# ArtSymbioCyc, a metabolic network database collection dedicated to arthropod symbioses: a case study, the tripartite cooperation in Sipha maydis

Patrice Baa-Puyoulet, Léo Gerlin, Nicolas Parisot, Sergio Peignier, François Renoz, Federica Calevro, Hubert Charles

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## To cite this version:

Patrice Baa-Puyoulet, Léo Gerlin, Nicolas Parisot, Sergio Peignier, François Renoz, et al.. ArtSymbioCyc, a metabolic network database collection dedicated to arthropod symbioses: a case study, the tripartite cooperation in Sipha maydis. mSystems, 2025, 10 (4), 10.1128/msystems.00140-25. hal-04987746

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# ArtSymbioCyc, a metabolic network database collection dedicated to arthropod symbioses: a case study, the tripartite cooperation in *Sipha maydis*

Patrice Baa-Puyoulet,¹ Léo Gerlin,¹ Nicolas Parisot,¹ Sergio Peignier,¹ François Renoz,² Federica Calevro,¹ Hubert Charles¹

**AUTHOR AFFILIATIONS** See affiliation list on p. 13.

**ABSTRACT** Most arthropods live in close association with bacteria. The genomes of associated partners have co-evolved, creating situations of interdependence that are complex to decipher despite the availability of their complete sequences. We developed ArtSymbioCyc, a metabolism-oriented database collection gathering genomic resources for arthropods and their associated bacteria. ArtSymbioCyc uses the powerful tools of the BioCyc community to produce high-quality annotations and to analyze and compare metabolic networks on a genome-wide scale. We used ArtSymbioCyc to study the case of the tripartite symbiosis of the cereal aphid *Sipha maydis* focusing on amino acid and vitamin metabolisms, as these compounds are known to be important in this strictly phloemophagous insect. We showed that the metabolic pathways of the insect host and its two obligate bacterial associates are interdependent and specialized in the exploitation of Poaceae phloem, particularly for the biosynthesis of sulfur-containing amino acids and most vitamins. This demonstrates that ArtSymbioCyc does not only reveal the individual metabolic capacities of each partner and their respective contributions to the holobiont they constitute but also allows to predict the essential inputs that must come from host nutrition.

**IMPORTANCE** The evolution has driven the emergence of complex arthropod-microbe symbiotic systems, whose metabolic integration is difficult to unravel. With its user-friendly interface, ArtSymbioCyc (https://artsymbiocyc.cycadsys.org) eases and speeds up the analysis of metabolic networks by enabling precise inference of compound exchanges between associated partners and helps unveil the adaptive potential of arthropods in contexts such as conservation or agricultural control.

**KEYWORDS** symbiosis, metabolism, metabolic network, insects, database, Aphididae, *Buchnera aphidicola*, *Serratia symbiotica*, amino acids, vitamins

The holobiont and hologenome concepts offer a broader vision of the individual by including the microbial organisms associated with the host—whether external, internal, or even intracellular—into a single system (1–3). The pervasiveness, as well as the functional and evolutionary importance, of symbiotic relationships is now widely established and questions the very notions of individuals and species (4, 5). Indeed, we can no longer consider individuals as entities but must see the network of complex interactions that make up the fabric of life. Since individuals can be considered as interacting agents in a network of interactions, it seems just as important to understand the holobiont's overall as the intrinsic capacities of each partner (6).

This is particularly true for insects, which constitute the most diverse phylum of animals (7). They make an essential contribution to ecosystem services worldwide, including soil formation and pollination (8). They are vectors of numerous human,

Editor Jonathan L. Klassen, University of Connecticut, Storrs, Connecticut, USA

Peer Reviewer Rosario Gil, Paterna, Valencia, Spain

Address correspondence to Patrice Baa-Puyoulet, patrice.baa-puyoulet@inrae.fr, or Hubert Charles, hubert.charles@insa-lyon.fr.

The authors declare no conflict of interest.

See the funding table on p. 13.

Received 29 January 2025

Accepted 20 February 2025

Published 21 March 2025

Copyright © 2025 Baa-Puyoulet et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.
animal, and plant diseases, as well as pests of all major crops worldwide (9). In this
sense, understanding their adaptation mechanisms, notably through the symbiotic
relationships they maintain with microorganisms, is essential to decipher how insects
can cope with environmental changes and improve control strategies against certain
pests (10, 11). The ever-increasing number of sequencing projects allows for carrying
out global genomic analyses for a very wide range of insect species. To date, NCBI's
genomics section references thousands of insects and around two million bacteria,
of which 516 genomes are associated with the keyword "endosymbionts," making it
possible to reconstruct, at least in part, certain hologenomes consisting of the host and
its associated endosymbiotic or gut bacteria.

Automated reconstruction of metabolic networks from the genomic information of
holobiont partners remains a challenge, particularly with regard to the consistency of
functional annotations on a genome scale. For that purpose, we previously built the
CycADS information system (12), which aggregates genome-scale functional annotations
from different methods with identical pipelines and parameter settings for all interact-
ing organisms to ensure a consistent description of enzymes, reactions, and pathways
and hence to guarantee the comparability of their respective networks. In the present
work, we used CycADS in conjunction with the Pathway Tools software (13) to build
the BioCyc-like (14) ArtSymbioCyc collection of databases (https://artsymbiocyc.cycad-
sys.org/). During the automated and expert analysis process, we also exploited the
Pathway Tools embedded MetaCyc database (15), a curated database of experimentally
elucidated metabolic pathways from all domains of life, which facilitates researchers,
in particular, to identify gaps in pathways and potential metabolic complementations
between associated partners. Finally, the ArtSymbioCyc interface enables users to
determine the precursors, intermediates, and final compounds that must necessarily be
imported from food, transformed, and transferred between associated organisms.

ArtSymbioCyc contains the metabolic networks, based on the available genomic
information, of 10 holobionts corresponding to six crop pest host-insects (Acyrthosiphon
pisum, Cinara cedri, Sipha maydis, Bemisia tabaci strains MEAM1 and MED, and Sitophilus
oryzae), three blood-eaters host-insects (Pediculus humanus corporis, Cimex lectularius,
and Glossina morsitans), and the model insect Drosophila melanogaster. These hosts are
accompanied by 1 to 4 of the 21 intracellular endosymbionts or commensal-associated
bacteria listed in the collection (Table S1).

To illustrate the main feature usage of ArtSymbioCyc, we have decrypted the
metabolic network of the *S. maydis* holobiont, composed here by the aphid host, that
was recently sequenced (16), and its co-obligate symbionts, *Buchnera aphidicola* and
*Serratia symbiotica* (17). The cereal aphid *S. maydis* (Chaitophorinae) feeds on many
grass species (Poaceae) and is distributed worldwide in most temperate climates where
it often damages cereal crops (18). Like all strict phloem-feeding insects, *S. maydis* is
dependent on obligate symbionts, which supply it with compounds that are too rare or
absent from its diet. Although housed in different bacteriocytes within the aphid body
cavity, the two nutritional endosymbionts are spatially close. *S. symbiotica* is confined
to large syncytial secondary bacteriocytes embedded between uninucleate primary
bacteriocytes containing *B. aphidicola* (16, 17). This topology facilitates metabolic
exchanges, and the two symbiotic bacteria carry out or participate in reactions allowing
the synthesis of essential amino acids and vitamins (17).

ArtSymbioCyc has enabled us to depict the intertwined metabolisms of these three
associated species and to finely track the origin and the fate of each metabolite to
identify the main compounds that must feed the system. We propose the ArtSymbioCyc
collection as a relevant and user-friendly resource to decipher the intimate and complex
co-dependencies on which arthropod holobionts are based.
RESULTS AND DISCUSSION

ArtSymbioCyc, a collection of metabolic networks of arthropod symbioses

ArtSymbioCyc is a Pathway Genome DataBase (BioCyc PGDB) collection containing the metabolic networks inferred from the reference genomes of 10 insects accompanied by their respective intracellular symbionts or commensal bacteria: three aphid species *A. pisum*, *C. cedri*, and *S. maydis*; two strains of the sweet potato whitefly *B. tabaci*; the bed bug *C. lectularius*; the fruit fly *D. melanogaster*; the tsetse fly *G. morsitans*; the body louse *P. humanus corporis*; the rice weevil *S. oryzae*. The list of all the databases currently contained in ArtSymbioCyc as well as the description of the main features of the corresponding metabolic network are reported in Table 1 and Table S1.

The ArtSymbioCyc metabolic networks were reconstructed using CycADS (12), an annotation management system originally developed for the reconstruction of pea aphid metabolism (46, 47). CycADS facilitates the collection and management of information from genomic data and various protein annotation methods in an SQL database. The annotation methods aggregated by CycADS are the ones coming from Blast2GO (48, 49), InterProScan (50), KAAS-KEGG (51), and PRIAM (52) pipelines. A quality score (number of evidence) is generated for each annotation, and the predictions of all methods are displayed on the genes and proteins pages of the Cyc database, allowing users to assess the quality of the annotation of enzymes in the network. The data

<table><caption>TABLE 1 Organisms contained in the ArtSymbioCyc collectionª</caption><thead><tr><th>Organisms (hosts and associated bacteria)</th><th>Reference(s)</th></tr></thead><tbody><tr><td>Acyrthosiphon pisum AL4f</td><td>(19)</td></tr><tr><td>Buchnera aphidicola APS</td><td>(20)</td></tr><tr><td>Candidatus Hamiltonella defensa T5A</td><td>(21)</td></tr><tr><td>Sipha maydis Midelt</td><td>(16)</td></tr><tr><td>Buchnera aphidicola Sm Midelt</td><td>(17)</td></tr><tr><td>Serratia symbiotica Sm Midelt</td><td>(17)</td></tr><tr><td>Cinara cedri</td><td>(22)</td></tr><tr><td>Buchnera aphidicola BCc</td><td>(23, 24)</td></tr><tr><td>Serratia symbiotica Cc</td><td>(25)</td></tr><tr><td>Cimex lectularius Harlan</td><td>(26)</td></tr><tr><td>Wolbachia sp.</td><td>(27)</td></tr><tr><td>Drosophila melanogaster</td><td>(28)</td></tr><tr><td>Lactiplantibacillus plantarum plantarum NC8</td><td>(29)</td></tr><tr><td>Acetobacter pomorum WJL DM001</td><td>(30)</td></tr><tr><td>Wolbachia sp.</td><td>(31)</td></tr><tr><td>Glossina morsitans Yale</td><td>(32)</td></tr><tr><td>Sodalis glossinidius morsitan</td><td>(33)</td></tr><tr><td>Wigglesworthia glossinidia (Yale colony)</td><td>(34)</td></tr><tr><td>Bemisia tabaci MEAM1</td><td>(35)</td></tr><tr><td>Candidatus Portiera aleyrodidarum MEAM</td><td>(35)</td></tr><tr><td>Hamiltonella defensa MEAM1</td><td>(36)</td></tr><tr><td>Rickettsia sp. MEAM1</td><td>(37)</td></tr><tr><td>Bemisia tabaci MED</td><td>(38)</td></tr><tr><td>Candidatus Portiera aleyrodidarum BT-QVLC</td><td>(39)</td></tr><tr><td>Hamiltonella defensa MED</td><td>(40)</td></tr><tr><td>Candidatus Cardinium hertigii</td><td>(41)</td></tr><tr><td>Wolbachia sp.</td><td>(42)</td></tr><tr><td>Pediculus humanus corporis USDA</td><td>(43)</td></tr><tr><td>Candidatus Riesia pediculicola USDA</td><td>(43)</td></tr><tr><td>Sitophilus oryzae Bouriz</td><td>(44)</td></tr><tr><td>Candidatus Sodalis pierantonius SOE</td><td>(45)</td></tr></tbody></table>

<footnote>ªSee Table S1 for more information about the different databases, genome accession numbers, and specific features of the corresponding metabolic networks.</footnote>
collected in CycADS are then formatted to generate *ad hoc* files ("Path-o-logic files") used by the Pathway Tools software (13) to produce a BioCyc-type-enriched metabolic database (12). Figure 1 schematically represents the complete process of annotating, storing, and organizing information, including the various CycADS processes that enable the production of BioCyc databases (PGDB) at the organism level or in a holobiont annotation process so-called "multi-organisms" in the Pathway Tools process. ArtSymbioCyc can be used to carry out broad comparative analyses between associated or non-associated organisms.

## ArtSymbioCyc to build high-quality genome-scale metabolic networks

To compare our reconstruction process with arthropods and symbiont genome-scale metabolic models (GSMMs) developed for flux balance analysis (FBA) (53, 54), we retrieved the Enzyme Commission (EC) numbers of 11 GSMMs (Table S2), recovering most of the up-to-date models available in the literature for these organisms. We compared their EC numbers with the ones obtained from our metabolic networks from ArtSymbioCyc for the same organisms. EC numbers were chosen as a comparative metric, as the reaction or metabolite identifiers are not homogeneous between the different GSMMs or between a GSMM and ArtSymbioCyc. EC numbers are identifiers for enzymatic activity, and they can be used as indicators of the coverage of metabolic activities in the different reconstructions.

We plotted the overlaps or specificities of EC numbers using area-proportional Venn diagrams (Fig. S1). For 10 out of the 11 GSMMs, we found that GSMMs are subsets of ArtSymbioCyc: almost all the EC numbers of the GSMMs are found in ArtSymbioCyc networks, but an important fraction of EC numbers is present only in ArtSymbioCyc.

The only GSMM with coverage of metabolic capacities close to ArtSymbioCyc is the work of Cesur et al. (55) on *D. melanogaster*. The authors took advantage of a large amount of information available on HMR2 (human metabolic reaction database 2) and adapted it to *D. melanogaster* using orthologies between the human and the *D. melanogaster* genomes available in the FlyBase database (56). They also integrated metabolic reconstruction based on the MetaCyc database (based on the same reconstruction tools as ArtSymbioCyc) (15). This shows that the BioCyc-based reconstruction process could be systematically integrated into all GSMMs to extend the metabolic coverage of each organism as far as possible, and our database is a valuable tool for this purpose. However, it would require very intensive additional work to achieve the quality and coverage of the *D. melanogaster* model in the non-model organisms we study here.

For *A. pisum* (the pea aphid), we manually examined the EC numbers that do not overlap (i.e., specific to either Blow's GSMM [57] or ArtSymbioCyc). Of the 14 EC numbers that are GSMM specific, 8 of them are obsolete EC numbers that have been reclassified in ArtSymbioCyc reconstruction. For the six remaining cases, we found that a very close enzymatic activity was found in ArtSymbioCyc for the associated genes, such as for D-aspartate oxidase (written as 1.4.3.1 in the GSMM vs 1.4.3.15 in ArtSymbioCyc) or phosphopantothenate-cysteine ligase (written as 6.3.2.5 in the GSMM vs 6.3.2.51 in ArtSymbioCyc). For this latter enzyme, we note that the ArtSymbioCyc EC number might be more accurate, as it is described in the KEGG database (58) as the eukaryotic version of the enzyme. For the last two cases, we estimated that a manual investigation is required to decide which annotation is the most appropriate: the gene LOC100168402 is identified as encoding for an enzyme that acts on GTP in the GSMM, whereas it is identified as an enzyme that acts on dUTP and dCTP in ArtSymbioCyc. Conversely, we examined the EC numbers of *A. pisum* that are specific to ArtSymbioCyc. Some of them are related to the degradation of key metabolites, such as amino acids and nucleotides. Also, many of them are related to secondary metabolism, including biosynthesis and degradation of sphingolipids (ceramide), carotenoids (retinoate and neurosporene), and catecholamine neurotransmitters (dopamine and norepinephrine). These families of metabolites are known to be of great importance for aphids (59) or more broadly for insects (60–62). Overall, the additional metabolic capacities provided by ArtSymbioCyc
<figure><img src="image_3.png" /><figcaption>**FIG 1** The three-step pipeline for metabolic network reconstructions of ArtSymbioCyc. (A) Functional annotations of the protein data set (protein fasta file input) are predicted by several annotation methods (i.e., Blast2GO, Interproscan, KAAS, and Priam). (B) CycADS collects these annotation files together with the gff/gb genome structural annotation files (annotation loaders process). CycADS creates its own internal representation of information (CycADS factory process), enabling it to be stored in an SQL database and to generate structured annotations for Path-o-Logic tools (annotation generators process). (C) Pathway tools build the PGDB from the Path-o-Logic File (PF) information and the genome sequence based on MetaCyc, using (i) pruning of the reconstructed pathways for a simple organism or (ii) without taxonomic pruning for a multi-organism reconstruction mixing prokaryotic and eukaryotic pathways (Path-o-Logic Builder process). The ontology editor process is used to add useful metadata such as sequence source information, associated publications, external links description, etc., and finally, a consistency checker process is applied to each PGDB. An example of representation, termed glyph, can also be found in the web interface. It represents the sequence of reactions (lines) undergone by compounds (rounds) in a pathway present in the PGDB. These PGDBs are stored in an SQL database. They can be accessed through the ArtSymbioCyc interface.</figcaption></figure>

show that GSMMs lack secondary metabolism and some degradation processes. These absences in GSMMs are not expected to be detrimental for FBA as this latter approach aims to (semi-)quantitatively model growth processes based on the main biomass components (e.g., DNA, RNA, proteins...) (53). A GSMM that is too large would also increase the risk of modeling artifacts that can occur in FBA and would require extensive manual curation (54). However, for a more qualitative and exploratory analysis of arthropod/symbiont metabolisms, crucial pathways for organisms' adaptation or development are missed if we only focus on incomplete GSMMs tailored for FBA.

## ArtSymbioCyc to ease and speed up metabolic network comparisons and analyses of host symbionts complementation

Many studies have been devoted to comparing symbiotic systems in order to decipher nutritional complementation (63–67) or to study genome evolution and the selective pressures exerted on the genomes of associated partners (68–70). For the first time, the ArtSymbioCyc collection and its BioCyc interface offer the community powerful tools capable of automatically carrying out a very large number of comparative analyses with high-quality graphical outputs (71). As an example, Table S3 compares the main biosynthetic pathways between the three aphid symbiotic systems *A. pisum*, *C. cedri*,
and *S. maydis*, and Fig. S2 compares the central metabolic pathways of these three host species. It should be noted, however, that human expertise is still required to validate or complete certain data (e.g., arginine biosynthesis in Table S3).

## A case study: the tripartite cooperation between *S. maydis* and its nutritional symbionts

The newly sequenced *S. maydis* genome (16) encodes 2,523 enzymes involved in 273 metabolic pathways. As a comparison, the reference *A. pisum* genome (AL4f, 23 March 2018) encodes 3,897 enzymes involved in 289 metabolic pathways. The two aphid holobionts are expected to differ in several aspects (Table S1), as the pea aphid contains only the primary symbiont *B. aphidicola*, whereas, in *S. maydis*, *B. aphidicola* with a reduced genome of 0.46 Mbp cooperates with the more recently acquired co-obligate symbiont *S. symbiotica* in several metabolic pathways. The most important differences between the two metabolic networks are summarized in Fig. 2. Overall, *S. maydis* appears as a metabolic subset of *A. pisum* and has restricted catabolic capacities as it is unable to assimilate certain carbohydrates, inorganic sulfur, and choline.

## Amino acid metabolism in *S. maydis*

From the ArtSymbioCyc interface, users can track the fate of compounds at the end (so-called dead-end products) or at the beginning (so-called precursors) of a metabolic pathway. Thus, we have been able to reconstruct the integrated metabolic networks for the biosynthesis of amino acids shared between *S. maydis* and its symbionts. Amino acid production is partitioned between *B. aphidicola* and *S. maydis*, which are therefore dependent on each other, while *S. symbiotica* reveals to be a sink for these important compounds (Fig. 3). With the exception of glycine, which is a metabolic hub, both nutritional symbionts have lost most of their ability to produce the non-essential amino acids that are either produced by the host (glutamate, aspartate, serine, proline, and tyrosine), or found in abundance in phloem sap (glutamine and asparagine [72]). Regarding the essential amino acids, *S. symbiotica* has conserved two incomplete pathways, which are partially redundant with those present in *B. aphidicola*, suggesting that the co-obligate symbiont could boost the system by producing chorismate for the three aromatic amino acids phenylalanine, tyrosine, tryptophan, and meso-diaminopimelate for lysine. *S. symbiotica* is therefore dependent on *B. aphidicola* and/or the aphid to produce all the essential amino acids.

*B. aphidicola* has the capability to produce histidine, threonine, tryptophan, and phenylalanine, although the last transamination step from phenylpyruvate to phenylalanine is performed only in the host compartment, which is likely to prevent the symbiont to produce this amino acid in a selfish manner, as reported for the pea aphid-*Buchnera* system (46). Again, as in the case of the pea aphid, tyrosine is produced solely by *S. maydis* from phenylalanine, itself synthesized from phenylpyruvate supplied by *B. aphidicola*. A reversible interconversion between glycine and threonine is encoded in the aphid genome (via L-threonine aldolase), but this is more likely to be a threonine salvage reaction than a biosynthetic one (73). *B. aphidicola* can synthesize the three branched amino acids (valine, isoleucine, and leucine) up to the final transamination step, the latter being performed by the aphid. The lysine biosynthesis pathway is complete in *B. aphidicola*, while the last step is lacking in *S. symbiotica*.

The complete biosynthetic pathways of cysteine and methionine from central precursors require the transformation of assimilated sulfate into sulfite for the incorporation of sulfur into the molecules. In *B. aphidicola* and *S. symbiotica*, these pathways are not functional. Similarly, *S. maydis* has lost the ability to produce sulfite from sulfate. Cysteine biosynthesis from methionine (via homocysteine) is possible in *S. maydis* but not in *B. aphidicola* and *S. symbiotica*. Cysteine is probably absent or present in very low quantities in the phloem of Poaceae (42, 72), while S-methyl-L-methionine (SMM) has been shown to be the main form of methionine circulating in wheat phloem (74). As *S. maydis* can demethylate SMM using the enzyme homocysteine S-methyltransferase,
<figure><img src="image_4.png" /><figcaption>A. pisum</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>S. maydis</figcaption></figure>

<table><tbody><tr><td rowspan="4">Biosyntheses</td><td rowspan="4">amino acids</td><td>Arg</td><td>✓Ba</td><td>(Aphid / Ba)</td></tr><tr><td>Sulfurated amino acid</td><td>✓Ba</td><td></td></tr><tr><td>Chorismate</td><td>✓Ba</td><td>✓Ba✓Ss</td></tr><tr><td>DAP</td><td>✓Ba</td><td>✓Ba✓Ss</td></tr><tr><td rowspan="5">vitamins</td><td>Coenzyme A</td><td>✓(Aphid / Ba)</td><td>✓(Aphid / Ss)</td></tr><tr><td>B1</td><td></td><td>✓Ss</td></tr><tr><td>B2</td><td>✓Ba</td><td>✓Ss</td></tr><tr><td>FRDP (heme O precursor)</td><td>✓Aphid✓Ba</td><td>✓Aphid✓Ss</td></tr><tr><td>NAD from NADP</td><td>✓Aphid</td><td>X</td></tr><tr><td rowspan="5">Assimilation</td><td rowspan="5">carbo-<br>hydrate</td><td>Sulfate</td><td>✓Ba</td><td>X</td></tr><tr><td>Sulfite</td><td>✓Aphid✓Ba</td><td>X</td></tr><tr><td>Phosphatidylcholine hydrolysis</td><td>✓Aphid</td><td>X</td></tr><tr><td>Glycine betaine production</td><td>✓Aphid</td><td>X</td></tr><tr><td>Mannose</td><td>✓Aphid</td><td>X</td></tr><tr><td></td><td></td><td>Mannitol</td><td>✓Aphid</td><td>X</td></tr><tr><td></td><td></td><td>Melobiose</td><td>✓Aphid</td><td>X</td></tr></tbody></table>

✓ Achievable

<figure><img src="image_6.png" /></figure>

Codependence ( means codependence between diet and one organism)

<figure><img src="image_7.png" /></figure>

X Unachievable, expected to be absent/undone in holobiont metabolism

<figure><img src="image_8.png" /></figure>

Unachievable, expected to be compensated by a supply from aphid diet

<caption>FIG 2 Main differences between the metabolisms of *A. pisum* and *S. maydis* holobionts. Differences between the two *B. aphidicola* strains that have no direct impact on their respective host's metabolism are not shown. The organism achieving or co-achieving the metabolic process is referred to as aphid for *A. pisum* or *S. maydis*, Ba for *B. aphidicola*, or Ss for *S. symbiotica*. DAP: L,L-diaminopimelate; FRDP: farnesyl diphosphate.</caption>

SMM is the best candidate (rather than methionine) to enter the system and be used as a precursor for methionine and cysteine biosynthesis that are distributed to the symbiotic bacterial partners. This dependence on the organic sulfur source in the phloem appears to be a rather specific feature of this holobiont, as *A. pisum* holobiont achieves both inorganic sulfur assimilation and sulfur-containing amino acid biosynthesis (Fig. 2). This could be linked to the abundance of SMM in the phloem of Poaceae such as wheat (74).
<figure><img src="image_9.png" /><figcaption>**FIG 3** The integrated metabolic network for amino acid biosynthesis of *S. maydis* holobiont. Final products (amino acids) are framed by a circle, and the unframed compounds represent the precursors. Amino acids and precursors are colored according to the compartment where they can be biosynthesized (*S. maydis*, *B. aphidicola*, or *S. symbiotica* cells). Some are hence bicolored or tricolored. Linear arrows represent a biosynthetic pathway, and thick empty arrows represent transport reactions. Question marks correspond to the hypotheses raised by the genomic inference we carried out for the present work. 3-M-2-OB: 3-methyl-2-oxobutanoate; 3-M-2-OP: 3-methyl-2-oxopentanoate; 3 P-G: 3-P-D-glycerate; 4-M-2-OP: 4-methyl-2-oxopentanoate; CBMP: carbamoyl phosphate; CHO: chorismate; DAP: L,L-diaminopimelate; ERP: D-erythrose 4-phosphate; HCYS: homocysteine; ONN: ornithine; PHPYR: phenylpyruvate; PRPP: 5-phospho-α-D-ribose 1-diphosphate; PYR: pyruvate; SMM: S-methyl-L-methionine.</figcaption></figure>

In *B. aphidicola*, only the last part of the arginine pathway, which consists of the synthesis of arginine from ornithine, is conserved. Furthermore, Renoz et al. (17) reported that only one gene (*carA*) of the two (*carA* and *carB*) required for the production of carbamoyl-P (CBMP), a required co-substrate of the pathway, is present in *B. aphidicola* symbiont of *S. maydis*. Therefore, we hypothesize that another unidentified gene replaces *carB*, or CBMP is produced by *S. maydis* and supplied to *B. aphidicola* for use in the subsequent steps. In *S. symbiotica*, the pathway is completely lacking. *S. maydis* is able to synthesize ornithine from glutamate and encodes the complete enzymatic complex for CBMP production but lacks the ability to perform the final steps in the
<figure><img src="image_10.png" /><figcaption>**FIG 4** The integrated metabolic network for the biosynthesis of vitamins of *S. maydis* holobiont. Final products (vitamins) are framed by a circle; unframed compounds represent precursors. Vitamins and precursors are colored according to the compartment where they can be biosynthesized (*S. maydis*, *B. aphidicola*, or *S. symbiotica* cells). Some are bicolored. Linear arrows represent a biosynthetic pathway, and thick empty arrows represent transport reactions. acCoA: acetyl coenzyme-A; β-CAR: β-carotene; β-NRN: β-nicotinate D-ribonucleotide; dPCoA: dephosphocoenzyme A; FAD: flavin adenine dinucleotide; FMN: flavin mononucleotide; FRDP: farnesyl diphosphate; G3P: glyceraldehyde 3-phosphate; GLY: glycine; PC: phosphatidyl choline; PPTN: phosphopantotheine; PRPP: 5-phosphoribosyl diphosphate; PXL-5P: pyridoxal 5-phosphate; PYR: pyruvate; QLN: quinolinate; RB-5P: ribulose 5-phosphate; THFA: tetrahydrofolate; THPT: tetrahydrobiopterin.</figcaption></figure>

pathway leading to arginine production. This makes *S. maydis* and *B. aphidicola* co-dependent for arginine synthesis.

## Vitamin metabolism in S. maydis

In contrast to what we observed for amino acid biosynthesis, a small number of shared pathways between *S. maydis* and its nutritional symbionts have been found for vitamin biosynthesis (Fig. 4). The symbiotic system appears to rely heavily on the direct supply of vitamins from the plant for eukaryote-specific vitamins such as SMM (vitamin U), which
is also essential for methionine and cysteine biosynthesis (see above), ascorbate (vitamin C), and beta-carotene, the latter being converted by the aphid into retinol (vitamin A). The same observation applies to other more generalist vitamins that the host can absorb from the phloem sap and eventually distribute to its bacterial partners, which have lost the corresponding biosynthetic pathways: pantothenate (vitamin B5), biotin (vitamin B7), pyridoxine (vitamin B6), phylloquinone (vitamin K1), that can be converted by the aphid into menaquinone (vitamin K2), folate polyglutamate (the circulating form of B9 vitamin), that the host and *S. symbiotica* are able to convert into tetrahydrofolate.

Pantothenate (vitamin B5) is an important compound for insects and bacteria, notably for the production of the essential coenzyme A (CoA). However, *S. maydis* is unable to synthesize CoA from pantothenate and must export the latter to *S. symbiotica*, which has conserved the capability to produce CoA. This genomic analysis does not rule out the possibility that the bacterium returns intermediate compounds such as 4P-pantheine or dephospho-CoA to the host, as *S. maydis* encodes in its genome the final steps of the pathway from these precursors (Fig. 4). Conversely, *B. aphidicola* has completely lost the ability to produce CoA and must import it directly from *S. symbiotica* or *S. maydis*.

The case of the biotin (vitamin B7) biosynthesis pathway (Fig. 5) is puzzling. Indeed, the first part of the pathway, linked to fatty acid biosynthesis, is conserved in *B. aphidicola* and is missing in *S. symbiotica*. The final part of the pathway was considered, in a former analysis (17), as shared between *S. symbiotica*, which has conserved

<figure><img src="image_11.png" /><figcaption>**FIG 5** Using the ArtSymbioCyc interface to compare biotin biosynthesis in *S. maydis* and *A. pisum* holobionts. See the color code in the legend to visualize the two compared holobionts *A. pisum* (left side) and *S. maydis* (right side). (A) Comparison of the number of compounds produced in different metabolic categories, including "synthesis of enzymatic cofactors." Clicking on the diagram gives access to synthetic square representations of the different pathways in this class of metabolism (B), including that of biotin. Then, with another click, you can access the details of the pathway, i.e., enzymes, reactions, and compounds within so-called pathway collages (C) to identify the overall capacities of the holobiont and its associated partners. In this biotin-specific analysis, we can see that complete biosynthesis is not possible since any of the holobiont partners can carry out step 2.3.1.47 (8-amino-7-oxononanoate synthase), visualized by the red dotted rectangle (bottom right).</figcaption></figure>
the enzymes ensuring the first two steps, and *B. aphidicola*, which has conserved the enzymes ensuring the last two steps. The availability of the insect host genome shed new light on this pathway, showing that the 8-amino-7-oxononanoate synthase (EC 2.3.1.47), which links the two portions of the pathway, is absent not only from the symbiotic bacteria genomes but also from the *S. maydis* genome. Consequently, our new analysis suggests that biotin cannot be produced by the *S. maydis* symbiotic system (Fig. 5), and this vitamin is entirely supplied by the phloem sap as we propose in Fig. 4.

Nicotinamide (vitamin B3) is essential for the production of NAD and its derivatives. Complete NAD biosynthesis is typically of bacterial origin, but *B. aphidicola* and *S. symbiotica* have lost the corresponding genes. However, *S. maydis* can produce NAD from late intermediates such as quinolate or β-nicotinate D-ribonucleotide, which may be present in the phloem. Consequently, *S. maydis* can support *S. symbiotica* directly for NAD or for β-nicotinate D-ribonucleotide, as the end of the pathway is conserved in the bacterium. It should be noted that *B. aphidicola* must import NAD and NADP from its partners, as this symbiont has lost the enzymes needed to switch from one compound to the other.

The biosynthesis of thiamine (vitamin B1) and riboflavin (vitamin B2) is fully ensured by *S. symbiotica*, which encodes the entire pathway, from 5-phospho-α-D-ribose 1-diphosphate for B1 and from GTP and D-ribulose-5P for B2. It should be noted that, once again, *B. aphidicola* has lost the ability to produce active forms of the vitamins B1 and B2 (thiamine-P, thiamine-PP, flavin mononucleotide, and flavin adenine dinucleotide) and must obtain them from *S. symbiotica*. *S. maydis* can produce heme b from Gly and farnesyl diphosphate (FRDP) from acetyl-CoA, both required for heme O incorporation. *S. symbiotica* only needs to import heme b since the bacterium can synthesize FRDP from pyruvate and glyceraldehyde-3P, whereas *B. aphidicola* is totally dependent on the insect or on *S. symbiotica* for these biosynthetic pathways.

Lipoic acid is a cofactor for at least five enzymes, two of which belong to the citric acid cycle. The two enzymes required for lipoic acid biosynthesis are present in all three partners starting from octanoate, one of the very few cofactors that can be synthesized by *B. aphidicola*.

Tetrahydrobiopterin is an essential enzymatic cofactor (e.g., for the synthesis of aromatic amino acids), which is required in insects but not in bacteria. The tetrahydro-biopterin biosynthetic pathway is complete starting from GTP in *S. maydis*.

Although not a vitamin *per se*, phosphatidylcholine is supposed to be an essential membrane compound for the aphid, but its biosynthesis is not possible by any of the three associated members and must come from the plant (Fig. 4). The presence of lipids and phosphatidylcholine has been found in the phloem of plants of several families (75, 76), but not necessarily in Poaceae, as phloem lipids have been little studied to date and perhaps not at a concentration allowing their use for membrane structure. *B. aphidicola* and *S. symbiotica* may not require phosphatidylcholine, as has been documented for most bacteria that tend towards avirulence (77).

Finally, choline (not shown in Fig. 4) cannot be recovered from phosphatidylcholine in *S. maydis*. Moreover, the aphid, as well as its symbionts, has lost the capability to produce the osmoprotective glycine betaine from choline degradation, unlike *A. pisum*, which has retained both two metabolic capabilities (Fig. 2). Although glycine betaine transport by the phloem within the plant remains poorly understood, it is abundant in Poaceae (78), and this plant source might directly feed the holobiont (thus relieving it of choline). It is also possible that bacterial partners do not need glycine betaine by producing analogous osmoprotectants, such as ethanolamine or glycerol derivatives, as it has been suggested for the commensal microbiota of *D. melanogaster* (79).

## Concluding remarks

We show that ArtSymbioCyc is a unique resource for exploring and comparing the genome-wide metabolic networks of associated partners. It is also a tool for detecting critical nutritional interactions and thus for better understanding the adaptive potential
of symbiotic organisms. ArtSymbioCyc is also a powerful tool for producing high-quality genome-scale metabolic networks with homogeneous annotations predicted by the CysADS system.

By focusing on amino acid and vitamin metabolism in the *S. maydis* holobiont, we showed that the three symbiotic partners evolved together to specifically exploit the phloem of Poaceae. For example, phloem SMM is probably the only source of sulfur for cysteine and methionine biosynthesis, and most vitamins can only be synthesized from specific plant precursors. Throughout their evolutionary history, the genomes of *B. aphidicola* and *S. symbiotica* have greatly reduced their repertoire of genes for vitamin and amino acid biosynthesis and have become highly dependent on their aphid host. Nevertheless, it is remarkable that the metabolisms are still highly intertwined, with obligatory mutual complementations between the three partners, as it has been shown in other aphids and more widely in other hemipterans (11, 67). This strong connectivity, probably selected during evolution to avoid the selfish behavior of one of the partners, seals their common destiny within the plural structure that is the holobiont (3). It should be noted, however, that symbiont exchanges are still possible in highly integrated symbioses, with new symbionts potentially contributing new genes and enabling their host to change niche (11) as well as that symbiont selfish dynamics are sometimes observed (64). Thus, the holobiont concept does not presuppose that the evolutionary interests of the associated partners are convergent, which has even led some authors to reject the term itself (80). In view of the importance of nutritional symbioses in the adaptation of a wide range of insects to their environment, including some of the most serious pests, the ArtSymbioCyc database is a valuable tool to pursue this line of investigation, notably by including more holobionts in the future.

# MATERIALS AND METHODS

## Database collection implementation

The 10 arthropod holobionts included in ArtSymbioCyc at the time of writing have been added mostly based on the previous studies carried out by the authors (Table S1). All the symbiotic organisms in ArthropodaCyc, the largest public database of arthropod metabolisms (81), will gradually be integrated with their corresponding endosymbionts into ArtSymbiocyc, but other organisms, as well as specific partial holobionts (i.e., *A. pisum*—*Buchnera* only), can be included on request.

The architecture and the various steps of genome annotation and metabolic network reconstruction are presented in Fig. 1 in the results section above. To remove putative contaminant bacterial sequences from host genomes, the CycADS annotation system has been improved as described in Baa-Puyoulet et al. (81). Proteins identified as bacterial contaminants are not eliminated from the database but are excluded from the Pathway Tools reaction inference (i.e., from the metabolic network). A warning message appears on their corresponding gene page.

ArtSymbioCyc fully leverages the comprehensive BioCyc interface and its metabolism data analysis tools. Using the BioCyc online interface, users can perform several analyses with advanced query tools and robust web-based genomic data viewers. Additionally, ArtSymbioCyc allows data downloads in various formats for further analysis, using tools like Cytoscape (82) and MetExplore (83), or for integration into custom analysis software and pipelines.

# ACKNOWLEDGMENTS

We would like to thank Juan Perez-Limon for his help in developing some of the parameters of the CycADS annotation system that feeds the ArtSymbioCyc database. We also thank Aurélie Herbomez for secretarial assistance.

Research at BF2i was supported by the Institut National de la Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), and the Institut National des
Sciences Appliquées de Lyon (INSA Lyon). This work was supported by the Agence Nationale de la Recherche (ANR) programs "Co-adaptations hôtes-microbiote: mécanismes et conséquences-Hmicmac" (ANR-16-CE02-0014) and "Fight Bedbug Infestations: guide insecticide treatments and develop alternative methods of control- FBI" (ANR number PrANR-21-CE35-0011).

P.B.-P. and H.C. conceived the project. P.B.-P., N.P., and S.P. developed the database and the associated pipelines. P.B.-P. and L.G. produced the figures. P.B.-P., L.G., N.P., F.R., S.P., F.C., and H.C. analyzed the *S. maydis* holobiont data, contributed to the drafting of the manuscript, and revised and approved the final version of the manuscript.

## AUTHOR AFFILIATIONS

## AUTHOR ORCIDs

Patrice Baa-Puyoulet http://orcid.org/0000-0002-7033-7245

Léo Gerlin http://orcid.org/0000-0002-1398-2790

Nicolas Parisot http://orcid.org/0000-0001-5217-8415

Sergio Peignier http://orcid.org/0000-0002-9004-3033

François Renoz http://orcid.org/0000-0003-3716-4562

Federica Calevro http://orcid.org/0000-0001-7856-9617

Hubert Charles http://orcid.org/0000-0002-0809-4705

## FUNDING

<table><thead><tr><th>Funder</th><th>Grant(s)</th><th>Author(s)</th></tr></thead><tbody><tr><td>Agence Nationale de la Recherche</td><td>ANR-16-CE02-0014</td><td>Patrice Baa-Puyoulet<br>Nicolas Parisot<br>Sergio Peignier<br>Federica Calevro<br>Hubert Charles</td></tr><tr><td>Agence Nationale de la Recherche</td><td>PrANR-21-CE35-0011</td><td>Patrice Baa-Puyoulet<br>Nicolas Parisot<br>Federica Calevro<br>Hubert Charles</td></tr></tbody></table>

## AUTHOR CONTRIBUTIONS

Patrice Baa-Puyoulet, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing | Léo Gerlin, Data curation, Formal analysis, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review and editing | Nicolas Parisot, Data curation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review and editing | Sergio Peignier, Software, Validation, Writing – original draft, Writing – review and editing | François Renoz, Visualization, Writing – original draft, Writing – review and editing | Federica Calevro, Funding acquisition, Writing – original draft, Writing – review and editing | Hubert Charles, Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing

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

<footnote n="2">²Biodiversity Research Centre, Earth and Life Institute, UCLouvain, Louvain-la-Neuve, Belgium</footnote>
## DATA AVAILABILITY

Metabolic network reconstructions were carried out using Pathway Tools 27.0 (12 April 2023). Annual updates of ArtSymbioCyc are carried out to search for and re- annotate new versions of genomes when necessary and to monitor the evolution of the Pathway Tools required for network reconstruction and the analysis interface. Metabolic network reconstructions and the resulting BioCyc metabolism databases are available in the ArtSymbioCyc collection database (https://artsymbiocyc.cycadsys.org/). The annotations, inferred reactions, and networks files of the genomes or proteomes have also been made available in a dedicated data set (84).

## ADDITIONAL FILES

The following material is available online.

## Supplemental Material

Supplemental material (mSystems00140-25-s0001.pdf). Figures S1 and S2; Tables S1 to S3.

## Open Peer Review

PEER REVIEW HISTORY (review-history.pdf). An accounting of the reviewer comments and feedback.

## REFERENCES

1. Margulis L. 1991. Symbiogenesis and symbioticism, p 3-14. In Margulis L, Fester R (ed), Symbiosis as a source of evolutionary innovation - speciation and morphogenesis. MIT Press Ltd, Cambridge, MA.

2. Simon J-C, Marchesi JR, Mougel C, Selosse M-A. 2019. Host-microbiota interactions: from holobiont theory to analysis. Microbiome 7:1-5. https://doi.org/10.1186/s40168-019-0619-4

3. Shigenobu S, Yorimoto S. 2022. Aphid hologenomics: current status and future challenges. Curr Opin Insect Sci 50:100882. https://doi.org/10.1016/j.cois.2022.100882

4. McFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lošo T, Douglas AE, Dubilier N, Eberl G, Fukami T, Gilbert SF, et al. 2013. Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci U S A 110:3229-3236. https://doi.org/10.1073/pnas.1218525110

5. Foster KR, Schlüter J, Coyte KZ, Rakoff-Nahoum S. 2017. The evolution of the host microbiome as an ecosystem on a leash. Nature New Biol 548:43-51. https://doi.org/10.1038/nature23292

6. Rosenberg E, Zilber-Rosenberg I. 2018. The hologenome concept of evolution after 10 years. Microbiome 6:78. https://doi.org/10.1186/s4016 8-018-0457-9

7. Stork NE. 2018. How many species of insects and other terrestrial arthropods are there on earth? Annu Rev Entomol 63:31-45. https://doi. org/10.1146/annurev-ento-020117-043348

8. Losey JE, Vaughan M. 2006. The economic value of ecological services provided by insects. Bioscience 56:311. https://doi.org/10.1641/0006-35 68(2006)56[311:TEVOES]2.0.CO;2

9. Belluco S, Bertola M, Montarsi F, Di Martino G, Granato A, Stella R, Martinello M, Bordin F, Mutinelli F. 2023. Insects and public health: an overview. Insects 14:240. https://doi.org/10.3390/insects14030240

10. Klepzig KD, Adams AS, Handelsman J, Raffa KF. 2009. Symbioses: a key driver of insect physiological processes, ecological interactions, evolutionary diversification, and impacts on humans. Environ Entomol 38:67-77. https://doi.org/10.1603/022.038.0109

11. Husnik F, McCutcheon JP. 2016. Repeated replacement of an intrabacte- rial symbiont in the tripartite nested mealybug symbiosis. Proc Natl Acad Sci U S A 113:E5416-E5424. https://doi.org/10.1073/pnas.1603910 113

12. Vellozo AF, Véron AS, Baa-Puyoulet P, Huerta-Cepas J, Cottret L, Febvay G, Calevro F, Rahbé Y, Douglas AE, Gabaldón T, Sagot M-F, Charles H, Colella S. 2011. CycADS: an annotation database system to ease the development and update of BioCyc databases. Database (Oxford) 2011:bar008. https://doi.org/10.1093/database/bar008

13. Karp PD, Midford PE, Billington R, Kothari A, Krummenacker M, Latendresse M, Ong WK, Subhraveti P, Caspi R, Fulcher C, Keseler IM, Paley SM. 2021. Pathway Tools version 23.0 update: software for pathway/genome informatics and systems biology. Brief Bioinform 22:109-126. https://doi.org/10.1093/bib/bbz104

14. Karp PD, Billington R, Caspi R, Fulcher CA, Latendresse M, Kothari A, Keseler IM, Krummenacker M, Midford PE, Ong Q, Ong WK, Paley SM, Subhraveti P. 2019. The BioCyc collection of microbial genomes and metabolic pathways. Brief Bioinform 20:1085-1093. https://doi.org/10.1 093/bib/bbx085

15. Caspi R, Billington R, Keseler IM, Kothari A, Krummenacker M, Midford PE, Ong WK, Paley S, Subhraveti P, Karp PD. 2020. The MetaCyc database of metabolic pathways and enzymes - a 2019 update. Nucleic Acids Res 48:D445-D453. https://doi.org/10.1093/nar/gkz862

16. Renoz F, Parisot N, Baa-Puyoulet P, Gerlin L, Fakhour S, Charles H, Hance T, Calevro F. 2024. PacBio Hi-Fi genome assembly of *Sipha maydis*, a model for the study of multipartite mutualism in insects. Sci Data 11:450. https://doi.org/10.1038/s41597-024-03297-x

17. Renoz F, Ambroise J, Bearzatto B, Fakhour S, Parisot N, Ribeiro Lopes M, Gala J-L, Calevro F, Hance T. 2022. The di-symbiotic systems in the aphids *Sipha maydis* and *Periphyllus lyropictus* provide a contrasting picture of recent co-obligate nutritional endosymbiosis in aphids. Microorganisms 10:1-21. https://doi.org/10.3390/microorganisms10071 360

18. Wieczorek K, Bugaj-Nawrocka A. 2014. Invasive aphids of the tribe Siphini: a model of potentially suitable ecological niches. Agr Forest Entomol 16:434-443. https://doi.org/10.1111/afe.12073

19. Li Y, Park H, Smith TE, Moran NA. 2019. Gene family evolution in the pea aphid based on chromosome-level genome assembly. Mol Biol Evol 36:2143-2156. https://doi.org/10.1093/molbev/msz138

20. Shigenobu S, Watanabe H, Hattori M, Sakaki Y, Ishikawa H. 2000. Genome sequence of the endocellular bacterial symbiont of aphids *Buchnera* sp. APS. Nature 407:81-86. https://doi.org/10.1038/35024074

21. Degnan PH, Yu Y, Sisneros N, Wing RA, Moran NA. 2009. *Hamiltonella defensa*, genome evolution of protective bacterial endosymbiont from pathogenic ancestors. Proc Natl Acad Sci U S A 106:9063-9068. https://d oi.org/10.1073/pnas.0900194106

22. Julca I, Marcet-Houben M, Cruz F, Vargas-Chavez C, Johnston JS, Gómez- Garrido J, Frias L, Corvelo A, Loska D, Cámara F, Gut M, Alioto T, Latorre A, Gabaldón T. 2020. Phylogenomics identifies an ancestral burst of
gene duplications predating the diversification of Aphidomorpha. Mol
Biol Evol 37:730–756. https://doi.org/10.1093/molbev/msz261

23. Pérez-Brocal V, Gil R, Ramos S, Lamelas A, Postigo M, Michelena JM, Silva FJ, Moya A, Latorre A. 2006. A small microbial genome: the end of a long symbiotic relationship? Science 314:312–313. https://doi.org/10.1126/science.1130441

24. Gil R, Sabater-Muñoz B, Perez-Brocal V, Silva FJ, Latorre A. 2006. Plasmids in the aphid endosymbiont *Buchnera aphidicola* with the smallest genomes. A puzzling evolutionary story. *Gene* 370:17–25. https://doi.org/10.1016/j.gene.2005.10.043

25. Lamelas A, Gosalbes MJ, Manzano-Marín A, Peretó J, Moya A, Latorre A. 2011. *Serratia symbiotica* from the aphid *Cinara cedri*: a missing link from facultative to obligate insect endosymbiont. PLoS Genet 7:e1002357. https://doi.org/10.1371/journal.pgen.1002357

26. Benoit JB, Adelman ZN, Reinhardt K, Dolan A, Poelchau M, Jennings EC, Szuter EM, Hagan RW, Gujar H, Shukla JN, et al. 2016. Unique features of a global human ectoparasite identified through sequencing of the bed bug genome. Nat Commun 7:10165. https://doi.org/10.1038/ncomms10165

27. Nikoh N, Hosokawa T, Moriyama M, Oshima K, Hattori M, Fukatsu T. 2014. Evolutionary origin of insect-*Wolbachia* nutritional mutualism. Proc Natl Acad Sci U S A 111:10257–10262. https://doi.org/10.1073/pnas.1409284111

28. Hoskins RA, Carlson JW, Wan KH, Park S, Mendez I, Galle SE, Booth BW, Pfeiffer BD, George RA, Svirskas R, et al. 2015. The release 6 reference sequence of the *Drosophila melanogaster* genome. Genome Res 25:445–458. https://doi.org/10.1101/gr.185579.114

29. Axelsson L, Rud I, Naterstad K, Blom H, Renckens B, Boekhorst J, Kleerebezem M, van Hijum S, Siezen RJ. 2012. Genome sequence of the naturally plasmid-free *Lactobacillus plantarum* strain NC8 (CCUG 61730). J Bacteriol 194:2391–2392. https://doi.org/10.1128/JB.00141-12

30. Shin SC, Kim S-H, You H, Kim B, Kim AC, Lee K-A, Yoon J-H, Ryu J-H, Lee W-J. 2011. *Drosophila* microbiome modulates host developmental and metabolic homeostasis via insulin signaling. Science 334:670–674. https://doi.org/10.1126/science.1212782

31. Duarte EH, Carvalho A, López-Madrigal S, Costa J, Teixeira L. 2021. Forward genetics in *Wolbachia*: regulation of Wolbachia proliferation by the amplification and deletion of an addictive genomic island. PLoS Genet 17:e1009612. https://doi.org/10.1371/journal.pgen.1009612

32. Attardo GM, ABila PP, Auma JE, Baumann AA, Benoit JB, Brelsfoard CL, Ribeiro JMC, Cotton JA, Pham DQD, Darby AC. 2014. Genome sequence of the tsetse fly (*Glossina morsitans*): vector of African trypanosomiasis. Science 344:380–386. https://doi.org/10.1126/science.1249656

33. Toh H, Weiss BL, Perkin SAH, Yamashita A, Oshima K, Hattori M, Aksoy S. 2006. Massive genome erosion and functional adaptations provide insights into the symbiotic lifestyle of *Sodalis glossinidius* in the tsetse host. Genome Res 16:149–156. https://doi.org/10.1101/gr.4106106

34. Rio RVM, Symula RE, Wang J, Lohs C, Wu Y, Snyder AK, Bjornson RD, Oshima K, Biehl BS, Perna NT, Hattori M, Aksoy S. 2012. Insight into the transmission biology and species-specific functional capabilities of tsetse (Diptera: glossinidae) obligate symbiont *Wigglesworthia*. mBio 3:e00240-11. https://doi.org/10.1128/mBio.000240-11

35. Chen W, Hasegawa DK, Kaur N, Kliot A, Pinheiro PV, Luan J, Stensmyr MC, Zheng Y, Liu W, Sun H, et al. 2016. The draft genome of whitefly *Bemisia tabaci* MEAM1, a global crop pest, provides novel insights into virus transmission, host adaptation, and insecticide resistance. BMC Biol 14:110. https://doi.org/10.1186/s12915-016-0321-y

36. Rao Q, Wang S, Su Y-L, Bing X-L, Liu S-S, Wang X-W. 2012. Draft genome sequence of "Candidatus Hamiltonella defensa," an endosymbiont of the whitefly *Bemisia tabaci*. J Bacteriol 194:3558. https://doi.org/10.1128/JB.00069-12

37. Rao Q, Wang S, Zhu D-T, Wang X-W, Liu S-S. 2012. Draft genome sequence of *Rickettsia* sp. strain MEAM1, isolated from the whitefly *Bemisia tabaci*. J Bacteriol 194:4741–4742. https://doi.org/10.1128/JB.00909-12

38. Xie W, Chen C, Yang Z, Guo L, Yang X, Wang D, Chen M, Huang J, Wen Y, Zeng Y, et al. 2017. Genome sequencing of the sweetpotato whitefly *Bemisia tabaci* MED/Q. Gigascience 6:1–7. https://doi.org/10.1093/gigascience/gix018

39. Santos-Garcia D, Farnier P-A, Beitia F, Zchori-Fein E, Vavre F, Mouton L, Moya A, Latorre A, Silva FJ. 2012. Complete genome sequence of "Candidatus Portiera aleyrodidarum" BT-QVLC, an obligate symbiont that supplies amino acids and carotenoids to *Bemisia tabaci*. J Bacteriol 194:6654–6655. https://doi.org/10.1128/JB.01793-12

40. Rao Q, Rollat-Farnier P-A, Zhu D-T, Santos-Garcia D, Silva FJ, Moya A, Latorre A, Klein CC, Vavre F, Sagot M-F, Liu S-S, Mouton L, Wang X-W. 2015. Genome reduction and potential metabolic complementation of the dual endosymbionts in the whitefly *Bemisia tabaci*. BMC Genomics 16:226. https://doi.org/10.1186/s12864-015-1379-6

41. Santos-Garcia D, Rollat-Farnier P-A, Beitia F, Zchori-Fein E, Vavre F, Mouton L, Moya A, Latorre A, Silva FJ. 2014. The genome of *Cardinium* cBtQ1 provides insights into genome reduction, symbiont motility, and its settlement in *Bemisia tabaci*. Genome Biol Evol 6:1013–1030. https://doi.org/10.1093/gbe/evu077

42. Selvaraj G, Santos-Garcia D, Mozes-Daube N, Medina S, Zchori-Fein E, Freilich S. 2021. An eco-systems biology approach for modeling tritrophic networks reveals the influence of dietary amino acids on symbiont dynamics of *Bemisia tabaci*. FEMS Microbiol Ecol 97:1–14. https://doi.org/10.1093/femsec/flab117

43. Kirkness EF, Haas BJ, Sun W, Braig HR, Perotti MA, Clark JM, Lee SH, Robertson HM, Kennedy RC, Elhaik E, et al. 2010. Genome sequences of the human body louse and its primary endosymbiont provide insights into the permanent parasitic lifestyle. Proc Natl Acad Sci U S A 107:12168–12173. https://doi.org/10.1073/pnas.1003379107

44. Parisot N, Vargas-Chávez C, Goubert C, Baa-Puyoulet P, Balmand S, Beranger L, Blanc C, Bonnamour A, Boulesteix M, Burlet N, et al. 2021. The transposable element-rich genome of the cereal pest *Sitophilus oryzae*. BMC Biol 19:241. https://doi.org/10.1186/s12915-021-01158-2

45. Oakeson KF, Gil R, Clayton AL, Dunn DM, von Niederhausern AC, Hamil C, Aoyagi A, Duval B, Baca A, Silva FJ, Vallier A, Jackson DG, Latorre A, Weiss RB, Heddi A, Moya A, Dale C. 2014. Genome degeneration and adaptation in a nascent stage of symbiosis. Genome Biol Evol 6:76–93. https://doi.org/10.1093/gbe/evt210

46. Wilson ACC, Ashton PD, Calevro F, Charles H, Colella S, Febvay G, Jander G, Kushlan PF, Macdonald SJ, Schwartz JF, Thomas GH, Douglas AE. 2010. Genomic insight into the amino acid relations of the pea aphid, *Acyrthosiphon pisum*, with its symbiotic bacterium *Buchnera aphidicola*. Insect Mol Biol 19 Suppl 2:249–258. https://doi.org/10.1111/j.1365-2583.2009.00942.x

47. International Aphid Genomics Consortium. 2010. Genome sequence of the pea aphid *Acyrthosiphon pisum*. PLoS Biol 8:e1000313. https://doi.org/10.1371/journal.pbio.1000313

48. Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. 2005. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21:3674–3676. https://doi.org/10.1093/bioinformatics/bti610

49. Conesa A, Götz S. 2008. Blast2GO: a comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics 2008:619832. https://doi.org/10.1155/2008/619832

50. Jones P, Binns D, Chang H-Y, Fraser M, Li W, McAnulla C, McWilliam H, Maslen J, Mitchell A, Nuka G, Pesseat S, Quinn AF, Sangrador-Vegas A, Scheremetjew M, Yong S-Y, Lopez R, Hunter S. 2014. InterProScan 5: genome-scale protein function classification. Bioinformatics 30:1236–1240. https://doi.org/10.1093/bioinformatics/btu031

51. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. 2007. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res 35:W182–W185. https://doi.org/10.1093/nar/gkm321

52. Claudel-Renard C, Chevalet C, Faraut T, Kahn D. 2003. Enzyme-specific profiles for genome annotation: PRIAM. Nucleic Acids Res 31:6633–6639. https://doi.org/10.1093/nar/gkg847

53. Orth JD, Thiele I, Palsson BØ. 2010. What is flux balance analysis? Nat Biotechnol 28:245–248. https://doi.org/10.1038/nbt.1614

54. Thiele I, Palsson BØ. 2010. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc 5:93–121. https://doi.org/10.1038/nprot.2009.203

55. Cesur MF, Basile A, Patil KR, Çakir T. 2023. A new metabolic model of *Drosophila melanogaster* and the integrative analysis of Parkinson's disease. Life Sci Alliance 6:e202201695. https://doi.org/10.26508/lsa.20201695

56. Larkin A, Marygold SJ, Antonazzo G, Attrill H, Dos Santos G, Garapati PV, Goodman JL, Gramates LS, Millburn G, Strelets VB, Tabone CJ, Thurmond J, FlyBase Consortium. 2021. FlyBase: updates to the *Drosophila melanogaster* knowledge base. Nucleic Acids Res 49:D899–D907. https://doi.org/10.1093/nar/gkaa1026

57. Blow F, Ankrah NYD, Clark N, Koo I, Allman EL, Liu Q, Anitha M, Patterson AD, Douglas AE. 2020. Impact of facultative bacteria on the metabolic function of an obligate insect-bacterial symbiosis. mBio 11:e00402-20. https://doi.org/10.1128/mBio.000402-20
58. Kanehisa M, Goto S, Kawashima S, Nakaya A. 2002. The KEGG databases at GenomeNet. Nucleic Acids Res 30:42–46. https://doi.org/10.1093/nar/30.1.42

59. Takemura M, Maoka T, Koyanagi T, Kawase N, Nishida R, Tsuchida T, Hironaka M, Ueda T, Misawa N. 2021. Elucidation of the whole carotenoid biosynthetic pathway of aphids at the gene level and arthropodal food chain involving aphids and the red dragonfly. BMC Zool 6:19. https://doi.org/10.1186/s40850-021-00082-w

60. Hamdorf K, Höglund G, Juse A, Stusek P. 1989. Effect of neurotransmitters on movement of screening pigment in insect superposition eyes. Z Naturforsch C 44:992–998. https://doi.org/10.1515/znc-1989-11-1220

61. Verlinden H. 2018. Dopamine signalling in locusts and other insects. Insect Biochem Mol Biol 97:40–52. https://doi.org/10.1016/j.ibmb.2018.04.005

62. Panevska A, Skočaj M, Križaj I, Maček P, Sepčić K. 2019. Ceramide phosphoethanolamine, an enigmatic cellular membrane sphingolipid. Biochim Biophys Acta Biomembr 1861:1284–1292. https://doi.org/10.1016/j.bbamem.2019.05.001

63. Belda E, Silva FJ, Peretó J, Moya A. 2012. Metabolic networks of *Sodalis glossinidius*: a systems biology approach to reductive evolution. PLoS One 7:e30652. https://doi.org/10.1371/journal.pone.0030652

64. Ankrah NYD, Luan J, Douglas AE. 2017. Cooperative metabolism in a three-partner insect-bacterial symbiosis revealed by metabolic modeling. J Bacteriol 199:e00872-16. https://doi.org/10.1128/JB.00872-16

65. Serbus LR, Rodriguez BG, Sharmin Z, Momtaz A, Christensen S. 2017. Predictive genomic analyses inform the basis for vitamin metabolism and provisioning in bacteria-arthropod endosymbioses. G3 (Bethesda) 7:1887–1898. https://doi.org/10.1534/g3.117.042184

66. Hall RJ, Flanagan LA, Bottery MJ, Springthorpe V, Thorpe S, Darby AC, Wood AJ, Thomas GH. 2019. A tale of three species: adaptation of *Sodalis glossinidius* to tsetse biology. *Wigglesworthia* metabolism, and host diet. mBio 10:e02106-18. https://doi.org/10.1128/mBio.02106-18

67. Renoz F. 2024. The nutritional dimension of facultative bacterial symbiosis in aphids: current status and methodological considerations for future research. Curr Res Insect Sci 5:100070. https://doi.org/10.1016/j.cris.2023.100070

68. Belda E, Moya A, Bentley S, Silva FJ. 2010. Mobile genetic element proliferation and gene inactivation impact over the genome structure and metabolic capabilities of *Sodalis glossinidius*, the secondary endosymbiont of tsetse flies. BMC Genomics 11:449. https://doi.org/10.1186/1471-2164-11-449

69. Wernegreen JJ. 2017. In it for the long haul: evolutionary consequences of persistent endosymbiosis. Curr Opin Genet Dev 47:83–90. https://doi.org/10.1016/j.gde.2017.08.006

70. Douglas AE. 2018. Omics and the metabolic function of insect-microbial symbioses. Curr Opin Insect Sci 29:1–6. https://doi.org/10.1016/j.cois.2018.05.012

71. Paley S, Caspi R, O'Maille P, Karp PD. 2024. The comparative genome dashboard. Front Microbiol 15:1447632. https://doi.org/10.3389/fmicb.2024.1447632

72. Fukumorita T, Chino M. 1982. Sugar, amino acid and inorganic contents in rice phloem sap. Plant Cell Physiol 23:273–283. https://doi.org/10.1093/oxfordjournals.pcp.a076347

73. Hansen AK, Moran NA. 2011. Aphid genome expression reveals host-symbiont cooperation in the production of amino acids. Proc Natl Acad Sci U S A 108:2849–2854. https://doi.org/10.1073/pnas.1013465108

74. Bourgis F, Roje S, Nuccio ML, Fisher DB, Tarczynski MC, Li C, Herschbach C, Rennenberg H, Pimenta MJ, Shen T-L, Gage DA, Hanson AD. 1999. S-methylmethionine plays a major role in phloem sulfur transport and is synthesized by a novel type of methyltransferase. Plant Cell 11:1485–1498. https://doi.org/10.1105/tpc.11.8.1485

75. Benning UF, Tamot B, Guelette BS, Hoffmann-Benning S. 2012. New aspects of phloem-mediated long-distance lipid signaling in plants. Front Plant Sci 3:53. https://doi.org/10.3389/fpls.2012.00053

76. Koenig AM, Hoffmann-Benning S. 2020. The interplay of phloem-mobile signals in plant development and stress response. Biosci Rep 40:BSR20193329. https://doi.org/10.1042/BSR20193329

77. Liu X, Sun Y, Cao F, Xiong M, Yang S, Li Y, Yu X, Li Y, Wang X. 2017. Absence of phosphatidylylcholine in bacterial membranes facilitates translocation of Sec-dependent β-lactamase AmpC from cytoplasm to periplasm in two *Pseudomonas* strains. Microb Pathog 106:94–102. https://doi.org/10.1016/j.micpath.2016.04.010

78. Annunziata MG, Ciariello LF, Woodrow P, Dell'Aversana E, Carillo P. 2019. Spatial and temporal profile of glycine betaine accumulation in plants under abiotic stresses. Front Plant Sci 10:230. https://doi.org/10.389/fpls.2019.00230

79. Consuegra J, Grenier T, Baa-Puyoulet P, Rahioui I, Akherraz H, Gervais H, Parisot N, da Silva P, Charles H, Calevro F, Leulier F. 2020. Drosophila-associated bacteria differentially shape the nutritional requirements of their host during juvenile growth. PLoS Biol 18:e3000681. https://doi.org/10.1371/journal.pbio.3000681

80. Douglas AE, Werren JH. 2016. Holes in the hologenome: why host-microbe symbioses are not holobionts. mBio 7:e02099-15. https://doi.org/10.1128/mBio.02099-15

81. Baa-Puyoulet P, Parisot N, Febvay G, Huerta-Cepas J, Vellozo AF, Gabaldón T, Calevro F, Charles H, Colella S. 2016. ArthropodaCyc: a CycADS powered collection of BioCyc databases to analyse and compare metabolism of arthropods. Database (Oxford) 2016:baw081. https://doi.org/10.1093/database/baw081

82. Franz M, Lopes CT, Huck G, Dong Y, Sumer O, Bader GD. 2016. Cytoscape.js: a graph theory library for visualisation and analysis. Bioinformatics 32:309–311. https://doi.org/10.1093/bioinformatics/btv557

83. Cottret L, Wildridge D, Vinson F, Barrett MP, Charles H, Sagot M-F, Jourdan F. 2010. MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks. Nucleic Acids Res 38:W132–W137. https://doi.org/10.1093/nar/gkq312

84. Bâa-Puyoulet P, Gerlin L, Parisot N, Peignier S, Renoz F, Calevro F, Charles H. 2024. ArtSymbioCyc, a metabolic network database collection dedicated to insect symbioses. Recherche Data Gouv. https://doi.org/10.57745/IRQOEL