Eukaryotic biodiversity of Arctic and Antarctic sea ice
– a molecular approach
zur Erlangung des Grades einer Diplom-Biologin vorgelegt von
Braunschweig, den 28. September 2007
1 ufer: Prof. Dr. Michael Wettern
1 ufer: Prof. Dr. Ulrich Bathmann
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List of Tables
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rRNA rpm ss
ACC Antarctic Circumpolar Currents
BLAST Basic Local Alignment Search Tool bp base pairs
Cytosin combined phylogenetic group dissolved inorganic phospate dissolved organic carbon dissolved organic nitrogen desoxyribonucleic acid ds dNTP
G double stranded desoxy ribonukleosid triphosphate
Guanin kb kilo base pair
NADW North Atlantic Deep Water
RNA optical density operational taxonomic unit polymerase chain reaction practical salinity unit ribosomal desoxyribonucleic acid ribonucleic acid ribosomal ribonucleic acid rounds per minute single stranded
Thermus aquaticus unit: unit for enzyme activity
Sea ice covers extensive areas of the polar regions. The conditions within and around the ice are highly variable. This results in many different habitats for organisms, ranging from protozoans to huge animals.
The investigation of sea ice in general is difficult, that is why no spatial or temporal coverage of sampling sites was possible so far. The observation and description of sympagic communities were usually done by various microscopic techniques.
The detectable biodiversity can be increased by methods which base on the identification of characteristic DNA fragments. This approach allows the analysis of organisms, which are too small for light-microscopy, not distinguishable by its morphology or very rare. A well known method for other ecosystems is sequencing of 18S libraries which provides a highly conserved fragment of all eukaryotes in the sample for sequence analysis.
The aim of the present study is to use 18S libraries to analyse the eukaryotic biodiversity of sea ice and to estimate its advantages and boundaries.
Samples from Van Mijenfjorden on Svalbard (Arctic) and from the Weddel Sea
(Antarctica) were analysed by sequencing of 18S clone libraries and compared concerning their biodiversity. The samples originated from sea ice which differed in the generic ice class and its age, for instance. Therefore, assumptions about the influence of biotic and abiotic conditions on the biodiversity were possible.
The resulting phylogenetic trees varied significantly, whereas the biodiversity was mainly influenced by the processes during sea-ice formation and ageing.
At the Antarctic stations, also biochemical parameters were measured. These data allow the comparison with former investigations which used microscopic methods. The results clearly show similar species compositions, even though the influence of various factors makes significant conclusions difficult.
The Arctic samples were compared with results from expeditions in the southwest of Svalbard. In the present study, surprisingly low numbers of bacillariophyta were found, which is maybe related to the extremely low temperature during this winter or to the influence of the coast nearby.
This study represents a first step into the high-throughput analysis of sea-ice biodiversity by using 18S PCR. For protozoa and metazoa, results agreed in general with those of other identification methods.
A quantification of the observed class and kingdoms is not reasonable, especially for metazoa. Descriptions on species-level would require additional primers and sequencing reactions which is difficult for a high-throughput approach but also not necessary for a first large scale monitoring of sea-ice biodiversity.
”Make everything as simple as possible, but not simpler” (Einstein)
In former times, Arctic and Antarctic regions were expected to be almost devoid of life.
It was taught that organisms could not tolerate such extreme conditions.
But since 1841, when Ehrenberg found mircroorganisms in Arctic sea ice for the first time, our picture of the sea ice ecosystem has become more and more complex. Organisms, ranging from small bacteria and single-celled eukaryotes up to metazoans, live there and even attain high production rates.
The aim of this thesis is to improve our understanding of eukaryotic biodiversity of sea ice by using molecular methods. Besides being able to detect very small and rare species the molecular approach enables morphologically very similar species to be distinguished or even new ones to be identified. The thesis entails the analysis of sea ice samples from the Weddel Sea during a period of one month and from Van Mijenfjorden during a three month period.
Physical processes within the sea ice and in the ocean are analysed in order to understand the mechanisms which control the sea ice biodiversity.
The experimental approach of this work is based on the amplification of
18S rDNA sequences and the generation of 18S clone libraries. The investigation of all abundant species is realized by high-throughput TOPO-TA cloning and sequencing.
The gained sequence data are analysed in a comparable way by the construction of phylogenetic trees using the ARB database. All phylogenetic trees will be compared and the influence of abiotic factors will be discussed.
2 CHAPTER 1. INTRODUCTION
The polar regions are defined as the areas around the north and the south pole. Most parts of these large areas are covered with snow and ice causing
°C and the precipitation as low as 250 mm per year.
Depending on the definition, the Arctic is either the region of the midnight sun, north of the Arctic Circle (66
°33’) or north of the tree line. Another possibility to define the border of the Arctic region is to use the isotherm of
°C in July.
The Antarctic region is the area south of 60
°S, including the continent
The polar regions are covered by sea ice with a great interannual variability in sea ice extent and thickness.
The global coverage of sea ice constitutes up to 13 % of the earth’s surface and is distributed mainly in the Arctic and
In the Arctic, sea ice is encircled by land which blocks its flow southwards resulting in thicker and often ridged ice.
The opposite is the case in the
Antarctic where the sea ice around the continent is only bounded by oceans.
On average, this results in thinner and younger ice compared to the Arctic.
The maximum sea ice extent in the Arctic is about 14×10
2 in February and about 20×10
2 in September in the Antarctic. The difference to the minimum ice extent, which is in the Arctic 7×10
2 during September and in the Antarctic 4×10
Antarctic sea ice can move freely and reach higher drift speeds leading to higher melting rates in warmer waters further north.
Another consequence of the semi-enclosed Arctic ocean is the formation of multiyear ice which is much more common in the north and can reach a thickness of 4 to 5 m.
Multiyear ice influences the biodiversity and species composition.
Sea ice also provides a basis for breeding, resting and hunting and is therefore also important for birds and mammals even during the summer season.
Antarctica and the surrounding oceans are strongly influenced by the Antarctic
The ACC flows eastwards due to strong westerly winds around the Antarctic
Between the Antarctic Peninsula and Cape Horn, it flows through the Drake
Deep water from the North Atlantic (NADW) is upwelled at the
1.1. POLAR REGIONS 3
4 CHAPTER 1. INTRODUCTION so-called Antarctic Divergence and is mixed with the Antarctic Circumpolar
Water. The westerly winds also force a large, near-surface Ekman transport to the north. The direction of the water masses influences the sea ice drift and is therefore important for interpretation of the biodiversity of Antarctic sea ice.
Typical Antarctic sea ice usually does not attain a thickness of solid ice than
can therefore reach high concentrations. Especially in the western Weddell
Sea, where highly deformed pack-ice occurs and even persists throughout the year.
This causes typical communities within the Antarctic sea ice compared to the dominant type of Arctic sea ice which reaches a thickness of 1 to 4.5
The composition and distribution of those sympagic communities is strongly dependent on the age and the thickness of the ice due to several processes which influence the physical features within the sea ice such as brine volume, salinity, pH and optical properties. The ice is colonized by viruses, bacteria, protists and fungi, which are partially endemic.
These microorganisms are common in both polar regions. They are spread over the whole ice column as
Metazoans differ in both regions: Arctic sea ice contains nematodes, rotifers, turbellarians and copepods whereas Antarctic sea ice is dominated by copepods and turbellarians. The so-called krill, which can attain a very high biomass, is a very important component of the food web.
Structure of sea ice
As described above, the structure of sea ice varies considerably depending on the conditions during formation but also during ageing. These processes
the ice-history to interpret the resulting species composition.
The formation of sea ice depends on the water turbulence.
At temperatures under – 1.8
°C , water forms a dense suspension of ice crystals, called frazil ice or grease ice.
Under quiet conditions, the frazil crystals freeze together and form a thin layer of ice on the ocean surface, which is called nilas. On the underside of this layer, ice growth continues to form congelation ice.
This congelation growth leads to the typical structure of first-year ice.
If the water is moved by wind and waves, the crystals at the surface can not easily stick to each other to form a consolidated layer.
Therefore, the cyclic compression of the frazil ice leads to single pancake-like ice floes
1.3. BIOLOGY OF SEA ICE 5 with raised rims of ice on the edges.
Further in from the ice edge, the water surface is calmed and the pancake freeze together into smaller floes or pancakes of 3-5 metres.
The bottom of this ice is very rough because the pancakes were jumbled together during the freezing process.
Single pancakes are rafted over one another or even protrude upwards resulting in a much thicker consolidated ice layer. This solid pack ice is typical in the
Southern Ocean, but also develops in the Greenland or Bering Seas for example.
The formation of ice also leads to two typical crystal structures: needle like crystals, known as columnar ice, form under calm conditions. On a rough water surface, there will be small, round crystals which form so-called granular ice. Often, a combination of both ice types appears.
During the freezing process of the water molecules, salts are expelled and form the highly saltine brine, with a salinity of 143 parts per thousand at – 10
This semisolid matrix changes during ageing and the brine
°C the fraction of this bulk liquid can be less than 5% whereas at lower
connectivity of pores and hence, to a change in permeability for nutrients and
A third characteristic ice type in the Antarctic region is the unconsolidated under-ice layer, called ”platelet layer”.
These thin ice discs are produced when deep water is upwelled underneath ice shelves and supercooled
Biology of sea ice
Primary production of ice algae is 10 to 30% of overall primary production in
, is 1 to 4 % of the annual biogenic carbon production of the Southern Ocean
food source for zooplankton during the winter.
6 CHAPTER 1. INTRODUCTION
T, °C S , ppt
, % largescale z ice
-2 -10 40 150 5 20
Figure 1.2: Schematic representation of the ice environment depicting attenuation of solar radiation, distribution of small-scale (sub-mm to mm) porosity feeding into large-scale (mm to dm) pores. Salinity-depth and brine volume-
highly variable. A typical distribution of species within the ice is composed of
75% diatoms, 14% autotrophic flagellates and 11% heterotrophs.
Planktonic organisms as well as detrital material from the upper water column are incorporated into the sea ice during its formation. As outlined by
The various materials such as silt, diatom frustules and living plankton can either rise with frazil ice to accumulate at the surface or by propagating wave fields.
This passive ”harvesting” process may enhance the introduction of
the abundance of raphid pennate diatoms and foraminifers as proposed by
The species composition of bottom-ice communities is also
succession processes .
Depending on the size of the organisms and their ability to adapt to the conditions within the brine channels, so-called sympagic communities develop during the ageing of the sea ice.
1.4. ICE ALGAE 7
The sympagic environment holds a wide range of ecological niches, characterized by different combinations of physico-chemical boundary conditions.
Compared to the open ocean, the temporal variability of light conditions is much smaller and the location within space is more fixed. For autotrophic organisms this means more constant irradiance for photosynthesis.
On the other hand, they have to sustain lower temperatures and higher salinities than in the water column. At lower temperatures, which leads to a closed or semiclosed pore system, the nutrient supply varies due to lower exchange
Besides, a lack of nutrients can be
communities include viruses, bacteria, algae, lower fungi, flagellates, protists
organisms with regard to their species composition, distribution and abun-
between ice cores taken 30 cm apart.
This indicates the complexity of the sea ice ecosystem. The patchy distribution of organisms is mainly caused by the ice type and therefore by incorporation processes and physico-chemical conditions.
The most dominant representatives of sympagic communities are pennate diatoms, which can produce chlorophyll concentrations of up to 1000µg per
. The highest biomass of algae can be found in platelet ice and near the bottom of fast ice. Typical ice algae are, depending on the habitat and the season, Fragilariopsis, Haslea, Thalassiosira, Navicula, Amphiphrora, Melosira,
Phaeocystis and Nitzschia species.
algae in Arctic pack-ice is not lower during the winter season, even though the abundance of ice-algal cells is significantly lower. This clearly indicates the potential of surviving the winter, which is possible by several overwintering
observed distinct difference between autumn surface-water communities and
Algal blooms are also typical at the ice edge due to shallow and stable surface
8 CHAPTER 1. INTRODUCTION
blooms in the open water, after the ice has retread, often cover a huge area and therefore play an important role for grazers.
Sympagic communities can be split into different groups, depending on the ice type and their vertical distribution within the ice. An overview is given
consist of the infiltration communitiy at the snow-ice interface, which is typical for Antarctic pack ice. Another surface community occurs due to deformation processes and flooding of the ice surface in the Arctic and Antarctic region.
Because of the higher irradiance, the cell concentrations can be 10–100 times higher than the underlying water. A very important community in the Arctic, occurs in melt pools, which can cover 50–60% of the Arctic sea ice. Depending on their formation, either by surface thawing or by splashing, they can be freshwater, brackish or saltwater ponds and contain a variety of organisms
In the Antarctic sea ice, melt pools can develop below the surface of consolidated snow. The high production rates there are due to small diatoms and flagellates on the fast ice or to terrestrial and snow algal assemblages in the coastal tide-crack zone.
The interior habitat begins under the surface communities.
The uppermost freeboard community develops in rotting ice and can include algae producing high chlorophyll a levels. Krill has also been observed in this layer.
Underneath the freeboard community, which was only found in Antarctic sea ice, an area with brine channels and band communities exists.
These communities living in the brine channels are of varying diversity, depending on the physical conditions which determine the permeability and therefore an exchange between ice and water communities.
Diffuse communities, which have hardly been studied in the Arctic, in
Antarctic pack ice comprise bacteria, diatoms, dinoflagellates, autotrophic and heterotrophic flagellates, foraminifers, ciliates and also micrometazoans
and Antarctic sea ice, are dominated by diatoms and dinoflagellates.
The bottom ice communities consist of interstitial communities within the congelation ice layer and the platelet ice communities under it.
The most abundant species in the Arctic are pennate diatoms, but autotrophic and heterotrophic flagellates, ciliates, dinoflagellates, heliozoans, rotifers, nematodes, copepods, turbellarians and polychaete larvae can also be found.
Centric diatoms occur more often in pack ice areas.
The platelet ice layer is very favourable environment because it com-
1.4. ICE ALGAE 9 bines more stable conditions than in the water column, but also more space than within the consolidated ice. It also allows better nutrient exchange and
layers of several metres thickness, ”superblooms” of algae accompanied by
Platelet ice communities cover a clearly different habitat which is defined by a different crystal structure and orientation, more space between the crystals, nutrient exchange potential and shading by the interstitial communities. The so-called sub-ice communities are loosely attached to the underside of the sea
Dominant species in the Antarctic sub-ice communities are the pennate diatoms
Berkeleya sp., Entomoneis spp.
The main abiotic factors causing the described distribution of communities are nutrients, especially silicate for diatoms, brine volume and the generic
-concentration, grazing pressure and short-term extremes as well as interspecific competition have not yet been investigated.
In general, ice algae are adapted to the sea ice by several mechanisms.
A cold resistance is realized by antifreeze proteins (AFP), which help to depress freezing temperatures and modifying and suppressing ice crystal growth.
AFPs also protect cell membranes from cold-induced damage by inhibiting the recrystallization of ice in and around the cell. Also, an extremely high salt
ionic composition of the cell. Salt-tolerant organisms can increase the extrusion of salt by increased usage of ion transporters. The accumulation of osmolytes enables to maintain the cellular water potential constant. Some of the organic osmolytes even have a cryoprotective function, which helps to recover freeze
membranes and proteins by sugars. Ice algae also have to adapt rapidly to varying light conditions and to develop protective mechanisms against high
CHAPTER 1. INTRODUCTION
Figure 1.3: Schematic representation of biological communities which can be
Previous methods to investigate the biodiversity of sea ice used microscopic techniques to look at the fixed organisms in melted sea ice.
Bacteria and microbial Eukarya, which play a very important role in natural ecosytems, often lack distinct morphological characteristics, or can not be pre-
extreme and isolated environments have been sources of novel phylotypes. The sequence analysis of the 18S rRNA genes of marine picoeukaryotes, which are
standing of the species composition in sea ice communities, an increasing number of genetic and immunological methods have been developed. The 18S rRNA gene, which is common for all eukaryotes, is used for 18S PCR, quantitative
cloned and sequenced 18S rDNAs were done with deep-sea samples from the
and a surprisingly high phylogenetic diversity.
So far, no molecular approach has been used to investigate sea ice samples, neither from the Arctic nor the Antarctic region.
1.6. STUDY AREA 11
18S ribosomal DNA
Ribosoms are important organelles in every cell because they are crucial for the biosynthesis of proteins. They consist of ribosomal RNA, which is encoded in the so-called ribosomal DNA (rDNA) and proteins. In eukaryotes, the nucleus encloses between 10
5 and 10
7 ribosomes, each composed of four subunits of different sizes. The 18S subunit is usually used for phylogenetic analyses of eukaryotes. Due to its size, it contains sufficient phylogenetic information but is still easier to handle than the large subunit.
The function of the rRNA is a basis for today’s living organisms and was developed early in evolution. As assumed nowadays, rRNA evolves in the same speed in all organisms. Therefore, the rRNA is an important tool to analyse the phylogeny. To simplify the method, the more stable rDNA is used instead of the rRNA.
Depending on the intention of the experiment, more or less conserved fragments are used. Some highly conserved fragments are common for all organisms whereas others can be used to define species. The number of mutations is assumed to differ proportionally to the time and is therefore almost independent of the pressure of natural selection.
The alignment of rRNA sequences of different organisms provides information on their relationship to each other. Based on the calculated phylogenetic distance, a so-called phylogenetic tree can be constructed. But the resulting phylogeny is always completed by morphological and physiological information.
The study area in the northern hemisphere is part of the western Svalbard region. The norwegian archipelago is located between 77
° and 80° North and
° and 35° East. The islands are surrounded by the Arctic Ocean, the Barents
Sea, the Norwegian Sea and the Greenland Sea. The western part of Svalbard is strongly influenced by the warmer and more saline Atlantic water of the gulf stream system. Compared to the canadian and sibirian region, the area of western Svalbard is free of ice for a longer period of the year. As described
occurs in the southern Greenland Sea and southwest of Svalbard. Therefore, the abiotic and biotic conditions there correspond to the conditions in lower latitudes of the canadian and sibirian Arctic.
In 2006, the North Greenland Sea did not freeze near the western coast of
An ice cover could only form on the shallow semi-closed fjord
was therefore chosen as the study area. The oceanographic conditions on the fjord, which is about 70 m deep, are comparable to the open ocean, but the influence of wind and currents is much lower. Due to the proximity to the
12 CHAPTER 1. INTRODUCTION
Figure 1.4: Schematic representation of the ocean currents in the Arctic
1.6. STUDY AREA
Perennial pack ice
Marginal ice zone
Seasonal pack ice
Figure 1.5: Sea-ice regimes and regional structuring of Weddell Sea ecosystem
(not drawn to scale). Also shown is the mean path of ice drift as determined
coast, the biodiversity within the ice can be strongly influenced by the local life-history traits, local topography, glacial runoff as well as local circulation
In Antarctica, all samples where taken in the north-western part of the
about 2.8 million km
, a strong clock wise sea-ice drift with the so-called
This area is characterized by a perennial ice cover and a convergent flow regime. The southern, eastern and central parts of the Weddel Sea belong to the circum-antarctic seasonal pack-ice belt. The ACC transports solid ice, as
cover in the western area, the southern and eastern Weddel Sea has areas with thin ice or even ice-free polynias. This leads to much higher light intensities penetrating through the ice and into the water column. The perennial sea ice is then transported further north where it reaches the marginal ice zone.
This geographical distribution changes, both the temporal evolution and the structure of the sea ice and therefore has important consequences for the ecosystem.
14 CHAPTER 1. INTRODUCTION
Material and Methods
Sequencing of 18S clone libaries
The aim of this work is to investigate sea ice from Arctic and Antarctic regions to compare biodiversity under spring conditions. During ANT XXIII/7, RV in autumn 2006 Polarstern collected ice cores from stations between 60
°6 south near the Antarctic peninsula. At station 060923, the ice was taken from ice floes broken by the research vessel whereas all other ice cores were
extract sea ice communities. Immediately after drilling the ice was crushed and melted in the double amount of pre-filtered (GF/F 0,7µm, Whatman, Dassel,
Germany) sea water at 4
°C. Samples were fixed to a Polycarbonate filter (Isopore mebrane filter, 1,2 µm pore size, Millipore, Schwalbach, Germany) using a filter apparatus.
In spring 2006 sea ice samples were taken from the Arctic fjord ”Van Mijen-
and the 15th of May. To separate the core from the ice cover on the fjord several holes were drilled to form a circle. The loose ice block was lifted out of the water using ice screws. The lowest 30 cm were separated and packed for transport in light and mechanically safe plastic bags and aluminium boxes
(Zarges). Duration of transport was between 3 and 48 hours at +4 and – 25
To fix sea ice organisms by filtering (filter apparatus), sea ice was melted in pre-filtered (GF/F 0,7µm, Whatman, Dassel, Germany) sea water. To estimate the influence of abiotic factors, CTD measurements were done using the
SAIV A/S model SD 204.From both investigation sites, filter were frozen in
2 ml Eppendorf cups or Apex-Tubes at – 80
°C for further analyses in the lab.
16 CHAPTER 2. MATERIAL AND METHODS
Figure 2.1: Sea-ice concentration maps of the sampling sites at Weddel Sea at the sampling day. On September 20 th
, 2006, the two samples 060920D (west) and 060920F (east) were taken.
Figure 2.2: Topographic maps of Svalbard and Van Mijenfjorden on Svalbard.
The encircled area in the map of Van Mijenfjorden indicates the sampling area of the stations 060331 and 060421.
2.1. SEQUENCING OF 18S CLONE LIBARIES 17
Plant DNeasy-Kit (Qiagen)
DNA extraction from Arctic and Antarctic sea ice samples was processed in the same way for all collected samples. The protocol follows instructions of the DNeasy Plant Mini Kit (Qiagen, Hilden, Germany) and was optimized for samples which are fixed on filters. In this work the principle of the single steps in the protocol will be explained. Detailed informations about the reagents in the protocol are not in hand. All informations offered by Qiagen are listed in the appendix (ref.!)
Organic material was removed from the filter chemically by adding the lysis buffer and mechanically by vortexing. If the filter was not colored anymore after this treatment it was removed from the tube.
The following steps of the protocol aimed at the complete cell lysis without breaking DNA fragments. This was realized by the addition of 2 to 3 spoons glass beads (Sigma-Aldrich, Munich, Germany) to the lysate. In the minibeadbeater (biospec products, Bartlesville, USA) these glass beads hit for 60 s at 5000 rpm and ground the cell material. Immediately after this treatment the tubes need to be cooled on ice for a view minutes to avoid damage to the DNA because of warming.
For the following work only DNA was needed. Hence the enzyme RNase was added to the lysate to destroy RNA in the sample during incubation at 65
°C for 10 min.
The lysate includes several types of cell fragments that need to be removed from the sample. To proceed this separation a second buffer was added which increases the pH to 8. The buffer precipitates proteins, polysaccharides and detergent. The whole lysate was transfered to a Spin Column (QIAshredder
Mini Spin Column) with a membrane to collect precipitates. After a centrifugation step all cell fragments except DNA were removed from the flow-through.
Centrifugation during the whole DNA extraction was done with Eppendorf centrifuge 5417R.
The flow-through still includes small particles and molecules that can disturb further analyses. The third buffer, consisting of ethanol and salts among other ingredients, is necessary to precipitate DNA and to bind it to the silica-gelbased membrane of a second spin column. Based on positive charged groups of the anion exchanger column, the negative charged backbone of the DNA binds to the membrane. The process depends on the pH of the buffer. Therefore, a defined amount of salts are included in the buffer. After another centrifugation step, only the DNA is bound to the membrane. Proteins and other molecules without strong negative charged groups can pass the membrane.
The DNA was washed by addition of two times wash buffer including ethanol.
Afterwards, the ethanol need to be removed completely by centrifugation be-
18 CHAPTER 2. MATERIAL AND METHODS cause it influences subsequent reactions.
The washed DNA was eluted from the membrane in two steps, in contrast to the protocol. The Arctic samples were eluted first in 40 µL buffer, incubated for 5 min on ice and then centrifuged for 1 min at 8000 rpm. Afterwards, 20 µL buffer were added and the samples were centrifuged for 2 min at 8000 rpm to increase the yield. Samples taken during ANT XXIII/7 were already extracted on board, except sample G which was carried out later in Bremerhaven. The
DNA extraction for the Antarctic samples was done following the qiagen protocol except the elution step. Here, a total volume of elution buffer was used in two steps. Centrifugation was done at 8000 rpm. The elution of sample G was done with only 40 µL to increase the yield.
The concentration and the quality of the extracted DNA had to be quantified to calculate the composition of further experiments. The principle of DNA concentration measurements based on the photometric analysis of liquids. In this work I used the NanoDrop NS-1000 (Peqlab, Wilmington, USA). This spectrophotometer uses a monochromator to fractionise the light before entering the sample. The light is diffracted by molecules while passing the solution.
The deflection results in changes of the wavelength and can be measured by a detector. NanoDrop NS-1000 analyses the light spectrum between 220 and 750 nm. For each measurement only 1.5 µL of sample were necessary.
PCR amplification of 18S rDNA fragments
The aim of this work is to identify eucaryotic organisms by means of 18S rDNA sequencing. Therefore highly conservative DNA fragments were amplified by
Polymerase Chain Reaction (PCR) and analysed by sequencing defined parts of these fragments.
The DNA encoding for ribosomal proteins is very conserved between all organisms. The 18S rDNA only occurs in eukaryotic organisms and makes it therefore possible to exclude bacterial DNA from further investigations. Some regions of the 18S rDNA are more suitable for phylogenetic analyses than others. In this
The PCR reaction is based on the elongation of nuclein acids analogous to the transcription process in living cells. Hence the enzyme polymerase as well as all four nucleotids and suitable conditions are essential for the process. An
DNA template aimed to be 50 ng/ µL. In cases with very low concentrated
DNA the amount of used template was much lower but at least 10 ng/ µL. The
HotMasterMix (Eppendorf, Wesseling-Berzdorf, Germany) includes Taq DNA
2.1. SEQUENCING OF 18S CLONE LIBARIES 19
denaturation at 94
°C, (2) Hybridisation of template DNA and primers at 52°C,
(3) Elongation of the new strand from 5’ to 3’ by the DNA Polymerase and (4) first cycle of DNA amplification is finished.
20 CHAPTER 2. MATERIAL AND METHODS
Table 2.1: Thermocycler program for 18S PCR showing the temperature and the duration of each cycle as well as the number of repetitions.
temperature duration repetition
1 cycle hold
Polymerase, 200 µM of each dNTP and 1.5mM MgCl
. For amplification of eukaryotic 18S rDNA fragments the forward primer 1F and the reverse primer
Operon Biotechnologies GmbH (Germany). Thermal cycling was carried out on the PCR Mastercycler (Eppendorf, Wesseling-Berzdorf, Germany). This ensures the denaturation (94
°C) of double-stranded DNA, the annealing (52°C) of the primers to the complementary DNA and the extension of the primer (68
°C to 72
After PCR amplification the 18S rDNA fragments were transformed into bacterias to built up clone libraries. Hence, DNA fragments of the appropriate size were selected by gel electrophoresis using the Mini-sub cell GT and the
PowerPac basic power supply (BioRad). The PCR products were marked with
SybrGreenI nucleic acid gel stain (Invitrogen, Karlsruhe, Germany) and mixed with loading buffer (Qiagen, Hilden, Germany). An incubation for 5 min at room temperature under low light conditions allows the cyanine dye to bind to double-stranded DNA. To reduce the decomposition of the light sensitive Sybr-
GreenI the whole electrophoresis process needs to be protected against strong light. According to the size of the DNA fragments, agarose gels (Agarose high resolution, Sigma-Aldrich, Munich, Germany) with 1.2 % agarose in TAE buffer
(Tris Acetate-EDTA buffer, Sigma-Aldrich, Munich, Germany) were prepared.
By using a 1kb ladder (Sigma-Aldrich, Munich, Germany), the size of the DNA fragments can be defined. To view the stained DNA a Safe Imager blue light transilluminator (Invitrogen, Karlsruhe, Germany) was used. The DNA-dyecomplex can absorb blue light at 498 nm and emit it at 522 nm. Hence, the green parts of the gel indicate included DNA. An example for the result of the gel electrophoresis is shown in Fig.
DNA bands of appropriate size were cut out of the gel precise and purified by means of the MinElute Gel Extraction Kit (Qiagen, Hilden, Germany). Following the protocol the gel was dissolved in a high-salt buffer during the incubation step. The high-salt conditions allow the selective binding of DNA on the silica membrane. Impurities can be washed from the DNA by use of an ethanol con-
2.1. SEQUENCING OF 18S CLONE LIBARIES 21 taining wash buffer. The elution was processes with a low-salt buffer releasing the DNA from the silica membrane. To concentrate the eluate only 10 µL elution buffer were used for all Antarctic samples. In all cases of Arctic samples, which yielded very low DNA concentrations, the elution step was repeated to guarantee the maximum yield.
Again, the concentration of the purified DNA was measured using the Nan-
Clone library generation
The construction of clone libraries from 18S rDNA fragments was done using the TOPO TA Cloning Kit (Invitrogen, Karlsruhe, Germany). This method is based on the following steps: ligation into the plasmid vector, transformation into bacteria cells, separation and amplification of the cells and extraction of the plasmids from bacteria cells. The 18S rDNA PCR fragments were ligated
Topoisomerase I. Compared to other ligation protocols, neither the digestion of
DNA fragments nor the linearisation, dephosporylation or digestion of the vector is necessary. The supplied vector pCR2.1-TOPO is already linearised and bound to the Topoisomerase I. The formation of a covalent bond between the tyrosyl residue of the enzyme and the 3’phosphate of the cleaved vector allows to keep the vector in the activated state. The single 3’-thymidine overhang of the vector binds efficiently over hydrogen bonds to the single 3’-adenosine overhang of the PCR-product, which is always synthesised by the Taq polymerase. The unbound 5’hydroxyl group of the PCR fragment then attacks the phospho-tyrosyl bond between the vector and the enzyme. The energy saved in the phospho-tyrosyl bond is used by the enzyme to catalyse the ligation process between vector and 18S rDNA fragment. The ligation was done following the protocol in the TOPO TA Cloning Kit using at least 50ng/µL of PCR product.
Transformation of plasmids into bacteria cells can be done in two different ways.
The chemical transformation uses heat shock to allow insertion of PCR products into the chemically competent E.coli (One Shot TOP10 Chemically Competent
Cells, Invitrogen, Karlsruhe, Germany). The heat shock is performed at 42
°C in a waterbath (Thermomixer comfort, Eppendorf, Wesseling-Berzdorf, Germany) following the TOPO TA Cloning Kit (Invitrogen, Karlsruhe, Germany) which includes besides cells and vector also S.O.C.medium (Invitrogen, Karlsruhe, Germany)for the incubation of cells. The transformation rate for the chemical transformation is lower than for electroporation. Hence, all samples except sample 061008 were transformed using electroporation. The electroporation bases on the increase of the permeability of the cell membrane caused by an external electrical field. Pores in the semipermeable membrane are formed when the electrical field is applied in the appropriate strength and duration.
Substances, for instance plasmids, can pass the pores and enter the cell nu-
22 CHAPTER 2. MATERIAL AND METHODS cleus.
The cell suspension (25 to 50 µL), gently mixed with 2 µL ligation product, needs to be protected from arcing processes. A higher salt concentration increases the electrical conductivity which may kill the bacteria cells. Hence, the ligation product was desalted by pipetting it on a nitrocellulos filter (0,025 µm;
13 mm; Millipore, Schwalbach, Germany)sitting on deionized water in cell culture plates (Nunc, Germany). An incubation of 5 min allows the diffusion of salt through the membrane from the higher concentrated solution to the lower concentrated one. The desalted ligation product was directly used for the electroporation process.
The cell suspension, mixed with the ligation product, was added to a precooled quartz cuvettes (BioRad, Hercules, USA). Immediately, the cuvette was put into the electroporation chamber of the GenePulser Xcell (BioRad, Germany). The set voltage was 1.8 kV and the pulse length 5 ms. The actual time and voltage always differed little from the set one and is shown in Directly after the pulse, 250 µL room-tempered S.O.C. medium was added to
Biosciences, San Jose, USA)and incubated at 37
°C (incubator 1000, Heidolph
Instruments, Schwabach, Germany) and mixed at 250 rpm (Unimax 1010; Heidolph Instruments, Schwabach, Germany) for one hour to allow gene expression of antibiotics resistance genes.
After the incubation step, transformed cells were plated on cell culture plates
50 µg/mL Ampicillin. To make blue-white selection possible, 40 µL of X-Gal
(promega, Mannheim, Germany) with a concentration of 40 µg/ µL were added to each plate. The cell suspension was plated in different concentrations, depending on the transformation method and the resulting transformation rate
The dilution of the cells was proceed in S.O.C. medium to a final volume of
50 to 80 µL to allow an equal dispersion and separation of the cells. Plating was done with a Trigalski-spattle under a clean bench (Hera safe, Heraeus,
Hanau, Germany). During the incubation at 37
°C the formation of colonies of different clones was possible. Each of them was containing a variation of the
18S-fragment, depending on the DNA pool in the origin sample.
Working with clone libraries makes an sufficient amount of cells necessary.
Therefore, the cells were amplified by picking some cells from each colony and transferring them to LB medium. For all clones of station 061008 and partial
all other cells were grown in LB PlasmidGRO
(Genetix, Munich, Germany) to maximize the yield of cells.
For each sample, the first clones were grown in 3 mL medium in 15 mL Falcon tubes and processed separately until sequencing. If the results were successfully, all steps were done at 96 scale. The LB medium was distributed to the tubes of
2.1. SEQUENCING OF 18S CLONE LIBARIES 23 the Deep Well-Plates 96 (Assay Block 2 mL, Costar, Bodenheim, Germany) by using multi-channel pipettes (Eppendorf, Wesseling-Berzdorf, Germany) during working process under the clean bench. For 96 scale, only 1,2 mL medium were used leading to a smaller yield of cells. The cells were allowed to grow for 20 to
24 hours at 37
°C while mixing at 250 rpm in the incubator (Heidolph unimax,
Heidolph instruments GmbH & Co.KG, Schwabach, Germany). The duration was found to be optimal for LB PlasmidGRO
T M being 21 hours. This was the shortest incubation time leading to a sufficient yield of cells. Longer growth periods may cause an increasing number of dead cells.
From each sample a backup was made by freezing 140 µL of cell suspension
(in 96-well Mikrotiter plates, Biozym, Germany), mixed with 60 µL of 50% glycerol at – 80
°C. The rest of the suspension was centrifuged for 10 min at
4000 rpm (centrifuge 5810R, Eppendorf, Wesseling-Berzdorf, Germany)to harvest the cells and remove the medium.
For analyzing only the 18S fragments the plasmids needed to be extracted from the bacteria cells. This is done, in general, by breaking the cell walls by acidification, precipitating the genomic DNA and pelleting the cell fragments and genomic DNA by centrifugation. The supernatants, containing the plasmids in high-salt buffer, are selective absorbed by silica membranes in filter columns.
This selective binding process allows, after a washing step using ethanol, the elution of pure plasmid DNA in low-salt buffer. Proteins, RNAs, salts and other metabolites flow through the membrane. Binding, washing and elution processes were proceed by either centrifugation or using vacuum manifolds depending on the used protocol and throughput.
Each station was first proceed in a low throughput to testify the method and the quality of the 18S fragment. This was done with the QIAprep Spin Miniprep
Kit (Qiagen, Hilden, Germany) using centrifugation (centrifuge 5417R, Eppendorf, Wesseling-Berzdorf, Germany) as discribed in the protocol. The washing step was proceed only once, using PE buffer but the second centrifugation step was enlarged to 3 min to completely remove ethanol.
The higher throughput was done for station 061008 with R.E.A.L. Prep 96
Kit (Qiagen, Hilden, Germany) allowing plasmid preparation for 96 samples at once. The performance followed the protocol and used the vacuum manifold
(Qiagen, Hilden, Germany). All other 96 plates were processed by the robot freedom evo (Tecan, Germany) using the software EVOware Standard. The program corresponds to the preparation steps of the R.E.A.L. Prep 96 Kit but the elution volume was set to 75 µL.
A few results of the plasmid preparation were measured by using the NanoDrop.
define the necessary volume for sequencing reaction.
24 CHAPTER 2. MATERIAL AND METHODS
Sequencing of clone libraries
Sequence Analysis (DyeEx-Kit)
Sequencing of DNA and RNA is the only way to view nucleotides base by base.
Other methods compare sizes of fragments or describe binding with known probes. New sequencing methods such as the primer-extension-method allow the analysis of up to 1000 nucleotides. Although you get signals for each single nucleotide there are still mistakes possible in the sequence.
Sequencing reactions bases on a PCR step using dideoxynucleotides (ddNTPs) carrying base-specific fluorescent dyes and working as terminators. Randomly, these ddNTPs are incorporated at each single position of the whole sequence.
The missing hydroxide group at the third as well as at the fifth position of the nucleotide avoid further elongation. The separately labeled ddNTPs, which fluorescent at different wavelengths, can be analyzed using fluorescent-based electrophoresis. The gel has to be capable to separate between molecules which differ in size by only one nucleotid.
In this work, sequencing PCR was proceed using 50 to 100 ng DNA, the BigDye
Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, Hercules, USA) and the universal primer for eukaryotic organisms 528R. The BigDye Sequencing Kit contains 5x Sequencing buffer and Premix hence supplying enzyme, dNTPs, ddNTPs, salts and water. The used Primer, positioned 500 bp behind
To process the incorporation of dNTPs and labeled ddNTPs accordingly to the
DNA sequence a thermocycler is necessary to realize sequencing specific heating
is optimized for a wide range of organisms by using only 52
°C for the annealing step. The lower the annealing temperature is set, the less specific do the primers bind. The sequencing PCR was proceed with the PCR Mastercycler
(Eppendorf, Wesseling-Berzdorf, Germany).
High-throughput sequencing at 96-scale was done for all stations. For sequencing twin.tec PCR Plates 96 (Eppendorf, Wesseling-Berzdorf, Germany) were used.
Products of the sequencing reaction need to be purified by residual primers, unincorporated dye terminators and free salts. For a small number of samples this was done with the DyeEx 2.0 Spin Kit (Qiagen, Hilden, Germany). First, 96-scaled samples were done with the aid of the DyeEx 96 Kit
(Qiagen, Hilden, Germany) using the vakuum manifold. Most sequencing reactions proceed at 96 scale were purified by the robot freedom evo (Tecan,
Germany) using the software EVOware Standard and the sequencing reaction cleanup kit ”Montage SEQ
” (Millipore GmbH, Schwalbach, Germany). As
buffer into twin.tec PCR Plates 96 (Eppendorf, Wesseling-Berzdorf, Germany).
2.3. PHYLOGENETIC ANALYSIS 25
Table 2.2: Thermocycler program for sequencing reaction showing the temperature, duration and number of repetitions of several cycles.
heating up to 1
1 min 28 cycles heating up to hold
10 s 28 cycles heating up to hold heating up to hold hold
4 min 28 cycles
°C samples were first eluted in 20 µL but later in 30 µL elution buffer into twin.tec
PCR Plates 96 (Eppendorf, Wesseling-Berzdorf, Germany). The set volume was dependent on the ensuing preparation proceedings. One possibility is to add 10 µL of 20 µL eluate to 10 µL HiDi Formamide (Applied Biosystems, Lincoln, USA) and denatured at 95
°C for 3 min (PCR Mastercycler, Eppendorf,
Wesseling-Berzdorf, Germany). Another way is to vaporise 30 µL eluate using a SpeedVac (Savant SPD131DDA SpeedVac Concentrator, Thermo Scientific, Dreieich, Germany), combined with a Refrigerated Vapor Trap (RVT400,
Thermo Scientific, Dreieich, Germany) and a Oil-Free Vacuum Pump (OFP400,
Thermo Scientific, Dreieich, Germany).
and dissolve it in 10 µL HiDi Formamide (Applied Biosystems, USA). Again, the denaturing was proceed. The twin.tec PCR Plates 96 (Eppendorf, Wesseling-Berzdorf, Germany) were closed with 96-Well Plate Septa (Applied Biosystems, Lincoln, USA).
Automated sequencing was done using a 4-capillary sequencer (3130 Genetic
Analyzer, Applied Biosystems, Lincoln, USA). Viewing chromatograms can help to estimate the quality of the sequencing reaction. High and clearly separated amplitudes are necessary to gain reliable sequences. In this work chromatograms were viewed using chromas 2.31 (technelysium).
Sequencing only gives informations about the succession of nucleotides and therefore about the number of differences. To fit it into a phylogenetic tree by comparing with known sequences, different procedures are possible. The first and very common way to get a rough idea of the position of the sample in the phylogenetic tree is the usage of online databases such as BLAST (Basic
26 CHAPTER 2. MATERIAL AND METHODS
Local Alignment Search Tool). A phylogenetic tree can be obtained by computational phylogenetic methods using special programs, for instance Staden package (SourceForge, version 1.5). The genetic distance between sequences can be calculated by the neighbor-joining tool. For the estimation of phylogenie the tree needs to have the least number of evolutionary changes. Hence, the
ice, to a phylogenetic tree.
The quality of all sequences was controlled by quality clipping and Phred which are included in the Staden Package. The quality clipping uses confidence values and a minimum sequence length. Additional, the Phred software can calculate quality values to each base. These quality values are log-transformed error probabilities. The Staden Package provides also the alignment tool Gap4 shotgun assembly. This tool compares sequences and defines regions of high similarity to interpret the relation between these sequences. In this work, the minimum exact match was set to 200bp, the maximum number of pads to 10 and the maximum consensus length to 10000bp. The maximum percentage mismatch, which was 2.0 in this case, defines the minimal percentage of consensus which groups aligned sequences to one OTU (Operational Taxonomic Unit).
OTUs are compaired with the sequences of an existing phylogenetic tree and added to the appropriate position. In this work the OTUs were put into ARB
by base frequency. The filter was programmed to exclude the whole column if unknown residues appeared at any position and if real gaps were maximal.
Ambiguity codes and lower case letters were ignored.
The treeing method of the ARB-package is based on the maximum parsimony. Since the resulting tree does not always correspond to the NCBI BLAST
This treatment often leads to a completely different position of the OTU in the tree which is now more similar to the sequence with the highest score in BLAST search.
The species diversity of the phylogenetic tree only take the OTUs in account.
Therefore, also the number of sequences which form on OTU need to be included into the results to compare quantitative.
2.3. PHYLOGENETIC ANALYSIS 27
Figure 2.4: Illustration of an agarose gel; marker (left column) and Antarctic samples were stained with SybrGreenI.
Figure 2.5: Map of the utilized vector pCR 2.1-TOPO; the PCR product is
28 CHAPTER 2. MATERIAL AND METHODS
Sampling of ice cores
In the Arctic, ice cores were taken at 5 dates and 2 different locations, respectively. For the preparation of 18S libraries the samples originating from the fjord were chosen, because their salinity was comparable to those of the
Antarctic sea ice samples. The water at the second location is only seasonally connected to the ocean but always to a freshwater inflow and is therefore less saline. To determine the abiotic conditions in the sea ice, temperature measurements were done in the air over the ice and in the water column.
Salinity, density, and fluorescence were also determined in the water.
The structure of the lowest ice layer was observed and ice and snow thickness were measured. All data of the surface water layer of the selected stations are shown
Abiotic parameters in the Antarctic sea ice were analysed by David Thomas,
Stathis Papadimitriou (School of Ocean Science at the University of Wales,
Bangor) and Marcel Nikolaus (Norsk Polar Institute, Tromsø).
Because these data are more suitable for the interpretation of a relationship between the sea ice biodiversity and abiotic conditions, no additional information about the water column are given here.
and brine salinity and chlorophyll concentration are shown besides snow- and ice thickness data. The given salinities and bottom-ice temperatures for the samples 060920D, 060920F and 060923 were not determined at the same ice core but only at 060919 and 060924 and therefore must be interpreted with care. The mentioned physical measurements were only done once a day. Hence,
lowest 10 cm were used for further experiments only the appropriate abiotic
Stathis Papadimitriou (School of Ocean Science at the University of Wales,
30 CHAPTER 3. RESULTS
For the Antarctic samples, 5 dates were investigated which are spread over the whole sampling period and sampling area. Because the Arctic sea ice developed very late in 2006, samples were selected which date later in the season but also spread over almost one month.
The position of the sampling sites in the Weddel Sea is shown in Figure
XXIII/7 and plotted by Lasse Rabenstein (AWI, Bremerhaven).
Due to the varying facilities at the Arctic and Antarctic sampling sites, only measurements of the air temperature and ice and snow thickness are comparable. The temperature-dependent stratigraphy of the Antarctic samples was plotted by Marcel Nikolaus (Norsk Polarinstitutt, Tromsø), as shown in
Table 3.1: Abiotic conditions at the sampling sites; water temperatures, salinities, densities and fluorescence is measured at 1.25 m depth at station 060331 and at 1.01 m depth at station 060421.
sample ice thickness
[cm] snow thickness
[cm] air temp.
°C] bottom-ice temp. [
°C] water temp.
°C] ice structure
columnar brine salinity
[psu] bulk salinity
DNA extraction and amplification
Concentration and absorption ratio of the template DNA can be found in Table
2.1-TOPO, the transformation of the plasmids into E.coli was done as described
3.2. DNA EXTRACTION AND AMPLIFICATION 31
-15.0 -10.0 -5.0
Figure 3.1: Temperature-dependent stratigraphy of Antarctic sea-ice samples
32 CHAPTER 3. RESULTS
Table 3.2: Nutrient supply of the Antarctic stations.
Si:N:P ratio 2.78
Si:N:P ratio 5 : 2 : 1 25.7 : 12.3 : 1 2.2 : 1.8 : 1 2.7 : 3.5 : 1
Table 3.3: Results of the generation of the 18S libraries and analyses in ARB for Arctic and Antarctic stations sample 60331 60421 060920D 060920F 60923 61002 61008 extracted DNA 2.52
174 91 196 80 273 69 245 number of seq.
>500bp number of
OTUs number of
The gained sequences were grouped to OTUs using staden package (Source-
Forge, version 1.5).
All OTUs were compared to the ARB database.
3.3. PHYLOGENETIC ANALYSIS 33
Table 3.4: Results of NanoDrop measurements: DNA concentration and OD ratios are given after DNA extraction from environmental samples, purification after gel extraction and plasmid preparation (mean values).
sample extracted DNA
A260/A230 eluted DNA
plasmid preparation 64.6
the interpretation, new groups of species could be identified. These so-called
”Combined Phylogenetic Groups” (CPG) pool all sequences with the same closest relative in ARB and the same BLAST search result.
examples of the BLAST search are listed, showing the overlap between query and best hit (”query coverage”) the and maximal identity.
defined CPGs were calculated as part of the total number of OTUs (see Figure
The total number of sequences or OTUs of each taxonomic group can be found on top of each column. The given CPGs are calculated relatively to this total number.
tween all stations which are more clear in the sequence-based bar chart (see
within the appropriate kingdom is shown. The charts are calculated for the kingdoms which contain the highest numbers of sequences and several different
is shown. The fraction of the genus Fragilariopsis can be plotted, because this well observed algae class was safely identified by ARB and BLAST. The species names are not given because different Polar Fragilariopsis species produced the same bootstrap values in ARB and comparable scores by using the BLAST search.
The bacillariophyta are represented by Fragilariopsis in all stations, but in 3
34 CHAPTER 3. RESULTS
the family dinophyceae are plotted. Except at station 061002, which is only represented by 2 sequences, all sequence-based values are dominated by one order of the dinophyceae family.
the same way.
Here, no significant difference between the sequence- and
OTU-based fractions can be observed and each station contains only one or two CPGs.
Calculation of species diversity
The number of sequenced clones from the different stations varies as shown in
increasing sequencing effort has to be estimated. This so-called saturation level
can be calculated. Rarefraction curves of S obs
(Mao Tau) were plotted for the two stations with high numbers of sequences clones and also OTUs and CPGs
saturation of the sequencing effort would be reached.
The phylogenetic trees of the different stations need to be compared to analyze the results from an ecological point of view. A common method to characterize species diversity in a community is the calculation of the Shannon
H = − s
X p i ln p i i=1
The equation bases on the proportion of each species (i) relative to the total number of species (p i
). It includes the species abundance and the evenness of the present species. The value of H can rise ad infinitum, depending on the species richness and the equability. The evenness, which approaches 1 if all species are equally abundant, can be calculated as following:
E = H/ln s
The influence of the sequencing effort on both indices is analysed by plotting
The biodiversity indices were used to estimate the influence of abiotic pa-
lation to the total thickness, including the ice layer and the snow layer on the
3.4. CALCULATION OF SPECIES DIVERSITY 35
75 38 46 28
Choanoflagellates other Stramenopiles
Cryptophyta unclassified eucaryotes
(a) Composition of CPGs of Arctic and Antarctic stations; calculation based on relative distribution of OTUs.
195 80 273 69 245 174 91
Choanoflagellates other Stramenopiles
Cryptophyta unclassified eucaryotes
(b) Relative composition of CPGs of Arctic and Antarctic stations; calculation based on relative distribution of sequences.
Figure 3.2: Relative composition of ”Combined phylogenetic groups” using
OTUs (a) and all sequences (with >500bp and after quality clipping) of the clone library (b). The number on top of each column indicates the total number of OTUs (a) or sequences (b), which were used for the calculation.
36 CHAPTER 3. RESULTS
Fragilariopsis sp. (OTUs) other pennate diatoms (seq.)
Fragilariopsis sp. (seq.) centric diatoms (OTUs) other pennate diatoms (OTUs) centric diatoms (seq.)
(a) Composition of CPGs of Arctic and Antarctic stations; calculation based on relative distribution of OTUs and sequences (shaded) of all Bacillariophyta.
37 174 7 70 10 41 2 2 5
Prorocentrales (OTUs) Prorocentrales (seq.)
Gymnodiniales (OTUs) Gymnodiniales (seq.)
Syndiniales (OTUs) undefined (OTUs)
Syndiniales (seq.) undefined (seq.)
6 7 82
(b) Composition of CPGs of Arctic and Antarctic stations; calculation based on relative distribution of OTUs and sequences (shaded) of all Dinophyceae.
Figure 3.3: Relative composition of ”Combined phylogenetic groups” of all
Bacillariophyta (a) and Dinophyceae (b). The number on top of each column indicates the total number of OTUs or sequences, which were grouped to Bacillariophyta (a) and Dinophyceae (b). The left column of each station shows
OTU-based numbers, sequence-based numbers are shaded.
3.4. CALCULATION OF SPECIES DIVERSITY 37
14 29 3 3 5 5 4 66
Copepoda, Diaptomidae (OTUs)
Copepoda, Neocalanus (seq.)
Nematoda (seq.) Tubularia (OTUs)
Copepoda, Ecbathyrion (OTUs) Copepoda, Ecbathyrion (seq.)
Copepoda, Diaptomidae (seq.) Copepoda, Neocalanus (OTUs)
Figure 3.4: Relative distribution of ”Combined phylogenetic groups”; calculation based on OTUs and sequences (shaded) of all Metazoa. The number on top of each column indicates the total number of OTUs or sequences, which were grouped to Metazoa
10 y = 0,1783x + 13
10 y = 0,1533x + 8
0 50 100 150
Number of clones
0 50 100 150 200
Number of clones
(a) Rarefraction curve analysis of the
Antarctic station 060920D.
(b) Rarefraction curve analysis of the
Antarctic station 061008.
Figure 3.5: Rarefraction curve analyses of S obs
(Mao Tau) vs. the sequencing
Table 3.5: Shannon- diversity indices of Arctic and Antarctic stations.
sample 60331 60421 060920D 060920F 60923 61002 61008
Shannon index H 1.337
38 CHAPTER 3. RESULTS
0 y = -0,001x + 1,0874
50 100 150 200
Number of clones
Figure 3.6: Correlation between Shannon diversity index and the number of sequenced clones of all Arctic and Antarctic stations.
0 y = -0,0007x + 0,5958
50 100 150 200
Number of clones
Figure 3.7: Correlation between Eveness and the number of sequenced clones of all Arctic and Antarctic stations.
0,4 y = -0,2824x + 1,2247
0,4 y = 0,4661x + 0,8699
0,4 0,6 0,8 1 1,2
Total thickness [m]
0 0,1 0,2 0,3
Thickness of snow layer [m]
(a) Distribution of the Shannon diversity index of Arctic and Antarctic stations depending on the total thickness of the snow and ice layer
(b) Distribution of the Shannon diversity index of Arctic and Antarctic stations depending on the thickness of the snow layer
Figure 3.8: Influence of the total thickness of the snow and ice layer (a) and only the snow layer (B) of Arctic and Antarctic stations on the sea ice biodiversity; the line indicates the slope of the calculated regression.
3.4. CALCULATION OF SPECIES DIVERSITY 39
0,4 y = -0,3895x + 1,2827
0,6 0,8 1
Sea-ice thickness [m]
Figure 3.9: Influence of the thickness of the ice layer of Arctic and Antarctic stations on the sea-ice biodiversity; the line indicates the slope of the calculated regression.
ice (a) as well as the thickness of the snow layer (b). The influence of only the
The biodiversity index was also related to the air temperature in Figure
°C within a short time, the change can not be proportional to the change in biodiversity.
1,5 y = -0,0293x + 1,9738
= 0,447 y = -0,0046x + 0,8925
-20 -15 -10 -5
Air temperature [°C]
(a) Distribution of the Shannon diversity index of Arctic and Antarctic stations depending on the air temperature during sampling.
32 34 36 38 40 42 44 46 48 50
Brine salinity [psu]
(b) Distribution of the Shannon diversity index of Antarctic stations depending on the brine salinity.
Figure 3.10: Influence of the air temperature (a) and the brine salinity (b) of
Arctic and Antarctic stations on the biodiversity of sea ice; the line indicates the slope of the calculated regression.
40 CHAPTER 3. RESULTS
The explanation for the differences between the observed sea-ice samples requires the consideration of several factors. In the Arctic, the sampling site is a shallow, semi-enclosed fjord which hence, is influenced by the nearby coast.
Both Arctic stations were taken from the same location, that is why no spatial variation was expected. Hence, differing results can be explained by temporal variations leading to changing light and temperature conditions.
In contrast, the Antarctic samples were all taken at different positions. Therefore, the results need to be interpreted relating to spatial and temporal vari-
For these reasons, a conclusion about a distinct community composition being present due to defined parameters is difficult. The observed species compositions at the different sampling sites can not be clearly related to the location, the abiotic conditions or the time of sampling.
The sampling conditions in Antarctica were much better because the drilled ice cores could be directly transported to the lab to be filtered. The DNA was extracted on board of RV Polarstern or immediately frozen at – 80
In the Arctic, the sampling took one or two days, meanwhile the ice cores stayed at the air temperature. The filtration and freezing of the filters was done after even longer periods. But a clear influence on the discovered biodiversity is not expected since the number of organisms would not change distinctly at these low temperatures. After filtering the melted sea ice, the filters were frozen at
°C and further analyzed at AWI Bremerhaven. The transport of the samples back to Germany was, due to logistic problems, only possible in cooled, isolated containers, which could not avoid a warming up to 0
°C for maximal a few hours. Because DNA is comparatively stable, no significant degradation of the DNA is assumed.
42 CHAPTER 4. DISCUSSION
Geophysical and oceanographic measurements
During ANT XXIII/7, various geophysical, oceanographic and biological measurements were done. Therefore, data for the calculation of ice-concentration maps could be used and the structure of the sea ice layers could be defined.
Also, time-consuming measurements of different nutrients as well as salinity measurements were made by David Thomas and Stathis Papadimitriou (School of Ocean Science at the University of Wales, Bangor) and could be used for this work. These data are more reliable than the Arctic CTD data which only allowed measurements in the water column. The instruments on RV Polarstern were used during the whole cruise and gave comparable data.
For this work, only selected physical data were used depending on their assumed impact on the biodiversity. Oceanographic data colleced in the water column under the ice, such as temperature, salinity and density were not included into the interpretation because the variations are probably too small to influence the highly tolerant sea ice communities.
The melted sea ice was filtered by following the same protocol. Even though
Arctic samples were prepared by another person and under different laboratory facilities than the Antarctic ones, no significant impact of the sampling procedure on the quality of the samples is expected. Important details, such as melting in prefiltered seawater at 4
°C or mixing the sample bottles to include also fast-sinking organisms, were considered in both cases.
DNA extraction on board of the RV Polarstern was done using the same protocol as for the extractions at AWI. The application of the standard DNA extraction kit ”DNeasy Plant Mini Kit” ensured a sufficient quantity of DNA. By disrupting the samples with glass beads and the bead beater, also the DNA of those cells was extracted which are surrounded by frustules or other difficult-to-break cell walls. But in some cases, e.g. if high concentrations of polysaccharides and polyphenolics were present, other extraction methods such as CTAB extraction would be necessary. For high-throughput applications, this method is too timeconsuming. Hence, the fast but possibly not exhaustive method was used.
The quality of the extracted DNA was always tested by NanoDrop measurements. The OD ratios of OD260/OD280 of pure DNA is between 1.8 and 2.0
and a smaller value is caused by protein contamination. The OD260/OD230 ration is used to determine the contamination by phenolate ions, thiocyanates and other organic compounds, which is indicated by values smaller than 2.0.
tration after extraction from environmental samples was sufficient except for
4.2. PROCESSING 43
Arctic samples. Nevertheless, these two samples showed clear DNA bands at the appropriate size after gel electrophoresis and were used for further analysis.
The purity indicated by OD260/OD280 values of 1.6 to 1.8 was good enough for subsequent steps. In contrast, the OD230/OD260 ratios were not satisfactory.
Anyway, the extracted DNA was used because this contamination would not affect the following 18S PCR.
The amplification of the 18S fragments was done in exactly the same way for all samples. The results were controlled by gel electrophoresis, as described in
1528 bp, it was cut out and eluted out of the gel. Otherwise, the 18S PCR was repeated. These steps allow a purification of the desired DNA fragment from other nucleic acids or contaminations. The purity of the eluted DNA was insufficient, which can be explained by the applied chemicals for the gel extraction step. These contaminations were not expected to interfere with further reactions, hence, the extracted DNA was used.
The usage of only one primer set for all samples makes it possible to compare them. On the other hand, an effective amplification of 18S rDNA fragments from all eukaryotic organisms is not assured. As discovered by Katja Metfies
(pers. comm.), the used primer does not bind with the appropriate efficiency to 18S rDNA of Cryptophyta. The ratio of Cryptophyta in a sample was lower if 18S PCR was used compared to other methods. Even though the primer sequence is highly conserved within eukaryotic organisms, mismatches can not be excluded because the primer was not tested for all eukaryotic organisms.
Mismatches at the primer region would necessitate a lower annealing temperature during the PCR reaction. But since only one annealing temperature was used here, probably not all 18S rDNAs were amplified in the same quantity.
Cloning and sequencing
The extracted 18S rDNA fragments needed to be inserted into plasmids and cloned in E.coli to differentiate between the single 18S rDNAs in the sample.
Because only a small fraction of the 18S rDNA is finally transformed into the E.coli cell, a very high number of clones is necessary to include also rare species into the clone library.
the total diversity. The construction of rarefraction curves was done for two stations with a high number of sequenced clones, OTUs and CPGs.
showed a rising slope. This means, that a higher sampling effort would have lead to more OTUs and the phylogenetic diversity would have increased. For
44 CHAPTER 4. DISCUSSION the remaining stations with similar or lower sample sizes it can be assumed, that the saturation point is also not reached yet.
Recapitulatory, a higher number of clones needs to be sequenced at all stations to gain a complete image of the biodiversity, i.e. also including rare species.
The ligation and transformation using the TOPO TA Cloning kit (see
chemical transformation of station 061008 was less efficient and it was necessary to plate 10 times more transformed cells to achieve a sufficient number of clones on the selective cell culture plates. The varying transformation rate and the different transformation method does not effect the results because the success of the transformation process does not depend on the sequence of the vector. Therefore, it is a question of statistics which fragment is included into the E.coli cells.
Also, there is no known influence of the inserted DNA on the ability of the cells to grow on the selective plates. Therefore, the colony picking, choosing white, clearly shaped and big colonies, did not influence the resulting biodiversity analyses.
Possible mistakes, such as picking colonies consisting of two clones, did result in overlaying sequences and were therefore excluded at quality clipping step. A contamination of the clone libraries in the liquid LB medium can not occur due to the addition of Ampicillin. If, anyhow, bacteria or yeast would grow, their genomic DNA would be excluded at the plasmid preparation step. Bacterial plasmids could be amplified during the sequencing reaction, if the plasmid contains the sequence for the primer annealing. The resulting sequence could then be identified as non-eukaryotic and hence, be excluded from the final interpretation.
The plasmid preparation step was done for most samples by the robot freedom evo (Tecan, Germany). This made the high throughput analysis possible. At the same time it causes a risk for cross-contaminations. Even though, the robot works more exact than any human being could, a software or program error could cause wrong pipetting steps. A mixing of liquids from different samples can not be ruled out. Cross-contaminations would lead to chromatograms with superposed signals, which are also excluded due to the quality clipping.
The quality and quantity of the isolated plasmids was investigated by using
280 ng/µL. The OD260/OD280 ratios were in most cases between 1.8 and 2.0
indicating pure enough nucleic acids. In contrast, the OD260/OD230 ratios were too low. This can be explained by the incomplete removal of the ethanol during the plasmid preparation.
An inhibition of the following sequencing reaction was not expected due to the residual ethanol. An extra purification step, which would lead to big losses of plasmid DNA, was therefore not carried
4.3. PHYLOGENETIC TREES 45 out.
The plasmid DNA was used for the sequencing reaction.
As described in
of the transformed 18S rDNA fragments. Also this PCR reaction uses only one annealing temperature, which maybe prefers the amplification of some of the 18S rDNA fragments. But because the annealing temperature is set low, the specificity of the annealing step is low and therefore, relatively many mismatches are tolerated. No eukaryotic species are known whose 18S rDNA fragments are not amplified by the used primer.
The products of the sequencing reaction were purified. Mistakes or unequal treatments at this step would not influence the results, but the quality of the sequence. If the sequence reactions would stand too long after adding the HiDi
Formamide (Applied Biosystems, USA) until sequence analysing, it could lead to week signals. Also, the usage of too old and therefore untight septa may cause a weakening of the labeled ddNTPs, especially of ddGTPs and ddCTPs.
This might change the resulting sequence in single positions.
Phylogenetic analysis using Staden package and ARB
For the construction of phylogenetic trees the dissimilarity between sequences is used because it is qualitatively related to the evolutionary distance between organisms. That means, at least for highly conserved genes, that the most recent common ancestor has a high sequence identity to the query sequence.
For eukaryotes, the similarity between closely related species should be at least
The sequence information resulting from the sequence analyzer were examined by the quality clipping function of the staden package (SourceForge, version
1.5). This function allows to remove weak and overlying sequences. Though, the program does not mark single ”weak” bases, which can be indicators for sequencing errors.
Hence, these errors are treated and interpreted as mismatches. If several of these mismatches accumulate, this will result in lower similarity values and therefore in incorrect numbers of OTUs per sample.
The sequences were grouped by staden package on the basis of a 98 % similarity.
The gained OTUs had to be compared to each other and to known sequences of the phylogenetic tree of the ARB package, which contains about 26.000
sequences. Nevertheless, many species are missing in the ARB-phylogenetic tree, especially those of rare and not often detected species.
The closest relatives to the sequences in this thesis are therefore often species which does not occur in Polar regions. In these cases, only the class or phylum can be defined.
Many of the bootstrap values in the ARB-tree were low, i.e.
46 CHAPTER 4. DISCUSSION
95%, which can be due to distantly related sequences or due to an incorrect alignment. For this reason, an additional classification method is helpful.
As a second tool for comparative sequence analysis, the NCBI database was used for all OTUs.
Exemplary chosen results of the BLAST search in the
query sequence, which is aligned are given as query coverage values. The upper limit of identical aligned residues in the alignment is called maximal identity.
They were compared with the positions of the OTUs in the ARB-tree.
If they were not sorted into the same phylum, the ARB-tree and the appendant filters were calculated again for this OTU. In most cases, the outcome of this was a new position of the sequence in the ARB-tree with higher bootstrap values. The taxonomic position with the highest similarity values in ARB and
BLAST were used for further analyses. The resulting trees are attached in the
with more than 500 bp of one station, together with the closest relatives in the ARB tree. All OTUs which grouped together using the ARB database and which also gave the same BLAST results, were marked with rectangles.
Even though more than 2% of all these OTUs did not match each other, they had to be analysed as on group, a so-called CPG. Due to a lack of known
18S rDNA sequences from polar regions, a more detailed phylogenetic analysis is not possible. The lowest taxonomic level which could be defined using the combined results from ARB and BLAST, classifies the CPGs.
A common conclusion for all phylogenetic trees is the dominance of bacillariophyta, dinoflagellates and metazoa. But also, a very high variability between the stations is obvious.
All trees include OTUs with bootstrap values down to 96%. A similarity of less than 98% means that the two compared sequences belong to organisms from different classes or even phyla.
If neither in ARB nor in BLAST a sequence from this class can be found, the query sequence belongs to a very rare class or even to an unknown class or phylum. Another reason for the low bootstrap value can be a mistake during the alignment process. Mutations or bad sequence qualities also have to take into account. A possibility to control the phylogenetic position of this OTU can be a second sequence reaction. This can be done either of the same fragment to test the method or the whole 18S rDNA can be investigated.
This shows the relative abundance of the different CPGs, which were grouped together to the phylum or kingdom level to simplify the analysis. In (a) all
OTUs were used for the calculation. To quantify the distribution of the CPGs between all sequenced clones, the columns in (b) are based on all sequences with more than 500 bp. The bar charts show distinct differences between the
4.3. PHYLOGENETIC TREES 47 stations. Whereas the stations 060920D and 060920F are clearly dominated by
in all other Antarctic stations. Arctic samples include besides dinophyceae, stramenopiles and bacillariophyta with more than 10%each also high fractions of metazoa and fungi and are therefore different from the Antarctic stations.
Rare classes and families such as haptophytes, choanoflagellates or cryptophyta only occur at particular stations.
This could be either due to a patchy distribution or because of the low number of analysed sequences.
A conclusion about the quantity of each CPG in the environmental sample needs to be made with caution.
First, not all abundant organisms are represented by the number of clones in this work, as shown by the rarefraction curves. The second problem is the specificity of the method: it is not clear, whether 18S rDNAs of all eukaryotic organisms are amplified equally well.
Additionally, many species contain more than one copy of the 18S rDNA gene.
The limitations of the method will be discussed later in this chapter.
In the next Chapter, the bar charts will be compared and interpreted concerning the causes for the variable diversity. Also, the influence of abiotic factors will be discussed using restriction curves.
The ecosystem sea ice is highly variable with respect to species composition.
An extensive investigation of the present conditions, biotic as well as abiotic,
varies due to its generic ice, brine volume and structure, temperature, brine salinity, nutrient supply, irradiance, grazing and interspecific pressure as well as CO
The complexity of the sea-ice ecosystem combined with a small number of samples which all differ in their spatial and temporal distribution, makes it hard to identify distinctly all factors, which caused the observed species composition.
Former studies also consider different
the interactions and to characterize the corresponding sea-ice communities.
All possibly important factors will therefore be discussed here, even though the results can only be assumptions. The size of clone-libraries is too small as shown by the rarefraction curves. The unequal number of clones per sample
significant environmental conclusions.
The correlation between biodiversity index and sample size, but also between eveness and sample size was plotted
Both trend lines decrease if the sampling size increases.
This means, that the dominance of certain species becomes more clear the more clones are
48 CHAPTER 4. DISCUSSION sequenced. For the following discussion, which use the biodiversity index, an equal sample sample size would be meaningful.
The spatial distribution can only be discussed for Antarctic samples. Here, a north to south transect was investigated, and the northernmost samples can be assumed to be the oldest. This is due to the sea ice formation in the south which than, general speaking, drifts to the north. As discussed before, older sea ice underlies a succession. Therefore, typical species of sea-ice communities
The species composition is also subjected to interspecific and seasonal conditions, which will be explained later. This seasonal change mainly explains the development from 94% bacillariophyta at the southernmost station to only 7% diatoms at 060920D and 060920F,
sympagic communities does not allow an interpretation only due to its spatial distribution.
The temporal distribution is expected to follow seasonal variations.
Folsamples are presumed to include more photosynthetic active and silicondependent species, because they were taken earliest in the season. Again, the opposite was found, which excludes the three weeks difference between the stations from the main influencing factors.
Light conditions, which vary extremely during the year, were comparably similar throughout the sampling period. Of more significant impact on the availability of light for sea-ice organisms is the thickness of the snow- and
between 75 cm and 125 cm, the Arctic stations had only a 50 to 65 cm layer.
The snow layer on the ice, which also decreases the light intensities within the ice, reaches from 2 to 34 cm. To analyse, if there is a correlation between the snow- and ice thickness and the biodiversity, the Shannon index was
over the snow layer (b) as well as over the total thickness (a), consistent of the snow- and ice layer. A regression of the determined distribution of data in (a) gives a slowly dropping slope, whereas (b) leads to a rising regression curve. The resulting assumptions of these plots are not consistent as expected for two light-dimmishing parameters. The thickness of the snow-cover does not influence the biodiversity whereas the total thickness leads to a slightly decreasing index, as indicated by the slope of the regression curve. A plot of
the most significant decrease of the regression curve. This might be due to a varying snow-layer because of wind and changing temperatures, whereas the
4.3. PHYLOGENETIC TREES 49 ice-layer is much more stable. This confirms, that a thicker ice cover, which decreases the light intensity, supports the succession process, whereas the snow layer is not of clear importance. Besides, a thicker ice layer is usually caused by a longer freezing period or colder temperatures, which also increases succession and thus decreases biodiversity.
The abiotic conditions are generally influenced by the temperature.
The cooling process within the ice causes a decrease in the volume of the brine channels. The resulting removal of water from the brine causes higher salinities.
To investigate the impact of the temperature, the biodiversity index is plotted against the measurements within the corresponding ice layer of the Arctic and
decreasing biodiversity due to a temperature rise. These results dissent from the expected negative influence on the biodiversity, because only well adapted species are able to tolerate low temperatures. The findings can be explained by the influence of the water column on the investigated bottom-ice layer.
at the freezing point due to the nearby water and hence, is relatively stabil.
Therefore it can be concluded, that biodiversity of bottom ice communities is independent of the local air temperature at a certain time.
The temperature-dependent brine salinity of the Antarctic samples is shown in
due to higher salinities. This can be explained by the necessity for organisms to be well adapted to highly varying salinities by storing osmolytes such as
DMSP inside the cell.
The most important limiting factor for phytoplankton, as claimed by
inorganic nitrogen (DIN) and carbon (DIC), dissolved inorganic phosphorus
Silicate is essential for organisms, for instance diatoms, which incorporate it into their frustules. The maximum biomass of this often dominant class of sea-ice organisms is often controlled by silicate, but also the species composition
A common tool to estimate the role of the various nutrients is the comparison
composition depending on the irradiance, microbe reactions and the species composition, which adapt their biochemical compositions and nutrient-reserve
50 CHAPTER 4. DISCUSSION pools to the available nutrients. The Redfield ratio was also called an ”average
dominating organisms. Diatoms, for instance, have a higher N:P requirement than Phaeocystis and very low N:P ratios are used by N
2 fixers. This complex self-regulating process makes significant conclusions about the actual condition of marine or sea-ice organisms difficult.
Nevertheless, the results of this work will be compared concerning their nutrient composition.
The complexicity of the interaction between biogeochemical, biotic and abiotic factors are very complex, especially at this low number of samples that is why this discussion is only speculative.
The station 060923 has a very high silicate fraction, which allowed the silicate-dependent organisms further growth but also might indicate nitrogen or even phosphorus limitation and hence, affect the maximum abundance of all phytoplankton species.
The other diatom-dominated stations 061002 and 061008 show much lower
Si:N:P-ratios, but also low N:P-ratios. Low silicate values, maybe due to biological uptake, allow non-silicon-dependent organisms to compete increasingly successfully.
The N:P values of 2 or 3.5 are clearly below the expected Redfield ratio of
16 and the conclusion for these stations as well as for the station 060920, is therefore nitrogen and silicate limitation, also supported by the low measured absolute values. The nitrogen limitation is especially significant at the station
060920, even though similar low values were measured in Antarctic sea ice
In case of nutrient limitation, the two northernmost stations, 060920D and
060920F were expected to consist of a high ratio of heterotrophic organisms, which do not depend on dissolved nutrients. This assumption can be confirmed
which is lower than at the stations 061002 and 061008. Similar low values were
explained by local conditions and processes during ice formation.
The very low chlorophyll a value for the silicate-rich sample 060923 (2.7 µg l
) disagrees clearly with the high fraction of photosynthetic organisms as
temperature, which was lowest at this station. At very low mean temperatures, the density of the ice decreases resulting in smaller brine pockets and less available space for sympagic communities.
A calculated concentration of chlorophyll a per area would allow a more significant comparison. Without information about chlorophyll a values per area or the size of the brine pockets, two other possibilities have to take into account. The unexpected
4.3. PHYLOGENETIC TREES 51 low chlorophyll a per litre can be either explained by an overestimation of
by sea ice containing almost only dead bacillariophyta cells, which can also be detected by 18S PCR. It can therefore be suggested, that the nitrogen and phosphorus concentrations limited the photosynthetic active organisms, whereas heterotrophic species or nitrogen fixers developed increasingly resulting in a species composition as observed at station 060920.
In contrast, the stations 061002 and 061008 consist of high fractions of autotrophic organisms, but are also, compared to the Redfield ratio, nutrient
growth conditions for diatoms are assumed to be unfavourable leading to an increased fraction of N
2 fixers and heterotrophic organisms.
In a spatial point of view, a nutrient depletion from south to north becomes apparent.
This confirms the suggestion, that the sea ice at the southernmost stations is the youngest one and is therefore not nutrient depleted. Following the ocean currents in the Weddel Sea, sea ice drifts to the western part of the Weddel Sea and is then pushed to the north. Hence, organisms in the ice of station 060920 and 060923 differ from the other stations due to the lack of nutrients but also because of succession.
In case of the stations 060920D, 060920F and 060923, which are supposed to be formed at the same time due to its present position, the impact of abiotic factors on the species composition is obvious. The comparison of the thickness of the ice layer could lead to the assumption, that the stations 060920 are younger than 060923. But on the other hand, the lower nutrient supply of the stations 060920D and 060920F and the species composition would result in the opposite conclusion. A possible explanation has to be linked to the
on the ice structure and its abiotic conditions. This can be confirmed by the
Whereas the ice structure of station 060920 was defined to be granular, which means fast growing, all other stations consist of a columnar ice structure. As
leads to the inclusion of higher amounts of organic and anorganic material
(Gerhard Dieckmann, pers.comm.).
These favourable conditions may have caused a rapid phytoplankton growth and hence, a fast depletion of nutrients, especially silicate and nitrogen.
The resulting limitation of phytoplankton growth at the stations 060920D and 060920F allowed increased development of
Due to the slower ice formation at station 060923, a nutrient depletion and resulting change in biogeochemical processes did not occur yet, and hence,
52 CHAPTER 4. DISCUSSION species composition was still dominated by photosynthetically active algae.
The succession may have also slowed down because of low temperatures and low-light conditions due to a thicker ice layer. This presumed influence of the
showed there, that the air temperature during sampling does not influence the biodiversity, the mean temperature trend controls other abiotic factors and therefore also the species composition. The mean temperature of at least several days has to be observed to reason on the biodiversity.
An additional reason for higher nutrient concentrations at station 060923 can be flooding events due to a thicker snow layer. The weight of the snow layer push the ice under the water surface and therefore causes the input of nutrient-rich water which replenish the nutrient concentrations in the upper amounts of biomass due to higher irradiance and the interaction with the open water.
Larger openings and leads have to be considered in case of station
060923, because the ice floes were already broken by RV Polarstern.
A comparison between the two southernmost stations 061002 and 061008 shows very similar abiotic conditions except the brine salinity, which is significantly higher at station 061008.
Increased brine salinities in the bottom-ice layer generally indicate smaller volumes of the brine pockets and channels or higher gravity drainage from upper ice layers. The volume of the brine pockets limits the maximal size of organisms within the ice. Hence, the much higher fraction of metazoa in sample 061002 compared to station 061008 maybe enabled even multicellular organisms to penetrate into the bottom ice layers to graze on protozoans.
Another possible explanation for the difference in metazoan abundance bases on the used methods. During the 18S PCR, all appropriate DNA fragments, which were fixed on filters, are amplified.
If a multicellular organism was situated in the sample and not removed from the filter for physiological identifications, each single cell of this organism could be expressed by a sequenced clone. Finally, this would cause a high number of clones belonging to only one individuum. A quantification for multicellular organisms using 18S
CPGs, which means, that at least two organisms were included in station
The comparison of the Arctic and Antarctic results is difficult because of varying environmental conditions, but also sampling techniques and potential mistakes have to be taken into account.
The climate conditions in the Arctic during the winter 2005 to 2006 varied from earlier years.
The mean temperature in January was, for instance, about 10
°C higher than ever measured. The comparability of these data therefore has to be questioned in
4.3. PHYLOGENETIC TREES 53 general.
Arctic sea ice origins from a shallow, semi-closed fjord system with a comparably calm water surface in contrast to the pack-ice on the open ocean in the Weddel Sea. Also the close coast of Svalbard is likely to influence the species composition within the fast-ice. A major difference between Arctic and
A difference in Metazoan diversity between Arctic and Antarctic sea ice can be
species, Arctic Metazoa were represented by Nematoda and Turbellaria. Also
since Suessiales and Syndiniales only occured in Arctic samples.
The investigated Arctic sea ice (fast-ice) was thinner and younger than at the
Antarctic stations (pack-ice). The ice at the Arctic stations was not coloured due to algae growth as observed at the Antarctic stations.
The two Arctic samples were taken at the same position that is why the seasonal change in species compositon could be analyzed.
The calculated biodiversity index of both stations is higher compared to the Antarctic results
but also by a shorter influence of succession.
The low amount of diatoms in both Arctic samples is comparable with the northernmost Antarctic stations which were dominated by dinoflagellates due to nutrient depletion.
Unfortunately these assumptions can not be proved because no oceanographic or nutrient measurements were done in the Arctic.
Microscopic analyses of data, collected in March and April 2003 in the fast-ice
Results clearly show the dominance of diatoms in bottom communities, besides chrysophytes, cryptophytes and flagellates.
Despite low light conditions at the bottom of the ice due to thicker ice layers and more extreme abiotic conditions, mainly photosynthetic active species were found in contrast to the findings in the fjord ice of Van Mijenfjorden. Besides nutrients, which can not be compared here, the generic ice-class and conditions during formation are supposed to be the main influencing factors.
Rough water conditions on the open ocean cause mixing of the water column and allows therefore incorporation of non-motile cells into the ice. In contrast, in Van Mijenfjorden, cells sink during the dark period, if they are not attached to the ice during the autumn. The resulting extremely low concentration of cells in the water column combined with calm water in the fjord lead to only few incorporated cells during ice formation and hence, low numbers of large, non-motile cells in the bottom-ice communities.
Some of the species which were grouped to the CPG ”other stramenopiles”
54 CHAPTER 4. DISCUSSION and ”Fungi” still need to be identified. Saccharomyces sp. were also found in melt poles on Arctic sea ice (E. Helmke, pers.comm.), but additional fungi species are likely included.
The comparison between the results of the two dates in the beginning of the polar-day season are surprising. Instead of an increasing number of dinoflagellates, as observed in Antarctic samples, they are reduced and Metazoans become dominant instead. Again, caution is adviced to quantify these results.
As discussed for station 061002, each cell of this multicellular organisms can be expressed by another sequence and therefore mislead the actual distribution of
Metazoa. On the other hand, an increase of Metazoa after maximal primary production in spring is possible.
To quantify the distribution, additional analyses are necessary.
pack-ice in the Fram Strait. The opposite species composition was reported because Nematoda and Turbellaria were found in September whereas in March and April, Nauplii clearly dominated.
The difference can be explained by the varying conditions during sea-ice formation. Additionally, an interaction between the two sampling sites can be supposed: Nematoda and Turbellaria overwinter in calm areas and return during summer to the open ocean to graze phytoplankton blooms.
A more significant conclusion about development in Arctic sea-ice biodiversity can be obtained by analysing more stations, each composed of larger clone libraries. The time period of sampling need to be longer and should last more than one year.During the expedition ANT XXIII/7 of RV Polarstern , the same ice stations were observed by Maike Kramer (IPOE Kiel, Germany) and
Julia Hager (AWI Bremerhaven, Germany).
Microscopic analyses used by Julia Hager also show significant differences in the species composition and the number of empty frustules.
A first rough investigation revealed at the northermost station 060920 very high numbers of empty frustules and indefinable material. Using electron microscopy, various dinoflagellates were identified. The found diatoms were dominated by centric species, which in total confirms the results of the molecular biological approach.
In comparison, the southern station 061008 was clearly dominated by pennate diatoms, especially Fragilariopsis and Pseudonitzschia. But also, ciliats and dinoflagellates contribute to the higher biomass of this sample.
Metazoan distribution differed significantly between northernmost stations and station 061008 due to the influence of fast ice communities from
also varied from the other stations investigated by 18S PCR. For pro-
4.3. PHYLOGENETIC TREES 55 tozoans, this interaction is not assumed because a migration is not known and a distinct variation between this station and the closest station further east.
The combination of molecular biology and microscopic techniques can give extensive information about the sea ice biodiversity: the complete identification of species can be done by DNA-based methods whereas the quality and quantity of the cells can be described by microscopic observations.
Figure 4.1: Map of the western Weddel Sea showing the Larsen Polynia (dark region in the west) and the southern part of the course plot of RV Polarstern
Limitations of the method
The intention of this work was the identification of the sea ice biodiversity, but compared to former studies, it based on sequence analysis. In contrast to microscopic techniques, also very small organisms or even deformed or destroyed ones can be recognized. An optimized application could allow a fast and easy monitoring of the entire ecosystem. But until now, there are some open questions that is why a combination with other methods is recommended.
Major difficulties with the interpretation of 18S PCR occur because of multiple copies of the 18S rDNA gene in many species. The number of copies
56 CHAPTER 4. DISCUSSION
The used universal primers are supposed to allow amplification of all eucaryotic
18S rDNA fragments. They were developed and tested almost 20 years ago
only show one less represented class (Cryptophyta, Katja Metfies, pers.comm.) it is likely that the amplification efficiency varies. A combination of different primers and annealing temperatures would probably improve completeness.
18S PCR was used to analyze melted sea ice. This method gives sequence informations about all included 18S rDNA fragments, but it is not possible to distinguish between living and dead organisms, which can be important for the interpretation of the results. Also, the state of the organisms can not be described.
Incorrect conclusions can also occur because a high number of identical sequences are interpreted as a highly abundant class even though they origin from one single multicellular organism.
Conclusively, a quantification of the results gained only by 18S PCR is not possible. The method needs to be improved e.g. by excluding multicellular organisms and by the development of equations which calculate the number of
OTUs depending on the copy number of the 18S rDNA gene of the identified species. This will only be possible, if more 18S rDNA sequences were generated.
So far, a combination of different methods gives best results.
The eukaryotic biodiversity of Arctic and Antarctic sea ice was investigated by sequencing of 18S clone libraries. Phylogenetic trees, which originate from two ice cores from Van Mijenfjorden on Svalbard, based on sequences of 91 and 174 clones respectively.
Antarctic ice cores were taken from 5 different locations in the Weddel Sea, which varied in their location, sampling-date, generic ice-class, age of the ice and abiotic conditions. The appropriate number of sequenced clones differed between 69 and 273, which were all gained by the same approach to exclude the influence of methodical differences on the investigated biodiversity. The resulting phylogenetic trees therefore show the variation in species composition caused by environmental factors.
Biotic and abiotic factors were measured on RV Polarstern for the Antarctic samples and were finally related to the observed eukaryotic biodiversity. Main influencing factors, which caused a significant change in species composition, were assumed to be abiotic conditions during sea-ice formation and ageing. Depending on the efficiency of the incorporation process, the number of cells and the concentration of nutrients within the ice varies. The composition of organisms therefore ranges from a clear dominance of bacillariophyta in relatively young and nutrient richer samples to almost 90% dinoflagellates in older and nutrient depleted samples.
The conditions within the ice are additionally influenced by extreme air temperatures, resulting in higher salinities, less space and maybe interspecific competition. This means, an increase of successtion, caused by extreme environmental conditions, influences the biodiversity of sea ice. Changing temperatures can also control the grazing pressure because larger brine channels at higher temperatures enable metazoans to penetrate into the ice. This distinct variation in metazoan abundance was found in Arctic and Antarctic samples, but can also have methodical reasons.
The observed class of organisms as well as the main distribution is in accord with results of microscopic investigations of the same stations in Antarctica and
58 CHAPTER 5. CONCLUSION former expeditions in the Arctic.
The boundaries of the used method clearly lead to the conclusion, that a combination of different methods is necessary to obtain reliable and significant results.
The abundance of multiple copies of the 18S rDNA gen, for instance, makes a quantification difficult. A combination of different primers, which are tested for the actual number of known eukaryotic species, would help to ensure, that all eukaryotes are included in the results. Also, the design of new species- and class-specific primers would lead to a more complex picture of the biodiversity.
The used method can detect unknown species which show low similarity to the sequences in the database. Those sequences with very low similarity-values were also part of the investigated samples. The origin of these sequences needs to be observed by full-length sequencing of the 18S rDNA gen.
The used protocol and the facilities for high-throughput analysis make a higherscaled observation of the sea ice biodiversity possible. A comparison between different samples and an estimation of the impact of changing environmental conditions on the biodiversity of sea ice is possible, even though the method needs to be improved.
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The medium was sterilized for 20 min at 121
°C at a pressure of 2 bar.
1liter LB medium (liquid):
Tryptone (Sigma-Aldrich, Munich, Germany) yeast extract (Omnilab, Bremen, Germany)
NaCl (Sigma-Aldrich, Munich, Germany)
1liter LB medium (solid):
Tryptone (Sigma-Aldrich, Munich, Germany) yeast extract (Omnilab, Bremen, Germany)
(Sigma-Aldrich, Munich, Germany)
(Sigma-Aldrich, Munich, Germany)
Table B.1: Phylogenetic position of the Antarctic station 060923 following
BLAST search (best hit) and ARB; results are exemplary chosen from the complete list of OTUs
OTU CPG BLAST result
G11-002C11 Fragilariopsis sp.
G11-003D08 Fragilariopsis sp.
G11-001D05 Fragilariopsis sp.
G11-005E08 Fragilariopsis sp.
G11-004F08 Fragilariopsis sp.
G11-002B09 Fragilariopsis sp.
G11-002D08 Fragilariopsis sp.
G11-002A11 Fragilariopsis sp.
G11-004B12 Fragilariopsis sp.
G11-004H09 pennate diatoms Nitzschia sigma
G11-001B07 pennate diatoms Plathelminthes 100
OTU CPG BLAST result
G11-002H09 pennate diatoms Fragilariopsis cylindrus
G11-005B05 pennate diatoms Fragilariopsis cylindrus
G11-003E04 pennate diatoms Haslea sp.
G11-001A05 centric diatoms Amphora sp.
G11-005H08 centric diatoms centric diatoms centric diatoms
G11-004H12 centric diatoms
G11-004A12 centric diatoms
G11-003D12 centric diatoms centric diatoms
Fragilariopsis 100 cylindrus
100 coverage identity
68 APPENDIX B. PHYLOGENETIC ANALYSIS
Figure B.1: Phylogenetic tree showing OTUs of station 060920D. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
Figure B.2: Phylogenetic tree showing OTUs of station 060920F. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
70 APPENDIX B. PHYLOGENETIC ANALYSIS
Centric diatoms other stramenopiles
Figure B.3: Phylogenetic tree showing OTUs of station 060923. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
Figure B.4: Phylogenetic tree showing OTUs of station 061002. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
72 APPENDIX B. PHYLOGENETIC ANALYSIS
Figure B.5: Phylogenetic tree showing OTUs of station 061008. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
Figure B.6: Phylogenetic tree showing OTUs of station 060331. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
74 APPENDIX B. PHYLOGENETIC ANALYSIS
Figure B.7: Phylogenetic tree showing OTUs of station 060421. The OTUs are combined to CPGs (based on ARB treeing and the BLAST search)
Vielen lieben Dank
Ich m¨ Dr.
Michael Wettern bedanken, der
Ein ganz besonderer Dank geht an Andreas Krell, der mir bei meiner
Allhusen, Christiane Uhlig, Maddalena Bayer, Jessi Kegel, Nikolai Hoch,
Adnan Erdogan und Jan Strauß danken, die mich nicht nur bei der Arbeit danken.
Bei meinen Freunden in Braunschweig, Bremerhaven und dem Rest der
Ein besonders lieber Dank gilt auch meinem Freund Daniel, der mich und mir immer ein wichtiger Halt war.
Zuhilfenahme der angegebenen Quellen und Hilfsmittel angefertigt wurde.
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