i

Picoplankton Community Analysis along the Atlantic

Meridional Transect AMT22

Greta Reintjes

Master Thesis

Bremen 2013

Max Planck International Research School for Marine Microbiology

Max Planck Institute for Marine Microbiology

&

The University of Bremen

ii

Master Thesis proposed by Greta Reintjes

Bremen, March 2013

1. Examiner: Prof.Dr.Rudolf Amann

2. Examiner: PD. Dr.Bernhard Fuchs

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Affidavit

Statement

Hiermit versichere ich dass ich diese Arbeit selbständig verfasst und keine anderen als die

angegebenen Quellen und Hilfsmittel verwendet habe.

I hereby declare that the following master thesis has been written by myself and that no

sources have been used in the preparation of this thesis other than those referenced in the

thesis itself. All figures which are not self made but gathered from external sources are

marked as such.

Bremen, March 2013 ……………………….......…

Greta Reintjes

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Summary

The purpose of this study was to analyse the marine picoplankton community along the

Atlantic Meridional Transect AMT22. The diversity and abundance of dominant taxonomic

groups, potential biogeographical patterns in their distribution and their relation to

environmental parameters were investigated. We applied catalyzed reporter deposition-

fluorescence in situ hybridisation (CARD-FISH) and massive parallel tag sequencing of the

16S rRNA gene.

Firstly, the bacterioplanktonic diversity in distinct biogeographical provinces (Longhurst et al.,

2007) was analysed using tag sequencing. A high microbial diversity was found in all

provinces. Eight phyla represented 97% of the relative sequence abundance of all provinces.

The Proteobacteria, Cyanobacteria and Bacteroidetes have an average abundance of 39.5 ±

11.5, 28.5 ± 10.5% and 12 ± 7% respectively in all provinces. Other phyla Planctomycetes,

Chloroflexi, Deferribacteres and Planctomycetes made up < 10% of the total sequence

abundance. Of the Proteobacteria the alphaproteobacterial clade SAR11 made up nearly half

of the abundance with 41.5 ± 15.5%. The Gammaproteobacteria were the second most

abundance proteobacterial class with 39 ± 14%. A large portion of this (15 ± 5%) was made

up of the SAR86 clade.

Secondly the abundance and distribution of the dominate taxon along an Atlantic transect

was analysed. The absolute picoplankton abundance (cells ml-1) changed with latitude and

with depth and was positively correlated with high chlorophyll a concentrations (r2 0.76).

Bacteria dominate the surface waters of all provinces with 72 ± 16%. Archaea had an

absolute abundance of 6.1E+04 ± 2.1E+04 cells ml-1 throughout the water column. However,

their relative abundance showed a significant change from 1% at the surface to 40% at 150

m depth.

This study found that the taxonomic groups which dominate the sequence data could also be

found and enumerated using CARD-FISH. These groups made up a significant fraction of the

total cellular abundance of the bacterioplankton community. Only a few groups (SAR11,

SAR86 and Bacteroidetes) could be found at all latitudes and depths and although they were

ubiquitous in the sequencing data, their relative abundances did vary.

The diversity analysis showed that at different taxonomic level biogeographic distribution

patterns were present. They depended on distance (km) or environmental variation between

the provinces. The combined analysis of the diversity and abundance of microorganisms

based on biogeographic patterns resulted in a more accurate interpretation of the

biogeography of microorganisms in the Atlantic Ocean. Understanding the biogeography of

microorganisms is a key step in understanding the ecosystem function of specific microbial

assemblages.

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Contents

1. Introduction

2. Methods

2.1. Sampling

2.2. Classification of Biogeographical Provinces

2.3. Catalyzed Reporter Deposition-Fluorescence in situ Hybridisation (CARD-FISH) for

Planktonic Samples on Membrane Filters According to Pernthaler et al.(2004)

2.4. Statistical Analysis of Abundances

2.5. Sampling for Massive Parallel Tag Sequencing

2.6. DNA Extraction

2.7. Fusion Primer Design

2.7.1. Theoretical Background to PCR and Fusion Primers

2.7.2. Procedure

2.8. Roche 454 Pyro- Sequencing

2.9. Analysis of 454 Sequences

3. Results and Discussion

3.1. Classification of Ocean Biogeographic Provinces along the AMT22

3.2. Sequencing Statistics and Diversity Analysis

3.3. Relative Abundance of Phyla

3.4. Relative Abundance of Dominant Phyla

3.5. Absolute and Relative Abundances of Picoplankton Along the AMT22

3.6. Absolute and Relative Abundances of the Dominant Bacterial Taxon Along the

AMT22

3.6.1. Cyanobacteria

3.6.2. SAR11 and SAR86

3.6.3. Bacteroidetes

3.7. Other Groups of the Bacterioplankton Community

4. Conclusion

5. Acknowledgments

6. References

7. Appendices

6

Abbreviations

AAIW Antarctic Intermediate Water

AMT Atlantic Meridional Transect

BLAST Basic local alignment search tool

bp Basepair

CARD-FISH Catalysed Reporter Deposition-Fluorescence in situ

Hybridisation

CCD charge coupled device

CTD Conductivity/ Temperature/ Depth Profiler

DAPI 4',6-diamidino-2-phenylindole

DCM Deep Chlorophyll Maximum

DNA Deoxyribonucleic acid

dNTPs deoxyribonucleotide triphosphates

EB Elution buffer

EDTA Ethylene diamine tetra acetic acid

emPCR Emulsion Polymerase-Chain-Reaction

FISH Fluorescence in situ Hybridisation

HCL Hydrochloric Acid

NADR North Atlantic Drift

NAST North Atlantic Subtropical Gyre

NATR North Atlantic Tropical Gyre

NGS Next generation sequencing

nt Nucleotide

ODV Ocean Data View

OTU Operation Taxonomic Unit

PAST Palaeontological Statistics

PBS Phosphate Buffer Solution

PCR Polymerase-Chain-Reaction

PE Ethanol Wash Buffer

PTP Picotiterplate

QG Solubilisation and Binding Buffer

rDNA Ribosomal deoxyribonucleic acid

RNA Ribonucleic acid

rRNA Ribosomal ribonucleic acid

RRV Royal Research Vessel

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RT Room temperature

SATL South Atlantic Gyre

SDS Sodium dodecyl sulphate

SSTC South Atlantic Subtropical Gyre

SSU Small ribosomal subunit

TAE Tris-acetate-EDTA

TAQ Thermus aquaticus

Tris HCL Tris (hydroxymethyl) aminomethane Hydrochloric Acid

V3, V4 Hyper variable Region

WTRA Western Tropical Gyre

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Introduction

The Atlantic Meridional Transect (AMT) is a multidisciplinary ocean observatory program

started in 1995 (Robinson et al., 2006). Its aim is to understand the biological, chemical and

physical parameters of the Atlantic Ocean (www.amt-uk.org). The Atlantic Ocean is the

world’s second largest ocean and covers approximately 20 percent of the earth’s surface. It

is highly variable in its physical oceanography and biogeography. It is not homogeneous but

has varying nutrient concentrations partly due to seasonal mixing and heat stratification of

water masses. This heterogeneity causes variations in its primary production which is

dependent on solar irradiance and nutrient availability. Correspondingly it has areas of high

primary production in high temperate and equatorial regions, where seasonal mixing occurs,

and areas of low primary production in gyral regions where there is a high amount of thermal

stratification (Longhurst, 2007).

One of the major findings of the AMT was that the Atlantic Ocean can be sectioned into

provinces with characteristic biotic (phytoplankton and zooplankton) and abiotic features

(Longhurst et al., 1995). Longhurst et al., (1995) defined the distinct provinces based mainly

on the biodiversity and abundance of primary producers (phytoplankton). However marine

microbial communities are known to make up a considerable amount of biomass and

contribute significantly to the biogeochemistry of the oceans (Azam & Malfatti, 2007). They

are key organisms in the degradation of organic matter derived from primary production but

can also make up a significant fraction of the primary production (Wetz et al., 2008;

Zwirglmaier et al., 2008).

Marine microorganisms were long believed to have a ubiquitous distribution due to their

large population size and because normal geographical isolation is thought to have little

effect on their dispersal rates. This is especially true for the marine microorganisms which

find themselves in an environment where there are few geographical barriers and a

continuous circulation (Martiny et al., 2006). Previous studies have shown that the

composition of the Atlantic Ocean surface water bacterioplankton differs with latitude

(Schattenhofer et al., 2009). This has also been shown for other environments and a large

body of research now supports the idea that marine microorganisms are not randomly

distributed but exhibit biogeographical patterns (Fuhrman et al., 2008; Green & Bohannan,

2006; Lomolino et al., 2006; Martiny et al., 2006).

Currently there are three main hypotheses attempting to explain the biogeography of

microorganisms. The first is based on the Baas-Becking and Beijerinck hypothesis

“everything is everywhere: but the environment selects”. In this sense, if the environment

presented a suitable ecological niche then any microorganisms could exist there (O'Malley,

9

2007). This indicates that the biogeography of microorganisms reflects the influence of

environmental factors and variations. The second is based on spatial and temporal

variations due to historic events. This hypothesis explains biogeography based on speciation

events due to past environmental conditions or influences. Additionally the hypothesis

incorporates historic geographical isolation events. The third hypothesis is a mix of the two

previous. It bases the biogeography of microorganisms on environmental and historical

factors (Martiny et al., 2006). However, the attempts to define universal laws for the

distribution and biogeography of microorganisms are still far from finished.

This is due, in part, to the lack of understand in the factors that control the distribution and

diversity of microbes. The complexity of the microbial environment can be represented by an

n-dimensional hyperspace. With n being the number of possible environmental parameters

effecting a microorganism (Whittaker et al., 1973). However the classification of distinct

biogeographic provinces (Longhurst, 2007) was a key step in defining the environment to

which marine microorganisms are exposed and enable a more detailed analysis of the

biogeography of microorganisms in the Atlantic Ocean.

Another difficulty in the definition of the biogeography of microorganisms is the problem

associated with the microbial species definition. A large fraction of microbes are resistant to

cultivation and due to their lack of distinguishing features and small size are hard to

differentiate. Microbiologists alternatively use molecular tool to distinguish a microbial

species. The development of cultivation independent techniques such as the polymerase

chain reaction (PCR) and DNA sequencing allows for the identification of microorganisms

directly from the environment without the need for isolation. The main method associated

with the definition of a microbial species is the use of universal genes for a phylogenetic

based taxonomic classification. The 16S ribosomal DNA (rDNA) gene is currently the most

used gene for phylogenetic based classification. The 16S rDNA gene has a ubiquitous

presence in prokaryotic and eukaryotic cells, has a relative slow evolution, and functional

homology (Nübel et al., 1997) making it ideal for phylogenetic comparisons. The

comparative analysis of the 16S rDNA gene is a well established approach for the

phylogenetic classification of Bacteria and Archaea, with extensive databases available

(Huse et al., 2008; Tamaki et al., 2011; Woese, 1987; Zuckerkandl & Pauling, 1965).

The DNA based phylogenetic classification has been further enhanced by the development

of next generation sequencing techniques (NGS) (Frias-Lopez et al., 2008; Huse et al.,

2008). The combination of PCR with NGS yields microbial diversity data up to three orders

of magnitudes greater than previous methods (Ghiglione et al., 2012; Kirchman et al., 2010).

The massive parallel sequencing of the 16s rDNA to characterise a microbial population was

initiated by Sogin et al., (2006). They reported bacterial communities with up to two orders of

magnitude higher complexity than ever reported. Additionally the barcoding of samples

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enables the simultaneous sequencing of several samples in single sequencing run (Tamaki

et al., 2011) making it cost effective.

The sequencing of the 16s rRNA gene has additionally allowed for the identification of

signature sequences which are unique for different taxonomic groups of microorganisms.

These signature sequences can be targeted by complimentary oligonucleotides (probes) for

identification purposes. Fluorescence in situ hybridisation (FISH) uses probes which are

labelled with a fluorochrome allowing for, with the use of fluorescent microscopy, a

phylogenetic staining (Amann et al., 2001; DeLong et al., 1989). Using this method, specific

bacterial taxonomic groups can be targeted and enumerated in their environment. The

application of this method to analyse the abundance of specific microbial groups has given

new insight into the relative abundance of specific taxonomic groups in different habitats

(Grossart et al., 2005; Morris et al., 2012; Pérez et al., 2005; Thiele et al., 2012).

With the development of new methods our understanding of the diversity and abundance of

marine microorganisms has significantly increased. This is important because they dominate

the marine environment in terms of abundance, diversity and metabolic activates (Azam &

Malfatti, 2007).Additionally they are key mediators of the biogeochemical cycling of elements

in the ocean (Arrigo, 2004; Falkowski et al., 2008).

The application of these molecular techniques has given a more accurate insight into

microbial community diversities which can now be applied to analysis of biogeography.

In this study we applied massive parallel tag sequencing of the 16S rDNA gene and catalytic

reporter deposition-fluorescence in situ hybridisation (CARD-FISH) to analyse the microbial

community composition of the Atlantic Ocean. Additionally we used biotic, environmental

and geographical similarity matrixes to analyse the biogeography of the dominant taxonomic

groups (Martiny et al., 2006).

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2. Methods

2.1 Sampling

During the Atlantic Meridional Transect AMT22 from 50°N to 50°S, upon the RRV James

Cook (Southampton, UK, to Punta Arenas, Chile, 10 Oct to 24 Nov 2012), seawater samples

were taken using a Sea Bird CTD (Sea Bird Electronics Inc., U.S.A). The CTD was deployed

twice daily between 20 and 400 m water depth at predawn and solar noon intervals. For all

74 sampling stations (Figure 1) three individual depths were sampled (surface; 20 m, DCM;

various and mesopelagic; 150 m). If the DCM was 150 m or deeper, the mesopelagic

sample was taken from > 200 m. From each sample 100 ml of seawater was fixed in 1%

formaldehyde for 1 hr at RT. Subsequently, 20 ml subsamples were filtered (200 mbar) onto

47 mm polycarbonate filters with a 0.2 µm pore size in triplicates. These filters were then

stored at -20°C until further analysis.

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Figure 1:Map of the 74 sampling points along the AMT22. The individual dot colours indicate the biogeographic provinces in which the sample was taken. Red: North Atlantic Drift (NADR), Orange: North Atlantic Subtropical Gyre (NAST), Yellow: North Atlantic Tropical Gyre (NATR), Green: western Tropical Gyre (WTRA), White: South Atlantic Gyre (SATL), Pink: South Atlantic Subtropical Gyre (SSTC) (Longhurst et al., 1995). The map colours indicate the average chlorophyll a concentrations (mg m

-3) during the AMT22 time period

(www.oceancolor.gstc.nansa.gov). Red circles indicate sites analysis using pyro- sequencing.

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2.2 Classification of Biogeographic Provinces

The AMT22 passed through six ocean provinces the North Atlantic Drift (NADR), North

Atlantic Subtropical Gyre (NAST), North Atlantic Tropical Gyre (NATR), Western Tropical

Gyre (WTRA), South Atlantic Gyre (SATL), and the South Atlantic Subtropical Gyre (SSTC)

according to(Longhurst, 2007). The ocean biogeographical provinces were identified using

their physical, chemical and biological characteristics. These were measured at every CTD

sampling station from 0 m to 500 m depth. Temperature (°C) was measured using a SEA-

BIRD 3 premium temperature sensor. Dissolved oxygen (ml l-1) was measured using the

Sea-Bird 43 dissolved oxygen sensor and calibrated against Winkler titration measurements

from 9 samples collected from the pre-dawn CTD. Conductivity (S m-1) was measured using

a Sea-Bird4 conductivity sensor. Fluorescence (mg m-3) was measured using a CTG FAST

track Fast Repetition Rate fluorimeter and calibrated against extracted chlorophyll-a

measurements made on seawater samples collected from 9 depths at each station.

Pressure (mbar) was measured using a Digiquartz pressure sensor suspended below the

CTD. Salinity (PSU) was measured using a Guildline Autosal 8400B salinometer and

calibrated against bench salinometer measurements from 4 samples collected from each

cast.

2.3 Catalyzed Reporter Deposition-Fluorescence in situ Hybridisation

(CARD-FISH) for planktonic samples on membrane filters according to

(Pernthaler et al., 2004).

Figure 2: Schematic representation of CARD-FISH method from Arb-Silva (Quast et al., 2013a)

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All stations and depths were analysed using CARD-FISH (Figure 2). The filters were first

embedded in 0.1 % LE agarose (Biozym Scientific, Germany) and subsequently

permeabilised using lysozyme (10 mg ml-1 in 0.05 M EDTA, pH 8.0; 0.1 M Tris-HCL, pH 8.0).

Next endogenous peroxidases were inactivated by incubating the filters in 0.01 M HCL for 15

min. Then the samples were hybridised with 16s rRNA probes chosen based on previous

literature and the study by (Schattenhofer et al., 2009) (Table 1). Hybridisation was carried

out in humidity chambers at 46 °C for 2.5 hrs. The hybridisation buffer (formamide

concentration varied according to probe used, see Appendix 1) was mixed with a probe

concentration of 8.42 ng µl-1. After hybridisation the filters were washed in pre heated (48 °C)

wash buffer for 10 min at 48 °C and then incubated in 1 X PBS for 15 min at RT. Next the

amplification was carried out using an amplification buffer H2O2 solution at a ratio of 100:1

with 1 mg ml-1 fluorescently labelled tyramide (Appendix 1.). Amplification was carried out at

46 °C for 45 min. After the CARD-FISH process the filters were counter stained with DAPI

and mounted using a citiflour/vector shield (4:1) mounting solution. CARD-FISH and DAPI

staining the cells were visualised and enumerated on a Zeiss Axioskop 2 motplus

fluorescent microscope.

Table 1: List of probes with sequence and specific formamide (FA) concentration applied during this study.

Probe Target organisms Sequence (5′→3′) FA

(%)

Reference

Arch915 Almost all Archaea GTGCTCCCCCGCCAATTCCT 35 (Amann et al.,

1990)

Cren554 Crenarchaeota marine

group I

TTAGGCCCAATAATCMTCCT 0 (Massana et

al., 1997)

Eury806 Euryarchaeota marine

group II

CACAGCGTTTACACCTAG 0 (Teira et al.,

2004)

Eub338 I-III Almost all Bacteria GCWGCCWCCCGTAGGWGT 35 (Amann et al.,

1990)

Non338 Control ACTCCTACGGGAGGCAGC 35 (Wallner et al.,

2005)

Gam42a γ-Subgroup of

Proteobacteria

GCCTTCCCACATCGTTT 35 (Manz et al.,

1992)

Ros537 Roseobacter-clade CAACGCTAACCCCCTCC 35 (Eilers et al.,

2001)

SAR86-1249 SAR86 clade TTAGCGTCCGTCTGTAT 35 (Eilers et al.,

2000)

SAR86-1245-

h3

Helper to SAR86 1245 GGATTRGCACCACCTCGCGGC 35 (Zubkov et al.,

2001)

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SAR86-1245-

h5

Helper to SAR86 1245 CCATTGTAGCACGTGTGTAGC 35 (Zubkov et al.,

2001)

CF319a most Flavobacteria, some

Bacteroidetes, some

Sphingobacteria

TGGTCCGTGTCTCAGTAC 35 (Manz et al.,

1996)

SAR11 MIX SAR11 clade GGACCTTCTTATTCGGGT 25 (Morris et al.,

2002)

Pro405 Prochlorococcus AGAGGCCTTCGTCCCTCA 40 (West et al.,

2001)

SYN405 Synechococcus AGAGGCCTTCATCCCTCA 40 (West et al.,

2001)

SAR202–

312R

SAR202 clade TGTCTCAGTCCCCCTCTG 40 (Morris et al.,

2002)

SAR324-1412 SAR324 clade GCCCCTGTCAACTCCCAT 35 (Schattenhofer

et al., 2009)

POL740 Polaribacter CCCTCAGCGTCAGTACATACGT 35 (Malmstrom et

al., 2004)

EUK516 Eukarya ACCAGACTTGCCCTCC

0 (Amann et al.,

1990)

2.4 Statistical Analysis of Abundances

Absolute (cell ml-1) and relative cell abundances (% of total DAPI)were enumerated at every

sampling point for all probes. The results were graphed as contours plots using the ocean

data view 4 (ODV) software (www.odv.awi.de). The relative abundance of bacterial groups in

biogeographical provinces were visualised with pie charts using Sigmaplot

(www.sigmaplot.co.uk). Additionally the relative abundance data was correlated to physical

parameters using Spearman Rank Order correlations. This correlation was applied because

it does not define variable as dependent or independent and measure the strength of the

association between all variables. The correlation results are indicated with the correlation

coefficient r, which indicates the strength of the correlation (-1 strong negative correlation to

+1 strong positive correlation).

2.5 Sampling for Massive Parallel Tag Sequencing

Large volumes of seawater (10 - 45 l) were sampled from 20 m depth at every solar noon

station for DNA analysis. The water was sequentially filtrated onto 142 mm polycarbonate

filters with pore sizes of 10 µm, 3 µm and 0.2 µm. These filters were stored at -80 °C until

further analysis. The samples analysed by pyro- sequencing are indicated with red circles in

Figure 1.

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2.6 DNA Extraction

Microbial DNA was extraction using the MoBio Ultra Clean Soil DNA Extraction Kit (MoBio

Laboratories, Inc., Carlsbad, CA,) as recommended by the manufacturer with the alteration

that instead of soil a fixed size (150mm x 250mm) polycarbonate filter piece was directly

added to the Bead Solution Tubes. The method comprise of an initial chemical lyses of cells

using an SDS based solution and the subsequent mechanical lyses of cells. SDS is a

detergent which aids the breakdown of cell membranes specifically fatty acids and lipids.

The mechanical lysis was done by vortexing the cells in a bead solution. After cell lyses

impurities such as proteins and salts, which would interfere with further analysis, were

removed by precipitation and centrifugation steps. The DNA was then bond to a silica

membrane within a column in the presence of a high salt solution. Further washing to

remove salts was done using > 70% ethanol to avoid any elution of the DNA. Finally the

DNA was eluted using a Tris-HCL buffer, pH 8.0.

2.7 Fusion Primer Design

2.7.1 Theoretical Background to PCR and Fusion Primers

The polymerase chain reaction (PCR) enables the exponential amplification of a targeted

strand of DNA. In the reaction the heat stable polymerase (Taq), derived from the bacterium

Thermus aquaticus, is used to amplify single stranded DNA fragments with a primer, short

complementary oligonucleotide DNA fragment (Innis et al., 1988). In a series of temperature

cycles the DNA is denatured, the primer is annealed and elongation occurs to create a

complimentary DNA strand of the targeted DNA sequence (Schochetman et al., 1988).

Gene specific primers consist of a short oligonucleotide fragment (20 bp length)

complimentary to the targeted genes DNA sequence. In this study “fusion primers” were

used to amplify selected regions of bacterial SSU rDNA. Our fusion primers had a Sfi-A or B

site and a barcode sequence attached to the 5’- prime end of the gene specific primer

(Figure 3). After PCR the Sfi-A or B site is digested using the Sfil enzyme to generate a 3-

base single stranded overhang to which the 454 sequencing adaptors are ligated. This

allows for direct sequencing of the PCR product. The barcode consists of a unique 6

nucleotide sequence which allows for the pooling of multiple PCR products onto one

sequence run (Binladen et al., 2007).

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Figure 3: Schematic representation of “Fusion Primers” layout. The Sif A and B are located on the 5’ end indicated in blue. The gene specific primer is on the 3’ end indicated in red. In the centre is a barcode (yellow).

The fusion primers used in this study targeted the V3 – V4 region of the 16S rDNA of

Bacteria and Archaea (Table 2). The comparative sequence analysis of the whole 16S rRNA

or hyper variable regions such as V3 or V6 are well established approach for the

phylogenetic classification of Bacteria and Archaea, with extensive databases available

(Huse et al., 2008; Tamaki et al., 2011; Woese, 1987). The primers used in this study were

tested and evaluated elsewhere (Klindworth et al., 2012).

Together with gene specific primers, phusion polymerase (New England, Bioloabs, UK) was

used to amplify the DNA. Phusion polymerase is a high fidelity polymerase (Frey &

Suppman, 1995). It has high speed and yield amplification with an error rate of 4.4 X 10-7

errors per base pair, which is 50 times lower than the regular Taq polymerase. This is due to

the 3´- 5´ exonuclease or “proofreading” activity, which results in a 3-fold increase in the

fidelity of DNA synthesis (Li et al., 2006).

Table 2:Sequence of Primers applied in this study, primers were names after (Alm et al., 1996)

Primer Name Sequence 5’ – 3’ Fragment

size (bp)

Annealing

temperature

(°C)

16S_D_BAC_0341_A_s CCTACGGGNGGCWGCAG 444 55

16S_D_BAC_0785_A_a ACTACHVGGGTATCTAATCC 444 55

16S_D_ARCH_0340_A_s CCCTACGGGGYGCASCAG 660 57

16S_D_ARCH_1000_A_a GGCCATGCACCWCCTCTC 660 57

2.7.2 Procedure

PCR was carried out in a total volume of 20 µl using the primers indicated inTable 2.The

master mix components and concentrations are shown in Table 3. The master mix and

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DNAwas incubated in a thermocycler (Mastercycler Tm gradient, Eppendorf, Hamburg,

Germany) with the program indicated inTable 3. Subsequently, the PCR products were

visualized by gel electrophoresis with a 1% LE agarose (Biozyme, Oldendorf, Germany)

dissolved in 100 ml 1X TAE Buffer (For 2 l; 50 X TAE Buffer; 484 g 2 M Tris, 114.2 ml glacial

acetic acid and 200 ml 0.5 M EDTA pH 8.0). A total of 19 µl of the PCR product was mixed

with 5 µl 6 X loading dye (30%Glycerol, 0.25% Bromophenol blue in Milli-Q® water) and

loaded onto the gel. 5 µlpeqGOLD DNA ladder (PEQLAB Biotechnologie GMBH, Erlangen,

Germany) was used as a standard. Electrophoresis was carried out for 1 hr at 100 V. The

gel was stained for 30 min in ethidium bromide nd visualised using a documentation system

(Vilber-Lourmat, Eberhardzell, Germany).

Table 3:PCR reaction mix and thermoycler conditions applied in this study. X is the temperature used for annealing which varied according to the primers used.

PCR Reaction Thermocycler conditions

Molecular grade H2O

5 x HF buffer

dNTP’s mix (2,5 mM)

Forward Primer ( 100 µM)

Reverse Primer (100 µM)

Phusion Polymerase (0,02 units µl-1

)

DNA (10 ngµL-1

)

DMSO

12 µl

4 µl

1.6 µl

0.4 µl

0.4 µl

0.2 µl

1 µl

0.3 µl

1 cycle:

94°C for 5 min

35 cycles:

94°C for 30 sec

X °C for 30 sec

72°C for 2 min

1 cycle:

72°C for 10 min

Amplicon bands were visualized using a transilluminator DR-45M (Clare Chemical

Research, Göttingen, Germany) and cut out with a sterile scalpel. The cut out gel slices were

transferred in pre weighed 1.5 ml tubes and the DNA was purified using the Qiagen

MinElute® kit (Qiagen, Hilden, Germany). Briefly the weight of the slice was determined and

three volumes of QG buffer were added to one volume gel. The mix was incubated at 50 °C

for 10 min. Then one volume isopropanol was added and mixed by inverting. This was

applied to a MinElute spin column and centrifuged at 12,000 x g for 1 min. The flow through

was discarded and 500 µl QG buffer was added to the column followed by centrifugation at

13,200 x g for 1 min. Again the flow through was discarded and 750 µl of PE buffer was

added and this was centrifugation at 12,000 x g for 1 min. The column was placed in a new

collection tube and the wash step was repeated with 96% ethanol. Finally the column was

place in a new clean 1.5 ml tube and 10 µl EB buffer was added to the centre of the

19

membrane without touching the wall of the column and incubated for 5 min at RT. The DNA

was eluted by centrifugation at 12,000 x g for 1 min yielding 8 - 9 µl purified DNA.

After purification the PCR products were pooled into libraries containing several samples but

only one replicate of each barcode. The libraries had a minimum DNA concentration of 1 µg

DNA which was measure using a Qubit assay (Invitrogen, Darmstadt, Germany). The

libraries were then sent to the Max-Planck Institute for Plant Genomics in Cologne, for

sequencing on a ROCHE 454 titanium FLX (ROCHE, Germany).

2.8 ROCHE 454 Pyro- Sequencing

The Roche 454 sequencing approach is a sequencing by synthesis method. The DNA used

during sequencing can be genomic DNA fragments or amplicons. The DNA with attached

sequence adaptors is immobilized on capture beads. One piece of DNA is immobilized on

one capture bead (Margulies et al., 2005). These DNA fragments are them amplified on the

bead in an emulsion PCR (emPCR) reaction (Roche, 2010c). After the emPCR a single

capture bead will have multiple copied of a single fragment of DNA attached to it. Now the

beads are transferred to a picotiter plate (PTP). The PTP has a very small valve diameter

(44 µm) allowing for only one capture bead per valve (Dressman et al., 2003; Ghadessy et

al., 2001) (Figure 4 A-F). Then enzymes (polymerase, apyrase, ATP sulfuryase, luciferase)

are added to each valve for the sequencing reaction. The DNA fragment is synthesised

using a polymerase. The PTP is sequentially flooded with one of the four

deoxyribonucleotide triphosphates (dNTPs) (Margulies et al., 2005), if a dNTP is

incorporated then pyrophosphate (PPi) is released. The ATP sulfurase quantitatively

converts the PPi to ATP. When ATP is formed a light signal is produced by the luciferase

catalysed reaction. This light is detected by a charge coupled device (CCD) camera and

integrated into a pyrogram. The process continues with the addition of the next dNTP and a

complementary DNA strand is synthesised. The sequence of which can be deduced from the

pyrogram signal intensities (Figure 4 G). This is done for each valves and each DNA

fragment which is bound to the initial bead. This allows for a high number of individual

sequencing reactions to be performed simultaneously(Roche, 2010d).

20

(G)

Figure 4 A-G :Principle of 454-Sequencing, images modified from (Mardis, 2008). (A) Top Left: The DNA is fragmented and adaptors are added to the 5’ and 3’ ends. (B) The DNA fragment is incorporated into a bead, then the beads are captured in droplets of the oil from the emulsion PCR mixture. During the emPCR the DNA on the individual beads is amplified exponentially resulting in millions of copies of a single DNA fragment on every bead. (C) The beads are purified out of the emPCR mixture and beads are deposited into valves of the PTP. (D) Additional enzyme beads are added to each valve. (E) Microscope picture of emPCR process showing empty droplets and droplets with beads. The small arrow is indicated a bead and the large arrow a droplet. (F) Scanning electron microscope picture of PTP valves. (G)During sequencing the DNA-polymerase incorporates the complementary nucleotide and sets free inorganic pyrophosphate. The pyrophosphate is converted by the action of sulfurylase to ATP. During the action of luciferase energy in form of ATP is uses to create a flash of light. The light is detected by a CCD Camera and the Nucleotide sequence is given out as a pyrogram by the software. Apyrase degrades surplus molecules of ATP and e.g. dGTP before the next nucleotide is washed over the picotiter plate. Images modified from (Fabrice & Didier, 2009).

2.9 Analysis of 454 Sequences

The sequence reads from the 454 sequencer were further processed using the

bioinformatics pipeline of the SILVA project (Quast et al., 2013b). This involved quality

controls for sequence length (> 200 bp) and the presences of ambiguities (< 2%) and

homopoymers (<2%). All sequences which did not meeting these criteria were removed and

not considered in further analysis. The remaining reads were aligned against the SSU rRNA

seed of the SILVA database release 108 (http://www.arb-

silva.de/documentation/background/release-108). Reads which were not aligned were not

further considered in this study. This allowed for the removal of putative non SSU rRNA

gene reads and other artefacts. The remaining reads were dereplicated, clustered and

classified. Dereplication was done with cd-hit-est of the cd-hit package 3.1.2

(http://www.bioinformatics.org/cd-hit) using an identity criterion of 1.00 and a word size of 8.

21

The reads remaining after dereplication were clustered with cd-hit-est using an identity

criterion of 0.98. The longest read of each cluster was used as a reference for taxonomic

classification. The classification was done by a local BLAST search against the SILVA

SSURef 108 NR database (http://www.arb-silva.de/projects/ssu-ref-nr/) using blast-2.2.22+

(http://blast.ncbi.nlm.nih.gov/Blast.cgi) with standard settings. The obtained full SILVA

taxonomic path of the best blast hit was assigned to the read when the values for

(% sequence identity + %alignment coverage)/2

were at least 93.0. Finally the taxonomic path of each cluster reference read was mapped

onto the other reads in the cluster and the corresponding replicates. This gave (semi-)

quantitative information (number of individual reads representing in a taxonomic pool) on the

composition of the original PCR amplicon pool. The relative abundance of sequences

belonging to a taxonomic level was represented in 100% stack column graphs. The analysis

of ecological distance between the samples was computed with a Bray-Curtis similarity

analysis with 1000 times bootstrapping in the statistical software package

PASThttp://folk.uio.no/ohammer/past/).

Richness and diversity analyses were done using OTU (operational taxonomic unit, from

98% similarity clustering of sequences) as the basic unit. Due to the variability in the

bacterial species definition and the bias applied to the method by PCR direct abundance

analysis of the sequences was not used to do diversity analysis. Rarefraction curves were

calculated for each site based on the OTU number.

22

3. Results & Discussion

3.1 Classification of Ocean Biogeographic Provinces along the AMT22

Oceanic biogeographic provinces are dynamic with varying boundary locations (Oliver &

Irwin, 2008). This is due to the variation of oceanographic and atmospheric pressures acting

on the oceans at any given time. Biogeographic provinces are classified based on their

physical, chemical and biological parameters. The AMT22 covered 6 biogeographic

provinces according to their definition by Longhurst, (2007). The boundary of each province

was determined using the change in temperature (°C), salinity (PSU), oxygen (µmol l-1) and

chlorophyll a (mg m-3) shown in Figure 5 and Figure 6.

Figure 5: Temperature (°C) and salinity (PSU) section plot along the AMT22 by latitude (50°N– 45°S).

23

Figure 6: Oxygen concentration and chlorophyll a (calibrated against Winkler titrations) section plot along the AMT22 by latitude (50 °N – 45 °S).

The first province crossed during the cruise was the North Atlantic Drift (NADR) extending

from 50°N to 43°N. It had constant temperatures of 10 – 15 °C along a vertical and latitudinal

gradient. The salinity had a constant value of 35.5 PSU. Oxygen had a high concentration in

the surface region (260 - 270 µmol l-1) but stayed at a consistent 240 µmol l-1with depth. High

surface chlorophyll a values of 1 mg m-3 were measured which decreased with depth.

Next the North Atlantic Subtropical Gyre (NAST), which covered latitude from 43°N to 32°N,

was crossed. The surface water temperature was 20 °C which decrease rapidly to 15 °C by

100 m. Salinity increased to 36.5 PSU along a latitudinal gradient and was highest in surface

waters at 32°N. Oxygen concentrations were at a maximum of 240 µmol l-1 at 100 m. The

highest chlorophyll a concentrations were measured at 100 m depth (1 – 1.2 mg m-3). The

area of maximum chlorophyll a deepened along a latitudinal gradient (50 to 150 m).

The next province transverse during the AMT22 was the North Atlantic Tropical Gyre

(NATR) from 32°N to 17°N. It was defined based on a characteristic increase in water

temperature to 25 °C at the surface. The temperature decreased with depth and gradually

reaching 15 °C at 400 m. A high broad band of salinity (36 PSU) is also characteristic of the

province and was observed during this study. Oxygen concentrations had a maximum of 230

µmol l-1 at a depth of 100 to 200 m throughout the province. The chlorophyll a maximum (>

1mg m-3) was at 120 m depth. The Western Tropical Gyral (WTRA) province spanned from

24

17 °N to 8 °S. It had high surface temperatures of 25 - 27 °C, which were the highest

seawater temperatures observed during this study. Temperature decreased quickly with

depth to 15 °C within 200 m. Salinity was highest at 70 m depth (36 PSU) and decreased to

35 PSU above and below. Oxygen was highest at the surface (200 µmol l-1) but decrease

considerably with depth (100 µmol l-1). There was a wide band of chlorophyll a (0.5 – 1.5 mg

m-3) between 70 – 150 m depth.

The last two provinces transverse during the AMT22 were the South Atlantic Gyre (SATL)

and the South Atlantic Subtropical Gyral (SSTC) province. The SATL was the largest

province and spanned from 8 °S to 35 °S. It had surface temperatures of 20 -25 °C which

decreased slowly with depth. Salinity was high (37 PSU) at the surface to 200 m but

decreased below that. The oxygen concentration was 220 µmol l-1 throughout the water

column with a slight decrease with depth. Chlorophyll a was low with a maximum of < 0.5mg

m-3 between 150 – 200 m. The most rapid change in the physical parameters was observed

during the transition between the SATL and the SSTC provinces. The SSTC is defined by

characteristic steep gradients in temperature and salinity. These were also observed during

the AMT22 where surface temperatures drop to 15 °C and decreased even further to 5 °C by

120 m depth. These were the lowest temperatures measured along the AMT22. The same

rapid change in salinity was observed with the lowest salinity concentrations of the cruise

being observe (34.5 PSU) in this province. A high oxygen concentration was observed

throughout the water column (270 µmol l-1). In the surface waters of the SSTC the highest

chlorophyll a concentrations (> 1.5mg m-3) were measured between 0 and 70 m.

The NADR and SSTC provinces showed constant temperature and salinity values

throughout the water column, indicating a deep mixing process. Deep mixing increases the

nutrient availability in surface waters and results in high primary productivity (Longhurst,

2007). This was also observed during this study by the high chlorophyll a and oxygen values

in the water column, corresponding to oxygen production by photosynthesis.

In the central provinces (NAST, NATR, WTRA, SATL) a thermocline was observed. A

thermocline is an area in the water column with an abrupt change in temperature. Often

associated with a thermocline is a deep chlorophyll maximum (DCM) layer (Mann & Lazier,

1996). This was also observed in this study through the deepening of the chlorophyll a layer

(Figure 6). A DCM layer forms because a thermocline acts as a barrier trapping nutrients in

deeper waters. Phototrophic organisms aggregate near the thermocline to obtain essential

nutrients required for photosynthesis. In the NAST and southern SATL regions the depth of

the thermocline varied. The formation of a thermocline is dependent on the heating of

surface waters by solar irradiance. When the solar irradiance decreases sea surface

temperatures decrease and the thermocline diminishes. Subsequently mixing can occur and

25

nutrients are made available in surface waters allowing for primary production (Mann &

Lazier, 1996).

The gyral provinces (NATR and SATL) have deeper warm water and salinity layers due to

the down welling of water from the Ekman transport. The Ekman transport is the net motion

of fluid resulting from the balance of the Coriolis force and wind turbulence. It causes a

convergence of water in the gyre regions and the subsequent down welling due to the

excess mass of water converged (Mann & Lazier, 1996). This down welling causes a

depression in the thermocline which is usually deeper in the SATL province (Maranön et al.,

2000). The high surface salinity observed in the gyral regions is due to the characterised net

evaporation at these latitudes (Robinson et al., 2006; Weisse & Storch, 2010).

The WTRA province is characterised by high precipitation rates (Longhurst et al 2007),

which explained the low salinity values measured at the surface during this study. The

Ekman transport also acts on this region but causes an upwelling of Antarctic Intermediate

Water (AAIW). This was observed by the influx of low oxygen waters from depth. These

waters are low in oxygen due to their prolonged absence from the atmosphere (Robinson et

al., 2006).

3.2 Sequencing Statistics and Diversity Analysis

The 16S rRNA hypervariable regions V3-V4 was amplified because it has previously been

shown to be 99% accurate when classified to genus level (Huse et al., 2008). The six

sampling sites are referred to by the specific name of the province in which they were taken.

A large amount of sequences were produced from a single sequencing run (summary

statistics are shown in Table 4). Sample richness varied from 5806 to 2276 OTUs.

Rarefraction analysis of the bacterial diversity (Appendix 2) indicated that only part of the

total richness of each site was observed in our samples although previous studies have

indicated an asymptotic curve could be obtained for Atlantic planktonic samples (Friedline et

al., 2012).

26

Table 4: Sequencing statistics for 6 bacterial communities along the AMT22. Sequences indicates the total number of sequences obtained for a specific sample. Checked sequences are sequences which passed the quality controls. Clustering of sequences into OTUs was done using cd-hit-est with a criterion of 0.98. Replicates indicate sequences with 100% identity.

Site /Province NADR NAST NTRA WTRA SATL SSTC

Statistics

Number of sequences 29505 17134 25429 15662 18310 20912

Average length (bp) 458 510 452 458 458 458

Checked sequences 18633 10409 14147 9472 11785 14465

Clusters (98%) (OTUs) 5806 2276 2956 3227 3504 3557

Replicates 5027 4419 8294 2932 2984 3041

The sequencing resulted in 22583.5 ± 6921.5 sequences reads per site which fell into 4041

± 1765 OTUs (clustered at 98% identity). The average sequence length was 465 bp covering

the complete 16S rRNA gene hypervariable regions V3 and V4. The variability in number of

sequences and number of OTU was taken into account in the diversity analysis.

Microbial community diversity indices for all 6 sites based on a 98% sequence similarity cut

off (OTU) showed high microbial diversity (Table 5). There was no significant spatial pattern

observed in the diversity analysis. However the highest bacterial richness (number of OTUs)

and diversity (Shannon’s Index) were found in the NADR and SSTC provinces. These

provinces have characteristic high primary production associated with a large amount of

organic matter production which could result in an increase in the diversity of

microorganisms (Teeling et al., 2012). Simpson’s dominance index indicated that all sites

were dominated by specific organisms. This correlated to the evenness values which were

low indicating that there were rare and abundance organisms present.

Table 5: Diversity indices results for 6 bacterial communities along the AMT22. Individual OTU indicated the number of OTUs present at each site. Dominance was calculated using the 1+ Simpson’s index.

Diversity Indices NADR NAST NTRA WTRA SATL SSTC

Individual OTUs 5806 2276 3956 3227 3504 3557

Dominance Index 0.29 0.47 0.39 0.34 0.35 0.25

Shannon’s Index 1.57 1.15 1.27 1.44 1.39 1.57

Evenness (Shannon’s H Equitability) 0.54 0.35 0.41 0.47 0.45 0.60

27

3.3 Relative Abundance of Phyla

Eight phyla represented 97% of the relative sequence abundance of all provinces (Figure 7

a). The Proteobacteria had an average abundance of 39.5 ± 11.5% (Figure 7 a) and were

most abundant in the NAST and NATR provinces (51%). The Cyanobacteria had an average

abundance of 28.5 ± 10.5% in all provinces. Additionally the Bacteroidetes were present at

all station with 12 ± 7%. The abundance of Bacteroidetes was higher in the NADR and

SSTC provinces which had higher chlorophyll a concentrations. Bacteroidetes are known to

play an important role in the degradation or organic matter and have been previously

associated with phytoplankton blooms (Pereira, 2010; Teeling et al., 2012).

Actinobacteria made up a similar abundance with a maximum (15%) in the WRTA province.

This high abundance of Actinobacteria has previously been shown by (Morris et al., 2012)

however their functional role is still unknown because there are no isolated representatives.

The other phyla (Planctomycetes, Chloroflexi, Deferribacteres and Planctomycetes)

represent <10% abundance in all regions. Not indicated in Figure 7a. are phyla which had

relative sequence abundance below 1%. The results obtained in this study was consistent

with other studies of marine ecosystems (Friedline et al., 2012; Ghiglione et al., 2012;

Kirchman et al., 2010; Schmitt et al., 2012). These studies found similar abundance at the

phylum level, although they targeted various regions of the 16S rRNA.

The relative abundance of phyla in each province was analysed using a Bray-Curtis

similarity cluster (Figure 7 b). It compares the presence, absence and relative abundance of

each phylum between each province. There was a higher similarity between the sites

located in areas of low chlorophyll a, high temperature and high salinity (NAST, SATL,

NATR). Sites which had a low similarity exhibited high chlorophyll a measurements. Sites

with comparable physical and chemical conditions showed a high similarity in the abundance

of different phyla. This is evidence of biogeographical distribution at the phylum level. The

SSTC province showed the lowest similarity to all other provinces. From the relative

abundance it is apparent that a change in the dominance from Proteobacteria to

Cyanobacteria occurred in this province.

28

(a)

(b)

0.72

0.76

0.80

0.84

0.88

0.92

0.96

Sim

ilarity

SS

TC

NA

ST

SA

TL

NA

TR

WT

RA

NA

DR

Figure 7: Comparison of bacterial abundance at phylum level between the different sampling sites. (a) 100% stack column graph representing relative sequence abundances of the dominant phyla at different stations. (b) Bray-Curtis cluster analysis of the bacterial diversity at the phylum level using PAST.

29

3.4 Relative Abundance of Dominant Phyla

The relative abundance of Proteobacteria, Cyanobacteria and Bacteroidetes represented a

significant fraction (76%) of all sequences. Their high abundance could indicate a significant

function in the environment (Hunt et al., 2012) therefore they were individually analysed to a

deeper taxonomic resolution.

The Cyanobacteria were represented by two main genera. The Prochlorococcus

represented 83% of all cyanobacterial sequences in the subtropical and tropical provinces

and the genus Synechococcus represented 10 ± 5% in all provinces.

The Proteobacteria made up the highest abundance (51%)at all sites. Of this 99% consists

of the classes Alphaproteobacteria (55 ± 15%), Gammaproteobacteria (39 ± 14%),

Deltaproteobacteria (8 ± 5%) and Betaproteobacteria (2 ± 1%). Other Proteobacteria made

up less than 0.5% abundance together (Figure 8 a). Alphaproteobacteria had the highest

abundance in all provinces. The Alphaproteobacteria SAR11 made up nearly half of this

abundance with 41.5 ± 15.5%. SAR11 was present to a high abundance in all provinces but

was highest in the NATR and SATL provinces. These are the two gyral provinces which

have characteristic low chlorophyll a concentrations and are considered to be oligotrophic

environments. SAR11 is known for its ability to strive under oligotrophic conditions (Morris et

al., 2002) which could explain the high abundance in these regions. The wide distribution of

SAR11 shown in this study has been previously shown and it is believe to be ubiquitous in

the marine environment (Giovannoni et al., 2005; Hunt et al., 2012; Rappé et al., 2002).

The Gammaproteobacteria were the second most abundance class (39 ± 14%). Their

abundance was highest in the NADR, NAST and SSTC provinces which are characterised

by high primary production. Gammaproteobacteria have been associated with the

degradation of organic matter from phytoplankton which may explain their high abundance in

these provinces (Tada et al., 2011). Additionally a large portion of the gammaproteobacterial

abundance was made up of the SAR86 clade (15 ± 5%). Previous studies have shown

similar high abundances in this clade throughout the water column (Dupont et al., 2011;

Molloy, 2012).

Bray-Curtis similarity analysis (Figure 8 b) showed that there was a high similarity between

the Proteobacteria in all sites (r2 0.72). There was no distinguishable biogeographical

distribution within the Proteobacteria. The high similarity could be due to the dominance of

single subgroups such as SAR11 and SAR86, which appear to have omnipresence

throughout all provinces.

30

(a)

(b)

0.75

0.78

0.81

0.84

0.87

0.90

0.93

0.96

0.99

Sim

ilarity

WT

RA

NA

DR

SA

TL

SS

TC

NA

TR

NA

ST

Figure 8: Comparison of proteobacterial abundance, at class and order level, between the different sampling sites. (a) 100% stack column graph representing relative sequence abundances of the dominant classes at different stations. (b) Bray-Curtis cluster analysis of the proteobacterial diversity at the class level using PAST.

The Bacteroidetes were analysed to genus level for each biogeographical province because

they were represented at class and order level to 92% by the Flavobacteria,

Flavobacteriales. The relative abundances of Bacteroidetes was analysed by Bray-Curtis

31

similarity clustering (Figure 9). The similarity between sites was much less (r2 0.26) than

previously seen in the Proteobacteria. Geographically closer sites were clustered together. A

high similarity between geographically adjacent site such as NTRA and WTRA was

observed. Between the NAST and NADR province there was a low similarity (r2 0.32) but

they were still more similar to each other than more distant provinces. The clustering of

adjacent provinces indicates a similarity in the diversity in geographically closer regions. This

also leads to the inference that there is a latitudinal biogeographical distribution of distinct

Bacteroidetes genera.

The sequence abundances indicated that at a phylum level there was a high similarity

between all biogeographical provinces. The main differences that were observed could not

be related to geographical location but to the physical and chemical structure of the

environment. At a phylum level there was a clustering correlated to the level of primary

production within the environment.

The Proteobacteria did not exhibit a distinct clustering based on geographical location

because they are dominate by groups such as SAR11 or SAR86 which had an

omnipresents. The Bacteroidetes however had a more diverse assemblage with no clear

dominating genera and show distinct geographical distributions.

32

0.24

0.32

0.40

0.48

0.56

0.64

0.72

0.80

0.88

0.96

Sim

ilarity

NT

RA

WT

RA

SA

TL

SS

TC

NA

ST

NA

DR

Figure 9: Bray-Curtis cluster analysis of the Bacteroidetes diversity at the genus level using PAST.

High through-put pyrosequencing of the PCR amplified 16S rRNA gene provides an in depth

analysis of the bacterial diversity in distinct biogeographical provinces. The diversity analysis

lead to the conclusion the bacterial communities are not randomly but biogeographically

separated. However high through-put sequencing is semi quantitative and limited due to

PCR bias (Engelbrektson et al., 2010; Lee et al., 2012; Sergeant et al., 2012). To overcome

this limitation CARD-FISH was used to analyse the in situ abundance of the organisms

which dominated the sequencing data. This data was subsequently correlated to the

physical and chemical measurements taken at each sampling point, to see if there was a

biogeographical distribution pattern.

3.5 Absolute and Relative Abundances of Picoplankton along AMT22

To get an indication of the latitudinal and vertical distribution of the picoplanktonic community

of the Atlantic Ocean the three domains of life was analysed for their absolute and relative

33

abundances. There was a considerable difference when looking at the absolute (cell ml-1)

and relative cell abundances (% of DAPI). This is indicated in Figures 15 a & b and 16 a & b.

Figure 10:(a) Latitudinal-depth contours of Picoplankton cell abundances determined by DAPI (DNA) staining from 50°N to 50°S from 20 to 300m.(b) Latitudinal-depth contours of bacterial cell abundances determined by CARD-FISH using the Eub338 I-III probe.

The absolute picoplankton abundance (cells ml-1) changed with latitude and with depth

(Figure 10 a). In high latitudes and at the equator there were >1.5E+06 cells ml-1, whereas

gyre regions had <1.0E+06 cell ml-1. With depth there was a change from > 1.5E+06 cells

ml-1 to < 5E+05 cells ml-1. The picoplankton abundance was positively correlated high

chlorophyll a concentrations (r2 0.76).The highest cell numbers were observed in the surface

waters below 40 °S, shown in red figure 11 a. This was also the area of highest chlorophyll

a. Not hybridized absolute cell numbers did not reflect a specific latitudinal or depth

distribution (2.9E+05 ± 1.2E+05 cells ml-1). The correlation of picoplankton abundance with

34

high chlorophyll a can be accounted for by the fact that a large part of the picoplankton is

itself phototrophic. Eukaryotic primary production in the ocean is nutrient limited (Margalef,

1987). In high latitudes and at the equator there are higher mixing rates which results in the

availability of nutrients (Robinson et al., 2006). Subsequently, there is a significant increase

the amount of primary production (Yooseph et al., 2010) and in the absolute cell numbers,

which was also observed during this study. The increase in primary production results in a

high amount of organic matter production due to fixation of inorganic carbon by phototrophs

(Falkowski et al., 1998). This increase in organic matter causes an increase in the

heterotrophic prokaryotic community (Teeling et al., 2012; Yooseph et al., 2010). This was

also seen in the difference in the bacterial cell abundances in this study (Figure 10 b).

Bacteria showed a decrease in absolute cell abundances with depth from 1.1E+06 cells ml-1

to 8.2E+04 cells ml-1. Additionally, there were higher cell numbers in high and central

latitudes, corresponding with the picoplankton high abundance areas. Bacteria were

positively correlation to high light (r2 0.43) and chlorophyll a (r20.71). Although there was a

higher absolute abundance of Bacteria in high and central latitudes, they made up a larger

proportion of the picoplankton in gyre regions (up to 98%) (Figure 11). Bacteria dominate the

surface waters of all provinces with an average abundance of 72 ± 16%. The relative

abundance of Bacteria decreased to 59 ± 15% in the DCM and to 51 ± 9% in the

mesopelagic layer. The high abundance of Bacteria in marine systems has resulted in a

large amount of research to deduce the role which they play and their significance in higher

food webs and element cycles (DeLong, 2009).

There was a change in the community from Bacteria dominated at the surface to a near

mixed community of Bacteria and Archaea in mesopelagic depths in all biogeographical

provinces.

35

Figure 11: Latitudinal-depth contours of bacterial and archaeal relative cell abundances (% DAPI counts).

Archaea had an absolute abundance of 6.1E+04 ± 2.1E+04 cells ml-1 throughout the water

column, however their relative abundance (Figure 11)showed a significant change from 0 to

40%. Archaea had an abundance of 2 ± 1% at the surface, with an increase to 7% in the

NADR province. This increased to 10 ± 5% in the DCM layer and reached a maximum of 37

± 3% in mesopelagic depths. The increase in the relative abundance of Archaea has also

been reported by (Herndl et al., 2005). They measured the archaeal production and found it

contributed to up to 37% of the total prokaryotic production in meso- and bathypelagic

depths. This indicates that Archaea are an active part of the deep ocean prokaryotic

community. There was a clear difference in the distribution of the two domains but unlike the

Bacteria the absolute abundance of Archaea stays relatively constant with depth.

3.6 Relative Abundances and Biogeography of the Dominant Bacterial

Taxon along the AMT22

The dominate groups found in the tag sequence (Prochlorococcus, Synechococcus, SAR11,

SAR86 and Bacteroidetes) were analysis for relative cellular abundances and distribution.

Their relative cellular abundances were enumerated by using groups specific CARD-FISH

probes. Results for each biogeographical region are shown in appendix 3.

36

3.6.1 Cyanobacteria

The Cyanobacteria are photoautotrophic prokaryotes (Whitton & Potts, 2012). Two classes,

Prochlorococcus and Synechococcus, dominated the picoplankton community in the

euphotic zones (<300 m) (Figure 12). Prochlorococcus is unicellular and has a considerable

impact on global carbon cycles. Marine primary production accounts for 40% of the global

carbon fixation, of which Prochlorococcus contributes up to 50% (Malmstrom et al., 2013;

Partensky et al., 1999). This study found a 20% abundance of Prochlorococcus in tropical

and subtropical regions which was also shown in the study by (Schattenhofer et al., 2009).

At the surface it represented 13.5 ± 5.5% abundance and in the DCM 9 ± 6%. It was also

present at 150 m in the SATL provinces at 3%. In the gyral provinces (NATR, SATL) it was

the second most abundant group with 19% at the surface and 13.5 ± 1.5% in the DCM layer.

Previously have shown it to be ubiquitous in tropical and subtropical regions (40° N to 40°S)

and can occupies a considerable area of the water column (20 -200 m) (Partensky et al.,

1999), which was also observed in our study (2% at 200 m). Spearman Rank correlations

indicated a positive relationship between Prochlorococcus and temperature (r2 0.68) and

light (r2 0.63). This is consistent with its phototrophic metabolisms and temperature

dependent distribution (Malmstrom et al., 2013). Previous genomic and chemical analysis of

different Prochlorococcus strains showed that it has evolved divinyl derivatives of chlorophyll

a and chlorophyll b. These pigments absorb the fluorescence emission of the blue part of the

light spectrum and are characteristic of the Prochlorococcus. Blue light penetrates deepest

into the oceans and these pigments allow Prochlorococcus to exist in areas of less than 1%

surface irradiance (Zwirglmaier et al., 2008).

Synechococcus had a lower abundance than Prochlorococcus but had a wider latitudinal

distribution. It highest abundance was in high latitudes where it made up 5 ± 5% of the

picoplankton. Although Prochlorococcus and Synechococcus were present throughout the

water column there was a higher overall abundance of Prochlorococcus especially in lower

latitudes. Previous studies have shown that Synechococcus exists at about one order or

magnitude lower than Prochlorococcus but still makes a considerable contribution to the

carbon fixation of the oceans(Palenik et al., 2003).Its higher abundance in areas of higher

bacteria abundances (NADR, SSTC) could be related to its growth dependence on lysis of

heterotrophic Bacteria. (Weinbauer et al., 2011) showed higher growth rates of

Synechococcus in the presence of viruses due to their ability to utilize essential nutrients in

organic forms (amino acids, oligopeptides, phosphonates).

37

Figure 12: Latitudinal-depth contours of Prochlorococcus and Synechococcus (SYN) relative cell abundances (% DAPI counts).

3.6.2SAR11 and SAR 86 Clade

The Alphaproteobacterium SAR11 represented up to 50% of the picoplankton community

(Figure 13).It made up 30.5 ± 5.5% of all cells in the surface, 20.5 ± 14.5% in the DCM and

26.5 ± 11.5% in the mesopelagic layer. It had a high abundance (>20%) across all latitudes

and with depth. It was more abundant in the North Atlantic gyre region (NTRA, NAST) which

was also shown by (Schattenhofer et al., 2009). SAR11 was first isolated by (Rappé et al.,

2002) and is likely the most abundant heterotrophic bacterial group in the marine

environment. It dominates in both oligotrophic and copiotrophic conditions and has been

shown to have photoheterotrophic nutrient uptake abilities (Gomez-Pereira et al., 2012).

It had a lower abundance in the SATL region, which was also shown on the AMT20 (25%)

and AMT13 (22%) (Mary et al., 2006; Schattenhofer et al., 2009). It also showed a low

abundance in the SSTC province with only 6% in the DCM layer. Previous reasons for a low

abundance were related to the variability in nutrient availability (Morris et al., 2002), however

the SSTC region has high mixing rates and nutrient availability. Another reason for their low

abundance could be the decrease in light penetration due to high primary production at the

surface resulting in a decreases in nutrient uptake. SAR11 have been shown to use

38

proteorhodopsins for nutrient and amino acid uptake (Gomez-Pereira et al., 2012; Mary et

al., 2008). Additionally (Morris et al., 2012) have recently indicated that the SAR11 clade is

comprised of multiple ecotypes which may have varying nutrient requirements. They have

shown that a fraction of the SAR11 community responds rapidly to the input of organic

matter by phytoplankton and are thus phytoplankton dependent, whereas the North Atlantic

ecotypes is more dependent on amino acid and reduced sulphur uptake. This variation in

ecotypes nutrient dependence could indicate variations in the abundance.

The Gammaproteobacterium SAR86 was present along all latitudes up to 200 m depth

(Figure 13). The abundance of SAR86 was one order of magnitude lower than SAR11.

SAR86 was most abundance (5%) in the surface waters of the gyral latitudes and high

southern latitudes. The uncultured SAR86 clade has previously been reported

(Schattenhofer et al., 2009) at much lower relative abundances (0.5%). In this study two

helper probes were applied which has been shown to increase the probe binding ability

(Fuchs et al., 2000; Zubkov et al., 2001). These results indicated that this group maybe more

abundance in the surface waters than previously thought.

Both SAR11 and SAR86 are heterotrophic Bacteria which coexist in the water column of the

Atlantic Ocean. The reason for their coexistence could be due to their carbon compound

specialisation. SAR86 has specialised for the uptake of lipids and carbohydrates (Dupont et

al., 2011) where as SAR11 is specialised in the uptake of C1 compounds (Morris et al.,

2012; Rappé et al., 2002).

39

Figure 13: Latitudinal-depth contours of SAR11 and SAR86 relative cell abundances (% DAPI counts). The x-axis scale varies between the two plots (SAR11 100%, SAR86 10%).

3.6.3 Bacteroidetes

The members of the Bacteroidetes represented an average abundance of 5% (Figure 14).

They were present throughout the water column but were most abundance in the surface.

Their highest abundance was in high latitudes (NADR, SSTC) where they had up to 25 %

abundance. They were positively correlated to chlorophyll a concentrations (0.77) which has

been previously shown by (Schattenhofer et al., 2009). The Bacteroidetes have been

extensively studies due to their direct association with primary production in the marine

environment. They are key players in the degradation of phytoplankton derived organic

matter in coastal systems (Tada et al., 2011). They have also been shown to exhibit

succession patterns associated with the variability in available organic matter (Fernandez-

Gomez et al., 2013; Pereira, 2010; Teeling et al., 2012). The apparent selection by different

organic matter compounds makes them an interesting for the study of biogeography.

However in this and other studies (Schattenhofer et al., 2009) Bacteroidetes also made up a

significant fraction in the low nutrient and chlorophyll a provinces (NTRA, SATL). These

Bacteroidetes seem to cope with limiting conditions in contrast to their costal counterparts.

40

This data also corresponds to the genus level Bray-Curtis similarity analysis of the 454

sequences of Bacteroidetes which indicated variability between different provinces.

Figure 14: Latitudinal-depth contours of Bacteroidetes relative cell abundances (% DAPI counts).

3.6.4 Other Groups of the Bacterioplankton Community

In addition to these groups which were singled out due to their high abundance in the 454

tag sequencing data, other bacterial groups were also analysed by CARD-FISH. These

groups (Roseobacter, SAR202 and SAR324) have previously been shown by (Schattenhofer

et al., 2009) to have a high cellular abundance in the Atlantic ocean. They represented minor

abundance in the tag sequence data. However two of these groups are known for their

abundance in the meso- and bathypelagic water column (Giovannoni & Vergin, 2012; Swan

et al., 2011) which were not analysed by tag sequencing.

The group Roseobacter was present in the surface waters of all provinces and the DCM of

NADR, representing 3.5 ± 0.5% of the total abundance (Appendix 3). Their distribution was

positively correlated with chlorophyll a (r2 0.763) and negatively with temperature and salinity

(r2 0.293, 0.345 respectively). The Cloroflexi like SAR202 was contrastingly only present in

the meopelagic depth representing 11.5 ± 4.5% of the total abundance. This has previously

been shown by Giovannoni & Vergin, (2012) and Morris et al., (2004) who showed that

SAR202 accounted for 10% of all bacterioplankton from 500- 4000m.

SAR324 exhibited the same mesopelagic distribution and was present at 4 ± 1%. Similar

wide distribution patterns have been shown previously in the Eastern Atlantic Ocean by

Schattenhofer et al., (2009). Swan et al., (2011) showed that SAR324 could be

chemolithoautotrophs which fix inorganic carbon at significant rates in the deep ocean.

41

Conclusion

This study has increased our understanding of the bacterioplanktonic diversity, distribution

and abundance in the Atlantic Ocean. It complements previous diversity and abundance

studies of the bacterioplankton of the Eastern and Central Atlantic Ocean (Friedline et al.,

2012; Morris et al., 2012; Schattenhofer et al., 2009).

Firstly, the bacterioplanktonic diversity in different biogeographical provinces was analysed

using massive parallel tag sequencing and subsequently, the abundance and distribution

patterns of the dominate bacterioplanktonic groups throughout the Atlantic Ocean were

enumerate. The dominant community made up a significant fraction of the total cellular

abundance of the picoplankton community. There were few groups (SAR11, SAR86 and

Bacteroidetes) which could be found at all latitudes and depths and although they were

ubiquitous in the 454 sequences, their relative abundances did vary. There was no direct

comparison between the relative sequence abundance and relative cellular abundance due

to the different nature of the methods applied. The distribution and abundance of the

dominant bacterioplankton groups could be correlated with the presence of strong

environmental drivers such as chlorophyll a and temperature. Additionally this could be

associated with previously described distribution patterns and assumed metabolic and

physiological capabilities of the organisms. The results presented here are consistent with

the emerging picture of the distribution patterns of the dominant microorganisms within the

Atlantic Ocean.

The methods applied in this study differ from previous studies because the diversity,

abundance and distribution were analysed and related to environmental parameters. When

analysing diversity using 454 sequencing a high taxonomic resolution is obtained but there is

no direct relation to the relative abundance, because there is a PCR step in the method (Lee

et al., 2012). The sequencing results can only be used for the analysis of presence and

absence or for a comparative analysis between the diversity and relative sequence

abundance of different sites, as shown in this study. The change in relative sequence

abundance can then be related to the change in diversity with latitude and correlated to

environmental parameters. However it is difficult to deduce from this, which organisms are

abundance or activity in the environment. The use of CARD-FISH allows for the analysis of

abundance which can be related to activity.

From the diversity results presented here it becomes apparent that the taxonomic resolution

is important when looking at the biogeography of microorganisms. Distinct biogeographical

trends may not be apparent or accurate at a broader taxonomic resolution. In this study at a

phylum level there was an apparent biogeography distribution based on environmental

42

parameters. Bray Curtis similarity analysis showed that sites with low chlorophyll a and high

temperatures were more similarly to each other. This indicated that at a phylum level there

was a difference in the abundance, presence and absence of different phyla depending on

primary production and temperature.

Within the classes of the Proteobacteria however there was no apparent biogeographical

distribution. This could have been due to the dominance of ubiquitious groups in all

provinces (SAR11, SAR86), or due to the fact that the Proteobacteria are a highly diverse

group of organisms with varying metabolic capabilities.

Within the Bacteroidetes there was a distinct biogeographical with latitude. Geographically

closer samples were more similar indicating a limited distribution or geographical isolation of

specific genera. From these three examples it became apparent that it is important to

consider the taxonomic resolution when looking for a biogeographical pattern due to the

ecophysiological and metabolic flexibility within different taxonomic groups.

When looking at diversity based on a high taxonomic level there is no ecological similarity

considered. Microorganisms of the same order can have extremely different physiologies.

This can be shown by the apparent ubiquitous nature of SAR11. This Alphaproteobacterium

was present to a high abundance throughout the Atlantic Ocean and showed no

biogeographical distribution in this study. However recent analysis have indicated that there

are specific ecotypes of SAR11 with varying nutrient requirements (Morris et al., 2012). It

may be that specific ecotypes of SAR11 do show a biogeographical distribution however this

is not reflected at a broad taxonomic level. The lineages microdiversity could determine its

success in the marine environment (Friedline et al., 2012) but could also give an indication of

it biogeographic distribution and possible reasons for its variations in abundance.

When looking at the biogeography of microorganisms it is important to consider that a

biogeographical distribution pattern is only expected if there is ecological coherence within a

lineage (Philippot et al., 2010). Then an association between the environment and the

biodiveristy can be defined. If there is no ecological coherence then a pattern of distribution

based on the chemical and physical environment is hard to assume because the

ecophysiologies can vary.

The Cyanobacteria are one of the few phyla which show ecological coherence (all

photoautotrophs). The diversity and distribution of cyanobacteria can therefore be correlated

with light because this is an essential requirement. They are known for having specific

temperature optimums (Zwirglmaier et al., 2008) which can be analysed and in this study

we saw a difference between the distribution of Synechococcus and Prochlorococcus, with

Prochlorococcus showing a correlation to higher temperatures. This was also reflected in

their abundance and distribution patterns from CARD-FISH analysis. The ecological

43

coherence and high abundance of Cyanobacteria may also account for the biogeographical

patterns observed in the 454 data at the phylum level.

The importance of taxonomic resolution could also be shown in the biogeographical pattern

in the Bacteriodetes shown in this study. They have been associated with high chlorophyll a

areas in this and previous studies using the relative cellular abundance. They did occur to

higher abundance in regions of high chlorophyll a in this study but not exclusively. The

diversity varied between different regions based on latitudinal distance not on the chlorophyll

a concentrations. Provinces with high chlorophyll a were not more similar in diversity. This

indicates that when interpreting microbial biogeography it is important to incorporate the

ecology of the specific taxonomic level not just the diversity or abundance.

The combined analysis of the diversity and abundance of microorganisms based on

biogeographical patterns resulted in a more accurate interpretation of the biogeography of

microorganisms in the Atlantic Ocean. Understanding the biogeography of groups of

microorganisms is a key step in understanding the ecosystem function of specific microbial

assemblages and interpreting and prediction variations to this pattern.

44

Acknowledgements

This master’s thesis was sponsored by the Max Planck International Research School for

Marine Microbiology. Thanks to the Master and crew of the RRV James Cook as well as the

principle scientist Glen Tarren from Plymouth Marine Laboratories. Thank you to my

supervisor Rudolf Amann who made this master possible and to the Department of

Molecular Ecology for hosting me. Additional thanks goes to Jörg Wulf, Martha

Schattenhofer, Mike Zubkov and Sara Cregeen for their technical support and insightful

discussions on cruise. Thank you also to Bernhard Fuchs, Christin Bennke and Marion

Stagars.

My final thanks goes to my mother Susanne Zühlke and the Marmic 15 (sunshine) class.

You have been a constant supportive ear and ever helping hand, thank you.

45

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Websites www.oceancolor.gstc.nansa.gov

www.odv.awi.de

www.sigmaplot.co.uk

http://www.arb-silva.de/documentation/background/release-108

http://www.bioinformatics.org/cd-hit

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53

Appendices

Apendix 1.

Corresponding NaCl concentrations in wash buffer for formamide concentration in hybridisation buffer.

% formamide in hybridization

buffer

[NaCl] in Mol μl 5 M NaCl

0 0.900 8900

5 0.636 6260

10 0.450 4400

15 0.318 3080

20 0.225 2150

25 0.159 1490

30 0.112 1020

35 0.080 700

40 0.056 460

45 0.040 300

50 0.028 180

55 0.020 100

60 0.014 40

Dye labels used in this study and their characteristic excitiation (+/- 10 nm)

Dye Excitiation (+/- 10 nm) Emission (+/-10nm)

DAPIb (for DNA

counterstaining)

358 350

Alexa 488 495 519

Alexa 594 590 617

54

Appendix 2.

Rarefraction analysis for each sample representing a biogeographical province.

55

56

57

Appendix 3.

58

Relative abundance of the dominant bacterioplankton groups (represented by the CARD-FISH hybridization with probes Eub338 I-III (bacteria), ARCH915 (Archaea), SAR11- MIX (SAR 11 clade), ROS537 (Roseobacter), SAR86-1245 (SAR 86 clade), CF319a (Bacteroidetes), SAR202-312R (SAR 202 clade), CYA664 (Cyanobacteria), SYN405 (Synechococcus); Pro405 (Prochlorococcus), SAR324-1412 (SAR324 clade). Abundance is shown for different biogeographical provinces (from 50 °N to 50°S, NADR, NAST, NATR, WTRA, SATL, SSTC) and across a vertical gradient (20m, DCM and 150m representing the surface, DCM and mesopelagic water column). Cell which did not hybridize with one of the applied group specific groups are indicated in green.