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\DOI{10.5802/crchim.259}
\datereceived{2023-04-03}
\daterevised{2023-06-24}
\datererevised{2023-08-02}
\dateaccepted{2023-08-31}
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\dateposted{2024-02-05}
\begin{document}

\begin{noXML}

%\makeatletter
%\def\TITREspecial{\relax}
%\def\cdr@specialtitle@english{Chemical Ecology -- Chemical Mediation in the Environment}
%%\def\cdr@specialtitle@french{\'Ecologie chimique -- M\'ediation chimique dans l'environnement}
%\makeatother

\title{Identification of defensive antimicrobial compounds from
environmental \protect\textit{Serratia marcescens} SNB-CN88 strain associated
with macro-holobiont (termite nest) using a molecular network approach}

\alttitle{Identification \`{a} l'aide d'une approche par  r\'{e}seau
mol\'{e}culaire de compos\'{e}s  antimicrobiens \`{a} partir d'une
souche environnementale  de \textit{Serratia marcescens} SNB-CN88
associ\'{e}e \`{a} un macro-holobiont (nid de termites)}

\author{\firstname{Dung} \lastname{Nguyen}}
\address{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR~2301, 91198 Gif-Sur-Yvette, France}
\email[D. Nguyen]{dungnvp14@gmail.com}

\author{\firstname{Marceau} \lastname{Levasseur}}
\addressSameAs{1}{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR 2301, 91198 Gif-Sur-Yvette, France}
\email[M. Levasseur]{marceau.levasseur@cnrs.fr}

\author{\firstname{Juliette} \lastname{Segret}}
\addressSameAs{1}{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR 2301, 91198 Gif-Sur-Yvette, France}
\email[J. Segret]{juliette.segret@cnrs.fr}

\author{\firstname{Jonathan} \lastname{Sorres}}
\addressSameAs{1}{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR 2301, 91198 Gif-Sur-Yvette, France}
\email[J. Sorres]{jon.sorres@gmail.com}

\author{\firstname{T\'{e}o} \lastname{Hebra}}
\addressSameAs{1}{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR 2301, 91198 Gif-Sur-Yvette, France}
\email[T. Hebra]{teo.hebra@uochb.cas.cz;}

\author{\firstname{David} \lastname{Touboul}\CDRorcid{0000-0003-2751-774X}}
\addressSameAs{1}{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR 2301, 91198 Gif-Sur-Yvette, France}
\address{Laboratoire de Chimie Mol\'{e}culaire (LCM), 
CNRS UMR 9168, \'{E}cole Polytechnique, 
Institut Polytechnique de Paris, 91128 Palaiseau, France}
\email[D. Touboul]{david.touboul@cnrs.fr}

\author{\firstname{V\'{e}ronique} \lastname{Eparvier}\CDRorcid{0000-0002-2954-0866}\IsCorresp}
\addressSameAs{1}{Universit\'{e} Paris-Saclay, CNRS, 
Institut de Chimie Des Substances Naturelles, 
UPR 2301, 91198 Gif-Sur-Yvette, France}
\email[V. Eparvier]{veronique.eparvier@cnrs.fr}

\shortrunauthors

\keywords{\kwd{\textit{Serratia marcescens}}
\kwd{Environmental microorganism}
\kwd{Antimicrobial}
\kwd{Stephensiolide}
\kwd{Glucosamine}}

\altkeywords{\kwd{\textit{Serratia marcescens}}
\kwd{Micro-organisme environnemental}
\kwd{Antimicrobien}
\kwd{Stephensiolide}
\kwd{Glucosamine}}

\begin{abstract}
Environmental microbes are an underexploited resource for the discovery
of bioactive compounds. An integrated approach combining reversed-phase
high-performance liquid chromatography and high-resolution tandem mass
spectrometry with the use of molecular networks was applied to annotate
novel chemical structures with potential antimicrobial activities. This
metabolomic approach coupled with biological screening of environmental
strains allowed the identification of 22 compounds, including 11
glucosamine derivatives and 10 cyclopeptides, from a bacterial strain
of \textit{Serratia marcescens}. Three new glucosamine derivatives and
two stephensiolides were annotated. Two antibacterial stephensiolides,
named stephensiolides E and F, were isolated to confirm annotations.
\end{abstract}

\begin{altabstract}
Les microbes de l'environnement constituent une ressource
sous-exploit\'{e}e pour la d\'{e}couverte de compos\'{e}s bioactifs.
Une approche int\'{e}gr\'{e}e combinant la chromatographie liquide
haute performance en phase invers\'{e}e et la spectrom\'{e}trie de
masse en tandem \`{a} haute r\'{e}solution avec une visualisation
sous~forme de r\'{e}seaux mol\'{e}culaires a \'{e}t\'{e} utilis\'{e}e
pour annoter de nouvelles structures chimiques avec de
potentielles~activit\'{e}s antimicrobiennes. Cette approche
m\'{e}tabolomique, coupl\'{e}e \`{a} un criblage biologique de souches
environnementales, a permis d'identifier 22 compos\'{e}s, dont 11
d\'{e}riv\'{e}s de glucosamine et 11 cyclopeptides, \`{a} partir d'une
souche bact\'{e}rienne de \textit{Serratia marcescens}. Deux
compos\'{e}s antibact\'{e}riens ont \'{e}t\'{e} isol\'{e}s et leurs
structures ont \'{e}t\'{e} d\'{e}termin\'{e}es comme \'{e}tant le
stephensiolide F et le compos\'{e} nouvellement d\'{e}crit, le
dehydrostephensiolide F.
\end{altabstract}

\thanks{This work has benefited from an ``Investissement d'Avenir''
grant managed by the French National Research Agency (CEBA, ref.
ANR-10-LABX-0025).}

\maketitle

\vspace*{8pt}

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\let\rmmu\upmu

\section{Introduction}\label{sec1}
Plants are the main sources of natural products and have contributed to
the discovery of drugs for the treatment of various human 
diseases~\cite{1a,1b}. However, the arsenal of specialized metabolites has
been recently expanded to include those of microbial origin and, among
others, those associated with plants and  insects~\cite{2a,2b,2c}. Indeed, the
discovery of penicillin isolated from \textit{Penicillium}~sp. fungus
led to the search for many other classes of antimicrobial compounds in
the fungal and bacterial kingdoms. Actually, the effectiveness of
antimicrobial drugs is decreasing while the resistance of
microorganisms is significantly  increasing~\cite{3}. The rapid spread
and emergence of multidrug-resistant (MDR) and extensively
drug-resistant (XDR) bacteria and fungi are considered to be major
threats to global public health in the 21st  century~\cite{4a,4b}. Over the
last few decades, many of the existing drugs used to treat infectious
diseases have become increasingly ineffective because of the global
emergence of antimicrobial resistance (AMR). Therefore, there is a
constant demand to find new, effective compounds that could help
alleviate some of this pressure. 

Symbiotic microorganisms have captured the attention of many
researchers because they can produce novel bioactive 
compounds~\cite{2a,2b,2c}, many of which possess broad-spectrum antimicrobial 
activities~\cite{5}. However, while highly promising, research in this
area is still in its infancy. Symbiotic microbes produce a plethora of
bioactive compounds that promote the health of their host and may lead
to the ecological success of holobionts (such as plant and/or insect 
holobionts)~\cite{6a,6b}. Therefore, these environmental microorganisms
have the ability to produce antimicrobial compounds because of the
constant environmental pressure. The selection pressure is even
stronger in areas with high  biodiversity~\cite{7a,7b,7c}. Thus, we focused
our research efforts in the team Functional Chemistry---Chemical
Ecology of \textit{Institut de Chimie des Substances Naturelles} (ICSN
of the \textit{Centre National de la Recherche Scientifique} (CNRS)) on
our library of symbiotic strains from French Guiana, including those
associated with insects or plants, from which many antimicrobial
compounds have been isolated 
recently~\cite{8a,8b,8c,8d,8e,8f,8g,8h,9a,9b,9c}. Among several strain
extracts tested in a broad range of antimicrobial assays, the SNB-CN88
crude extract showed a minimal inhibitory concentration (MIC) of 
$8~\rmmu\mathrm{g}/\mathrm{mL}$ against methicillin-resistant
\textit{Staphylococcus aureus} (MRSA) without cytotoxicity on healthy
human cells (MRC5 lines). 

SNB-CN88, isolated from a termite nest, was identified as a strain of
\textit{Serratia marcescens}, a bacterial species widely distributed in
the environment and an opportunistic Gram-negative nosocomial pathogen
belonging to the \textit{Enterobacteriaceae} family. This bacterium isolated
from a termite nest had already been observed in French
Guiana,~associated with mosquito  colonies~\cite{10}. 

In our study, approaches based on high-resolution mass spectrometry
(HRMS) and tandem mass spectrometry (MS/MS) were used to explore the
specialized metabolome of the mutualistic bacterial strain SNB-CN88.
Molecular diversity was annotated in a first step by exploring the
molecular network generated by MS/MS data, finely studying
fragmentation patterns, and then proposing putative \textit{in silico}
structures. In a second step, the isolation of the bioactive compounds
was performed to confirm their structures and determine their
antibacterial activities.

\section{Results and discussion}\label{sec2}
Molecular network (MN) is now considered a standard bioinformatic tool
in the metabolomic community. Its paradigm is based on the observation
that compounds with a high degree of structural similarity share
comparable MS/MS fragmentation patterns. To provide a clear separation
between MS/MS spectral clusters, only the most relevant similarity
scores are selected using dedicated filtering steps. In this study, we
used  MetGem~\cite{11a,11b} to explore the metabolome of \textit{Serratia
marcescens}. This software allows the parallel investigation of two
complementary representations of a raw dataset, one based on a classic
GNPS-style MN and another based on the t-SNE  algorithm~\cite{11a,11b,12}.
The t-SNE graph preserves the relationships between related groups of
spectra, while the MN output allows an unambiguous separation of
clusters. This multivariate embedding method focuses on local distances
using nonlinear outputs to represent the entire data space. The
relevance of the t-SNE output and its ability to accurately map the
spectral distribution of the metabolome of \textit{Serratia marcescens}
will be illustrated in the following\unskip\break 
experiments.

\begin{figure*}
\vspace*{.9pt}
\includegraphics{fig01}
\vspace*{1pt}
\caption{\label{fig1}t-SNE molecular network generated from metabolic
extract fractions of \textit{Serratia marcescens} SNB-CN88 colored
according to their MIC against MRSA. Dereplicated clusters are circled
in black. Dereplicated specialized metabolite clusters with MICs
${&lt;}64~\rmmu\mathrm{g}/\mathrm{mL}$ are circled in blue for cluster A,
red for cluster B and green for cluster C. Node sizes are relative to
the maximum intensity of ions in the whole dataset.}
\vspace*{2pt}
\end{figure*}

In this study, the crude extract of \textit{Serratia marcescens}
SNB-CN88 strain was fractionated into 18 fractions (F2 to F19) and each
fraction was tested against MRSA. Fractions F14 and F15 exhibited the
highest quantities (F14 (257~mg), F15 (467~mg)) as well as the highest
activities ($\mathrm{MIC}&lt;32~\rmmu\mathrm{g}/\mathrm{mL}$, 
Supplementary Table~S1). The activities observed for the fractions were
lower than those of the crude extract, suggesting a synergistic or
additive effect of the compounds in the mixture. Therefore, we sought
to identify most of the metabolites in the SNB-CN88 extract. All
fractions were then analyzed by liquid chromatography coupled to tandem
high-resolution mass spectrometry (LC-HRMS/MS) in positive ion mode
with data-dependent acquisition (DDA) mode. The generated MS/MS data
were processed to create a molecular network (MN) using MetGem software
and the t-SNE algorithm, which allows visualization of cluster 
proximity~\cite{11a,11b}. Molecules with intense MS signals are present in
clusters A, B, and C in t-SNE MN. These clusters group fractions
identified as the most active against MRSA and mainly belong to
fractions F14 and F15  (Figure~\ref{fig1}). 

In order to annotate actives molecules, a reduced t-SNE molecular
network from only the F14 and F15 fractions was generated from 1221
nodes with $m/z$ values ranging from 211 to 1361. As expected, clusters
A, B, and C were also identified in this reduced MN 
(Figure~\ref{fig2}).

\begin{figure*}
\includegraphics{fig02}
\vspace*{3pt}
\caption{\label{fig2}t-SNE molecular network generated from active
fractions of F14 and F15 of \textit{Serratia marcescens} SNB-CN88.
Dereplicated specialized metabolite clusters are circled in blue
for cluster A, red for cluster B and green for cluster C. Node sizes
are relative to the maximum intensity of ions in the whole dataset.}
\vspace*{3pt}
\end{figure*}

A first annotation was performed by interrogating MS/MS spectral
databases.~To refine the annotation of the features and to respect the
standards of reproducible science, the annotation levels proposed by
the Metabolomics Standards Initiative (MSI) were  used~\cite{12}. Level
0 corresponds to an unambiguous 3D structure obtained from isolated
pure compounds, level 1 corresponds to the compound identified in
comparison with a standard, level 2 corresponds to a putative
annotation (MS/MS library comparison or tentative structure), level 3
includes a chemical class assignment (comparison with literature), and
level 4 corresponds to unknown molecules  (Supplementary Table~S2).

The molecules in cluster A were searched using PubChem. The proposed
structures described in the literature led to the annotation of already
reported natural compounds, i.e., glucosamine derivatives 
(Figure~\ref{fig3})~\cite{13a,13b}. These compounds are small molecules
($m/z$ 545 to 627 for [M$+$H]$^{+}$ ions) composed of a sugar (glucose,
hexose), an amino acid (valine), a fatty acid (C13 to C17), and a
butyric or oxo-hexanoic acid. The highly intense fragment ion
corresponding to the sugar moiety was observed at $m/z$ 232.1177,
leading to several fragments at  $m/z$ 214.1071 (loss of one water
molecule), 196.0981 (loss of two water molecules), 166.0859, 144.0652,
and 126.0546  (Supplementary Figures~S1--S7). Compound \textbf{1} shows
a molecular peak at $m/z$ 559.3950  [M$+$H]$^{+}$ (calculated 559.3953,
err. 0.5 ppm) corresponding to the molecular formula of
C$_{29}$H$_{55}$N$_{2}$O$_{8}$. This compound has a fatty acid moiety
labelled at  $m/z$ 328.2819 (saturated C$_{14}$ fatty acid chain with a
valine residue calculated 328.2840, err. 6~ppm) and a glucose residue
bound to butyric acid labelled at  $m/z$ 232.1181 (calculated 232.1176,
err. $-$2~ppm); therefore, its structure is similar to the glucosamine
derivative C (\textbf{1})  (Supplementary Figure~S1)~\cite{13a,13b}.
\looseness=1

\begin{figure*}
\vspace*{-2pt}
\includegraphics{fig03}
\vspace*{-2pt}
\caption{\label{fig3}(A)~Annotated Cluster C obtained for t-SNE
molecular network generated. (B)~Enlargement of nodes for annotation.
The color of the nodes is relative to the representation of the
fractions F14 (blue) and F15 (red) and their sizes relative to the
maximum intensity of these ions in the whole dataset.}
\end{figure*}

Similar to compound \textbf{1}, each compound in cluster A exhibits a
major fragment at  $m/z$ 232.1 and their fragments  (Supplementary
Figures~S2--S7). Compounds \textbf{2}--\textbf{7} have been annotated
by comparison with the literature as glucosamide derivatives analogs
(Glu) A, C, D, E, F, H and L. MS/MS spectrum of compounds \textbf{8},
\textbf{9} and \textbf{10} showed a fragment at $m/z$ 348.2525,
340.2839 and 370.2944, respectively, corresponding to a valine residue
bound to a unsaturated C$_{16:4}$ for \textbf{8} and a 
C$_{15:1}$ fatty acid for \textbf{9} (Supplementary
Figure~S7). MS/MS data from compound \textbf{10} shows a major fragment 
{corresponding} to a valine linked to a saturated C$_{17}$ fatty acid
acyl chain and not to C$_{16:\mathrm{OH}}$ as described previously for
Glucosamine  derivatives L~\cite{13a}. These three new annotated
glucosamine derivatives \textbf{8}--\textbf{10} were named glucosamine
derivatives O,  P and L~\cite{13a,13b,14a,14b}.
\looseness=-1

Cluster B contains compounds related to $N$-acetyl-D-glucosamine and
was annotated via the GNPS databases  (Figure~\ref{fig4}). Indeed, the
only dereplicated compound of cluster B is the potential precursor of
the compounds of cluster A. This molecule exhibits a  $m/z$ value at
232.1177 and corresponds to the calculated chemical formula of
C$_{10}$H$_{18}$NO$_{5}$ (err. 1.1 ppm,  Supplementary Figure~S8).
Compound \textbf{11} was dereplicated by MS data as
$N$-(2-ethyl-3,4-dihydroxy-3,4-dihydro-2$H$-pyran-5-yl)butyramide. 

\begin{figure*}
\vspace*{-3pt}
\includegraphics{fig04}
\vspace*{-2pt}
\caption{\label{fig4}(left) Dereplicated $N$-acetyl-D-glucosamine
($m/z$ 232.1177) in Cluster B, (right) comparison between database and
experimental mass spectra.}
\vspace*{-3pt}
\end{figure*}

The different nodes observed in cluster B suggest that different sugars
may be present in our extract. Thanks to the use of the t-SNE
algorithm, we were able to annotate the glucosamine precursor
\textbf{11}, observed as a solitary node when using classical GNPS-like
representation~\cite{13a,13b}. 

The size of the nodes is relative to the maximum intensity of these
ions in the data set, thus allowing to estimate the amount of each
molecule in the extract or fractions of \textit{S. marcescens}. The
main compounds found in fraction F14 are molecules \textbf{1},
\textbf{2}, \textbf{3} and \textbf{11}, and in fraction 15 compounds
\textbf{2}, \textbf{5}, \textbf{6} and \textbf{11}. Only compound
\textbf{2} (GluE) is found in high proportion in these two fractions.
All these metabolites may be partly responsible for the observed
antibacterial activity. Analogs of glucosamine derivatives have been
reported in the literature to have antibacterial 
activity~\cite{13a,13b,14a,14b,15a,15b}. Bioassays on  compound
\textbf{1} (GluC derivative), previously isolated from a strain  of
\textit{Serratia} sp., showed weak activity against
\textit{Mycobacterium diernhoferi} which is probably due to the
complexity of its cell  wall~\cite{14a}. Several other glucosamine
analogs have been annotated in the metabolic profiles of
\textit{Serratia marcescens} strains and some of them (GluC and GluA)
showed MIC values of  $156~\rmmu\mathrm{g}/\mathrm{mL}$ against
\textit{S. aureus}~\cite{13a,13b}. Therefore, the observed biological
activity of our strain extract is due to GluC, D, E, F and L or either
to the synergistic or additive effect of the glucosamide mixture or to
other compounds. This is why we were also concerned with Cluster C.

In cluster C, 6 stephensiolides were annotated by comparing the MS data
with the chemical formulas in the  literature~\cite{13a,13b,15a,15b}. The
stephensiolides (Stp) were described with five amino acid residues
(Thr-Ser-Ser-Val/Ile-Val/Ile) linked to a $\beta$-hydroxy fatty acyl
residue  (C8--C14)~\cite{13a,13b,16}. Therefore, MS/MS spectra were used for
preliminary screening\unskip\break 
of stephensiolide analogs  
(Supplementary
Figures~S9--S15). Compounds \textbf{12}--\textbf{18} were dereplicated
as stephensiolides C, D, E, F, G, I and R, respectively 
(Figure~\ref{fig5}). Two analogs \textbf{19}  and \textbf{20}  were
proposed by comparison with MS/MS spectra database. The difference in
$m/z$ between compound \textbf{15} and compound \textbf{19} is 2.0152
(calculated 2.0157, err. 2.48 ppm), which corresponds to a double bond
located on the C9 alkyl chain from the MS/MS fragmentation spectra 
(Supplementary Figure~S16). Then, the difference in mass between 
compounds \textbf{20} and \textbf{15}  is 42.047 Da, which may
correspond to 3 additional methylene groups (calculated 42.047, err. 0
ppm), i.e.  an unsaturated C12 alkyl chain  (Supplementary Figure~S17).
Then, these two annotated compounds were named by comparison with the
literature stephensiolides U2 (\textbf{19}) and dehydrostephensiolide F
(\textbf{20}). Finally, the use of t-SNE algorithm for molecular
network visualization allows us to observe that on the right of cluster
C (separated by a dotted line in Figure~\ref{fig5}) amino acid residues 5
are always valines, while on the left of the same cluster Ile/Leu
residues are always found  (Supplementary Figures S9--S17). These data
suggest that the sequence of the different amino acids of
stephensiolides may vary as reported by 
Clements-Decker et~al.\ (Figure~\ref{fig5})~\cite{13a,13b}. As a result, we
were able to identify molecules \textbf{21}  and \textbf{22}  as
stephensiolides K and  Q~\cite{13a,13b}.

\begin{figure*}
\vspace*{-4pt}
\includegraphics{fig05}
\vspace*{-3pt}
\caption{\label{fig5}\fontsize{9}{10.8}\selectfont
(A)~Annotated Cluster C obtained for the generated
t-SNE molecular network.  (B)~Enlargement of nodes for annotation, part
surrounded by dotted lines. The color of the nodes is relative to the
representation of the fractions F14 (blue) and F15 (red) and their
sizes relative to the maximum intensity of these ions in the whole
dataset.}
\end{figure*}

\begin{figure*}
\vspace*{3pt}
\includegraphics{fig06}
\vspace*{3pt}
\caption{\label{fig6}Major NMR correlations observed for compounds
\textbf{14} and \textbf{15}, COSY correlations are shown in bold and
HMBC correlations by arrows.}
\vspace*{3pt}
\end{figure*}

In order to confirm annotation of the major compounds, fraction F14 and
F15 were re-fractionated to isolate pure molecules. Seven subfractions
from fraction F14 and 5 subfractions form F15 were obtained by flash
chromatography (Supplementary Table~S1). All these fractions were
biologically tested showing that fractions F14.F and F15.E are the most
active with MIC at 32 and  $8~\rmmu\mathrm{g}/\mathrm{mL}$,
respectively\unskip\break 
(Supplementary Table~S1). 

The purification of fraction F14.F allowed us to isolate the major
compound \textbf{14}. The HR-ESI-MS analyses show a molecular peak at
$m/z$ 654.4108  [M$+$H]$^{+}$ corresponding to the calculated molecular
formula of C$_{32}$H$_{56}$N$_{5}$O$_{9}$ (calculated 654.4078, err.
4.58 ppm). Analysis of the $\mbox{}^1$D and
$\mbox{}^2$D NMR spectra and LC-MS/MS indicated
the presence of five amino acids: threonine and two valine and serine
residues  (Supplementary Figures S18--S24). A large aliphatic peak in
the $\mbox{}^1$H NMR spectrum of compound 14 suggested the presence of a long
alkyl chain typical of lipopeptides. HMBC correlations indicated that
the nitrogen atom of the threonine was acylated with this alkyl chain,
whereas the shift of Thr H-2 suggested that the hydroxyl group of
threonine was esterified  (Figure~\ref{fig6}). Further HMBC
correlations show that threonine is linked to valine via an ester bond
and to serine through an amide bond. The positions of the remaining
serine and valine residues were determined by COSY correlations between
NH and H-1 and HMBC correlations between NH/H-1/H-2 and their
respective carbonyls  (Figure~\ref{fig6}). Purification of the F15.E
fraction allowed us to isolate the major compound \textbf{15}. HR-ESI-MS
analyses show a molecular peak at  $m/z$ 668.4224 [M$+$H]$^+$
(calculated 668.4229, err. 0.8 ppm) corresponding to the calculated
molecular formula of C$_{33}$H$_{57}$N$_{5}$O$_{9}$. 
MS and\unskip\break 
NMR analysis
of this compound determined the presence of the following 5 amino
acids: threonine, valine, isoleucine, and two serine residues, as well
as the presence of an alkyl chain  (Supplementary Figures~S25--S30).
The amino acid residue chain was determined in the same way as that for
compound \textbf{14}  (Figure~\ref{fig6}). The masses of these two compounds
allow us to determine that we have C12 fatty acid chains. The olefinic
signals in the $\mbox{}^1$H NMR spectra for \textbf{14} 
and \textbf{15} and two carbons
in  $\mbox{}^{13}$C NMR observed at 130.1/128.9 and 131.9/129.6~ppm,
respectively, suggest the presence of a double bond within the lipid
side chain. The location of these double bonds for \textbf{14} and \textbf{15} were
determined by HMBC correlations to be between the C-5 and C-6 carbons
in the acyl chain. The $^{13}$C shifts of the vinyl carbons along with
constants between the sp2 proton (10.9~Hz,  Supplementary Figure~S26)
suggest the Z isomer~\cite{17a,17b,17c}. All the experimental 
$\mbox{}^1$D and $\mbox{}^2$D NMR data and comparison with the
literature allowed us to determine that stephensiolides E (\textbf{14}) and F
(\textbf{15}) were  isolated~\cite{13a,13b,14a,14b,15a,15b,16}. 
\looseness=-1

The compounds predominantly found in fractions F14
(\textbf{12}--\textbf{14}) and F15 (\textbf{14}--\textbf{20}) seem to
be responsible for the observed activities. The major compounds
\textbf{14}  and \textbf{15}  isolated from fractions F14.F and F15.E
showed antimicrobial activity against MRSA (MIC ${=}$ 4 and
$8~\rmmu\mathrm{g}/\mathrm{mL}$, respectively). Only StpE 
(\textbf{14}) is found in a large proportion in these two fractions.
This result can explain the observed antimicrobial activity of the
\textit{Serratia marcescens} strain. Compounds \textbf{14}  and
\textbf{15}  were previously isolated from \textit{Serratia} sp. and
\textit{Lecanicillium} sp. strains and showed activity against
\textit{Bacillus subtilis} and MRSA  $(\mathrm{MICs} &lt;
32~\rmmu\mathrm{g}/\mathrm{mL})$~\cite{15a,15b}.\unskip\break  
The metabolites
\textbf{12}--\textbf{17} named stpC, D, F, G, and I were also isolated
from the \textit{Lecanicillium} sp. strain and showed activity against
MRSA with MIC values of 128, 32, 32, 16 and 
$4~\rmmu\mathrm{g}/\mathrm{mL}$, respectively, whereas weak or no
activity was observed in a previous study for other stephensiolides
(StpQ, StpR, StpK) against \textit{S.~aureus}, with MIC higher than  
$300~\rmmu\mathrm{g}/\mathrm{mL}$~\cite{13b}.\looseness=1

\section{Conclusion}\label{sec3}
The molecular network approach using the t-SNE algorithm allowed us to
easily annotate new target compounds responsible for the observed
biological activity on~MRSA. Our study highlighted that
\textit{Serratia marcescens} SNB-CN88, isolated from a termite nest,
could produce diverse stephensiolides and glucosamine analogs with
antimicrobial activity against methicillin-resistant
\textit{Staphylococcus aureus} (MRSA). Moreover, 22 compounds were
annotated; 2 stephensiolides and 3 glucosamine derivatives were
identified for the first time in this study, and two major compounds,
including new metabolites from active fractions of SNB-CN88 crude
extract, were isolated and structurally characterized. Compounds
\textbf{14} and \textbf{15} were identified as known stephensiolides E
and F (for which $\mbox{}^{13}$C and  $\mbox{}^{1}$H NMR are described
for the first time, see  Supplementary Table~S3). All identified
compounds contributed to the observed biological activity of the crude
extract and its fractions. First, stephensiolide E and F showed
antimicrobial activity against MRSA with 
$\mathrm{MIC}\leq8~\rmmu\mathrm{g}/\mathrm{mL}$.  Other compounds that
were not isolated in this study could also have antimicrobial
activities. In particular, the glucosamine derivative E (\textbf{2}),
which is present in large amounts in the fractions, has never been
isolated, characterized, or tested biologically. This compound may
possess antibacterial activity similar to that of its analog
(glucosamine derivative C). 

Preliminary data suggest that this strain SNB-CN88 of \textit{Serratia
marcescens} biosynthesizes different compounds from the strain of the
same species published by  Clements-Decker et~al.~\cite{13a,13b} and
suggested another operational chemical unit (OCU) of \textit{S.
marcescens}, as proposed by Barth\'{e}lemy  et~al.~\cite{18}. Clardy's
team determined the biosynthetic origin of stephensiolides by
sequencing the genome of \textit{Anopheles}-associated
\textit{Serratia} sp. and demonstrated that biosynthesis differed
according to the media used \textit{in vitro}, which appear to 
differ from the\unskip\break 
natural  environment~\cite{16}. 
Consequently, the strain
origin may explain the molecular composition differences observed with
those previously published in the literature. 

Stephensiolides may play a protective role against entomopathogenic
bacteria and  viruses~\cite{13a,13b,16}. This study suggests that termite
mounds (workers, soldiers, tunnel and nest, here called meta-holobiont)
can be putatively protected from biotic aggressions of the environment
by association with a \textit{Serratia} sp. strain. In return, this
association would allow \textit{Serratia} sp. strains in association
with the termite meta-holobiont to be easily propagated in the
environment because of the termites' way of life (e.g. swarming,
feeding, prospecting\,{\ldots}). 

The Gram-negative bacterium \textit{Serratia marcescens} is also known
to be an opportunistic pathogen responsible for a wide range of human
diseases, including ocular, uropathogenic, and respiratory 
infections~\cite{19a,19b}. Studying the termite microbiome could help to
understand the transmission of this human infectious disease and
improve our understanding of the complex interspecies relationships
that contribute to the transmission of vector-borne infectious agents. 

\section{Materials and methods}\label{sec4}

\subsection{General experimental procedure}\label{sec4.1}
NMR spectra were recorded on Bruker 300, 500, 600, and 700~MHz
spectrometers (Bruker, Rheinstetten, Germany). The chemical shifts
($\rmdelta$) are reported as ppm based on the solvent signal, and the
coupling constants $(J)$ are in hertz. Preparative HPLC was conducted
using a Gilson system equipped with a 322 pumping device, a GX-271
fraction collector, a 171 diode array detector, and a prep ELSII. All
solvents were HPLC grade, purchased from Sigma-Aldrich
(Saint-Quentin-Fallavier, France).

\subsection{Isolation and identification of termite mutualistic
microorganisms}\label{sec4.2}
{The mutualistic bacterial  strain}
was isolated in 2009 from an environment (termite aerial
nest of \textit{Nasutitermes similis}) sampled in Piste de Saint-Elie
in French Guiana (ABSCH-CNA-FR-240495-2). The strain SNB-CN88 from the
strain library collection at
ICSN was identified as \textit{Serratia
marcescens}. Taxonomic marker
analyses were\unskip\break 
externally performed by
BACTUP, France. Bacterial isolates were
identified on the basis of 16S rDNA sequence analysis. The sequences
were aligned with DNA sequences from GenBank, NCBI
(\url{http://www.ncbi.nlm.nih.gov}, accessed on 7 June 2021), using BLASTN
2.2.28. The sequences were deposited in GenBank under the registry
number KJ023777. 

\subsection{Culture and extraction of microorganisms}\label{sec4.3}

\subsubsection{General cultivation and extraction
procedure}\label{sec4.3.1} 
SNB-CN88 was cultivated on 330 Petri dishes (14~cm diameter) at 
28~\textdegree C for 15 days on potato dextrose agar (PDA) medium
(Dominique Dutscher SAS, Brumath, France). The culture medium
containing the mycelium was cut into small pieces and macerated three
times at room temperature with ethyl acetate (EtOAc) on a rotary shaker
(70 rpm) for 24~h. The contents were extracted with 10~L of EtOAc using
a separatory funnel. Insoluble residues were removed via filtration,
and the organic phase was washed three times with an equivalent volume
of water (H$_2$O), dried with anhydrous solid Na$_{2}$SO$_{4}$, and
then evaporated using a rotary evaporator under reduced pressure and a
temperature of  30~\textdegree C to yield a crude\unskip\break  
extract (2.7~g). 

\subsubsection{Fractionation of SNB-CN88}\label{sec4.3.2}
The crude extract (2.7~g) was fractionated using reverse-phase flash
chromatography (Grace Reveleris, Grace, Maryland, USA) with a C18
column and UV and DEDL detectors. A 10-min step gradient of
H$_{2}$O/formic acid (99.9/0.1)-acetonitrile/formic acid (99.9/0.1)
(v/v 95/5, 75/25, 50/50, 20/80, 0/100) with a flow rate of 80 mL/min
was performed, followed by a second gradient 50\% acetonitrile/formic
acid (99.9/0.1)-methylene chloride for 15~min and then 100\% methylene
chloride in 15~min with a flow rate of 80~mL/min was performed to
generate 18 fractions, named F2 (38.8~mg), F3 (19.4~mg), F4 (13.9~mg),
F5 (26.6~mg), F6 (83.0~mg), F7 (5.6~mg), F8 (96.9~mg), F9 (62.2~mg),
F10 (46.7~mg), F11 (34.6~mg), F12 (76.5~mg), F13 (90.7~mg), F14
(257~mg), F15 (467~mg), F16 (165~mg), F17 (76.5~mg), F18 (26.2~mg) and
F19 (586~mg). 

The F14 fraction was fractionated by flash reverse phase chromatography
using a C18 column and UV and ELSD 
detectors.
A 6.5-min step
gradient\unskip\break 
of solvent A (H$_{2}$O/formic acid (99.9/0.1)) and solvent B
(acetonitrile) (v/v 75/15, 0/100) followed by a second gradient 50\%
acetonitrile (B) and 50\% dichloromethane (A) for 6.7~min and finished
with a third gradient 100\% isopropyl alcohol for 10~min with a flow
rate of 30 mL/min were performed to generate 7 fractions, named F14.A
(2.1~mg), F14.B (0.9~mg), F14.C (1.8~mg), F14.D (3.4~mg), F14.E
(17.0~mg), F14.F (42.8~mg), F14.G (0.7~mg).

The F15 fraction was fractionated by flash reverse phase chromatography
(CombiFlash NextGen300, Teledyne Technology, USA) using a C18 column
and UV and ELSD detectors. A 5.9-min step gradient of solvent A
(H$_{2}$O/formic acid (99.9/0.1)) and solvent B (acetonitrile) (95:5)
followed by a second gradient 57.6\% acetonitrile (B) and 42.4\%
dichloromethane (A) for 8.3~min and a third gradient 54.4\%
acetonitrile (B) and 45.6\% dichloromethane (A) for 2. 7~min with a
flow rate of 30~mL/min were performed to generate 5 fractions, named
F15.A (2.0~mg), F15.B (5.9~mg), F15.C (2.0~mg), F15.D (4.5~mg), F15.E
(212.0~mg). 

Fractions F14.F and F15.E (20~mg) were re-purified by preparative HPLC
(Agilent InfinityLab Proshel $120\times4$ SB-C18,  $21.2\times
1500$~mm) with the following\unskip\break
parameters: flow rate: 21~mL/min, eluents:
H$_{2}$O$+$\ubreak0.1\% formic acid (A) and ACN (B), gradient (using isocratic
elution): 40\% B to 55\% B (in 4~min), 55\% B (in 9~min), 55\% B to
100\% B (in 9~min), 100\% B (in 10~min) to give compound \textbf{14}
($t_R$ 12.8~min, 2.3~mg) and compound \textbf{15} ($t_R$ 14.8~min,
1.2~mg), respectively.

\subsubsection{Molecules isolation and
characterization}\label{sec4.3.3}
Stephensiolide E (\textbf{14}) white powder; $\mbox{}^1$H NMR
(700~MHz, DMSO-$d_6$)  $\rmdelta_{\mathrm{H}}$ Threonine1: 7.94 (1H, d
(J ${=}$ 9.3~Hz), NH), 4.46 (1H, m, H-1), 5.29 (1H, m, H-2), 1.15 (3H, m,
H-3), $\rmdelta$H Serine2: 7.52 (1H, d (J ${=}$ 7.6~Hz), NH), 4.25 (1H,
m, H-1), 3.47 (1H, m, H-2a), 3.51 (1H, m, H-2b), $\rmdelta$H Serine3:
7.84 (1H, d (J ${=}$ 7.6~Hz), NH), 4.13 (1H, m, H-1), 3.52 (1H, m, H-2a),
3.69 (1H, m, H-2b), Valine4: 7.72 (1H, d (J ${=}$ 7.3~Hz), NH), 4.13 (H,
m, H-1), 2.02 (2H, m, H-2), 0.85 (3H, m, H-4), 0.84 (3H, m, H-3),
$\rmdelta$H Valine5: 8.39 (1H, d (J ${=}$ 6.4~Hz), NH), 4.19 (1H, m,
H-2), 2.02 (1H, m, H-3), 0.86 (3H, m, H-5), 0.83 (3H, m, H-4),
$\rmdelta${H Acyl: 5.36 (1H, m, H-5), 5.35 (1H, m, H-6), 2.27 (2H, m,
H-2), 2.02 (2H, m, H-4), 1.99 (2H, m, H-7), 1.29 (2H, m, H-8), 1.59
(2H, m, H-3), 1.25 (4H, m, H-9 and H-11), 1.24 (2H, m, H-2, H-10), 0.85
(3H, m, H-12); $^{13}$C NMR (700~MHz,\unskip\break 
DMSO-$d_6$)} $\rmdelta${C Threonine1:
168.7 (C, C${=}$O), 55.8\unskip\break  
(CH, C-1), 
69.9 (CH, C-2), 17.5 (CH3, C-3);}
$\rmdelta$C Serine2: 170.5 (C, C${=}$O), 61.3 (CH2, H-2), 54.6 (CH, C-1),
$\rmdelta$C Serine3: 170.6 (C, C${=}$O), 59.7 (CH2, H-2), 55.2 (CH, C-1),
$\rmdelta$C Valine4: 170.7 (C, C${=}$O), 57.8 (CH, C-1), 28.9 (CH, C-2),
19.1 (CH3, C-3), 18.4 (CH3, C-4), $\rmdelta$H Valine5: 170.1 (C, C1),
57.5 (CH, C-1), 30.0 (CH, C-2), 18.7 (CH$_{2}$, C-3), 18.3 (CH$_{3}$,
C-4), $\rmdelta_{\mathrm{H}}$ Acyl: 172.9 (C${=}$O), 130.1 (CH, C-6),
128.9 (CH, C-5), 34.9 (CH$_2$, C-2), 31.1 (CH$_{2}$, C-10), 29.1
(CH$_{2}$, C-8), 28.3 (CH$_{2}$, C-9), 26.6 (CH$_{2}$, C-7), 26.3
(CH$_{2}$, C-4), 25.4 (CH$_{2}$, C-3), 22.0 (CH$_{2}$, C-11), 13.9
(CH$_{3}$, C-12). ESI--HRMS  $m/z$ [M$+$H]$^+$ 654.4108 (calcd for
C$_{31}$H$_{56}$N$_{5}$O$_9$H$^+$, 642.4078 err. 4.5~ppm). 

Stephensiolide F (15) white powder; $\mbox{}^1$H NMR (700~MHz, MeOD)
$\rmdelta$H Threonine1: 7.07 (1H, d (J ${=}$ 8.9~Hz), NH), 4.72 (1H, m,
H-1), 5.56 (1H, q (J ${=}$ 6.5~Hz), H-2), 1.29 (3H, m, H-3), $\rmdelta$H
Serine2: 7.28 (1H, d, (J ${=}$ 7.2~Hz), NH), 4.36 (1H, m, H-1), 3.78 (2H,
m, H-2), $\rmdelta$H Serine3: 6.96 (1H, d (J ${=}$ 7.2~Hz), NH), 4.36
(1H, m, H-1), 3.96 (1H, m, H-2a), 3.82 (1H, m, H-2b), $\rmdelta$H
Valine4: 7.12 (1H, d (J ${=}$ 8.9~Hz), NH), 4.24 (1H, t (J ${=}$ 8.9~Hz),
H-1), 2.13 (1H, m, H-2), 0.96 (6H, m, H-3 and H-4), $\rmdelta$H
Isoleucine5: 6.96 (1H, d (J ${=}$ 6.8~Hz), NH), 4.24 (1H, t (J ${=}$
6.8~Hz), H-1), 1.82 (1H, m, H-2), 1.51 (1H, m, H-3a), 1.21 (1H, m,
H-3b), 0.96 (3H, m, H-4), 0.91 (3H, m, H-5), $\rmdelta$H Acyl: 5.42
(1H, m, H-5), 5.41 (1H, m, H-6), 2.36 (2H, m, H-2), 1.71 (1H, m, H-3),
1.29-1.38 (12H, m, H-4, H7, H8, H9, H10, H11), 0.96 (3H, m, H-12); $^{13}$C
NMR (700~MHz, MeOD) $\rmdelta$C Threonine1: 171.9 (C, C${=}$O), 71.5 (CH,
C-2), 57.5 (CH, C-1), 19.7 (CH3, C-3); $\rmdelta$C Serine2: 173.3 (C,
C${=}$O), 62.9 (CH$_{2}$, H-2), 56.2 (CH, C-1), $\rmdelta$C Serine3: 173.3
(C, C${=}$O), 56.1 (CH, C-1), 61.0 (CH2, H-2), $\rmdelta$C Valine4: 170.7
(C, C${=}$O), 57.8 (CH, C-1), 28.9 (CH, C-2), 19.1 (CH3, C-3), 18.4 (CH3,
C-4), $\rmdelta$H Isoleucine5: 172.5 (C, C${=}$O), 59.8 (CH, C-1), 37.6
(CH, C-2), 27.0 (CH2, C-3), 15.6 (CH3, C-4), 14.0 (CH3, C-5);
$\rmdelta_{\mathrm{H}}$ Acyl: 176.9 (C${=}$O), 131.9 (CH, C-6), 129.6 (CH,
C-5), 23.6-36.6 (8CH$_{2}$, C-2, C-3, C-4, 7-5, C-8, C-9, C-10, C-11),
11.0 (CH$_{3}$, C-12). ESI--HRMS $m/z$  [M$+$H]$^+$ 668.4241 (calcd for
C$_{33}$H$_{56}$N$_{5}$O$_{9}$H$^+$, 668.4229 err. 0.8~ppm).

\subsection{Metabolomic analysis}\label{sec4.4}

\subsubsection{LC-MS/MS analyses}\label{sec4.4.1}
Crude extract and fractions of SNB-CN88 were prepared at 1~mg/mL in
methanol and filtered on a $0.45~\rmmu\mathrm{m}$ PTFE membrane. LC-MS/MS
analyses were performed with an HPLC 1260 Prime \mbox{chromatography} chain
(Agilent Technologies, Waldbrom, Germany) coupled with an Agilent 6546
Q-ToF mass spectrometer (Agilent Technologies, Walbronn, Germany). LC
separation was performed using an Accucore RP-MS column  ($100 \times
2.1$~mm, $2.6~\rmmu\mathrm{m}$, Thermo Scientific, Les Ulis, France)
with a mobile phase of H$_{2}$O/formic acid (99.9:0.1) and
acetonitrile/formic acid (99.9:0.1). The column oven was set at
45~\textdegree C. The compounds were eluted with a flow rate of
0.4~mL/min with a gradient from 5\% B to 100\% B in 20~min and then
100\% B for 3~min. The injection volume was $5~\rmmu\mathrm{L}$ for all
analyses. For the electrospray ionization source, the mass spectra were
acquired in positive ionization mode with the following parameters:
temperature of the drying gas 325~\textdegree C, flow rate of the
focalizer gas  10~L/min, capillary voltage 3500~V, nozzle voltage
500~V, fragmentor voltage 130~V, skimmer voltage 45~V and RF voltage of
the octopole  1750~V. An internal calibration was performed using two
standards: purine and hexakis(1H,1H,3H-tetrafluoropropyxy)phosphazene
($m/z$ 121.0509 and $m/z$ 922.0098), allowing high-resolution masses
with less than 5 ppm error. MS/MS data-dependent acquisition was
performed on the 5 most intense ions detected by a full MS1 scan in the
$m/z$ 200--1000 range, above a threshold of 1000 counts. The selected
precursor ions were fragmented with a collision energy set at 30~eV
with an isolation window of 1.3~amu. The mass range of the precursor
and fragment ions was set between 50 and $1000~m/z$.

\subsubsection{Data processing analysis}\label{sec4.4.2}
The raw data files were converted from .d format (Agilent Technologies)
to .mzML format using MSConvert software, which is part of the Proteo
Wizard  3.0 package~\cite{20}. All .mzML files were reprocessed using
MZmine v. 2.53 software. Mass detection was performed using an MS/MS
background noise level of 1000 for MS1 and 50 for MS/MS. The ADAP
chromatogram builder was used with a minimum group size of 3, minimum
group intensity of 1000, and  $m/z$ tolerance of 0.005 (or 15 ppm).
Chromatogram devolution was performed with the ADAP wavelet algorithm
using the following parameters: a threshold signal-to-noise ratio of
30, a minimum component peak height of 50~000, a threshold
coefficient/area ratio of 10, a peak duration of\unskip\break  
0.001--1~min, and a
wavelet retention time range of 0.01--0.08~min. Isotope clustering was
performed \mbox{using} the isotope peak clustering algorithm with an  $m/z$
tolerance of 0.005 (or 15 ppm) and a retention time tolerance of 
0.1~min. Peaks were filtered using the filter function of the component
list to remove all components associated with no MS/MS spectrum. Peak
alignment was performed using the attached alignment function, with an 
$m/z$ tolerance of 0.005 (or 15 ppm), a weight for  $m/z$ of 80, a
retention time tolerance of 0.1~min, and a weight for retention time of
20. The ``export/import'' function was used to generate .mgf and .csv
files. MetGem version 1.3.4 was used to generate the molecular
networks. To add a ``network'' visualization, the spectra were filtered
by keeping the 10 most intense peaks in a sliding window in the
spectrum of ${\pm}$ 50 Da. Peaks present in the range of ${\pm}$ 17~Da
around the  $m/z$ of the precursor ion were removed. The  $m/z$
tolerance to match peaks was set at 0.04 Da, and cosine scores were
only considered when a minimum of two peaks were matched between 2
spectra. The number of iterations, perplexity, learning speed, and
early exaggeration were set to 5000, 25, 10, and 12, respectively, for
the t-SNE representation.  Figures were generated using the MetGem
export function and ChemDraw Professional 16.0 (PerkinElmer). The NMR
spectra were processed and analyzed using TopSpin 3.6.2 (Bruker,
Rheinstetten, Germany). 

\subsection{Biological essay}\label{sec4.5}
The crude extracts and pure isolated compounds were tested on human
pathogenic methicillin-resistant \textit{Staphylococcus aureus} (ATCC
33591). The test was performed in conformance with the reference
protocols of the European Committee on Antimicrobial Susceptibility 
Testing~\cite{21}. The MIC was obtained
after 24~h. Vancomycin was used as a positive control. 

For cytotoxic assays, the crude extracts and isolated compounds were
tested in triplicate at concentrations of 
$10~\rmmu\mathrm{g}/\mathrm{mL}$ and  $1~\rmmu\mathrm{g}/\mathrm{mL}$
in the MRC5 cell line (ATCC CCL-171, Human Lung Fibroblast Cells),
following the procedure described by  Temp\^{e}te et~al.~\cite{22}.


\section*{Declaration of interests}
The authors do not work for, advise, own shares in, or receive funds
from any organization that could\unskip\break  
benefit from this article, and have
declared no affiliations other than their research organizations.

{\vspace*{-2pt}}

\section*{Acknowledgments}

{\vspace*{-2pt}}

The authors are grateful to N. Pollet, Universit\'{e} Paris-Saclay,
CNRS, IRD, \'{E}volution G\'{e}nomes Comportement \&amp; \'{E}cologie,
91198 Gif-Sur-Yvette, France for their assistance in strain
identification. 

\back{}

{\vspace*{-2pt}}

\section*{Supplementary data}

{\vspace*{-2pt}}

Supporting information for this article is available on the journal's
website under \printDOI\ or from the author.  

\CDRsupplementaryTwotypes{supplementary-material}{\cdrattach{crchim-259-suppl.pdf}}

{\vspace*{-2pt}}

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