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Article

Changes in Free-Living and Particle-Associated Bacterial Communities Depending on the Growth Phases of Marine Green Algae, Tetraselmis suecica

1
Department of Biotechnology, Sangmyung University, Seoul 03016, Korea
2
Marine Ecosystem Research Center, Korea Institute of Ocean Science and Technology, Busan 49111, Korea
3
Key Laboratory of Marine Ecosystem and Biogeochemistry, State Oceanic Administration & Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2021, 9(2), 171; https://doi.org/10.3390/jmse9020171
Submission received: 23 January 2021 / Revised: 4 February 2021 / Accepted: 5 February 2021 / Published: 8 February 2021
(This article belongs to the Special Issue Taxonomy and Ecology of Marine Algae)

Abstract

:
Bacteria are remarkably associated with the growth of green algae Tetraselmis which are used as a feed source in aquaculture, but Tetraselmis-associated bacterial community is characterized insufficiently. Here, as a first step towards characterization of the associated bacteria, we investigated the community composition of free-living (FLB) and particle-associated (PAB) bacteria in each growth phase (lag, exponential, stationary, and death) of Tetraselmis suecica P039 culture using pyrosequencing. The percentage of shared operational taxonomic units (OTUs) between FLB and PAB communities was substantially high (≥92.4%), but their bacterial community compositions were significantly (p = 0.05) different from each other. The PAB community was more variable than the FLB community depending on the growth phase of T. suecica. In the PAB community, the proportions of Marinobacter and Flavobacteriaceae were considerably varied in accordance with the cell number of T. suecica, but there was no clear variation in the FLB community composition. This suggests that the PAB community may have a stronger association with the algal growth than the FLB community. Interestingly, irrespective of the growth phase, Roseobacter clade and genus Muricauda were predominant in both FLB and PAB communities, indicating that bacterial communities in T. suecica culture may positively affect the algae growth and that they are potentially capable of enhancing the T. suecica growth.

1. Introduction

Marine green microalga genus Tetraselmis is well-known to have a high lipid content and fast growth [1,2], and thus it has been widely used in multiple industries, for example, a source of nutrition for invertebrates in aquaculture [3], feedstock of biofuel production [4], and cosmetic applications [5]. In order to save the cost for algal production, there have been attempts to advance the algal-culture technique which enables gaining a higher biomass of this green algae.
Algal-culture techniques have been developed based on adjusting physiochemical factors (e.g., light intensity, nutrient limitation, temperature, pH, CO2 concentration, and salinity) which are well known to have an intimate association with algal growth [6,7]. Recently, bacteria which have a symbiotic relationship to algae have been considered as a new factor to advance the algal-culture technique, allowing to gain a higher algal biomass. Bacteria can affect the growth of algae in various ways which ranged from mutualism to parasitism [8,9,10,11,12]. Interestingly, the maximum algal cell density is obviously enhanced when symbiotic bacteria are added to the algal culture, compared to that in the optimum culture condition (e.g., culture media, temperature, salinity, pH, etc.) without bacteria, for example, the biomass productivity of T. striata was enhanced up to two-fold by the addition of two bacterial strains (Pelgibacter bermudensis and Stappia sp.) [4]. These findings show the possibility that bacteria can be an important factor to advance a culture technique for algae.
Due to the high economic value of T. suecica, studies on developing the mass culture technique for this algae have been carried out, and in order to advance this culture technique, bacteria which enhanced the algal growth were isolated more recently [13,14]. Thus, understanding mutualism between T. suecica and co-existing bacteria is thought to be important, but there is a significant knowledge gap for this ecological relationship due to a lack of evidence. The two bacterial groups exist in the algal culture. These include free-living (FLB) and particle-associated (PAB) bacteria which are phylogenetically distinct. Based on previous findings, these two groups are closely associated with the growth of algae even though PAB showed stronger species-specific association to the host algae [8,15,16,17]. In addition, their community compositions are distinctly varied depending on the growth phase of algae due to the change in composition and quantity of dissolve organic matters (DOM) released from the host algae. However, in previous studies, only the FLB composition was identified, and the previous analysis method (terminal restriction fragment length polymorphism) may not be adequate to gain a high resolution for the characterization of bacterial community composition in T. suecica culture due to the methodological limitation [13].
The present study aims to elucidate bacterial taxa which were associated with the growth of T. suecica. To address this, we investigated the community composition of both FLB and PAB and a variation in the two bacterial groups depending on the growth phase of T. suecica with the next generation sequencing (NGS) approach, allowing a high taxonomic resolution.

2. Materials and Methods

2.1. Algal Culture and Cell Growth Analysis

A culture of T. suecica P039 (cell size: Average 16.2 μm length and 10.6 μm width in 33 cells) which was isolated from coastal water in Deukryang Bay, Korea, was obtained from the Korea Marine Microalgae Culture Center (Pukyong National University, Busan, Korea). It has been maintained in an autoclaved f/2 medium [18] at 20 °C in a 12:12 h light:dark cycle with a photon flux density of approximately 65 µmol photons m−2 s−1. The growth stage of T. suecica was determined based on the growth curve (Figure S1).
Cell growth curves were analyzed at every 2-day intervals using cell numbers measured with the Sedgwick-Rafter counting chamber. At the same time, bacterial cells were counted by using the 4′,6-diamidino-2-phenylindole (DAPI) (D9542, Sigma-Aldrich, Darmstadt, Germany) staining method [19]. Briefly, all glass wares and reagents were sterilized with 10% nitric acid treatments and filtration with a 0.22 μm nuclepore membrane (Millipore, Cork, Ireland), respectively. As for bacteria counting, 20 mL of cultures was preserved with 1 mL of formaldehyde (37% formaldehyde), and then stored at 4 °C and a dark condition. For DAPI staining, we mixed 1 mL of the preserved cultures and 100 μL of DAPI (0.1 μg mL−1), and incubated it for 5 min. Then, the cells were filtered through the pore size 0.2 μm black filter (Isopore membrane; Millipore, Bedford, MA, USA) using a hand pump with less than 178 mmHg in pressure. The filters were mounted on an objective slide, and observed using a fluorescent microscope (Axioskop, Carl Zeiss, Oberkochen, Germany).

2.2. Sample Collection and DNA Extraction

To investigate a change in the bacteria community composition depending on the growth stages, the T. suecica culture was harvested in lag (day 2), exponential (day 8), stationary (day 20), and decline (day 32) growth phases. In addition, we used the size-fractionated filtration method for collecting the separate bacteria of both PAB and FLB from the culture. One hundred mL of T. suecica culture were filtered sequentially through a 10 μm (PAB) and 0.2 μm (FLB) pore size membrane filter (diameter: 47 mm; Millipore, Cork, Ireland). Each loaded filter was immediately placed in a 2-mL microtube (Axygen Sciences, CA) that contained 800 μL extraction buffer (100 mM Tris-HCl, 100 mM Na2-EDTA, 100 mM sodium phosphate, 1.5 M NaCl, 1% CTAB) and was then stored at −80 °C until the DNA was extracted.
The DNA was extracted using a modified CTAB protocol [20]. Briefly, 2 mL of microtubes containing membrane filters and the extraction buffer (100 mM Tris-HCl, 100 mM Na2-EDTA, 100 mM sodium phosphate, 1.5 M NaCl, 1% CTAB) were subjected to three cycles of immersion in liquid N2 until completely frozen and then thawed in a 65 °C water bath. After 8 µL of proteinase K was added (10 mg mL−1 in TE buffer), the samples were incubated at 37 °C for 30 min. Then, after the addition of 80 µL of 20% sodium dodecyl sulfate (SDS), the samples were incubated at 65 °C for 2 h, shaken gently with an equal volume of chloroform-isoamyl alcohol (24:1), and then centrifuged at 10,000× g for 5 min. The aqueous phase was transferred to a new 2 mL tube containing 88.8 µL of 3 M sodium acetate (pH 5.1), and 587 µL of isopropanol (≥99%) was added. Following centrifugation at 14,000× g for 20 min, the supernatant was decanted, 1 mL of cold 70% ethanol was added, and the samples were centrifuged at 14,000× g for 15 min. The pellets were air dried at room temperature before being dissolved in 100 µL of TE buffer (10 mM Tris-HCl, 1 mM EDTA; pH 8).

2.3. Pyrosequencing

Metagenomic sequencing was performed using the 454 GS FLX Titanium Sequencer System (Roche, Basel, Switzerland). Briefly, target rDNA retrieved from the cultured samples was amplified using the polymerase chain reaction (PCR) performed with two universal bacterial primers: 27F, 5′-GAG TTT GAT CMT GGC TCA G-3′ and 518R, 5′-TTA CCG CGG CTG CTG G-3′. Each primer was tagged using multiplex identifier (MID) adaptors according to the manufacturer’s instructions (Roche, Mannheim, Germany), which allowed for the automatic sorting of the pyrosequencing-derived sequencing reads based on the MID adaptors. In addition, MID-linked 27F and 518R were linked to the pyrosequencing primers 5′-CGT ATC GCC TCC CTC GCG CCA TCA G-3′ and 5′-CTA TGC GCC TTG CCA GCC CGC TCAG-3′, respectively, according to the manufacturer’s instructions (Roche, Mannheim, Germany).
Metagenomic PCR was performed with 20 μL reaction mixtures containing 2 μL 10× Ex Taq buffer (TaKaRa, Kyoto, Japan), 2 μL of a dNTP mixture (4 mM), 1 μL of each primer (10 pM), 0.2 μL Ex Taq polymerase (2.5 U), and 0.1 μg of the environmental DNA template. PCR cycling was performed in an iCycler (Bio-Rad, Hercules, CA, USA) at 94 °C for 5 min, followed by 35 cycles at 94 °C for 20 s, 52 °C for 40 s, and 72 °C for 1 min, and a final extension at 72 °C for 10 min. The resulting PCR products were electrophoresed in 1.0% agarose gel, stained with ethidium bromide, and viewed under ultraviolet transillumination.
Prior to pyrosequencing, amplified PCR products were individually purified using a Dual PCR Purification Kit (Bionics, Seoul, Korea) and, subsequently, equal volumes of each purified PCR product were mixed together. Pyrosequencing of the MID-tagged PCR amplicons was performed using a 454 GS FLX Titanium system (Roche, Mannheim, Germany) with a commercial service at Macrogen, Inc. (Seoul, Korea).

2.4. Pyrosequencing Data Analysis

After each sequencing procedure had been completed, a quality check was performed to remove short sequence reads (e.g., less than 150 bp), low-quality sequences, sequence artifacts and chloroplast sequences, and any non-bacterial ribosome sequences and chimeras [21,22]. Using the basic local alignment search tool (BLAST), all of the sequence reads were compared to the Silva rRNA database [23]. Sequence reads which were similar with an E-value of less than 0.01 were admitted as partial 16S rDNA sequences. The taxonomy of the sequence with the highest similarity was assigned to the sequence read (genus and class level). To analyze operational taxonomic units (OTUs), the CD-HIT-OTU software was used for clustering [24] and the Mothur software was used for Shannon-Weaver diversity and Chao richness estimation [25]. All data from the 454 pyrosequences were deposited into the Genebank database.
To examine the similarities and differences in the community composition (at the OTU level) among the samples (FLB and PAB communities depending on the growth phase of T. suecica), PRIMER ver. 7 [26] and R studio ver. 5.3 [27] were used to generate the heatmap and dendrogram for the hierarchical cluster analysis, together with similarity profiles (SIMPROF, p = 0.05). All the analyses were performed based on the Bray-Curtis dissimilarity index.

3. Results and Discussion

3.1. Cell Growth of Tetraselmis suecica and Bacteria in Cultures

The green algae T. suecica and FLB in the culture appeared as a common, typical S-shaped growth curve (Figure 1), but the growth of FLB was faster than that of T. suecica. The highest density (3,774,000 cells mL−1) of bacterial cells was shown at day 10, whereas T. suecica reached the maximum cell density (827,830 cells mL−1) at day 18. Community compositions of FLB and PAB were investigated using the samples which were collected at day 2, 8, 20, and 32, referring to the lag, exponential, stationary, and death growth phase of T. suecica.

3.2. Pyrosequencing Data and Comparison of FLB and PAB in Tetraselmis suecica

The pyrosequencing analysis generated 3742–9409 nucleotide fragments of FLBs and 8078–13,725 nucleotide fragments of PAB. All of the samples reached saturation in the rarefaction curve indicating that a sufficient amount of sequences was identified by the pyrosequencing used in this study (Figure S1). The number of bacterial OTUs (≥97% similarity) in FLB and PAB were 35 and 30, respectively, and all bacterial OTUs in PAB were present in FLB (Figure 2A).
Based on alpha diversity indices (Shannon and Simpson), the level of bacterial diversity in FLB was clearly higher than that in PAB (Table 1). The averages of diversity indices of FLB were 3.39 (Shannon) and 0.84 (Simpson), but those of PAB were 1.99 (Shannon) and 0.57 (Simpson), respectively. Together with these findings, the bacterial community in FLB was more diverse than that in PAB.
The proportion of shared OTUs between FLB and PAB communities was remarkably high. It was 100% of PAB and ≥92.4% of FLB (Figure 2A). According to previous findings, this proportion is determined by the concentration of particles [28,29,30], and the proportion of shared bacterial OTUs between FLB and PAB communities was relatively high in certain marine environments where a higher concentration of particles existed [31,32,33,34]. In this study, we used the culture which contained a high concentration of cells. Therefore, this might result in a high proportion of shared bacterial OTUs between the two bacterial communities in this study. Interestingly, we have obtained similar results (i.e., high proportion of shared bacterial OTUs) in previous studies where dinoflagellate cultures were used [28,35].

3.3. Difference between FLB and PAB Communities in Tetraselmis suecica Culture

Interestingly, there was a clear difference in the bacterial community composition between FLB and PAB communities even though a proportion of shared bacterial OTUs was remarkably high. The genus Roseobacter, belonging to the class Rhodobacteraceae (56.7–60.1%), was most dominant in the FLB community (Figure 3). The second most dominant groups were genera Oceanicaulis (family Hyphomonadaceae, 6.3–9.3%), Loktanella (Rhodobacteraceae, 2.9–8.6%), Muricauda (Flavobacteriaceae, 4.8–6.5%), Roseibacterium (Rhodobacteraceae, 3.5–6.3%), and Marinobacter (Alteromonadaceae, 1.9–7.1%). Whereas, in the PAB community, the family Flavobacteriaceae (19.5–36.9%, unidentified at the genus level) and the genus Marinobacter (10.2–30.1%) were predominant groups, with Oceanicaulis (8.2–14.3%), Loktanella (4.8–5.8%), and Muricauda (5.5–8.1%) the second most dominant genera (Figure 3). These two bacterial communities at the OTU level were significantly distinct (77.5% of similarity level, p = 0.05) in the cluster analysis and the SIMPROF test (Figure 4). Organic matters released from phytoplankton play an important role in the determination of abundance and community composition of heterotrophic bacteria in aquatic environments [8]. There are two types of organic matters which originated from phytoplankton [8], one is the low molecular weight (LMW) molecule (e.g., amino acids, organic acids, and carbohydrate, etc.) and the other is the high molecular weight (HMW) macromolecule (e.g., polysaccharides, proteins, nucleic acids, and lipids, etc.). The environments where FLB and PAB communities distribute are clearly distinct in terms of the ratio between LMW and HMW. Thus, this may lead to a significant difference in the community composition between FLB and PAB. For example, the most dominant taxa in FLB and PAB were Rhodobacteraceae (genus Roseobacter) and Flavobacteriaceae, respectively. Based on previous findings, the Roseobacter clade is capable of utilizing various LMW compounds that originated from phytoplankton as a carbon source [36,37,38]. Whereas, Flavobacteriaceae prefer to use HMW compounds and can convert these into LMW compounds [39].

3.4. Variation in Bacterial Community Composition Depending on the Growth Stage of Tetraselmis suecica

The number of bacterial OTUs observed in the lag, exponential, stationary, and death growth phases of T. suecica was 29, 31, 27, and 28, respectively for FLB (Figure 3B) and 27, 27, 25, 25, respectively for PAB (Figure 2C). There was no significant difference in bacterial diversity depending on the growth phase of host green algae (Table 1). The range of the Shannon index was 3.105–3.540 (FLB) and 1.908–2.066 (PAB), and the range of the Simpson index was 0.792–0.863 (FLB) and 0.543–0.594 (PAB). Whereas, depending on the growth phase of T. suecica, the community composition of FLB and PAB was varied, and, interestingly, the PAB community was more variable than the FLB community (Figure 3 and Figure 4). In the hierarchical cluster analysis, the PAB community composition in the death phase of T. suecica was significantly (p = 0.05) distinct to that in the other growth phases (lag, exponential, and stationary phases) at the OTU level, where there was no significantly different composition of FLB communities in each growth phase of green algae (Figure 4). To our knowledge, PAB has a stronger species-specific association to the growth and physiological condition of host algae [15,16,17,28,35], since the microhabitat for PAB is provided by algae [40,41].
Rhodobacteraceae OTU1, belonging to the Roseobacter clade, was generally predominant in both FLB and PAB communities even though its proportion in FLB was higher than that in PAB. This suggests that this bacterial OTU may be intimately associated with T. suecica. The Roseobacter clade can provide growth-promoting compounds (e.g., vitamin B12) to various algal species, including Tetraselmis [12,42,43]. Based on a recent study [13], the growth yield of T. suecica F and M33 was increased when three isolates from the Roseobacter clade were co-cultivated. Interestingly, the bacterial isolate, belonging to genus Muricauda, has also shown the capability to enhance the growth of T. suecica F and M33 [13]. This genus was one of the dominant taxa in both FLB and PAB communities in our study. Given these findings, dominant bacterial groups of PAB and FLB communities established in T. suecica culture may positively contribute to the growth of host green algae. However, the actual impact of these bacterial taxa on the growth of T. suecica is thought to be unclear. For example, a cell number of T. suecica was largely decreased in the death phase, but the proportion of these bacterial taxa was not significantly decreased (Figure 1 and Figure 3). To our knowledge, inorganic nutrients which are essential to algal growth were generally depleted in the death phase of algae due to the consumption by the algae. Thus, it is more likely that the decrease in T. suecica cells in the death phase may be caused by the depletion of inorganic nutrients even though growth promoting bacteria (e.g., Roseobacter clade and Muricauda) were present.
In the PAB community, the proportion of Marinobacter was gradually decreased in accordance with the increase in cell number of T. suecica. Its proportion in the lag and exponential growth phase was clearly higher than that in the stationary and death phase, in which the algal growth rate was relatively low (Figure 1 and Figure 3). Several clades of this bacterial genus can secrete a siderophore called vibrioferrin, allowing the promotion of the algal assimilation of iron [44]. Therefore, a lower proportion of Marinobacter in the stationary and death phases may adversely affect the growth of T. suecica.
Flavobacteriaceae can primarily consume HMW compounds and convert them into LMW compounds [39]. Thus, an abundance of this bacteria is generally elevated when a number of HMW compounds were released from the algae, as a result of cell lysis [45,46,47,48]. Similarly, in this study, the proportion of Flavobacteriaceae in the PAB community gradually increased in accordance with an increase in the cell number of T. suecica (Figure 1 and Figure 3), resulting in an elevation of the HMW compound concentration.

3.5. Conclusions and Remarks

The present study is the first to characterize FLB and PAB communities in T. suecica culture using the NGS approach. Based on our findings, FLB and PAB communities were significantly distinct (p = 0.05), the PAB community was more affected depending on the growth phases of T. suecica than FLB community. In addition, bacterial taxa (e.g., Roseobacter clade and Muricauda) which are capable of enhancing the growth of host green algae were dominant in both FLB and PAB communities, irrespective of growth phase of T. suecica. These findings suggest that bacterial community in T. suecica culture may positively affect the growth of host algae. However, to evaluate the actual impact of bacterial communities on the growth of T. suecica, further extensive studies, such as growth promoting mechanism of bacteria in algal culture, are needed.

Supplementary Materials

The following are available online at https://www.mdpi.com/2077-1312/9/2/171/s1. Figure S1: OTU counts (A) and rarefaction (B) of each growth phase of Tetraselmis suecica. Abbreviations: FLB: Free-living bacteria; PAB: Particle-associated bacteria; Exp: Exponential; Stn: Stationary; Dth: Death.

Author Contributions

Conceptualization, B.S.P. and J.-S.K.; methodology, W.-J.C. and R.G.; investigation, W.-J.C. and H.K.; data curation, B.S.P.; writing—original draft preparation, B.S.P.; writing—review and editing, B.S.P., W.-J.C., R.G., H.K. and J.-S.K.; supervision, J.-S.K.; funding acquisition, B.S.P. and J.-S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A2C2013373), and the Korea Institute of Ocean Science and Technology (PE99921).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chisti, Y. Biodiesel from microalgae. Biotechnol. Adv. 2007, 25, 294–306. [Google Scholar] [CrossRef]
  2. Teo, C.L.; Jamaluddin, H.; Zain, N.A.M.; Idris, A. Biodiesel production via lipase catalysed transesterification of microalgae lipids from Tetraselmis sp. Renew. Energy 2014, 68, 1–5. [Google Scholar] [CrossRef]
  3. Peña, M.R.; Villegas, C.T. Cell growth, effect of filtrate and nutritive value of the tropical Prasinophyte Tetraselmis tetrathele (Butcher) at different phases of culture. Aquac. Res. 2005, 36, 1500–1508. [Google Scholar] [CrossRef]
  4. Park, J.; Park, B.S.; Wang, P.; Patidar, S.K.; Kim, J.H.; Kim, S.H.; Han, M.S. Phycospheric native bacteria Pelagibaca bermudensis and Stappia sp. ameliorate biomass productivity of Tetraselmis striata (KCTC1432BP) in co-cultivation system through mutualistic interaction. Front. Plant Sci. 2017, 8, 289. [Google Scholar] [CrossRef] [Green Version]
  5. Pertile, P.; Zanella, L.; Herrmann, M.; Joppe, H.; Gaebler, S. Extracts of Tetraselmis sp. U.S. Patent US2010/0143267 A1, 10 June 2010. [Google Scholar]
  6. Mitra, M.; Patidar, S.K.; George, B.; Shah, F.; Mishra, S. A euryhaline Nannochloropsis gaditana with potential for nutraceutical (EPA) and biodiesel production. Algal Res. 2015, 8, 161–167. [Google Scholar] [CrossRef]
  7. Patidar, S.K.; Mitra, M.; George, B.; Soundarya, R.; Mishra, S. Potential of Monoraphidium minutum for carbon sequestration and lipid production in response to varying growth mode. Bioresour. Technol. 2014, 172, 32–40. [Google Scholar] [CrossRef]
  8. Buchan, A.; LeCleir, G.R.; Gulvik, C.A.; González, J.M. Master recyclers: Features and functions of bacteria associated with phytoplankton blooms. Nat. Rev. Microbiol. 2014, 12, 686–698. [Google Scholar] [CrossRef]
  9. Geng, H.; Belas, R. Molecular mechanisms underlying Roseobacter–phytoplankton symbioses. Curr. Opin. Biotechnol. 2010, 21, 332–338. [Google Scholar] [CrossRef]
  10. Park, B.S.; Joo, J.H.; Baek, K.D.; Han, M.S. A mutualistic interaction between the bacterium Pseudomonas asplenii and the harmful algal species Chattonella marina (Raphidophyceae). Harmful Algae 2016, 56, 29–36. [Google Scholar] [CrossRef]
  11. Park, B.S.; Erdner, D.L.; Bacosa, H.P.; Liu, Z.; Buskey, E.J. Potential effects of bacterial communities on the formation of blooms of the harmful dinoflagellate Prorocentrum after the 2014 Texas City “Y” oil spill (USA). Harmful Algae 2020, 95, 101802. [Google Scholar] [CrossRef] [PubMed]
  12. Seyedsayamdost, M.R.; Case, R.J.; Kolter, R.; Clardy, J. The Jekyll-and-Hyde chemistry of Phaeobacter gallaeciensis. Nat. Chem. 2011, 3, 331–335. [Google Scholar] [CrossRef] [PubMed]
  13. Biondi, N.; Cheloni, G.; Rodolfi, L.; Viti, C.; Giovannetti, L.; Tredici, M.R. Tetraselmis suecica F&M-M33 growth is influenced by its associated bacteria. Microb. Biotechnol. 2018, 11, 211–223. [Google Scholar]
  14. Piampiano, E.; Pini, F.; Biondi, N.; Garcia, C.J.; Decorosi, F.; Tomàs-Barberàn, F.A.; Giovannetti, L.; Viti, C. Tetraselmis suecica F&M-M33 phycosphere: Associated bacteria and exo-metabolome characterisation. Eur. J. Phycol. 2020, 1–11. [Google Scholar] [CrossRef]
  15. Crump, B.C.; Armbrust, E.V.; Baross, J.A. Phylogenetic analysis of particle-attached and free-living bacterial communities in the Columbia River, its estuary, and the adjacent coastal ocean. Appl. Environ. Microbiol. 1999, 65, 3192–3204. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Jasti, S.; Sieracki, M.E.; Poulton, N.J.; Giewat, M.W.; Rooney-Varga, J.N. Phylogenetic diversity and specificity of bacteria closely associated with Alexandrium spp. and other phytoplankton. Appl. Environ. Microbiol. 2005, 71, 3483–3494. [Google Scholar] [CrossRef] [Green Version]
  17. Rooney-Varga, J.N.; Giewat, M.W.; Savin, M.C.; Sood, S.; LeGresley, M.; Martin, J.L. Links between phytoplankton and bacterial community dynamics in a coastal marine environment. Microb. Ecol. 2005, 49, 163–175. [Google Scholar] [CrossRef] [PubMed]
  18. Guillard, R.R.; Ryther, J.H. Studies of marine planktonic diatoms: I. Cyclotella nana Hustedt, and Detonula confervacea (Cleve) Gran. Can. J. Microbiol. 1962, 8, 229–239. [Google Scholar] [CrossRef]
  19. Turley, C.M. Direct estimates of bacterial numbers in seawater samples without incurring cell loss due to sample storage. In Handbook of Methods in Aquatic Microbial Ecology; CRC Press: Boca Raton, FL, USA, 1993; pp. 143–147. [Google Scholar]
  20. Park, B.S.; Wang, P.; Kim, J.H.; Kim, J.H.; Gobler, C.J.; Han, M.S. Resolving the intra-specific succession within Cochlodinium polykrikoides populations in southern Korean coastal waters via use of quantitative PCR assays. Harmful Algae 2014, 37, 133–141. [Google Scholar] [CrossRef]
  21. Gontcharova, V.; Youn, E.; Wolcott, R.D.; Hollister, E.B.; Gentry, T.J.; Dowd, S.E. Black box chimera check (B2C2): A windows-based software for batch depletion of chimeras from bacterial 16S rRNA gene datasets. Open Microbiol. J. 2010, 4, 47. [Google Scholar] [CrossRef]
  22. Huse, S.M.; Huber, J.A.; Morrison, H.G.; Sogin, M.L.; Welch, D.M. Accuracy and quality of massively parallel DNA pyrosequencing. Genome Biol. 2007, 8, R143. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Quast, C.; Pruesse, E.; Yilmaz, P.; Gerken, J.; Schweer, T.; Yarza, P.; Peplies, J.; Glöckner, F.O. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2012, 41, D590–D596. [Google Scholar] [CrossRef]
  24. Li, W.; Fu, L.; Niu, B.; Wu, S.; Wooley, J. Ultrafast clustering algorithms for metagenomic sequence analysis. Brief Bioinform. 2012, 13, 656–668. [Google Scholar] [CrossRef] [PubMed]
  25. Schloss, P.D.; Westcott, S.L.; Ryabin, T.; Hall, J.R.; Hartmann, M.; Hollister, E.B.; Lesniewski, R.A.; Oakley, B.B.; Parks, D.H.; Robinson, C.J.; et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 2009, 75, 7537–7541. [Google Scholar] [CrossRef] [Green Version]
  26. Clarke, K.; Gorley, R. PRIMER v7: User Manual/Tutorial; Primer-E: Plymouth, UK, 2015; 296p. [Google Scholar]
  27. Team, R. RStudio: Integrated Development for R; RStudio Inc.: Boston, MA, USA, 2015; 700p. [Google Scholar]
  28. Park, B.S.; Guo, R.; Lim, W.A.; Ki, J.S. Importance of free-living and particle-associated bacteria for the growth of the harmful dinoflagellate Prorocentrum minimum: Evidence in culture stages. Mar. Freshw. Res. 2018, 69, 290–299. [Google Scholar] [CrossRef]
  29. Parveen, B.; Mary, I.; Vellet, A.; Ravet, V.; Debroas, D. Temporal dynamics and phylogenetic diversity of free-living and particle-associated Verrucomicrobia communities in relation to environmental variables in a mesotrophic lake. FEMS Microbiol. Ecol. 2013, 83, 189–201. [Google Scholar] [CrossRef] [Green Version]
  30. Rösel, S.; Grossart, H.P. Contrasting dynamics in activity and community composition of free-living and particle-associated bacteria in spring. Aquat. Microb. Ecol. 2012, 66, 169–181. [Google Scholar] [CrossRef] [Green Version]
  31. Noble, P.A.; Bidle, K.D.; Fletcher, M. Natural Microbial Community Compositions Compared by a Back-Propagating Neural Network and Cluster Analysis of 5S rRNA. Appl. Environ. Microbiol. 1997, 63, 1762–1770. [Google Scholar] [CrossRef] [Green Version]
  32. Riemann, L.; Winding, A. Community dynamics of free-living and particle-associated bacterial assemblages during a freshwater phytoplankton bloom. Microb. Ecol. 2001, 42, 274–285. [Google Scholar] [CrossRef] [PubMed]
  33. Tang, X.; Li, L.; Shao, K.; Wang, B.; Cai, X.; Zhang, L.; Chao, J.; Gao, G. Pyrosequencing analysis of free-living and attached bacterial communities in Meiliang Bay, Lake Taihu, a large eutrophic shallow lake in China. Can. J. Microbiol. 2015, 61, 22–31. [Google Scholar] [CrossRef] [PubMed]
  34. Zhang, R.; Liu, B.; Lau, S.C.; Ki, J.S.; Qian, P.Y. Particle-attached and free-living bacterial communities in a contrasting marine environment: Victoria Harbor, Hong Kong. FEMS Microbiol. Ecol. 2007, 61, 496–508. [Google Scholar] [CrossRef] [Green Version]
  35. Park, B.S.; Guo, R.; Lim, W.A.; Ki, J.S. Pyrosequencing reveals specific associations of bacterial clades Roseobacter and Flavobacterium with the harmful dinoflagellate Cochlodinium polykrikoides growing in culture. Mar. Ecol. 2017, 38, e12474. [Google Scholar] [CrossRef]
  36. Buchan, A.; González, J.M.; Moran, M.A. Overview of the marine Roseobacter lineage. Appl. Environ. Microbiol. 2005, 71, 5665–5677. [Google Scholar] [CrossRef] [Green Version]
  37. Merzouk, A.; Levasseur, M.; Scarratt, M.; Michaud, S.; Lizotte, M.; Rivkin, R.B.; Kiene, R.P. Bacterial DMSP metabolism during the senescence of the spring diatom bloom in the Northwest Atlantic. Mar. Ecol. Prog. Ser. 2008, 369, 1–11. [Google Scholar] [CrossRef]
  38. Wagner-Döbler, I.; Biebl, H. Environmental biology of the marine Roseobacter lineage. Annu. Rev. Microbiol. 2006, 60, 255–280. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Teeling, H.; Fuchs, B.M.; Becher, D.; Klockow, C.; Gardebrecht, A.; Bennke, C.M.; Kassabgy, M.; Huang, S.; Mann, A.J.; Waldmann, J.; et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science 2012, 336, 608–611. [Google Scholar] [CrossRef]
  40. Bagatini, I.L.; Eiler, A.; Bertilsson, S.; Klaveness, D.; Tessarolli, L.P.; Vieira, A.A.H. Host-specificity and dynamics in bacterial communities associated with bloom-forming freshwater phytoplankton. PLoS ONE 2014, 9, e85950. [Google Scholar] [CrossRef] [Green Version]
  41. Worm, J.; Søndergaard, M. Dynamics of heterotrophic bacteria attached to Microcystis spp. (Cyanobacteria). Aquat. Microb. Ecol. 1998, 14, 19–28. [Google Scholar] [CrossRef] [Green Version]
  42. Helliwell, K.E.; Wheeler, G.L.; Leptos, K.C.; Goldstein, R.E.; Smith, A.G. Insights into the evolution of vitamin B12 auxotrophy from sequenced algal genomes. Mol. Biol. Evol. 2011, 28, 2921–2933. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Wagner-Döbler, I.; Ballhausen, B.; Berger, M.; Brinkhoff, T.; Buchholz, I.; Bunk, B.; Cypionka, H.; Daniel, R.; Drepper, T.; Gerdts, G.; et al. The complete genome sequence of the algal symbiont Dinoroseobacter shibae: A hitchhiker’s guide to life in the sea. ISME J. 2010, 4, 61–77. [Google Scholar] [CrossRef] [Green Version]
  44. Amin, S.A.; Green, D.H.; Hart, M.C.; Küpper, F.C.; Sunda, W.G.; Carrano, C.J. Photolysis of iron–siderophore chelates promotes bacterial–algal mutualism. Proc. Natl. Acad. Sci. USA 2009, 106, 17071–17076. [Google Scholar] [CrossRef] [Green Version]
  45. Azam, F.; Malfatti, F. Microbial structuring of marine ecosystems. Nat. Rev. Microbiol. 2007, 5, 782–791. [Google Scholar] [CrossRef]
  46. Pinhassi, J.; Sala, M.M.; Havskum, H.; Peters, F.; Guadayol, O.; Malits, A.; Marrasé, C. Changes in bacterioplankton composition under different phytoplankton regimens. Appl. Environ. Microbiol. 2004, 70, 6753–6766. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Riemann, L.; Steward, G.F.; Azam, F. Dynamics of bacterial community composition and activity during a mesocosm diatom bloom. Appl. Environ. Microbiol. 2000, 66, 578–587. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Simon, M.; Glöckner, F.O.; Amann, R. Different community structure and temperature optima of heterotrophic picoplankton in various regions of the Southern Ocean. Aquat. Microb. Ecol. 1999, 18, 275–284. [Google Scholar] [CrossRef] [Green Version]
Figure 1. The growth curves of Tetraselmis suecica and the associated bacteria. Arrows represent each sampling point. Abbreviations: FLB: Free-living bacteria; PAB: Particle-associated bacteria; Exp: Exponential; Stn: Stationary; Dth: Death.
Figure 1. The growth curves of Tetraselmis suecica and the associated bacteria. Arrows represent each sampling point. Abbreviations: FLB: Free-living bacteria; PAB: Particle-associated bacteria; Exp: Exponential; Stn: Stationary; Dth: Death.
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Figure 2. Bacterial operational taxonomic units (OTUs) Venn diagram. (A): Venn diagram enumerates shared bacterial OTUs between free-living (FLB) and particle-associated (PAB); (B,C): Venn diagrams enumerate FLB and PAB OTUs, shared by and exclusive to lag, exponential (Exp), stationary (Stn), and death (Dth) growth phases of T. suecica. The percentage number (lower right corner of each Venn-diagram) indicates the proportion of shared bacterial OTUs.
Figure 2. Bacterial operational taxonomic units (OTUs) Venn diagram. (A): Venn diagram enumerates shared bacterial OTUs between free-living (FLB) and particle-associated (PAB); (B,C): Venn diagrams enumerate FLB and PAB OTUs, shared by and exclusive to lag, exponential (Exp), stationary (Stn), and death (Dth) growth phases of T. suecica. The percentage number (lower right corner of each Venn-diagram) indicates the proportion of shared bacterial OTUs.
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Figure 3. Composition of the FLB and PAB communities in lag, exponential (Exp), stationary (Stn), and death (Dth) growth phases of T. suecica. (A): Order; (B): Family; and (C): Genus level.
Figure 3. Composition of the FLB and PAB communities in lag, exponential (Exp), stationary (Stn), and death (Dth) growth phases of T. suecica. (A): Order; (B): Family; and (C): Genus level.
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Figure 4. Heatmap for a comparison of the bacterial community composition among the samples at the species level. The values in the heat map represent the log-transformed relative abundance (Log X + 1) of each bacterial OTU, and similarity matrices were generated using the Bray–Curtis method. In the cluster analysis on Y-axis, the red dot-lines indicate where divisions are not statistically significant, as judged by similarity profiles (SIMPROF) carried out at p = 0.05.
Figure 4. Heatmap for a comparison of the bacterial community composition among the samples at the species level. The values in the heat map represent the log-transformed relative abundance (Log X + 1) of each bacterial OTU, and similarity matrices were generated using the Bray–Curtis method. In the cluster analysis on Y-axis, the red dot-lines indicate where divisions are not statistically significant, as judged by similarity profiles (SIMPROF) carried out at p = 0.05.
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Table 1. Number of sequence reads and alpha diversity indices (Shannon and Simpson) PAB and FLB samples, which were isolated from each growth phase of T. suecica culture (P-039).
Table 1. Number of sequence reads and alpha diversity indices (Shannon and Simpson) PAB and FLB samples, which were isolated from each growth phase of T. suecica culture (P-039).
SamplesRead CountDiversity Indices
ShannonSimpson
Particle-associatedLag10,6832.0230.569
Exponential13,7251.9080.543
Stationary94331.9610.565
Death80782.0660.594
Free-livingLag72333.1050.792
Exponential37423.5400.850
Stationary94093.4180.844
Death78543.4900.863
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Park, B.S.; Choi, W.-J.; Guo, R.; Kim, H.; Ki, J.-S. Changes in Free-Living and Particle-Associated Bacterial Communities Depending on the Growth Phases of Marine Green Algae, Tetraselmis suecica. J. Mar. Sci. Eng. 2021, 9, 171. https://doi.org/10.3390/jmse9020171

AMA Style

Park BS, Choi W-J, Guo R, Kim H, Ki J-S. Changes in Free-Living and Particle-Associated Bacterial Communities Depending on the Growth Phases of Marine Green Algae, Tetraselmis suecica. Journal of Marine Science and Engineering. 2021; 9(2):171. https://doi.org/10.3390/jmse9020171

Chicago/Turabian Style

Park, Bum Soo, Won-Ji Choi, Ruoyu Guo, Hansol Kim, and Jang-Seu Ki. 2021. "Changes in Free-Living and Particle-Associated Bacterial Communities Depending on the Growth Phases of Marine Green Algae, Tetraselmis suecica" Journal of Marine Science and Engineering 9, no. 2: 171. https://doi.org/10.3390/jmse9020171

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