Phytoplankton-Associated Bacterial Community Composition and Succession during Toxic Diatom Bloom and Non-Bloom Events.
Pseudo-nitzschia blooms often occur in coastal and open ocean environments, sometimes leading to the production of the neurotoxin domoic acid that can cause severe negative impacts to higher trophic levels. Increasing evidence suggests a close relationship between phytoplankton bloom and bacterial assemblages, however, the microbial composition and succession during a bloom process is unknown. Here, we investigate the bacterial assemblages before, during and after toxic and non-toxic Pseudo-nitzschia blooms to determine the patterns of bacterial succession in a natural bloom setting. Opportunistic sampling of bacterial community profiles were determined weekly at Santa Cruz Municipal Wharf by 454 pyrosequencing and analyzed together with domoic acid levels, phytoplankton community and biomass, nutrients and temperature. We asked if the bacterial communities are similar between bloom and non-bloom events and if domoic acid or the presence of toxic algal species acts as a driving force that can significantly structure phytoplankton-associated bacterial communities. We found that bacterial diversity generally increases when Pseudo-nitzschia numbers decline. Furthermore, bacterial diversity is higher when the low-DA producing P. fraudulenta dominates the algal bloom while bacterial diversity is lower when high-DA producing P. australis dominates the algal bloom, suggesting that the presence of algal toxin can structure bacterial community. We also found bloom-related succession patterns among associated bacterial groups; Gamma-proteobacteria, were dominant during low toxic P. fraudulenta blooms comprising mostly of Vibrio spp., which increased in relative abundance (6-65%) as the bloom progresses. On the other hand, Firmicutes bacteria comprising mostly of Planococcus spp. (12-86%) dominate during high toxic P. australis blooms, with the bacterial assemblage showing the same bloom-related successional patterns in three independent bloom events. Other environmental variables such as nitrate and phosphate and temperature appear to influence some low abundant bacterial groups as well. Our results suggest that phytoplankton-associated bacterial communities are strongly affected not just by phytoplankton bloom in general, but also by the type of algal species that dominates in the natural bloom.
Department of Ocean Sciences and Institute of Marine Sciences, University of California, Santa Cruz, Santa Cruz, CA USA.
Marilou P
MP
Sison-Mangus
Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA USA.
Sunny
S
Jiang
Department of Ocean Sciences and Institute of Marine Sciences, University of California, Santa Cruz, Santa Cruz, CA USA.
Raphael M
RM
Kudela
Department of Ocean Sciences and Institute of Marine Sciences, University of California, Santa Cruz, Santa Cruz, CA USA.
Sanjin
S
Mehic
Planococcus; Pseudo-nitzschia; Vibrio; algal bloom; bacteria; diatom; domoic acid; nutrients
Nat Toxins. 1995;3(6):428-35
8612005
Appl Environ Microbiol. 2000 Feb;66(2):578-87
10653721
ISME J. 2011 Mar;5(3):436-45
20827289
Appl Environ Microbiol. 2006 Jul;72(7):5069-72
16820507
Appl Environ Microbiol. 1990 Jun;56(6):1977-80
2383016
PLoS One. 2010 Mar 10;5(3):e9490
20224823
Mar Genomics. 2014 Dec;18 Pt B:185-92
25211053
Science. 2012 May 4;336(6081):608-11
22556258
Appl Environ Microbiol. 1999 Feb;65(2):514-22
9925576
FEMS Microbiol Ecol. 2002 Oct 1;42(1):25-35
19709263
Appl Environ Microbiol. 2015 Sep 1;81(17):5703-13
26070682
Nature. 2005 Nov 3;438(7064):90-3
16267554
Microb Ecol. 2005 Jan;49(1):163-75
15688258
Proc Natl Acad Sci U S A. 2009 Oct 6;106(40):17071-6
19805106
Genome Biol. 2007;8(7):R143
17659080
Nat Rev Microbiol. 2014 Oct;12(10):686-98
25134618
Open Microbiol J. 2010 Aug 11;4:47-52
21339894
Proc Natl Acad Sci U S A. 2016 Feb 9;113(6):1576-81
26802122
ISME J. 2016 Jan;10 (1):39-50
26196334
ISME J. 2014 Jan;8(1):63-76
23985747
Nature. 2000 Jan 6;403(6765):80-4
10638756
J Eukaryot Microbiol. 2004 Mar-Apr;51(2):139-44
15134248
Nature. 2015 Jun 4;522(7554):98-101
26017307
Appl Environ Microbiol. 2007 Aug;73(16):5261-7
17586664
Bioinformatics. 2010 Jan 15;26(2):266-7
19914921
Nat Methods. 2010 May;7(5):335-6
20383131
Appl Environ Microbiol. 2014 Apr;80(7):2071-83
24463966
J Mol Biol. 1990 Oct 5;215(3):403-10
2231712
Bioinformatics. 2010 Oct 1;26(19):2460-1
20709691
Elife. 2016 Apr 07;5:e11888
27054497
Mar Environ Res. 2014 Aug;99:106-16
24838080
Environ Microbiol. 2005 Jun;7(6):860-73
15892705
Nat Chem. 2011 Apr;3(4):331-5
21430694