Factors which might affect microbial communities have been a popular point of study in the past, especially looking at the relative importance of temperature and nutrient concentrations. It has been found that bacterioplankton diversity followed a latitudinal gradient, with maximum potential richness being primarily driven by temperature. This study furthers these findings and aims to characterize seasonal patterns of bacterioplankton in the Western English Channel. Three different hypotheses were looked at. These included, looking at whether the observed seasonal patterns correlate with (1) varying concentrations of inorganic nutrients, (2) annual water-temperature cycle or (3) the population structure of the eukaryotic phytoplankton and zooplankton.
Seawater samples were collected over 6 years. DNA was extracted from samples and 16S rDNA V6 amplification and pyrosequencing took place. The established sequence data was then analysed and standardised.
The data showed that a total of 8794 operational taxonomic units (OTU) of bacterioplankton were identified. Significant seasonal variations in OTU frequency were found but there were also strong repeating patterns. The Alphaproteobacteria were the most abundant class, this has been found in other studies. Alpha diversity remained relatively constant across the time series but showed distinct patterns with the diversity in winter and lowest in summer. OTU richness was most similar when comparing the same time of year, there were large seasonal differences inter-annual suggesting that the seasonal cycle was consistent across the years. Rickettsiales and Rhodobacterales were some of the most abundant orders and had different seasonal abundances. The difference in the length of each day accounted for a 65% of variance in community diversity.
This study confirmed that strong seasonal patterns occur in surface water microbial communities. The biggest factor affecting overall bacterial richness was day length. The length of the time series meant that subtle changes in patterns of individual taxa were observed. SAR11 and Roseobacter were two examples of different taxa showing seasonal cycles. It was found that the seasonal variance in bacterial community composition were due to environmental factors rather than interactions with eukaryotes.
Overall, I did not like this paper. I found that the authors repeated themselves quite a lot in the introduction and that there were too many different components of the results; therefore it was difficult to interpret. I am not sure if it is just me that thinks this as the subject area doesn’t interest me much.
Jack A Gilbert, Joshua A Steele, J Gregory Caporaso, Lars Steinbrück, Jens Reeder, Ben Temperton, Susan Huse, Alice C McHardy, Rob Knight, Ian Joint, Paul Somerfield, Jed A Fuhrman and Dawn Field (2011). Defining seasonal marine microbiology community dynamics. The ISME Journal 6, 298-308.
http://www.nature.com/ismej/journal/v6/n2/full/ismej2011107a.html
Hi Sophie,
ReplyDeleteI think I am a Iittle confused about the authors hypothesises and conclusions here. Am I right in thinking they concluded the biggest factor correlating with diversity was day length (which is considered an environmental factor), although this was not one of their original hypothesises? And I also wondered how the authors came to the conclusion that seasonal variances in community composition were due to environmental factors rather than interactions with eukaryotes, or any of the other hypothesises?
Also the paper focusses on bacterial richness as a diversity index, did they say how they measured/defined this? Was it just the number of OTUs or did they account for the relative abundance of each group or the functional diversity present?
Thank you :)
Hi Vicky,
ReplyDeleteWith regards to day length, this was found to be the variable with the most explanatory power for overall bacterial richness. I think this was a bit of a surprise! There was nothing metioned about it in the methods and material section, however there is a section about it in the results. Basically to test whether changes in nutrients and and temperature provided the best correlation witbh changes in community diversity distance-based linear modeling was used.
Correlations between interactions with eukaryotes and seasonal variances were found but they were not as highly correlated as environmental factors.
Finally from my understanding, the number of OTUs was used as a diversity metric.
I hope this helps!
Hi Sophie,
ReplyDeleteI think this paper illustrates the problem that Vicky pointed out in her blog on Caporaso et al.'s study: "Importantly this study provides evidence that traditionally observed seasonal changes diversity are actually driven by the relative abundance of the same taxonomic groups, rather than absolute changes in community as was previously thought." (from Vicky's blog:Is the ocean just one big “seed bank” of microbial diversity?) So OTU richness is probably not the best way to study seasonal changes in community pattern.
Also "difference in day length" seems to me a very vague description of the selective force driving the observed pattern.
Differences in day length are intimitely linked to the seasons and can be broken down to several factors:
a) variation in sunlight influencing photosynthesis output
b) frequency of storms varies from season to season and causes the stratification in the water column to break up and makes nutrients available again
c) shorter days possibly mean that zooplankton spend more time grazing in shallow waters on their daily vertical migration
I can imagine that it is a combination of various factors, that's why the authors probably found a stronger correlation with changes in day length rahter than interaction with eukaryotes on its own.
This study furthered the work of Gilbert et al. (2009), which demonstrated am ideal for monitoring microbial diversity in marine ecosystems. Seasonal patterns were looked at using non-parametric multivariate analysis, based on ocurrances of bacterial OTUs. So they looked at seasonal changes in diversity but not at day length.
ReplyDeleteI have found another paper, Pinhassi and Hagstrom (2000), looking at seasonal distribution of marine bacterioplankton. In this paper in order to look at the populations densities of different bacteria, whole-genome DNA hybridization was used. Seasonal changes were found.
Do you think other studies could use this method?