Introduction
The hydrogen isotopic composition of fatty acids of microorganisms has been
shown to depend on different factors like metabolism, salinity, biosynthetic
pathways, growth phase and temperature (Dirghangi and Pagani, 2013; Fang et
al., 2014; Heinzelmann et al., 2015a, b; X. N. Zhang et al., 2009; Z. Zhang
et al., 2009). While most of these factors lead to relatively small
variations in the deuterium-to-hydrogen (D / H) ratio of fatty acids
(10–20 ‰), differences in the central metabolism of microorganisms
have a much more pronounced effect (X. N. Zhang et al., 2009). Both photo-
and chemoautotrophs produce fatty acids depleted in D compared to growth
water with the stable hydrogen isotopic fractionation factor ε
between the nC16:0 fatty acid, the most commonly occurring fatty acid in
microorganisms, and water (εlipid/water) ranging between
-160 to -220 ‰ and -250 and -400 ‰, respectively
(Campbell et al., 2009; Chikaraishi et al., 2004; Heinzelmann et al., 2015a,
b; Sessions et al., 2002; Valentine et al., 2004; X. N. Zhang et al., 2009;
Zhang and Sachs, 2007). In contrast, heterotrophs produce nC16:0 fatty acid
with either a relatively minor depletion or an enrichment in D compared to
the growth water with εlipid/water values ranging between
-150 and +200 ‰ (Dirghangi and Pagani, 2013; Fang et al., 2014;
Heinzelmann et al., 2015a, b; Sessions et al., 2002; X. N. Zhang et al.,
2009). It has been speculated that the differences in hydrogen isotopic
composition of fatty acids produced by organisms expressing different core
metabolisms (i.e. heterotrophy and photo- and chemoautotrophy) are mainly due
to the D / H ratio of the H added to nicotinamide adenine dinucleotide
phosphate (NADP+) and the hydrogen isotope fractionation associated with
the reduction of NADP+ to NADPH, which is used during fatty acid
biosynthesis (X. N. Zhang et al., 2009). NADP+ is reduced to NADPH
during a number of different reactions in multiple different metabolic
pathways (each associated with different hydrogen isotopic fractionations)
and is subsequently used as a major source of hydrogen in lipid biosynthesis
(Robins et al., 2003; Saito et al., 1980; Schmidt et al., 2003).
Although the metabolism of a microorganism in pure culture is reflected by
the D / H ratio of its fatty acids, it is not clear whether the D / H
ratio of fatty acids from environmental microbial communities can be used to
assess the “community-integrated” core metabolisms and changes therein in
nature. Culture conditions rarely represent environmental conditions since
cultures are typically axenic and use a single substrate; they do not take
into account microbial interactions, which have been shown to affect the
hydrogen isotopic composition of lipids (Dawson et al., 2015) and they test a
limited number of potential substrates, energy sources and core metabolisms.
Previous studies of environmental samples observed a wide range in the
D / H ratio of lipids in both the marine water column and sediment (Jones
et al., 2008; Li et al., 2009), suggesting inputs of organisms with a variety
of metabolisms. Osburn et al. (2011) showed that different microbial
communities from various hot springs in Yellowstone National Park produce
fatty acids with hydrogen isotopic compositions in line with the metabolism
expressed by the source organism. The D / H ratio of specific fatty
acids, which could be attributed to microorganisms expressing a specific core
metabolism, was within the range expected for that metabolism. On the other
hand, the D / H ratio of common or general fatty acids (e.g. nC16:0)
allowed for assessing the metabolism of the main contributors of these more
general fatty acid, but not necessarily the metabolism of the dominant
community members (Osburn et al., 2011). These first environmental results
indicate the applicability of this new method, which clearly indicates the
limitation of looking only at general occurring fatty acids.
Here, we studied the seasonal variability of the hydrogen isotopic
composition of fatty acids from coastal North Sea water sampled from the
jetty at the Royal Netherlands Institute for Sea Research (NIOZ) in order to
examine the relationship between hydrogen isotope fractionation in fatty
acids and the general metabolism of the microbial community. Time series
studies have been previously performed at the NIOZ jetty to determine
phytoplankton and prokaryotic abundances and composition (Alderkamp et al.,
2006; Brandsma et al., 2012; Brussaard et al., 1996; Philippart et al., 2000,
2010; Pitcher et al., 2011; Sintes et al., 2013), lipid composition (Brandsma
et al., 2012; Pitcher et al., 2011), and chlorophyll a concentration
(Philippart et al., 2010). Typically, the spring bloom in the coastal North
Sea is predominantly comprised of Phaeocystis globosa, followed
directly by a bloom of various diatom species, a second moderate diatom bloom
of Thalassiosira spp. and Chaetoceros socialis that occurs
in early summer. An autumn bloom is formed by Thalassiosira spp.,
C. socialis, cryptophytes and cyanobacteria (Brandsma et al., 2012;
Cadée and Hegeman, 2002). However the autumn bloom seems to have weakened
over the last years (Philippart et al., 2010). The abundance of bacteria
increases following the algal blooms and the bacteria are dominated by
heterotrophs, e.g. bacteria belonging to Bacteroidetes
(Alderkamp et al., 2006), using released organic matter from declining
phytoplankton blooms as carbon, nitrogen and phosphate sources. The intact
polar lipid (IPL) composition of the microbial community was shown to be
composed mainly of phospholipids, sulfoquinovosyldiacylglycerol and betaine
lipids with a limited taxonomic potential (Brandsma et al., 2012). The main
source of those lipids was assumed to be the eukaryotic plankton.
This well-studied site should allow us to trace the shift from an
environment dominated by photoautotrophs during major phytoplankton blooms,
towards an environment with a higher abundance of heterotrophic bacteria
following the end of the bloom (Brandsma et al., 2012). These shifts in the
community structure should be reflected in the D / H ratio of fatty acids. We,
therefore, analysed the D / H ratio of polar-lipid-derived fatty acids (PLFAs)
over a seasonal cycle and compared this with phytoplankton composition data
and abundance and information on the bacterial diversity obtained by 16S
rRNA gene amplicon sequencing.
Material and methods
Study site and sampling
From September 2010 until December 2011 water samples were taken from the
NIOZ sampling jetty in the Marsdiep at the western entrance of the North Sea
into the Wadden Sea near the island of Texel (53∘00′06′′ N,
4∘47′21′′ E). Surface water samples (depth max ± 50 cm
below surface) were collected for suspended particulate matter (SPM) biweekly
during high tide to ensure that water sampled was from the North Sea.
For lipid analysis measured volumes of water (ca. 9–11 L) were filtered
consecutively, without pre-filtration, through pre-ashed 3 and
0.7 µm pore size glass fibre filters (GF/F, Whatman; 142 mm
diameter) and stored at -20 ∘C until lipid extraction. For DNA
analysis approximately 1 L seawater was filtered through a polycarbonate
filter (0.2 µm pore size; 142 mm diameter; Millipore filters) and
stored at -80 ∘C until extraction.
Salinity measurements were done during the time of sampling with either an
Aanderaa conductivity/temperature sensor 3211 connected to an Aanderaa
data logger DL3634 (Aanderaa Data Instruments AS, Norway) or a
refractometer/salinometer Endeco type 102 handheld (Endeco, USA).
For chlorophyll a measurements 500 mL sea water was filtered through a
47 mm GF/F filter (0.7 µm pore size, Whatman, GE Healthcare Life
Sciences, Little Chalfont, UK) and immediately frozen in liquid nitrogen.
Samples were thawed and homogenized with glass beads and extracted with
methanol. Chlorophyll a concentration was measured with a Dionex
high-performance liquid chromatograph (HPLC) (Philippart et al., 2010).
Water samples for salinity versus δDwater calibration (see
below) were sampled weekly between March and September 2013 at high tide.
Salinity was determined using a conductivity meter (VWR EC300) calibrated to
IAPSO standard seawater of salinities 10, 30, 35 and 37.
Polar-lipid-derived fatty acids
Filters were extracted for IPLs and eventually fatty acid analysis. The 0.7 µm filters did not yield enough total lipid extract for analysis.
Therefore, only fatty acids obtained from the 3 µm filters were
analysed. Due to fast clogging of the filters and a corresponding decrease of
the pore size (Sørensen et al., 2013), the 3 µm filters will
most likely contain most of the microorganisms present in North Sea water,
although it cannot be excluded that the microorganisms retained on the filter
are biased towards a larger cell size. Freeze-dried filters were extracted
via a modified Bligh–Dyer method (Bligh and Dyer, 1959; Rütters et al.,
2002) with methanol (MeOH) / dichloromethane (DCM) / phosphate buffer
(2:1:0.8, v/v/v) using ultrasonication (Heinzelmann et al., 2014).
Approximately 0.5–1 mg of the Bligh–Dyer extract (BDE) was separated into a
neutral and polar lipid fraction using silica column chromatography
(Heinzelmann et al., 2014). The BDE was added onto a DCM pre-rinsed silica
column (0.5 g; activated for 3 h at 150 ∘C) and eluted with 7 mL
of DCM and 15 mL of MeOH. The resulting fractions were dried under nitrogen
and stored at -20 ∘C. PLFAs were obtained via saponification of
the MeOH fraction with 1 N KOH in MeOH (96 %). The samples were refluxed
at 140 ∘C for 1 h. Afterwards the pH was adjusted to 5 with
2 N
HCl / MeOH (1/1); bidistilled H2O and DCM were added. The
MeOH / H2O layer was washed twice with DCM, the DCM layers
combined and water removed using Na2SO4. The sample was dried under
nitrogen and stored in the fridge. The PLFAs were methylated with boron
trifluoride-methanol (BF3-MeOH) for 5 min at 60 ∘C. Afterwards
H2O and DCM were added. The H2O / MeOH layer was washed three
times with DCM, and potential traces of water were removed over a small
Na2SO4 column after which the DCM was evaporated under a stream of
nitrogen. In order to obtain a clean PLFA fraction for isotope analysis, the
methylated extract was separated over an aluminium oxide (Al2O3)
column, eluting the methylated PLFAs with three column volumes of DCM. For
identification of the position of double bonds in unsaturated fatty acids,
the methylated PLFAs were derivatized with dimethyldisulfide (DMDS) (Nichols
et al., 1986). Hexane, DMDS and I2 / ether (60 mg mL-1) were
added to the fatty acids and incubated at 40 ∘C overnight. After
adding hexane, the iodine was deactivated by addition of a 5 % aqueous
solution of Na2S2O3. The aqueous phase was washed twice with
hexane. The combined hexane layers were cleaned over Na2SO4 and
dried under a stream of nitrogen. The dried extracts were stored at
4 ∘C.
Fatty acid and hydrogen isotope analysis
The fatty acid fractions were analysed by gas chromatography (GC) using an
Agilent 6890 GC with a flame ionization detector (FID) using a fused silica
capillary column (25 m × 320 µm) coated with CP Sil-5
(film thickness 0.12 µm) with helium as carrier gas. The
temperature programme was as follows: initial temperature 70 ∘C,
increase of temperature to 130 ∘C with 20 ∘C min-1,
and then to 320 ∘C with 4 ∘C min-1, which was kept for
10 min. Individual compounds and double bond positions (see above) were
identified using GC–mass spectrometry (MS) (Schouten et al., 1998).
Hydrogen isotope analysis of the fatty acid fraction was performed by GC
thermal conversion (TC) isotope ratio monitoring (ir) MS using an Agilent
7890 GC connected via Thermo GC Isolink and Conflo IV interfaces to a Thermo
Delta V MS according to Chivall et al. (2014). Samples were injected onto an
Agilent CP-Sil 5 CB column (25 m × 0.32 mm ID; 0.4 µm
film thickness; He carrier gas, 1.0 mL min-1). The GC temperature
programme was 70 to 145 ∘C at 20 ∘C min-1, then to
320 ∘C at 4 ∘C min-1, where it was kept for 15 min.
Eluting compounds were converted to H2 at 1420∘C in an
Al2O3 tube before introduction into the mass spectrometer. The
H3+ correction factor was determined daily and was constant at
5.3 ± 0.2. A set of standard n-alkanes with known isotopic
composition (Mixture B prepared by Arndt Schimmelmann, University of Indiana)
was analysed daily prior to analysing samples in order to monitor the system
performance. Samples were only analysed when the n-alkanes in Mix B had an
average deviation from their offline determined value of
< 5 ‰. An internal standard, squalane (δD = -170 ‰), was co-injected with each fatty acid sample
fraction in order to monitor the accuracy of the measurements over time with
δD = -164 ± 4 ‰. The δD of the
individual fatty acids was measured in duplicates and corrected for the added
methyl group (Heinzelmann et al., 2015b). δD of water samples was
determined by elemental analysis (EA)/TC/irMS according to Chivall et
al. (2014).
Phytoplankton abundance and diversity
Phytoplankton samples were preserved with acid Lugol's iodine, and cells were
counted with a Zeiss inverted microscope using 3 mL counting chambers. Most
photoautotrophic microorganisms were identified to species level, but some
were clustered into taxonomic and size groups (Philippart et al., 2000). For
each sampling date in the period from September 2010 to December 2011, the
densities of the most abundant phytoplankton species or species' groups were
calculated. The three most dominant phytoplankton species (or groups)
together comprised, on average, more than 60 % of the total numbers of
marine phytoplankton in the Marsdiep during this study period.
DNA extraction
The 0.2 µm polycarbonate filters were defrosted and cut into small
pieces with sterile scissors and then transferred into a 50 mL falcon tube.
Filter pieces were lysed by bead-beating with ∼ 1 g of sterile 0.1 mm
zirconium beads (Biospec, Bartlesville, OK) in 10 mL RLT buffer (Qiagen) and
100 µL β-mercaptoethanol for 10 min; 1/60 volume RNase A
(5 µg µL-1) was added to the lysate, incubated for
30 min at 37 ∘C and afterwards cooled down for 5 min on ice. The
lysate was purified with the DNeasy Blood and Tissue Kit (Qiagen, Hilden).
DNA was eluted with 3 × 100 µL AE buffer, the eluates
pooled and reconcentrated. DNA quality and concentration was estimated by
NanoDrop (Thermo Scientific, Waltham, MA) quantification.
16S rRNA gene amplicon sequencing and analysis
The general bacterial diversity was assessed by 16S rRNA gene amplicon
pyrotag sequencing. The extracted DNA was quantified fluorometrically with
Quant-iT™
PicoGreen® dsDNA Assay Kit (Life
Technologies, the Netherlands).
PCRs were performed with the universal (Bacteria and Archaea)
primers S-D-Arch 0519-a-S-15 (5′-CAGCMGCCGCGGTAA-3′) and
S-D-Bact-785-a-A-21 (5′-GACTACHVGGGTATCTAATCC-3′) (Klindworth et
al., 2012) adapted for pyrosequencing by the addition of sequencing adapters
and multiplex identifier (MID) sequences. To minimize bias three independent
PCRs were performed containing the following: 16.3 µL H2O,
6 µL HF Phusion buffer, 2.4 µL dNTP (25 mM),
1.5 µL forward and reverse primer (10 µM; each containing
an unique MID tail), 0.5 µL Phusion Taq and 2 µL DNA
(6 ng µL-1). The PCR conditions were the following:
98 ∘C, 30 s; 25 × [98 ∘C, 10 s; 53 ∘C,
20 s; 72 ∘C, 30 s]; 72 ∘C, 7 min and 4 ∘C,
5 min.
The PCR products were loaded on a 1 % agarose gel and stained with
SYBR® Safe (Life Technologies, the Netherlands). Bands were excised with a sterile scalpel and purified with
Qiaquick Gel Extraction Kit (QIAGEN, Valencia, CA) following the
manufacturer's instructions. PCR purified products were quantified with
Quant-iT™
PicoGreen® dsDNA Assay Kit (Life
Technologies, the Netherlands). Equimolar concentrations of the barcoded PCR
products were pooled and sequenced on GS FLX Titanium platform (454 Life
Sciences) by Macrogen Inc., South Korea.
Samples were analysed using the QIIME pipeline (Caporaso et al., 2010). Raw
sequences were demultiplexed and then quality-filtered with a minimum quality
score of 25, length between 250 and 350 bp, and allowing a maximum of two errors in
the barcode sequence. Sequences were then clustered into operational
taxonomic units (OTUs, 97 % similarity) with UCLUST (Edgar, 2010). Reads
were aligned to the Greengenes Core reference alignment (DeSantis et al.,
2006) using the PyNAST algorithm (Caporaso et al., 2010). Taxonomy was
assigned based on the Greengenes taxonomy and a Greengenes reference database
(version 12_10) (McDonald et al., 2012; Werner et al., 2012). Representative
OTU sequences assigned to the specific taxonomic groups were extracted
through classify.seqs and get.lineage in Mothur (Schloss et al., 2009) by
using the Greengenes reference and taxonomy files. The 16S rRNA gene amplicon
reads (raw data) were deposited in the NCBI Sequence Read Archive (SRA)
under BioProject number PRJNA293285.
Phylogenetic analyses
The phylogenetic affiliation of the 16S rRNA gene sequences was compared to
release 119 of the Silva NR SSU Ref database (http://www.arb-silva.de/;
Quast, 2012) using the ARB software package (Ludwig et al., 2004). Sequences
were added to the reference tree supplied by the Silva database using the ARB
Parsimony tool.
Results
Chlorophyll a concentration and phytoplankton abundance and
diversity
Chlorophyll a concentrations ranged between 0.4 and
22.2 µg L-1 (Fig. 1; Table S1 in the Supplement). During late
autumn, winter and early spring concentrations were low at
∼ 4 µg L-1. A peak in the chlorophyll a
concentration occurred in the beginning of April and values stayed relatively
high during this month, indicative of the spring bloom. Subsequently, the
chlorophyll a concentration decreased again, reaching pre-bloom levels
and stayed relatively constant thereafter.
Values of εFA compared to chlorophyll a
concentrations. εFA is the weighted average of
nC14:0, nC16:1, nC16:0, nC18:0 fatty
acids and the nC20:5 PUFA from jetty samples taken from August 2010 to December 2011.
Phytoplankton diversity and abundance was determined using light microscopy,
and the two to three most abundant phytoplankton species were identified and
counted (Table S2). The majority of the phytoplankton was composed of
Phaeocystis globosa, diatoms and cyanobacteria (Fig. 2), with the
spring bloom primarily being made up of P. globosa. The highest
abundance of diatoms was also during spring, while the cyanobacteria reached
the highest abundance in the beginning of the sampling period from autumn
until late winter and again during summer.
Phytoplankton diversity and abundance (measured in cells L-1) observed
in the coastal North Sea between August 2010 and December 2011.
Bacterial diversity
To assess bacterial diversity, 16S rRNA gene amplicon sequencing was
performed on approximately half of the SPM samples (Table S3a, b).
The bacteria detected consisted mainly of members of
Actinobacteria, Bacteriodetes, Planctomycetes,
α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria and
Verrucomicrobia (Fig. 3; Table S3a). The majority of the reads
belonged to the orders of Flavobacteriales,
Rhodobacterales, Rickettsiales, Alteromonadales
and Oceanospirillales. The Flavobacteriales clade were one
of the main contributors (12 to 32 %) to the total bacteria reads with a
maximum from beginning of April until the end of May. The percentage of reads
attributed to Flavobacteriales decreased during summer and early
autumn. Sequence reads affiliated to Rhodobacterales (6 to
12 %) and Rickettsiales (3 to 17 %) were the most
represented within the α-Proteobacteria.
Alteromonadales reads made up between 9 and 17 % of all bacteria
reads, and the percentage of Oceanospirillales reads was between 3
and 12 % of the total bacteria reads (Fig. 3; Table S3b).
For a more accurate taxonomic classification of the bacterial groups,
sequence reads of Bacteriodetes, α-Proteobacteria and γ-Proteobacteria were
extracted from the dataset and a phylogenetic tree was constructed
(Figs. S1–S3a, b). Within Flavobacteriales
(Bacteroidetes) the majority of the reads fell either within
Cryomorphaceae or Flavobacteriaceae with sequences
clustering within Fluviicola and Crocinitomix,
Flavobacterium and Tenacibaculum, respectively. Within
Rhodobacterales (α-Proteobacteria) most of the
reads belonged to Rhodobacteraceae and sequences within this family
were closely related to the genus Octadecabacter. Within
Rickettsiales most of the reads were affiliated to
Pelagibacteraceae (SAR11 cluster). The majority of the
γ-Proteobacteria reads were classified within
Alteromonadales and Oceanospirillales. The
Alteromonadales reads and sequences fell within the linage of the
uncultured HTCC2188-isolate and OM60-clade and various
members of the Alteromonadaceae family. The Halomonadaceae
family comprised most of the Oceanospirillales reads and
additionally sequences clustered with various members of
Oceanospirillaceae.
Fatty acid distribution in North Sea SPM
Polar-lipid-derived fatty acids were comprised of nC14:0, nC16:1ω7, nC16:0, nC18:0, the polyunsaturated fatty acid (PUFA)
nC20:5, and various unsaturated nC18 fatty acids (Fig. 4; Table S4). The
nC14:0 fatty acid followed a seasonal cycle with the lowest relative
abundance during winter and the highest from June to August (Fig. 4a). The
nC16:0 fatty acid was the dominant fatty acid (21–38 %) with no clear
seasonal pattern (Fig. 4c). The nC16:1 fatty acid was the next most
abundant fatty acid (13–35 %) with a maximum from March to April
(Fig. 4b). Various unsaturated nC18: × fatty acids were observed
throughout the season. Due to low abundance of the individual fatty acids and
co-elutions the double bond positions could not be determined. These
unsaturated fatty acids made up 9–30 % of all fatty acids (Fig. 4d). The
nC18:0 fatty acid had relative abundances varying between 2 and 18 % with
the highest relative abundance during autumn months (10–18 %) and the
lowest during spring, 2–6 % (Fig. 4e). A nC20:5 PUFA (Fig. 4f) was
observed in most samples with the highest relative abundance during March and
April (11–14 %) and early August (18 %). Trace amounts of nC15:0,
iC15:0 and aiC15:0 fatty acids were also detected.
Order-level bacterial diversity and abundance in North Sea water
based on the 16S rRNA gene sequence.
Relative abundance of fatty acids and chlorophyll a
concentration in North Sea SPM. (a) nC14:0, (b) nC16:1,
(c) nC16:0, (d) nC18:x, (e) nC18:0,
(f) nC20:5 PUFA and chlorophyll a.
Hydrogen isotopic composition of fatty acids
δD values of nC14:0, nC16:1ω7, nC16:0, nC18:0 and
nC20:5 fatty acids were obtained for most of the samples (Table S5). The
D / H ratio of the other fatty acids could not be determined with
sufficient accuracy due to either incomplete separation or low abundance.
In general, nC14:0 and nC20:5 were the most depleted fatty acids with
δD values ranging between -198 to -241 ‰ and -180 to
-241 ‰, respectively. The nC18:0 was typically the fatty acid
with the highest δD values ranging between -175 and
-212 ‰ (Table S5).
Discussion
Hydrogen isotopic fractionation expressed in fatty acids
For the proper assessment of the impact of metabolism on the hydrogen
isotopic composition of fatty acids, the hydrogen isotopic fractionation of
the fatty acids versus water is required (εlipid/water).
For this, the δD of the water (δDwater) at the time
of sampling is needed. However, at the time of sampling of the SPM
unfortunately no water samples were taken and preserved for δD
analysis. Therefore, we used an alternative approach to estimate δDwater using the salinity of the water measured at the time of
sampling. A strong correlation between salinity and δDwater
is generally observed in marine environments since both parameters depend on
evaporation, precipitation and freshwater influx (Craig and Gordon, 1965;
Mook, 2001). To establish a local salinity – δDwater
correlation, water samples were collected weekly during high tide (March to
September 2013) and salinity and δDwater were measured.
Indeed, a strong correlation between salinity and δDwater
is observed (R2=0.68; Fig. S4). Using this correlation and the
salinities measured, we reconstructed δDwater values at the
time of sampling of the biomass (Table 1). The error in the estimate of
δDwater values resulting from this approach is
approximately 1.5 ‰, which is less than the error in the
determination of δD of the fatty acids (1–12 ‰) and minor
compared to the entire range in fatty acid δD (-174 to
-241 ‰) and εlipid/water (-173 to
-237 ‰).
D / H fractionation between fatty acids and North Sea water for
fatty acids derived from suspended particulate matter in North Sea water
samples. N.D. indicates not determined. Date format is DD/MM/YY
Date
Salinity
δDwater (‰)
εlipid/water (‰)
εΣFA (‰)
(estimated)
C14:0
C16:0
C16:1*
C18:0
C20:5 PUFA
weighted average
C14, C16:1, C16, C18
16/08/10
27.3
-8.2
-212 ± 2
-194 ± 3
-194 ± 3
-178 ± 4
-185 ± 2
-196 ± 2
30/08/10
29.7
-4.1
-218 ± 3
-198 ± 3
-186 ± 3
-182 ± 2
-195 ± 2
-197 ± 2
15/09/10
30
-3.6
-213 ± 3
-203 ± 2
-194 ± 2
-183 ± 2
-177 ± 3
-201 ± 2
28/09/10
24.7
-12.6
-209 ± 2
-188 ± 2
-182 ± 2
-187 ± 2
-197 ± 3
-190 ± 2
15/11/10
30
-3.6
-211 ± 3
-200 ± 2
-179 ± 2
-197 ± 2
N.D.
-196 ± 2
26/11/10
24.8
-12.4
-216 ± 3
-192 ± 3
-178 ± 3
-193 ± 3
N.D.
-193 ± 2
10/12/10
27.1
-8.5
-218 ± 2
-181 ± 2
-184 ± 2
-195 ± 2
N.D.
-190 ± 1
17/12/10
24.1
-13.6
-221 ± 3
-182 ± 2
-183 ± 2
-177 ± 3
N.D.
-188 ± 2
10/01/11
27.8
-7.3
-215 ± 4
-195 ± 3
-180 ± 2
-198 ± 2
N.D.
-192 ± 2
24/01/11
23.0
-15.5
-200 ± 3
-179 ± 2
-183 ± 2
-180 ± 2
-197 ± 3
-183 ± 2
17/02/11
29.3
-4.8
-219 ± 2
-204 ± 2
-191 ± 2
-203 ± 2
N.D.
-201 ± 1
08/03/11
25.8
-10.7
-218 ± 6
-206 ± 3
-197 ± 2
-173 ± 4
-227 ± 9
-202 ± 2
23/03/11
26.8
-9.0
-234 ± 2
-209 ± 3
-198 ± 2
-182 ± 5
-234 ± 2
-207 ± 2
05/04/11
29.2
-4.9
-219 ± 4
-206 ± 5
-205 ± 4
-208 ± 6
-220 ± 5
-208 ± 2
19/04/11
27.7
-7.5
-229 ± 2
-219 ± 2
-215 ± 2
N.D.
-235 ± 2
-213 ± 1
03/05/11
31.1
-1.7
-237 ± 6
-224 ± 2
-213 ± 3
-210 ± 3
-235 ± 3
-223 ± 2
18/05/11
31.8
-0.5
-219 ± 2
-205 ± 2
-197 ± 3
-177 ± 2
-213 ± 2
-203 ± 2
17/06/11
32.0
0.7
-225 ± 3
-211 ± 2
-196 ± 4
-191 ± 2
N.D.
-209 ± 2
30/06/11
31.2
-1.6
-224 ± 2
-208 ± 2
-200 ± 2
-173 ± 7
-212 ± 2
-209 ± 2
15/07/11
30.0
-3.6
-202 ± 2
-192 ± 2
-185 ± 2
-178 ± 3
-215 ± 3
-191 ± 2
27/07/11
26.3
-9.9
-213 ± 3
-192 ± 3
-195 ± 2
-172 ± 2
-193 ± 7
-194 ± 2
08/08/11
29.4
-4.6
-219 ± 7
-198 ± 4
-197 ± 5
-176 ± 7
-231 ± 4
-200 ± 2
22/08/11
26.9
-8.9
-224 ± 2
-195 ± 2
-182 ± 5
-183 ± 3
-195 ± 2
-199 ± 2
06/09/11
26.8
-9.0
-217 ± 6
-210 ± 2
-213 ± 4
-209 ± 3
-211 ± 3
-212 ± 2
21/09/11
30.1
-3.4
-215 ± 2
-201 ± 2
-182 ± 2
-191 ± 3
N.D.
-198 ± 1
11/10/11
32.8
1.2
-214 ± 4
-192 ± 2
-184 ± 3
-189 ± 4
-227 ± 2
-194 ± 2
28/10/11
32.2
0.1
-217 ± 2
-188 ± 2
-181 ± 3
-184 ± 2
-207 ± 4
-190 ± 2
15/11/11
28.9
-5.5
-208 ± 12
-194 ± 3
-187 ± 5
-179 ± 6
-217 ± 2
-192 ± 2
28/11/11
31.7
-0.7
-217 ± 2
-192 ± 2
-189 ± 2
-180 ± 3
-197 ± 2
-195 ± 1
16/12/11
31.7
-0.7
-198 ± 7
-179 ± 4
-173 ± 5
-187 ± 4
N.D.
-180 ± 2
nC16:1*: double bond at the ω7 position.
All fatty acids were depleted in D compared to water with the fractionation
factor εlipid/water ranging from -173 to
-237 ‰, all following a similar seasonal trend with the highest
degree of fractionation during spring to early summer, and early autumn
(Fig. 5; Table 1). The lowest degree of fractionation (most positive
εlipid/water values) was in general during late autumn
and the winter months.
The D / H fractionation between fatty acids and North Sea water for fatty
acids derived from suspended particulate matter in North Sea water samples.
Plotted are the εlipid/water values of
nC14:0, nC16:1, nC16:0, nC18:0 fatty
acids and nC20:5 PUFA.
Source affects the hydrogen isotopic composition of individual fatty
acids
The nC20:5 PUFA is the most specific fatty acid detected in North Sea SPM
and is exclusively produced by algae (Carrie et al., 1998). Here the nC20:5
PUFA is generally one of the most D-depleted fatty acids (Fig. 5), which is
in agreement with culture studies that show that photoautotrophic
microorganisms produce fatty acids that are depleted in D with
εlipid/water values between -160 and -220 ‰
(Heinzelmann et al., 2015b, and references therein), while heterotrophic
microorganisms on the other hand produce fatty acids with
εlipid/water values ranging between -150 and
+200 ‰ (Heinzelmann et al., 2015b, and references therein).
Furthermore, its concentration increased at the time of the phytoplankton
bloom (Fig. 4). Interestingly, after the phytoplankton bloom, when the
abundance of pelagic algae had decreased (Fig. 4), it became more enriched in
D (Fig. 5). This enrichment might be due to changes in the relative
contribution of source organisms. In diatoms nC20:5 PUFA can be one of the
most abundant fatty acids, while Phaeocystis produces it in minor
amounts only (Table S6). During the spring bloom both organisms will
contribute to the fatty acid pool, while afterwards diatoms are the main
source (Fig. 2; Table S2). A changing contribution from different species
could potentially affect the hydrogen isotopic composition of a fatty acid
even if the source organisms are all photoautotrophic phytoplankton. For
instance, colony-forming algae such as Eudorina unicocca and
Volvox aureus have been shown to fractionate much less against D
than other algae (Zhang et al., 2007; Heinzelmann et al., 2015b). Indeed,
Phaeocystis, although belonging to a different phylum, is also a
colony-forming algae. However, if this were the reason for the changing D
content of the nC20:5 PUFA following the spring bloom, it would then be
expected to become more D-depleted with a reduced contribution from
Phaeocystis, not D-enriched. A potential reason for the relatively
D-enriched Phaeocystis lipids could be excretion of large amounts of
D-depleted organic matter, leading directly or indirectly, through the
isotopic composition of cell water, to D-enriched lipids (Sachs et al.,
2016), as has been observed for colony-forming algae. Increased organic
matter excretion by phytoplankton at the end of the bloom could therefore be
another mechanism explaining the D enrichment of the nC20:5 PUFA. Another
possible reason could be that after the bloom and due to nutrient limitation,
phytoplankton hypothetically might use more storage products potentially
leading to an increased production of NADPH via other pathways than
photosynthesis. The NADPH produced by photoautotrophs via photosystem I is
depleted in D (X. N. Zhang et al., 2009), while NADPH produced via the
pentose phosphate (OPP) pathway and the tricarboxylic acid (TCA) cycle is
relatively enriched in D (Heinzelmann et al., 2015b; X. N. Zhang et al.,
2009). The utilization of storage products would lead to an increased
reduction of NADP+ to NADPH via both the OPP pathway and the TCA cycle
leading to more positive εlipid/water values of the
nC20:5 PUFA after the bloom. In batch culture with increasing nutrient
limitation fatty acids of algae became enriched in D with increasing age of
the culture (Heinzelmann et al., 2015b) potentially due to a shift in the
origin of NADPH or the excretion of organic matter or a combination of
multiple factors.
Of all other fatty acids nC14:0 was generally the most D-depleted fatty
acid, possibly suggesting a higher contribution of photoautotrophic organisms
to this fatty acid. However, it has been reported that fatty acids in general
seem to become more enriched in D with chain length both in cultures and in
environmental samples, which might play a minor role here as well (Jones et
al., 2008; Campbell et al., 2009; Osburn et al., 2011). The quite similar
εlipid/water values of nC16:0 (-179 to
-224 ‰) and nC16:1 (-173 to -215 ‰) suggest similar
sources for the two fatty acids. The least negative
εlipid/water values for nC18:0 suggest that the sources
of this fatty acid might differ from the other fatty acids, i.e. with a higher
contribution of heterotrophs compared to the other fatty acids.
Alternatively, as discussed above fatty acids become more enriched in D with
increasing chain length both in cultures and environmental samples (Jones et
al., 2008; Campbell et al., 2009; Osburn et al., 2011), which could be part of
the reason why the nC18:0 is relatively enriched in D.
Fatty acid profiles of representatives of most members of the phytoplankton
and bacterial community observed at our site have been previously reported
(Table S6) and can be used to assess the main sources of the different fatty
acid pools. The main bacterial contributors to the nC16:0 and
nC16:1ω7 fatty acids are most likely members of
Alteromonadales and Halomonadaceae, while the majority
of bacterial contributors to the nC14:0 and nC18:0 fatty acid are derived
from Puniceicoccales (Table S6). Both
Flavobacteriales and Rhodobacteraceae, which make up a
large part of the total bacteria reads, will hardly contribute to the
measured isotopic signal as they have been reported to produce only traces of
nC14:0, nC16:0, nC16:1ω7 or nC18:0 fatty acids (Table S6).
The observed phytoplankton species are main contributors to the nC14:0,
nC16:0 and nC16:1ω7 fatty acid pools but contribute relatively
little to the nC18:0 fatty acid pools. Phaeocystis produces mainly
the nC14:0 and nC16:0 fatty acids (Hamm and Rousseau, 2003; Nichols et
al., 1991).
Overall, the majority of the nC14:0 fatty acid pool will likely be
predominately derived from photoautotrophs (Table S6), which potentially
explains why the nC14:0 is almost always the most depleted fatty acid. The
nC18:0 fatty acid, on the other hand, will be largely derived from
heterotrophic bacteria (Table S6) resulting in more D-enriched signal
compared to that of the nC14:0 fatty acid. However, the hydrogen isotopic
composition of the nC18:0 fatty acid still falls within the range for
photoautotrophic organisms, albeit at the higher end, suggesting that
although it is only produced in minor amounts by phytoplankton, a relatively
high abundance of phytoplankton could still determine its isotopic
composition.
None of the fatty acids measured in the North Sea SPM have εlipid/water values which fall in the range of those predicted for
chemoautotrophs (-264 to -345 ‰; Heinzelmann et al., 2015b, and
references therein). This fits with the observation that sequence reads of
chemoautotrophic bacteria accounted for < 3 % of the total
bacterial reads (Fig. 3; Table S3a, b), and thus it is unlikely that this
metabolism plays an important role in this environment.
Linking seasonal changes of hydrogen isotope fractionation to changes
in community metabolism
In general most fatty acids showed a similar seasonal trend with the most
negative ε values in spring and the most positive ε
values in the winter (Fig. 5). In order to assess the dominant metabolism of
the whole microbial community we calculated a weighted average ε
of all measured fatty acids apart from the specific nC20:5 PUFA. The
weighted average εlipid/water (εΣFA) followed the same seasonal trend as the
εlipid/water values of the individual fatty acids
(Figs. 1, 5) and ranged between -180 and -225 ‰ with an average
of -199 ‰.
Compared to the chlorophyll a concentration, the εΣFA followed an opposite seasonal trend; that is, when the
chlorophyll a concentration increased in early April, εΣFA decreased (Fig. 5). The chlorophyll a maximum in
April–May indicates a spring bloom (Fig. 1), which is known to occur annually
in North Sea coastal waters (Brandsma et al., 2012; Philippart et al., 2010)
and corresponds with a shift towards more negative values for
εΣFA, as well as a high abundance of the
algal-derived nC20:5 PUFA (Fig. 4). It is likely that at least during the
spring bloom the majority of the fatty acids are derived from the dominant
algae, i.e. Phaeocystis and diatoms, which make up the majority of
the bloom, leading to a D-depleted signal. Thus, the observation that the
value of εΣFA was more negative during the spring
bloom when the environment is dominated by photoautotrophic microorganisms
(Fig. 3) fits with an increased contribution by photoautotrophs relative to
heterotrophic microorganisms to the fatty acid pool. At the end of the bloom
more positive εΣFA values were observed, which is
in agreement with an increased abundance of heterotrophic bacterioplankton in
previous studies (Sintes et al., 2013), living on released organic material (Alderkamp et al., 2006). This
fits well with previous observations by Brandsma et al. (2012), who studied
both the phytoplankton and bacterial communities during a period of 12
months. Cell counts contained in their study showed that the bacterial cell
counts were lowest during the spring bloom, increased right after and stayed
more or less stable throughout the rest of the sampling period. Phytoplankton
cell counts on the other hand were highest during the bloom and dropped
extremely afterwards with only the cyanobacteria cell counts increasing
slightly in late summer/early autumn. At the same time they showed that in
general the bacteria cell count was 10 times higher than the phytoplankton
cell count. This suggests that the whole environment after the bloom might be
dominated by heterotrophic bacteria. The relative stability of the system
throughout the last decades (Philippart et al., 2000) suggests that the
situation might have been similar during the sampling period described here.
Thus, εΣFA values reflect a mixed signal derived
from mainly photoautotrophic and, to a lesser extent, heterotrophic
microorganisms. Nevertheless, εlipid/water values for all
fatty acids remain in the range of photoautotrophic metabolism (Heinzelmann
et al., 2015b, and references therein), indicating that, overall, the fatty
acids in this coastal seawater are mostly derived from phototrophic
organisms. This is in accordance with the assumption that IPLs (containing
fatty acids) in coastal North Sea waters over the annual cycle were
predominantly derived from phytoplankton (Brandsma et al., 2012). Our results
show that it is possible to study whole community core metabolism in a
natural environment by determining the weighted average D / H ratio of
all fatty acids.