# Bacterial tubular networks channel carbohydrates in insect endosymbiosis

Séverine Balmand, Camille Rivard, Sergio Peignier, Rachel

Santarella-Mellwig, Meriem Ghanem-Debbache, Justin Maire, Tobias Engl,

Mariana Galvão Ferrarini, Elisa Dell'aglio, Blanca Soriano-Saiz, et al.

► To cite this version:

Séverine Balmand, Camille Rivard, Sergio Peignier, Rachel Santarella-Mellwig, Meriem Ghanem-Debbache, et al.. Bacterial tubular networks channel carbohydrates in insect endosymbiosis. Cell, 2025, 10.1016/j.cell.2025.10.001. hal-05395665

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Distributed under a Creative Commons Attribution 4.0 International License
# Bacterial tubular networks channel carbohydrates in insect endosymbiosis

## Graphical abstract

<figure><img src="image_2.png" /></figure>

## Authors

Séverine Balmand, Camille Rivard, Sergio Peignier, ..., Martin Kaltenpoth, Abdelaziz Heddi, Anna Zaidman-Rémy

## Correspondence

abdelaziz.heddi@insa-lyon.fr (A.H.),
anna.zaidman@insa-lyon.fr (A.Z.-R.)

## In brief

Bacteria with an intracellular lifestyle need to feed from inside their host cells. This study shows an adaptation of certain symbiotic bacteria, allowing them to actively retrieve nutrients from the host. High-pressure cryofixation has been combined with volume electron microscopy and *in situ* high spatial resolution chemical analysis. It reveals a complex bacterial membranous network that increases the exchange interface between the bacteria and host cytosol and maximizes carbohydrate acquisition.

## Highlights

* Volume electron microscopy unveils intensive membrane networks in insect symbiotic cells

* These tubenets are formed by intracellular bacteria, the insect's nutritional symbionts

* *In situ* high spatial resolution chemical analysis shows tubenets' enrichment in sugar

* Bacterial tubenets increase the interface of exchange, maximizing nutrient acquisition
<figure><img src="image_3.png" /></figure>

Short article

# Bacterial tubular networks channel carbohydrates in insect endosymbiosis

Séverine Balmand,<fnref n="1" /> Camille Rivard,<fnref n="2" />,<fnref n="3" />,<fnref n="11" /> Sergio Peignier,<fnref n="1" />,<fnref n="11" /> Rachel Santarella-Mellwig,<fnref n="4" /> Meriem Ghanem-Debbache,<fnref n="1" /> Justin Maire,<fnref n="1" /> Tobias Engl,<fnref n="5" />,<fnref n="6" /> Mariana Galvão Ferrarini,<fnref n="1" /> Elisa Dell'Aglio,<fnref n="1" /> Blanca Soriano-Saiz,<fnref n="1" /> Charline Dalverny,<fnref n="7" /> Veronica La Padula,<fnref n="7" /> Petri Turunen,<fnref n="8" /> Isabelle Rahioui,<fnref n="1" /> Agnès Vallier,<fnref n="1" /> Carole Vincent-Monégat,<fnref n="1" /> Baptiste Vierne,<fnref n="1" /> Nicolas Parisot,<fnref n="1" /> Guy Condemine,<fnref n="9" /> Pedro Da Silva,<fnref n="1" /> Xavier Jaurand,<fnref n="7" /> Yannick Schwab,<fnref n="4" /> Martin Kaltenpoth,<fnref n="5" />,<fnref n="6" /> Abdelaziz Heddi,<fnref n="1" />,\* and Anna Zaidman-Rémy<fnref n="1" />,<fnref n="10" />,<fnref n="12" />,\*

## SUMMARY

Symbiosis is widespread in nature and plays a fundamental role in organism adaptation and evolution. In nutritional endosymbiosis, host cells accommodate intracellular bacteria and act as a “metabolic factory,” requiring extensive metabolic exchanges between host and endosymbiont. To investigate the mechanisms supporting these exchanges, we used the association between the bacterium *Sodalis pierantonius* and the insect *Sitophilus* spp. that thrives on an exclusive cereal diet. Volume electron microscopy uncovered that endosymbionts generate complex membranous tubular networks (tubenets) that connect bacteria and drastically increase their exchange surface with the host cytosol. *In situ* high spatial resolution chemical analysis indicated that tubenets are enriched in carbohydrates, which are the main substrate used by bacteria to generate nutrients for the host. Multiple membranous structures favoring nutrient absorption are described in multicellular organisms. This work demonstrates that bacteria have convergently evolved a similar “biostrategy” that enhances nutrient acquisition by increasing membrane interface.

## INTRODUCTION

Protists, bacteria, and viruses have evolved many strategies to hijack nutrients and thrive within host cells.<fnref n="1" />,<fnref n="2" /> While extensively studied in the context of parasitism, mechanisms of nutrient transfer remain poorly explored in intracellular mutualism, despite metabolic exchanges being central in these associations.<fnref n="3" /> Intracellular mutualistic bacteria (endosymbionts) are frequently associated with insects and contribute to their ability to colonize a wide diversity of ecosystems.<fnref n="4" /> By complementing nutritional needs, endosymbionts allow their hosts to thrive on restricted diets, including blood (e.g., tsetse flies and bed bugs), plant sap (e.g., aphids and mealybugs), or grains (e.g., cereal weevils).<fnref n="5" /> Endosymbionts are transmitted vertically over thousands

of host generations, preventing genetic recombination with free-living bacteria. This leads to host-endosymbiont coevolution<fnref n="6" /> and increases interactions and complementation between partners, resulting in metabolic interdependency.<fnref n="7" />,<fnref n="8" />⁻¹⁸ Endosymbionts are housed within specific host cells, the bacteriocytes, which in many species group into an organ, the bacterium. Insect bacteriocytes can be viewed as cross-kingdom “metabolic factories” that produce nutrients for the associated partners.<fnref n="3" />,<fnref n="5" /> This metabolic cooperation requires extensive metabolite exchanges between endosymbionts and host cells.¹⁸ So far, the mechanisms allowing these exchanges have been investigated by genomic and transcriptomic approaches, which provided evidence that transporter-encoding gene families are amplified in several host species.¹⁹ In pea aphids, transporters

<footnote n="1">¹INRAE, INSA Lyon, BF2I, UMR203, 69621 Villeurbanne, France</footnote>

<footnote n="2">²Synchrotron SOLEIL, 91192 Gif-sur-Yvette, France</footnote>

<footnote n="3">³TRANSFORM, INRAE, 44316 Nantes, France</footnote>

<footnote n="4">⁴Electron Microscopy Core Facility, European Molecular Biology Laboratory, 69117 Heidelberg, Germany</footnote>

<footnote n="5">⁵Evolutionary Ecology, Institute for Organismic and Molecular Evolution (iomE), Johannes Gutenberg University, Hanns-Dieter-Hüsch-Weg 15, 55128 Mainz, Germany</footnote>

<footnote n="6">⁶Max Planck Institute for Chemical Ecology, Department of Insect Symbiosis, Hans-Knoell-Str. 8, 07745 Jena, Germany</footnote>

<footnote n="7">⁷Centre Technologique des Microstructures, Université Claude Bernard Lyon 1, 69622 Villeurbanne, France</footnote>

<footnote n="8">⁸Microscopy Core Facility, Institute of Molecular Biology, 55128 Mainz, Germany</footnote>

<footnote n="9">⁹Université Lyon, Université Claude Bernard Lyon 1, CNRS, INSA Lyon, UMR5240 MAP, 69621 Villeurbanne, France</footnote>

<footnote n="10">¹⁰Institut Universitaire de France (IUF), 75005 Paris, France</footnote>

<footnote n="11">¹¹These authors contributed equally</footnote>

<footnote n="12">¹²Lead contact</footnote>

<footnote>\*Correspondence: abdelaziz.heddi@insa-lyon.fr (A.H.), anna.zaidman@insa-lyon.fr (A.Z.-R.)
https://doi.org/10.1016/j.cell.2025.10.001</footnote>
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(legend on next page)
may ensure active metabolite exchanges across bacteriocyte
membranes and the symbiosomal (M3) membrane that sur-
rounds the endosymbionts in this association.¹⁹⁻²³ In contrast
to their hosts, endosymbiont genomes often retain very few
transporter-encoding genes,²⁰ raising questions on how endo-
symbionts uptake nutrients from the host and whether and
how bacteria exchange metabolites with each other within bac-
teriocytes.²⁴ To tackle these questions, we used the association
between the rice weevil *Sitophilus oryzae* and the bacterial endo-
symbiont *Sodalis pierantonius* as a model system. Using biolog-
ical, genomic, and transcriptomic data, we previously high-
lighted that *S. pierantonius* supplies weevils with cofactors,
vitamins, and amino acids that are scarce in cereal grains.²⁵⁻²⁸
In particular, like in several other beetles,²⁹⁻³² endosymbionts
provide the host with the aromatic amino acids phenylalanine
and tyrosine that are required for cuticle completion.²⁷ This en-
hances the weevil's protection from desiccation and against bi-
otic antagonists.²⁹,³³ Although the insect is able to produce tyro-
sine from phenylalanine, it relies on endosymbionts to produce
phenylalanine, a scarce amino acid in cereal grains.²⁸ *S. pieran-
tonius* has retained a complete shikimate pathway and produces
phenylalanine from carbohydrate metabolism.²⁶ Remarkably,
symbiotic but not aposymbiotic weevils (artificially deprived
from endosymbionts) are able to develop when raised solely
on a starch carbohydrate-only diet.³⁴ This indicates that endo-
symbionts can proliferate and complement the host with phenyl-
alanine when provided with carbohydrates.³⁴ Previous transcrip-
tomics studies have shown that weevil bacteriocytes are
overloaded in carbohydrates, as, in addition to glycolysis, the
polyol pathway is highly activated within bacteriocytes.³⁵ This
raises the question of the mechanism by which endosymbionts
efficiently access these primary metabolic sources. Here, using
volume electron microscopy and *in situ* high-resolution chemical
analysis, we show that endosymbionts use complex membra-
nous structures, or “tubenets,” to access host nutrients inside
host cells.

RESULTS AND DISCUSSION

The host gut epithelium exhibits an extensive and
polarized vesicular network

In weevil larvae, bacteriocytes form a bacteriome organ located
at the fore-midgut junction, with no direct connection to the gut
lumen (Figure S1A), raising the question of how dietary nutrients
reach the bacteriome. We examined larval gut and bacteriome

with transmission electron microscopy (TEM) upon high-pressure freezing (HPF) to better preserve lipid membranes. We revealed numerous intracellular vesicles in the enterocytes forming the epithelium that separates the gut lumen from the bacteriome (Figures S1B–S1H). We hypothesized that this extensive vesicular network could be involved in transporting nutrients from the lumen to the bacteriome. To analyze the nature of the vesicles, we conducted immunostainings using antibodies (Table S1) against early (Rab5-positive) and late (Rab7-positive) endosomes.36 We observed a high prevalence of Rab-positive vesicles in larval enterocytes with epifluorescence microscopy (Figure 1). Rab5 and Rab7 staining were asymmetric within enterocytes, presenting a predominant apical (lumen side) and basal (bacteriome side) location, respectively (Figures 1A–1G). This polarized distribution could be evocative of active transcytosis, which could ensure a rapid and efficient transport of nutrients through enterocytes, from the gut lumen to the internal space where the bacteriome is located (Figure 1H). Intriguingly, Rab5 polarized location was less contrasted in aposymbiotic larvae, in which the bacteriome organ is absent³⁷: apical-basal differences were significantly larger in symbiotic than in aposymbiotic larvae (one-sided Wilcoxon rank-sum test Mann-Whitney U; U = 36; n₁ = n₂ = 6; *p* = 0.001; no statistical effect was found for Rab7). This may suggest a potential influence of the endosymbiont and/or bacteriome, either through direct bacterial activity—such as the modulation of host vesicular transport³⁸—or through indirect effects on host metabolism.

Endosymbionts produce numerous tubular
membranous extensions

Unexpectedly, membrane staining used on larval or adult bacteriomes also highlighted abundant membranous material within the bacteriocyte cytosol, in between endosymbionts (Video S1; Figures S2A and S2B). Importantly, in *Sitophilus* species, the endosymbiont *S. pierantonius* is directly located in the host cell cytosol³⁹ and is not surrounded by a host symbiosomal membrane, in contrast to many other endosymbiotic associations.²⁴ Ultrastructural analyses performed in this work confirmed the absence of a host symbiosomal membrane around endosymbionts (Figure 2). However, it showed that the space between endosymbionts inside the host cytosol is packed with tubular structures arising from endosymbionts (Figure 2). These structures are about 20 nm in diameter and can exceed 200 nm in length. They can be seen in between bacteria (e.g., in Figures 2A and 2C–2E) and in between bacteria and host vesicles (Figures 2B

**Figure 1. The host gut epithelium exhibits an extensive and polarized vesicular network**

(A–E) Immunostaining of the intestinal epithelium using antibodies against Rab5, an early endosome marker (A, C, and D), and Rab7, a late endosome marker (B). The apical side corresponds to the gut lumen; the bacteriome is located next to the basal side. Blue, DAPI (nuclei); green, Rab5/Rab7; red, autofluorescence. (C–E) present an example of the staining measurement on gut transversal sections, here for Rab5. In (D), the epithelium was delimited. In (E), the equidistant line between the basal and apical borders of the epithelium was used to delimit the basal (cyan) and apical (yellow) regions. Observations were made on 9 (for Rab5) and 10 (for Rab7) independent experiments. Scale bars, 20 µm (A and B) and 100 µm (C–E).

(F and G) Boxplots representing mean gray values for Rab5 (F) and Rab7 (G) staining in the apical and basal regions. Central lines indicate medians, box limits indicate upper and lower quartiles, and whiskers indicate the minimal and maximal values of the dataset; *n* = 6 biological replicates for each staining. \* *p* < 0.05 by one-sided Wilcoxon tests (p = 0.047 for Rab5, *p* = 0.016 for Rab7).

(H) Detailed drawing of a bacteriome (left) and localization of Rab5 (early) and Rab7 (late) endosome markers in a gut epithelial cell, based on the immunostaining data, showing the working hypothesis of vesicle transcytosis from the lumen to the bacteriome.

See also Figure S1.
<figure><img src="image_12.png" /><figcaption>**Figure 2.** Endosymbionts produce numerous tubular membranous extensions inside bacteriocytes</figcaption></figure>

(A–E) TEM observation of sections of bacteriomes fixed by HPF. Tubular structures (arrow: examples) are observed longitudinally or transversely sectioned, revealing their membranous nature. Tubules have a diameter of 20.9 nm (± 2.8 nm, *n* = 50). These structures, hereafter referred to as “tubenets,” are located between bacteria and vesicles (arrow in B) or between bacteria (arrows in A, C, D, and E). Note that *S. pierantonius* forms long bacteria,³⁹ which are here visualized on transversal sections.

(F) Tubenets are stained by antibodies directed against the bacterial protein Lpp after an immunogold protocol, indicating a bacterial origin of tubenets. Antibodies are localized thanks to gold particles (black dots). *, bacteria, v, vesicles.

(G) Tomogram slice with superimposed 3D segmentation of bacteria (bact) and tubenets. Bact 2 and 3 are represented as transparent layers to allow visualization of the lateral connections between bacteria and tubenets (black arrowheads).

(H and I) 3D rendering from the same tomogram as in (G). The segmentation of bact 3 is not shown for better visualization. (H) Connections are observed between bacteria and tubenets (black arrowheads). For clearer representation, not all tubenets are displayed in this panel. (I) Complex interconnections between the tubenets and between tubenets and bacteria are visualized along their long axes.

(J) 3D rendering from another tomogram, highlighting numerous connections between tubenets and a bacterium.

*(legend continued on next page)*
Cell
Short article

and 2C). S. oryzae present three main developmental stages: larval, pupal, and adult (Figure 3A). These structures were observed at the larval stage (Figures 2G–2M and 3B), but also during metamorphosis (Figures 3C and 3D) and at the adult stage (Figures 2A–2F, 3E, and 3F). Transversal sections (e.g., in Figures 2A, 3E, 3F, and S2C) highlighted the membranous nature of the tubules. Their membrane presents a similar aspect and width to the endosymbiotic outer membrane (approximately 10 nm; Figures S2C and S2D). We confirmed the bacterial origin of these tubules with immunogold staining using antibodies against the Braun lipoprotein (Lpp, a bacterial protein linking the peptidoglycan layer to the outer membrane in Gram-negative bacteria; Figures 2F and S3A–S3D), against the lipid A (lipopolysaccharide [LPS] outer layer; Figures S3E and S3F), and against the outer membrane porin OmpC (Figures S3G and S3H). The fact that these structures harbor three characteristic bacterial markers strongly suggests that they are formed from the endosymbiont's outer membrane. Electron tomography was used to understand their spatial organization and connections (Figures 2G–2M; Videos S2 and S3). The tomograms revealed that the tubules are positioned between bacteria and run longitudinally along the bacterial membrane. They connect repeatedly to endosymbionts along their length, forming tethers to the bacterial membrane (Figures 2G–2M). Similar connections were observed between tubules (Figures 2G–2J), hence generating complex tridimensional nets. The unprecedented scale of these membranous structures and their tridimensional organization along bacteria and multiple connections is fundamentally different from the isolated, linear connections typical of nanotubes, previously described as connecting bacteria.40–53 We below refer to the structures described here as tubenets to reflect their network-like architecture. Importantly, the tridimensional modeling indicated that tubenets connect bacteria to each other but also drastically increase the surface of interaction of endosymbionts with the host cytosol, suggesting a function in host-bacteria nutrient exchanges.

To investigate whether these structures are conserved among insect endosymbionts, we analyzed four additional coleopteran species (Figures 3G–3P). We did not observe any similar structures in the lesser grain borer *Rhyzopertha dominica* (Bostrichidae; Figures 3G and 3H) and the saw-toothed grain beetle *Oryzaephilus surinamensis* (Silvanidae; Figures 3L and 3M), two beetles that harbor anciently associated *Shikimatogenerans* endosymbionts.²⁹ These endosymbionts have highly reduced genomes: *Shikimatogenerans bostrichidophilus*, an endosymbiont of *R. dominica*, has a genome of 172,971 bp,³² and *S. silvanidophilus*, an endosymbiont of *O. surinamensis*, has a genome of 307,680 bp.³¹ By contrast, *S. pierantonius* has a genome of 4,513,140 bp,²⁶ similar in size to the genome of free-living bacteria, such as *Escherichia coli* (4,900,968 bp).⁵⁶ Due to the massive gene loss along evolution, *Shikimatogenerans* endosymbionts have lost the capacity to produce their own membranes and

strongly rely on their host for lipid input, making it unlikely that they could produce lipid-costly structures as the tubenets. Moreover, these endosymbionts are enclosed into a host symbiosomal membrane,⁵⁷ as many other endosymbionts,²⁴ and in contrast to S. pierantonius in *Sitophilus*'s bacteriocytes.³⁹ This suggests that nutrient transport could be instead mainly ensured and controlled by the host in these long-lasting symbioses, similarly to other endosymbioses such as the pea aphid association with *B. aphidicola*.⁵⁸ We then analyzed two other symbiotic *Sitophilus* species, S. zeamais (Figures 3I–3K) and S. granarius (Figures 3N–3P), that harbor sister-endosymbiotic bacteria but display distinct ecology and physiology. S. oryzae and S. zeamais have a thick cuticle and a cosmopolitan distribution, demonstrating an adaptation to warm and dry climates. By contrast, S. granarius does not face such environmental challenges, as it lives under more moderate climates and exclusively inside storage facilities. Strikingly, while we detected a high number of tubenets in S. zeamais (Figures 3I–3K), such structures were not seen in S. granarius (Figures 3N–3P). It is noteworthy that S. granarius has a significantly lower endosymbiotic load and a thinner cuticle when compared with S. zeamais and S. oryzae.²⁷ Hence, within the genus *Sitophilus*, the formation of tubenets by endosymbionts parallels the bacterial load and the intensity of bacterial biosynthetic activity. Therefore, we hypothesize that bacteria in S. oryzae and S. zeamais could use tubenets to acquire high amounts of nutrients required for their intense growth, which in turn impacts host development.

Endosymbiont tubenets and host vesicles are enriched
in carbohydrates

To address whether tubenets serve as nutritional host-endo-
symbiont interfaces, we aimed to characterize their metabolic
content. To do so, we used the young adult stage, when endo-
symbionts provide a key metabolic input for the insect by pro-
ducing critical amino acids for cuticle synthesis following
metamorphosis.²⁷,³⁷ We used a synchrotron scanning trans-
mission X-ray microscope (STXM), which offers a spatial reso-
lution of 30 nm, to identify *in situ* the nature of the carbon con-
tent inside bacterial tubenets and host vesicles. From the four
STXM stacks of images analyzed, we extracted the carbon
spectral signature in 85 selected regions of interest (ROIs),
defined by correlative TEM observations of the same fields
post-STXM experiment (Figures S4A–S4D). Spectra were back-
ground-corrected using a linear regression fit (Figure S4E). The
following analyses were focused on the more informative 284–
290 eV energy range (Figure S4F). We further applied a Z score
normalization process on the ROI spectra to highlight their po-
tential differences and subtract the signal due to the resin used
to embed samples (Figures S4G and S4H) before clustering the
spectra based on their correlation profiles (Figure 4A). Ward hi-
erarchical clustering analysis on the correlation matrix revealed
that bacterial tubenets and host vesicles presented high

(K–M) Still images from a tomogram showing continuity between tubenets and the bacterial outer membrane at different connection points (arrowheads). Scale bars, 100 nm (A and J–M), 500 nm (B–E), and 200 nm (F–I). TEM images are representative of 8 independent HPF experiments on a total of 51 individuals (imaging numerous sections of each). Volume microscopy acquisition was performed on seven different regions of the same sample, with reconstruction of two of them, here presented. Tubenets were observed at different stages: adult in (A–F); larval in (G–M).
See also Figures S2 and S3 and Videos S1, S2, and S3.
<figure><img src="image_13.png" /><figcaption>**Figure 3.** Prevalence of tubenets along *S. oryzae* life stages and in other coleopteran species</figcaption></figure>

(A–F) Representation of the *S. oryzae* life cycle and TEM observations of HPF-fixed bacteriome sections at larval (B), pupal (C and D), and adult (E and F) stages. Tubenets were observed with a similar ultrastructure at all stages analyzed. Endosymbionts are expected to have a high need for carbohydrates as they divide along bacterial stages and at the beginning of the adult stage when they exponentially grow (days 1 to 5).²⁷ On the host side, the need for the amino acids produced by the bacteria from carbohydrates is especially high at the young adult stage, when the cuticle is formed (days 1 to 7).²⁷
(G–P) Ultrastructure of endosymbionts inside bacteriocytes of host species *Rhyzopertha dominica* (G and H), *S. zeamais* (I–K), *Oryzaephilus surinamensis* (L and M), and *S. granarius* (N–P) revealed by TEM observation of sections of HPF-fixed bacteriomes. Apart from *S. oryzae* (B–F), tubenets were only detected in *S. zeamais* (I–K).*, examples of bacteria. Black arrows (H and M), host membrane surrounding *S. bostrichidophilus* and *S. silvanidophilus*, endosymbionts of *R. dominica* and *O. surinamensis*, respectively. White arrows, examples of rough endoplasmic reticulum (RER), visible in some samples. The endosymbionts *S. bostrichidophilus* (G and H) and *S. silvanidophilus* (L and M) are Bacteroidota; the endosymbionts of *Sitophilus* spp. (B–F, I–K, and N–P) are from the distant Pseudomonadota phylum. The insect species are Coleoptera from three distinct families: Bostrichidae (*R. dominica*; G and H), Silvanidae (*O. surinamensis*, L and M), and Curculionidae (*Sitophilus* spp., B–F, I–K, and N–P) that are estimated to have diverged more than 200 mya.⁵⁴ In the *Sitophilus* genus, *S. zeamais* (I–K) and *S. oryzae* (B–F) are estimated to be the closest (as compared with *S. granarius*, N–P) and to have split some 8.7 mya.⁵⁵ Images are representative of 2, 1, 5, 2, and 2 independent HPF experiments on a total of 3, 3, 10, 6, and 7 individuals for *S. oryzae* pupae, *R. dominica*, *S. zeamais*, *O. surinamensis*, and *S. granarius*, respectively. Scale bars, (B–F) 200 nm; (G and H) 1 µm; (I–K) 200 nm; (L) 5 µm; (M) 2 µm; and (N–P) 200 nm.

similarities with regard to their carbon content and marked dif-
ferences to mitochondria, endosymbiotic cytosol, and host
cytosol (Figure 4A). To address which carbon compounds drive
these contrasted profiles, we correlated the ROI spectra with
normalized spectra of carbohydrates, amino acids, proteins,
and lipids from reference datasets (see STAR Methods and
Figure S4I). Remarkably, tubenets and host vesicle spectra
correlated strongly with carbohydrate spectra, while the other
ROI spectra correlated strongly with protein and amino acid
spectra (Figure 4A). Hence, while all cell compartments contain
a cocktail of carbohydrates, lipids, and amino acids, bacterial

tubenets and host vesicles are enriched in carbohydrates rela-
tive to amino acids when compared with mitochondria and
bacteria. This distribution can be visualized on the STXM
stacks by mapping the correlation of each pixel's spectrum
with those of reference compounds (Figure 4B). Hence, the
STXM data revealed that tubenets and vesicles have a similar
content and are enriched in carbohydrates.

To strengthen these results, we additionally performed a
more classic approach of modeling the experimental ROI
spectra with reference spectra. To work with a reduced number
of reference spectra, we first clustered them based on their
<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /><figcaption>Figure 4. STXM analysis of the carbon composition of bacteriome sections</figcaption></figure>

Spectra corresponding to the region of interest (ROI) identified as tubenets, endosymbionts, mitochondria, and host cytosol or vesicles were identified through TEM observation post-STXM experiment and were normalized and treated to highlight differences.

(A) Ward hierarchical clustering analysis was performed on the correlation matrix to reveal higher similarities in the nature of carbon content between spectra. ROI spectra were correlated with normalized dataset spectra for carbohydrates, amino acids, proteins, and lipids.

(B) STXM image acquired on a bacteriome section at 287.7 eV (top left) and the corresponding same area identified with TEM (middle left). The red rectangles refer to the higher magnification TEM image (bottom left), where endosymbionts (') and tubenets (arrows) are visible. On the right panel: corresponding spatial correlations between the spectra of each pixel and the reference spectra for glucose (top), lipid (middle), and glutamine (as an example of an amino acid; bottom). The correlation is represented as a heatmap, with red representing high correlation and blue representing anti-correlation. It shows the enrichment in carbohydrate compounds in tubenet-rich areas. Black rectangles correspond to the higher magnification presented in the left bottom panel. Scale bars, 1 µm (top and middle) and 200 nm (bottom). The STXM experiment provided 4 stacks of images, from 2 independent grids and 2 independent samples. 85 ROI were statistically treated. See also Figures S4–S6.

similarity (Figure S4I) before using the most central spectra for each of these clusters of references to fit the experimental ROI spectra. Figures S5A and S5B provide examples of experimental, modeled spectra and their corresponding reference components for three endosymbiont ROIs (Figure S5A) and three tubenet ROIs (Figure S5B). These data show that while the models all involve the use of a variety of references, some of which are common to both tubenets and endosymbionts, the modeling of the tubenets' spectra relies more strongly on the use of the carbohydrate reference. Applying reconstruction models on all 85 ROI spectra enabled us to use a statistical approach and demonstrate that the coefficients that need to be applied to the carbohydrate reference spectrum to best model the tubenets' spectra are significantly higher than the coefficients required to model any other ROI's spectra, except the vesicles, with which no significant differences are found (Figure S5C). These results confirm the higher abundance of carbohydrates in tubenets and host vesicles as compared with the endosymbiotic cytosol and mitochondria compartments. While the chemical resolution in these STXM data was

not sufficient to determine precisely which type of carbohydrates are present, we analyzed the gut carbohydrate content of insects fed on wheat grains and found that the main simple carbohydrate present in the gut is glucose, followed by a smaller proportion of trehalose (Figure S6A). Hence, we suppose that at least a part of the carbohydrates detected in the vesicles and tubenets correspond to glucose.

The *in situ* global analysis of the tubenets' content suggests an essential function in nutrient acquisition, especially carbohydrates, and points toward endosymbionts retrieving nutrients from the host through these membranous extensions. Based on these data, we propose three non-exclusive possibilities on the tubenets' mechanism of action in the *Sitophilus/Sodalis* association. First, the content similarity and carbohydrate enrichment in both tubenets and host vesicles revealed by the STXM analysis indicate a path for carbohydrate transfer through cargo membranous structures, both on the host and bacterial side. This suggests a possible continuity between these membranous compartments, which would provide bacteria direct access to the host endosomal content. Second, the observation that tubenets
connect to multiple bacteria suggests that they could transfer nu-
trients from bacteria to bacteria in a nutritional inter-bacteria
cooperation. Last, the tubenets' complex three-dimensional or-
ganization procures a drastic increase of the bacterial exchange
interface with the host cytosol, likely facilitating carbohydrate
diffusion from the host cytosol to bacteria. Interestingly, when
we examined which transporter-encoding genes are present in
the genome of S. pierantonius (Figure S6B), we found that out
of three phosphotransferase system (PTS) sugar transporters
characterized in E. coli, two are conserved: (1) the PTS glucose
(Glc)-specific, which consists of two subunits, the II A component
(IIA<sup>Glc</sup>; encoded by the *crr* gene) and the II CB component (IICB<sup>Glc</sup>;
encoded by the *ptsG* gene); and (2) the PTS N-acetyl-
glucosamine (Nag)-specific II CBA component (IICBA<sup>Nag</sup>;
encoded by the *nagE* gene). These genes are highly expressed in
S. pierantonius, as well as the gene encoding the porin OmpC,
suggesting they contribute to sugar import through the bacterial
cell wall (Figure S6B). Based on what has been described in
E. coli, this indicates that OmpC, present not only on the cell
wall outer membrane but also on tubenets (Figure S3H), could
favor the passive translocation of sugars into these structures,
while the PTS transporters located at the endosymbiont inner
membrane would actively import glucose from the periplasm or
the tubenet internal space to the bacterial cytosol (Figure S6B).

In conclusion, this work reveals that endosymbionts inside host
cells use a dense and complex network of tubenets to acquire nu-
trients, in particular carbohydrates. While they appear structurally
fundamentally different from previously described nanotubes,
they are another demonstration of the long-unsuspected capacity
of bacteria to produce different types of membranous extensions
to feed. Most importantly, they represent a striking example of
adaptation supporting the important metabolic exchanges that
are known to occur between host and symbiont in intracellular
symbioses.¹⁸ In the context of mutualism, carbohydrate sourcing
by bacterial tubenets likely contributes to the important bacterial
growth in the young adult’s first days and therefore to the bacterial
production of amino acids required for the host’s cuticle comple-
tion, which in turn allows the insect to adapt to different ecological
niches. The selection of various complex membranous structures
that increase the surface exchange and favor nutrition exchanges
and absorption has been repetitively observed in animal and plant
multicellular organisms: e.g., small intestine microvilli⁵⁹ and
placenta in mammals, complex root ramification in plants, or ex-
change interface between extracellular fungi and plants in arbus-
cular mycorrhizal symbioses.⁶⁰ Here, we reveal that bacteria have
also evolved a similar “biostrategy” for nutrient uptake through the
production of complex tridimensional and interconnected tubular
networks. Nutritional intracellular symbioses are widespread, not
only in insects, where they are estimated to occur in 15% of spe-
cies, but also in other important symbioses, including in plants. As
they all rely on massive exchanges of metabolites between host
and symbiont, it will be of particular interest to address whether
convergent adaptations contribute to nutrient transfer in other
symbioses.

Limitations of the study

We show here that the tubenets harbor components of the bacte-
rial outer membrane, such as the LPS and the proteins Lpp and

OmpC, indicating that these structures are generated by endo-
symbionts. However, while *S. pierantonius* has the capacity to
produce its own membranes,²⁶ the production of such complex
lipid structures is likely very costly for bacteria. It will be pertinent
to evaluate in future studies a possible contribution of the host to
their formation, possibly through a fusion with other host membra-
nous compartments, such as host endocytic vesicles. This will
also contribute to deciphering whether enrichment in carbohy-
drates in tubenets is achieved by the fusion of tubenets to host
glucose-rich transport vesicles and/or by cytosolic glucose diffu-
sion through porins on the “extension” of the bacterial outer mem-
brane that tubenets constitute. Another point of interest will be to
identify the molecular mechanisms that are involved in the forma-
tion of such a complex membranous network and compare it to
the mechanisms involved in the formation of nanotubes⁴⁵,⁴⁶ or
outer membrane hypervesiculation (reviewed in ⁶¹). Last, this
study does not address the mechanisms of transport of the amino
acids synthesized by bacteria to the host, which remain to be iden-
tified in future work.

RESOURCE AVAILABILITY

Lead contact

Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Anna Zaidman-Rémy (anna.zaidman@insa-lyon.fr).

**Materials availability**

This study did not generate new unique reagents.

Data and code availability

* The tomograms are available at EMPIAR: https://doi.org/10.6019/EMPIAR-12198 and EMPIAR: https://doi.org/10.6019/EMPIAR-12602. STXM Synchrotron data have been deposited at figshare: https://doi.org/10.6084/m9 figshare.26271673. These data are publicly available as of the date of publication.

* This paper does not report original code.

* Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

ACKNOWLEDGMENTS

TEM was performed at the Centre Technologique des Microstructures (Université Lyon 1). Spinning disc confocal imaging was performed at the Microscopy Core Facility IMB, Mainz, supported by Deutsche Forschungsgemeinschaft with INST 247/912-1 FUGG. We acknowledge SOLEIL for provision of synchrotron radiation facilities (proposal no. 20181345) and HERMES beamline staff Belkhou Rachid, Besson Adrien, Swaraj Sufal, and Stanescu Stefan for assistance in using the beamline; Olga Roudenko (GRADES group) for help with XANES map data normalization; and Adam P. Hitchcock (McMaster University) for advice on the first treatment steps. We thank Paolo Ronchi from the EMBL Electron Microscopy lab for advice on volume-electron microscopy and Karel Mocaer from Heidelberg University, Centre for Organismal Studies, for help with Amira software. We thank Rita Rebollo and Peter Liehl for critical reading of the manuscript and discussions. Figures 1H, S3A, and S6 were created in BioRender.com: ZAIDMAN, A. (2025) (https://BioRender.com/vw74tt0, https://BioRender.com/9l2numi, and https://BioRender.com/lx0ybs8). The graphical abstract was created by the scientific illustrator Veronica La Pada (The Drawing Scientist).

Funding is as follows: Santé des Plantes et Environnement Department of Institut National de Recherche pour l'Agriculture, l'alimentation et l'environnement; Institut National des Sciences Appliquées Lyon; Federation of Research Biodiversité, Eau, Environnement, Ville et Santé BioEEnViS (grant
Short article

A.Z.-R.; grant S.B.); French ANR-17-CE20-0031-01 GREEN (A.H.); French ANR-19-CE20-0010 FOCuS (A.Z.-R.); French Ministry for Research PhD fellowship (J.M.); INSA Lyon doctoral scholarship, societal issues "Environ-ment: natural, industrial and urban environments" and "Global health and Bioengineering" (B.S.-S.); Synchrotron SOLEIL project proposal no. 20181345 (A.Z.-R.); Max Planck Society (T.E. and M.K.); German Research Foundation (DFG) GRK2526/1 "GenEvo" (M.K.); and European Research Council Consolidator Grant ERC CoG 819585 "SYMBeetle" (M.K.).

AUTHOR CONTRIBUTIONS

Conceptualization: S.B., A.H., and A.Z.-R.; data curation: S.B., C.R., S.P., and A.Z.-R.; formal analysis: C.R. and S.P.; funding acquisition: S.B., M.K., A.H., and A.Z.-R.; investigation: S.B., C.R., R.S.-M., M.G.-D., J.M., T.E., M.G.F., E.D., B.S.-S., C.D., V.L.P., P.T., I.R., A.V., C.V.-M., B.V., P.D.S., and A.Z.-R.; methodology: S.B., C.R., S.P., and R.S.-M.; project administration: S.B. and A.Z.-R.; resources: C.R., M.G.-D., J.M., T.E., B.S.-S., C.D., V.L.P., P.T., N. P., Y.S., X.J., and M.K.; software: S.P.; supervision: G.C., A.H., and A.Z.-R.; validation: S.B., C.R., P.D.S., A.H., and A.Z.-R.; visualization: S.B., C.R., S. P., R.S.-M., P.T., and A.Z.-R.; writing - original draft: S.B., C.R., S.P., A.H., C.V.-M., P.T., and A.Z.-R.; writing - review & editing: S.B., C.R., S.P., R. S.-M., J.M., T.E., M.G.F., E.D., P.T., C.V.-M., N.P., G.C., Y.S., M.K., A.H., and A.Z.-R.

DECLARATION OF INTERESTS

The authors declare no competing interests.

STAR★METHODS

Detailed methods are provided in the online version of this paper and include
the following:

● KEY RESOURCES TABLE

● EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

○ *Sitophilus* spp

*Oryzaephilus surinamensis*

*Rhyzopertha dominica*

● METHOD DETAILS

○ Ethics

○ Insect sampling

○ Simple carbohydrate dosage in insect gut

○ Western blot

○ Spinning disc confocal microscopy

○ Sample Preparation for immunofluorescence

○ Immunofluorescence

○ High-pressure Freezing (HPF)

○ Transmission electron microscopy

○ Electron tomography

○ Immunogold

○ C K-edge NEXAFS spectra collection on STXM

○ C K-edge NEXAFS spectra analyses

○ Genome and transcriptome data mining

● QUANTIFICATION AND STATISTICAL ANALYSIS

○ STXM spectra modeling coefficients

○ Rab5 and Rab7 polarity in gut epithelia

○ Membrane width of bacteria and tubenets

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.cell.
2025.10.001.

Received: August 28, 2024

Revised: July 21, 2025

Accepted: October 1, 2025

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## STAR★METHODS

### KEY RESOURCES TABLE

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3"><strong>Antibodies</strong></td></tr><tr><td>Anti-Rab5</td><td>Abcam Limited (Cambridge, UK)</td><td>Cat# ab31261, RRID: AB_882240</td></tr><tr><td>Anti-Rab7</td><td>Abcam Limited (Cambridge, UK)</td><td>Cat#ab50533, RRID: AB_882241</td></tr><tr><td>Anti-LipidA</td><td>LSBio (Newark, CA, USA)</td><td>Cat# LS- C682834-500</td></tr><tr><td>Anti-OmpC</td><td>AssayGenie (Dublin, Ireland)</td><td>Cat# PACO34698</td></tr><tr><td>Goat anti-Rabbit IgG (H+L) Cross-Adsorbed Secondary Antibody, Rhodamine Red™-X</td><td>Invitrogen Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>RRID: AB_2556551</td></tr><tr><td>Goat anti-Mouse IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor Plus™ 488</td><td>Invitrogen Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>RRID: AB_2633275</td></tr><tr><td>Goat Anti-Rat IgG (whole molecule)-Peroxidase antibody</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #A9037, RRID: AB_258429</td></tr><tr><td>Goat anti-Rat IgG (H+L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488</td><td>Invitrogen Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>RRID: AB_2534074</td></tr><tr><td>Goat-anti-Rat IgG (H&L) old conjugate 15 nm</td><td>Aurion (Wageningen, Netherlands)</td><td>SKU: 815.055</td></tr><tr><td>Donkey anti-Goat IgG (H+L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488</td><td>Invitrogen Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>RRID: AB_2534102</td></tr><tr><td>Donkey-anti-Goat IgG (H&L) Gold conjugate 15 nm</td><td>Aurion (Wageningen, Netherlands)</td><td>SKU: 815.333</td></tr><tr><td>Donkey anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488</td><td>Invitrogen Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>RRID: AB_2535792</td></tr><tr><td>Goat-anti-Rabbit IgG (H&L) Gold conjugate 15 nm</td><td>Aurion (Wageningen, Netherlands)</td><td>SKU: 815.011</td></tr><tr><td colspan="3"><strong>Chemicals, peptides, and recombinant proteins</strong></td></tr><tr><td>Acetone puriss. p.a., ACS reagent, reag. ISO, reag. Ph. Eur.</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #32201</td></tr><tr><td>Acetonitrile Gradient Grade for Liquid Chromatography LiChrosolv® Reag. Ph Eur</td><td>VWR international LLC (Fontenay-sous-Bois, France)</td><td>Cat # 1.00030.2500</td></tr><tr><td>Agar</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #A1296</td></tr><tr><td>Butanol-1</td><td>CARLO ERBA Reagents SAS (Val de Reuil, France)</td><td>Cat #308251</td></tr><tr><td>Blocking solution for donkey gold conjugates</td><td>Aurion (Wageningen, Netherlands)</td><td>SKU: 905.005</td></tr><tr><td>Albumin Bovine Protease Free</td><td>Euromedex (Souffelweyersheim, France)</td><td>Cat #04-100-812-C</td></tr><tr><td>CellMask™ Orange Plasma Membrane Stains</td><td>Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>Cat #C10045</td></tr><tr><td>Dako, Fluorescence Mounting Medium</td><td>Agilent Technologies (Santa Clara, CA, USA)</td><td>Cat # GM304</td></tr><tr><td>DAPI</td><td>Thermo Fisher Scientific Inc.</td><td>Cat #D1306</td></tr><tr><td>Amersham ECL substrate western blotting detection reagent</td><td>Cytiva (Wilmington DE, USA)</td><td>Cat #RPN2209</td></tr><tr><td>Epoxy Embedding Medium kit (EPON)</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #45359-1EA-F</td></tr><tr><td>Erythritol</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #PHR1479-1G</td></tr><tr><td>Ethanol Gradient Grade for Liquid Chromatography LiChrosolv®</td><td>Supelco Inc. (Bellefonte, PA, USA)</td><td>Cat #1.11727.1000</td></tr><tr><td>Ethanol absolute anhydrous for Analysis, ACS Reag. Ph Eur</td><td>CARLO ERBA Reagents SAS (Val de Reuil, France)</td><td>Cat #4146012</td></tr></tbody></table>

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<figure><img src="image_18.png" /></figure>

Continued

<table><thead><tr><td>REAGENT or RESOURCE</td><td>SOURCE</td><td>IDENTIFIER</td></tr></thead><tbody><tr><td>Fluoro Gel with DABCO™</td><td>Electron Microscopy Science (Hatfield, PA, USA)</td><td>Cat #17985</td></tr><tr><td>Fructose</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #31140</td></tr><tr><td>Glucose</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #7021</td></tr><tr><td>Aqueous Glutaraldehyde solution 50% EM-grade</td><td>Electron Microscopy Science (Hatfield, PA, USA)</td><td>Cat #13320</td></tr><tr><td>Glycine</td><td>Euromedex (Souffelweyersheim, France)</td><td>Cat #26-128-6405-C</td></tr><tr><td>Halt protease inhibitor cocktail</td><td>Thermo Fisher Scientific Inc. (Waltham, MA, USA).</td><td>Cat #87785</td></tr><tr><td>Hexadecen</td><td>Merck KGaA, (Darmstadt, Germany)</td><td>Cat #8220640100</td></tr><tr><td>Hoechst 33342</td><td>Thermo Fisher Scientific Inc. (Waltham, MA, USA)</td><td>Cat # R37165</td></tr><tr><td>Lead(II) nitrate for analysis EMSURE® ACS,Reag. Ph Eur</td><td>Merck KGaA, (Darmstadt, Germany)</td><td>Cat # 1.07398</td></tr><tr><td>Magnesium chloride</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #M8266</td></tr><tr><td>Maltose</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #47266</td></tr><tr><td>Mannitol</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #M9546</td></tr><tr><td>D-(+)-Melezitose monohydrate</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #07304</td></tr><tr><td>methylcyclohexan</td><td>CARLO ERBA Reagents SAS (Val de Reuil, France)</td><td>Cat #528264</td></tr><tr><td>Normal Goat Serum</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #G7402</td></tr><tr><td>Osmium Tetroxide, Crystalline</td><td>Electron Microscopy Science (Hatfield, PA, USA)</td><td>Cat #19134</td></tr><tr><td>Paraformaldehyde 16% aqueous solution, EM grade</td><td>Electron Microscopy Science (Hatfield, PA, USA)</td><td>Cat #15710</td></tr><tr><td>Potassium chloride</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #P9541</td></tr><tr><td>Potassium phosphate monobasic</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #1.04873</td></tr><tr><td>Raffinose</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #95068</td></tr><tr><td>Surgipath Paraplast Plus</td><td>Leica Microsystemes SA (Nanterre, France)</td><td>Cat # 39602004</td></tr><tr><td>SDS PAGE 4–20% Mini-PROTEAN® TGX Stain-Free™ Protein Gels</td><td>Bio Rad SAS (Nanterre, France)</td><td>Cat # 4568093</td></tr><tr><td>Silicon Rhodamine-DNA (SiR-DNA)</td><td>Spirochrome AG (Stein am Rhein - Switzerland)</td><td>Cat # SC007</td></tr><tr><td>Sorbitol</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #85529</td></tr><tr><td>Sodium chloride</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #S7683</td></tr><tr><td>Sodium Hydroxyde Solution 1.0N</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #S2770</td></tr><tr><td>Sodium Hydroxyde Solution 50% in H2O</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #415413</td></tr><tr><td>Sodium phosphate dibasic</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #S0876</td></tr><tr><td>Tri-Sodium citrate dihydrate</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat # 1064480500</td></tr></tbody></table>

(Continued on next page)
Continued

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td>Sucrose</td><td>Sigma-Aldrich LLC(St. Louis, MO, USA)</td><td>Cat #S7903</td></tr><tr><td>Trehalose dihydrate</td><td>Sigma-Aldrich LLC(St. Louis, MO, USA)</td><td>Cat #T0167</td></tr><tr><td>Tris-buffered saline 10X solution</td><td>Bio Rad SAS (Nanterre, France)</td><td>Cat #1706435</td></tr><tr><td>Tris HCl</td><td>Euromedex (Souffelweyersheim, France)</td><td>Cat #EU0011</td></tr><tr><td>triton X-100</td><td>Sigma-Aldrich LLC(St. Louis, MO, USA)</td><td>Cat #T8787</td></tr><tr><td>Tween-20</td><td>Sigma-Aldrich LLC(St. Louis, MO, USA)</td><td>Cat # P1379</td></tr><tr><td>uranyl acetate</td><td>Electron Microscopy Science (Hatfield, PA, USA)</td><td>Cat #22400</td></tr></tbody></table>

Critical commercial assays

<table><tr><td>Epoxy Embedding Medium kit (EPON)</td><td>Sigma-Aldrich LLC (St. Louis, MO, USA)</td><td>Cat #45359-1EA-F</td></tr><tr><td>MinuteTM Total Protein Extraction Kit for Animal Cultured Cells and Tissues</td><td>Invent Biotechnologies Inc. (Plymouth, MN, USA)</td><td>Cat # SD-001/SN-002</td></tr></table>

Deposited data

<table><tr><td>Tomogram</td><td>This manuscript. Deposited on EMPIAR.</td><td>EMPIAR: https://doi.org/10.6019/EMPIAR-12198</td></tr><tr><td>Tomogram</td><td>This manuscript. Deposited on EMPIAR.</td><td>EMPIAR: https://doi.org/10.6019/EMPIAR-12602</td></tr><tr><td>STXM raw data</td><td>This manuscript. Deposited on Figshare</td><td>Figshare: https://doi.org/10.6084/m9.f figshare.26271673</td></tr><tr><td>Raw sequencing data (transcriptomics) from Ferrarini et al.<sup>62</sup></td><td>Ferrarini et al.,<sup>62</sup> on NCBI-SRA</td><td>NCBI-SRA: PRJNA918957</td></tr><tr><td>Reference spectra are from aXis2000 database</td><td>Hitchcock<sup>63</sup></td><td>(http://unicorn.mcmaster.ca/aXis2000.html)</td></tr></table>

Experimental models: Organisms/strains

<table><tr><td>Sitophilus oryzae: Bouriz strain</td><td>Our laboratory (BF2i; France)</td><td>N/A</td></tr><tr><td>Sitophilus oryzae: Bouriz strain, aposymbiotic strain</td><td>Our laboratory (BF2i; France)</td><td>N/A</td></tr><tr><td>Sitophilus zeamais: Lagoa strain</td><td>Our laboratory (BF2i; France)</td><td>N/A</td></tr><tr><td>Sitophilus granarius: Brayard strain</td><td>Our laboratory (BF2i; France)</td><td>N/A</td></tr><tr><td>Oryzaephilus surinamensis</td><td>Julius Kühn Institute / Federal Research Center for Cultivated Plants (Berlin, Germany)</td><td>N/A</td></tr><tr><td>Rhyzopertha dominica</td><td>Julius Kühn Institute / Federal Research Center for Cultivated Plants (Berlin, Germany)</td><td>N/A</td></tr></table>

Software and algorithms

<table><tr><td>Fiji version of ImageJ (v1.53t)</td><td>Schindelin et al.<sup>64</sup></td><td>https://imagej.nih.gov/ij/</td></tr><tr><td>KEGG Pathway</td><td>N/A</td><td>https://www.genome.jp/kegg/pathway.html</td></tr><tr><td>Olympus Microscope Cell Sens dimension software</td><td>Olympus</td><td>N/A</td></tr><tr><td>Philips CM120 software Gatan DigitalMicrograph</td><td>Philips</td><td>N/A</td></tr><tr><td>SerialEM software</td><td>Mastronarde<sup>65</sup></td><td>https://bio3d.colorado.edu/SerialEM/</td></tr><tr><td>Leica Application Suite X 3.7.6.25997</td><td>Leica Microsystems CMS GmbH</td><td>https://www.leica-microsystems.com/products/microscope-software/p/leica-application-suite/</td></tr><tr><td>Pixelator STXM Control Software</td><td>Paul Scherrer Institute, the Max-Planck-Institut für Intelligente Systeme and Semafor Informatik & Energie AG</td><td>N/A</td></tr></table>

(Continued on next page)
**Continued**

<table><thead><tr><td>REAGENT or RESOURCE</td><td>SOURCE</td><td>IDENTIFIER</td></tr></thead><tbody><tr><td>Amira 3D software</td><td>Thermo Fisher Scientific</td><td>https://www.thermofisher.com/fr/fr/home/electron-microscopy/products/software-em-3d-vis/amira-software.html</td></tr><tr><td>Huygens Essential software</td><td>Scientific Volume Imaging, the Netherlands</td><td>https://svi.nl/Huygens-Essential</td></tr><tr><td>Imaris software</td><td>Oxford Instruments</td><td>https://imaris.oxinst.com/</td></tr><tr><td>aXis2000 software</td><td>Hitchcock<sup>63</sup></td><td>http://unicorn.mcmaster.ca/aXis2000.html</td></tr><tr><td>Athena package in Demeter 0.9.26</td><td>Newville<sup>66</sup>; Ravel and Newville<sup>67</sup></td><td>https://bruceravel.github.io/demeter/</td></tr><tr><td>hierarchical clustering algorithm in Python 3.7 packages Pandas and Seaborn</td><td>McKinney<sup>58</sup></td><td>https://www.python.org</td></tr><tr><td>hierarchical clustering algorithm in Python 3.7 packages Pandas and Seaborn</td><td>Waskom<sup>69</sup></td><td>N/A</td></tr><tr><td>K-medoids Partition Around Medoids clustering algorithm implemented in the scikit-learn Python 3.7 library</td><td>Friedman<sup>70</sup></td><td>https://www.python.org</td></tr><tr><td>Elastic-Net algorithm implemented in the scikit-learn Python 3.7 library</td><td>Pedregosa<sup>71</sup></td><td>https://www.python.org</td></tr><tr><td>R Studio</td><td>N/A</td><td>https://github.com/rstudio/rstudio</td></tr></tbody></table>

**EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS**

**Sitophilus spp**

**Sitophilus oryzae**

The S. oryzae strain used in the study is the Bouriz strain, maintained in the BF2i laboratory since 1984 from S. oryzae found on rice in the Valey of Azergues (France).

The S. oryzae aposymbiotic strain was obtained by heat treatment in 2010, following a protocol described previously.⁷² Briefly, Sitophilus oryzae adults of about one-week-old were maintained for 28 days at 35°C and between 80 and 90% relative humidity. Following this treatment, females were sexed, isolated individually, and let to lay eggs on grains. Among each female's offsprings, fourth-instar larvae were extracted from grains to check for absence of S. pierantonius, by FISH and PCR.⁷² Larvae with no S. pierantonius FISH signal and no endosymbiont gene PCR amplification were deemed aposymbiotic. One such lineage was maintained, separately, under the same conditions as symbiotic individuals (see below). The absence of endosymbionts in the aposymbiotic strain is checked by end-point PCR twice a year.

**Sitophilus zeamais**

The S. zeamais strain used in the study is the Lagoa strain, maintained in the BF2i laboratory since 1990 from S. zeamais found in a miller's attic in Lagoa (Portugal).

**Sitophilus granarius**

The S. granarius strain used in the study is the Brayard strain, maintained in the BF2i laboratory since 1982 from S. granarius found in a miller's attic in the Jura area (France).

The three Sitophilus strains used in this study are free of any facultative symbionts, including Wolbachia, and harbors only S. pierantonius.⁷³ This endosymbiotic bacterium is not culturable and is solely analyzed in this work inside the host tissue.

All three cereal weevil Sitophilus strains were reared in a climate chamber at 27.5°C, 70% relative humidity, with no light source on wheat grains (sterilized at -80°C) as a food source and substrate. The strains were maintained in boxes of wheat grains (sterilized at -80°C) as a food source and substrate.⁷³ The adults were changed of substrate every three days, generating synchronized rearing. The insect presents four larval stages, a pupal stage during which full metamorphosis is performed, and an adult stage. Different stages were used in this study and are indicated in the corresponding figure legends. In large majority of the cases, fourth instar larvae and adults were used. The individual insects for each experimental treatments were randomly picked from the rearing boxes and randomly assigned to the experiments. The sex was not established for the insect used because it is not decipherable at larval stage and is only determined upon ovaries dissection in the adult. Nevertheless, for the main structures described i.e. bacterial structures (tubenets), sex-based analysis is not expected to be relevant.

**Oryzaephilus surinamensis**

Oryzaephilus surinamensis were obtained from the Julius Kühn Institute / Federal Research Center for Cultivated Plants (Berlin, Germany) and maintained on rolled oats as substrate at 27-28°C and 60% relative humidity with a 16/8 h light/dark cycle. Adults
randomly picked from the rearing population were used in this study. The sex was not established for the insect used because it is not decipherable at larval stage and is only determined upon ovaries dissection in the adult.

## Rhyzopertha dominica

Rhyzopertha dominica were obtained from the Julius Kühn Institute / Federal Research Center for Cultivated Plants (Berlin, Germany) and maintained on intact wheat grains at 27-28°C and 60% relative humidity with a 16/8 h light/dark cycle. Adults randomly picked from the rearing population were used in this study. The sex was not established for the insect used because it is not decipherable at larval stage and is only determined upon ovaries dissection in the adult.

## METHOD DETAILS

### Ethics

No ethical approval is required for work on insects in France.

### Insect sampling

For sampling, insects were immersed in buffer A solution (25mM KCl, 10mM MgCl2, 250mM Sucrose, 35mM Tris-HCl pH 7.5) and dissected under a stereomicroscope. In *Sitophilus* strains, a unique larval bacteriome located at the foregut-midgut junction dissociates at the onset of metamorphosis and generates multiple bacteriomes at the apex of mesenteric caeca of young adults.²⁷,³⁷
Whole individuals or dissected organs were prepared as described below.

### Simple carbohydrate dosage in insect gut

For each sample, 20 guts from D5 adults were dissected and placed in a solution containing 2 µL of erythritol internal standard (25 mM erythritol in a mixture of 22 µL water and 96 µL absolute ethanol) Erythritol was obtained from Sigma-Aldrich LLC (St. Louis, MO, USA), and ethanol from Supelco Inc. (Bellefonte, PA, USA). To facilitate alcoholic extraction, five metal beads were added to each tube and samples were grinded using a Precellys®Evolution homogenizer (Bertin Technologies SAS, Montigny le Bretonneux, France) at 6800 rpm for 3 times 30 seconds. The samples were incubated at 80°C for 10 min, followed by centrifugation at 10,000 g for 10 min.

The sugars were analyzed by HPLC using an Agilent 1260 system (Agilent Technologies France SAS, Les Ulis, France) equipped with a Phenomenex-Luna® Omega column (3 µm particule size, 100 Å pore size, 150 mm x 4.6 mm; Phenomenex SAS, Sartrouville, France). Separation was achieved using an 80:20 acetonitrile/water mixture (v/v) with acetonitrile source from VWR international LLC (Fontenay-sous-Bois, France). The mobile phase was delivered at a flow rate of 0.8 ml/min and a temperature of 25°C. Detection was performed using a Sedex® LT-ELSD-100 evaporative light scattering detector (SEDERE SAS, Olivet, France). Quantification was based on the internal standard erythritol, and the response factors for each sugar were determined using a standard carbohydrate mix containing sorbitol, mannitol, trehalose, glucose, fructose, sucrose, melecitose, raffinose and maltose (all from Sigma-Aldrich LLC, St Louis, MO USA). The experiment was repeated on three samples of 20 guts.

### Western blot

20 midguts of three-day-old symbiotic and aposymbiotic adults were dissected in diethylpyrocarbonate-treated buffer A (25 mM KCl, 10 mM MgCl2, 250 mM sucrose, 35 mM Tris/HCl, pH = 7.5) and stored at -80 °C.

The protein sample was prepared from these pools of 20 midguts mixed with the sample buffer from MinuteTM Total Protein Extraction Kit for Animal Cultured Cells and Tissues (Invent Biotechnologies Inc.), supplemented with Halt protease inhibitor cocktail (Thermo Scientific), and loaded for 4-20% stain-free SDS PAGE (Bio Rad Inc.). Following electrophoresis, total protein was activated using UV exposure according to the manufacturer's instructions and imaged prior to transfer for normalization purposes. Proteins were blotted to nitrocellulose membrane using a semi-dry transfer system and blocked with 3% bovine serum albumin (BSA) in TBS-T (Tris-buffered saline, 0.1% Tween-20) for 1 hour at room temperature (RT).

Membranes were incubated 2 hours at room temperature with Rabbit polyclonal anti-serum directed against Lpp (anti-Lpp antibody, Proteogenix), used as the primary antibody diluted in TBS-T buffer (1 :500 v/v), followed by incubation with 1 :5000 (v/v) diluted anti-rabbit IgG -peroxydase antibody (Sigma) 1 :5000 (v/v) during 2 hours at room temperature.

Bands were detected using enhanced chemiluminescence (ECL) substrate (AmershamTM), and images were captured using the ChemiDoc MP Imaging System (Bio-Rad).

### Spinning disc confocal microscopy

For spinning disc confocal microscopy, the whole gut samples were dissected in phosphate buffered saline (PBS 137 mM NaCl, 2.7 mM KCl, 12.5 mM Na2HPO4, 2 mM KH2PO4, pH 7.4) fixed overnight in freshly prepared 4% paraformaldehyde in PBS, rinsed thoroughly with PBS and cleared by incubating 60 min in 10% saccharose in PBS and 60 min in 30% saccharose in PBS. Fixed samples were mounted on a microscope slide, followed by staining. DNA was stained with either 10 µg/mL Hoechst 33342 (Thermofisher) or 1 µM Silicon Rhodamine-DNA (SiR-DNA, Spirochrome) and 5 µg/mL Cell Mask Orange Plasma Membrane Marker (Thermofisher) was used as a membrane marker. Staining solution (200 µL) was added and after 45 min the samples were washed 2 times with PBS. After
**Cell**
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washing, a drop of mounting medium (Dako, Agilent Technologies) was added, and coverslip (thickness #1.5) was placed on top. Samples were stored at 4°C overnight.

Images were acquired using an inverted spinning disc confocal microscope system (Visiscope 5 Elements, Visitron Systems GmbH, Puchheim, Germany), built on a Nikon Ti2 stand equipped with a confocal spinning disc (CSU-W1; Yokogawa, Tokyo, Japan) with 50 µm pinhole diameter disc and Prime BSI sCMOS camera (2048 x 2048 pixels, 6.5 µm pixel size, Photometrics). Images of z-stacks (frame averaging between 4-8 frames) were acquired using either 60x 1.2 NA water immersion (CFI Plan Apo VC 60xWI, Nikon) or 100x 1.49 NA oil immersion (CF1 Apo SR TIRF 100x) objectives with z-step sizes of 0.5 µm and 0.1 µm. Laser lines of 405 nm, 561 nm and 640 nm were used for the fluorescence excitation and the emission was acquired using quad band dichroic mirror (D101-T405/488/568/647, Semrock) and the emission filters 460/50 band pass (ET460/50m, Chroma), 692/40 band pass (FF01-692/40, Semrock) and 633 long pass (BLP01-633R, Semrock) for Hoechst, CellMask Orange and SiR-DNA, respectively. Image deconvolution was successfully applied to increase signal-to-noise ratio (SNR) and improve the resolution of the images. Briefly, the images were deconvolved using Huygens Essential (Scientific Volume Imaging, the Netherlands) software in wizard mode (CMLE algorithm, max. iterations 40, quality criteria 0.05, SNR 12 unless stated otherwise). The line profile generation and image preparation were performed using the Fiji version of ImageJ (v1.53t).⁶⁴ Video S1 was generated using Imaris software (Oxford Instruments).

**Sample Preparation for immunofluorescence**

Bacteriome (for larvae) or midgut with bacteriomes (for pupae and adults) were dissected in buffer A solution (25mM KCl, 10mM MgCl2, 250mM Sucrose, 1% DEPC, 35mM Tris-HCl pH 7.5) and fixed in paraformaldehyde 4%, supplemented with triton X-100 0,1% for larger pieces. Afterward, fixative was replaced by several baths of PBS before embedding in agar 1.3%, and dehydration through a graded ethanol series. Samples were then moved in butanol-1 at 4°C until paraffin impregnation with Paraplast. Wax blocks were kept in a cold and dust free place until sectioning. 3 µm thick tissue sections were done using a rotary microtome (HM340E, ThermoScientific) placed on poly-lysine coated slides, dried overnight in a 37°C oven and kept at 4°C until processing.

**Pre-adsorption of antibodies (OmpC, lipid A)**

Prior to immunofluorescence and immunogold labeling, commercial primary antibodies targeting OmpC and Lipid A were pre-ad-sorbed on aposymbiotic S. oryzae tissues to minimize non-specific binding. To prepare the adsorbing material, guts from 30 aposym-biotic adults were dissected in buffer A (25 mM KCl, 10 mM MgCl2, 250 mM sucrose, 35 mM Tris-HCl, pH 7.5). The dissected tissues were transferred with 3 additional aposymbiotic larvae into a tube containing approximately 30 µL of distilled water and stored at –80 °C for several hours. Samples were then lyophilized during 16h using the freeze-dryer ALPHA 1-2 LDplus (Christ, Osterode am Harz, Germany), ground into a fine powder using a Precellys homogenizer (Bertin Technologies SAS, Montigny-le-Bretonneux, France) at 8500 rpm, 2 times 45 sec. including a 30 sec. break, and stored at –20 °C until use. One day before the immunolabeling experiments, 500 µL of PBS was added to the powdered tissue along with bovine serum albumin (BSA) to reach a final concentration of 0.1%, and the appropriate volume of antibody was added to reach the desired final concentration. The mixture was incubated overnight at 4 °C. Before use, the solution was centrifuged for 5 minutes at 10,000 × g, the supernatant was collected and centrifuged again for 3 minutes at 10,000 × g. The final supernatant was used directly as the antibody solution without further dilution.

**Immunofluorescence**

Paraffin sections were dewaxed in two baths of methylcyclohexan for 10 min, rinsed in ethanol 100°, and rehydrated through an ethanol gradient to PBS. All slides were incubated with 1% BSA in PBS during 30 min prior primary antibody incubation (see Table S1 for references and dilutions, incubation time and temperature). Primary antibodies were diluted in PBS containing 0.1% BSA. PBS with BSA 0,1% without antibody was used as negative control. Afterward, sections were washed with PBS containing Tween 0,2%. Then samples were incubated with secondary antibodies, diluted in 0,1% BSA (Table S1), for 1 h at room temperature. Sections were then washed with PBS-Tween, rinsed with PBS and with several baths of water. Then sections were left to dry on the bench and mounted using Fluoro Gel with DABCO™ mounting medium in addition with DAPI for nuclear staining (3 µg per ml of medium). Images were taken with an epifluorescence microscope (Olympus IX81 with a XM10 monochrome camera or LEICA DMI8 equipped with Thunder Image 3D Assay, and with a K3M monochrome camera), using appropriate filters for antibody staining, DAPI, and unspecific autofluorescence from tissues. Images were processed with ImageJ (Fiji).⁶⁴ For clarity of presentation, some images were adjusted for brightness and contrast (corrections applied uniformly to the entire images). In addition, some images were cropped in a manner that preserved the overall representation of the results.

**High-pressure Freezing (HPF)**

For TEM, electron tomography, Immunogold and STXM, samples were first fixed using the High-pressure Freezing (HPF) technique: tissues were freshly dissected in buffer A solution (25mM KCl, 10mM MgCl2, 250mM Sucrose, 1% DEPC, 35mM Tris-HCl pH 7.5), transferred to gold-plated copper specimen carriers (Cylinder shaped indentation on both sides, diam. 2 x 0.2 mm; Leica), and coated with 1-hexadecene. HPF was performed using the Leica HPM100.

Frozen samples were subsequently freeze-substituted in a substitution solution whose preparation differed according to the final purpose: for ultrastructural observations in TEM, the FS solution was composed of acetone with OsO4 1%, uranyl acetate 0.25%, glutaraldehyde 0,5% and water 1,5%. For the immunogold protocols, the FS solution was the same but without OsO4. For the STXM experiment, the FS solution was only water 1.5% in acetone. In the AFS2 FS apparatus (Leica), the samples in the carriers
were left in the FS solution for about 30 h at -90°C, then the temperature was slowly increased to -30°C at a rate of 5°C/h. They were left for another 24 h at -30°C until the temperature was again increased at room temperature at a rate of 10°C/h. During this temperature rise, the FS solution was replaced by several acetone baths to rinse the samples which were also removed from their carrier. At room temperature the acetone was gradually replaced by Epon (Epoxy Embedding Medium kit), until the final embedding in Epon for 72 h at 60°C.

## Transmission electron microscopy

Sections 70-nm-thick were cut from the Epon block with a Leica UC7 ultramicrotome and deposited on copper/formvar grids. Once sections were dried, they were contrasted with lead citrate according to Reynolds et al.⁷⁴ before observation under a Philips CM120 transmission electron microscope at 80 keV. For TEM observation after the STXM experiment, the grids were carefully detached from their holder, contrasted and observed using the same conditions as for TEM alone. Regions corresponding to the STXM acquisitions were detected through whiter areas caused by damage from previous irradiation.

## Electron tomography

Sections of 250 nm thickness were made on a UC7 ultramicrotome (Leica Microsystems, Wetzlar, Germany) and placed on Formvar-coated slot grids. Gold fiducials (10 nm protein A gold) were added to the grids to help later with alignment and reconstruction of the tomograms. Grids were post-stained with 2% uranyl acetate in methanol and lead citrate and imaged on a Tecnai F30 (Thermo Fisher Scientific, Waltham, MA, USA) transmission electron microscope equipped with a Gatan OneView camera (Gatan, Inc., Pleasanton, USA). Precise target positions were manually selected using the SerialEM software and acquired by dual-axis tomography (–60° to +60° per axis; increment of 1°) at 12,000x magnification (2.05 nm/px). Image analysis and segmentation was preformed using the Amira 3D software (Thermo Fisher Scientific, Waltham, MA, USA).

## Immunogold

Sections 70-nm-thick were cut from the Epon block with a Leica UC7 ultramicrotome and deposited on nickel/formvar grids. Nickel grids supporting sections in Epon were first incubated for 20 s in filtered 3% NaOH solution, to unmask the resin prior antibody incubation and then rinsed with ethanol solutions of decreasing concentrations, from absolute ethanol to 30°, and washed in PBS. Subsequently, to block nonspecific staining, the sections were incubated at room temperature in 0.05 M Glycine-PBS for 15 min, followed by either Normal Goat Serum 5% + BSA 5% in PBS (for Lpp and OmpC experiment) or Aurion Blocking solution for donkey gold conjugates (for LipidA experiment) for 30 minutes and 0,1% BSA for 5 minutes. After these pretreatment steps, primary antibodies diluted in PBS (see Table S1 for references, dilutions, incubation time and temperature) were applied, and after washings, the sections were incubated with a diluted gold conjugated secondary antibody for 2 hours (Table S1). In all experiments, anti-GroEL antibody was used as a positive control and no primary antibody as a negative control. After immunostaining, sections were contrasted with 4% uranyl acetate solution for 20 min, and lead citrate for 7 min. Final washes were performed and sections left to dry before observation under a transmission electron microscope. For OmpC and LipidA experiment, as the contrast was weak, grids were subsequently exposed to osmium tetroxide vapors during 2 hours before observation. Sections were imaged on a Philips CM120 at an acceleration voltage of 80 kV equipped with a Gatan Orius 200 camera (Lpp) or a JEOL 1400 at 120 kV with a Gatan Rio 16 camera (OmpC and LipidA). For clarity of presentation, some images were adjusted for brightness and contrast. These adjustments were applied uniformly to the entire image. In addition, some images were cropped in a manner that preserved the overall representation of the results.

## C K-edge NEXAFS spectra collection on STXM

Sections 70-nm-thick were cut from the Epon block with a Leica UC7 ultramicrotome and deposited on copper/formvar grids. The grids supporting the ultrathin sections of the samples, prepared as mentioned before, were mounted on the sample holder of the STXM and pre-screened using an optical microscope to select the areas of interest. The sample holder was then placed in the experimental STXM chamber, pumped down to 10⁻² mbar.

The micro-spectroscopic data were collected on the STXM end-station of the HERMES beamline (SOLEIL synchrotron), a particularly well-adapted beamline for carbon K-edge investigations.⁶⁵,⁷⁵,⁷⁶ The X-ray beam was focused to 43 nm using a 35D Fresnel zone plate and the transmission signal was collected using a photomultiplier tube. The energy of the STXM was calibrated using the well-resolved 3p Rydberg peaks of gaseous CO₂ for the C K-edge⁷⁷ at 290.46, 292.46 and 294.70 eV. The stacks of images were collected on fields of view of 4.85 x 4.85 to 7.85 x 7.85 µm², scanning the sample with 50 nm steps in both horizontal and vertical directions at each energy increment over the energy range of C K-edge. Each stack was composed of 103 images, covering the energy range between 280 and 320 eV, with a sampling step set of 0.8 eV from 280 to 284 eV, 0.36 eV from 284 to 286 eV, 0.08 eV from 286 to 290 eV (the edge region), 0.4 eV from 290 to 296 eV and 1 eV from 296 to 320 eV with a dwell time of 5 ms per pixel at each energy step.

## C K-edge NEXAFS spectra analyses

### Spectra extraction and correction

The four stacks of images were analyzed using aXis2000 (http://unicorn.mcmaster.ca/aXis2000.html) software.⁶³ The images were aligned using the alignment routine of the Stack Analyze program (Jacobsen/Stony Brook). The transmission images were then
converted into optical density (OD) scales according to the following equation: OD = -ln(I/I₀), where I₀ represents the incident X-ray flux measured on a free area of the sample holder (a hole in the thin section) and I represents the measured transmitted intensity at the pixel of interest.

C K-edge spectra were extracted from the stacks of images in regions of interest (ROI) manually selected using the Zimba tool in aXis2000 and based on the morphologic information obtained from correlative TEM observation of the same field, post STXM experiment (Figure S5). Extracted spectra were reduced using the standard normalization procedure of the Athena package in Demeter 0.9.26.⁶⁶,⁶⁷ E₀ edge energy was chosen as the maximum of the spectra first derivative. Spectra were background corrected using a linear regression fit through the pre-edge region [E₀−7.0 eV; E₀−4.5 eV] and a polynomial regression fit through the post-edge region [E₀+4.4 eV; E₀+33.0 eV] (Figure S4E). Further data processing was conducted on the 284-290 eV energy range (Figure S4F), corresponding to the more informative range of the spectra, corresponding to the pre-edge, the edge and the white line.

Reference spectra are from aXis2000 database⁶³ (http://unicorn.mcmaster.ca/aXis2000.html): poly-ala, poly-arg, poly-asn, poly-asp, poly-cys, poly-gln, poly- glu, poly-gly, poly- his, poly-ile, poly-leu, poly-lys, poly-met, poly-phe, poly-pro, poly-ser, poly-thr, poly-trp, poly-tyr, poly-val, Fructose, Glucose, protein: Albumin) and from Rivard et al.⁷⁸: lipid and starch.

### Normalization and hierarchical clustering

To compare experimental ROI spectra together and with reference spectra, a z-score normalization process was applied to adjust the values in the spectra dataset so that they have the same scale. This process enforces each spectrum to have a zero mean and a unitary standard deviation. In brief, the mean value from each spectrum was subtracted so that the average value for each spectrum equal to zero. Each spectrum was then divided by its standard deviation, to ensure that each spectrum has a unitary standard deviation, i.e. ensure that the spread of the data in each spectrum is the same (Figure S4G). Second, in order to highlight the difference between the signals, the average profile of all the ROI spectra was calculated and subtracted from each of the spectra (Figure S4H). The Pearson correlation between the ROI spectra and the reference spectra was computed. The hierarchical clustering algorithm⁷⁹ was applied, with a complete method, in order to cluster simultaneously ROI and references based on their correlation profiles, forming a correlation matrix represented in Figure 4A. These steps were achieved using the Python 3.7 packages Pandas⁸⁸ and Sea-born.⁶⁹ This approach was also applied in each pixel of the stacks to produce correlation maps between the spectra in each pixel of the stack and the reference spectra (Figure 4B).

### Modeling of experimental spectra

In order to conduct ROI spectra linear regression from a restrained number of references, while limiting the effect of multicollinearity of references, as several references exhibited highly correlated spectra, the K-medoids Partition Around Medoids (PAM) clustering algorithm was applied to the references' dataset. To determine the most suitable number of clusters K to be considered, the K-medoids algorithm was run for all possible numbers of clusters. For each K value the average inertia of the clusters was calculated, i.e. the average distance between the references of each cluster and its medoid (MSE). With 10 clusters the MSE curve indicates rather homogeneous clusters. The clusters of reference spectra obtained are presented in Figure S4I. The central reference (medoid) of each cluster, corresponding to the most representative reference of the cluster, was retained as reference for the regression analysis.

The ROI spectra were modeled as a positive linear combination of reference spectra using the Elastic-Net regression algorithm.⁷⁰ The Elastic-Net algorithm performs a regression applying simultaneously $\ell_1$ and $\ell_2$ regularizations. This algorithm is a compromise between Ridge regression (pure $\ell_2$ regularization) and Lasso regression (pure $\ell_1$ regularization) and tends to select only few non-zero coefficients as Lasso, but avoiding possibly degenerated behavior, thanks to the $\ell_2$ that stabilizes the algorithm. More formally, given a matrix X representing the reference spectra column-wise (here K references) described along N wave-lenshs, and for each each ROI spectrum vector y, the algorithm aims at finding a coefficient vector $C^*$ that minimizes the objective function stated hereafter (in this work, all coefficients were enforced to be positive).

$$C^* = \operatorname*{argmin}_C 1/(2N) \times \| y - X \cdot C \|_2^2 + \alpha \times \rho \times \| C \|_1 + \alpha \times (1 - \rho) / 2 \times \| C \|_2^2 \quad (\text{Equation 1})$$

The trade-off between $\ell_1$ and $\ell_2$ regularizations is controlled by the mixing parameter $\rho \in [0,1]$. For $\rho = 0$ only the $\ell_2$ regularization is used (equivalent to Ridge regression) and for $\rho = 1$ only the $\ell_1$ regularization is performed (equivalent to Lasso regression). Since in this work we search rather sparse coefficient vectors (few non-zero coefficients), we set $\rho = 0.9$. The overall regularization strength is determined by parameter $\alpha \ge 0$. The task is simply an ordinary least squares regression for $\alpha = 0$, while higher values increase both regularization penalties simultaneously. This parameter was set using the inner 10-fold cross-validation technique exploring a logarithmic scale grid of 100 values between $\alpha_{max} = \max_{i \ne j} (|X_i^T \cdot X_j|) / (N \times \rho)$ and $\alpha_{min} = \alpha_{max} \times 10^{-3}$. The ElasticNetCV model implemented in the scikit-learn Python 3.7 library was used.⁷¹ Examples are provided in Figures S5A and S5B.

### Genome and transcriptome data mining

The genes encoding porins and simple carbohydrate transporters present in S. oryzae's genome²⁶ were identified using the KEGG pathway database (https://www.genome.jp/kegg/pathway.html).

The expression of the corresponding genes was then retrieved from Ferrarini et al. dataset.⁶² Levels of expression at these genes at different stages were represented as Log10 normalized counts as a heat map, allowing comparison with the maximum and median level of expression of all S. pierantonius genes in the whole dual RNASeq dataset.
# QUANTIFICATION AND STATISTICAL ANALYSIS

## STXM spectra modeling coefficients

The coefficients applied on the various clusters of reference to model each experimental spectrum were statistically compared two by two using non-parametric two-sided Mann-Whitney. The Benjamini-Hochberg procedure for multiple test correction was applied to control the false discovery rate by adjusting the p-values of the individual tests.

The results are represented as boxplots in Figure S5C, where the central line indicates the median, the box limits indicate the upper and lower quartiles. Each point represents the coefficient used on a given reference spectra for the modeling of a ROI spectrum. 85 ROI were modelized, issued from 4 stacks. Significant differences are indicated as follow: *: 1.00e-02 < p ≤ 5.00e-02; **: 1.00e-03 < p ≤ 1.00e-02; ***: 1.00e-04 < p ≤ 1.00e-03; ****: p ≤ 1.00e-04 where p is the corrected p-value.

## Rab5 and Rab7 polarity in gut epithelia

To determine whether the localization of Rab5 and Rab7 is polarized, we compared the mean gray values of the basal and apical half of the epithelium stained with either Rab5 or Rab7 antibodies.

Briefly, after immunofluorescence experiment targeting Rab5 and Rab7, observations were performed with a LEICA DMi8 epifluorescence microscope equipped with Thunder Image 3D Assay, under specific emission filters: 630/75 for the red signal (Rab5 or autofluorescence), 527/30 for the green signal (Rab7 or autofluorescence), and 470/40 for the blue signal (DAPI). Images were captured using a Leica K3M camera. For each antibody tested, six images corresponding to six independent biological replicates were analyzed. To separate the two regions of interest (apical and basal), a binary mask of the gut was first generated by merging the three image channels (red, green, and blue) using Fiji. A midline equidistant from the apical and basal edges of the gut was then extracted using the Skeletonize 2D/3D plugin (Figure 1D). This skeleton was manually pruned by removing the shortest branches to retain only the main structure. The resulting line was used as a reference to define two separate masks, corresponding to the apical (API) and basal (BAS) regions (Figure 1E). These masks were converted into Regions of Interest (ROI). Raw images were split into individual channels, and only the channel corresponding to the specific signal of interest was considered for quantification. Mean gray values were measured in Fiji within each ROI.

This approach generated six paired measurements of basal and apical mean gray values, for each antibody. We did not assume normality because of the small sample size, and hence performed Wilcoxon signed-rank tests using R Studio.

For Rab5, we performed a one-sided Wilcoxon test with the a priori that the apical staining would be more intense than the basal staining and obtained a p-value of 0.047, indicating that Rab5 mean gray values were significantly higher in the apical half than in the basal half of the epithelia.

For Rab7, we performed a one-sided Wilcoxon test with the a priori that the basal staining would be more intense than the apical staining and obtained a p-value of 0.016, indicating that Rab7 mean gray values were significantly higher in the basal half than in the basal half of the epithelia.

The measurements are represented as boxplots in Figures 1F and 1G, where the central line indicates the median, and the box limits indicate the upper and lower quartiles. The asterisk indicates the significance (p ≤ 5.00e-02). The statistical details can be found here and in the figure legend.

To test whether the differences observed in the marker intensity in our images (epithelia of symbiotic larvae appearing with a more contrasted polarity than epithelia of aposymbiotic larvae) were quantitatively significant, we used the same type of measurements on aposymbiotic (n = 6 paired measurements) and compared them with symbiotic data (n = 6 paired measurements). We used a one-sided Wilcoxon rank-sum test (Mann-Whitney U) that confirmed that the apical–basal differences were significantly larger in symbiotic than in aposymbiotic larvae for the Rab5 signal (U = 36; n₁ = n₂ = 6; p = 0.001). The test was non-significant for the Rab7 signal performed on similar data (n₁ = n₂=6).

## Membrane width of bacteria and tubenets

Width of the bacterial outer membrane and of the tubenet membrane was measured in FiJi using the segment tool to define segment of interest and applying the measurement tool on them. 21 measurements were obtained for each category (bacterial outer membrane or tubenet membrane). These measurements were then compared by using a Wilcoxon test (p-value = 0.416) and a Welch Two Sample t-test (p-value = 0.545) (R Studio). Both tests were non-significant.

The measurements are represented as boxplots in Figure S2D, where the central line indicates the median, the box limits indicate the upper and lower quartiles, and the points indicate an outlier. The statistical details can be found here and in the figure legend.
**Supplemental figures**

<figure><img src="image_19.png" /><figcaption>**Figure S1. Ultrastructure of the larval gut epithelium in the bacteriome vicinity, related to Figure 1**</figcaption></figure>

(A) Drawing (left) and photo (right) of S. oryzae larva. The bacteriome is in purple. The frame indicates the area corresponding to the TEM image in (B). Anterior is left.

(B) TEM imaging of the gut epithelial cells and of bacteriocytes in the nearby bacteriome. Frames correspond to the regions observed with higher magnification in (C–F).

(C) Apical side of a gut epithelial cell with endocytic vesicles.

(D–H) Basal side of gut epithelial cells. In (E), the nearby bacteriome is visible, with complex membranous structures at the gut-bacteriome interface. Red arrowheads, endocytosis; Blue arrowheads, exocytosis; Arrows, intracellular vesicles; lu, gut lumen; MVB, multivesicular body; Mi, mitochondria; M, microvileness; gBM, gut basal membrane; bBM, bacteriome basal membrane; *, endosymbionts; Nu, nucleus; Bact, bacteriome; Gut epith, gut epithelium.

Scale bars, 2 µm (B) and 500 nm (C–H).
<figure><img src="image_20.png" /><figcaption>**Figure S2.** Membranous material present in between bacteria in the bacteriocyte, related to Figure 2</figcaption></figure>

(A) Single confocal section of a z stack (0.1 µm z step) of the adult bacteriome stained with silicon-rhodamine (SiR)-DNA and imaged using a spinning disc confocal microscope with 100× magnification. Middle and right panels: higher magnification of the region framed in (A) with SiR-DNA and membrane staining, respectively. Similar staining was observed on three independent adults and three independent larvae.

(B) Normalized Line profile of SiR-DNA and membrane staining showing an alternation between the bacterial DNA and membranous structures. Intensity values were normalized to the average value of the corresponding channel to allow for better visual comparison between different channels.

(C) Ultrastructure of endosymbionts and tubenets imaged by TEM observation of HPF-fixed bacteriome sections in an *S. oryzae* young adult. Examples of measurement of the bacterial outer membrane (cyan) and tubenet membrane (red) width are represented. The bacterial outer membrane is an asymmetric lipid bilayer formed of LPS on the outer leaflet and phospholipids on the inner leaflet.⁸⁰ Due to the LPS membrane outer face reacting more strongly with heavy metal stains, the outer membrane appears as a combination of a darker outer face and lighter inner face, itself delimited on the inner side by the peptidoglycan present in the periplasm.⁸⁰ The tubenet membrane presents a similar appearance. Scale bar, 50 nm. *, endosymbiotic bacteria.

(D) Boxplots representing the width of the outer membrane of endosymbionts and the membrane of tubenets. The central line indicates the median, the box limits indicate the upper and lower quartiles, the whiskers indicate the minimal and maximal values of the dataset, with the exception of an outlier indicated as a point. *n* = 21 measurements. No significant differences were detected using a Wilcoxon test (*p* value = 0.416) and a Welch two-sample t test (*p* value = 0.545).
<figure><img src="image_21.png" /><figcaption>**Figure S3.** The tubenets contain LPS and two outer membrane proteins, Lpp and OmpC, related to Figure 2</figcaption></figure>

Immunogold staining was performed with antibodies raised against *S. pierantonius* Lpp outer membrane protein and with commercial antibodies raised against *E. coli* outer membrane protein OmpC and *E. coli* lipid A (LPS).

(A) Schematic representation of the Gram-negative bacterial cell wall and antibodies used. OmpC is a porin located inside the outer membrane. Lpp is a protein linked to the inner side of the outer membrane. Lipid A is the membrane-anchoring lipid domain of the LPS, which forms the outer leaflet of the outer membrane.

(B) Western blot confirming the specificity of the Lpp antibody. On the left: total protein on electrophoresis gel (load control). On the right: a band corresponding to the estimated molecular weight of Lpp is detected in the protein extract from symbiotic gut and bacteriomes, while the band is not detected in a symbiotic extract (lacking endosymbionts).

(C) Immunostaining using antibodies against Lpp on symbiotic and aposymbiotic adult tissues. The bacteriome (dotted line) containing the endosymbionts in the symbiotic insect is positively stained.

(D) Immunogold with the Lpp antibodies. Small black dots correspond to 15 nm-diameter gold particles conjugated to the antibodies. They indicate the location of antibodies recognizing the bacterial Lpp in the tissue section. Both the bacterial cell wall and tubenets are marked. The antibodies used were obtained from two distinct rats injected with Lpp and tested independently to confirm the specificity of the staining. Upper panel: Lpp antibodies used at dilutions of 1/200, 1/100, and 1/50. Lower panel: antibodies obtained from another rat immunized with Lpp, at dilution 1/50; Positive control: antibodies raised against bacterial chaperonin GroEL, known to be localized inside the bacterial cytosol³⁸; negative control: experiment performed without any primary antibody—only secondary antibody was used.

(E) Immunostaining using antibodies against the lipid A on symbiotic and aposymbiotic adult tissues. The bacteriome (dotted line) containing the endosymbionts in the symbiotic insect is positively stained.

(F) Two examples of immunogold staining using antibodies against the lipid A indicate that lipid A is recognized on both the endosymbiotic cell wall and tubenets.

(G) Immunostaining using antibodies against OmpC on symbiotic and aposymbiotic adult tissues. The bacteriome (dotted line) containing the endosymbionts in the symbiotic insect is positively stained. Some light aspecific staining is observed in the aposymbiotic samples (mainly in smooth muscle cells along the midgut).

(H) Two examples of immunogold staining using antibodies against OmpC show recognition of both the endosymbiotic cell wall and tubenets. \*, examples of endosymbiotic bacteria. Sym, symbiotic samples; Apo, aposymbiotic samples; Lpp immunogold observation was repeated with two independent antibodies (from two different rats), and the experiment was repeated 2 times. Lipid A and OmpC immunogold experiments were repeated two and three times, respectively. Scale bars, (C, E, and G) 50 µm; (D) 200 nm, except for controls: 500 nm; and (F and H) 200 nm.
<figure><img src="image_22.png" /><figcaption>Figure S4. STXM analysis pipeline, related to Figure 4 and STAR Methods</figcaption></figure>

(A–D) Examples of the correlation between STXM data and TEM images for the selection of regions of interest (ROIs). TEM (left panels) performed after the STXM experiment allowed visualizing the ultrastructural context in the zones of the STXM stack and identifying the corresponding area (red rectangle) on the STXM images (right panels). The STXM images presented here were acquired on a bacteriome section at 287.7 eV, the energy at which the contrast is maximum and allows deciphering bacteria. Examples of ROI (in green) selected for tubenets (A), mitochondria (B), bacteria (C), and cytosol (D) in the STXM stack for spectra extraction of the corresponding pixels. Note that some artefactual holes are present in the tissue section, which appear in black on STXM images, while they appear in white on TEM images. Scale bars, 200 nm (TEM) and 2 µm (STXM). Mi, mitochondria; *, endosymbiotic bacteria; arrowheads, tubenets.

(E–H) Spectra analysis. (E) Normalized spectra corresponding to 85 ROI identified in the four STXM stack data as tubenets, endosymbiont, host cytosol, host vesicles, and mitochondria, thanks to the correlation with TEM post-STXM imaging. (F) Enlargement of the spectra in the 284–290 eV energy range corresponding to the rectangle in (E). (G) To better compare the spectra, a Z score normalization process was applied to force each spectrum to have a zero mean and a unitary standard deviation. (H) To highlight the differences between the spectra, the average spectrum of all the ROIs spectra was subtracted from each spectrum,

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emphasizing a clear difference between endosymbionts on one side and tubenets and vesicles on the other side between 287 and 288 eV. Intensity, normalized intensity (a.u.). Avg, average.

(l) Reference spectra associated with their corresponding clusters used for reconstruction. Description of the 10 references or cluster of references used (see Method details for the mode of cluster definition). Medoid spectra for each cluster (i.e., the spectra that best represent each cluster) are represented on the right of the references integrated in the corresponding cluster. These medoid spectra are the spectra further used to enter the modeling of the experimental spectra.
<figure><img src="image_23.png" /><figcaption>Figure S5. Modeling of the ROI spectra with the reference spectra, related to Figures 4 and S4 and STAR Methods</figcaption></figure>

(A and B) Examples of modeling of the experimental spectra with reference spectra for endosymbionts ROI (A) and tubenets ROI (B). Reconstruction: model. Real: experimental spectra. The resin component has been subtracted from these spectra for the graphic presentation but was considered for the fitting process. The coefficient of determination R² indicated corresponds to the modeling with the resin included.

(C) Boxplots representing the coefficients used to fit the experimental results obtained for all the ROI. The coefficients applied to the spectra of carbohydrate, lipid, amino acid glutamine, and embedding resin are presented here, among up to 10 reference spectra that were allowed in the modeling of the experimental spectra. The central line indicates the median, and the box limits indicate the upper and lower quartiles. Whiskers represent the 1.5 interquartile range (IQR). Each point represents the coefficient used on a given reference spectrum for the modeling of an ROI spectrum (85 ROI were modeled from 4 stacks). Non-parametric two-sided Mann-Whitney tests were performed to compare all distributions two by two, with a Benjamini-Hochberg multiple test correction. Significant differences are indicated as follows: *: 1.00e-02 < *p* ≤ 5.00e-02; **: 1.00e-03 < *p* ≤ 1.00e-02; ***: 1.00e-04 < *p* ≤ 1.00e-03; and ****: *p* ≤ 1.00e-04, where *p* is the corrected *p* value.
<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /><figcaption>**Figure S6.** Major simple carbohydrates present in the insect gut and glucose transporters present in the endosymbiont's membrane, related to Figure 4</figcaption></figure>

(A) HPLC (high-performance liquid chromatography) analysis of simple carbohydrates in the insect guts (adults). The analysis of three independent samples corresponding to 20 insect guts each is represented. Glucose was the most abundant simple carbohydrate in percentage. Trehalose was also detected. Sorbitol, mannitol, maltose, fructose, sucrose, melezitose, and raffinose were not detected.

(B) The genome of the endosymbiont *S. pierantonius* encodes the proteins required to import glucose through the cell wall. The representative scheme is based on the mechanisms described in *E. coli*.⁸¹ The porin OmpC, which allows passive, nonselective entry of glucose from the outside of the bacteria through its outer membrane, is conserved. Two PTS transporters reported to transport glucose through the inner membrane in *E. coli* are also conserved: the glucose-specific PTS, which consists of two subunits, the IIA<sup>Glc</sup> (encoded by the *crr* gene) and the IICB<sup>Glc</sup> (encoded by the *ptsG* gene), and the N-acetyl-glucosamine-specific PTS IICBA<sup>Nag</sup> (encoded by the *nagE* gene).⁸¹ *ompC* and the three genes encoding the PTS transporters are strongly expressed in *S. pierantonius* at all *S. oryzae*'s stages analyzed: larval (L), pupal (P), and adult (A). The small boxes next to the genes represent their level of expression at these different stages, represented as log10 normalized counts, allowing comparison with the maximum and median level of expression of all *S. pierantonius* genes. Genomic data were mined from the genome of *S. pierantonius*.²⁶ Expression data were mined from a dual RNA sequencing (RNA-seq) analysis published in Ferrarini et al.⁶²