Molecular characterization of Pseudo-nitzschia community structure and species ecology in a hydrographically complex estuarine system (Puget Sound, Washington, USA)

Abstract

Species within the toxic marine diatom genus Pseudo-nitzschia coexist in coastal and estuarine waters globally and are difficult to distinguish by microscopy. Here, we describe a sensitive, high throughput PCR-based Automated Ribosomal Intergenic Spacer Analysis (ARISA) approach to determine the relative abundance of Pseudo-nitzschia species within natural communities over space and time. The method was quantitatively validated using simplified mixtures of DNA or ITS1 standards from isolates of P. pungens, P. multiseries, and P. delicatissima. Relative abundance calculations based on ARISA profiles from these mixtures reflected input ratios, with minor deviations resulting from intraspecific variability. ARISA was used to identify and quantify at least eight species within Puget Sound and the eastern Strait of Juan de Fuca, Washington, USA: P. americana, P. australis/P. seriata, P. cuspidata, P. delicatissima, P. fraudulenta, P. fryxelliana, P. multiseries, and P. pungens; genotypes corresponding to P. pungens var. pungens and P. pungens var. cingulata were identified by environmental sequencing. The different species were significantly correlated with physical (temperature, salinity), biological (chlorophyll a fluorescence, oxygen), and/or chemical (ammonium, nutrient ratios) factors. The ability to determine shifts in the relative abundance of Pseudo-nitzschia species over spatial and temporal scales relevant to dispersion and selection facilitates dissection of the varied mechanisms driving vertical and horizontal species distribution patterns in hydrographically complex systems.

Pseudo-nitzschia species (Bacillariophyceae) identification and delineation using mitochondrial cox1 gene sequences as compared to LSU rDNA

“…Molecular species characterization using nucleotide sequences of the nuclearencoded large-subunit (LSU) ribosomal DNA (rDNA) and the internal transcribed spacer region (ITS1-5.8S-ITS2) have become essential supporting criteria in species delineation [9][10][11][12][13][14][15][16]. Other molecular techniques used in Pseudonitzschia studies included automated ribosomal intergenic spacer analysis (ARISA) [17][18][19]; rapid whole-cell detection using fluorescence in situ hybridization (FISH) [12,[20][21][22][23]; and the development of species-specific microsatellite markers for population genetics [24,25].…”

Temporal variation of Skeletonema community composition from a long-term time series in Narragansett Bay identified using high-throughput DNA sequencing

“…Molecular characterizations have provided insights into the ecology of cryptic and pseudo-cryptic species (denoted hereafter as cryptic species), though studies of natural samples are limited. For example, targeted molecular analyses revealed that cryptic species in the genus Pseudonitzschia sampled from Puget Sound, Washington, varied in their relative abundances over space and time, and shifts in species composition were correlated with different environmental conditions (Hubbard et al 2014). Similarly, cryptic species of Pseudonitzschia in the Gulf of Naples showed distinct patterns of species occurrence over time (Ruggiero et al 2015).…”

Pseudo-nitzschia Challenged with Co-occurring Viral Communities Display Diverse Infection Phenotypes

“…Pseudo-nitzschia communities sampled over the year became so rare that they were undetectable with ARISA 20% of the time, particularly during winter months ( Figures 2C,D ). Thus, Pseudo-nitzschia concentrations were likely lower than 1 cell L -1 ( Hubbard et al, 2014 ). Yet the viral communities from those months were still infective of Pseudo-nitzschia isolates.…”

“…Peak area was summed over two base pair bins and divided by total fluorescence, which gave a relative abundance. Peaks were identified using predicted ITS lengths from the Pseudo-nitzschia isolates as well as from reported ITS lengths in Hubbard et al (2008 , 2014 ). The resulting community profiles were analyzed using the statistics package Primer-6 ( Clarke and Warwick, 2001 ).…”