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<p>While much is known about the abundance and genetic diversity of environmental
microbial communities, little is known about their taxon-specific activity. In this
thesis I address this gap using a model marine microbe, the cyanobacterium <italic>Prochlorococcus
spp.</italic>, which numerically dominates tropical and subtropical open oceans and
encompasses a group of genetically defined clades that are ecologically distinct.
Ribosomal RNA is a promising indicator of in situ activity because of its essential
role in protein synthesis as well as its phylogenetic information, which could be
used to distinguish clades among mixed populations. Here I show that, in a laboratory
system the specific growth rate of representative <italic>Prochlorococcus</italic>
strains could be quantitative predicted from cellular rRNA content (assessed by RT-qPCR),
cell size (assessed by flow cytometry) and temperature. Applying this approach in
the field, I show unique clade-specific activity patterns for <italic>Prochlorococcus</italic>.
For example, vertically within the euphotic zone, eHL-II activity is strongly impacted
by light and is consistent with patterns of photosynthesis and on a horizontal transect
from Hawaii to San Diego, eHL-I and eHL-II activities exhibit significant transitions
and appear to be regulated by temperature, nutrient and vertical mixing gradients.
Using ribosomal tag pyrosequencing of DNA and RNA, I have extended our observation
to the Eubacterial community and described the biomass distribution (rDNA) and activity
(rRNA) patterns from two representative depths (25 and 100 m) at a well-studied oligotrophic
ocean station. These results show that for some populations the abundances and activities
are significantly uncoupled, which suggests substantial top-down controls or physical
transport processes. Further exploring the taxon-specific activity patterns along
with abundances and environmental variables across time and space is essential to
better understanding the dynamics of a complex microbial system as well as predicting
the consequences of environmental change.</p>
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