCR experiments to quantify DSLLAV1 and DSLV8 during algal infection, we encountered technical challenges. Specifically, low-copy viral targets within the Chlorella-based infection system often failed to amplify consistently, even under carefully optimized conditions. These difficulties underscore the susceptibility of qPCR to inhibition and its limited sensitivity at low template concentrations, thereby highlighting the need for a more robust and reliable quantification method. Droplet digital PCR (ddPCR), which partitions reactions into thousands of nanoliter droplets and applies Poisson statistics for absolute quantification, offers higher sensitivity and robustness to inhibitors but has yet to be applied to algal CVv systems (Dingle et al., 2013, McDermott et al., 2013, Rački et al., 2014, Sedlak et al., 2014).

To address this challenge, we developed and optimized a duplex ddPCR assay for the simultaneous detection and quantification of DSLLAV1 and DSLV8. Using plasmid standards, the assay demonstrated high specificity and sensitivity, with detection limits of 0.13 and 0.16 copies/µL, respectively. When applied to actual infection samples, ddPCR showed clear advantages over conventional qPCR, particularly in detecting low-abundance targets within complex sample matrices. This method enables direct quantification of virus–virophage dynamics in freshwater samples and provides a robust foundation for future ecological and evolutionary studies of CVv systems in algal hosts.