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Article

Research article

J. Microbiol. Biotechnol. 2019; 29(12): 1957-1968

Published online December 28, 2019 https://doi.org/10.4010/jmb.1910.10046

Copyright © The Korean Society for Microbiology and Biotechnology.

Assessment of the Dynamics of Microbial Community Associated with Tetraselmis suecica Culture under Different LED Lights Using Next-Generation Sequencing

Su-Jeong Yang 1, Hyun-Woo Kim 1, Seok-Gwan Choi 2, Sangdeok Chung 2, Seok Jin Oh 3, Shweta Bharat Borkar 4 and Hak Jun Kim 4*

1Interdisciplinary program of Biomedical, Mechanical and Electrical Engineering, Pukyong National University, Busan, 48513, Republic of Korea, 2National Institute of Fisheries Science (NIFS), Busan, 46083, Republic of Korea, 3Department of Oceanography, Pukyong National University, Busan 48513, Republic of Korea, 4Department of Chemistry, Pukyong National University, Busan 48513, Republic of Korea

Correspondence to:Hak Jun  Kim
kimhj@pknu.ac.kr

Received: October 21, 2019; Accepted: November 12, 2019

Abstract

Tetraselmis is a green algal genus, some of whose species are important in aquaculture as well as biotechnology. In algal culture, fluorescent lamps, traditional light source for culturing algae, are now being replaced by a cost-effective light-emitting diodes (LEDs). In this study, we investigated the effect of LED light of different wavelengths (white, red, yellow, and blue) on the growth of Tetraselmis suecica and its associated microbial community structures using the next-generation sequencing (NGS). The fastest growth rate of T. suecica was shown in the red light, whereas the slowest was in yellow. The highest OTUs (3426) were identified on day 0, whereas the lowest ones (308) were found on day 15 under red light. The top 100 OTUs associated with day 0 and day 5 cultures of T. suecica under the red and yellow LED were compared. Only 26 OTUs were commonly identified among four samples. The highest numbers of unique OTUs were identified at day 0, indicating the high degree of initial microbial diversity of the T. suecica inoculum. The red light-unique OTUs occupied 34.98%, whereas the yellow-specific OTUs accounted for only 2.2%. This result suggested a higher degree of interaction in T. suecica culture under the red light, where stronger photosynthesis occurs. Apparently, the microbial community associated with T. suecica related to the oxygen produced by algal photosynthesis. This result may expand our knowledge about the algaebacteria consortia, which would be useful for various biotechnological applications including wastewater treatment, bioremediation, and sustainable aquaculture.

Keywords: Next-generation sequencing, metagenomics, LED, microalgae, microbial commnuity

Introduction

Tetraselmis is a green algal genus, some of whose species are widely aquacultured as good food sources for bivalves, penaeid shrimp larvae, and rotifers [1]. These marine microalgae are known to have a large spectrum of antimicrobial activity [2, 3] along with high potential as a probiotic for fish [4]. Tetraselmis has also been proposed as a source of vitamins or fatty acids for humans and animals [5-7]. In addition, mass culturing of Tetraselmis is essential for biofuel production and has been carried out in various studies [8, 9]. As one of the cost-effective algal culture system, the traditional fluorescent lamps are now being replaced by a light-emitting diodes (LEDs) for its longer lifespan and higher electrical efficiency

Since microalgae are photosynthetic organisms, light is the most important factor in culturing them. Many studies on algae were performed to understand the wavelength dependence of the photosynthesis process, while the effect of the exposure to different light spectra has been much less investigated [10]. Microalgae require optimal light conditions to achieve maximum photosynthetic rate economically [11]. Located at the bottom of the aquatic food chain, microalgae are autotrophic organisms that produce organic matter through photosynthesis. They form colonies or are surrounded by a microbiome of mucous substances called the ‘phycosphere,’ where many bacteria are attached and symbiotic. Strong interactions between microalgae and bacteria occur in the phycosphere and can have either a positive or negative effect on each other. Bacteria provide microalgae with CO2, inorganic nutrients, and vitamin sources, but obtain the oxygen and extracellular substances generated by microalgae. Microalgae and bacteria exist together in almost all aquatic environments and play key roles in nutrient cycling and energy flow [12, 13].

Microbial communities are usually examined by morphological identification. However, since the bacterial communities are difficult to observe directly, they are first separated by isolation and then analyzed using methods such as clone libraries or RFLP [14, 15], which requires a lot of time and effort. Next-generation sequencing (NGS) is a technique used to quickly analyze microbiota in detail without isolating the microorganism separately [16, 17]. There are two ways; the first is a nucleotide sequence analysis targeting 16S rRNA and the second is a shotgun method. We chose the former, using DNA barcodes. The 16S rRNA has a conserved region common to all species and a hypervariable region which is used as a DNA barcode that can classify specific species. With NGS, metagenomic analysis makes it possible to identify all species in a sample, even those that are present in low abundance. The Illumina Miseq platform in particular generates a large number of high-quality sequence reads that enable detection of the microbial taxa across a high number of taxonomic profiles from samples [18].

It was confirmed that the growth of microalgae varied depending on different wavelengths [11, 19]. As a result, interacting microorganisms are affected by wavelength or the rate of photosynthesis of algae. However, little research has been done on the effect of light wavelengths on the algae-microbiome community structure. In this study, we investigated the effect of LED light of different wavelengths (white, red, yellow, blue) on the growth rate of T. suecica and its associated microbial communities using next-generation sequencing (NGS) technology.

Materials and Methods

Culture

The experimental species T. suecica was received from the Library of Marine Samples, KIOST, Korea. For the culture, f/2 medium was used, which was filtered (0.22µm pore size, Millipore GSWP) with selenium to a final concentration of 0.001 µM. The medium was maintained at 20°C, 30 psu, with light intensity of about 100 µmol/m2/s (12L: 12D; cool-white fluorescent lamp). The experimental instruments were UV-treated for 20 min or more, and all experiments were performed on a clean bench.

As a light source, a fluorescent lamp with multiple wavelengths, a red light (650 nm), a yellow light (590 nm), and a blue light (450 nm) were used. The microalgae were grown to a late stage of the logarithmic growth phase under a cool-white fluorescent lamp (12L: 12D) at 20°C, 30 psu and then inoculated to a final density of cells with about 1.0 × 102 in f/2 medium 3L [20]. For each condition, two bottles were used.

Genomic DNA Extraction

From the mass cultured samples, 15 ml was filtered through a 0.45 µM GN-6 membrane filter (Pall Corporation, USA) every 5 days until the 25th day. Next, the filters were homogenized with a TissueLyser II (QIAGEN, Germany) and incubated in a heat block at 60°C for 2 h. Then, genomic DNA was extracted using a DNeasy Plant Mini Kit (QIAGEN) following the manufacturer’s instructions and stored at -70°C until used as a template for qPCR and library preparation.

Quantitative PCR Analysis of T. suecica

Genomic DNA was quantified by quantitative real-time PCR (qPCR) with phytoplankton primers P23MISQF1 and P23MISQR1 targeting plastid 23S ribosomal DNA and 341F and 785R targeting 16S ribosomal DNA to measure the relative number of T. suecica and microbial community, respectively (Table 1). The PCR mixture (20 µl) contained 4 µl ultrapure water, 1 µl forward and reverse primer (10 µM)), 10 µl 2X SYBR Green Premix Ex Taq II (Takara Bio Inc., Japan) and 4 µl genomic DNA as a template. Real-time PCR was carried out under the following conditions: initial denaturation step at 94°C for 3 min, followed by 35 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 30 sec. The process was completed with a final extension at 72°C for 5 min. A standard curve was constructed using plasmid containing each primer set with a range of 0.01 pg to 0.01 ng [21, 22]. The reaction was performed using a DNA Engine Chromo 4 Real-Time PCR Detection System (Bio-Rad, USA).

NGS Library Preparation and Sequencing

In order to analyze the microbial community structures associated with the growth of T. suecica, cultures at day 5 and day 15 under the red and yellow LED lights were harvested and samples at day 0 were used as a control. The first PCR was conducted using 341F and 785R with overhanging adaptors for MiSeq Sequencing (Table 1). The PCR mixture (20 µl) contained 1 µl primer (10 µM, forward and reverse), 0.1 µl Ex Taq DNA polymerase (TaKaRa), 2 µl Ex 10X Buffer, 2 µl dNTPs (0.5 µM, TaKaRa), ultrapure water and a template. The amounts of ultrapure water and template were adjusted to have the same DNA concentrations for the library construction as well as the samples. The PCR was performed under the following conditions: initial denaturation step at 94°C for 3 min, followed by 10 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 30 sec. The process was completed with a final extension at 72°C for 3 min. The first PCR products were separated by 1.5% agarose gel electrophoresis and stained with loading star dye (Dynebio, Korea). Amplicons with the expected size (511 bp) were cut from the gel and purified using an AccuPrep Gel Purification Kit (Bioneer, Korea) for the second PCR, which was performed using Illumina Nextera XT indexing primers (Table 1). The PCR mixture (20 µl) contained 9.3 µl of ultrapure water, 1 µl primer (10 µM, forward and reverse), 0.5 µl Phusion High Fidelity DNA polymerase (NEB, UK), 4 µl 5X Phusion Buffer, 0.5 µl dNTPs (10 µM, TaKaRa) and 4 µl purified first PCR products as a template and the PCR was carried out under the following conditions: initial denaturation step at 94°C for 3 min, followed by 15 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 30 sec. The process was completed with a final extension at 72°C for 3 min. Then, gel purification was performed as described above. The quality and quantity of the libraries were measured using a 2100 Bioanalyzer (Agilent Technologies, USA) and sequencing was performed at 300 bp paired-end reads with a MiSeq sequencer (Illumina, USA).

Bioinformatics of NGS Data

Among the raw data, sequences with under QV 20 and read length less than 100 nucleotides were trimmed using the CLC Genomic Workbench v.8.0 (CLC Bio, USA). End-paired amplicons were constructed with over 6 bp overlapping sequences and omitting any mismatches option, size selection (400~500 bp), and primer trimming with the pdiffs=1 option were performed using Mothur software v.1.35.0 [23]. Operational taxonomic units with 99.6% similarity cutoff were clustered and chimeras were removed using UCHIME software v.8.1 (http://drive5.com/uchime). OTUs with less than 0.001% of total reads were removed. The sequences of OTUs were compared against known species from the NCBI-NT database using BLAST (BLASTN, version 2.2.30+). OTU sequences with more than 97% identity to the database were assigned to the top-hit species names while genus names were assigned for OTUs with 90~96% identity. OTUs with less than 90% identity to the database were described as “unclassified.” The Venn diagram was generated with Draw Venn Diagram (http://bioinformatics.psb.ugent.be/webtools/Venn/ ).

Results

Quantitative Analysis of Microbial Community

According to qPCR result with P23MISQF1 and P23MISQR1 primer set, the fastest growth rate of T. suecica was identified under the red LED light followed by white, blue and yellow (Fig. 1A). The rate was steadily increased in all wavelengths during the study period, but not in the red wavelength on day 25. The 341F and 785R primer is a universal primer set that amplifies the 16S rRNA region of microorganisms. The number of microorganisms increased steeply after one day of cultivation, reaching a peak and showing fast growth rate compared with T. suecica (Fig. 1B). Thereafter, microbial copy numbers did not show any significant changes, indicating the limit of nutrition in the culture. It was noteworthy that the lowest copy numbers of total microorganism were also shown in the culture under the yellow light throughout the culture time. This may have come from the low amount of organic carbon source by T. suecica under the light. As shown in Fig. 1C, the ratio of T. suecica to total bacteria was low until day 10 of inoculation, but this ratio increased significantly thereafter.(Fig. 1C). This result indicated the exponential growth of T. suecica approximately 10 days after inoculation.

Community Structures Generated by Next-Generation Sequencing

Microbial community structures associated with the growth rates of T. suecica were analyzed by a next-generation sequencing (NGS) technique using 341F and 785R primer. The cultures on days 5 and 15 under the red light were chosen as ‘fast-growing’ microbial communities, whereas those under the yellow light were named ‘slow-growing’ communities. The day 0 community was analyzed as the control. All OTUs were assigned to species if the similarity was 97% or more, to genus if similarity was 90-96%, and to unclassified if less than 90%. Most OTUs showed more than 97% sequence identity to the database. The obtained OTUs numbers ranged from 308 to 3426. The highest OTU numbers were identified on day 0 (3426), whereas the lowest ones were found on day 15 under the red light (15R). For our convenience, OTUs with lower than 0.001%of total reads were eliminated from further analysis, which occupied approximately 2–4% of total read numbers. Obtained OTUs were classified into 1 phytoplankton phylum including Chlorophyceae and 8 bacterial classes including Actinobacteridae, Alphaproteobacteria, Cyto-phagia, Flavobacteria, Gammaproteobacteria, Phycisphaerae, Planctomycetacia, and Sphingobacteria (Table 2). Smaller class numbers were identified in the red lights (17 on day 15 and 21 on day 5), whereas its higher numbers were found in the yellow light (29 on both day 15 and day 5). Day 0 showed the highest microbial class numbers. Collectively, lower microbial taxa were identified in the ‘fast-growing’ T. suecica cultures, suggesting strong photosynthesis has an adverse effect in several microbial classes such as Planctomycetia, which was identified only in the yellow light (Table 2).

Microbial community structures with different culture times and lights were compared (Table 3 and Fig. 2). T. suecica dominated in all the examined cultures except for day 5 under yellow light (5Y). On day 0, T. suecica occupied about 34% followed by M. roseacus (30%), Rhabdobacter sp (8%), and Halomonas sp. (7%). In 5R, T. suecica accounted for about half of the community, 21% Halomonas sp., 17% Alteromonas australica, 6% M. roseacus. In day 5 under the yellow light (day 5Y), M. roseacus occupied 38% followed by 11% of Pseudomonas sp., and 6% of Rhabdobacter sp. On day 15, M. roseacus accounted for 37% and 33% in the red and yellow lights, respectively. M. roseacus was dominant compared to other bacteria (Fig. 2A). Except for T. suecica, the community structure of 5R appeared different than 5Y compared to the day of inoculation. On day 15, there were only a small number of bacteria that were present on day 5, and M. roseacus was most dominant. (Fig. 2B).

Microbial community structures associated with T. seucica cultures under the LED lights with two different wave-lengths were compared (Fig. 3). First, we compared the top 100 OTUs among day 0, day 5 under the yellow (5Y) and red (5R) using the Venn-diagram (Fig. 3A). Only 26 OTUs were commonly identified among day 0, 5R, and 5Y. The highest numbers of unique OTUs were identified at day 0 indicating the high degree of initial microbial diversity of the T. suecica inoculum. The highest proportion of unique OTUs were identified in the red light (34.98%), whereas the yellow-specific OTUs occupied only 2.2% (Table 4-1) This result suggested that a higher degree of interaction in T. suecica culture under the red light, in which its strong photosynthesis occurs. By contrast, the highest proportion of shared OTUs with those in day 0 were identified in 5Y (19%) compared with those in 5R (Table 4-1 and Fig. 3A).

On day 15, compared with the remaining OTUs in the red and yellow wavelengths, the numbers of shared OTU were 37, but the shared proportions were 97.31% and 91.2%, respectively, in which M. roseacus was the most abundant bacteria (Table 4-2). Duplicated experiments were conducted to determine the microbiota associated with the growth of photosynthetic T. seucica (Figs. 3C and 3D). On day 15, the microbial communities under the red light exhibited a high degree of similarity sharing 53 OTUs with 98.56% and 97.93% identity in their proportions. By contrast, microbial communities in duplicated experiments under the yellow light showed higher degree of dissimilarity, sharing only 13 OTUs with 62.73% and 3.89% identity (Fig. 3D). This result suggested that the microbial community associated with T. suecica is strongly related to photosynthesis.

The reproducibility of the microbial community associated with T. suecica was tested by the replication of the experiment (Table 4-3,4). We found that 53 OTUs shared between two independent cultures under the red light on day 5 occupied 99% and 98%, respectively (Fig. 3C). Although the numbers of unique OTUs in each culture under the red light were 43 (5R-1) and 41 (5R-2), their proportions were negligible, indicating that the microbial community associated with the growth of T. suecica was not a result of random combination of bacterial components. For the slow growth T. suecica under the yellow light, which exhibited the low photosynthetic efficiency, only 13 OTUs were shared and their proportions were 63% and 96%, respectively, depending on the growth of T. suecica (Table 4-3 and Fig. 3C). Collectively, on day 5, the efficiency of photosynthesis of T. suecica may have been the critical factor in determining microbial community.

Discussion

In this study, we investigated the effect of the LED light with different wavelengths (white, red, yellow, blue) on the growth rate of T. suecica and its associated microbial communities using next-generation sequencing (NGS) technology. Analysis of microbial community structure using NGS techniques revealed significantly higher diversity than the traditionall methods including the clone libraries or DGGE community profiling [24]. The primer set used in the present study, 341F andas been proven to show the wide range of microbial taxa coverage with little non-specific amplification [25, 26]. The results of artificial conditions in the laboratory are essential to understanding the growth characteristics in outdoor cultures [27]. The culture was non-axenic, which is associated with bacteria present in the natural environment and cultured with algae [16]. Besides, the non-axenic microalgae cultures are applied in the green-water technique, and it is important to recognize the microbiota associated with the microalgae cultures [28].

A light regime generally produces the most intense photosynthesis at wavelength from 575 to 720 nm, and is most effective in the red (650~680 nm) and blue (400~500 nm). According to the previous study, the growth rate of T. suecica under different types of wavelengths was reported to be fast in order of white, red and blue [29], but in this study, red had the fastest growth rate followed by white, blue, and yellow. This result may be due to the difference in the white light source. The spectrums of commercially available white light lamps are different and the white fluorescent lamp in this study may not be effective as one in another study. Further study should be conducted to compare white lamps with different spectrums. The samples cultured until the 25th day seemed to reach the stationary phase and the red wavelength with the fastest growth seemed to be the death phase from the 15th day presumably due to the nutritional limit in the culture (Fig. 1).

After a day of inoculation, the ratio of T. suecica to bacteria is low because bacterial growth is much faster than eukaryotic microalgae consuming the organic nutrients in the subculture, but soon its growth rate is decreased by the limited amount of the organic nutrient before the growth of T. suecica, which further provides it by photosynthesis (Fig. 3). In fact, we have found that T. suecica was the least abundant among the samples at the slowest growing yellow wavelength (Fig. 4). This appears to be due to the relatively low photosynthesis of algae at the yellow wavelength providing the low amounts of organic matter for bacterial use.

While the proportion of other bacteria decreased over time, only M. roseacus increased in the culture of T. suecica (Fig. 4). Marivita is a heterotrophic and strictly aerobic bacterium, which is closely associated with the algae [30]. Therefore, given the high number of T suecica, the higher amount of the produced oxygen may have facilitated the growth of this bacterium. M. roseacus is a novel species that was first reported to be isolated from the surface of a coccolithophore. It appears to be beneficial to the growth of algae, which may exhibit specific dependence between bacteria and algae even though the genus Marivita may be a product induced by artificial laboratory culture experiments [30]. Probably because of its special metabolic pathway to algae, it may occupy half of the community composition on day 15 and have growth priority compared to other bacteria. So, M. roseacus seemed to be predominant despite the different wavelengths (Fig. 2). Alternatively, M. roseacus is known to produce bacteriochlorophyll a, which can survive by photosynthesis in conditions with limited organic carbon sources [31]. Certain bacteria have been reported to exert an effect on microalgae, indicating that the combination of microalgae and bacteria may be decisive for co-culture [12].

It is conceivable that bacteria will interact with microalgae with nutrients during the culture. Here, we demonstrated that fast-growing bacteria consumed organic nutrients quickly in the subculture, and metabolites generated by bacterial communities affected the growth of the microalgae as well. However, it is surprising to find out that the remaining bacterial community on day 15 shared about half of its OTUs and its proportion of contigs was more than 90% (Table 4-2 and Fig. 3B). The community structures between the two samples were also highly similar to each other. A similar result was also shown in the study by Han, in which bacterial density remained at a similar level by consuming the original organic substance and resulted in a similar microalgal density [12]. Therefore, the fast-growing bacteria determined the initial microbial community with little effect by the low-numbered microalgae. Although the growth of both microalgae and bacteria is affected by their complex interactions, the initial community composition appears to be determined by the random composition of the inoculated bacteria in the subcultured samples. Thereafter, the determined bacterial community can be harmful or beneficial to the growth of a microalgae affecting its growth. The experiment was duplicated per each condition, and the community structures of two cultures were compared (Fig. 4). Photosynthesis occurred well in the red wavelength, and the microbial community was rapidly transformed so that the community structure was similar on day 5. On the other hand, the yellow wavelength had relatively slow photosynthesis, and the bacteria showed more influence on each other. The number of OTUs shared within the two cultures was small even under the same condition due to the randomly inoculated bacteria, as expected (Table 4-4 and Figs. 3C and 4).

As a result, the red wavelength has a positive effect on the growth of T. suecica. However, its growth was also affected by the randomly established initial bacterial community structure, which may be related to the difference in the metabolites the bacteria release. As photosynthetic microalgae growth increases in 5-10 days after inoculation, consuming the carbon dioxide produced by the heterotrophic bacteria, the initial microbial community continues to change, optimizing themselves in the oxygen-rich environment. In fact, aerobic bacteria can promote microalgal growth by reducing the photosynthetic oxygen in nature [32]. We could therefore expect that the remaining species would be aerobic heterotrophic or photosynthetic bacteria (Table 5). On day 15, all remaining species in the red and yellow lights were aerobic bacteria due to oxygen produced by the photosynthesis of T. suecica. Especially, M. roseacus seems to be the most dominant because it is aerobic and can photosynthesize. This study can be taken further by adding organic matter or specific bacteria and more algae. Actually, earlier studies proposed that amino acids and vitamins regulate the relationship between microalgae and bacteria [33, 34]. When cultured in medium with extra additives, beneficial effects were enhanced extending our knowledge of interaction between the microalgae and its associated bacteria [12].

In conclusion, we herein introduced the NGS technique to analyze the precise microbial community structure changes during the culture of T. suecica, which has been difficult and complicated to accomplish by conventional methods. As a result, we were able to extend our knowledge about the interaction between microalgae and heterotrophic bacteria in a complicated aquatic microbial ecosystem. Algae-bacteria consortia can be seen as a very important concept in understanding the aquatic environment and ecosystem, and may also provide important knowledge for biotechnological applications including in wastewater treatment, bioremediation, and sustainable aquaculture [35].

Acknowledgment

This study was supported by a grant from the National Institute of Fisheries Science (R2019021).

Conflict of Interest

The authors have no financial conflicts of interest to declare.

Fig 1.

Figure 1.Quantitative PCR result of Tetraselmis suecica and its associated microorganisms grown under the four different wavelength LED lights. (A) The relative copy numbers of T. suecica measured by the plastid 23S rDNA. (B) The relative copy numbers of microorganisms by the numbers of 16S rRNA. (C) The ratio of T. suecica to total bacteria in different cultivation times.
Journal of Microbiology and Biotechnology 2019; 29: 1957-1968https://doi.org/10.4010/jmb.1910.10046

Fig 2.

Figure 2.Microbial community structure at species level on day 0, day 5 of the red and yellow wavelengths with T. suecica included (A) and excluded (B). Each bar shows the proportion of microbial species according to 97 % sequence similarity.
Journal of Microbiology and Biotechnology 2019; 29: 1957-1968https://doi.org/10.4010/jmb.1910.10046

Fig 3.

Figure 3.Three-way Venn diagram illustrating the number of shared and specific OTUs among the day of inoculation and day 5 (A), between the red and yellow wavelengths on day 15 (B), between same wavelengths of red light (C), and yellow light (D).
Journal of Microbiology and Biotechnology 2019; 29: 1957-1968https://doi.org/10.4010/jmb.1910.10046

Fig 4.

Figure 4.Bacterial community structures at the species level on day 5 of the red and yellow wavelengths.
Journal of Microbiology and Biotechnology 2019; 29: 1957-1968https://doi.org/10.4010/jmb.1910.10046

Table 1 . Primers used in this study..

NameSequence (5' to 3')Target region
341FCCTACGGGNGGCWGCAG16S
785RGACTACHVGGGTATCTAATCC16S
P23MISQF1GGACARWAAGACCCTATGMAG23S
P23MISQR1AGATYAGCCTGTTATCCCT23S
Forward adapterTCGTCGGCAGCGTCAGATGTGTATAAGAGACAG
Reverse adapterGTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG

Table 2 . Summary of OTUs generated by 16S universal primers at day 0, 5, and 15 samples under the red and yellow lights..

ClassDay 0Day 5 - RedDay 5 - YellowDay 15 - RedDay 15 - Yellow

OTUsProportion (%)OTUsProportion (%)OTUsProportion (%)OTUsProportion (%)OTUsProportion (%)
Actinobacteridae11.72
Alphaproteobacteria1336.3277.151244.21738.781438.20
Chlorophyceae134.23150.08123.21155.38154.33
Cytophagia28.1516.2110.8911.58
Flavobacteriia10.1210.2610.22
Gammaproteobacteria1818.091041.051122.3552.7773.05
Phycisphaerae11.1411.2512.5711.5711.46
Planctomycetia10.9920.63
Sphinogobacteriia10.2310.2210.3310.3920.50
Unclassified10.1410.25
Total38100.0021100.0029100.0017100.0029100.00

Table 3 . Top 20 OTUs associated with day 0, day 5, and day 15 samples of T. suecica under the red and yellow LED lights..

NoDay 0Day 5 -RedDay 5 -YellowDay 15 -RedDay 15 -Yellow

SpeciesGenBank numberProportion (%)SpeciesGenBank numberProportion (%)SpeciesGenBank numberProportion (%)SpeciesGenBank numberProportion (%)SpeciesGenBank numberProportion (%)
1Tetraselmis suecicaKU16709734.00Tetraselmis suecicaKU16709750.08Marivita roseacusNR_13266238.34Tetraselmis suecicaKU16709755.38Tetraselmis suecicaKU16709754.33
2Marivita roseacusNR_13266230.15Halomonas sp.KY47401820.78Tetraselmis suecicaKU16709723.21Marivita roseacusNR_13266237.26Marivita roseacusNR_13266231.99
3Rhabdobacter sp.NR_1477507.88Alteromonas sp.KP09995816.72Pseudomonas sp.KY02031811.38Halomonas sp.KY4740182.09Stappia indicaKY6162462.84
4Halomonas sp.LT9341707.55Marivita roseacusNR_1326626.01Rhabdobacter sp.NR_1477506.21Unclassified1.57Rhabdobacter sp.NR_1477501.58
5Marinobacter lipolyticusKX8180422.96Marinobacter adhaerensKY6018711.88Halomonas sp.KY4740185.10Rhabdobacter sp.NR_1477500.89Unclassified1.46
6Stappia indicaMF9283722.25Unclassified1.25Unclassified2.57Oceanicaulis alexandriiFN5624020.55Alcanivorax sp.KU6815061.19
7Rhodococcus fasciansMG2056331.71Halomonas sp.KY4740180.33Rhodobacteraceae bacteriumKM2790141.79Unclassified0.39Rhodobacteraceae bacteriumKM2790140.83
8Phyllobacteriaceae bacteriumKM2790121.47Ahrensia kielensisKM6131500.32Legionella sp.KU5087931.42Phyllobacteriaceae bacteriumKM2790120.33Legionella sp.KU5087930.81
9Pseudomonas stutzeriMF3834631.29Pseudoalteromonas lipolyticaLC2218450.32Marinobacter lipolyticusKX8180421.30Stappia sp.LT6297840.24Marivita roseacusNR_1326620.65
10Alteromonas sp.MG0104451.14Thalassospira sp.LN8683900.28Stappia indicaKY6162461.20Alteromonas australicaKP0999580.23Unclassified0.54
11Unclassified1.13Mesoflavibacter zeaxanthinifaciensNR_1140330.26Planctomyces marisNR_0253270.99Arenibacter sp.KU9481540.22Planctomyces marisNR_0253270.49
12Marinobacter alkaliphilusMG0294541.06Legionella sp.KU5087930.25Alteromonas macleodiiKY4364470.90Marivita roseacusNR_1326620.18Stappia indicaKY6162460.40
13Pseudomonas xinjiangensisKU6012731.04Unclassified0.22Marinobacter adhaerensKY6048710.78Methylophaga sp.KC2953430.15Unclassified0.36
14Marinobacter adhaerensKY6048710.76Vibrio harveyiKY6976830.22Phyllobacteriaceae bacteriumKM2790120.70Legionella sp.KU5087930.15Unclassified0.25
15Pseudomonas sp.KX0000120.48Alteromonas additaKY7871600.22Alcanivorax sp.KU6815060.47Marinobacter adhaerensKY6048710.15Thalassospira sp.LN8683900.24
16Oceanicaulis alexandriiFN5624030.38Methylophaga sp.KC2953430.19Marinobacter sp.LT2212580.40Stappia indicaKY6162460.12Oceanicola nitratireducensNR_1163690.22
17Pseudoalteromonas prydzensisKX4171430.29Hyphomonas sp.KM27900180.17Marivita roseacusNR_1326620.37Thalassospira sp.LN8683900.10Oceanicaulis alexandriiFN5624030.19
18Hoeflea sp.KC4690760.28Halomonas sp.KX7800670.15Unclassified0.33Marivita roseacusNR_1326620.17
19Sphingomonas sp.KX4192270.25Stappia sp.LT6297840.10Stappia indicaKY6162460.33Marivita roseacusNR_1326620.17
20Unclassified0.23Phyllobacteriaceae bacteriumKM2793750.12Hoeflea sp.KC4690760.32Pseudomonas sp.KY0203180.16

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