Download Drivers of Population Dynamics in Bacterioplankton

Digital Comprehensive Summaries of Uppsala Dissertations
from the Faculty of Science and Technology 1230
Drivers of Population Dynamics in
Bacterioplankton
Spotlight on Alphaproteobacteria and its dominant
SAR11 Lineage
FRIEDERIKE HEINRICH
ACTA
UNIVERSITATIS
UPSALIENSIS
UPPSALA
2015
ISSN 1651-6214
ISBN 978-91-554-9172-7
urn:nbn:se:uu:diva-245072
Dissertation presented at Uppsala University to be publicly examined in Fries-salen,
Evolutionsbiologiskt Centrum (EBC), Norbyvägen 14, Uppsala, Friday, 10 April 2015 at
10:00 for the degree of Doctor of Philosophy. The examination will be conducted in English.
Faculty examiner: Prof. David Kirchman (University of Delaware, School of Marine Science
and Policy, Lewes).
Abstract
Heinrich, F. 2015. Drivers of Population Dynamics in Bacterioplankton. Spotlight
on Alphaproteobacteria and its dominant SAR11 Lineage. Digital Comprehensive Summaries
of Uppsala Dissertations from the Faculty of Science and Technology 1230. 54 pp. Uppsala:
Acta Universitatis Upsaliensis. ISBN 978-91-554-9172-7.
Bacteria are mediators of biogeochemical cycles and are in this way vital for maintaining life on
earth. Their distribution, abundance and functioning are driven by environmental heterogeneity
and dynamic change in abiotic and biotic factors. Both, freshwater lakes and oceans play
central roles in the global carbon cycle and bacteria in these systems perform many services
for the ecosystems, such as the transfer of organic carbon from primary producers to higher
trophic levels. With estimated relative abundances up to 50% of the total bacterioplankton,
the Alphaproteobacteria lineage SAR11 is the most abundant group of aquatic bacteria. It is
globally distributed and can be partitioned into multiple sub-clades, one of which is exclusive
to freshwaters. Until recently, the distribution, abundance and ecological role of this freshwater
SAR11 named LD12 was unknown. The aim of the thesis was to study the drivers and
mechanisms that influence the dynamics of aquatic bacterial communities in general and the
SAR11 and LD12 groups in particular. The thesis consists of environmental surveys of a
mesotrophic Lake Erken and the western Southern Ocean, an experiment and a data-mining
exercise to reveal the phylogenetic structure of the SAR11 lineage on various temporal and
spatial scales. The analysis of a long-term bacterioplankton community survey in lake Erken
provided insights about the dynamics of the entire bacterial community and the LD12 population
over an annual cycle. The results demonstrate that LD12 can be an equally abundant member
of freshwater communities as marine SAR11 in oceans. LD12 featured strong seasonality and
was positively coupled to environmental conditions indicative for an oligotrophic lifestyle.
LD12 as well as other dominant lake bacterioplankton also maintained stable populations
throughout spatial and temporal varying environments, but at high phylogenetic resolution,
habitat preferences were revealed, particularly in response to oxygen concentrations. The later
was not the case in LD12 as a single ribotype dominated. This is in stark contrast to the
habitat partitioning with light availability, depth and water masses observed for marine SAR11
subclades in the Southern Ocean. The global data-mining corroborated that LD12 as a group
was much less diverse than SAR11 furthermore, suggesting that the marine-freshwater barrier
acted as a population bottleneck. My work shows that bacterial populations can respond in very
different ways to environmental drivers, highlight the importance of highly resolved temporal
and spatial scales as well as the need for high phylogenetic resolutions to target ecologically
coherent populations.
Keywords: bacterial community dynamics, Alphaproteobacteria, SAR11, LD12, Southern
Ocean, lakes
Friederike Heinrich, Department of Ecology and Genetics, Limnology, Norbyv 18 D, Uppsala
University, SE-75236 Uppsala, Sweden.
© Friederike Heinrich 2015
ISSN 1651-6214
ISBN 978-91-554-9172-7
urn:nbn:se:uu:diva-245072 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-245072)
“Mistakes are the usual bridge between inexperience and wisdom”
Phyllis Theroux
Dedicated to curiosity
Supervisors:
Prof. Stefan Bertilsson
Department of Ecology and Genetics,
Limnology
Executive Manager, SciLifeLab
Uppsala, Sweden
Dr. Alexander Eiler
Department of Ecology and Genetics,
Limnology
Uppsala, Sweden
Dr. Annelie Wendeberg
Department Environmental Microbiology
Center for Environmental Research
Leipzig, Germany
Opponent:
Prof. David Louis Kirchman
School of Marine Science and Policy
University of Delaware
USA
List of Papers and Manuscripts
This thesis is based on the following papers, which are referred to in the text
by their Roman numerals.
I
II
III
IV
V
Logares, R., Bråte, J., Heinrich, F., Shalchian-Tabrizi, K., and
Bertilsson, S. (2010). Infrequent transitions between saline and
fresh waters in one of the most abundant microbial lineages
(SAR11). Molecular Biology and Evolution, 27:347–357
Heinrich, F., Eiler, A., Farnelid, H., Riemann, L. and Bertilsson,
S. Abundance and diversity of Alphaproteobacteria in the
Southern Ocean: the dark side of SAR11. Manuscript.
Heinrich, F. Eiler, A., and Bertilsson, S. (2013) Seasonality and
environmental control of freshwater SAR11 (LD12) in a temperate lake (Lake Erken, Sweden). Aquatic Microbial Ecoloy,
70:33–44
Heinrich, F., Eiler, A., Andersson, A. and Bertilsson, S.
Alteration of lake bacterioplankton diversity and community
composition during lake stratification and gradual oxygen depletion. Manuscript.
Eiler, A., Heinrich, F. Bertilsson, S. (2012) Coherent dynamics
and association networks among lake bacterioplankton taxa.
The ISME Journal, 6:330–342
Paper I, III and V are reproduced with the kind permission from the Publishers: Oxford University Press, Inter-Research and Nature Publishing Group.
List of additional Papers and Manuscripts
Papers not included in the thesis:
Alonso-Sáez, L., Waller, A. S. A., Mende, D. R. D., Bakker, K. K., Farnelid,
H. H., Yager, P. L. P., Lovejoy, C. C., Tremblay, J. - É. J., Potvin, M. M.,
Heinrich, F. et al. (2012). Role for urea in nitrification by polar marine Archaea. Proc. Natl. Acad. Sci. U.S.A., 109: 17989–17994
Alonso-Sáez, L., Andersson, A., Heinrich, F., and Bertilsson, S. (2011).
High archaeal diversity in Antarctic circumpolar deep waters. Environmental
Microbiology Reports, 3: 689–697
Contents
1
Introduction ............................................................................................. 11
1.1 A primer on bacteria ........................................................................ 11
1.2 Bacterial diversity and its importance ............................................. 12
1.3 Constraints on bacteria: competing in time and space .................... 13
1.3.1 Bacterial biogeography ............................................................ 14
1.3.2 Phylogenetic measures as an alternative alpha and beta
diversity measure ................................................................................. 15
1.4 Aquatic bacteria - Spotlight on Alphaproteobacteria ...................... 16
1.4.1 The secret life of aquatic ecosystems ...................................... 16
1.4.2 Marine Alphaproteobacteria .................................................... 17
1.4.3 Freshwater Alphaproteobacteria .............................................. 18
1.4.4 SAR11 as models in aquatic bacteriology ............................... 18
2
The Present Thesis .................................................................................. 20
2.1 Aims ................................................................................................ 20
2.2 Methods ........................................................................................... 21
2.2.1 Study sites and experiments .................................................... 21
2.2.2 Analytical methods .................................................................. 22
2.3 Results ............................................................................................. 27
2.4 Conclusions and Outlook ................................................................ 36
3
Summary in Swedish .............................................................................. 41
4
Summary For Kids .................................................................................. 45
5
Acknowledgements ................................................................................. 46
6
References ............................................................................................... 49
Abbreviations
16S rDNA
AASW
CARD
CDW
DNA
FISH
NMDS
OTU
PCR
PYC
RNA
SW
THE
UPGMA
16S rRNA gene
Antarctic Surface Water
Catalyzed Reporter Deposition
Circumpolar-Deep-Water
Deoxyribonucleic Acid
Fluorescence in-situ hybridization
Nonmetric Multidimensional Scaling
Operational Taxonomic Unit
Polymerase Chain Reaction
Pycnocline
Ribonucleic Acid
Shelfwater
Thermocline
Unweighted Paired-Group Average
List of Figures
Figure 1. Conceptual figure of space-time relationships
Figure 2. Sampling-map of the Southern Ocean.
Figure 3. Methodological strategies for bacterial community analysis
Figure 4. Distinct saline and freshwater lineages in SAR11
Figure 5. SAR11 fluorescence microscopy images
Figure 6. Distribution of SAR11 populations in the Southern Ocean
Figure 7. Seasonal dynamics of LD12 relative abundance in Lake Erken
Figure 8. NMDS of community composition in Lake Erken
Figure 9. From phyla to OTU – time course of Actinobacteria abundance
Figure 10. Standardized abundance profiles for identified tribes
Figure 11. Sub-network centered around tribe LD12
Figure 12. How I showed my kids what I see in the microscope
1 Introduction
1.1 A primer on bacteria
The age of Earth is estimated to be 4.5 billion years and ancestors of extant
bacteria are thought to have appeared around 3.8 billion years ago (DeLong
and Pace 2001). Therewith, bacteria have been residing on Earth the last
80% of its existence and continue to inhabit and shape every corner of the
biosphere, from bedrock to the atmosphere (Amaral-Zettler et al. 2014).
Their immense biomass, estimated to make up as much as 90% of the total biomass on Earth (Fuhrman et al. 1989, Whitman et al. 1998) and the
vast metabolic diversity makes them to mediating hubs in biogeochemical
cycles (Falkowski 2008). A main service that bacteria perform for many
ecosystems, and in particular aquatic systems such as oceans and lakes, is
the transfer of organic carbon from primary producers to higher trophic levels, thereby forming the basis for the so-called microbial loop (Azam et al.
1983, Pomeroy 1974, Fenchel et al. 2008).
The total abundance of bacteria in nature varies greatly between ecosystems, but typically reach as many as 107 cells per ml water or 1010 cells per
cm3 soil. This results in impressive 4-6 x 1030 bacterial cells on Earth
(Whitman et al. 1998, Torsvik et al. 2002). Even after decades of debate
about how many bacterial species make up this immense number, no consensus has been reached.
One of several reasons for this is the problem around the definition of microbial species. None of the features that classically define a species, such as
reproductive barriers, morphology, or physiology can be readily adapted to
bacteria. An alternative and very practical definition relies on the genetic
similarity between organisms. It is now very common to use 97% similarity
in the slowly evolving 16S rRNA gene to group bacteria together into socalled operational taxonomic units (OTUs) (Rossello-Moran and Amann
2001, Stackbrandt et al. 2002). However, this approach has frequently been
called into question, since the concept of “OTUs” is not backed up by theory
and sometimes has little biological meaning.
“Species” are biological units, where bacterial genotypic variation is the
result of sequence variation in alleles, but also dominated by changes in gene
content. Despite many theoretical concerns, recent evidence suggests that
bacteria are organized into ecologically cohesive genotypic clusters (Achtman and Wagner 2008, Gevers et al. 2005, Schmidt et al. 2014).
11
Thus, incorporating coherence in ecological properties for operationally
defined taxonomic units such as OTUs would bring meaning and predictive
power to the concept.
To circumvent the fractious term “species“ I used both the technical term
OTU, and the genetic term “population” to imply common ecological properties. A population refers to a group of bacterial cells with a
pre-defined genetic similarity in the 16S rRNA gene that is assumed to share
a certain extent of ecological cohesion. The exact definition varied among
the studies in this thesis reflecting the dynamic development and missing
consensus in the field.
Despite the current inability to robustly define the fundamental biological
units of bacterial diversity (e.g. species), significant progress in uncovering
the complexity of bacterial communities is now enabled by rapidly evolving
technologies. This is for example mirrored in the rapidly increasing number
of complete bacterial genomes (>15.000). However, this number becomes
dwarfed compared to the recently estimated existence of millions if not tens
of millions bacterial “species” on Earth (Eisen informal report).
An additional factor limiting our current ability to study bacteria is the
fact that the vast majority of bacteria remain uncultivated and as of today
over, half of the 50 defined bacterial phyla remain without cultured representatives (Hugenholz et al. 1998, Rappé and Giovannoni 2003). Our realization that bacteria and other microorganisms are of central importance for
the Earth system leaves plenty of urgent questions that must be addressed if
we are to come closer to understanding biogeochemical and ecological roles.
1.2 Bacterial diversity and its importance
Biodiversity may be defined as the variety and variability among organisms
and the ecological complexes in which they occur. Biodiversity can be considered at different scales of biological organization, from genes to ecosystems (Brönmark et al. 2002). Ecologists mainly distinguish between three
aspects of diversity, the local diversity within a single community or a
system (α-diversity), the comparative diversity between communities or
systems (β-diversity) and a measure across multiple communities or systems
(γ-diversity) (Tuomisto et al. 2011, Bunge et al. 2014).
Many measures describing the different aspects of diversity rely on
frameworks that in one way or another define the fundamental units of diversity (i.e. a species). The awareness of the limitations of grouping organisms in predefined (taxonomic) groups led to the concept of phylogenetic
diversity (PD). This approach does not only circumvent the problematic
“species” issue, in addition it provides information about the evolutionary
relationships between communities to be compared (Faith 1992).
12
Studying bacterial diversity is in many ways a fruitful approach to retrieve ecological information about the communities and the systems they
inhabit. It does not only allow for a comparison between environments but
also gives the opportunity to understand the mechanisms underpinning the
distribution of bacteria, and to what degree communities can resist disturbances. Thus, by determining diversity we can also, at least in theory, predict
ecosystem functioning and sustainability (Fakruddin et al 2013).
1.3 Constraints on bacteria: competing in time and
space
Due to specific physical and metabolic needs, bacterial populations occupy
unique niches representing a complex set of environmental properties. Niche
theory postulates that no two species can coexist over time if they have the
same niche (Hutchinson 1961, Prosser et al. 2007, Gifford et al. 2013). Yet,
the applicability of the niche concept for bacteria is challenged by the apparent lack of approaches to define the multitude of chemical and physical
properties on appropriate scales (i.e. micrometers). Usually, environmental
properties are defined by bulk measurements neglecting fine-scale heterogeneity in for example a drop of water.
Habitats are characterized by a multitude of local influences such as abiotic parameters including but not limited to nutrients, temperature, radiation
climate, oxygen, salinity or pH as well as biotic factors including the presence and action of viruses, microeukaryote predation or parasitism.
However, the environmental setting is not only directly defined by those
parameters as such, but is shaped by complex networks of abiotic and biotic
interactions. Within a bacterial community, tightly wired interactions within
populations (Intra-population) and between populations (Inter-population)
are know to occur and also play major parts in defining the occurrence of
populations in the environment.
In addition to this type of system-intrinsic interactions (local interactions)
the successful establishment depends also on system-extrinsic processes
(regional processes). These are for example the dispersal potential of a population, including migration in or out of a given environment (Lindström and
Langenheder 2012). Many bacteria are motile by actively swimming and
gliding or passively motile by using gas vesicles for buoyancy; the range for
such mobility is still very limited because of their small size (Martiny et al.
2006). Hence, other assisted transport mechanisms, such as hitchhiking by
attaching to particles or larger motile organisms, or simply being temporarily
ingested by predators and travel like "Jonah and the whale" for later release
via fecal matter may support long distance dispersal of bacteria.
13
The space in which bacteria find a niche is multidimensional. One can reduce the complexity, by reducing the constraints on bacteria to two dimensions: Space and Time (Figure 1).
By reducing the dimensions, microbial ecologists can start to describe, interpret and understand observed patterns in bacterial diversity and how diversity is linked to the functional potential of bacterial communities along
these dimensions. Hence as a result of probing the dynamics of bacterial
communities, the opportunity for understanding processes underpinning
ecosystem function opens up.
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Figure 1. Conceptual figure describing the space-time relationships of bacterial
communities. The bacterial community, pictured as a box of cells, is not static but is
forced to restructure along with environmental changes taking place along time and
space dimensions. The biotic and abiotic drivers of communities and populations
change continuously along these dimensions and form a complex network of interactions where niches constantly emerge and disappear. Depending on the characteristics of the community and of the populations within, the bacterial community undergoes constant changes and also exerts a feedback on the abiotic and biotic drivers.
1.3.1 Bacterial biogeography
Biogeographic patterns are primarily caused by the heterogeneity in chemical and physical properties of the environment (Levin 1992, Martiny et al.
2006, Hanson et al. 2012) and biotic interactions. However, dispersal and
evolutionary processes also influence biogeographic patterns in bacteria.
Since bacteria are small in size, biogeographic patterns may not only be apparent at the macroscale, but can also arise at the microscale (Sparrow
1999). This highlights a general challenge for microbial ecologists; i.e. to
study microorganisms and their traits at the most meaningful scales.
14
The capacity of a microbial cell or functionally associated consortia or
community to directly interact with the surrounding environment is in many
ways spatially limited to the microscale because of the small size of bacteria.
Aside from creating patchiness in the environment, particles and their
boundary layers give rise to spatial differences in apparently “homogenic“
environments (Stocker 2012). On the macroscale, biogeographic patterns
have frequently been observed over spatial scales down to a few meters,
revealing patterns such as the existence of distinct microbial communities in
different depth strata of freshwater lakes (Garcia et al. 2013). Thus it comes
as no surprise that bacterial communities frequently differ markedly between
lake systems (Yannarell and Triplett 2004, DeWeaver et al. 2005, Newton et
al. 2011).
Temporal scales are particularly relevant regarding growth rates. Thus
relevant timescales do not only depend on the system and its character but
also on intrinsic features of the population under scrutiny. Both of these factors are of central importance for interpreting both relationships between
environmental conditions and specific populations as well as co-occurrence
patterns. Using statistical inferences on temporal co-occurrence data, new
information can be gathered about mechanisms and processes controlling
bacterial community interactions (Fuhrman et al. 2015). Positive associations among taxa can for example be interpreted as ecological coherence or
mutualistic interactions whereas negative associations suggest either niche
partitioning or direct interactions, such as competition or allelopathy.
Studying competition in bacterial communities is challenging and often
centered around the constant battle for nutrients. Bacteria have evolved different strategies to satisfy their need for resources (Hibbing et al. 2010);
some use high affinity systems to acquire dissolved nutrients under low nutrient concentrations, whereas copiotrophic bacteria are more competitive
under high nutrient concentrations and exploit patches of nutrients in time
and space. These changes in dynamics are not two-dimensional and often are
wired within a network of interactions. To cite Hibbings et al. 2009: An
“interaction network resembles the game of ‘rock, paper, scissors’: species A
dominates species B, which outcompetes species C, which in turn outcompetes species A.”
1.3.2 Phylogenetic measures as an alternative alpha and beta
diversity measure
Patterns of diversity can also be studied by using phylogenetic measures.
Such phylogenetic measures of biodiversity incorporate properties of phylogenetic relationships between genotypes within or between samples.
There are four main measures: (1) the Faith's PD (phylogenetic distance) is
defined as the total branch length spanned in a phylogenetic tree that include
15
all species in a local community (an alpha diversity measure); (2) the Mean
Phylogenetic Distance (MPD); (3) the Mean Nearest Taxon Distance
(MNTD) which can be used to describe community differences between
samples representing a beta-diversity measure and (4) Unifrac distance. By
comparing observed MPD and MNTD with measures obtained from null
models, some first insights into the ecological and evolutionary forces that
shape bacterial communities can be obtained (Horner Devine and Bohannan
2006).
There are three outcomes of such an analysis: The first is called phylogenetic clustering and shows that co-occurring populations are more closely
related than expected by chance. The second is called phylogenetic overdispersion and is a result of co-occurring populations being more distantly related. And third, random patterns can occur. The main assumption of this
approach is that closely related taxa are more likely to interact intensely with
each other than with more distantly related taxa. Developed further, this
means that interspecific interactions are influenced by the net ecological
similarity of taxa, and closely related taxa tend to be more similar ecologically than distantly related taxa (Harvey and Pagel 1991). Situations where
co-occurring genotypes are observed to be more closely related than expected by chance is termed phylogenetic clustering (Webb 2002). This indicates that habitat filtering, the exclusion of organisms that can not adapt to
the local environment, is important in maintaining diversity and might be
more important than competition. In contrast, a community composed of
distantly related genotypes could be the result of current or past competitive
exclusion between similar (and thus closely related) genotypes. This has
been linked to convergent evolution in traits important for persistence in a
given environment (Cavender-Bares et al. 2004, Kembel and Hubbell 2006).
1.4 Aquatic bacteria - Spotlight on Alphaproteobacteria
1.4.1 The secret life of aquatic ecosystems
Aquatic ecosystems cover a large part of our planet and bacteria inhabit the
countless streams and rivers, the vast and deep global oceans as well as the
107 million lakes on the globe. We still know very little about who those
bacteria are, how they live and how they specifically influence the environment at the local and global scale (Rappé and Giovannoni 2004, Newton et
al. 2011). One major reason for this shortage of information is our apparent
inability to isolate and cultivate most of these aquatic microorganisms, however, there has been recent advances in cultivation-independent detection
methods that offer attractive shortcuts to learn about the biology uncultured
microbes. Through those methods we are now beginning to realize the diversity and composition of microbial communities in the biosphere.
16
1.4.2 Marine Alphaproteobacteria
Alphaproteobacteria are generally a major component of marine bacterial
communities (Hagström et al. 2002, Cottrell et al. 2000). The high abundance and global distribution of Alphaproteobacteria suggest that they mediate a significant fraction of the dissolved organic matter (DOM) flux in the
oceans. This phylum is characterized by a very high morphological, metabolic and phylogenetic diversity. At present, 140 genera are described with
functional capacities spanning over the entire metabolic landscape, including
photo-, litho- and organotroph energy acquisition, autotrophy or heterotrophy to acquire carbon for biosynthesis and combinations of the above (i.e.
mixotrophy as reviewed in Eiler 2006). Proton pumping photoproteins such
as proteorhodopsins have been found in a variety of bacteria, including the
major alphaproteobacterial lineages Rhodobactereales, Rhodospirales and
Pelagibactereales (review DeLong and Beja 2010). Light-dependent adaptive strategies for energy acquisition are thus well recognized in the Alphaproteobacteria.
The Roseobacter lineage includes abundant and widespread members of
the order of Rhodobactereales. This lineage plays an important role in the
global carbon and sulfur cycles and many representatives are capable of
aerobic anoxygenic photosynthesis, while many can also oxidize carbon
monoxide, which is a potent greenhouse gas (Döbler et al. 2006). Finally,
many taxa within this lineage have the ability to produce dimethylsulfide
through degradation of algal osmolytes.
Roseobacter affiliated bacteria have been detected in a large variety of
habitats, from coastal regions to deep-sea sediments and from polar ice to
tropical latitudes. They can constitute up to 10% of all bacteria in the Arctic
Ocean and North Sea (Malmstrom et al. 2007) or up to 25% of the total bacterial community in the Southern Ocean (Brinkhoff et al. 2007, Selje et al.
2004, Topping et al. 2006). Other related groups, such as the RCA (Roseobacter-clade-affiliated), are believed to be strictly heterotrophic and have
been shown to contribute up to 20% of the total bacterial community in the
Southern Ocean (Selje et al. 2004). The RCA strain LE-17 for example
seems to be strongly associated with phytoplankton blooms and to be unable
to grow in non-bloom seawater (Mayali et al. 2008).
Sphingomonas is another abundant and widespread genus within the Alphaproteobacteria. They play important ecological roles in a wide range of
marine habitats (Cavicchioli et al. 1999) and are especially significant in
polar environments where they often appear as dominant members of the
bacterial community and hence are suggested to be important contributors to
the total biomass and nutrient recycling (Eguchi et al. 2001, Cavicchioli et
al. 1999).
However, beyond a doubt, the vast majority of Alphaproteobacteria in the
global ocean are affiliated with the SAR11 lineage. SAR11 is probably the
17
most abundant marine bacterial lineage and up to 50% of the prokaryotic
abundance in the marine surface waters are estimated to belong to this group
(Morris et al. 2002, Malmström et al. 2007, Schattenhofer et al. 2009, Lefort
and Gasol 2013). Since the SAR11 lineage was used as a model in this thesis, they are discussed in depth below.
1.4.3 Freshwater Alphaproteobacteria
In freshwater lakes, the Alphaproteobacteria are ubiquitous although less
numerous than in marine environments. Compared to their marine counterparts, the freshwater Alphaproteobacteria are poorly studied, but the available data suggest that the dominant taxa in freshwater lakes are both resistant
to grazing (Salcher et al. 2005) and abundant under oligotrophic conditions
(Eiler et al. 2003). The most widely distributed freshwater lake lineage within the Alphaproteobacteria is LD12 (alfV lineage; Newton et al. 2011), the
freshwater sister group to marine SAR11. Other abundant lineages are the
alfIII overlapping with the genus Sphingomonas and the alfIV lineage which
features the genera Novosphingobium, and tribe Pyxis and Sphingopyxis. The
alfI (related to the Rhizobiales) and alfII (related to Caulobacter and Brevundimonas) lineages are also fairly common in lake ecosysems (Newton et
al. 2011).
1.4.4 SAR11 as models in aquatic bacteriology
The SAR11 lineage within the Alphaproteobacteria appears to be the dominant bacterioplankton in the surface of the oceans and freshwaters, where
they contribute up to 50% of the total microbial community (Morris et al.
2002, Newton et al. 2011, Heinrich et al. 2013, Salcher et al. 2011, Eiler et
al. 2009). With an estimated global population size of 2.4 x 1028 cells, the
SAR11 group is among the most successful lineages on the planet, but in
spite of this, many questions remain unanswered concerning its ecology and
physiology.
The difficulties to cultivate SAR11 strains have been one of the main obstacles for understanding their ecological roles. A little more than a decade
ago, the first cultured SAR11 strain (Candidatus Pelagibacter ubique) was
isolated from marine waters outside the coast of Oregon (Rappé et al. 2002).
Since that time, intense studies of this and other more recent isolates, and
single amplified genomes have generated a large amount of genomic information. In combination with shotgun metagenomic analysis, the diversity
and population structure of the lineage has been revealed and the many and
variable functional traits have been described.
Even if there is considerable genomic variation in the SAR11 lineage,
some shared features emerge, including the ability to compete successfully
under oligotrophic and nutrient-poor conditions, and the ability to scavenge a
18
wide range of substrates using high-affinity and broad-specificity transporters (Giovannoni et al. 2005, Lauro et al. 2009, Sowell et al. 2009, Grote et
al. 2012). SAR11 cells appear to be specialized in utilization of low molecular organic compounds and are less competitive under high productivity
conditions such as during phytoplankton blooms (Malmström et al. 2005,
Alonso et al. 2006, Tripp et al. 2008).
Members of the SAR11 clade have also been found in brackish (Kan et
al. 2008) and freshwater ecosystems (LD12; Zwart et al. 2002, Newton et al.
2011), but their ecological and biogeochemical roles in these biomes are still
uncertain. Although we know that SAR11 is widely distributed in aquatic
systems ranging from oceans to freshwaters, the biogeographic patterns and
ecology within the lineage is only beginning to be revealed (Carlson et al.
2008, Vergin et al. 2013).
Several phylogenetic subclades have been identified within the SAR11. In
some cases, these seem to be linked with specific environmental preferences,
suggesting that they may represent ecologically coherent populations or
"ecotypes" (Field et al. 1997, Brown and Fuhrman 2005, Kan et al. 2008,
Carlson et al. 2008). In freshwaters, the freshwater lineage LD12 has been
widely detected in clone libraries (Zwart et al. 2002, Newton et al. 2011),
but not until recently, when Salcher et al. (2011) published a first detailed
mapping of its distribution in some south-European lakes, was there any
quantitative information about their distribution patterns in lakes. From their
seminal work, it was clear that SAR11 were abundant also in lakes and particularly the upper solar-irradiated portion of the water column. Furthermore
SAR11 featured pronounced seasonal dynamics and were effective in using
small organic compounds (glucose, amino acids, acetate) at low concentrations, pointing to several shared ecological features with their marine sister
group.
19
2 The Present Thesis
2.1 Aims
The overall aim of this thesis is to contribute to a better understanding of
mechanisms underpinning bacterial community dynamics in aquatic systems
over spatial and temporal scales. A great deal can be learned from evaluating
the dynamics of community composition, population dynamics and the corresponding environmental parameters with regards to whether or not such
dynamics follow predictable patterns, which organisms interact and the nature of the interactions. To do this, I have decided to focus on class Alphaproteobacteria and particularly the abundant SAR11 lineage as a model group
as they are ubiquitous, abundant and successful in both marine and freshwater ecosystems. The apparent oligotrophic features and genome streamlining
within this lineage (Giovannoni et al. 2005) makes it an ideal model for the
vast majority of bacteria seen in lakes and oceans (Swan et al. 2013, Eiler et
al. 2014) and clearly separates it from studies focusing on other models.
The five papers included in the thesis contribute to the overall aim in the
following ways:
Paper I. Reconstructing the evolutionary history of SAR11 and in particular
the emergence of the freshwater subgroup LD12.
Paper II. Exploring the responses of common marine alphaproteobacterial
lineages and more highly resolved SAR11 populations to water mass regime,
solar exposure and other environmental constraints in the Southern Ocean.
Paper III. Assessing the abundance and ecological drivers controlling
freshwater SAR11: LD12
Paper IV. Understanding bacterial community shifts during gradual oxygen
depletion and niche partitioning of closely related genotypes in Lake Erken.
Paper V. Revealing population-niches in a complex interconnected web of
bacterial populations within a lake bacterioplankton community and assess
their environmental interactions
20
2.2 Methods
2.2.1 Study sites and experiments
The present thesis sets out to study aquatic systems that are of importance in
the global biosphere. The two systems selected were an intensively studied
freshwater lake and the inaccessible but globally significant western Southern Ocean. Using the analogy of water being the "blood of the biosphere"
with lakes and streams being the arteries and veins of the surrounding landscape (Williamson et al 2008), I imagine the Southern Ocean as the heart
pumping the global ocean currents across our planet.
Lakes play a central role in the global carbon cycle (Tranvik et al. 2009).
As most lakes on Earth are rather shallow, solar radiation reaches into a
large portion of the freshwater lake biome and accordingly freshwater systems rich in nutrients are among the most productive systems on Earth (Wetzel 2001). Because of a uniquely long history of limnological monitoring
and research as well as an established infrastructure for seasonal lake monitoring, lake Erken was surveyed for microbial community dynamics. Erken
is a medium-sized (23.7 km2 surface area), mesotrophic and dimictic lake in
central Sweden.
Compared to freshwater lakes, it is perhaps more evident that the Southern Ocean plays a significant role in global biogeochemical cycles.
This polar ocean features constantly low temperatures and considerable
patchiness in nutrient availability and trace elements, which in combination
with strong seasonality in solar irradiance shape dynamic temporal and spatial patters in productivity that account for 5-10% of the global primary
production. This sea is connected to the surrounding oceans by major oceanic currents that also contribute to the local partitioning of the water column
into water masses with limited connectivity. This massive transport of water,
energy, matter and organisms is the reason for the analogy to the pumping
heart.
The three freshwater-centered manuscripts build on a long-term microbial
sampling program linked to routine water quality monitoring. While Papers
II and V consider community dynamics taking place over a full year,
including the ice-covered winter period, Paper IV is focused exclusively on
the annual event of summer stratification with regards to the separate community trajectories in the two distinct water masses forming because of
thermal summer stratification. Paper I takes a global approach and relies on
archived bacterial community data from a wide range of marine and freshwater samples, whereas Paper II is based on samples and data collected
during an expedition to the Southern Ocean during Austral summer where
polynyas form along the Antarctic continent (Figure 2). The Southern Ocean
provinces sampled were the well-studied Ross Sea and the far less studied
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Amundsen Sea, where horizontal and vertical scales as well as different water masses are explored with regards to bacterial community composition.
Figure 2. Map demonstrating the sampling program in the Amundsen and Ross seas
in the Southern Ocean. Sampling depths is illustrated with boxes where the color
indicate the water mass with red being circumpolar deep water, blue being Antarctic
surface water, yellow being shelf water, light grey being the pycnocline and dark
grey being the thermocline. The size of the green circles marking the location of the
sampling stations marks the productivity at the station with surface water chlorophyll as the proxy.
In addition to the environmental surveys, I performed an experiment to test
the effect of naturally occurring light regimes on the bacterial community
composition in the Southern Ocean. Samples for the experiment were collected from surface water (5m depth) from a low-productive area in the
Amundsen Sea. One-liter polypropylene incubation bottles were filled with
700 ml surface seawater and subsequently exposed to natural solar radiation
and complete darkness. All incubations were carried out at near in situ temperature.
2.2.2 Analytical methods
I have mainly used three methods for assessing the composition of bacterial
communities and dynamics of individual populations (Figure 3). To provide
an overview of the combined communities I have relied on community-level
PCR assays targeting the entire bacterial domain with next generation sequencing methods (454 pyrosequencing). To specifically target individual
populations and single cells and to quantify the contribution of different
bacterial groups to the community, I have used both quantitative real time
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PCR and taxonomically directed fluorescence in-situ hybridization at the
single cell level. For all studies, and especially for Paper I, environmental
DNA sequences generated from earlier studies and field campaigns have
been retrieved from public databases such as Genbank, in order to provide
context to the data I have generated and reanalyze legacy data with regards
to my target organisms.
Figure 3. Methodological strategies for bacterial community or population analysis
used in this thesis
Molecular methods
Quantitative polymerase chain reaction (PCR):
The quantitative PCR technology combines gene amplification by the polymerase chain reaction with real-time fluorescence detection in one single
procedure. There are many strategies to achieve the detection, and the methods used in Paper III rely on amplicon quantification with a dye that becomes more intensively fluorescent upon binding to double stranded DNA
(SYBR Green). The progress of the amplification is thus monitored for every amplification cycle and compared to standards and titration curves for
absolute quantification. I also used this method in a biogeography study,
which is not included among the thesis papers, but briefly reported and
discussed in the thesis summary.
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Catalyzed Reporter Deposition Fluorescent Hybridization (CARD-FISH):
Direct single cell detection with oligonucleotide probes was used in Papers
II and III. The fluorescence in-situ hybridization (FISH) technique targets
individual cells from defined phylogenetic groups. FISH is a cytogenetic
technique, which is used to detect and localize the presence of specific sequence motifs in abundantly present ribosomal RNA. A fluorescence-labeled
oligonucleotide (probe) binds (hybridizes) specifically to a perfectly matching target sequence (rRNA) and unspecifically bound probe is then washed
away to eliminate false positives. Cells featuring the target sequence, typically chosen to be taxon- or group-specific, can then be directly observed in
a fluorescence microscope. However, cells in the environment and especially
in low-productive systems, are often very small and may contain only a few
rRNA molecules. This is often coupled to slow growth or starvation, but
may result in such cells escaping detection. A way to address this is to use a
signal enhancement by using, for example horseradish peroxidase (HRP)labeled oligonucleotide probes and a localized tyramide signal amplification
(Catalyzed Activity Reporter Deposition), which improves the detection
efficiency.
DNA sequencing of PCR amplicons:
The traditional way to obtain information about the taxonomic affiliation and
identity of PCR amplified genes is to use Sanger sequencing, either directly
or on cloned PCR products. Sanger sequencing is based on in vitro DNA
replication where chemically altered nucleotides (dideoxynucleotides) are
incorporated in newly synthesized DNA strands causing a termination
of the DNA elongation. Using radiolabels or more commonly, different
fluorophores, and either slab gels or capillary electrophoresis, the resulting
fragment mix can be resolved by length and the terminal base identified.
This sequencing method was used in Papers II and III.
Pyrosequencing is a more recent high-throughput sequencing
technology that generates a large number of DNA reads up to 450 bp length
through massively parallelized pyrosequencing (sequence by synthesis)
reactions. In Papers II-V, the 454 GS-FLX system (454 Life Sciences,
Brandford, CT, USA) was used and the resulting reads carried a samplespecific molecular barcode and covered the V4 region of the 16S rRNA gene
as well as more conserved flanking regions. Sequencing was performed
at the Center for Metagenomic Sequence Analysis hosted by the Royal Institute of Technology, Stockholm, Sweden. Downstream analysis of the amplicon sequences was mainly performed using the mother platform
(Schloss et al. 2009). Amplicon sequencing and subsequent analysis was
performed in Papers II-V.
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Methods for the analysis of community and population dynamics
Ordinations for beta diversity analysis:
Whole-community ordination approaches summarize taxon abundance tables
by depiction in one and more dimensions. In non-metric multidimensional
scaling, similar samples are plotted near each other; such analysis reveals
dynamics in community composition (beta diversity) across environmental
gradients such as depths and between seasons. Other multivariate analyses,
such as canonical correspondence analysis, enable samples and species to be
examined in the context of environmental conditions, such as nutrient concentrations. These approaches are used to link environmental and biotic variability to bacterial community structure. Ordinations were performed in Papers II- V.
Association networks for population analysis:
In this thesis, association networks have been generated from pairwise statistical inferences (e.g. Spearman correlations) using taxon abundance tables.
In addition to connections between individual microbial groups, which can
provide insights into the interactions among them, the networks can be explored for emergent overall properties, such as the degree of interconnectedness, which can be related to community behavior. Association networks
were constructed in Paper III and V.
Identification of populations contributing to community differences used in
Papers II and IV
SIMPER analysis.
Similarity Percentage analysis calculates the average Bray-Curtis dissimilarity between all pairs of inter-group samples (all samples from environment A
against all samples from environment B). This way, the contribution of each
population to the observed dissimilarity is assessed and allows the identification of populations that are most influential in the community differentiation
(Clark 1993).
Indicator-species analysis.
Species characteristic for a specific environment are often described as "indicator species". These are mostly found in a single type of environment and
are present in most sites from that specific environment. This method is
based on species specificity (relative abundance) and fidelity (presence and
absence) that together build the INDVAL value (Dufrene and Legendre
1997).
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Phylogenetic analysis
A central question in community ecology is what processes are responsible
for the identity and relative abundance of co-occurring populations in a local
community. The phylogenetic structure of a community reflects the pattern
of phylogenetic relatedness. Thus, observations of how related co-occurring
populations are, if they are more closely related or more distantly related as
expected for a randomly assembled community can identify the underlying
community assembly process. Phylogenetic analysis was performed in Paper I, II and IV. The basis for phylogenetic analysis is the construction of
robust phylogenies. Those can use functional genes or the 16S rRNA gene as
measure of relatedness and can show different evolutionary relations for the
same community. In the present thesis 16Sr RNA based phylogenies are
build by using RAXML (Stamatakis 2006), which is based on maximum
likelihood.
Phylogenetic Beta-Diversity:
UniFrac is a method that calculates the phylogenetic distance between populations and can determine if defined environments harbor significantly different microbial communities (Lozupone et al. 2010). Further, Unifrac can
determine if community differences are concentrated within particular lineages of the phylogenetic tree an can cluster environments to determine
whether there are environmental (such as salinity, temperature or solar radiation) and geographical parameters (such as altitude, distance to sea-level or
distribution over the continents) that cause communities to cluster.
Phylogenetic Alpha-Diversity: Faith`s PD and Mean Nearest Neighbor Distance
The Picante package (Kembel et al. 2010) implemented in the Renvironment, contains functions for calculating the most commonly used
measures of phylogenetic α-diversity (evolutionary relatedness within ecological communities) including Faith’s phylogenetic distance (PD, the sum
of all branch lengths separating taxa in a community; Faith 1992), the taxonomic distinctness index (Vane-Wright et al. 1991), the mean pairwise phylogenetic distance (MPD) and mean nearest taxon distance (MNTD) within a
community (Webb et al. 2008).
Statistics and Data visualization:
Statistical analysis have been performed with in the R–Environment mainly
using the packages vegan and picante. For visualization of the phylogenies
the interactive online tool ITOL was used (Letunic and Bork 2006). Result
and their statistics, were visualized using the R-environment (R Development Core Team (2010) and the vector based graphics software Inkscape
(www.inkscape.org).
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2.3 Results
Paper I. Infrequent Transitions between Saline and Fresh Waters in
One of the Most Abundant Microbial Lineages (SAR11)
Aim: To investigate the evolutionary history of SAR11, and in particular the
emergence of the freshwater subgroup LD12
Study: The aquatic bacterial lineage of SAR11 is one of the most successful
and abundant organisms on Earth and has an estimated global population
size of 2.4 x 10 28cells in the oceans. Subclades of SAR11 have also been
detected in brackish and fresh waters, but the evolutionary relationships between the species present in the different environments have been ambiguous. Both the marine and the freshwater SAR11 are exclusive to their respective biome and essentially never overlap in occurrence, except occasionally
in estuaries or other freshwater-saltwater mixing zones. This points to a strict
partitioning of genotypes between systems of low and high salinity.
Figure 4. Distinct saline and freshwater lineages in SAR11. Radial phylogram illustrating the amount of genetic divergence within the marine-brackish and freshwater
clusters.
Genome changes in the SAR11 lineage are now known to have occurred
gradually over ~800 million years (Luo et al. 2013). One of the major questions addressed in the present study was how frequently this lineage crossed
the saline–freshwater boundary during its evolutionary diversification. Since
aquatic bacteria are frequently dispersed between marine and freshwater
biomes, such transitions could, at least in theory have occurred repeatedly
over evolutionary timescales. In this paper, extensive 16S rDNA–based molecular phylogenies and metagenomic analysis from data-mined data were
conducted to assess this transition frequency and the evolutionary implications. The main result was that it is likely that only very few transitions oc27
curred, having resulted in distinct genetic linages that show no or very little
genetic linkage. Despite the global distribution, the freshwater lineage was
found to be far less diverse compared to the marine SAR11 clade.
The existence of only few ribotypes of LD12 points to a rapid diversification
and dispersal in freshwaters or the possession of slower evolutionary rates
compared to the marine lineage. Furthermore the partitioning into a freshwater and a marine lineage likely occurred early in the evolution of SAR11.
To conclude, the saline-freshwater boundary is likely a rather strong evolutionary barrier that is hard to cross and this promotes the evolution of clearly
distinct lineages in each of these two biomes.
Conclusion: The transition between oceans and lakes occurred early in the
history of SAR11 evolution and only at a few occasions. The freshwater
lineage exhibits a much lower diversity compared to the marine SAR11
Paper II: Abundance and diversity of Alphaproteobacteria in the
Southern Ocean: the dark side of SAR11
Aim: Study the response of common marine alphaproteobacterial lineages
and more highly resolved SAR11 populations to water mass regime, solar
exposure and other environmental constraints
Study: The alphaproteobacterial lineages SAR11 and Roseobacter represented major components of marine bacterial communities. Our study confirms this also for the Amundsen and Ross Seas within the Southern Ocean
despite the continuously low temperatures, annual extremes in solar irradiation and patchy inputs of autochthonous organic substrates; an environment
that is in many ways very different from other oceanic regions.
Population mapping and community analysis of bacterioplankton during
the highly dynamic summer season within the Ross and Amundsen Seas was
performed. In addition, experimental incubations in light and darkness were
studied and the impact of solar radiation and other environmental factors on
individual lineages within the class Alphaproteobacteria and subclades as
well as closely related populations (OTUs) within the SAR11 lineage were
assessed. Quantitative population tracking by fluorescence in-situ hybridization was combined with pyrosequencing-derived 16S rRNA inventories to
resolve the community beyond class and abundant lineages.
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Figure 5. SAR11 fluorescence microscopy images of identical fields from naturallight -cycle (a+b) and dark treatments (c+d). Images b+d are for DAPI-stained cells
detecting all DNA containing bacteria and a+c are CARD-FISH images with probes
specifically detecting SAR11. Note the auto-fluorescence of phytoplankton cells.
Both the experiments and the depth-resolved transect samples from the
Amundsen and Ross Seas confirmed SAR11 as a major component of the
bacterial community regardless of water mass and depth. However, the
experiments revealed that SAR11 as a lineage was less competitive under
solar-exposed conditions whereas the opposite response was observed for
Roseobacter. Resolving the SAR11 linage into subclades revealed clear
partitioning of these more highly resolved phylogenetic groups between the
different water masses and light regimes. Subclade Ic for example seemed to
be confined primarily to the CDW whereas it was rare in other deep waters
and closer to the surface. Such partitioning was also observed for more highly resolved and closely related OTUs at the 99% identity level.
Moreover, the diversity (richness) within the SAR11 lineage was significantly higher in the deep permanently dark water masses of the CDW.
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Figure 6. Distribution of SAR11 populations (OTUs) in the surface water (AASW)
and deep waters (CDW and SW). The subclade affiliation and average relative
abundance within the SAR11 community is given in the right upper corner of each
plot. The upper left panel (a) is an NMDS ordination illustrating the similarity of
SAR11-OTU composition between all collected samples. Environmental parameters
are fit onto the ordination. Panel b-d illustrates the distribution of single SAR11
OTUs onto the ordination plot. The bubble size denotes the relative abundance of
the OTU and contours is the predicted abundance as fitted onto the ordination.
Using this abundant marine bacterial lineage as a model, we could demonstrate clear separation of closely related bacterial populations between water
masses and along environmental gradients of light exposure, oxygen availability and phytoplankton and nutrients. It is evident that such ecologically
coherent populations can only be tracked at high phylogenetic resolution and
that ecological and evolutionary mechanisms underpinning the observed
phylogeographic patterns differ between water masses in the Southern
Ocean.
Conclusion: SAR11 was found to be less competitive under solar-exposed
conditions and instead seem to do well in permanently dark water masses.
Clear intra-lineage partitioning along environmental gradients was revealed
in agreement with recent reports from other marine systems.
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Paper III: Seasonality and environmental control of freshwater SAR11
(LD12) in a temperate lake (Lake Erken, Sweden)
Aim: To assess the abundance and ecological drivers controlling
freshwater SAR11, LD12
Study: At the time when this study was conducted, the abundance and ecological role of the freshwater sister group of SAR11 was more or less completely unknown and based mainly on anecdotal detection of 16S rRNA
genes in clone libraries from various lakes. The major aim of the study was
therefore to assess the abundance of LD12 in order to determine if it could at
least occasionally be as abundant as the marine sister group. A second objective was to take a correlative approach to investigate the ecology of the
group and the seasonal dynamics. The extensively monitored and studied
lake Erken was used as a model system for a temperate dimictic lake. The
seasonal dynamics of LD12 and other Alphaproteobacteria was analyzed by
the use of group-specific quantitative PCR, catalyzed reporter deposition
fluorescence in-situ hybridization (CARD-FISH) and 454 pyrosequencing of
the 16S rRNA gene.
Figure 7. Seasonal dynamics of LD12 relative abundance and Chl-a in the integrated
epilimnic and hypolimnic (bars) water masses. The relative abundance was estimated by qPCR. The period of maximum zooplankton density is indicated by the Daphnia insert.
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The results show, that LD12 can be as numerous in freshwater bacterioplankton as their more widely known SAR11 siblings in the ocean. Their
contribution to the total bacterioplankton community is strongly seasonal.
Over the course of one year, LD12 made up 1.8 - 40% of the total bacterial
16S rRNA pool (mean 14%) with pronounced peaks in both summer and late
fall (Figure 7). Except in spring, LD12 was by far the dominant clade of the
Alphaproteobacteria, contributing on average 72% to the total pool of 16S
rRNA amplicons within this class. We also found a single dominant LD12
ribotype persisted not only over time but also across different water masses
(epilimnion and hypolimnion) during summer stratification. Hence, the data
suggest low local divergence, but such inferences should be made with caution, as phylogenetic resolution that can be accessed with rRNA genes is
limited. LD12 abundance was positively coupled to nutrient concentrations
(phosphate, ammonia, nitrate, and silica), and water transparency. During
periods of high phytoplankton biomass and low concentrations of free inorganic nutrients LD12 decreased in abundance, a finding that is in agreement
with observations on SAR11 abundances in the marine environment. Hence
LD12 represents a major component of the freshwater bacterial community
and members of that clade are poor competitors during periods of high phytoplankton productivity, which likely is coupled to enhanced release of labile
organic compounds promoting copiotroph substrate acquisition strategies.
LD12 seem to thrive rather under conditions of high availability of inorganic
nutrients when phytoplankton is scarce.
Conclusions: LD12 is a major component of the lake microbiome and undergo pronounced seasonal dynamics coupled to nutrient availability and
water transparency. LD12 is also present and abundant in the hypolimnetic
water mass during summer stratification and seems to be locally dominated
by a single ribotype.
Paper IV: Alteration of lake bacterioplankton diversity and community
composition during lake stratification and gradual oxygen depletion
Aim: To assess bacterial community shifts during gradual oxygen depletion
and niche partitioning of closely related genotypes in Lake Erken
Study: Stratifying lakes, such as Lake Erken undergo gradual oxygen depletion and seasonal hypoxia in the hypolimnetic water masses. This is caused
by organic matter degradation with oxygen as terminal electron acceptor and
can has dramatic effects on larger organisms. However, also the microbiota
may respond to altered availability of oxygen and coupled changes, in for
example, nutrient levels during extended summer stratification. The main
objective was to explore how stratification and seasonal variations in different environmental factors influenced the resident bacterioplankton. We
32
therefore followed the temporal dynamics in epilimnetic and hypolimnetic
bacterial communities and populations across the entire period of summer
stratification (Figure 8). We found that bacterial diversity was significantly
higher in the hypoxic hypolimnion and this water mass also featured higher
beta diversity over time.
Figure 8. Non-metric multi-dimensional scaling ordination (NMDS) of a BrayCurtis similarity matrix among 20 pelagic samples obtained from Lake Erken from
the onset to the end of stratification (June through August). Red symbols indicate
samples from the hypolimnion whereas epilimnetic samples are indicated in blue.
Underlying colors mark the samples clustering in three periods of the stratification
process. a) Environmental variables fitted to the ordination are shown as black arrows. Samples are connected according to timeline. b) UPGMA dendrogram based
on Bray-Curtis distance. The water layer classification is shown in colors. The size
of the circles reflects the Shannon index.
Many abundant groups of freshwater bacteria, such as Actinobacteria acI,
Polynucleobacter and freshwater SAR11 (LD12), were abundant in both
water layers but distinct temporal and vertical population shifts were observed at higher phylogenetic resolution. Truly hypoxic populations were
identified but never made up a large proportion of the community.
Within the abundant Actinobacteria (43% of community) and the less abun33
dant Verrucomicrobia (4% of community), clades and OTUs responding in
contrasting ways to oxygen were identified, likely reflecting different ecologically coherent populations (Figure 9).
Our findings highlight the importance of considering the used phylogenetic
resolution in identifying coherent ecological units and that the seasonal succession in hypolimnetic bacteria is related to gradual oxygen depletion and
associated changes in water chemistry.
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Figure 9. From phyla to OTU – time course of relative abundance in epilimnion and
hypolimnion for the bacterial phylum Actinobacteria and the lineage acI resolved at
different phylogenetic resolution. The polarograms present the time course, with
each segment representing one sampling date, each circle (or number) represents the
relative abundance, blue lines mark the epilimnetic relative abundance and red lines
the hypolimnetic relative abundance.
Conclusion: Despite pronounced environmental changes, a few abundant
groups of freshwater bacteria consistently dominate the within-lake community regardless of the time and space. These groups are dominant under hypoxic hypolimnetic conditions as well as in solar exposed and highly oxygenated surface waters. However, at a finer level of phylogenetic resolution,
distinct populations are revealed that respond in contrasting ways to oxygen
and partition into either hypolimnion or epilimnion.
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Paper V: Coherent dynamics and association networks among lake bacterioplankton taxa
Aim: Reveal population-niches in a complex interconnected web of bacterial
populations and assess the interactions between populations and environment within a lake bacterioplankton community
Study: Bacterial communities undergo constant shifts in assembly and composition due to interactions between biotic and abiotic factors. Inter- and
Intrapopulation interactions are important in shaping the bacterial community and are at least partly responsible for the complex dynamics causing
community shifts. This study uses 454 pyrosequencing of 16S rRNA genes
to investigate associations of different bacterioplankton populations to environmental features and their co-occurrence patterns over an annual cycle in
the dimictic lake Erken. The bacterial community underwent a seasonal succession and individual populations were extensively synchronized and associated with seasonal events such as ice coverage, ice-off, mixing and phytoplankton blooms (Figure 10).
Figure 10: Standardized abundance profiles (z-scores) for identified tribes. The
upper (stack-plot) represents the average standardized abundance of the tribes with a
coherent cluster. The lower plot shows the individual abundance profiles for each
tribe with the coherent cluster. The number in parenthesis following the tribe names
correspond to the phylum or sub-phylum name respectively (1)
Actinobacteria. (2) Alphaproteobacteria (4) Gammaproteobacteria. The seasonal
events are indicated as (SPD) spring diatom bloom, (ZOO) zooplankton bloom,
(CYA) cyanobacterial bloom, (SUD) summer diatom bloom and (NIT) nitrification.
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Time-dependent rank correlations revealed strong ecological coherence for
taxonomically closely related populations. Synchronous dynamics were
however not always associated with phylogenetic relatedness. For example,
whereas several tribes within the freshwater Actinobacteria ac1-A clade
changed synchronously over time, the freshwater SAR11 (LD12) changed in
synchrony with tribes within Actinobacteria acI-C, acIV and a Gammaproteobacterium (Figure 10 and Figure 11).
#
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Figure 11. Example of a sub-network centered on the abundant freshwater SAR11
tribe LD12, which illustrates how this tribe is wired in its niche space. The blue
hexagons represent environmental factors and the red squares the tribes. Interactions
include positive (black lines) and negative correlations (red lines), dashed lines indicate time-lagged responses and the arrow indicates the direction of the time shift.
Conclusion: Association networks provide a highly compressed and simplified illustration of the typically complex ecological interactions that shape
bacterial communities. We argue that positive co-occurrences may represent
functional guilds of organisms performing similar or complementary functions, whereas negative correlations may reflect direct interactions such as
competition or may be the result of differences in resistance to losses by
grazing or viral lysis.
2.4 Conclusions and Outlook
This thesis presents further insights about the hidden world of bacterial
communities. The systems studied in this thesis, lakes and Southern Ocean,
undergo a constant change in properties due to for example seasonal changes
or episodic disturbances and the bacterial communities are forced to realign
in their composition in order to remain a functional unit of the ecosystem.
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I found that the tight connection of the community with its surrounding
environment implies a complex interplay between the organisms and the
environmental properties. These properties vary over space and in time and
in order to fully understand the dynamics of natural communities and populations, it is of critical importance to consider this when designing studies
and interpreting data. Looking at microbial community changes, I found the
phylogenetic resolution to be of pivotal importance. A starting point is often
the level of phyla or class, but as shown in several studies in this thesis, the
reality is that this coarse phylogenetic scale will overlook a lot of the dynamics that take place in lakes and oceans. In addition to the difficulty of defining and studying meaningful biological scales in aquatic microbiota, it is
also not always straightforward to disentangle spatial and temporal effects
and variable community interaction can also obscure the interpretation.
Microbial ecologists are certainly in for a challenge since a complex web of
interdependencies and competition between populations will set the stage for
a community to match the environment.
Putting knowledge gained in the present thesis into perspective:
Dispersal of bacteria could be imagined as rather boundless because of large
population sizes, the potential for long-distance passive dispersal as well as
high reproductive rates and huge genetic diversity (Logares et al. 2009,
Fenchel and Finlay 2004). Especially considering the "geographical boundlessness” and connectivity in aquatic systems, one may intuitively expect a
high degree of homogeneity in spatially separated bacterial communities.
However, the marine-freshwater boundary, characterized by a dramatic shift
in salinity, seems to be equally hard to overcome for bacteria as for macroorganisms (Logares et al. 2009).
Freshwater systems, e.g. lakes, are however much younger than oceans
and only during the co-existence of both systems could transitions have occurred. Surprisingly, these transitions have appeared rarely and this contributed to the emergence of genetically distinct SAR11 lineages. The reason for
the low frequency of such transitions is currently not known, but it is close at
hand to suggest that the expansion from one biome to the other likely involved several adaptive changes. Further investigation of the genetic differentiation between both sister-groups might reveal the full extent of what
makes a bacterium fresh.
Compared to the genetically diverse marine SAR11, freshwater SAR11
from diverse, and sometimes very distant, geographic locations are still very
closely related. The global distribution of LD12 was revealed by an extensive data mining and metadata collection and showed only little genetic variation within the LD12 on the 16S rRNA level. However, we did find support
for distinct ecotypes that partition according to continent, season, altitude,
pH and trophic status of the lakes (data not included in thesis).
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Thus, I argue for the need to carry out extended and spatially fine-scaled
research on the biogeography of LD12, since this will result in valuable
information on mechanisms behind the habitat differentiation of both groups.
Studying the SAR11 community in the Southern Ocean confirmed the
high genetic diversity within this group and revealed distinct patterns of
SAR11 subclade distribution patterns between water masses, characterized
by variable influences from solar-radiation and contrasting environmental
history. The existence of ecologically partitioned subclusters is corroborated
by the observed underdispersion (phylogenetic clustering) in the phylogenetic structure of the resident SAR11 populations. Still, the degree of phylogenetic clustering varies depending on the water masses and light regime. For
example, the strength of clustering decreased in the presence of light and at
the surface. Such variations point towards general differences in the ecological and evolutionary mechanism shaping the phylogenetic structure.
Recent studies revealed that the freshwater and the marine SAR11 have
opposite extreme ratios of mutation to recombination rates (Vos and Didelot
2009). The high recombination rates proposed within the SAR11 lineage
(Vergin et al. 2007, Zaremba et al. 2013), are thought to result in high genetic linkage between distantly related SAR11 facilitate the creation of novel
metabolic varieties and thus enable the conquest of new niches.
I found, that the SAR11 community not only consists of subclades that
exhibit clear niche partitioning but also form within the subclades distinct
distribution pattern. For example, populations of the most abundant SAR11
subclades find their niche space by partitioning by water depth. This implies
that these populations might exhibit plasticity with regards to the use of solar-radiation. As the SAR11 lineage is known to express proteorhodopsins
genes that might boost the energy supply via light driven proton pumping, it
would be of great interest to now study to which degree the different
SAR11-subclades and specific populations, make use of this feature. Is the
niche partitioning populations within the SAR11 subclade Iab driven by
plasticity with regards to the expression of proteorhodopsins? Future studies
could for example use transcriptomic and proteomic based approaches to
answer this question.
In this work, I found that, similar to the marine SAR11, the freshwater
SAR11, i.e. LD12, appears also to be a major component of the bacterial
community with temporally comparable abundance, pronounced seasonality,
an oligotrophic life style and a broad distribution within the freshwater biome.
The close examination of the LD12 community in the well-monitored
lake Erken revealed the existence of only one ribotype over season and
depth. Even during the massive change in the environment that take place
during stratification and oxygen depletion, this single ribotype was equally
distributed between the two water masses. Similar to the finding that phylo-
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genetically close related SAR11 populations live in habitats of very different
light condition, LD12 seems to also exhibit a broad phenotypic plasticity.
Future research on the ecology of LD12 should in my opinion focus on
two aspects of their biology First to understand what enables very similar
populations to be widely distributed without extended evolutionary divergence as observed in SAR11? For this purpose, focus on other phylogenetic
signals than the slowly evolving 16S rRNA gene as marker and genomic
information from single cell genomes will be of great value. Second, successful isolation of LD12 would enable us to perform experimental studies to
test their strategies to cope with changes in the environment.
In the study of the community distinction during lake stratification,
I found that the most abundant bacterial lineage showed similar distribution
patterns in the epilimnion and hypolimnion or exhibited only a slight preference for one or the other habitat. This finding implies that the ability to cope
with environmental shifts like oxygen depletion is a trait shared by many of
the successful freshwater bacterial lineages. Only a quarter of all
populations were differentially distributed between the epilimnion and hypolimnion, and those were preferentially associated with the hypolimnetic
zone. The differentiation between the communities in both water masses thus
appears to be caused by initially rare bacterial populations emerging under
oxygen-limited conditions. Thus I argue for careful interpretation of community structure surveys that do not consider rare organisms.
In order to evaluate the importance of rare community members, further
improvement of sequencing techniques is needed to exclude the risk of ambivalent data.
The study using association networks provided insights about
co-occurrence patterns of bacterial tribes that may represent functional
guilds performing similar or complementary functions in the lake. Both
positive and negative interactions were identified that may relate to
competition or interdependencies within the bacterial community. However,
co-occurrence patterns and observed correlations need to be interpreted with
caution since they rely exclusively on abundance-shifts whereas changes in
functionality should certainly also be taken into account. In addition, the
extreme versatility of the metabolic properties in bacterial communities will
likely influence the mechanisms of community shifts. Even if the use of the
16S rRNA gene is of great use for a mapping of the complex natural microflora, it is a rather blunt tool for resolving ecologically relevant populations
and processes. Observations based on changes in protein-coding marker
genes or even complete or partial genomes, are likely needed to fully assess
and interpreted changes and linkages within a community.
Combined, the gained knowledge from this thesis clearly shows that future research in microbial ecology needs to go deeper in several different
ways. High-resolution sampling, spatial as well as temporal, is essential to
understand the biology behind the observed patterns. The identification of
39
“hotspots” in space and time is also crucial for avoiding overlooking important biological events and phenomena.
Due to the lack of a proper expression for the science of investigating a
temporal hotspot in biological processes, I would like to suggest the term
“biokairography”, “the biological study of the right moment”, as a parallel
concept to “biogeography” (the study of the distribution of species in
geographic space and through geological time). The need to apply sufficiently high phylogenetic resolution to target and delimit ecologically coherent
bacterial populations is clearly demonstrated and highlighted in this thesis.
Concepts and hypotheses based on studies with limited consideration
for one or more of these three criteria can still be valuable in providing a first
overview of an ecological system or process, but can most certainly also
be misleading. Research already changed from approaches that only provide
“snapshots” of nature to now increasingly present comprehensive approaches. The awareness of the enormous gain of knowledge using long-term
studies and spatially fine-scaled surveys is constantly increasing.
Not least the rapid development of new molecular technologies and developments in bioinformatics allow for massive sampling and data analysis.
The value of studying controlled environments and experimental work to test
the concepts and hypotheses gained from environmental surveys are also
indispensable, since hypotheses formulated based on correlative environmental approaches, need to be validated.
To conclude with a citation of Tom Fenchel: “real progress in ecology
first of all depends on an increase of qualitative in-sight, and computers cannot compensate for this” (Fenchel 1987). In my eyes, this appeal is today
more valid than ever.
40
3 Summary in Swedish
Bakterier och andra mikroorganismer finns överallt i vår omgivning. En
droppe havsvatten kan innehålla en miljon bakterier och i en droppe sjövatten kan man sannolikt hitta tio gånger fler. Bakterier är betydelsefulla
primärproducenter och har en central roll som nedbrytare. Dessa processer
påverkar självfallet omsättningen av kol i biosfären, men även andra metabola processer som de utför har en avgörande betydelse för allt liv på jorden.
Att diskutera bakterier som ett kollektiv är dock något missvisande. De
mikrobiella samhällen som återfinns i sjöar och hav utgörs av tusentals olika
bakterier som alla har olika egenskaper och särdrag. De påverkar och påverkas av miljön på olika sätt och interagerar också med varandra i varierande
utsträckning.
Vilka bakterier hittar man då i en droppe vatten? Ja det är inte främst den
typen av snabbväxande bakterier som mikrobiologer är vana att renodla i
sina laboratorier och som har stor påverkan på oss människor genom sin
förmåga att orsaka sjukdom. Visst kan man även hitta koliforma bakterier
eller patogener i sjö- och havs-vatten, men det helt andra bakteriegrupper
som utgör den stora vattenlevande bakteriemassan. Många av dessa bakterier
kan vi inte odla i renkultur, utan en uppsjö av odlingsoberoende metoder för
att studera bakteriers artsammansättning, ekologi och funktion i ekosystemet
har utvecklats, tagits i bruk och bidragit till kunskapsutvecklingen inom det
miljömikrobiologiska forskningsfältet. Genom att studera bakteriernas
arvsmassa eller enstaka gener som kan användas för identifiering, har de
dominerande bakteriegrupperna kartlagts och deras utbredning och evolutionära släktskap har beskrivits.
En slutsats som kan dras från dessa studier är att bakterier i sjöar och hav
är besläktade men unika för respektive biom. Sötvattensbakterier återfinns i
just sötvatten och ingen annanstans och detsamma kan sägas för havsbakterier. Den övergipande fråga som mot denna bakgrund ställs i föreliggande
avhandling är vilka faktorer som styr bakteriesamhällens artsammansättning
i akvatiska ekosystem och om vilka likheter och skillnader det finns mellan
sjöar och hav i detta avseende. För att åstadkomma detta har jag valt att
fokusera mina studier på ett släkte bakterier som återfinns i både sjöar och
hav, men där individuella evolutionärt definierade undergrupper inom släktet
återfinns i ett av dessa biom, men aldrig i båda. Det släkte som huvuddelen
av arbetet i denna avhandling fokuserar på heter SAR11 och tillhör den artrika och funktionellt mångfacetterade klassen Alfaproteobakterier. Alfapro41
teobakterier är talrika i både sjöar och hav och just SAR11 är ofta, men inte
alltid, det fullständigt dominerande släktet inom denna klass. I våra
världshav kan SAR11 ibland utgöra upp till hälften av det totala antalet bakterier och har på grund av detta studerats intensivt under lång tid och då man
har lyckas odla representer från släktet har det varit möjligt att studera deras
arvsmassa och studera deras metabolism och mångfald. I sötvattenssystem
har detta släkte inte alls rönt lika stort intresse inom forskarsamhället. Sötvattensgruppen inom släktet SAR11 heter LD12 och var, tills helt nyligen,
endast känd från en gensekvens som kodar för ribosomalt RNA och som
återfanns i många olika sjöar från olika delar av världen. Kunskapen om
deras biologi var dock i det närmaste obefintlig.
I mina studier har jag byggt på de metoder som nämns ovan, men dragit
nytta av teknisk utveckling inom DNA sekvensering vilket möjliggjort mer
utförlig karakärisering av bakterier på ett större antal platser eller vid flera
tillfällen under året. Jag har dessutom kombinerat denna centrala metodik
med kompletterande metodansatser som inkluderar identifiering och visualisering av enstaka SAR11 och LD12 celler på enkelcellsnivå, kvantitativ
analys av markörgener med realtids-PCR, och nya statistiska ansatser för att
hitta robusta mönster i de komplexa data som erhålls. För att möjliggöra
jämförelsen mellan sötvatten och marina system har mina fältsystem
inkluderat såväl en välstuderad och måttligt produktiv sjö som olika vattenmassor och regioner i Södra Ishavet. Genom att leta i allmänt tillgängliga
databaser har det ochså varit möjligt att bredda dessa analyser för att belysa
globala mönster i detta släktes mångfald och evolution.
Med den sistnämnda ansatsen var det möjligt att beskriva inbördes
släktskap inom hela SAR11 släktet och det blev uppenbart att mångfalden
inom det marina SAR11 släktet var betydligt större än hos LD12 som uppvisade en förvånande liten global differentiering och variation. Släktskapen
visar också att att SAR11, under sin evolutionära historia, endast vid ett fåtal
tillfällen tagit språnget mellan söt- och saltvatten och att detta förmodligen
hände tidigt i släktskapets utveckling.
Södra ishavet känntecknas av kontinuerligt låga temperaturer och varieriande tillgång till solljus och näringsämnen vilket i kombination med
förekomst av åtskilda vattenmassor och havsströmmar skapar en heterogen
och krävande miljö för de havslevande bakterierna. Mina studier visar att
SAR11 kan hantera dessa utmaningar och utgör en stabil och hög andel av
bakteriesamhället oavsett vattendjup, näringsillgång eller förekomst av växtplankton som kan leverera substrat för deras tillväxt. I experiment kunde
man även se att SAR11 påverkas negativt av solstrålning medan solstrålningen hade motsatt effekt på andra Alfaproteobakterier inom släktet Roseobacter. Vi fann även att skilda, men närbesläktade grupper inom SAR11släktet uppvisar unika och varierande mönster i förekomst och abundans,
vilket sannolikt indikerar ekologisk differentiering inom släktskapet.
42
Tidigare studier har tydlig visat att bakteriesamhällen i sjöar ofta genomgår stora kvalitativa förändringar kopplat till olika årstider, väderdriven
ekosystem-påverkan eller andra dramatiska förändringar i sjöns karaktär.
Genom att använda kvantitativa molekylära metoder analyserades förekomsten av LD12 och deras abundans kunde vidare kopplas till olika
miljöfaktorer. Dessa studier visade att LD12 kan utgöra en andel av det totala bakteriesamhället som är i paritet med SAR11 i marina system (40%)
men också att denna grupp och även andra Alfaproteobakterier uppvisar en
betydande dynamik under året. LD12 gynnades under perioder som kännetecknades av hög halt fria näringsämnen, högt siktdjup och låg växtplanktonbiomassa. Flera olika LD12-populaioner identifierades, men en enstaka
population var dominant under alla säsonger och såväl epilimnion som hypolimnion.
För att bygga vidare på observationen att LD12 vidmakthöll en betydande
population i både yt- och djup-vattenmassor under sommarskiktningen, genomfördes en mer detaljerad studie av bakteriesmhällets förändringar under
denna period. Odlingsoberoende metoder användes för att följa hur olika
grupper och mer högupplösta populationer svarade på uppdelningen av
sjövattnet i två vattenmassor: solexponerat och varmt ytvatten samt mörkt
och kallt djupvatten med gradvis lägre syrgasinnehåll. Resultaten visade att
ett fåtal bakteriesläkten, inklusive LD12 och släktet ac1 inom fylum Actinobaceria, dominerade i såväl ytvatten som djupvatten och då även när det
mesta syret förbukats under en flera månader lång skiktning. Dessa släkten
är typiska sötvattensbakterier som återfinns i de flesta sjöar och resultaten
tyder därför på att förmågan att leva under väldigt olika miljöförhållanden
såsom i närvaro eller frånvaro av höga syrehalter, är en avnlig egenskap hos
sjöbakterier. Vid en mer högupplöst analys av dessa släkten visade det sig
dock att dessa släkten utgjordes av ett flertal distinkta populationer som
uppvisade viss preferens för endera vattenmassan eller för syrerika vs.
syrefattiga förhållanden.
Bakteriepopulationer interagerar nu inte bara med den omgivande miljön,
utan det finns också starka posiiva och negativa interaktioner mellan olika
mikroorganismer. För att identifiera och beskriva dessa kopplingar inom
samhället analyserades ytvattensamhället med avseende på kopplad dynamik. Populationer vars förekomst förändras på likartat sätt över tid kan
förutsättas endera vara funktionellt kopplade eller påverkat på likartat sätt av
styrande miljöfaktorer. På samma sätt kan populationer som kännetecknas av
inverterad dynamik förutsättas endera konkurrera med varandra vid nära
släktskap eller styras av helt olika miljöfaktorer om de endast är avlägset
besläktade. Genom att unyttja denna typ information i en nätverksanalys
kunde inbördes relationer i ett bakteriesamhälle beskrivas. Även här fanns ett
visst fokus på LD12 och släktet ac1 inom Actinobacteria, och dessa
dominerande bakeriegruppers koppling till andra typiska sötvattensbakterier
kunde beskrivas.
43
Sammanfattningsvis visar min forskning på betydande variation i hur olika bakeriegrupper svarar på olika typer av miljöfaktorer och att man ofta
behöver använda högupplösta verkyg för beskiva dessa gruppers dynamik på
ett sätt som ger mekanistisk förståelse av de processer som formar de komplexa bakteriesamhällen som finns i våra vatten.
44
4 Summary for Kids
Bacteria are everywhere and without them we could not live. Most of them
are our best friends. There are good guys and bad guys, but just like in our
word, most are nice. Some help us, like they ones which are in our guts, they
help you to make the best use of the food you eat. Others can make us sick.
They often sit in the bathrooms for example and want that you don’t wash
your hands so they can travel on your hands to a new place to make some
one sick. Some travel with the wind and cause your cold. The wind can be
your own sneeze for example. The world of bacteria is not so much different
than ours…just much smaller. Just as we humans, they can look very different and like different things to eat. Some can eat big things and some rather
porridge like things because they don’t have the “teeth “ to eat a steak. Some
bacteria like to play with others and even sit on each other and cuddle a
round a lot and share their food or even feed each other. Some like more to
float around alone. Bacteria are so
small, that we cannot see them with
our eyes. But if we use a magnification glass we can actually see them.
Even they might look just as little
blobs, when we use stronger magnification glasses we can see that they can
look very different from each other.
There are some that look like balls,
others like cheese chips, salt sticks or
donuts or noodles. Very funny! Just
like we, some are couch potatoes and Figure 12. How I showed my kids
just sit somewhere around and hope what I see in the microscope
food float bye. Others are very mobile
can use propellers to move around. What really makes them different from
us is, that they do not really have a mom and a dad. But it’s not as bad as you
think. They don’t mind. Once they want to become a family, they just divide
into two. So actually every bacterium is its own parent. Very cool, or?
Sometimes they like to get some new features to do something new. Just like
in a video game they can get extra powers from somewhere else. For examples viruses can deliver those extra features. Viruses just poke bacteria and
inject the new power into them. Great! That means they can now do things
they could not do before. Sometimes I wish I were a bacterium too.
45
5 Acknowledgements
I want to use these pages to express my deep gratitude to all the people that
influenced me in different ways, professional and personal. The biggest
thank you goes to Stefan, my supervisor. In the interview for the PhD position you stated, that you like to be challenged by your students. If I haven’t
done that in the last years, I certainly did it in these last weeks. You provided
me with a runway and let me try out my wings in the world of research. We
both know, I was not always flying high, however when I came to close to
the ground you provided me with the needed upwind and finally helped me
to land safely. Thank you for being my “ Doktorvater” and just as a real father, letting me do my own mistakes and evolve. Thank you for sharing your
visions that taught me so much of what I know today. Alex, from PhD companion to a supervisor. Your steps with your “high heels “, your voice in the
corridor and your cereals in the office. I thank you so much for this enormous help the last weeks to get the manuscripts in good shape. Thank you
for your critical thinking and all the advice in statistics. A big tack goes also
to Lars for all your kind constructive words and help. Special thanks also to
Silke and Eva for proof-reading and your kindness all these years. Gesa, I
thank you for your open mind and the little chats in the corridor. Thanks to
all Limno-Seniors for your kindness over all these years, thank you Anna,
Peter, Richard, Sebastian. And you Postdocs, you research drivers, thank you
ABC: Andrea, Birgit and Claudia, for all the little nice chats about science
and real life and thank you for all the encouragement. Thank you MMS:
Martha, Moritz and Sari for being so friendly persons and thanks to Heli,
Dolly, Karen, Kristin, Oona, Johanna and Raquel. Simone, Sarahi and Nuria,
your smile and laughter turn every winter day sunny. Omneya, I enjoyed the
trips to the workshops a lot, thank you for your company. Thank you Janne
and Christoffer for being so helpful all these years. Also a big “thank you”
goes to the entire crew of the research crew of Oden and the team at Erken.
Without them such research would not be possible. Speaking about, without
the numerous financial support in form of scholarships, travel grants and
stipends, I would not have been able to perform a great deal of the side projects, workshops and conferences. I thank the Federation of European Microbiological Society (FEMS), the Malméns foundation, the C. F. Liljevalch
foundation, the Olsson-Borghs foundation, the Ymer-80 foundation, the
European Cooperation in Science and Technology (COST), the Wallenberg
foundation and the EBC Graduate School.
46
My dear old and new PhDs, thank you all for going this way together. Thorsten, my roomy thank you for your endless attempts to relax me and for introducing me to the “nothing box” of the male brain. Even tough you didn´t
succeeded in teaching me how to use this box (since we females just don’t
have it), I am happy to know that half of the human population can. Thank
you also for the good time in Copenhagen. Valerie, it was such a pleasure to
share little and big thoughts about everything with you. In a few weeks we
will so party!! Thank you Roger for your enduring way and help in the last
weeks. Inga, thank you so much for you driving the journal club, and for all
the nice chats in between. Monica and Lucas, thanks for the pleasant time in
Italy. Alina, Anne, Blaize and Hannah, thank you for being such lovely persons. Martin and Leyden, Nicklas, Annastasija, Annika, Maria, Zee, Yang,
Jingying and Yinghua thank you for making the PhD group such a friendly
and diverse community. Thank you Jovanna for being such a strong driver
and inspiring source in our PhD community. Karolina, thanks for the little
breaks outside. Rhiannon, I enjoyed our escape trips to music and dance so
much. I want to thank you for your open ears and open mind and for all the
good chats we had. It means a lot to me. Time went by but I have not forgotten the time with the first generation PhD. Sara we started this journey together, shared 5 sek noodles, lab fun and the great time at SAME in Faro.
Lorena, thanks for being the best and long-term office mate. We periodically
switched residence on the desk when we changed our passions from science
to diapers back and forth. And thanks for tolerating our hotel room full of
food all the time in Nice at ASLO. Jürg, you taught me a lot and I always
admired your perfect organization. Thank you, Jürg and Yvonne for all the
great chats about science, family and life. Thanks also to Pia, Philip, Hannes
and Cristian. Laura you taught me a lot and I want to thank you for teaching
me how to fish in the dark for silver grains. Ramiro, thank you for showing
me how to take the first scary steps in the deep dark forest of phylogenies.
From phylophobic to phylophil. I would also like to thank the students I had
the pleasure to supervise and who helped me in the lab. Julia, Jenny and
Pianpian, I also did learned a lot from you! And thanks to all the people I
forgot to mention here, there are a lot more I have space for.
This thesis is more as a work-piece for me, thus I also want to thank people that deeply inspired me during all this years in research. Two very adorable women let me share their passion for the unknown in the deep ocean.
They infected me and showed me that it is ok to burn for something, even if
others might think methanoxidizer or a particle in the water column is boring. I had the luck to work beside you on the cruises and you let me feel the
deep satisfaction of the hard work on board of those ships. Thank you so
much, Antje Boetius and Trish Yager. Janos Hajdu, your caring and encouraging way as well as your enthusiasm that did influenced me a lot. You are a
true visionary with fantastic ideas and a lot of drive. The time on Oden was
47
the biggest adventure of my life. Hanna, thank you for the good time on
board. We were a great team, as well on deck, as in the lab and in front of
the fridge at 4 am. Remember our gigantic Roast-beef-sandwiches we so
badly deserved after the night shifts? And of cause Kevin and Marvin, your
presence made the lab and board life so much more fun!
Nothing "is rotten in the state of Denmark"! Thank you Jeppe Lund Nielsen
for the hospitality in your lab in Aalborg and teaching me how to FISH.
I also want to thank Michaela Salcher, Jakob Perntahler and Michael Zeder
in Zürich for the help to count the millions of cells on hundreds of filter
pieces.
My dear friends, Ida and your four boys, thanks for all the friendship, the
pancakes and for being such a lovely friend. Lisa, from neighbors to friends.
I always loved your chats about how it feels to step into a Lego.
Erik, what can I say? You were there for me in my dark hours and you
opened my eyes for the beauty in life when I was too tired to see it myself.
Thank you for all that you are. Håkan thank for your believe in me these few
last days of my PhD and for the word “stoooopid! “
My parents, I am so grateful that you always let me choose what to do with
my life and no matter what; my home is a harbor I can always return to. You
supported me in every way. And Dagmar, Andrea und Herbert, ich danke
Euch so sehr für all die Unterstützung und den Zuspruch während all der
Jahre. And Marie Luise! UZ! My beloved sister, you were and are always
there for me. I love you so much! Daniel, I have no words that could possibly express what you meant to me and how you always been there and made
me feel save. 16 years ago I went on my first student-party and was planning
to start the wild student-life. Who could have known, that we will go this
long way side-by-side and become a big family? From trying to teach me
physics to taking over much of the responsibly for the little once during the
last month. You were always there for me and supported me. Ich danke Dir
von ganzem Herzen und ein Leben ohne Dich kann ich mir nicht vorstellen.
My beloved little busiga barn, Klara and Anton, nothing makes me more
happy than your simile when you fall a sleep in my arms. You are the wings
that make me fly. I love you little guys more than I could ever have words
for.
Doing research in the microbial world taught me also about life as such.
No man is an island. We compete and need. We take and give.
Our world changes constantly too and in order to have a good life and be a
meaningful unit for society, we need to defend our niches and sometimes we
need to realign.
Thank you to all for helping me to understand.
48
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