Bacterial Responses to Ocean Acidification Featured

Ocean acidification, resulting from an increase in atmospheric CO2, is a growing concern as it is projected to impact all ocean regions and affect a wide variety of marine life. Although a significant amount of research has focused on studying the effects of ocean acidification (OA) on marine animal phyla and even eukaryotic phytoplankton, less attention has been focused on how OA affects marine bacteria. Both autotrophic (“producer”) and heterotrophic (“consumer”) bacteria play important roles in the marine food web; Synechococcus and Prochlorococcus (picocyanobacteria) alone contribute up to 50% of fixed carbon in the marine environment. The response of bacterioplankton to ocean acidification has been inconsistent across studies and more research is needed at multi-species and community scales as opposed to laboratory experiments on a single species of cultured bacteria.

Experimental design

Fig. 1: The treatment flasks, each held within a 5-gallon bucket all sitting in a tank of flowing seawater for temperature regulation.

Over the course of three weeks at FHL in the summer of 2016, an REU student and I examined the effect of increased pCO2 on (1) Synechococcus and Prochlorococcus abundance and (2) the diversity and taxonomic composition of the entire bacterial community present in local ocean water samples. Each of six flasks was filled with 3 liters of filtered seawater collected from the Ocean Acidification Environmental Lab. Aalborg GFC mass-flow controllers were used to regulate the flow of air or CO2 into the flasks (Figure 1). The waters surrounding San Juan Island experience an average pH of 7.8 ± 0.06 but the surrounding waters of Puget Sound experience a broad range of pH from 7.4 in Hood Canal to 8.6 in Port Susan and Padilla Bay. A pH of 8.05 ± 0.05 was maintained in three “control” flasks by bubbling ambient air into the seawater, and a pH of 7.60 ± 0.05 was maintained in three “acidified treatment” flasks by bubbling in a mixture of ambient air and CO2. Every other day, a 50% water change was performed for each flask using filtered seawater and 1.5 L of the discarded water was filtered through a 0.2 µm Sterivex filter to collect a sample of the microbial community for DNA extraction. Each morning, 1 ml of water was collected from each of the six flasks to be analyzed on a Novocyte flow cytometer, measuring the abundance of autotrophic bacteria (Synechococcus and Prochlorococcus) as well as total bacteria of each sample. Extracted DNA samples from each of the flasks over 21 days were amplified for 16S rRNA and were prepared for Illumina Miseq sequencing to identify the bacteria.

For both Synechococcus and Prochlorococcus bacteria populations, pH had an effect on abundance throughout the 21-day experiment. Mean abundance for both bacteria were significantly lower in the pH 7.60 treatment compared to the pH 8.0 treatment (Figure 2). Although community richness of the combined samples differed across experimental days, there was no significant difference in community richness nor evenness between pH treatments.



Bacterial abundance graphs

Fig. 2: Synechococcus (top graph) and Prochlorococcus (bottom graph) abundance over time in different pH treatments: blue line is “control” pH of 8.0 and red line is “acidified” pH of 7.6. Both species’ abundance were lowered significantly by acidic conditions. Weighted UniFrac distance is a measure of relative relatedness of community members; it incorporates phylogenetic distance and the relative abundance of specific organisms. Weighted UniFrac distance among samples from our different pH treatments was greater than the distance among samples within the same pH treatment. Meaning: samples within the same pH treatment were more closely related. Not surprisingly, weighted UniFrac distance was also different between samples taken on different days. An analysis of composition showed that there were various microbial taxa that significantly differed in their abundance between pH treatments (Table 1). Some of the taxa that showed the biggest differences were unassigned in my analyses. I am still analyzing this data set and hope to examine functional roles of some of the bacterial taxa that differed in abundance between pH treatments. Hopefully this will allow us to better understand the potential significance of their increase or decrease under acidified ocean conditions, and thus one possible impact on carbon fixation in the marine environment.

Bacteria relatedness

Tbl. 1: Taxa with significantly different percentile counts between pH treatments from an ANCOM analysis. The percentile counts represent the number of sequences identified as a given taxon in said percentage of samples within a given treatment. Taxa are listed in the order of highest 75th percentile counts to lowest, for pH 7.6 treatment.

- by Lisa Crummet
Assistant Professor of Biology at Soka University of America in Aliso Viejo, CA.

Leave a comment

Make sure you enter all the required information, indicated by an asterisk (*). HTML code is not allowed.

back to top