Variation in density, immune gene suppression, and coinfection outcomes among strains of the aphid endosymbiont Regiella insecticola

Abstract

Many insects harbor heritable microbes that influence host phenotypes. Symbiont strains establish at different densities within hosts. This variation is important evolutionarily because within-host density has been linked to the costs and benefits of the symbiosis for both partners. Studying the factors shaping within-host density is important to our broader understanding of host–microbe coevolution. Here we focused on different strains of Regiella insecticola, a facultative symbiont of aphids. We first showed that strains of Regiella establish in pea aphids at drastically different densities. We then found that variation in density is correlated with the expression levels of two key insect immune system genes (phenoloxidase and hemocytin), with the suppression of immune gene expression correlating with higher Regiella density. We then performed an experiment where we established coinfections of a higher- and a lower-density Regiella strain, and we showed that the higher-density strain is better able to persist in coinfections than the lower-density strain. Together, our results point to a potential mechanism that contributes to strain-level variation in symbiont density in this system, and our data suggest that symbiont fitness may be increased by establishing at higher density within hosts. Our work highlights the importance of within-host dynamics shaping symbiont evolution.

Introduction

Most insects harbor heritable microbes (Weinert et al., 2015). These symbiotic associations can range from parasitic to mutualistic, and symbionts have been shown to influence host traits including plant use, body color, and defense against natural enemies (Oliver et al., 2010; Zug & Hammerstein, 2015). An important aspect of insect–symbiont interactions is the within-host density of symbiont infections (Drew & King, 2022; Lopez-Madrigal & Duarte, 2019; Parker, 2021). Symbiont density has been shown to vary across individual insects, driven in part by genetic variation among microbes and/or hosts (Chong & Moran, 2016). For example, the density of Wolbachia, a widely distributed genus of bacteria that often acts as a reproductive parasite, varies drastically across bacterial strains and host species. The molecular mechanisms underlying this variation have been uncovered in some Wolbachia–host interactions: A region of the bacterial genome termed Octomom controls Wolbachia density in Drosophila melanogaster (Chrostek & Teixeira, 2015) and a host gene of unknown function drives Wolbachia density across species of Nasonia wasps (Funkhouser-Jones et al., 2018).

Within-host density is a particularly important aspect of host–symbiont interactions because it has been clearly linked with the fitness of both partners. Higher-density infections can confer benefits to hosts in some systems but also impose stronger costs on hosts. For example, higher-density Wolbachia infections confer stronger protection to Drosophila hosts against viral infection (Martinez et al., 2017) but also decrease host survival (Martinez et al., 2015). For symbionts, density has also been shown to influence fitness by affecting transmission success. The density of Wolbachia in naturally infected Drosophila innubila flies, for example, is correlated with maternal transmission rates (Unckless et al., 2009). Density might also influence microbial fitness to the extent that the fitnesses of both partners are linked by vertical transmission. However, it is possible that the “optimal” density is different from the perspectives of host and symbiont fitness, leading to antagonism over control of symbiont density even in mutualistic symbioses. Studying the forces shaping symbiont density, and in particular how symbionts balance within-host selective pressures versus the effects they have on host fitness, is important for our broader understanding of host–microbe associations.

Pea aphids (Acyrthosiphon pisum) are an important model for studying host–symbiont interactions. Aphids host several species of gram-negative bacteria, including an “obligate” symbiont called Buchnera aphidicola that is required for host survival and several “facultative” symbionts that are found at intermediate frequencies in natural populations and can confer important benefits to hosts (Oliver et al., 2010). For example, the Gammaproteobacteria Regiella insecticola (hereafter Regiella) has been shown to make pea aphids more resistant to specialist fungal pathogens (Scarborough et al., 2005; Parker et al., 2013). Outside of pea aphids, the role of Regiella is more complicated: An isolate of Regiella from the peach potato aphid (Myzus persicae), referred to as strain .515, was shown to confer protection against parasitoid wasp infection (i.e., harboring this strain of Regiella makes aphids less likely to become mummified after parasitism by a wasp; Vorburger et al., 2010). It is currently unclear if other Regiella strains also protect against parasitoids. However, strain .515 and another Regiella from the English grain aphid (Sitobion avenae), referred to here as .RR5, were shown not to provide significant protection against fungal pathogens (Parker et al., 2017). Regiella found in natural populations of pea aphids form two main phylogenetic groups (termed “clade 1” and “clade 2”) that are separated by around a half-million years (Henry et al., 2013). Recent studies have demonstrated that there is some horizontal transmission of Regiella across host lineages. Studies have also found that strains from both clades are found in natural populations and have shown that individual aphids can harbor coinfections of clade 1 with clade 2 Regiella strains (Guyomar et al., 2018). Previous work has found that Regiella strains vary in the density at which they establish in the same host genetic background (Parker et al., 2021). It has also been shown that across multiple strains of Regiella from pea aphids, symbiont density is correlated with the survival costs inflicted on aphids, but is not associated with the protective benefits to aphids from harboring symbionts (Parker et al., 2021).

Several recent studies have found that some facultative symbionts interact with the aphid innate immune system. Specifically, aphids harboring a strain of Regiella were shown to have decreased numbers of circulating immune cells (Schmitz et al., 2012) and reduced expression (Nichols et al., 2021) and protein levels (Luo et al., 2020) of phenolxoidase, a critical component of the insect innate immune system. Suppression of phenoloxidase (PO1) using RNAi leads to an increase in Regiella densities (Nichols et al., 2021). Similar trends have been found for other aphid endosymbionts: A recent study identified specific strains of the aphid facultative symbiont Hamiltonella defensa that reach extremely high densities within hosts and suppress expression of host immune genes (Kaech et al., 2021). Together these studies suggest differences in how symbionts interact with the host immune system could contribute to variation in density across symbiont strains.

In this study, we established multiple strains of Regiella in a single genotype of pea aphid. We show that variation in Regiella density is negatively correlated with the expression of two immune genes across symbiont strains. We then explored why high-density Regiella strains might persist in natural populations. We established aphid lines with coinfections of a higher-density strain with a lower-density strain, and we tracked symbiont loss over 8 generations using a strain-specific PCR assay. Our results suggest that the higher-density strain is maintained better in coinfections than the lower-density strain. Together, we argue that suppressing host immunity to establish at high densities might benefit symbionts even at the expense of host fitness, and we discuss these results in light of the within-host versus host-level selective pressures that shape symbiont evolution.

Materials and methods

Aphid and symbiont line maintenance

We maintained stock lines of aphids on fava bean plants (Vicia faba var. Windsor) at low densities (fewer than seven adults per plant) at 20°C, 16L:8D. These light and temperature conditions ensure parthenogenetic reproduction of aphids, allowing us to maintain different aphid genotypes in the laboratory. The experimental work in this study used the LSR1-01 aphid genotype, which was collected from alfalfa (Medicago sativa) near Ithaca, NY, in 1998 and was sequenced in the pea aphid genome project (International Aphid Genomics Consortium, 2010). This line was originally collected with Regiella (strain .LSR) but was subsequently cured of facultative symbionts using antibiotics. Aphids harboring the Regiella strains used in this study were collected from a variety of locations and maintained in the laboratory asexually (Regiella strain collection information can be found in Supplementary Table S2). Note that the names of the Regiella strains used in this study are consistent with previous publications (e.g., Gerardo et al., 2010; Vorburger et al., 2010; Parker et al., 2017; Nichols et al., 2021; Wu et al., 2022).

Secondary symbiont establishment and screening

We established different strains of Regiella into LSR1-01 using microinjection (Oliver et al., 2003; McLean et al., 2011). The strains we included in this study reflect a wide range of genotypic and phenotypic variation (Supplementary Figure S1). As noted above, we included representatives of the two main phylogenetic clades of Regiella found in pea aphids and also included two nonprotective strains originally isolated from other aphid species. Across Regiella strains, there is a large amount of genomic variation. For example, there are complete genomes available for strains .LSR and .515—each has hundreds of genes missing from the other strain across a wide variety of gene categories (Hansen et al., 2012).

Donor aphids were screened for seven species of facultative bacterial symbiont species found in pea aphids. For PCR screening, we extracted DNA from whole adult aphids using “Bender” buffer with and ethanol precipitation and wash as in previous studies (Bender et al., 1983), and we used PCR primers targeting each symbiont species (Supplementary Table S1; Henry et al., 2013; McLean et al., 2020; 94°C 2 min, 11 cycles of 94°C 20s, 56°C [declining 1°C each cycle] 50 s, 72°C 30 s, 25 cycles of 94°C 2 min, 45°C 50 s, 72°C 2 min, and a final extension of 72°C 5 min). None contained any secondary symbionts other than Regiella. We then attached a glass-pulled needle to a syringe and extracted hemolymph from an adult donor aphid and injected hemolymph containing Regiella from the donor lines into the thorax of 1-day-old recipient aphids (first instars). When the injected aphids became adults, we discarded the first 15 offspring, reared late birth-order offspring to adulthood, and screened them for Regiella as above. We rescreened each line for all of the facultative symbionts including Regiella before use in experiments. To assign Regiella strains to phylogenetic clades, we amplified and sequenced the murE gene as in previous studies (Henry et al., 2013; Parker et al., 2017).

Regiella density in vivo using qPCR and 16S amplicon sequencing

We used quantitative PCR (qPCR) to measure Regiella within-host density. Specifically, we amplified a gene in the Regiella genome and a gene in the aphid host genome, and we calculated density as the ratio of these values. For Regiella, we used primers that amplify a conserved region of the single-copy hrpA gene (F: CGCATTGGGAGAAAAGCCAAG; R: CCTTCCACCAAGCCATGACG) as in previous studies (Nichols et al., 2021; Parker et al., 2021). For the aphid host gene, we amplified glyceraldehyde-3-phosphatedehydrogenase (g3PDH; ACYPI009769; F: CGGGAATTTCATTGAACGAC; R: TCCACAACACGGTTGGAGTA) as in previous work (Nichols et al., 2021). We improved on previous methods (which used a relative C_T approach) by generating qPCR standards for both genes by cloning the target amplicons into One Shot TOP10 competent E. coli cells using the TOPO TA cloning kit with pCR 2.1 vector and extracting amplified plasmids using the GE Healthcare illustra plasmidPrep Mini Spin Kit under recommended conditions. The cloned fragments were sequenced with M13F primer for confirmation and quantified using a nanodrop (NanoDrop 2000 Thermo Scientific). We then included a 1:5 serial dilution ranging from 1.6 × 10⁷ to 5.12 × 10³ copies of the plasmid on each plate, which allowed us to measure the absolute number of copies of hrpA and g3PDH in each reaction. We then calculated Regiella density by taking the ratio of Regiella to host cells using the ratio of hrpA to g3PDH copies. To analyze variation in Regiella density across genotypes from qPCR data, we performed a nonparametric ANOVA (Kruskal–Wallis) in R v.4.0.2 using the kruskal.test function (relative density deviated significantly from a normal distribution). We performed a post hoc comparison of genotypes using a Dunn test in the FSA package (Ogle et al., 2022).

We then used 16S amplicon sequencing to measure the relative abundance of Regiella across lines as a second, independent method for estimating density. We extracted DNA from aphids from each line as above and amplified the V4 region of the bacterial 16S gene using primers 515F: GTGCCAGCMGCCGCGGTAA and 806R: GGACTACHVGGGTWTCTAAT. Amplicons were then sequenced on an Illumina Hi-seq with PE 250bp sequencing, aiming for approximately 30,000 reads per sample. Reads were analyzed using Mothur (Schloss et al., 2009) implemented in Galaxy (Hiltemann et al., 2019), using SILVA Release 132. The relative abundance of Regiella for each sample was calculated as the fraction of Regiella reads relative to the total number of reads. Regiella density measured by qPCR and 16S amplicon sequencing was compared using a Spearman’s rank correlation test, implemented in R v.4.0.2 with the cor.test function (method = “spearman”).

Host immune gene expression

We extracted RNA by first removing embryos from pooled groups of four adult aphids from four biological replicates of aphids infected with each symbiont genotype. We removed the embryos from adult aphids to measure gene expression of the adult aphid without including RNA from her embryos, as in previous studies (Nichols et al., 2021). We used Trizol and chloroform with an isopropanol precipitation and ethanol wash to isolate RNA, followed by the Zymo RNA Clean & Concentrator kit with gDNA wipeout with DNase I. We then used the iScript cDNA synthesis kit from Zymo to convert RNA to cDNA under recommended conditions.

We used primers that amplified 80–120 bp of two target immune genes of interest (PO1: ACYPI004484 and hemocytin: ACYPI003478) designed in a previous study (Nichols et al., 2021). For endogenous controls, we used two genes (glyceraldehydes-3-phosphate dehydrogenase (g3PDH): ACYPI009769 and 60S ribosomal protein L32 (rpl32): ACYPI000074). Concentrations of each primer pair were optimized against a 1:10 serial dilution of gDNA (200–0.2 ng gDNA per reaction) to an efficiency of 100 ± 10% (PO1: 100 nM; hemocytin: 100 nM; g3PDH: 400/350 nM F/R; and rpl32: 200 nM). Reactions were run on a CFX96 Real-Time System machine (Bio-Rad), with an initial step of 95°C for 3 min and 40 cycles of 95°C for 10 s and 60°C for 30 s. We ran three 20-μl technical replicates, each of which included a 1× PCR buffer, Mg²⁺ at 2 mM, dNTPs at 0.2 mM, EvaGreen at 1×, 0.025 units/μL of Invitrogen taq, and 40 ng of cDNA. We analyzed the effects of symbiont genotype on the expression levels of each gene using linear models in R v.4.0.2, with genotype as a fixed effect. We then compared expression in each aphid line harboring Regiella with symbiont-free aphids using post hoc comparisons (corrected for multiple comparisons) with the “multcomp” package (Hothorn et al., 2008).

To measure correlations between immune gene expression and symbiont density, we calculated the average −ΔΔC_T value for PO and for hemocytin for each genotype of Regiella (the amount each gene was downregulated compared with symbiont-free aphids), and we measured the correlation between these values and symbiont density (based on qPCR data) using the cor.test function in R v.4.0.2 (method = “pearson”).

Strain-specific Regiella detection

We designed primers that targeted strain-level variation in the hrpA gene among Regiella genotypes. Each primer pair amplified only one of two strains (genotype .LSR [F: 5ʹ-GCCCGTTTTGCTGTTTTCCC-3ʹ R: 5ʹ-AAAAGCATGGCTGGTTTGCC-3ʹ] or genotype .313 [F: 5ʹ-GCCCGTTTCGCTATTTTCCC-3ʹ R: 5ʹ-AAAAACGTGACGGGTTTGCC-3ʹ]), with PCR conditions of 95°C 2 min, 30 cycles of 95°C 30 s, 65°C 30 s, 68°C 50 s, and a final extension of 68°C 5 min. We verified that these primers were strain specific and could detect Regiella coinfections at up to a 1:99 dilution of DNA mixed from the two strains (Supplementary Figure S2).

Coinfection assay

We created coinfections of aphids with two strains of Regiella (.313 and .LSR). In our study, there was a 3.5× fold difference in density between these strains, but this difference was not statistically significant in our post hoc analysis (Figure 1A, Supplementary Table S3). However, the density of strains .LSR and .313 was found to be statistically significant in a previous study focusing on the effects of these Regiella strains on the aphid transcriptome (Nichols et al., 2021). Furthermore, the .LSR Regiella strain is widely used in the literature and there is a complete and annotated genome for this strain (International Aphid Genomics Consortium, 2010), and we therefore elected to use this strain for further study. We performed microinjections as above from an adult donor aphid to a 1- to 2-day-old aphid with an existing infection of the other genotype of Regiella (.LSR injected into aphids already harboring .313: N = 18 and .313 injected into aphids already harboring .LSR: N = 15) to create a coinfection with both genotypes. We injected the same volume of hemolymph from donor aphids into each recipient, which means that the number of bacteria injected into recipients differed between .LSR and .313 injections. We therefore also included injections of each strain of Regiella into control (uninfected) aphids in the experiment (.LSR injections: N = 22; .313 injections: N = 22). At each generation after injection (the first through eighth generations), we collected a single adult aphid from the cage and tested it for both strains of Regiella using the genotype-specific primers described above. Each aphid was determined to have an infection of Regiella genotype .LSR, Regiella genotype .313, a coinfection with both genotypes, or no detectable Regiella infection.

We analyzed these data using generalized linear mixed-effects models with the lme4 package in R v.4.0.2 (Bates et al., 2015). We assessed symbiont maintenance across the experiment, with the presence or absence of the injected symbiont strain as the dependent variable (modeled as a binomial outcome as determined by the presence or absence of PCR amplification). We included two factors and their interaction as fixed effects in the model: the strain of the injected symbiont (strain .LSR from “clade 1” or strain .313 from “clade 2”) and the background of the recipient aphid (i.e., whether it had a preexisting Regiella of the opposite strain or symbiont free). We included generation and experimental replicate as random effects. We built minimal models first by removing the interaction term, then aphid background, and then symbiont strain, and we determined statistical significance through model comparisons using ANOVA and chi-squared tests.

Results

Symbiont density

We found significant variation in the relative density of Regiella strains (Kruskal–Wallis χ² = 28.5, df = 6, p < .0001), with the ratio of Regiella/host cells in each aphid ranging from 0.3 to 14.8 (Figure 1A). Specifically we found that three Regiella strains were established at statistically significantly higher densities than strain .515, and strain .313 was established at a significantly higher density than strain .Md10 (post hoc tests at p < .05; Supplementary Table S3; Figure 1A).

In our 16S amplicon sequencing data, between 8.8% and 73% of mapped reads in our samples were identified as Regiella across samples, with the remainder of reads coming mainly from the aphid primary symbiont Buchnera aphidicola (Figure 1B). The rank order of Regiella/host relative abundance measured by qPCR and Regiella/total microbial abundance measured by 16S differed significantly (S = 12, p = .048), with the difference coming from strain .RR5. The rank order of the other six strains used in the study was the same between the two approaches to measuring density. It is unclear what is causing this difference in measurement for strain .RR5. One possibility is that there could be interactions between Regiella and the primary symbiont Buchnera, for example, if they are competing for space within the specialized cells (bacteriocytes) that harbor aphid symbionts. Because 16S data only provide the relative abundance of different microbes, estimates of Regiella density from 16S data could be influenced by differences in Buchnera density across lines. This issue makes measurements based on relative abundance using 16S less reliable than qPCR in our estimation.

Immune gene expression

Symbiont strain had a significant effect on Phenoloxidase 1 (ACYPI004484) expression (F = 33.9, df = 7, p < .0001; Figure 1C), with genotypes .313, .CF7, .meliA18, and .LSR significantly decreasing expression relative to symbiont-free aphids (Supplementary Table S4, Figure 1C). Similarly, Regiella influenced hemocytin (ACYPI003478) expression (F = 19.1, df = 7, p < .0001; Figure 1D), with .313, .CF7, .meliA18, and .Md10 significantly decreasing expression (Supplementary Table S5, Figure 1D).

Regiella density was negatively correlated with expression of Phenoloxidase 1 (t = 3.18, df = 5, p = .025; Figure 1E) and with expression of hemocytin (t = 2.92, df = 5, p = .033; Figure 1F). Higher-density Regiella strains were associated with larger decreases in PO1 and hemocytin expression (relative to uninfected aphids).

Coinjection experiments

We found that the effect of symbiont genotype did not influence establishment success (χ² = 2.1, df = 1, p = .15), but whether a host already contained a Regiella strain had a strong impact on whether injected symbionts could establish in a host (χ² = 37.7, df = 1, p < .0001). Importantly, there was a significant interaction between Regiella genotype and whether recipients already harbored the other strain of Regiella (χ² = 9.3, df = 1, p = .0023). Most replicates of strain .LSR Regiella were unable to establish in aphids already harboring strain .313 Regiella, with most lines losing strain .LSR at generation 2 after injection (Figure 2, top). Strain .313 Regiella, in contrast, were largely able to establish in aphids that already harbored a strain .LSR infection and persisted throughout the experiment in a coinfection (Figure 2, bottom). Note that at each generation, a single aphid from each host plant was harvested at random for DNA extraction and PCR screening—lines can therefore appear to “regain” a symbiont across generations due to individual differences among aphids on a plant (Figure 2).

Discussion

We measured within-host density of multiple Regiella strains and the effects of each strain on the expression levels of two host immune genes. We found significant variation in density among Regiella genotypes (Figures 1A and B), with the relative Regiella to host cell ratio varying across several orders of magnitude. We also found that Regiella strains vary in the extent to which they suppress the expression of two host immune genes (Figures 1C and D) and that stronger suppression is correlated with higher symbiont densities across Regiella strains (Figure 1E and F). The aphid immune system has been implicated in the regulation of vertically transmitted symbioses in several studies, with Regiella and another aphid facultative symbiont (Hamiltonella defensa) leading to decreased expression of key insect innate immune system genes and fewer circulating immune cells (Kaech et al., 2021; Luo et al., 2020; Nichols et al., 2021; Schmitz et al., 2012). It has also been shown previously that knocking down the expression of Phenoloxidase using RNAi leads to increased Regiella density over aphid development (Nichols et al., 2021). Together these studies point to a potential mechanism for strain-level variation in Regiella density, namely that strains might reach higher densities within hosts by more strongly suppressing host immune mechanisms. An important caveat of our study is that we used two strains that were collected from other aphid species (strain .515 from M. persiace and .RR5 from D. noxia). It is possible that these strains could establish at different within-host densities and/or have different effects on host immune gene expression in their original host species. Along these lines, strain .RR5 was able to establish at relatively high densities in its non-native pea aphid host but had no effect on immune gene expression. Interactions with PO and hemocytin are therefore not the only factors influencing Regiella density in this system.

Harboring Regiella can be costly for hosts, and higher-density symbiont infections (due to both host and symbiont genotype) impose stronger survival costs on aphids (Parker et al., 2021). One possibility is that despite the survival costs, high-density strains might still be beneficial for host aphids because they provide stronger protection against natural enemies. However, previous studies have found that protection against fungal pathogens is highly genotype by genotype dependent (a pattern which also extends to other aphid symbionts interacting with parasitoid wasps [Rouchet & Vorburger, 2014; McLean & Godfray, 2015])—specifically, lower-density “clade 1” Regiella strains provide stronger protection against some fungal genotypes than higher-density “clade 2” strains and vice versa. There is also no evidence that symbiont density and fungal protection are correlated across host genetic variation (Parker et al., 2021). Multiple studies therefore suggest that higher-density Regiella infections are not beneficial for host aphids.

Another possibility is that density influences transmission, as is the case in other systems (Unckless et al., 2009). Here we found that a higher-density strain (.313) and a lower-density strain (.LSR) persisted equally well in single infections across eight aphid generations (Figure 2). Anecdotally, we have also been able to maintain lower-density strains like .515 without loss of the symbiont over many years in the laboratory. However, aphid heritable symbionts exist in complex communities of multiple microbial species, and coinfections of different strains of Regiella have been found in the field (Guyomar et al., 2018). We found that Regiella strains differed in their ability to persist in coinfections. When the lower-density strain .LSR was injected into aphids already harboring strain .313, the injected symbiont was quickly lost from aphid lines. In contrast, the higher-density strain .313 was able to establish and persist as a coinfection in aphids already harboring strain .LSR. These data suggest that one potential advantage of establishing at high density within hosts is the ability to persist in coinfections within complex microbial communities and, more broadly, that within-host dynamics might contribute to the evolution of microbial densities in heritable symbioses. Importantly, we measured the outcomes of coinfections in only one host genetic background. An interesting possibility is that host genotype could influence the outcome of competition between strains of heritable symbionts. In addition, future studies are needed to link the patterns we measure in our laboratory study with field dynamics of strains in natural populations. More generally, studies across study systems are needed to determine the role of symbiont density in interactions among different symbiont species and the potential role of symbiont density in horizontal transmission.

These results fit well with other recent studies on symbiont density that have emphasized the importance of within-host dynamics on symbiont evolution. A recent experimental evolution study of Wolbachia infections in Drosophila, for example, did not find any reduction of symbiont density or in the fitness costs of symbionts to hosts across 17 generations of laboratory conditions expected to select for reduced symbiont virulence (Monnin et al., 2020). The authors speculate that within-host pressures select for symbionts with higher density despite the increased cost to hosts (Chrostek & Teixeira, 2018; Monnin et al., 2020; Parker, 2021). Together these studies suggest that vertically transmitted symbionts are subject to the same tradeoffs between virulence and transmission that shape host–pathogen coevolutionary dynamics, and they stress the critical importance of within-host dynamics in the evolution of vertically transmitted symbioses.

Data availability

Raw data was uploaded to Dryad with doi:10.5061/dryad.4f4qrfjhd (Goldstein et al., 2023).

Author contributions

E.B.G., L.M.H., and B.J.P. conceived of the project. E.B.G. and B.J.P. wrote the manuscript. E.B.G. and Y.d.A.A. carried out the experiments and molecular work. L.M.H. and B.J.P. contributed reagents, materials, and funding for the project. All authors edited the manuscript and approved the final version for submission.

Funding

This work was funded by U.S. National Science Foundation (NSF) Grant IOS-2152954 to B.J.P. and by BBSRC grant BB/W001632/1 to L.M.H. B.J.P is a Pew Scholar in the Biomedical Sciences, funded by the Pew Charitable Trusts.

Conflict of interest

The authors declare no conflict of interest.

Acknowledgments

Keertana Tallapragada and Will Brewer provided valuable assistance with the aphid rearing.

References