Adriane C. Jones

Marine bacterial, archaeal and protistan association networks reveal ecological linkages

Microbes have central roles in ocean food webs and global biogeochemical processes, yet specific ecological relationships among these taxa are largely unknown. This is in part due to the dilute, microscopic nature of the planktonic microbial community, which prevents direct observation of their interactions. Here, we use a holistic (that is, microbial system-wide) approach to investigate time-dependent variations among taxa from all three domains of life in a marine microbial community. We investigated the community composition of bacteria, archaea and protists through cultivation-independent methods, along with total bacterial and viral abundance, and physico-chemical observations. Samples and observations were collected monthly over 3 years at a well-described ocean time-series site of southern California. To find associations among these organisms, we calculated time-dependent rank correlations (that is, local similarity correlations) among relative abundances of bacteria, archaea, protists, total abundance of bacteria and viruses and physico-chemical parameters. We used a network generated from these statistical correlations to visualize and identify time-dependent associations among ecologically important taxa, for example, the SAR11 cluster, stramenopiles, alveolates, cyanobacteria and ammonia-oxidizing archaea. Negative correlations, perhaps suggesting competition or predation, were also common. The analysis revealed a progression of microbial communities through time, and also a group of unknown eukaryotes that were highly correlated with dinoflagellates, indicating possible symbioses or parasitism. Possible ‘keystone’ species were evident. The network has statistical features similar to previously described ecological networks, and in network parlance has non-random, small world properties (that is, highly interconnected nodes). This approach provides new insights into the natural history of microbes.

Defining DNA-Based Operational Taxonomic Units for Microbial-Eukaryote Ecology

ABSTRACT DNA sequence information has increasingly been used in ecological research on microbial eukaryotes. Sequence-based approaches have included studies of the total diversity of selected ecosystems, studies of the autecology of ecologically relevant species, and identification and enumeration of species of interest for human health. It is still uncommon, however, to delineate protistan species based on their genetic signatures. The reluctance to assign species-level designations based on DNA sequences is in part a consequence of the limited amount of sequence information presently available for many free-living microbial eukaryotes and in part a consequence of the problematic nature of and debate surrounding the microbial species concept. Despite the difficulties inherent in assigning species names to DNA sequences, there is a growing need to attach meaning to the burgeoning amount of sequence information entering the literature, and there is a growing desire to apply this information in ecological studies. We describe a computer-based tool that assigns DNA sequences from environmental databases to operational taxonomic units at approximately species-level distinctions. This approach provides a practical method for ecological studies of microbial eukaryotes (primarily protists) by enabling semiautomated analysis of large numbers of samples spanning great taxonomic breadth. Derivation of the algorithm was based on an analysis of complete small-subunit (18S) rRNA gene sequences and partial gene sequences obtained from the GenBank database for morphologically described protistan species. The program was tested using environmental 18S rRNA data sets for two oceanic ecosystems. A total of 388 operational taxonomic units were observed for 2,207 sequences obtained from samples collected in the western North Atlantic and eastern North Pacific oceans.

Investigating Microbial Eukaryotic Diversity from a Global Census: Insights from a Comparison of Pyrotag and Full-Length Sequences of 18S rRNA Genes

ABSTRACT Next-generation DNA sequencing (NGS) approaches are rapidly surpassing Sanger sequencing for characterizing the diversity of natural microbial communities. Despite this rapid transition, few comparisons exist between Sanger sequences and the generally much shorter reads of NGS. Operational taxonomic units (OTUs) derived from full-length (Sanger sequencing) and pyrotag (454 sequencing of the V9 hypervariable region) sequences of 18S rRNA genes from 10 global samples were analyzed in order to compare the resulting protistan community structures and species richness. Pyrotag OTUs called at 98% sequence similarity yielded numbers of OTUs that were similar overall to those for full-length sequences when the latter were called at 97% similarity. Singleton OTUs strongly influenced estimates of species richness but not the higher-level taxonomic composition of the community. The pyrotag and full-length sequence data sets had slightly different taxonomic compositions of rhizarians, stramenopiles, cryptophytes, and haptophytes, but the two data sets had similarly high compositions of alveolates. Pyrotag-based OTUs were often derived from sequences that mapped to multiple full-length OTUs at 100% similarity. Thus, pyrotags sequenced from a single hypervariable region might not be appropriate for establishing protistan species-level OTUs. However, nonmetric multidimensional scaling plots constructed with the two data sets yielded similar clusters, indicating that beta diversity analysis results were similar for the Sanger and NGS sequences. Short pyrotag sequences can provide holistic assessments of protistan communities, although care must be taken in interpreting the results. The longer reads (>500 bp) that are now becoming available through NGS should provide powerful tools for assessing the diversity of microbial eukaryotic assemblages.

Examination of the Seasonal Dynamics of the Toxic Dinoflagellate Alexandrium catenella at Redondo Beach, California, by Quantitative PCR

ABSTRACT The presence of neurotoxic species within the genus Alexandrium along the U.S. coastline has raised concern of potential poisoning through the consumption of contaminated seafood. Paralytic shellfish toxins (PSTs) detected in shellfish provide evidence that these harmful events have increased in frequency and severity along the California coast during the past 25 years, but the timing and location of these occurrences have been highly variable. We conducted a 4-year survey in King Harbor, CA, to investigate the seasonal dynamics of Alexandrium catenella and the presence of a particulate saxitoxin (STX), the parent compound of the PSTs. A quantitative PCR (qPCR) assay was developed for quantifying A. catenella in environmental microbial assemblages. This approach allowed for the detection of abundances as low as 12 cells liter−1, 2 orders of magnitude below threshold abundances that can impact food webs. A. catenella was found repeatedly during the study, particularly in spring, when cells were detected in 38% of the samples (27 to 5,680 cells liter−1). This peak in cell abundances was observed in 2006 and corresponded to a particulate STX concentration of 12 ng liter−1, whereas the maximum STX concentration of 26 ng liter−1 occurred in April 2008. Total cell abundances and toxin levels varied strongly throughout each year, but A. catenella was less abundant during summer, fall, and winter, when only 2 to 11% of the samples yielded positive qPCR results. The qPCR method developed here provides a useful tool for investigating the ecology of A. catenella at subbloom and bloom abundances.

Monthly to interannual variability of microbial eukaryote assemblages at four depths in the eastern North Pacific

The monthly, seasonal and interannual variability of microbial eukaryote assemblages were examined at 5 m, the deep chlorophyll maximum, 150 m and 500 m at the San Pedro Ocean Time-series station (eastern North Pacific). The depths spanned transitions in temperature, light, nutrients and oxygen, and included a persistently hypoxic environment at 500 m. Terminal restriction fragment length polymorphism was used for the analysis of 237 samples that were collected between September 2000 and December 2010. Spatiotemporal variability patterns of microeukaryote assemblages indicated the presence of distinct shallow and deep communities at the SPOT station, presumably reflecting taxa that were specifically adapted for the conditions in those environments. Community similarity values between assemblages collected 1 month apart at each depth ranged between ∼20% and ∼84% (averages were ∼50–59%). The assemblage at 5 m was temporally more dynamic than deeper assemblages and also displayed substantial interannual variability during the first ∼3 years of the study. Evidence of seasonality was detected for the microbial eukaryote assemblage at 5 m between January 2008 and December 2010 and at 150 m between September 2000 and December 2003. Seasonality was not detected for assemblages at the deep chlorophyll a maximum, which varied in depth seasonally, or at 500 m. Microbial eukaryote assemblages exhibited cyclical patterns in at least 1 year at each depth, implying an annual resetting of communities. Substantial interannual variability was detected for assemblages at all depths and represented the largest source of temporal variability in this temperate coastal ecosystem.

Seasonality and disturbance: annual pattern and response of the bacterial and microbial eukaryotic assemblages in a freshwater ecosystem.

High-throughput pyrosequencing of SSU rDNA genes was used to obtain monthly snapshots of eukaryotic and bacterial diversity and community structure at two locations in Lake Texoma, a low salinity lake in the south central United States, over 1 year. The lake experienced two disturbance events (i) a localized bloom of Prymnesium parvum restricted to one of the locations that lasted from January to April, and (ii) a large (17 cm), global rain event in the beginning of May, overlaid onto seasonal environmental change. Eukaryotic species richness as well as both eukaryotic and bacterial community similarity exhibited seasonal patterns, including distinct responses to the rain event. The P. parvum bloom created a natural experiment in which to directly explore the effects of an Ecosystem Disruptive Algal Bloom (EDAB) on the microbial community separated from seasonal changes. Microbial species richness was unaffected by the bloom, however, the eukaryotic community structure (evenness) and the patterns of both eukaryotic and bacterial community similarity at bloom and non-bloom sites were statistically distinct during the 4 months of the bloom. These results indicate that physical and biological disturbances as well as seasonal environmental forces contribute to the structure of both the eukaryotic and bacterial communities.

QUANTITATIVE REAL-TIME POLYMERASE CHAIN REACTION FOR COCHLODINIUM FULVESCENS (DINOPHYCEAE), A HARMFUL DINOFLAGELLATE FROM CALIFORNIA COASTAL WATERS 1

Harmful blooms formed by species of the dinoflagellate Cochlodinium have caused massive fish kills and substantial economic losses in the Pacific Ocean. Recently, prominent blooms of Cochlodinium have occurred in central and southern California (2004–2008), and Cochlodinium cells are now routinely observed in microscopical analysis of algal assemblages from Californian coastal waters. The first documented economic loss due to a Cochlodinium bloom in California occurred in Monterey Bay and resulted in the mortality of commercially farmed abalone. Increasing occurrences of Cochlodinium blooms, the fact that these cells preserve poorly using standard techniques, and the difficulty of identifying preserved specimens using morphological criteria make Cochlodinium species prime candidates for the development of a quantitative real‐time polymerase chain reaction (qPCR) approach. The 18S rDNA gene sequenced from Cochlodinium cells obtained from California coastal waters, as well as GenBank sequences of Cochlodinium, were used to design and test a Molecular Beacon® approach. The qPCR method developed in this study is species specific, sensitive for the detection of C. fulvescens that has given rise to the recent blooms in the eastern Pacific Ocean, and spans a dynamic abundance range of seven orders of magnitude. Initial application of the method to archived field samples collected during blooms in Monterey Bay revealed no statistically significant correlations between gene copy number and environmental parameters. However, the onset of Cochlodinium blooms in central California was consistent with previously reported findings of correlations to decreased surface temperature and increased inputs of nitrogenous nutrients.

Estimating Protistan Diversity Using High‐Throughput Sequencing

Sequencing hypervariable regions from the 18S rRNA gene is commonly employed to characterize protistan biodiversity, yet there are concerns that short reads do not provide the same taxonomic resolution as full‐length sequences. A total of 7,432 full‐length sequences were used to perform an in silico analysis of how sequences of various lengths and target regions impact downstream ecological interpretations. Sequences that were longer than 400 nucleotides and included the V4 hypervariable region generated results similar to those derived from full‐length 18S rRNA gene sequences. Present high‐throughput sequencing capabilities are approaching protistan diversity estimation comparable to whole gene sequences.

Gene expression in the mixotrophic prymnesiophyte, Prymnesium parvum, responds to prey availability

The mixotrophic prymnesiophyte, Prymnesium parvum, is a widely distributed alga with significant ecological importance. It produces toxins and can form ecosystem disruptive blooms that result in fish kills and changes in planktonic food web structure. However, the relationship between P. parvum and its prey on the molecular level is poorly understood. In this study, we used RNA-Seq technology to study changes in gene transcription of P. parvum in three treatments with different microbial populations available as potential prey: axenic P. parvum (no prey), bacterized P. paruvm, and axenic P. parvum with ciliates added as prey. Thousands of genes were differentially expressed among the three treatments. Most notably, transcriptome data indicated that P. parvum obtained organic carbon, including fatty acids, from both bacteria and ciliate prey for energy and cellular building blocks. The data also suggested that different prey provided P. parvum with macro- and micro-nutrients, namely organic nitrogen in the form of amino acids from ciliates, and iron from bacteria. However, both transcriptomic data and growth experiments indicated that P. parvum did not grow faster in the presence of prey despite the gains in nutrients, although algal abundances attained in culture were slightly greater in the presence of prey. The relationship between phototrophy, heterotrophy and growth of P. parvum is discussed.

Comparative Transcriptome Analysis of Four Prymnesiophyte Algae

Genomic studies of bacteria, archaea and viruses have provided insights into the microbial world by unveiling potential functional capabilities and molecular pathways. However, the rate of discovery has been slower among microbial eukaryotes, whose genomes are larger and more complex. Transcriptomic approaches provide a cost-effective alternative for examining genetic potential and physiological responses of microbial eukaryotes to environmental stimuli. In this study, we generated and compared the transcriptomes of four globally-distributed, bloom-forming prymnesiophyte algae: Prymnesium parvum, Chrysochromulina brevifilum, Chrysochromulina ericina and Phaeocystis antarctica. Our results revealed that the four transcriptomes possess a set of core genes that are similar in number and shared across all four organisms. The functional classifications of these core genes using the euKaryotic Orthologous Genes (KOG) database were also similar among the four study organisms. More broadly, when the frequencies of different cellular and physiological functions were compared with other protists, the species clustered by both phylogeny and nutritional modes. Thus, these clustering patterns provide insight into genomic factors relating to both evolutionary relationships as well as trophic ecology. This paper provides a novel comparative analysis of the transcriptomes of ecologically important and closely related prymnesiophyte protists and advances an emerging field of study that uses transcriptomics to reveal ecology and function in protists.