Bacteria–algae consortia in the light bring the benefit of O2 production and CO2 reduction for wastewater treatment, while the bottleneck for application is how it behaves in the dark. In this study, inoculum ratio and sludge retention time (SRT) affected nutrient removal rather than chemical oxygen demand (COD) removal. Dark conditions (with a sludge/Chlorella inoculum ratio of 1:2 at a SRT of 15 d) achieved comparable performance to those of light conditions, due to bacteria contribution and mechanical aeration. Compared with light conditions, the ratio of Chla/Chlb decreased and Caro/(Chla + Chlb) increased to response oxidative stress. In the dark, algae were associated with Nitrosomonas and Dechloromonas. Flavobacterium disassociated with Chlorella in the dark but associated with Chlorella in the light. Moreover, nitritation genes (amo and Hao) and denitrifying gene (narH) were up-regulated, while P metabolism genes (PPX and PPK) were down-regulated. It is proposed to enrich Nitrosomonas in the night and denitrify polyphosphate accumulating organisms (DPAO) in the daytime to establish short-cut nitrification and denitrifying phosphorus removal in practical applications.

  • Bacteria–algae inoculum ratio affected N and P removal, while SRT affected P removal.

  • Bacteria contributed more than algae towards COD, NH4+, and P removal.

  • Caro/(Chla + Chlb) increased and Chla/Chlb decreased.

  • Dark co-culture favored Nitrosomonas but was adverse to Flavobacterium.

  • N-related genes (amo, Hao, narH) were up-regulated, while P-related genes (PPX, PPK) were down-regulated.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Microalgae can utilize nitrogen and phosphorus in wastewater to grow and produce O2. To date, microalgae can achieve the multiple purposes of nutrient removal, CO2 reduction, biofuel recovery and hazardous contaminants removal (Sforza et al. 2014). However, microalgae alone are poorly settled and need long hydraulic retention times. Extracellular polymer substances secreted by bacteria can help in the bioflocculation of algae, and bacteria–algae consortia exhibit superior nutrient removal to algae alone and bacteria alone (Mohammad et al. 2020). Bacteria-algae consortia for wastewater treatment were initially developed in an open high rate algae pond (HRAP) with shallow water levels. Recently, it has raised much attention as it is a sustainable alternative to conventional activated sludge processes.

The symbiosis of algae-bacteria benefits from CO2/O2 exchange (Mohammad et al. 2020), bacteria produce indole-3-acetic acid (IAA) to promote algae growth, supplying vitamin B1/B7/B12 and siderophore to algae in exchange for organic carbon. Nevertheless, photosynthetic O2 supplied to bacteria is highly dependent on light availability, which varies widely with day/night diel rhythm, reactor depth, and seasonal variation, thereby light deficiency is a common occurrence. When light intensity is lower than the light compensation point of 5 μmol·m−2·s−1, photosynthesis of Chlorella ceases (Zhang & Perre 2020). During the night, algae biomass decays up to 30% (Edmundson & Huesemann 2015). Despite concerns about performance of bacteria–algae consortia during the night, 24 h illumination is unnecessary and even counterproductive towards nutrients removal. Jia & Yuan (2018) investigated 24 h continuous illumination and 16/8 h light/dark cycles, both of which achieved a removal of 60 mgN·L−1·d−1, but 24 h illumination led to a lower nitrification rate per unit biomass. Combined stress of algae and light also caused severe inhibition on Nitrospira (Huang et al. 2020).

In the dark, Chlorella sp. and Scenedesmus sp., the commonly found indigenous algae in wastewater treatment plant, can alter from autotrophy into heterotrophy, in which algae use organic carbon as an energy source to survive in the dark (Fallahi et al. 2021). At this point, a competitive relationship existed between algae and heterotrophic bacteria, whereas algae and nitrifying bacteria compete for CO2 in the light. A photoperiod of 12 h:12 h light/dark is often used, but a few studies have reported the performance in the dark. Compared with the light phase, the removal efficiency of COD, NH4+-N and P for the bacteria–algae consortia in the dark reduced by 1.8%, 7%–30%, and 5%–27%, respectively (Sforza et al. 2014; Chen et al. 2019; Mohammad et al. 2020). Although the same amount of N was removed in the light and in the dark, lower removal rates of NH4+, NO2, NO3 and even collapsed P removal was observed in the dark (Zhao et al. 2019). Nevertheless, Petrini et al. (2020) found that nitrification rate in the dark was equal to that in the light. Co-culture of Chlorella and Azospirillum in the dark showed higher affinity to ammonia and phosphorus (Perez-Garcia et al. 2010). Prolonged dark phase increased the bacteria/algae ratio (Lee et al. 2015). Bacteria secreted more abundant IAA and alleviated oxidative stress in the dark (Chen et al. 2019). To date, the performance of bacteria–algae consortia in the dark has remained controversial, and little is known about the bacterial community and the mechanism. Since algae assimilation and bacterial function (nitrification, denitrification, and luxury P uptake) are responsible for nutrient removal, the balance between algae and bacteria determines the performance, and it is workable to strengthen the bacterial contribution in the dark.

In our previous study (Fan et al. 2020), we confirmed the possibility of running the consortia in the dark. Dark conditions protected Nitrosomonas from the stress of light and algae. Here, we hypothesize that the bacteria–algae consortia in the dark rely more on bacteria to remove pollutants, and mechanical aeration favors bacteria over algae (Zhang et al. 2020). The aim of this study was to (1) seek factors affecting performance in the dark by adjusting the bacteria/algae inoculum ratio and SRT; (2) compare performance between light condition and dark conditions; (3) reveal mechanisms by profiling the role of bacteria and algae, the change of algae proportion and photosynthetic pigments, bacterial community and function genes. It provided support to maintain the superior performance of bacteria–algae during the night for real-world application.

Algae, bacteria and wastewater

The alga Chlorella sorokiniana was purchased from the Institute of Hydrobiology, Chinese Academy of Science (Wuhan, China). Here, 10% (v/v) C. sorokiniana was enriched with 100 mL synthetic wastewater in a biochemical incubator with illumination of 3000 lx at 25 °C, and shaken by hand three times per day. Then the algae were harvested by centrifugation at 4,000 rpm for 5 min. Activated sludge was collected from the LBZ municipal wastewater treatment plant (WWTP), Wuhan, China. It was acclimated with the synthetic wastewater in the laboratory.

According to the influent concentration of LBZ municipal WWTP, COD, NH4+-N, and PO43−-P concentrations of synthetic wastewater was set as 200, 30, and 4 mg/L, respectively, composed of (mg/L): glucose 155, sodium acetate 82, NH4Cl 114, KH2PO4 17, MgSO4·7H2O 25, CaCl2 28, and 1 mL trace elements that consisted of (g/L): ZnSO4·7H2O 22, H3BO3 11.4, MnCl2·4H2O 5.06, CoCl2·4H2O 1.61, CuSO4·5H2O 1.57, FeSO4·7H2O 4.99. The constituent was prepared according to Huang et al. (2015).

Consortia in the dark and in the light

The consortia were composed by Chlorella sorokiniana and activated sludge. (1) To seek optimum performance of the consortia in the dark, inoculum ratio (sludge/Chlorella) and SRT were adjusted. The inoculum ratio (sludge/Chlorella, wt/wt) was set as 1:0.5, 1:1, 1:2, 1:4 (labeled as SC0.5, SC1, SC2, SC4, the total biomass of each ratio was controlled at 2,500 mg/L). SRT was set as 10, 15, 20, 30 d (labeled as SRT10, SRT15, SRT20, SRT30). These influencing factor experiments were conducted in 1 L wide-mouth bottles for 45 d, wrapped in aluminum foil paper to avoid light at room temperature 20 °C and water temperature was 17–18 °C. (2) After the optimal inoculum ratio and SRT were determined (sludge/Chlorella 1:2, SRT 15d), the consortia were divided equally into two parts: one part still ran in the dark, and the other part ran in the light which took 27 d to acclimate to dark conditions switching to light conditions. Under the light conditions, illumination was provided by two fluorescent lamps with a light intensity of 3000 lx measured outside the bottles. The running cycle consisted of stirring at 150 rpm (2 h), mechanical aeration by air compressor (4 h, DO kept at 2–4 mg/L), and settling (1 h). The volume discharge ratio was 70% resulting in a hydraulic retention time (HRT) of 10 h. During the cycle, pH ranged at 7.0–7.2 (dark consortia) and 7.0–7.7 (light consortia).

Comparison among algae, bacteria, and the consortia

Wastewater was treated with the C. sorokiniana alone, activated sludge alone, and sludge/Chlorella consortia (S:C = 1:2, SRT 15 d). Initial biomass concentration of all treatments was 2,500 mg/L. The running cycle was the same as above except for algae alone. Due to the poor settling of algae, settling time of algae alone was prolonged to 2 h. COD, NH4+, P removal at stable phase was used for performance comparison and hierarchical cluster analysis to identify similarity among different groups (algae, bacteria, bac–alg light, and bac–alg dark) using SPSS 19.

Analytical methods

The effluent was filtrated through a 0.45-μm cellulose acetate membrane, and then COD, NH4+-N, PO43−-P were measured using the potassium dichromate method, ascorbic acid method, and Nessler's reagent spectrophotometry (APHA 2012). Samples of bac–alg dark and bac–alg light at stable phase were collected for measurement of photosynthetic pigments. Chlorophyll was extracted using methanol (Li et al. 2015). Mixed liquid was centrifuged at 13,400 rpm for 5 min; the pellet was extracted with 1.5 mL methanol for 60 min in the dark at 45 °C, afterwards supernatant was measured by ultraviolet spectrophotometry and the pigments were calculated based on Equations (1)–(3):
formula
(1)
formula
(2)
formula
(3)

Algae biomass in the light was estimated by Chla, algae biomass (g/L) = 0.0863 Chla – 0.0104 (R2 = 0.99). In the dark, Chla decoupled with algae biomass, so algae biomass was determined by cell counting, algae biomass (g/L) = 11.616 cell – 0.7469 (R2 = 0.99). Dilution and sonication (20 kHz for 5 min) were used to disperse algae in the consortia before cell counting. Algae biomass divided mixed liquid suspended solids (MLSS) was the algae proportion in the consortia.

Samples from bacteria and bacteria–algae were subjected to Illumina 16S rRNA gene high-throughput sequencing analysis, and the details can be found in our previous study (Fan et al. 2020). In brief, V3–V4 regions of bacterial 16S rRNA genes were amplified using primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′). PCR and sequencing were conducted on the Illumina MiSeq 2*300 platform at Songon Biotech Co., Ltd. (Shanghai, China).

Seeking optimal dark performance through influencing factors

Effect of inoculum ratio on performance was shown in Figure 1(a), and the optimum sludge/Chlorella ratio was 1:2. NH4+-N removal was 91% (1:0.5), 94% (1:1), 98% (1:2), 82% (1:4); and P removal was 87% (1:0.5), 91% (1:1), 95% (1:2), 81% (1:4). With increasing algae proportion, the consortia achieved higher N and P removal except for ratio 1:4. An excessive proportion of algae reduced the nitrifying population in the consortia (Fallahi et al. 2021). Moreover, within ratios of 1:0.5, 1:1, and 1:2, nutrient removal apparently increased, while COD removal remained unchanged, indicating that the inoculum ratio had a strong correlation with nutrient removal rather than COD removal. This phenomenon was also observed in light-cultured algae-bacteria consortia by Su et al. (2012).
Figure 1

Effect of sludge/Chlorella inoculum ratio (S:C) (a) and SRT (b) on pollutants removal.

Figure 1

Effect of sludge/Chlorella inoculum ratio (S:C) (a) and SRT (b) on pollutants removal.

Close modal

The performance at different SRTs of 10, 15, 20, 30 d is shown in Figure 1(b), and the optimum SRT was 15 d. SRT only affected P removal, since an SRT of 15, 20, 30 d showed no difference in COD and NH4+-N removal. Similar results were reported by Rada-Ariza et al. (2019), who found that NH4+-N removal efficiency did not differ among the investigated SRT range of 17–48 d, and shorter SRT favored nitrification over algal assimilation of nitrogen. The above results suggested that long SRT was not necessary. For an SRT as short as 10 d, Chlorella was detected in the supernatant in this study. Also, ammonium oxidizing bacteria (AOB) were washed out by applying the SRT of 10 d (Yang et al. 2018).

Performance of light and dark conditions

Performance of bacteria–algae at the optimum condition (bacteria/algae ratio of 1:2, SRT of 15 d) in the dark was compared with that in the light, as well as bacteria alone and algae alone (Figure 2(a)). The acclimation of the consortia in the dark (9 d) was more rapid than under light conditions (27 d). Compared with light conditions, despite the maximum removal efficiency (an indicator of pollutants removal potential) was inferior, the removal efficiency was more stable, thereby average COD, NH4+-N, and P removal in the dark was slightly increased by 3.6%, 2.6%, and 0%, respectively. Light provides energy for algae growth, but light-mediated damage to cytochrome-c of the electron transport system of AOB and nitrite oxidizing bacteria (NOB) led to the reduction of nitrification (Kwon et al. 2020). Although light intensity below 250 μmol m−2 s−1 did not show an obvious effect on nitrifying bacteria (Meng et al. 2019), combined stress of light and algae could slightly lower the relative abundance of AOB while severely inhibited NOB (Huang et al. 2020), hence an obvious nitrite accumulating rate (NAR) of about 30% occurred in the light (Figure 2(b)). Given that nitrite accumulation was not observed in the dark, a dark environment could relieve algae inhibition on Nitrospira. Furthermore, P removal between light and dark conditions was different. Although P removal ability of algae in heterotrophic mode was superior to that in mixotrophic mode (Kim et al. 2013), our previous research (Fan et al. 2019) found that the P removal of algae in the dark decreased by 13%–23% compared with light conditions, to a certain extent owing to slower algae growth in the dark.
Figure 2

Boxplots of COD, NH4+-N, and P removal for n = 20 (a), nitrite accumulation during a cycle (b), hierarchical cluster analysis with COD, NH4+-N, and P removal (c).

Figure 2

Boxplots of COD, NH4+-N, and P removal for n = 20 (a), nitrite accumulation during a cycle (b), hierarchical cluster analysis with COD, NH4+-N, and P removal (c).

Close modal

To distinguish the contribution of algae and bacteria to pollutant removal, hierarchical cluster analysis was conducted with an index of COD, NH4+-N, and P removal (Figure 2(c)). It revealed that the bac–alg consortia were closer to bacteria (activated sludge) either in the light or in the dark, confirming the major role of bacteria for COD, NH4+-N, and P removal. Bacterial contribution and mechanical aeration were the main reasons for excellent performance in this study. Some bacteria–algae consortia relied on algae assimilation showed fluctuation in N and P removal, as summarized in Table 1. Light or dark conditions exhibited little effect on COD removal, which was consistent with our study. Nevertheless, N and P removal in the dark even declined by 60% in some cases. Failure of P removal during the night was reported in an algal–bacterial aerobic granular sludge (Zhao et al. 2019), because cyanobacteria Leptolyngbya capable of much P uptake was inactive during the night and polyphosphate accumulating organisms (PAO) released excessive P. Mohammad et al. (2020) found that a bacteria/algae ratio of 1:2 produced sufficient dissolved oxygen (DO) in the light and the residual DO during the night remained at 5 mg/L, yet nitrification was inhibited and intense competition occurred between bacteria and algae (Chen et al. 2019). This competition could be alleviated by nighttime mechanical aeration, since mechanical aeration limited the reproduction of microalgae (Zhang et al. 2020). Also, it was reasonable to deduce that mechanical aeration supported the major role of bacteria in the consortia (Figure 2(c)).

Table 1

Algae–bacteria consortia treating wastewater in a light/dark cycle

ConsortiaCultivation modeCOD removal
NH4+-N removal
P removal
Reference
LightDarkLightDarkLightDark
Leptolyngbya + AS Shaking 94.8% 94.4% >99% >99% 65% 0% Zhao et al. (2019)  
Chlorella + indigenous bacteria Stirring and air with 5% CO2 – – 98.4% 96.9% 87.6% 60.6% Sforza et al. (2014)  
Chlorella sp 1602 +AS No aeration 94.4% 94.4% 97% 36% 100% 94.7% Chen et al. (2019)  
Scenedesmus + Acinetobacter Shaking 100% 100% 85% 55% 94% 94% Mohammad et al. (2020)  
Microalgal–bacterial granules Shaking 94.9% 93.1% 69.5% 62.5% 90.6% 80.8% Ji et al. (2021)  
C. sorokiniana + AS Stirring/aeration 83.5% 87.1% 95.6% 98.2% 96.3% 96.0% This study 
ConsortiaCultivation modeCOD removal
NH4+-N removal
P removal
Reference
LightDarkLightDarkLightDark
Leptolyngbya + AS Shaking 94.8% 94.4% >99% >99% 65% 0% Zhao et al. (2019)  
Chlorella + indigenous bacteria Stirring and air with 5% CO2 – – 98.4% 96.9% 87.6% 60.6% Sforza et al. (2014)  
Chlorella sp 1602 +AS No aeration 94.4% 94.4% 97% 36% 100% 94.7% Chen et al. (2019)  
Scenedesmus + Acinetobacter Shaking 100% 100% 85% 55% 94% 94% Mohammad et al. (2020)  
Microalgal–bacterial granules Shaking 94.9% 93.1% 69.5% 62.5% 90.6% 80.8% Ji et al. (2021)  
C. sorokiniana + AS Stirring/aeration 83.5% 87.1% 95.6% 98.2% 96.3% 96.0% This study 

*AS, activated sludge.

Algae proportion and pigments for stress response

The change of algae proportion over time is shown in Figure 3(a). The initial inoculum ratio of algae was about 60% in the consortia, and algae were washed out due to its poor settleability, with the algae proportion stabilized at 23.8% in the dark, while it rose to 26.3% when switched to light conditions. In general, mixotrophic growth of algae under light conditions made it more flexible to storing energy via illumination and oxidative phosphorylation, thus the algae proportion increased. In addition, algae are susceptible to light blocking and self-shading (Kwon et al. 2020), leading to the slight fluctuation in the algae proportion in the light. The algae maintained at a relatively low proportion in the consortia, and this balance between algae and PAO was important for synergistic P removal, since excess algae would inhibit PAO and reduce P removal (Mohamed et al. 2021).
Figure 3

Algae proportion in the consortia (a), Chla, Chlb, carotenoid and ratios of Chla/Chlb, Caro/(Chla + Chlb) (b).

Figure 3

Algae proportion in the consortia (a), Chla, Chlb, carotenoid and ratios of Chla/Chlb, Caro/(Chla + Chlb) (b).

Close modal

Photosynthetic pigments are commonly used to characterize the photo-acclimation of algae. Chlorophyll a (Chla), chlorophyllb (Chlb), and carotenoid (Caro) are shown in Figure 3(b). In the light, Chla, Chlb, and Caro were 6.71, 1.48, 1.69 mg/g MLSS, respectively, which decreased to 2.15, 0.69, 0.64 mg/g MLSS in the dark. Chlorophyll and carotenoid are responsible for light absorption, thus the reduction in pigments in the dark was reasonable. In addition, the ratios of Chl a/Chlb and Caro/(Chla + Chlb) are biomarkers of photosystem II (PSII) against oxidative stress. Compared with light conditions, Chla and Chlb content was reduced by 68 and 53% respectively, leading to a reduction of the Chla/Chlb ratio from 5 to 3, and this suggested algae adaption to dark conditions through up-regulating Chlb and weakening Chla (Li et al. 2022). In contrast, the Caro/(Chla + Chlb) ratio increased from 0.20 to 0.25, as carotenoids devitalized Chla to eliminate accumulated reactive oxygen species (ROS) in chloroplasts (Paliwal et al. 2015). Chen et al. (2019) reported less oxidative damage and more IAA promoting cell division for consortia under dark conditions. It can be concluded that algae down-regulated the Chla/Chlb ratio and up-regulated the Caro/(Chla + Chlb) ratio to protect chloroplasts in the dark, since algal N assimilation occurred in chloroplasts of algae (Chen et al. 2022).

Bacterial community shift in the dark

Function bacteria of activated sludge, bac–alg light and bac–alg dark are listed in Figure 4. Compared with light conditions, the consortia in the dark enriched Nitrosomonas, suggesting that nighttime is suitable to incorporate algae with Nitrosomonas. This was adverse to Dechloromonas and Flavobacterium (DPAO) (Xu et al. 2019), although Dechloromonas was still richer than that in activated sludge. Concurrently, reducing Flavobacterium and Dechloromonas stimulated their competitor Defluviicoccus (glycogen accumulating organism, GAO), and this was a plausible reason for no P improvement in the dark. This study and other research (Tang et al. 2018) found that Flavobacterium co-existed well with algae in the light, however, it declined in the dark which may be attributed to the dual role of Flavobacterium on algae, i.e., algicidal bacteria (Wang et al. 2020) and algae growth promoting bacteria (Cho et al. 2015). In addition, Flavobacterium and Terrimonas known as phycosphere bacteria of Chlorella decreased in the dark, suggesting their association with algae. The affiliation of phycosphere bacteria for algae was dependent on the environment. They were boosted with algal bloom, and released coumaric acid to kill the algae when algae were subjected to upheaval (Ramanan et al. 2016).
Figure 4

Functional bacteria of activated sludge, bac–alg light and bac–alg dark.

Figure 4

Functional bacteria of activated sludge, bac–alg light and bac–alg dark.

Close modal
Notably, in the dark, algae selectively stimulated rare genera (relative abundance < 1%) and inhibited abundant genera (relative abundance > 1%). The volcano plot (Figure 5(a)) distinguished 16 up-regulated and 15 down-regulated genera. In detail (Figure 5(b)), algae stimulated Lacibacterium (hydrolyzing bacteria), Chryseolinea (fermentative bacteria), Nitrosomonas (0.02% to 0.32%), and Byssovorax. In contrast, algae suppressed Zoogloea, Ferruginibacter (hydrolyzing bacteria), Tolumonas (fermentative bacteria), Terrimonas, Flavobactium (1.39% to 0.58%), and Lysobacter. It is worth stressing that the reduction in Lysobacter (9.14% to 0.11%) and increment in Byssovorax (0.78% to 2.07%). Lysobacter produced peptide to lyse algae (Puopolo et al. 2018). Byssovorax degraded dead bacteria. Therefore it was inferred that Lysobacter was killed by algae for defense, and then the dead Lysobacter was decomposed by Byssovorax.
Figure 5

Bacterial community shift in the dark compared with activated sludge by volcano plot showing changes with p-value < 0.05 (a), relative abundance of down-regulated and up-regulated bacteria (b).

Figure 5

Bacterial community shift in the dark compared with activated sludge by volcano plot showing changes with p-value < 0.05 (a), relative abundance of down-regulated and up-regulated bacteria (b).

Close modal

Metabolic genes shift in the dark

The main bacterial genes for C, N and P metabolism according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database are shown in Figure 6. Compared with activated sludge, the expression of carbohydrate metabolism genes, such as HK and pfkA (glycolysis genes), kor (tricarboxylic acid (TCA) cycle related gene), PDH (pyruvate oxidation gene) were enhanced in bac–alg consortia, this was evidence of utilization of algae-derived organic carbon by bacteria. For N removal, the nitritation genes amo and Hao catalyzes NH4+ to NH2OH, NH2OH to NO2, respectively. Gene amo in the dark (0.040‰) was absolutely higher than that in the light (0.003‰), as well as the trend for the Hao gene. The upward trend of these nitritation genes and denitrifying gene of narH (reduce NO3 to NO2) was expected to favor NO2 production, indeed this was consistent with the enrichment of Nitrosomonas (Figure 4) in the dark consortia. Nevertheless, nitrite was not accumulated (Figure 2(b)), and a possible speculation was nitrite utilization by DPAO. Although DPAO could use NO2 and NO3 as an electron acceptor, denitrifying phosphorus removal through NO2 showed lower phosphorus uptake than did NO3 (Hou et al. 2022), and this may explain the weakened expression of the PPX gene (decompose poly-P to Pi) and PPK gene (synthesize Pi to poly-P) in the dark. Overall, dark condition a induced gene changes for amo, Hao, narG, PPX and PPK, all of those pointing to NO2, NO3, P being involved in denitrifying phosphorus removal, which needs further research.
Figure 6

Metabolic genes of activated sludge, bac–alg dark, and bac–alg light according to KEGG database.

Figure 6

Metabolic genes of activated sludge, bac–alg dark, and bac–alg light according to KEGG database.

Close modal

In the dark, increasing inoculum ratio (sludge/Chlorella) in the range of 1:0.5–1:2 enhanced N and P removal. SRT only affected P removal. COD removal was not impacted by inoculum ratio and SRT. With sludge/Chlorella 1:2 and an SRT of 15 d, performance in the dark was comparable with that in the light, due to suppression of algae and favoring bacteria by aeration. Algae decreased Chla/Chlb and increased Caro/(Chla + Chlb) to respond to oxidative stress in the dark, while all these ratios increased in the light. In the dark, Chlorella enriched Nitrosomonas and posed no threat to Nitrospira, but phycosphere bacteria Flavobacterium and Terrimonas departed from algae. At the same time, nitritation genes (amo, Hao) and denitrifying gene (narH) were up-regulated, while P metabolism genes (PPX and PPK) were down-regulated. In the light Chlorella enriched the DPAOs of Dechloromonas and Flavobacterium. It is proposed to establish bacteria–algae consortia in the dark first and then switch to a night/day diel cycle, possibly to develop a short-cut nitrification–denitrifying phosphorus removal for practical application.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

This work was financially supported by National Environmental Protection Mining and Metallurgical Resource Utilization and Pollution Control Key Laboratory Open Fund (HB201915); and China Scholarship Council (201808420103).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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