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\begin{document}

\title{Chemical and transcriptomic diversity do not correlate with ascending
levels of social complexity in the insect order Blattodea}



\author[1]{Marek Golian}%
\author[2]{Daniel Friedman}%
\author[1]{Mark Harrison}%
\author[3]{Dino McMahon}%
\author[1]{Jan Buellesbach}%
\affil[1]{University of Münster}%
\affil[2]{UC Davis}%
\affil[3]{Free University of Berlin}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Eusocial insects, such as ants and termites, are characterized by high
levels of coordinated social organization. This is contrasted by
solitary insects, which display more limited forms of collective
behavior. It has been hypothesized that this gradient in
socio-behavioral sophistication is positively correlated with chemical
profile complexity, due to a potentially increased demand for diversity
in chemical communication mechanisms in insects with higher levels of
social complexity. However, this claim has rarely been assessed
empirically. Here, we compare different levels of chemical and
transcriptomic complexity in selected species of the order Blattodea
that represent different levels of social organization, from solitary to
eusocial. We primarily focus on cuticular hydrocarbon (CHC) complexity,
since it has repeatedly been demonstrated that CHCs are key signaling
molecules conveying a wide variety of chemical information in solitary
as well as eusocial insect species. We assessed CHC complexity and
divergence between our studied species of different social complexity
levels as well as the differentiation of their respective repertoires of
CHC biosynthesis gene transcripts. Surprisingly, we did not find any
consistent pattern of chemical complexity correlating with the degree of
social complexity, nor did the overall chemical divergence or
transcriptomic repertoire of CHC biosynthesis genes reflect on the
levels of social complexity. Our results challenge the assumption that
increasing social complexity is generally reflected in more complex
chemical profiles and point towards the need for a more cautious and
differentiated view on correlating complexity on a chemical, genetic,
and social level.%
\end{abstract}%



\sloppy


\textbf{Chemical and transcriptomic diversity do not correlate with
ascending levels of social complexity in the insect order Blattodea}

Marek J. Golian\textsuperscript{1}, Daniel A.
Friedman\textsuperscript{2}, Mark Harrison\textsuperscript{1}, Dino P.
McMahon\textsuperscript{3,4} \& Jan Buellesbach\textsuperscript{1,*}

\textsuperscript{1}Institute for Evolution \& Biodiversity, University
of M\selectlanguage{ngerman}ünster, Hüfferstr. 1, 48149 Münster, Germany

\textsuperscript{2}Department of Entomology, University of California -
Davis, 1 Shields Ave, Davis, CA 95616, USA

\textsuperscript{3}Institute of Biology -- Zoology, Freie Universität
Berlin, Unter den Eichen 87, 12205 Berlin, Germany

\textsuperscript{4}Department for Materials and Environment, BAM Federal
Institute for Materials Research and Testing, Unter den Eichen 87,
D-12205 Berlin, Germany

*Correspondence: Jan Buellesbach\emph{buellesb@uni-muenster.de}

\textbf{Keywords:}

Chemical ecology, insect societies, eusociality, cuticular hydrocarbons,
transcriptomes, biosynthesis genes, cockroaches, termites

Abstract

Eusocial insects, such as ants and termites, are characterized by high
levels of coordinated social organization. This is contrasted by
solitary insects, which display more limited forms of collective
behavior. It has been hypothesized that this gradient in
socio-behavioral sophistication is positively correlated with chemical
profile complexity, due to a potentially increased demand for diversity
in chemical communication mechanisms in insects with higher levels of
social complexity. However, this claim has rarely been assessed
empirically. Here, we compare different levels of chemical and
transcriptomic complexity in selected species of the order Blattodea
that represent different levels of social organization, from solitary to
eusocial. We primarily focus on cuticular hydrocarbon (CHC) complexity,
since it has repeatedly been demonstrated that CHCs are key signaling
molecules conveying a wide variety of chemical information in solitary
as well as eusocial insect species. We assessed CHC complexity and
divergence between our studied species of different social complexity
levels as well as the differentiation of their respective repertoires of
CHC biosynthesis gene transcripts. Surprisingly, we did not find any
consistent pattern of chemical complexity correlating with the degree of
social complexity, nor did the overall chemical divergence or
transcriptomic repertoire of CHC biosynthesis genes reflect on the
levels of social complexity. Our results challenge the assumption that
increasing social complexity is generally reflected in more complex
chemical profiles and point towards the need for a more cautious and
differentiated view on correlating complexity on a chemical, genetic,
and social level.











\section*{Introduction}

{\label{introduction}}

Insects have exploited chemical signaling as their primary communication
mode (Greenfield 2002; Missbach et al. 2014). Particularly cuticular
hydrocarbons (CHCs), nonpolar lipids coating the epicuticle of
terrestrial insects, have consistently been demonstrated as pivotal
signals and cues in a wide variety of chemical communication systems
(Blomquist and Bagnères 2010; Blomquist and Ginzel 2021). Predominantly,
CHCs have been shown to be major signaling molecules for nestmate
recognition in eusocial taxa (e.g. Leonhardt et al. 2016; Sprenger and
Menzel 2020) and for sexual and species-specific signaling mechanisms in
solitary taxa (e.g. Chung and Carroll 2015; Shahandeh et al. 2018). It
has been suggested that chemical profiles in eusocial insect societies,
with their multiple castes, task allocations and collective processes,
display a higher degree of complexity than in solitary species
(Linksvayer 2015; Korb and Thorne 2017; Kronauer and Libbrecht 2018;
Holland and Bloch 2020). However, there is no consensus as to how to
assess, quantify, and compare the degree of CHC profile complexity
across different species (Friedman et al. 2020; Holland and Bloch 2020).
Chemical complexity in CHC profiles has previously been assessed as the
total number of compounds of a given type, or total ratio of
structurally more complex CHC compounds (\emph{i.e.,} unsaturated and
methyl-branched CHCs) versus less complex compounds
(\emph{i.e.,}straight-chain CHCs) (Martin and Drijfhout 2009; Kather and
Martin 2015). Taking this approach, Kather and Martin (2015) did not
find any correlation between CHC diversity and social complexity in a
meta-study comparing chemical profiles in eusocial and solitary
Hymenopteran species.

Like the Hymenoptera (ants, bees, wasps, sawflies), the order Blattodea
encompasses all known levels of social complexity, from solitary
cockroaches to obligately eusocial termites. Particularly in termites,
which generally lack well-developed eyes, chemical signaling has been
repeatedly demonstrated to be a wide-spread and dominant form of
communication (Van der Meer et al. 1999; Bagnères and Hanus 2015). In
this context, CHCs have been particularly well investigated as
fundamental signaling cues for caste differentiation, nestmate
recognition and reproductive status conveyance in termites (Liebig et
al. 2009; Weil et al. 2009; Hoffmann et al. 2014). But in solitary
cockroaches as well, CHCs appear to carry out diverse signaling
functions, such as kin recognition and aggregation (Rivault et al. 1998;
Lihoreau and Rivault 2008; Hamilton et al. 2019). To the best of our
knowledge, no studies have yet attempted to directly compare CHC
diversity across different levels of social complexity within the order
Blattodea. In the present study, we compare levels of complexity between
CHC profiles of representative solitary and social species within the
order Blattodea. Through the availability of whole-genome transcriptomes
for our selected study species, we additionally explored CHC
biosynthesis gene transcript diversity and correlate it with the
different levels of social complexity as well as the respective CHC
compound classes they are predominantly associated with.

Our cockroach study species are \emph{Blatta orientalis} (Blattodea:
Blattidae) and \emph{Blattella germanica} (Blattodea: Ectobiidae). The
former is known as one of the most common cockroach pest species in
temperate regions around the world (Thoms and Robinson 1986, 1987;
Edwards and Short 1993), whereas the latter is well-established in
CHC-based chemical communication research (Gu et al. 1995; Rivault et
al. 1998; Fan et al. 2003; Pei et al. 2019). Within the termites,
although all species are considered eusocial, the level of organization
and social complexity varies across different termite societies in terms
of colony size, worker sterility and morphological differentiation of
castes (Abe 1987; Thorne 1997; Korb and Hartfelder 2008; Korb et al.
2015). One piece life type (OPT) or single-site termite species have a
low social complexity with small colonies and totipotent workers,
spending their entire lives nesting and feeding within the same
enclosed, wood-based habitat (Noirot 1970; Shellman-Reeve 1997; Korb and
Thorne 2017). They display an exceptionally flexible caste development,
with larval offspring retaining the capability to differentiate into
reproductives, alates or soldiers well into their late instar stages
(Noirot 1985b; Korb and Hartfelder 2008). This pattern is widely
considered to be the ancestral form and is characterized by a low to
intermediate form of social complexity (Noirot and Pasteels 1987, 1988;
Legendre et al. 2008). Low social complexity OPT termites are
represented in our study by the two species \emph{Kalotermes
flavicollis} and \emph{Neotermes castaneus}(Blattodea: Kalotermitidae).
Separate life type (ST) or central-site termite species divide their
nesting place from their multiple food sources and are thus
characterized by foraging (Noirot 1970; Abe 1987; Shellman-Reeve 1997).
As opposed to OPT termites, ST termites are more constrained in their
development due to an early instar separation into a wingless (apterous)
line that can further differentiate into permanently sterile soldiers
and workers and a nymphal line that eventually develops into sexual
alates (Noirot 1985a; Korb and Hartfelder 2008; Roisin and Korb 2010).
This pattern characterizes the most socially complex termite species
which can reach much larger and more differentiated colonies than OPT
termites (Noirot and Pasteels 1987, 1988; Legendre et al. 2008).
\emph{Reticulitermes flavipes} and\emph{Coptotermes formosanus}
(Blattodea: Rhinotermitidae) as well as\emph{Mastotermes darwiniensis}
(Blattodea: Mastotermitidae) represent ST termites in our study, whereas
the latter constitutes a particularly interesting case: The species
\emph{M. darwiniensis} is the only extant member of the family
Mastotermitidae and phylogenetically represents the most basal termite
lineage. However, this species displays all characteristics of ST
termites with large colonies, constrained developmental pathways and a
true worker caste (Inward et al. 2007b; Krishna et al. 2013). Since the
low social complexity OPT has been widely hypothesized to be the
ancestral termite state, the clear ST pattern of \emph{M. darwiniensis}
as basal and most ancient extant termite lineage represents an
unresolved and frequently debated conundrum (Inward et al. 2007a; Korb
and Thorne 2017; Chouvenc et al. 2021).

We tested the central hypothesis that chemical and social complexity are
correlated, and that, concordantly, the genetic repertoire for CHC
biosynthesis gene transcripts increases with the level of social
complexity. We focused on structurally complex CHC compounds
(unsaturated and methyl-branched) and the candidate genes that
potentially play a role in their biosynthesis and variation (mostly
desaturases and microsomal fatty acid synthases, see Fig. 1 and Holze et
al., 2021). Moreover, we constructed a chemical dendrogram based on CHC
divergence, compared it to the molecular phylogeny of our study species,
and correlated CHC biosynthesis gene transcript counts with the
respective CHC compound counts per analyzed species.



\section*{Materials \& Methods}

{\label{materials-methods}}

\subsection*{Tested termite and cockroach
species}

{\label{tested-termite-and-cockroach-species}}

In a previous study, chemical profiles analyzed among the same taxa
where found to be solely discriminable on the species level, rather than
on the colony (termites) or population (cockroaches) level (Golian et
al. 2022). Therefore, we restricted ourselves to two respective
laboratory colonies per termite species and two respective laboratory
populations per cockroach species. All species used in this study were
maintained in the Federal Institute of Materials Research and Testing
(BAM), Berlin. Termite colonies of \emph{R.~flavipes, C. formosanus,
K.~flavicollis} and \emph{N.~castaneus} were kept in a darkened room at
26°C and 84\% humidity, and colonies of~\emph{M.~darwiniensis} ~were
maintained at 28°C and 83\% humidity. All colonies were fed regularly
with pre-decayed birch wood. The cockroaches~\emph{B.~germanica}
~and~\emph{B.~orientalis} ~were maintained in mixed open rearing boxes
in 12-hour light/dark cycles at 26 °C and 50 \% humidity, from the day
of egg-laying until disposal of older adults. Cockroaches were reared on
a mixture of 77.0 \% dog biscuit powder, 19.2 \% oat flakes, 3.8 \%
brewer's yeast and supplied with water ad libitum and weekly with apple
and carrot slices. All cockroaches and termites were freeze-killed and
stored at -20 °C until further analysis.

\subsection*{CHC extraction and
analysis}

{\label{chc-extraction-and-analysis}}

To yield comparable amounts of extracts between our cockroaches and
termites that vary largely in size, we had to adjust extraction volumes
and pool smaller individuals. For this, we used 300 and 3000 \selectlanguage{greek}µ\selectlanguage{english}l MS pure
hexane (UniSolv, Darmstadt, Germany) on single \emph{B. germanica}
and\emph{B. orientalis} individuals, respectively, and 100 \selectlanguage{greek}µ\selectlanguage{english}l on pools
of 3 individuals per termite species for extraction. Extraction
procedures were then equalized to ensure comparability. Extractions were
performed in glass vials (20 ml for cockroaches and 2 ml for termites,
Agilent, Santa Clara, California, USA) on an orbital shaker (IKA KS 130
Basic, Staufen, Germany) for 10 minutes. Afterwards, the extract was
evaporated under a constant stream of gaseous carbon dioxide. Then, it
was resuspended in 5~\selectlanguage{greek}μ\selectlanguage{english}l in a hexane solution containing 7,5 ng/\selectlanguage{greek}μ\selectlanguage{english}l
dodecane (C12) as an internal standard. 3 \selectlanguage{greek}μ\selectlanguage{english}l of the resuspended extract
were then injected into a gas-chromatograph coupled with a tandem mass
spectrometer (GC-MS/MS) (GC: 7890B, Triple Quad: 7010B; Agilent
Technologies, Waldbronn, Germany) equipped with a fused silica column
(DB-5MS ultra inert; 30 m x 250 \selectlanguage{greek}μ\selectlanguage{english}m x 0.25 \selectlanguage{greek}μ\selectlanguage{english}m; Agilent J\&W GC columns,
Santa Clara, California, USA) in splitless mode at a temperature of 300
\selectlanguage{ngerman}°C with helium used as a carrier gas under constant flow of 2.25 ml/min.
The temperature program started at 60 °C held for 5 min, increasing 20
°C per minute up to 200 °C and then increasing 3 °C per minute to the
final temperature of 325 °C, held for 5 min.

CHC peak detection, integration, quantification and identification were
all carried out with Quantitative Analysis MassHunter Workstation
Software (Version B.09.00 / Build 9.0.647.0, Agilent Technologies, Santa
Clara, California, USA). The pre-defined integrator Agile 2 was used for
the peak integration algorithm to allow for maximum flexibility,
quantification was carried out over total ion chromatograms (TIC). All
peaks were then additionally checked for correct integration and
quantification, and, where necessary, re-integrated manually. CHC
compound identification was then carried out based on their
characteristic diagnostic ions and retention indices. Analysis was
focused exclusively on non-polar CHC compounds due to their repeatedly
demonstrated involvement in chemical signaling in both solitary and
eusocial Blattodea (e.g. Lihoreau and Rivault 2008; Hoffmann et al.
2014; Hamilton et al. 2019). The obtained values for the absolute peak
area integrals were standardized by dividing them through the total of
all CHC peak area integrals per sample, generating relative proportions
for all CHC compounds. These proportions were then summarized for the
individual CHC compound classes. Sample sizes for our individual species
were \emph{B. germanica} : 9, \emph{B.~orientalis} : 11, \emph{C.
formosanus} : 5, \emph{K. flavicollis} : 4, \emph{M. darwiniensis} :
4,\emph{N. castaneus} : 5 and \emph{R. flavipes} : 5. We focused on
termite workers to obtain the general colony-specific chemical profiles
as the vast majority of individuals constituting the respective colonies
are workers (Korb 2007; Roisin and Korb 2010; Korb and Thorne 2017).
Moreover, we attempted to render our study comparable to other studies
on chemical complexity in eusocial species also focusing exclusively on
profiles obtained from the worker caste (Martin and Drijfhout 2009;
Kather and Martin 2015). Similarly, we pooled the sexes of both
respective cockroach species to focus on representative species-specific
chemical profiles, with less emphasis on the more subtle sex-specific
differences (Pei et al. 2021).

\subsection*{Comparison of chemical and phylogenetic
divergence}

{\label{comparison-of-chemical-and-phylogenetic-divergence}}

To standardize the absolute peak area values for chemical clustering,
the normalization method of the function ``decostand'' of the community
ecology R package ``vegan'' was used (Oksanen et al. 2008), based on the
following formula:

\begin{equation}
T_{x,y}=\ \frac{P_{x,y}}{\sqrt{\sum P_{y^{2}}}}\nonumber \\
 \end{equation}

T\textsubscript{x,y} refers to the transformed peak area x of individual
y, P\textsubscript{x,y} to the absolute peak area x of individual y and
\selectlanguage{greek}Σ \selectlanguage{english}P\textsubscript{y}\textsuperscript{2} to the squared sums of all
absolute peak areas of individual y. This widely applied method for
normalizing ecological data was chosen to make the peak areas comparable
between our groups, to highlight the relative peak area differences and
to correct for size-dependent variation. Agglomerative hierarchical
cluster analysis (``\textbf{U} nweighted \textbf{P} air-\textbf{G}
roup\textbf{M} ethod with \textbf{A} rithmetic means'', \emph{i.e.}
UPGMA) was performed with the R package ``ape'' (Paradis et al. 2004),
based on average chemical Manhattan distances reflecting the median CHC
divergence separating the different cockroach and termite species. The
formula for calculating Manhattan distances is as follows:

\begin{equation}
\sum{[Y_{j}-Y_{k}]}\nonumber \\
 \end{equation}

The actual difference between two data points, in this case
Y\textsubscript{j} and Y\textsubscript{k}, is used based on the total
amount of CHC variation between the species. In contrast with Euclidean
distance where squared differences are used, the Manhattan distance is
less prone to be dominated by single large differences between the
compared component. It has thus been suggested that for multidimensional
phenotypes such as CHC profiles, the Manhattan distance metric is the
most ecologically meaningful (Oksanen 2009). The molecular phylogeny was
obtained and adapted from the latest published Blattodea phylogeny in He
et al. (2021). A Mantel test (Mantel 1967), conducted with the R package
``ade4''~(Dray and Dufour 2007), compared the molecular distances based
on the published Blattodea phylogeny with the average Manhattan CHC
divergence. The Mantel test was performed five times with 9999
permutations for each single test, the average probability is presented.

\subsection*{Analysis of transcriptomic gene
counts}

{\label{analysis-of-transcriptomic-gene-counts}}

We retrieved translated whole genome transcriptome sequences based on
whole-body RNA extractions for each of the seven investigated Blattodea
species as described in He et al. (2021). Total RNA was isolated from
individuals for all species. Due to the large body size, adult
cockroaches were cut into 4-6 parts for separate extraction, followed by
re-pooling. For the extraction itself, samples were suspended in
pre-cooled Trizol (Thermo Fisher Scientific) and homogenized twice at 10
s at 2 M/s with a 5-mm steal bead (Qiagen) using a tissue homogenizer
(MP Biomedicals). Total RNA was isolated with a chloroform extraction,
followed by isopropanol precipitation, according to instructions from
Trizol. Extracted total RNA was dissolved in RNA storage solution
(Ambion) and then incubated with 2 units of TurboDNase (Ambion) for 30
min at 37 \selectlanguage{ngerman}°C, followed by purification with an RNAeasy Mini kit (Qiagen)
according to manufacturer's instructions. Quantity and quality of RNA
were determined by Qubit and Bioanalyzer 2100, respectively. Following
pooling described in sample collection part, total RNA was used to
construct barcoded cDNA libraries using a NEXTflex\selectlanguage{english} Rapid Directional
mRNA-seq kit (Bioo Scientific). Briefly, mRNA was enriched using poly-A
beads from total RNA and subsequently fragmentated. First and
second-strand cDNA was synthesized and barcoded with NEXTflex\selectlanguage{english}RNA-seq
Barcode Adapters. The libraries were sequenced on an Illumina
NextSeq500/550 platform at Berlin Center for Genomics in Biodiversity
Research (BeGenDiv). We obtained orthologous sequences of enzymes which
have been selected according to a demonstrated function in CHC
biosynthesis via targeted knockdown studies (summarized in Holze et al.
2021) from NCBI. In order to estimate numbers of transcripts orthologous
to these enzymes, we first created Hidden Markov Models (HMMs) for each
of their protein sequences. For this, each of the query sequences was
blasted against a database of proteomes from 17 insect genomes
(\emph{Acyrthosiphon pisum, Bemisia tabaci, Blattella germanica,
Clitarchus hookeri, Coptotermes formosanus, Cryptotermes secundus,
Diploptera punctata, Drosophila melanogaster, Glossina morsitans,
Locusta migratoria, Macrotermes natalensis, Medauroidea extradentata,
Musca domestica, Periplaneta americana, Rhopalosiphum maidis, Stomoxys
calcitrans, Zootermopsis nevadensis} ) with blastp (version 2.7.1+,
Camacho et al. 2009). Blast output was filtered to contain only hits
with an e-value \textless{} 1e\textsuperscript{-10} and a minimum
sequence identity of 50\%. For each query gene, protein sequences of all
significant hits were retrieved from the protein database and aligned
with PRANK (version v.170427; Loytynoja 2014) at default settings.
Hidden Markov Models (HMM) were created for each alignment using
hmmbuild (version 3.1b2; Wheeler and Eddy 2013) at default settings.
These HMMs were then used to search the proteomes of our seven focal
Blattodea species using hmmsearch with a maximum e-value of
1e\textsuperscript{-5}. Output of these hmm-searches were then filtered
to contain only hits with a score of at least 100. If a transcript
appeared in multiple lists, it was attributed to the query HMM for which
it received the highest score. Finally, to verify these results, we
blasted all transcript sequences against the swissprot database
(accessed November 2020) with blastp (version 2.7.1+; Altschul et al.
1990). Any transcripts without clear orthology to the gene of interest
were then excluded from the transcript counts. We performed used a
generalized linear model (GLM) with Poisson family distribution to
compare the variation in transcript counts among the levels of social
complexity in our tested species and visualized the results with a
heatmap, utilizing the function ``heatmap'' provided by the R package
``stats''. Furthermore, we compared total gene transcript counts with
the total number of detected CHC compounds per species with a
\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} (chi-square) test.



\section*{Results}

{\label{results}}

We identified 134 CHC compounds in total from our representative termite
and cockroach species (Tab. S1). The six major CHC compound classes
detected were \emph{n} -alkanes, \emph{n} -alkenes, alkadienes as well
as mono-, di-, and tri-methyl-branched alkanes (Fig. 2). The different
compound classes greatly vary in relative amounts across all species and
not all classes were observed in each species. On average,\emph{n}
-alkanes show higher relative abundancies in termites (29.1 \%) than in
cockroaches (15.43 \%), whereas di-methyl-branched alkanes show the
reversed pattern with much higher average abundancies in cockroaches
(25.96 \%) than in termites (0.027 \%). Tri-methyl alkanes, on the other
hand, only occur in detectable quantities in \emph{B. germanica} .
Alkadienes were only found in Rf, \emph{M. darwiniensis} and \emph{N.
castaneus} , with minimal trace occurrences also in \emph{B. orientalis}
. Generally, mono-methyl-branched alkanes were the most abundantly
detected compound class across the tested cockroach and termite species,
however, they occurred in comparably low quantities in \emph{M.
darwiniensis} and \emph{N. castaneus} . Unsaturated compounds, generally
considered to be among the structurally more complex CHCs indicating
higher chemical complexity together with methyl-branched alkanes (Martin
and Drijfhout 2009; Kather and Martin 2015), occur inconsistently in two
high (ST) and one low (OPT) social complexity termite species, but only
in traces in the cockroaches. However, the most structurally complex
methyl-branched alkanes with three methyl branches occur exclusively in
just the cockroach species \emph{B. germanica} . Moreover, the
structurally most simple CHC profile, consisting almost exclusively
of\emph{n} -alkanes and mono-methyl-branched alkanes, was found in the
high social complexity termite \emph{C. formosanus} .

The molecular phylogeny of our tested termite and cockroach species
mostly mirrors their respective levels of social complexity except
for\emph{M. darwiniensis} and \emph{C. formosanus} , which represents
the most basal termite group despite displaying a high level of social
complexity (Fig. 3). This is not at all reflected in their chemical
phylogeny based on the average CHC divergence between the species.
Namely, the most highly supported cluster (99 Bootstrap) encompasses a
solitary (\emph{B. orientalis} ), highly social (\emph{C. formosanus} )
and lowly social (\emph{K. flavicollis} ) species. Moreover, all levels
of social complexity that cluster together in the molecular phylogeny
are basically broken off in the chemical phylogeny, with no recognizable
pattern. Unsurprisingly, a Mantel test found no significant correlation
between the molecular and chemical phylogeny (r = 0.3971, P = 0.1291).

Comparing overall CHC biosynthesis gene transcript counts with the total
number of CHC compounds detected in each species, we found no
significant correlation between the quantities (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} --
test, r=0.12, p=0.79; Fig. 4). \emph{R. flavipes} has the highest
transcript counts (191) but the third lowest CHC compound count (37),
conversely,\emph{M. darwiniensis} has the lowest transcript count (111)
but the second highest CHC compound count (59). Again, no trend towards
the different levels of social complexity could be detected, which is
best exemplified in the three high social complexity termite species,
where both the highest (\emph{R. flavipes} ) and the lowest (\emph{M.
darwiniensis} ) number of transcripts as well as the second highest
(\emph{M. darwiniensis} ) and the lowest number (\emph{C. formosanus} )
of CHC compounds was detected. Across all investigated CHC biosynthesis
gene transcripts (Tab. 1), counts did not vary systematically by social
complexity level (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}= 1.11, df = 1, p = 0.29), which
is also apparent in a heat map representing the individual transcript
counts per species normalized by their average relative abundancies
(Fig. 5).



\section*{Discussion}

{\label{discussion}}

\subsection*{CHC divergence and variation in relation to social
complexity}

{\label{chc-divergence-and-variation-in-relation-to-social-complexity}}

We compared chemical and associated transcriptomic complexity between
Blattodea species with increasing levels of social organization.
Overall, we did not find a consistent correlative pattern of CHC-based
chemical complexity paralleling the different levels of social
complexity in our representative Blattodea species. These results point
to large categorical differences in CHC profiles across species, which
appear to be independent from their level of social organization.

CHC divergence based on average chemical distances between the species
neither reflects the different levels of complexity nor the phylogenetic
divergence within the Blattodea (Fig. 3). \emph{M. darwiniensis} , the
most basal termite lineage (Inward et al. 2007b; Krishna et al. 2013)
chemically clusters together with both a high (\emph{R. flavipes} ) and
a low (\emph{N. castaneus} ) social complexity termite, and the solitary
cockroach \emph{B. orientalis} clusters with both a high (\emph{C.
formosanus} ) and a low (\emph{K. flavicollis} ) social complexity
termite. It has been hypothesized that chemical divergence clearly
differing from an established molecular phylogeny indicates selection on
chemical profiles for different functions overriding their phylogenetic
information (Marten et al. 2009; Buellesbach et al. 2013). However, our
chemical divergence does not display any pattern congruent with the
social hierarchy of our study species, rendering any assumptions on
selection for CHC functions reflective of the species' respective social
complexity highly unlikely. Concerning counts of gene transcripts
stemming from orthologs of CHC biosynthesis genes from other insect
species, these do neither quantitatively correlate with higher levels of
social complexity nor with the total number of CHC compounds detected in
each of our study species.

Future work could include more species as transcriptomes, genomes and
chemical profiles become available, and utilize scalable frameworks such
as phylogenetically-contrasted regression and Bayesian ancestral state
reconstruction models (Simon et al. 2019). Additionally, caste-specific
CHC variation in eusocial taxa could be taken into account in future
studies as well, potentially adding another layer of complexity, despite
the accompanying issues for direct comparability with solitary taxa.

\subsection*{}

{\label{section-8}}

\subsection*{CHC biosynthesis gene transcript variation across the
studied Blattodea
species}

{\label{chc-biosynthesis-gene-transcript-variation-across-the-studied-blattodea-species}}

Acetyl-CoA carboxylase (ACC) catalyzes the first and rate-limiting step
in CHC biosynthesis (Barber et al. 2005, see Fig. 1). In each of our
analyzed cockroach and termite species, we found several distinct ACC
transcripts (ranging from 3 in \emph{C. formosanus} to 8 in \emph{B.
germanica} ) based on orthology to the \emph{Drosophila} gene (Tab. 1).
This rich abundance of ACC transcripts strengthens the argument for the
universality of ACC as fundamental catalyst for the first step in CHC
biosynthesis (see also Fig. 5).

For FAS genes, seven of them had already been identified
in\emph{Blatella germanica} , with five showing a significant effect on
CHC compound quantities upon knockdown (Pei et al. 2019). In our
analyzed transcriptomes, we were able to detect transcripts with strong
orthology to two of these five FAS genes (BgFas 4 and 6). Transcripts
with orthology to \emph{BgFas4} were detectable across all seven
species, whereas \emph{BgFas6} transcripts were most abundant in the two
cockroaches and only in three of the five analyzed termites (Tab. 1).
Generally, it has been hypothesized that two types of FAS, cytosolic and
microsomal, differentially impact CHC biosynthesis, with the former
mainly governing non-methylated, straight-chain CHCs, and the latter
being more specific for methylated CHCs (Chung et al. 2014;
Wicker-Thomas et al. 2015, Fig. 1). Since we could not detect any
transcript copies of \emph{BgFas6} in both \emph{M. darwiniensis}
and\emph{N. castaneus} , the two species with the lowest amounts of
methyl-branched alkanes (Fig. 2), it is possible that the
\emph{BgFas6}transcripts stem from a microsomal FAS associated with the
production of methyl-branched alkanes. Intriguingly, for \emph{N.
castaneus} , in addition to showing both the lowest number and
proportion of methyl-branched alkanes, it also shows the lowest
transcript copy number of \emph{FASN2} orthologs, an
oenocyte-specifically expressed\emph{Drosophila} gene with a strong
effect on methyl-branched CHCs and thus speculated to be microsomal
(Chung et al. 2014; Wicker-Thomas et al. 2015).

Unsaturated compounds, whose biosynthesis is crucially dependent on
desaturases (Wicker-Thomas et al. 1997; Coyne et al. 1999; Dallerac et
al. 2000), occur in each of our studied Blattodea species, most
abundantly in \emph{R. flavipes} , \emph{M. darwiniensis} and \emph{N.
castaneus} , intermediately in \emph{B. orientalis} and \emph{B.
germanica} , but only in traces in \emph{K. flavicollis} and \emph{C.
formosanus} (Fig. 2). This partially reflects the respective numbers of
transcripts orthologous to the genes \emph{desat1} and \emph{desat2} ,
with the former being most abundantly represented in \emph{M.
darwiniensis} and \emph{N. castaneus} , and the latter in \emph{R.
flavipes} (Tab. 1).

Genes coding for P450 Decarbonylases of the gene subfamily CYP4G have
been shown to govern the final steps in CHC biosynthesis and have thus
been suggested to be stable, highly conserved and particularly vital
elements in this pathway (Feyereisen 2020; Holze et al. 2021, Fig. 1).
Concordantly, at least one \emph{Cyp4g} gene could be identified in all
insect genomes screened to date (Qiu et al. 2012; Feyereisen 2020). We
found transcripts orthologous to the \emph{Drosophila} gene\emph{Cyp4g1}
as well as the migratory locust \emph{Locusta migratoria}gene
\emph{LmCYP4G102} in all our tested species (Tab. 1). However, their
numbers vary largely with no apparent consistent pattern, hinting at
more transcriptomic variety for these vital CHC biosynthesis elements
than previously assumed.

The assessment of transcript counts as approximation of the actual
genomic repertoire for CHC biosynthesis genes naturally has its limits
and will remain speculative until targeted knockdown studies confirm the
actual functions of the transcripts as well as their underlying genes.
However, analyzing the abundance of unique transcripts per ortholog
allows valuable insights into functional diversity potentially exceeding
the information contained within whole-genome sequences (He et al. 2021;
Sprenger et al. 2021). Correlating transcriptomic diversity directly
with CHC profile variation has been attempted surprisingly rarely
despite its potential to approximate the genetic control of CHC
variation more accurately, as it has repeatedly been shown that the same
genotype can produce different CHC profiles (Holze et al. 2021; Sprenger
et al. 2021). Thus, our findings constitute promising first steps for
future studies with the potential to corroborate our transcriptomic
assessment with target gene counts once further genomic resources become
available.

\subsection*{CHC-based communication mechanisms and outlook for future
studies}

{\label{chc-based-communication-mechanisms-and-outlook-for-future-studies}}

It has long been hypothesized that the complexity of CHC profiles
reflects the complexity of chemically encoded communication mechanisms
necessary to maintain more socially complex insect societies (Korb and
Thorne 2017; Kronauer and Libbrecht 2018; Holland and Bloch 2020).
However, how CHC profiles actually encode biologically relevant
information such as nestmate affiliation or task allocation has remained
largely elusive so far (Buellesbach et al. 2018; Menzel et al. 2019;
Heggeseth et al. 2020). Further elucidation on the exact encoding
mechanisms in CHC profiles and which compound combinations actually
convey chemical information will be instrumental in gaining a better
understanding on how insect populations and societies are maintained at
different levels of social complexity. Furthermore, although insects
generally synthesize the majority of the components in their CHC
profiles themselves (Nelson and Blomquist, 1995; Blomquist and Bagn\selectlanguage{ngerman}ères,
2010), several studies have demonstrated the impact of several biotic
and abiotic factors such as diet, habitat and microbiome on CHC profiles
as well (Fedina et al. 2012; Rajpurohit et al. 2017; Teseo et al. 2019).
Thus, disentangling these factors from the conserved CHC profile
functionalities represents an additional challenge in future studies
that will nevertheless be indispensable to fully comprehend and explore
CHC-mediated communication mechanisms.

Future studies should also consider the occurrence of very-long chained
CHC compounds of up to C58 in Blattodea surface profiles as recently
demonstrated with non-standard analytical methods (Golian et al. 2022).
However, neither exact compound quantifications nor identifications
(\emph{e.g.,} discrimination between \emph{n} -alkanes and methyl-branch
alkanes) are so far possible in this higher chain length range extending
beyond the CHC compounds traditionally accessed and identified through
gas-chromatographic separation (Schnapp et al. 2016; Bien et al. 2019).
Therefore, to include very long-chain CHCs in future analyses, novel
methods are necessary to reliably assess their exact quantities and
compound classes. Moreover, despite CHCs clearly constituting the
dominant, most investigated compounds in chemical signaling (Blomquist
and Bagnères 2010; Chung and Carroll 2015) and have been implied to have
convergently evolved, unifying communication modalities in eusocial
insects (Leonhardt et al. 2016; Funaro et al. 2018), we cannot exclude
the additional potential of non-CHC compounds also used in signaling
which might reflect social complexity (e.g. Hanus et al. 2010; Smith et
al. 2016; Steitz et al. 2019). Lastly, CHC metabolic networks could be
amenable to various kinds of more elaborate complexity analyses such as
metabolic network pathfinding (Kim et al. 2017), identification of
critical connectors (Kim et al. 2019), determination of topological
characteristics (Goryashko et al. 2019), and flux balance analysis
(Beguerisse-Díaz et al. 2018). These types of complexity analyses have,
to our knowledge, not been attempted so far in this context at all and
might largely aid in obtaining a more holistic correlative view on
complexity on a chemical, genetic and social level.



\section*{Conclusions}

{\label{conclusions}}

Overall, we did not find any consistent patterns linking CHC profile
variation, CHC biosynthesis transcriptome diversity, and social
complexity across the seven Blattodea species included in our study.
This is partially reflective of the results Kather and Martin (2015)
obtained in their meta-analysis of solitary and eusocial Hymenopteran
CHC diversity, although this study was lacking the genetic component.
This implies that, at least for our representative species spanning
different levels of social complexity within the order Blattodea,
neither their CHC profiles nor their repertoire of CHC biosynthesis gene
transcripts does reflect any social hierarchy or correlate with their
social complexity. Concerning the genetic background of CHC
biosynthesis, however, it must be taken into account that our general
knowledge remains limited and mostly biased towards
\emph{Drosophila}(Holze et al. 2021), so it is quite possible that more
Blattodea-specific CHC biosynthesis genes exist which have not been
functionally characterized yet and have therefore eluded our
comprehensive gene transcript investigation. Nevertheless, our study
challenges the long-standing assumption of a general correlation between
increasing social complexity and chemical profile sophistication for our
Blattodea study species. Therefore, we strongly suggest more cautious
approaches for assessing, comparing, and interpreting chemical
complexity in insects with different levels of social organization.

\subsection*{}

{\label{section-10}}

\subsection*{Tables}

{\label{tables}}

\textbf{Tab 1} : List of 21 genes with a demonstrated function in the
CHC biosynthesis pathway for which we could detect transcripts in at
least one of our tested cockroach and termite species. The numbers
correspond to the position of the respective gene product in the
biosynthesis pathway (compare to Fig. 1). Gene acronyms, (putative)
functions, NCBI (or Genbank when not available in NCBI) IDs and the
taxon where the gene was originally described are indicated along with
the detected copy numbers in our tested species. The CHC biosynthesis
genes were retrieved from Holze et al. (2021).\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllll@{}}
\toprule
\# & Gene acronym / (putative) function & NCBI or Gen-bank ID & Original
taxon & Bg & Bo & Kf & Nc & Md & Cf & Rf\tabularnewline
\midrule
\endhead
1 & \emph{ACC} / Acetyl-CoA carboxylase & 35761 & \emph{Drosophila
melanogaster} (fruit fly) & 8 & 7 & 7 & 5 & 7 & 3 & 7\tabularnewline
2 & \emph{FASN2} / Fatty acid synthase 2 & 117361 & \emph{Drosophila
melanogaster} & 16 & 19 & 14 & 6 & 11 & 13 & 17\tabularnewline
3 & \emph{FASN3} / Fatty acid synthase 3 & 3355111 & \emph{Drosophila
melanogaster} & 0 & 0 & 1 & 0 & 2 & 0 & 0\tabularnewline
4 & \emph{BgFas4} / Fatty acid synthase & MK605591.1 & \emph{Blatella
germanica} (German cockroach) & 5 & 4 & 2 & 1 & 11 & 2 &
1\tabularnewline
5 & \emph{BgFas6} / Fatty acid synthase & MK605593.1 & \emph{Blatella
germanica} & 6 & 4 & 1 & 0 & 0 & 1 & 1\tabularnewline
6 & \emph{CG5599} / putative NADH dehydrogenase with LaAt activity &
32441 & \emph{Drosophila melanogaster} & 17 & 6 & 17 & 9 & 7 & 7 &
4\tabularnewline
7 & \emph{CG8680} / putative NADH dehydrogenase with LaAt activity &
33744 & \emph{Drosophila melanogaster} & 1 & 0 & 1 & 1 & 3 & 0 &
1\tabularnewline
8 & \emph{Desat1} / Desaturase 1 & 117369 & \emph{Drosophila
melanogaster} & 2 & 2 & 0 & 4 & 4 & 1 & 1\tabularnewline
9 & \emph{Desat2} / Desaturase 2 & 41536 & \emph{Drosophila
melanogaster} & 33 & 23 & 22 & 23 & 10 & 10 & 36\tabularnewline
10 & \emph{Fad2 /} Desaturase F & 44006 & \emph{Drosophila melanogaster}
& 1 & 0 & 0 & 1 & 0 & 1 & 7\tabularnewline
11 & \emph{CG18609} / putative Elongase (ELO) & 37158 & \emph{Drosophila
melanogaster} & 8 & 10 & 10 & 10 & 4 & 7 & 13\tabularnewline
12 & \emph{CG9458} / putative Elongase (ELO) & 41214 & \emph{Drosophila
melanogaster} & 10 & 18 & 10 & 12 & 8 & 6 & 15\tabularnewline
13 & \emph{spidey} / 3-keto-acyl-CoA-reductase (KAR) & 31703 &
\emph{Drosophila melanogaster} & 3 & 1 & 1 & 1 & 2 & 1 &
1\tabularnewline
14 & \emph{Hacd1} / 3-hydroxy-acyl-CoA-dehydratase (HADC) & 34614 &
\emph{Drosophila melanogaster} & 3 & 0 & 2 & 2 & 2 & 2 &
3\tabularnewline
15 & \emph{Hacd2} / 3-hydroxy-acyl-CoA-dehydratase (HADC) & 34762 &
\emph{Drosophila melanogaster} & 1 & 2 & 6 & 2 & 2 & 8 &
3\tabularnewline
16 & \emph{Sc2} / trans-enoyl-CoA-reductase (TER) & 38457 &
\emph{Drosophila melanogaster} & 4 & 2 & 2 & 2 & 1 & 1 &
2\tabularnewline
17 & \emph{NlFAR7} / fatty acyl-CoA reductase (FAR) & MG573162.1 &
\emph{Nilaparvata lugens} (brown planthopper) & 1 & 1 & 0 & 1 & 1 & 9 &
1\tabularnewline
18 & \emph{NlFAR9} / fatty acyl-CoA reductase (FAR) & MG573164.1 &
\emph{Nilaparvata lugens} & 1 & 1 & 0 & 0 & 0 & 0 & 0\tabularnewline
19 & \emph{CG10097} / putative fatty acyl-CoA reductase (FAR) & 3771756
& \emph{Drosophila melanogaster} & 35 & 32 & 28 & 32 & 25 & 38 &
55\tabularnewline
20 & \emph{Cyp4g1} / Cytochrome P450-4g1 & 30986 & \emph{Drosophila
melanogaster} & 10 & 4 & 4 & 5 & 2 & 9 & 19\tabularnewline
21 & \emph{LmCYP4G102} / Cytochrome P450-4g1 & ANW46746.1 &
\emph{Locusta migratoria} (grass hopper) & 3 & 7 & 5 & 6 & 9 & 4 &
4\tabularnewline
\bottomrule
\end{longtable}

\subsection*{}

{\label{section-11}}

\subsection*{}

{\label{section-12}}

\subsection*{Figure legends}

{\label{figure-legends}}

\textbf{Figure 1} : Simplified overview of CHC biosynthesis. The
biosynthesis pathway branches at different stages into different CHC
compound classes. The main CHC compound classes are methyl-branched
alkanes, straight-chain alkanes, alkenes and dienes. Enzyme
abbreviations: ACC: Acetyl-CoA carboxylase, FAS: Fatty acid synthase (m:
microsomal, c: cytosolic), LaAT: Lipoamide acyltransferase, ELO:
Elongase, KAR: 3-keto acyl-CoA-reductase, HADC:
3-hydroxy-acyl-CoA-dehydratase, TER: Trans-enoyl-CoA-reductase, FAR:
Fatty acyl-CoA reductase. CYP4G: Cytochrome P450 Decarbonylase. Numbers
next to the enzymes correspond to the associated gene transcripts we
detected in our tested Blattodea species (compare to Tab. 1). Adapted
from Holze, Schrader, and Buellesbach (2020).

\textbf{Figure 2} : Comparison of average CHC ratios (relative
percentages) from the studied representative termite and cockroach
species, categorized according to their levels of social complexity. The
six major CHC compound classes detected in these species were n-alkanes,
n-alkenes, as well as mono-, di-, tri and tetra-methyl branched alkanes
and are indicated by different colors. Acronyms for the investigated
species are used here and in all subsequent figures as follows: \emph{R.
flavipes} (Rf)\emph{, C.} \emph{formosanus} (Cf)\emph{, K.flavicollis}
(Kf), \emph{N.} \emph{castaneus} (Nc),\emph{M.~darwiniensis} (Md),
\emph{B.} \emph{germanica} (Bg) and\emph{B.} \emph{orientalis} (Bo).
Insect images have been obtained from the Darmstadt Insect Scanner
DISC3D (Str\selectlanguage{ngerman}öbel et al. 2018) and have been kindly provided by Sebastian
Schmelzle.

\textbf{Figure 3} : Comparison of molecular phylogeny (left) and a
chemical dendrogram (right) of our Blattodea study species. The
molecular phylogeny is adapted from He et al. (2021) and the chemical
dendrogram is based on average chemical Manhattan distances reflecting
the median CHC divergence separating the different cockroach and termite
species.

\textbf{Figure 4} : Comparison between counts of CHC biosynthesis gene
transcripts (indicated in blue) and counts of total individual CHC
compounds (indicated in orange) detected in our representative cockroach
and termite species. Correlations between these two metrics were
assessed with a 2 (chisquare) test (r=0.12, p=0.79). Their respective
levels of social complexity are indicated in both cases. Insect images
have been obtained from the Darmstadt Insect Scanner DISC3D (Ströbel et
al. 2018) and have been kindly provided by Sebastian Schmelzle.

\textbf{Figure 5} : Heatmap normalized by average relative abundances of
CHC biosynthesis gene transcript counts (columns) from high (darker
colors) to low (lighter colors) grouped by species and their respective
level of social complexity. The numbers indicated at the gene
transcripts correspond to their respective position in the CHC
biosynthesis pathway (see Fig. 1 and Tab. 1).



\section*{Data Accessibility
Statement}

{\label{data-accessibility-statement}}

All data underlying the presented study will be made available at the
dryad data repository under https://doi.org/10.5061/dryad.cc2fqz6dh.

\textbf{Competing Interests Statement}

The authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a
potential conflict of interest.



\section*{Author Contributions
section}

{\label{author-contributions-section}}

Conceptualization: J. B.; methodology: M.G., J.B., M.H.; validation: J.
B., M.G., M.H.; formal analysis: M.G., J.B., M.H.; investigation: J. B.,
M.G., M.H.; resources: D.P.M.; M.H.; data curation: J. B., M.G., M.H.;
writing---original draft preparation: J. B., D.A.F.; writing---review
and editing: J. B., D.A.F., M.H., D.P.M., M.G.; visualization: J. B.,
D.A.F. supervision: J.B., D.P.M.; project administration: J. B., D.P.M.;
funding acquisition: D.P.M., J.B.







\section*{Acknowledgments}

{\label{acknowledgments}}

We would like to thank Margy Alejandra Esparza Mora and Shixiong Jiang
for their assistance in caring for and providing the termite and
cockroach species as well as Katharina Meyer zu Riemsloh for help in
curating the transcriptome sequences. We further like to thank Sebastian
Schmelzle for providing the insect images. This research was partially
supported by research grants to Daniel A. Friedman (NSF, 20-077 ID
\#2010290), Dino P. McMahon (DFG, MC 436/5-1) and Jan Buellesbach (DFG,
BU3439/1-1).

\section*{Appendix}

{\label{appendix}}

\textbf{Tab. S1} : Retention indices (RI), CHC compound identifications
and the respective relative quantities as well as standard deviations
(in \%) for all tested cockroach and termite species. Non-detectable
amounts of the respective compounds are indicated by hyphens. Where
compound identifications were ambiguous due to multiple possible methyl
branch positions based on the detected ion pairs, all possible compound
configurations are given. Retention indices we calculated according to
the position of detected \emph{n} -alkanes in our samples and, where not
available, with a C21-40 \emph{n} -alkane standard run under the same
conditions. Please note that for compounds beyond C40, the\emph{n}
-alkane positions had to be extrapolated according to the average
distances between \emph{n} -alkanes.\selectlanguage{english}
\begin{longtable}[]{@{}llllllllll@{}}
\toprule
RI & Compound ID & Diagnostic ions & Bg & Bo & Nc & Kf & Md & Cf &
Rf\tabularnewline
\midrule
\endhead
1500 & n-C15 & 212 & - & - & 1.04 \selectlanguage{ngerman}± 0.05 & - & - & - & -\tabularnewline
1700 & n-C17 & 240 & - & - & 0.06 \selectlanguage{ngerman}± 0.03 & - & 0.01 \selectlanguage{ngerman}± 0 & - &
-\tabularnewline
1738 & 3-MeC17 & 239; 56; 224 & - & - & 0.14 \selectlanguage{ngerman}± 0.07 & - & - & - &
-\tabularnewline
2107 & n-C21 & 296 & - & - & 2.33 \selectlanguage{ngerman}± 0.26 & 0.09 \selectlanguage{ngerman}± 0.04 & 0.1 \selectlanguage{ngerman}± 0.03 & -
& -\tabularnewline
2207 & n-C22 & 310 & - & - & 2.49 \selectlanguage{ngerman}± 0.14 & - & 0.82 \selectlanguage{ngerman}± 0.24 & - & 0.06 \selectlanguage{ngerman}±
0.03\tabularnewline
2270 & 4-MeC22 & 309; 70; 280 & - & - & 1.03 \selectlanguage{ngerman}± 0.15 & - & - & - &
-\tabularnewline
2280 & C23-ene1 & 322 & - & - & - & - & 0.21 \selectlanguage{ngerman}± 0.06 & - & 1.13 \selectlanguage{ngerman}±
0.46\tabularnewline
2287 & C23-ene2 & 322 & - & - & - & - & 0.06 \selectlanguage{ngerman}± 0.02 & - & 0.07 \selectlanguage{ngerman}±
0.04\tabularnewline
2310 & n-C23 & 324 & 0.07 \selectlanguage{ngerman}± 0.07 & - & 13.48 \selectlanguage{ngerman}± 1.12 & 0.07 \selectlanguage{ngerman}± 0.02 & 7.57
\selectlanguage{ngerman}± 0.71 & - & 7.97 \selectlanguage{ngerman}± 1.38\tabularnewline
2343 & 9-; 11-;13-MeC23 & 323; 140; 224; 168; 196; & 0.01 \selectlanguage{ngerman}± 0.02 & - &
0.83 \selectlanguage{ngerman}± 0.22 & 0.01 \selectlanguage{ngerman}± 0.01 & 0.56 \selectlanguage{ngerman}± 0.18 & - & 0.39 \selectlanguage{ngerman}± 0.18\tabularnewline
2349 & 7-MeC23 & 323; 112; 252 & - & - & - & - & 0.09 \selectlanguage{ngerman}± 0.03 & - &
-\tabularnewline
2371 & 4-MeC23 & 323; 70; 294 & - & - & 3.45 \selectlanguage{ngerman}± 0.2 & - & 0.89 \selectlanguage{ngerman}± 0.26 & -
& 1.46 \selectlanguage{ngerman}± 0.56\tabularnewline
2379 & 7,11-;7,13-DiMeC23 & 309; 112; 266; 182; 196; 210; 168 & - & - &
- & - & 0.08 \selectlanguage{ngerman}± 0.02 & - & -\tabularnewline
2380 & 3-MeC23 & 323; 56; 308 & 0.02 \selectlanguage{ngerman}± 0.03 & - & 3.24 \selectlanguage{ngerman}± 0.19 & 0.04 \selectlanguage{ngerman}±
0.02 & 0.55 \selectlanguage{ngerman}± 0.13 & - & -\tabularnewline
2380 & C24-ene1 & 336 & - & - & - & - & - & - & 0.59 \selectlanguage{ngerman}±
0.25\tabularnewline
2386 & C24-ene2 & 336 & - & - & - & - & 0.09 \selectlanguage{ngerman}± 0.03 & - &
-\tabularnewline
2394 & C24-ene3 & 336 & - & - & - & - & 0.12 \selectlanguage{ngerman}± 0.04 & - &
-\tabularnewline
2409 & n-C24 & 338 & - & - & 4.79 \selectlanguage{ngerman}± 0.44 & 1.88 \selectlanguage{ngerman}± 0.39 & 3.33 \selectlanguage{ngerman}± 0.49 &
0.03 \selectlanguage{ngerman}± 0.03 & 5.92 \selectlanguage{ngerman}± 1.62\tabularnewline
2442 & 10-;12-;14-MeC24 & 337; 154; 224; 182; 196; 210; 168 & - & - &
0.11 \selectlanguage{ngerman}± 0.04 & 0.15 \selectlanguage{ngerman}± 0.11 & 0.66 \selectlanguage{ngerman}± 0.16 & 0.1 \selectlanguage{ngerman}± 0.09 & 1.01 \selectlanguage{ngerman}±
0.37\tabularnewline
2463 & C25-ene1 & 350 & - & - & - & - & - & - & 0.22 \selectlanguage{ngerman}±
0.1\tabularnewline
2473 & 4-MeC24 & 337; 70; 308 & - & - & 4.24 \selectlanguage{ngerman}± 1.16 & 4.11 \selectlanguage{ngerman}± 0.16 & 2.63
\selectlanguage{ngerman}± 0.36 & 0.22 \selectlanguage{ngerman}± 0.2 & 11.79 \selectlanguage{ngerman}± 2.02\tabularnewline
2483 & C25-ene2 & 350 & - & - & 3.41 \selectlanguage{ngerman}± 0.62 & - & - & - & 7.84 \selectlanguage{ngerman}±
0.82\tabularnewline
2483 & C25-diene1 & 348 & - & - & - & - & 3.93 \selectlanguage{ngerman}± 0.99 & - & 7.43 \selectlanguage{ngerman}±
1.05\tabularnewline
2480 & 3-MeC24 & 337; 56; 322 & - & - & - & 0.31 \selectlanguage{ngerman}± 0.02 & - & - &
-\tabularnewline
2484 & C25-ene3 & 350 & - & 0.01 & - & - & 3.84 \selectlanguage{ngerman}± 0.85 & - &
-\tabularnewline
2492 & C25-ene4 & 350 & - & - & - & - & 1.77 \selectlanguage{ngerman}± 0.36 & - &
-\tabularnewline
2509 & n-C25 & 352 & 0.32 \selectlanguage{ngerman}± 0.17 & 1.15 \selectlanguage{ngerman}± 0.96 & 11.1 \selectlanguage{ngerman}± 0.87 & 10.67 \selectlanguage{ngerman}±
0.4 & 9.49 \selectlanguage{ngerman}± 0.56 & 5.89 \selectlanguage{ngerman}± 5.17 & 12.91 \selectlanguage{ngerman}± 3.24\tabularnewline
2540 & C25-diene2 & 348 & - & - & - & - & 2.22 \selectlanguage{ngerman}± 0.21 & - &
-\tabularnewline
2542 & 9-;11-;13-;15-MeC25 (+ unsaturated non-CHC compound) & 351; 140;
252; 168; 224; 196; 224, 168 & 0.12 \selectlanguage{ngerman}± 0.1 & 0.13 \selectlanguage{ngerman}± 0.11 & 3.04 \selectlanguage{ngerman}± 0.89 &
6.51 \selectlanguage{ngerman}± 2.83 & 5.26 \selectlanguage{ngerman}± 0.41 & 11.19 \selectlanguage{ngerman}± 10.08 & 11.86 \selectlanguage{ngerman}± 1.83\tabularnewline
2551 & 7-MeC25 & 351; 112; 280 & 0.03 \selectlanguage{ngerman}± 0.1 & - & - & 3.18 \selectlanguage{ngerman}± 0.24 & 1.42
\selectlanguage{ngerman}± 0.46 & - & 2.39 \selectlanguage{ngerman}± 3.95\tabularnewline
2555 & C25diene3 & 348 & - & - & 6.18 \selectlanguage{ngerman}± 0.93 & - & - & - & 4.41 \selectlanguage{ngerman}±
1.35\tabularnewline
2562 & C25diene4 & 348 & - & - & 2.48 \selectlanguage{ngerman}± 0.33 & - & - & - &
-\tabularnewline
2557 & 5-MeC25 & 351; 84; 308 & 0.32 \selectlanguage{ngerman}± 0.25 & 1.12 \selectlanguage{ngerman}± 0.76 & - & - & 0.39
\selectlanguage{ngerman}± 0.07 & - & 1.29 \selectlanguage{ngerman}± 0.67\tabularnewline
2577 & 4-MeC25 & 351; 70; 322 & 0.21 \selectlanguage{ngerman}± 0.11 & 6.4 \selectlanguage{ngerman}± 1.81 & - & 5.69 \selectlanguage{ngerman}±
0.4 & 2.84 \selectlanguage{ngerman}± 0.93 & 12.13 \selectlanguage{ngerman}± 1.52 & 4.29 \selectlanguage{ngerman}± 1.46\tabularnewline
2575 & C25diene5 & 348 & - & - & 4.31 \selectlanguage{ngerman}± 0.22 & - & - & - & 3.3 \selectlanguage{ngerman}±
1.99\tabularnewline
2581 & 3-MeC25 & 351; 56; 336 & 0.19 \selectlanguage{ngerman}± 0.11 & 6.28 \selectlanguage{ngerman}± 1.96 & 4.11 \selectlanguage{ngerman}± 0.57
& 5.81 \selectlanguage{ngerman}± 0.58 & 3.94 \selectlanguage{ngerman}± 0.64 & 3.48 \selectlanguage{ngerman}± 2.87 & 6.44 \selectlanguage{ngerman}± 0.62\tabularnewline
2586 & 5,13-DiMeC25 & 337; 84; 322; 210; 196 & 0.11 \selectlanguage{ngerman}± 0.06 & - & - & - &
- & - & -\tabularnewline
2593 & C26-ene1 & 364 & - & - & - & - & 2.23 \selectlanguage{ngerman}± 0.57 & - &
-\tabularnewline
2600 & C26-ene2 & 364 & - & - & - & - & 2.52 \selectlanguage{ngerman}± 0.23 & - &
-\tabularnewline
2608 & n-C26 & 366 & 0.23 \selectlanguage{ngerman}± 0.13 & 0.82 \selectlanguage{ngerman}± 0.47 & - & 5.97 \selectlanguage{ngerman}± 0.27 & 4.51
\selectlanguage{ngerman}± 0.23 & 2.48 \selectlanguage{ngerman}± 1.75 & -\tabularnewline
2613 & 3,7-; 3,9-DiMeC25 & 337; 56; 350; 126; 280; 154; 252 & 0.15 \selectlanguage{ngerman}±
0.21 & 0.33 \selectlanguage{ngerman}± 0.36 & - & - & - & - & -\tabularnewline
2641 & 12-; 14; 16-MeC26 & 365; 182; 224; 210; 196; 238; 168 & 0.16 \selectlanguage{ngerman}±
0.09 & 3.21 \selectlanguage{ngerman}± 1.15 & - & 8.66 \selectlanguage{ngerman}± 0.76 & 1.89 \selectlanguage{ngerman}± 1.06 & 2.94 \selectlanguage{ngerman}± 2.17 & 0.36
\selectlanguage{ngerman}± 0.14\tabularnewline
2640 & C26diene & 362 & - & - & - & - & 0.53 \selectlanguage{ngerman}± 0.29 & - &
-\tabularnewline
2645 & 9-MeC26 & 365; 140; 266 & - & - & - & 3.03 \selectlanguage{ngerman}± 0.67 & - & - &
-\tabularnewline
2651 & 7-MeC26 & 365; 112; 294 & - & - & - & 0.67 \selectlanguage{ngerman}± 0.1 & - & - &
-\tabularnewline
2651 & 6-MeC26 & 365; 98; 308 & 0.02 \selectlanguage{ngerman}± 0.01 & - & - & - & - & - &
-\tabularnewline
2656 & 5-MeC26 & 365; 84; 322 & 0.05 \selectlanguage{ngerman}± 0.03 & 0.06 \selectlanguage{ngerman}± 0.03 & - & - & - &
- & -\tabularnewline
2669 & 4-MeC26 (+ unsaturated non-CHC compound) & 365; 70; 336 & 0.05 \selectlanguage{ngerman}±
0.03 & 0.58 \selectlanguage{ngerman}± 0.24 & - & 5.21 \selectlanguage{ngerman}± 0.16 & - & 5.08 \selectlanguage{ngerman}± 0.98 & 0.7 \selectlanguage{ngerman}±
0.29\tabularnewline
2681 & 3-MeC26 & 365; 56; 350 & 0.07 \selectlanguage{ngerman}± 0.03 & 0.3 \selectlanguage{ngerman}± 0.12 & - & 0.15 \selectlanguage{ngerman}±
0.06 & - & 0.15 \selectlanguage{ngerman}± 0.04 & 0.11 \selectlanguage{ngerman}± 0.04\tabularnewline
2680 & C27-ene1 & 378 & - & - & 2.05 \selectlanguage{ngerman}± 0.61 & - & - & - &
-\tabularnewline
2684 & C27-ene2 & 378 & - & - & 0.6 \selectlanguage{ngerman}± 0.25 & - & - & - &
-\tabularnewline
2689 & C27diene1 & 376 & - & - & - & - & 1.48 \selectlanguage{ngerman}± 0.36 & - &
-\tabularnewline
2694 & C27diene2 & 376 & - & - & - & - & 1.95 \selectlanguage{ngerman}± 0.34 & - &
-\tabularnewline
2699 & C27-ene3 & 378 & - & - & - & 0.11 \selectlanguage{ngerman}± 0.22 & 2.07 \selectlanguage{ngerman}± 0.36 & - &
-\tabularnewline
2703 & C27-ene4 & 378 & - & - & - & 0.11 \selectlanguage{ngerman}± 0.22 & 2.09 \selectlanguage{ngerman}± 1.21 & - &
-\tabularnewline
2711 & n-C27 & 380 & 3.92 \selectlanguage{ngerman}± 0.41 & 11.36 \selectlanguage{ngerman}± 3.14 & 5.13 \selectlanguage{ngerman}± 0.25 & 8.01 \selectlanguage{ngerman}±
0.45 & 4.36 \selectlanguage{ngerman}± 0.48 & 8.05 \selectlanguage{ngerman}± 0.98 & 0.15 \selectlanguage{ngerman}± 0.05\tabularnewline
2744 & 9-; 11-; 13-; 15-MeC27 & 379; 140; 280; 168; 252; 196; 224 & 5.04
\selectlanguage{ngerman}± 0.75 & 26.96 \selectlanguage{ngerman}± 19.32 & - & 13.39 \selectlanguage{ngerman}± 0.75 & 1.01 \selectlanguage{ngerman}± 0.26 & 20.47 \selectlanguage{ngerman}± 3.31 &
0.05 \selectlanguage{ngerman}± 0.03\tabularnewline
2742 & C27diene3 & 376 & - & - & - & - & 5.48 \selectlanguage{ngerman}± 0.28 & - &
-\tabularnewline
2752 & C28diene1 & 390 & - & - & 0.61 \selectlanguage{ngerman}± 0.14 & - & - & - &
-\tabularnewline
2756 & C27diene4 & 376 & - & - & 0.69 \selectlanguage{ngerman}± 0.32 & - & 0.48 \selectlanguage{ngerman}± 0.42 & - &
0.11 \selectlanguage{ngerman}± 0.11\tabularnewline
2756 & 7-MeC27 & 379; 112; 308 & - & - & - & 1.26 \selectlanguage{ngerman}± 0.31 & - & 0.22 \selectlanguage{ngerman}±
0.49 & -\tabularnewline
2761 & 5-MeC27 & 379; 84; 336 & 3.6 \selectlanguage{ngerman}± 0.47 & 6.37 \selectlanguage{ngerman}± 1.74 & - & - & - & -
& -\tabularnewline
2760 & C27diene5 & 376 & - & - & - & - & 0.97 \selectlanguage{ngerman}± 0.26 & - &
-\tabularnewline
2770 & 11,13-; 11,15-; 11,17-; 13,15-; 13,17-; 15,17-DiMeC27 & 365; 168;
266; 210; 224; 238; 196 & 1.67 \selectlanguage{ngerman}± 0.54 & 0.91 \selectlanguage{ngerman}± 0.48 & - & 4.3 \selectlanguage{ngerman}± 0.99 & -
& - & -\tabularnewline
2775 & 4-MeC27 & 379; 70; 350 & - & - & - & - & 1.01 \selectlanguage{ngerman}± 0.29 & 11.18 \selectlanguage{ngerman}±
3.67 & -\tabularnewline
2775 & 9,15-: 9.17-DiMeC27 & 365; 140; 294; 238; 196; 266; 168 & - & - &
- & 5.35 \selectlanguage{ngerman}± 0.77 & - & - & -\tabularnewline
2779 & C27diene6 & 376 & - & - & - & - & 2.71 \selectlanguage{ngerman}± 0.15 & - &
-\tabularnewline
2786 & 3-MeC27 & 379; 56; 364 & 3.24 \selectlanguage{ngerman}± 0.31 & 8.59 \selectlanguage{ngerman}± 1.62 & - & 0.85 \selectlanguage{ngerman}±
0.49 & 2.28 \selectlanguage{ngerman}± 0.2 & 6.76 \selectlanguage{ngerman}± 2.96 & -\tabularnewline
2784 & C28diene2 & 390 & - & - & - & - & 0.4 \selectlanguage{ngerman}± 0.08 & - &
-\tabularnewline
2792 & 5,17-DiMeC27 & 365; 84; 350; 266; 168 & 0.58 \selectlanguage{ngerman}± 0.1 & 7.12 \selectlanguage{ngerman}± 1.3 &
- & - & - & - & -\tabularnewline
2790 & 5,15-DiMeC27 & 365; 84; 350; 238; 196 & 0.12 \selectlanguage{ngerman}± 0.36 & 1.82 \selectlanguage{ngerman}± 1.06
& - & - & 0.48 \selectlanguage{ngerman}± 0.37 & - & -\tabularnewline
2791 & 5,9-; 5,11-; 5,13-DiMeC27 & 365; 84; 350; 154; 280; 182; 252;
210; 224 & 2.53 \selectlanguage{ngerman}± 0.57 & - & - & - & - & - & -\tabularnewline
2802 & C28-ene & 392 & - & - & - & - & 1.01 \selectlanguage{ngerman}± 0.39 & - &
-\tabularnewline
2813 & n-C28 & 394 & 2.35 \selectlanguage{ngerman}± 1.3 & 3.3 \selectlanguage{ngerman}± 1.21 & - & 1.31 \selectlanguage{ngerman}± 0.77 & 0.28 \selectlanguage{ngerman}±
0.08 & 0.57 \selectlanguage{ngerman}± 0.43 & -\tabularnewline
2814 & 3,9-; 3,11-DiMeC27 & 365; 56; 378; 154, 280; 282; 252 & 2.91 \selectlanguage{ngerman}±
0.61 & 0.06 \selectlanguage{ngerman}± 0.19 & - & - & - & - & -\tabularnewline
2816 & 3,7-DiMeC27 & 365; 56; 378; 126; 308 & 1.46 \selectlanguage{ngerman}± 0.58 & 3.8 \selectlanguage{ngerman}± 1.48 &
- & - & - & - & -\tabularnewline
2841 & 11-; 13-MeC28 & 393; 168; 266; 196; 238 & - & - & - & - & - &
1.85 \selectlanguage{ngerman}± 2.3 & -\tabularnewline
2840 & 12-; 14-MeC28 & 393; 182; 252; 210; 224 & 2.66 \selectlanguage{ngerman}± 0.63 & 1.41 \selectlanguage{ngerman}±
0.58 & - & - & - & - & -\tabularnewline
2843 & 3,9,11-; 3,9,13-; 3,9,15-; 3,9,17-TriMeC27 & 393; 56; 392; 154;
294; 196; 252; 224; 280; 168 & 0.88 \selectlanguage{ngerman}± 0.39 & - & - & - & - & - &
-\tabularnewline
2853 & 6-MeC28 & 393; 98; 336 & 0.57 \selectlanguage{ngerman}± 0.22 & 0.07 \selectlanguage{ngerman}± 0.04 & - & - & - &
- & -\tabularnewline
2858 & 5-MeC28 & 393; 84; 350 & 0.68 \selectlanguage{ngerman}± 0.23 & - & - & - & - & - &
-\tabularnewline
2864 & C29diene1 & 404 & - & - & - & - & 0.16 \selectlanguage{ngerman}± 0.05 & - &
-\tabularnewline
2868 & 4-MeC28 & 393; 70; 364 & 2.84 \selectlanguage{ngerman}± 0.74 & 0.27 \selectlanguage{ngerman}± 0.12 & - & - & - &
0.49 \selectlanguage{ngerman}± 0.48 & -\tabularnewline
2874 & C29-ene1 & 406 & - & 2.16 \selectlanguage{ngerman}± 1.06 & - & - & - & - &
-\tabularnewline
2881 & C29-ene2 & 406 & 1.21 \selectlanguage{ngerman}± 0.79 & - & 0.84 \selectlanguage{ngerman}± 0.35 & - & 2.04 \selectlanguage{ngerman}± 2.12
& 0.07 \selectlanguage{ngerman}± 0.09 & -\tabularnewline
2880 & C29diene2 & 404 & - & 0.3 \selectlanguage{ngerman}± 0.14 & - & - & - & - &
-\tabularnewline
2883 & C29diene3 & 404 & - & - & - & - & 4.09 \selectlanguage{ngerman}± 0.28 & - &
-\tabularnewline
2882 & 3-MeC28 & 393; 56; 378 & 2.27 \selectlanguage{ngerman}± 1.03 & - & - & - & - & - &
-\tabularnewline
2887 & 5,9-; 5,11-; 5,13-; 5,15-; 5,17-DiMeC28 & 379; 84; 364; 154; 294;
182; 266; 210; 238 & 0.48 \selectlanguage{ngerman}± 0.21 & - & - & - & - & - & -\tabularnewline
2894 & C29-ene3 & 406 & - & - & - & - & 0.12 \selectlanguage{ngerman}± 0.02 & - &
-\tabularnewline
2897 & 4,10-; 4,12-; 4,14-; 4,16-; 4,18-; 4,20-DiMeC28 & 379; 70; 378;
168; 280; 196; 252; 224; 308; 140 & 0.83 \selectlanguage{ngerman}± 0.61 & - & - & - & - & - &
-\tabularnewline
2909 & n-C29 & 408 & 4.26 \selectlanguage{ngerman}± 0.9 & 0.51 \selectlanguage{ngerman}± 0.24 & 1.64 \selectlanguage{ngerman}± 0.36 & 2.96 \selectlanguage{ngerman}±
1.53 & 0.34 \selectlanguage{ngerman}± 0.11 & 0.23 \selectlanguage{ngerman}± 0.17 & -\tabularnewline
2920 & 3,7-; 3,9-; 3,11-DiMeC28 & 479; 56; 392; 126; 322; 154; 294; 182;
266 & 1.48 \selectlanguage{ngerman}± 0.54 & - & - & - & - & - & -\tabularnewline
2940 & 11-; 13-; 15-MeC29 & 407; 168; 280; 196; 252; 224 & 7.25 \selectlanguage{ngerman}± 0.51 &
1.87 \selectlanguage{ngerman}± 0.88 & - & - & 0.07 \selectlanguage{ngerman}± 0.02 & 5.96 \selectlanguage{ngerman}± 8.04 & -\tabularnewline
2953 & 7-; 9-MeC29 & 407; 112; 336; 140; 308 & 3.26 \selectlanguage{ngerman}± 1.16 & 0.64 \selectlanguage{ngerman}± 0.3
& - & - & - & - & -\tabularnewline
2964 & 5-MeC29 & 407; 84; 364 & 4.4 \selectlanguage{ngerman}± 4.32 & - & - & - & 0.02 \selectlanguage{ngerman}± 0.02 & -
& -\tabularnewline
2979 & 11,17-; 11,19-; 11,21-; 13,17-; 13,19-DiMeC29 & 393; 168; 294;
266; 196; 322; 140; & 2.14 \selectlanguage{ngerman}± 1.19 & - & - & - & - & - & -\tabularnewline
2983 & 7,11-DiMeC29 & 393; 112; 350; 182; 280 & 1.91 \selectlanguage{ngerman}± 0.85 & - & - & -
& - & - & -\tabularnewline
2985 & 7,17-DiMeC29 & 393; 266; 196 & - & 0.14 \selectlanguage{ngerman}± 0.09 & - & - & - & - &
-\tabularnewline
2986 & 3-MeC29 & 407; 56; 392 & 4.8 \selectlanguage{ngerman}± 0.67 & 0.08 \selectlanguage{ngerman}± 0.03 & - & 0.14 \selectlanguage{ngerman}±
0.09 & - & 0.47 \selectlanguage{ngerman}± 0.47 & -\tabularnewline
2994 & 5,9-; 5,11-; 5,13-DiMeC29 & 393; 84; 378; 154; 308; 182; 280;
210; 252 & 1.98 \selectlanguage{ngerman}± 0.48 & 0.1 \selectlanguage{ngerman}± 0.06 & 0.02 \selectlanguage{ngerman}± 0.04 & - & - & - &
-\tabularnewline
3013 & 3,7-DiMeC29 & 393; 56; 406; 126; 336 & - & 0.45 \selectlanguage{ngerman}± 0.23 & - & - &
- & - & -\tabularnewline
3019 & 3,9-; 3,11-DiMeC29 & 393; 56; 406; 154; 308; 182; 280 & 6.44 \selectlanguage{ngerman}±
0.76 & - & 0.03 \selectlanguage{ngerman}± 0.07 & - & - & - & -\tabularnewline
3031 & 3,7-DiMeC29 & 393; 56; 406; 126; 336 & 0.63 \selectlanguage{ngerman}± 0.31 & - & - & - &
- & - & -\tabularnewline
3041 & 3,7,11-; 3,7,13-; 3,7,15-; 3,7,17-; 3,9,11-; 3,9,13-; 3,9,15-;
3,9,17-TriMeC29 & 421; 56; 420; 126; 350; 196; 280; 224; 252; 280; 196;
154; 322; & 4.4 \selectlanguage{ngerman}± 0.68 & - & - & - & - & - & -\tabularnewline
3061 & 14,18-; 14-22-DiMeC30 & 407; 210; 266; 280; 196; 336; 140; & 0.86
\selectlanguage{ngerman}± 0.43 & - & - & - & - & - & -\tabularnewline
3063 & 4-MeC30 & 421; 70; 392 & 0.34 \selectlanguage{ngerman}± 0.24 & - & - & - & - & - &
-\tabularnewline
3075 & C31ene & 434 & 0.18 \selectlanguage{ngerman}± 0.11 & 0.01 \selectlanguage{ngerman}± 0.02 & - & - & - & - &
-\tabularnewline
3076 & C31diene & 432 & - & - & - & - & 0.25 \selectlanguage{ngerman}± 0.13 & - &
-\tabularnewline
3080 & 5,9-; 5,11-; 5,13-; 5,15-DiMeC30 & 407; 84; 392; 154; 322; 182;
294; 210; 266; 238 & 0.17 \selectlanguage{ngerman}± 0.09 & 0.03 \selectlanguage{ngerman}± 0.1 & - & - & - & - &
-\tabularnewline
3088 & 4,8-; 4,10-; 4,12-DiMeC30 & 407; 70; 406; 140; 336; 168; 308;
196; 280 & 2.39 \selectlanguage{ngerman}± 0.86 & 0.01 \selectlanguage{ngerman}± 0.04 & - & - & - & - & -\tabularnewline
3102 & 3,9-; 3,11-DiMeC30 & 407; 56; 420; 154; 322; 182; 294 & 0.59 \selectlanguage{ngerman}±
0.41 & - & - & - & - & - & -\tabularnewline
3112 & 4,8,12-; 4,8,14-; 4,8,16-TriMeC30 (+ acetic acid) & 435; 70; 420;
140, 350; 210; 280; 238, 252; 266; 224 & 0.16 \selectlanguage{ngerman}± 0.12 & - & - & - & - & -
& -\tabularnewline
3130 & 11-; 13-; 15-MeC31 & 435; 168; 308; 196; 280; 224; 252 & 3.13 \selectlanguage{ngerman}±
0.76 & - & - & - & - & - & -\tabularnewline
3154 & 13,17-; 15,17-DiMeC31 & 421; 196; 294; 266; 224 & 2.16 \selectlanguage{ngerman}± 1 & 0.11
\selectlanguage{ngerman}± 0.38 & - & - & - & - & -\tabularnewline
3178 & 5,9-;5,11-; 5,13-; 5,15-;5,17-DiMeC31 & 421; 84; 406; 154; 336;
182; 308; 210; 280; 238; 252; 266; 224 & 1.83 \selectlanguage{ngerman}± 0.66 & - & - & - & - & -
& -\tabularnewline
3203 & 3,9-; 3,11-; 3,13-; 3,15-DiMeC31 & 421; 56; 434; 154; 336; 182;
308; 210; 280; 238; 252 & 0.52 \selectlanguage{ngerman}± 0.25 & 0.01 \selectlanguage{ngerman}± 0.03 & 0.01 \selectlanguage{ngerman}± 0.03 & - &
0.02 \selectlanguage{ngerman}± 0.02 & - & -\tabularnewline
3477 & C35-ene & 490 & - & - & - & - & 0.12 \selectlanguage{ngerman}± 0.04 & - &
-\tabularnewline
3531 & 11-MeC35 & 491; 168; 364 & - & - & - & - & - & - & 0.55 \selectlanguage{ngerman}±
0.31\tabularnewline
3629 & 12-MeC36 & 505; 182; 364 & - & - & - & - & - & - & 0.09 \selectlanguage{ngerman}±
0.06\tabularnewline
3729 & 11-; 13-MeC37 & 519; 168; 392; 196; 364 & - & - & 0.05 \selectlanguage{ngerman}± 0.05 & -
& - & - & 2.28 \selectlanguage{ngerman}± 1.11\tabularnewline
3751 & 11,15-DiMeC37 & 505; 168; 406; 238; 336 & - & - & - & - & - & - &
0.45 \selectlanguage{ngerman}± 0.23\tabularnewline
3774 & 5,15-; 5,17-DiMeC37 & 505; 84; 490; 236; 336; 266; 308 & - & - &
- & - & - & - & 0.65 \selectlanguage{ngerman}± 0.33\tabularnewline
3840 & C39diene & 544 & - & - & 0.28 \selectlanguage{ngerman}± 0.1 & - & - & - &
-\tabularnewline
3876 & C39-ene & 546 & - & - & 2.24 \selectlanguage{ngerman}± 0.18 & - & - & - &
-\tabularnewline
3927 & 11-;13-;15-MeC39 & 547; 168; 420; 168; 392; 224; 364 & - & - &
2.74 \selectlanguage{ngerman}± 0.41 & - & 0.06 \selectlanguage{ngerman}± 0.02 & - & 0.8 \selectlanguage{ngerman}± 0.37\tabularnewline
3949 & 11,15-DiMeC39 & 533; 168; 434; 238; 364 & - & - & - & - & - & - &
0.57 \selectlanguage{ngerman}± 0.26\tabularnewline
3953 & 13,17-DiMeC39 & 533; 196; 406; 266; 336 & - & - & 0.24 \selectlanguage{ngerman}± 0.06 & -
& - & - & -\tabularnewline
3973 & 5,15-; 5,17-DiMeC39 & 533; 84, 518; 238; 364; 266; 336 & - & - &
- & - & - & - & 0.32 \selectlanguage{ngerman}± 0.16\tabularnewline
4054 & C41diene & 572 & - & - & 5.32 \selectlanguage{ngerman}± 0.18 & - & - & - &
-\tabularnewline
4074 & C41-ene & 574 & - & - & 1.92 \selectlanguage{ngerman}± 0.5 & - & - & - & -\tabularnewline
4084 & C41-ene & 574 & - & - & 2.49 \selectlanguage{ngerman}± 0.36 & - & - & - &
-\tabularnewline
4143 & 11-; 13-; 15-; 17-MeC41 & 575; 168; 448; 196; 420; 224, 392; 252;
364 & 1.72 \selectlanguage{ngerman}± 1.2 & 0.52 \selectlanguage{ngerman}± 0.37 & 0.62 \selectlanguage{ngerman}± 0.23 & - & 0.11 \selectlanguage{ngerman}± 0.03 & - &
0.02 \selectlanguage{ngerman}± 0.04\tabularnewline
4173 & 13,15-; 13,17-DiMeC41 & 561; 196; 434; 238; 392; 266; 364 & 0.99
\selectlanguage{ngerman}± 1.52 & 0.6 \selectlanguage{ngerman}± 1.98 & 0.58 \selectlanguage{ngerman}± 0.15 & - & - & - & -\tabularnewline
\bottomrule
\end{longtable}



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{\label{references}}

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