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Article

Host-Dependent Variation in Tetranychus urticae Fitness and Microbiota Composition Across Strawberry Cultivars

by
Xu Zhang
1,2,
Hongjun Yang
1,2,
Zhiming Yan
1,2,
Yuanhua Wang
1,2,
Quanzhi Wang
1,2,
Shimei Huo
1,2,
Zhan Chen
3,4,
Jialong Cheng
1,2 and
Kun Yang
3,4,*
1
College of Agronomy and Horticulture, Jiangsu Vocational College of Agriculture and Forestry, Zhenjiang 212400, China
2
Jiangsu Engineering and Technology Center for Modern Horticulture, Zhenjiang 212400, China
3
Shandong Province Centre for Bioinvasions and Eco-Security, Qingdao Agricultural University, Qingdao 266109, China
4
Shandong Engineering Research Center for Environment-Friendly Agricultural Pest Management, College of Plant Health and Medicine, Qingdao Agricultural University, Qingdao 266109, China
*
Author to whom correspondence should be addressed.
Insects 2025, 16(8), 767; https://doi.org/10.3390/insects16080767
Submission received: 28 May 2025 / Revised: 20 July 2025 / Accepted: 21 July 2025 / Published: 25 July 2025
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Simple Summary

This study investigates how different strawberry cultivars affect the fitness and bacterial microbiota of the two-spotted spider mite, Tetranychus urticae. The research found that mites reared on the ‘Xuetu’ cultivar exhibited the highest fecundity, while those on ‘Xuelixiang’ had the shortest pre-adult development time. Additionally, ‘Xuelixiang’, ‘Xuetu’, and ‘Ningyu’ cultivars supported longer mite longevity compared to others. Microbiota analysis revealed that Wolbachia was the predominant bacterium across all mite groups, with varying abundances of other bacteria like Pedobacter and Virgibacillus depending on the strawberry cultivar. Notably, male mites exhibited higher bacterial diversity than females. These findings suggest that strawberry cultivar selection can influence mite fitness and microbiota composition, providing insights for developing integrated pest management strategies.

Abstract

Tetranychus urticae, commonly known as the two-spotted spider mite, is a highly adaptable and polyphagous arthropod in the family Tetranychidae, capable of feeding on over 1200 plant species, including strawberries (Fragaria × ananassa Duch.). The fitness and microbiota of herbivorous arthropods can vary significantly across different plant species and cultivars. In this study, we investigated the fecundity, longevity, growth rate, and microbiota composition of T. urticae reared on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Our findings revealed significant differences among cultivars: mites reared on the XT cultivar exhibited the highest fecundity (166.56 ± 7.82 eggs), while those on XLX had the shortest pre-adult period (7.71 ± 0.13 days). Longevity was significantly extended in mites reared on XLX, XT, and NY cultivars (25.95–26.83 days). Microbiota analysis via 16S rRNA sequencing showed that Proteobacteria dominated (>89.96% abundance) across all mite groups, with Wolbachia as the predominant symbiont (89.58–99.19%). Male mites exhibited higher bacterial diversity (Shannon and Chao1 indices) than females, though Wolbachia abundance did not differ significantly between sexes or cultivars. Functional predictions highlighted roles of microbiota in biosynthesis, detoxification, and energy metabolism. These findings underscore the influence of host plant variety on T. urticae fitness and microbiota composition, suggesting potential strategies for breeding resistant strawberry cultivars and leveraging microbial interactions for pest management.

1. Introduction

Tetranychus urticae Koch (Acari: Tetranychidae), commonly known as the two-spotted spider mite, is a highly adaptable and polyphagous arthropod in the family Tetranychidae. This mite is capable of feeding on over 1200 plant species across more than 140 different plant families, including numerous crops and ornamental species [1,2]. It is considered one of the most economically significant pests due to its capacity to cause severe damage to plants through direct feeding [3]. Its rapid reproduction rate and ability to quickly develop resistance to pesticides complicate control efforts [4,5]. The mite’s ability to survive in diverse environments contributes to its global distribution.
Bacterial microbiota in arthropods refers to the diverse communities of bacteria residing within or on insect hosts, engaging in symbiotic relationships that range from mutualistic to parasitic. These microbiota are integral to various physiological, ecological, and evolutionary processes, influencing arthropod health, behavior, and adaptation [6,7,8,9]. Microbiota are vital for the growth, resistance, reproductive manipulations, and host adaptation of arthropods. For instance, in aphids, the primary symbiont Buchnera (an obligate endosymbiont) synthesizes essential amino acids missing in phloem sap [10], while Wolbachia-infected mosquitoes show elevated basal immunity and dramatically reduced dengue virus replication [7]. In Drosophila, secondary symbiont Spiroplasma protects against parasitoids, and Acetobacter affects behavior [11]; in beetles, Nardonella aids detoxification, and Burkholderia confers chemical resistance [12,13]. In Bemisia tabaci (Gennadius, 1889), secondary symbiont Cardinium infection would significantly increase the thermotolerance of host whiteflies [8]. All these studies highlight the vital effects of microbiota, especially symbiont infection for host arthropods.
In spider mites, the bacterial microbiota is abundant and complex, with significant functions. A study based on five Tetranychus species found that some bacterial symbionts showed host-species specificity [9]. In Turtranychus Truncatus Ehara, mites coinfected with secondary symbionts Wolbachia and Spiroplasma had significantly higher daily fecundity and juvenile survival rates than those infected with a single bacterium or uninfected [14]. Wolbachia also induces cytoplasmic incompatibility in T. truncatus by significantly down-regulating chorion proteins S38-like and Rop [15]. Infected with a single bacterium mites or uninfected mites exhibited reduced thermotolerance [16]. In T. urticae, salivary protein SHOT1s are positively correlated with Wolbachia density and account for Wolbachia-mediated phenotypes [17].
Plants have developed various defense mechanisms against herbivorous arthropods, including spider mites, such as physical barriers and chemical responses [18]. For example, plants can raise many Si-mediated physical, biochemical, and molecular mechanisms in defense against pathogens and insect pests [19]. Plants can synthesize toxic metabolites (alkaloids, glucosinolates, cyanogenic glycosides, phenolics) and anti-digestive proteins (protease inhibitors) that impair insect growth, survival, or reproduction [20,21]. Additionally, there is an evolutionary “war” between pests and host plants; for instance, B. tabaci acquired a horizontally transferred gene (BtPMaT1) from host tomato to neutralize plant toxins [22].
Tetranychus urticae is a major pest of strawberries, yet the influence of different strawberry cultivars on its fitness and microbiota remains poorly understood. While host plant traits are known to shape herbivore performance and microbial communities in other arthropod systems [6,14,16], cultivar-specific effects on T. urticae biology and microbiome dynamics are underexplored. This study addresses this gap by systematically evaluating how strawberry varietal differences modulate mite fitness and associated bacterial symbionts, with implications for integrated pest management strategies.

2. Materials and Methods

2.1. Collection and Cultivation of Tetranychus urticae

The T. urticae population utilized in this study was collected from Jurong, Jiangsu Province, China, in November 2024. Upon arrival at the laboratory, isofemale lines were established from individual females to ensure clonal purity. Given the haplodiploid reproductive system of T. urticae, all individuals within a line are progeny of a single mother. The mites were initially reared on leaves of the ‘Hongyan’ (HY) strawberry cultivar, sourced from a local plantation in Jurong City.
Mite colonies were maintained in 90 mm Petri dishes under controlled laboratory conditions: 25 ± 1 °C, 60% relative humidity, and a 16:8 light–dark photoperiod. Fresh strawberry leaves were carefully washed, sterilized at high temperature (55 °C, 30 min), and placed on circular sponges within the dishes. The leaves were oriented with their abaxial side facing upward. Water was added to fully saturate the sponges, ensuring the water level in the dishes exceeded the sponge height. Filter paper was trimmed to cover the leaf edges. After preparation, mite-infested leaf sections were observed under a microscope, and areas with high mite density were cut and transferred for colony expansion. Labels were attached to track each colony. Water was replenished every 1–2 days, and dishes were replaced every 4–5 days.

2.2. Fitness Assessment of T. urticae on Different Strawberry Cultivars

2.2.1. Pre-Adult Development Period and Longevity

To assess the effects of various strawberry cultivars on the fitness of T. urticae, seven cultivars were selected: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). All strawberry cultivars were planted in laboratory at 25 ± 1 °C, 60% relative humidity, and a 16:8 light–dark photoperiod. For fitness assessments, mites were transferred to each of the seven test cultivars (HY, YX, TS, NY, XT, ZJ, XLX) and reared for two complete generations to record the fecundity, pre-adult period and longevity of spider mites. The fecundity, pre-adult period and longevity-tested mites were F2 offspring reared exclusively on their respective test cultivar. This ensured physiological adaptation to cultivar-specific traits before measurements. Experiments were conducted in an incubator maintained at 25 °C and 80% relative humidity. Leaves from the same nodal position of each cultivar were selected, inspected under a microscope, and cleaned of pests and predators using a soft brush. Each Petri dish was divided into four sectors using paper strips. One female mite and 2–3 male mites were placed in each sector. After oviposition, adults were removed, and egg hatching was monitored. Post-hatching, daily observations recorded mite lifespan, encompassing both nymphal and adult stages.

2.2.2. Fecundity Assessment

To evaluate the fecundity of T. urticae on different strawberry cultivars, experiments were performed under identical environmental conditions (25 °C, 80% relative humidity). Leaves were prepared as described above. Each Petri dish was divided into four sectors, with six replicate dishes per treatment group. One quiescent deutonymph-stage female and 2–3 male mites were introduced into each sector. Daily egg production was recorded starting from the first oviposition event.

2.3. Microbiota Analysis of T. urticae on Different Strawberry Cultivars

The bacterial microbiota of 1-day-old female and male T. urticae adults reared on four strawberry cultivars (TS, HY, FY, and YX) were analyzed using 16S rRNA gene sequencing, as the four cultivars were most widely grown commercial varieties in China, especially in Jiangsu Province. Each sample including 20 female/male spider mite adults. Genomic DNA was extracted from samples using the OMEGA Soil DNA Kit (M5635-02) (Omega Bio-Tek, Norcross, GA, USA), adhering to the manufacturer’s protocol. DNA concentration and purity were assessed using a NanoDrop NC2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA), with A260/A280 ratios confirming protein-free extracts, while integrity was verified via 1% agarose gel electrophoresis.
For bacterial 16S rRNA gene sequencing, nearly full-length amplicons (~1500 bp) were generated using primers 27F (5′-AGAGTTTGATCMTGGCTCAG-3′) and 1492R (5′-ACCTTGTTACGACTT-3′) in a two-step PCR process. The first PCR step included 25 cycles to amplify target regions, followed by a second 10-cycle PCR to incorporate 16 bp sample-specific barcodes. Reaction mixtures contained 5 μL Q5 reaction buffer (5×), 5 μL Q5 High-Fidelity GC buffer (5×), 0.25 μL Q5 DNA Polymerase (5 U/μL), 2 μL dNTPs (2.5 mM), 1 μL each primer (10 μM), 2 μL DNA template, and 8.75 μL ddH2O. Thermal cycling conditions were: 98 °C for 2 min (initial denaturation), followed by 25/10 cycles (first/second PCR) of 98 °C for 30 s, 55 °C for 30 s (annealing), and 72 °C for 90 s (extension), with a final 5 min extension at 72 °C. Amplicons were purified using Agencourt AMPure Beads (Beckman Coulter, Lane Cove West, NSW, Australia), quantified via PicoGreen dsDNA Assay, and pooled equimolarly for Single Molecule Real-Time (SMRT) sequencing on the PacBio Sequel platform. Circular consensus sequencing (CCS) was employed to minimize errors, generating high-accuracy reads (≥3 passes, ≥99% predicted accuracy). Raw sequences were processed using SMRT Link (v5.0.1.9585), trimmed to ≤2000 bp, and filtered to exclude low-quality reads.
Bioinformatic analysis was conducted in QIIME2 (2022.11). Demultiplexed reads were primer-trimmed with Cutadapt, denoised via DADA2, and aligned using MAFFT to generate amplicon sequence variants (ASVs). A phylogenetic tree was constructed with FastTree2, and taxonomy was assigned against the SILVA 138 (bacteria)databases. Alpha diversity metrics (Chao1, Shannon, Simpson, Faith’s PD) and beta diversity (Bray–Curtis, weighted/unweighted UniFrac) were calculated after rarefaction. Community structure differences were visualized via PCoA, NMDS, and UPGMA clustering, with statistical validation using PERMANOVA, ANOSIM, and LEfSe. Machine learning approaches, including Random Forest (5-fold cross-validation) and OPLS-DA, identified discriminative taxa. Co-occurrence networks were built using SparCC (pseudocount = 10−6, correlation cutoff = 0.7) and visualized with igraph. Functional profiling leveraged PICRUSt2 to predict metabolic pathways against MetaCyc and KEGG databases. All analyses were performed in R (v3.2.0) with packages like phyloseq and vegan, ensuring reproducibility and statistical rigor. While the data of fecundity and pre-adult period of T. urticae reared on different strawberry cultivars were first tested for normality (Kolmogorov—Smirnov test) and homogeneity of group variances (Levene’s test). As the fecundity data follows a normal distribution, they were analyzed with a one-way ANOVA with posthoc Tukey HSD analysis. Pre-adult period data do not follow a normal distribution; the data were ‘transformed with
y = l o g 10 ( x )
to make sure the data follow a normal distribution, and then the data of pre-adult period were analyzed with a one-way ANOVA with posthoc Tukey HSD analysis. The longevitiy (survival assay) of T. urticae reared on different strawberry cultivars was compared by the Kaplan–Meier method. SPSS 19 (IBM, Armonk, NY, USA) was used to carry out all statistical tests.

3. Results

3.1. Tetranychus urticae Fitness on Various Strawberry Cultivars

The fitness parameters of T. urticae were assessed on seven strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Among these, XT and NY cultivars supported the highest fecundity, with an average of 166.56 eggs per female, significantly surpassing all other cultivars (One-Way ANOVA, p < 0.05) (Figure 1).
The pre-adult periods of T. urticae reared on different cultivars were compared (Figure 2). Based on the results, pre-adult period of T. urticae reared on XLX breed (7.71 ± 0.13 days, Mean ± SEM) was significantly shorter than those reared on TS (10.11 ± 0.24, Mean ± SEM), XT cultivars (9.25 ± 0.37 days) and NY cutivars (9.00 ± 0.42 days) (One-Way ANOVA, p < 0.05).
Based on Log-rank (Mantel–Cox) test, for longevity of T. urticae reared on different cultivars, results showed that longevity of T. urticae reared on strawberry cultivars XLX (25.95 ± 1.39, Mean ± SEM), XT (26.83 ± 0.87) and NY (26.83 ± 1.03) were significantly longer than that of T. urticae reared on other strawberry cultivars (Figure 3).

3.2. Tetranychus urticae Bacterial Microbiota Changed in Various Strawberry Cultivars

3.2.1. Sequencing Data of Bacterial Microbiota in Tetranychus urticae

The bacterial microbiota of 1-day-old female and male T. urticae adults reared on 4 strawberry breeds (including TS, HY, FY and YX) were measured by 16s rRNA gene sequencing. Based on results, in different T. urticae samples reared on various strawberry cultivars, the ASVs (amplicon sequence variants) numbers ranged from 9454 to 15,975, and the denoised ASVs numbers ranged from 9369 to 15,942, all T. urticae samples including total 9 bacterial phyla, all samples ranged from 2 to 6 bacterial phyla, 4 to 38 bacterial species (Table 1). Based on Principal Coordinates Analysis (PCoA) all samples from different growth stages clustered together, which showed insignificant influence of different T. urticae groups reared on various strawberry cultivars on structures of microbiota, except for YXF group (Figure S1). For the top 19 bacterial genera of T. urticae, most bacterial genera were related to phyla Proteobacteria, Firmicutes and Actinobacteria (Figure 4).

3.2.2. Bacterial Communities in Tetranychus urticae Reared on Different Strawberry Cultivars

Based on 16s rRNA gene sequencing, in T. urticae, Proteobacteria bacteria occupy the largest proportion (over 89.96% in all groups) of the total bacteria abundance across all T. urticae groups reared on different strawberry cultivars, while Bacteroidetes bacteria are the second most abundant (Figure S2). Regarding bacterial species, the secondary symbiont, Wolbachia symbiont of T. urticae, is the most dominate bacterium, occupying more than 89.58% of the bacterial abundance in all T. urticae groups. Pedobacter sp. An13 and Virgibacillus halodenitrificans are abundant in some T. urticae groups reared on different strawberry cultivars (Figure 5). For Wolbachia, although the proportions varied in T. urticae groups reared on different strawberry cultivars ranged from YXF group (89.58 ± 3.82%, Mean ± SEM) to TSF (99.19 ± 0.28%), there were no significant differences among all T. urticae groups (Kruskal–Wallis test, p = 0.074) (Figure S3A), the Wolbachia proportion of male adults (94.02 ± 1.31%) was not significantly different than that of female adults (96.55 ± 1.38%) (Student’s t-test, t = −1.331, df = 30, p = 0.19) (Figure S3B).

3.2.3. Bacterial Microbiota Varied in Tetranychus urticae Reared on Different Strawberry Cultivars

The bacterial diversity across T. urticae reared on different strawberry cultivars was assessed using 16S rRNA gene sequencing. In total, the diversity index of male adults were significantly higher than that of female adults (Figure S4). Shannon index of male adults were significantly higher than that of female adults (Student’s t-test, t = 2.655, df = 30, p < 0.05), similar results detected in Chao1 index, as Chao1 index of T. urticae male adults were significantly higher than that of female adults (Student’s t-test, t = 3.376, df = 30, p < 0.01), while the Simpson index between T. urticae male and female adults were not significantly different (Student’s t-test, t = 3.376, df = 30, p = 0.12) (Figure S4).
As for diversity index of T. urticae on different strawberry cultivars, for Shannon indexes, the analysis revealed that the HYM group (0.69 ± 0.23, Mean ± SEM) and YXM group (0.69 ± 0.25) were significantly higher than that of TSF, HYF, FYM and FYF groups (Figure 6A). For Simpson indexes, the analysis revealed that the YXF group (0.18 ± 0.06), HYM group (0.16 ± 0.06) and YXM group (0.15 ± 0.06) were significantly higher than that of TSF and FYF groups (Figure 6B). For Chao1 indexes, the analysis revealed that the TSM group (30.13 ± 9.88), HYM group (30.77 ± 3.76) and YXM group (30.12 ± 8.78) were significantly higher than that of TSF and FYF groups (One-Way ANOVA, p < 0.05) (Figure 6C).
Based on bacterial microbiota function prediction results, most bacterial genes were related to Biosynthesis, while other bacterial genes were related to Degradation/Utilization/Assimilation, Detoxification, Generation of Precursor Metabolites and Energy, Glycan Pathways, Macromolecule Modification and Metabolic Clusters (Figure 7).

4. Discussion

The two-spotted spider mite, T. urticae, is a formidable pest with rapid reproductive rates and adaptive plasticity, enabling it to exploit diverse host plants. This study reveals critical impacts of strawberry cultivar variation on T. urticae biology. We demonstrate that cultivar traits significantly modulate (i) mite fitness parameters and (ii) associated bacterial microbiota composition. These findings provide actionable insights for developing integrated pest management (IPM) strategies.

4.1. Influence of Strawberry Cultivars on T. urticae Fitness

The observed variations in fecundity, development time, and longevity of T. urticae across different strawberry cultivars highlight the role of host plant characteristics in shaping pest biology. Notably, mites reared on the XT variety exhibited the highest fecundity, while those on the XLX variety had the shortest pre-adult period. These differences may be attributed to the varying nutritional profiles and secondary metabolite compositions of the cultivars, which can affect mite development and reproduction [23,24,25,26]. In western flower thrips Frankliniella occidentalis Pergande reared on different Rosa chinensis Jacq. cultivars, which F. occidentalis showed digestive enzyme activities in various cultivars [26]. Our findings also aligned with previous research indicating that plant genotype can influence herbivore performance through mechanisms like antibiosis, where plant compounds adversely affect pest biology [27].

4.2. Microbiota Composition and Its Modulation by Host Plants

The dominance of Proteobacteria, particularly Wolbachia, across all mite groups suggests a stable core microbiota in T. urticae, which results were consistent to other related research [28,29,30]. However, the presence of other bacterial taxa, such as Pedobacter and Virgibacillus, varied among mites reared on different cultivars, indicating that host plant species can modulate the peripheral microbiota, microbiota diversities also varied in T. urticae reared on different strawberry cultivars. This modulation may result from differences in plant chemistry, which can influence microbial acquisition and retention [31,32,33]. For example, host plants not only affected the biological characteristics and nutritional metabolism of pea aphids but also regulated the symbiotic density [34]. A secondary metabolite from cotton, Gossypol, suppressed Buchnera populations in cotton-melon aphid, Aphis gossypii [35]. The difference in plant chemistry among different strawberry cultivars may cause the changes in microbiota in T. urticae, which should be further explored. The role of Wolbachia in enhancing host detoxification pathways and conferring pesticide resistance has been documented [30]. Wolbachia thus serves as a foundational detoxifier, while cultivar-driven changes in ancillary bacteria may augment or impair this function. Resistant cultivars could exploit this by simultaneously challenging Wolbachia and disrupting supportive microbiota.
Functional profiling via PICRUSt2 predicted potential roles of the mite microbiota, primarily in biosynthesis, with secondary involvement in detoxification and energy metabolism (Figure 7). However, these inferences carry inherent limitations: Recent evaluations confirm that 16S-based functional tools (including PICRUSt2) lack sensitivity to detect biologically meaningful metabolic shifts due to incomplete reference databases and inability to resolve strain-level functions [36]. Thus, while these predictions hypothesize microbiota contributions to mite adaptation (e.g., detoxifying cultivar-specific plant compounds), they require validation. We advocate for metatranscriptomic/metabolomic approaches in future work to directly quantify microbial functions in T. urticae.

4.3. Sex-Based Differences in Microbial Diversity

The higher bacterial diversity observed in male mites compared to females raises questions about sex-specific interactions between T. urticae and its microbiota. These differences could stem from variations in behavior, physiology, or immune responses between sexes, which in turn affect microbial colonization and maintenance [37,38,39,40]. Understanding microbiota dynamics is crucial because cultivar-driven shifts correlate with fitness outcomes (Figure 1, Figure 2, Figure 3, Figure 5 and Figure 6), and predicted functions (e.g., detoxification; Figure 7) align with known symbiont roles in T. urticae [28,29,30]. While future studies should quantify enzymatic/metabolic consequences, our work establishes host plant variety as a key modulator of mite-microbiota functional interactions.

4.4. Implications for Integrated Pest Management

The study’s findings have practical implications for developing sustainable pest management strategies. By identifying strawberry cultivars that significantly reduce T. urticae fitness (e.g., ‘Tianshi’ prolonging development by 31% and ‘Zhangji’ reducing fecundity vs. ‘Xuetu’), breeders can prioritize these varieties to mitigate pest damage. Furthermore, host plants concurrently altered mite microbiota composition (Figure 5 and Figure 6), suggesting that cultivars favoring disadvantageous microbial shifts could synergistically enhance resistance—though causal links require experimental validation.
Separately, targeting conserved symbionts like Wolbachia (89–99% abundance) may offer control avenues, given its established roles in pesticide detoxification [30] and reproduction [17] in spider mites. By targeting Wolbachia, researchers could offer novel avenues for controlling mite populations [40,41,42]. Such approaches align with IPM principles, combining host resistance, biological tools, and targeted interventions.

4.5. Future Research Directions

Further studies are needed to elucidate the mechanisms underlying the interactions between host plants, T. urticae, and its microbiota. Investigating the functional roles of specific microbial taxa and their contributions to mite physiology and adaptability will enhance our understanding of these complex relationships. Additionally, exploring the potential for microbiota manipulation as a pest control strategy warrants attention, particularly in the context of developing resistance management programs.
In conclusion, this study tested and confirmed that strawberry cultivar traits significantly alter T. urticae fitness, and further demonstrate that these fitness differences correlate with host plant-induced microbiota shifts, evidenced by: (i) Microbiota diversity reductions in mites from poor-performance cultivars (Figure 6). (ii) Conserved Wolbachia dominance alongside cultivar-sensitive taxa (Figure 5). (iii) Predicted microbial functions mirroring fitness trends. These findings objectively inform breeding programs and reveal microbiota as a testable target for integrated pest management.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/insects16080767/s1, Figure S1. Beta diversity analysis of bacterial communities of Tetranychus urticae reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX), by 16s rRNA gene sequencing, the results of PCoA analysis was shown. Figure S2. Relative abundance of top 10 bacterial phylum in Tetranychus urticae 1-day-old male/female adults on 4 Chinese strawberry cultivars Tianshi (TS), Hongyan (HY), Ningyu (NY), Fenyu (FY) and Yuexiu (YX), by full-length 16s rRNA gene sequencing. In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male. Figure S3. Wolbachia proportions in bacterial communities in 1-day-old male and female Tetranychus urticae adults reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX). In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male. ns: no significant difference. Figure S4. Alpha diversity indices of bacterial communities in 1-day-old male and female Tetranychus urticae adults reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX). The diversity metrics presented include Shannon (A), Simpson (B), and Chao1 (C) indices. In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male.

Author Contributions

Conceptualization, X.Z., H.Y. and K.Y.; methodology, H.Y., K.Y. and Z.Y.; software, Y.W., S.H. and K.Y.; validation, Z.C., X.Z. and K.Y.; formal analysis, H.Y., Y.W. and K.Y.; investigation, J.C., Z.C. and X.Z.; resources, X.Z.; data curation, Y.W., H.Y. and K.Y.; writing—original draft preparation, Y.W., Q.W. and K.Y.; writing—review and editing, X.Z., K.Y., H.Y. and Q.W.; visualization, Q.W., H.Y. and K.Y.; supervision, X.Z., Q.W. and K.Y.; project administration, X.Z., Y.W. and K.Y.; funding acquisition, H.Y., X.Z. and K.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Science Fund of the Jiangsu Vocational College of Agriculture and Forestry (2021kj39), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (21KJB210012), the Qingdao Agricultural University High-Level Talent Fund (663-1121025), the Yafu Technology Innovation Team (2024kj02) and the Key Research Projects of Jiangsu Vocational College of Agriculture and Forestry (2023kj14).

Data Availability Statement

Sequence data that support the findings of this study have been deposited in the NCBI with the primary accession code SUB15348674.

Acknowledgments

The authors would like to thank all the editors and reviewers for the modifications and suggestions regarding the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Insects 16 00767 g001
Figure 1. Fecundity of Tetranychus urticae on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Different letters indicate significant differences as determined by One-Way ANOVA (p < 0.05).
Figure 1. Fecundity of Tetranychus urticae on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Different letters indicate significant differences as determined by One-Way ANOVA (p < 0.05).
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Insects 16 00767 g002
Figure 2. Log10 transformation of pre-adult periods of Tetranychus urticae on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Different letters indicate significant differences as determined by One-Way ANOVA (p < 0.05).
Figure 2. Log10 transformation of pre-adult periods of Tetranychus urticae on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Different letters indicate significant differences as determined by One-Way ANOVA (p < 0.05).
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Insects 16 00767 g003
Figure 3. Survivorship curve of Tetranychus urticae on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Different letters indicate significant differences as determined by Log-rank (Mantel–Cox) test (p < 0.05).
Figure 3. Survivorship curve of Tetranychus urticae on seven Chinese strawberry cultivars: Hongyan (HY), Yuexiu (YX), Tianshi (TS), Ningyu (NY), Xuetu (XT), Zhangjj (ZJ), and Xuelixiang (XLX). Different letters indicate significant differences as determined by Log-rank (Mantel–Cox) test (p < 0.05).
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Insects 16 00767 g004
Figure 4. Phylogenetic tree of top 19 abundant bacteria in Tetranychus urticae 1-day-old male/female adults on 4 Chinese strawberry cultivars Tianshi (TS), Hongyan (HY), Ningyu (NY), Fenyu (FY) and Yuexiu (YX), by 16S rRNA genes based on probabilistic methods of phylogenetic inference constructed by FastTree 2.0.0 software.
Figure 4. Phylogenetic tree of top 19 abundant bacteria in Tetranychus urticae 1-day-old male/female adults on 4 Chinese strawberry cultivars Tianshi (TS), Hongyan (HY), Ningyu (NY), Fenyu (FY) and Yuexiu (YX), by 16S rRNA genes based on probabilistic methods of phylogenetic inference constructed by FastTree 2.0.0 software.
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Insects 16 00767 g005
Figure 5. Relative abundance of top 10 bacterial species in Tetranychus urticae 1-day-old male/female adults on 4 Chinese strawberry cultivars Tianshi (TS), Hongyan (HY), Ningyu (NY), Fenyu (FY) and Yuexiu (YX), by full-length 16s rRNA gene sequencing. In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male.
Figure 5. Relative abundance of top 10 bacterial species in Tetranychus urticae 1-day-old male/female adults on 4 Chinese strawberry cultivars Tianshi (TS), Hongyan (HY), Ningyu (NY), Fenyu (FY) and Yuexiu (YX), by full-length 16s rRNA gene sequencing. In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male.
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Insects 16 00767 g006
Figure 6. Alpha diversity indices of bacterial communities in 1-day-old male and female Tetranychus urticae adults reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX). The diversity metrics presented include Shannon (A), Simpson (B), and Chao1 (C) indices. In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male. Different lowercase letters above the bars (a, b, c) indicate statistically significant differences between groups.
Figure 6. Alpha diversity indices of bacterial communities in 1-day-old male and female Tetranychus urticae adults reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX). The diversity metrics presented include Shannon (A), Simpson (B), and Chao1 (C) indices. In the group labels, the third letter denotes the sex of the mites: ‘F’ for female and ‘M’ for male. Different lowercase letters above the bars (a, b, c) indicate statistically significant differences between groups.
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Insects 16 00767 g007
Figure 7. Bacterial microbiota function prediction of Tetranychus urticae reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX), by 16s rRNA gene sequencing. Functional profiling leveraged PICRUSt2 to predict metabolic pathways against MetaCyc and KEGG databases.
Figure 7. Bacterial microbiota function prediction of Tetranychus urticae reared on four Chinese strawberry cultivars: Tianshi (TS), Hongyan (HY), Fenyu (FY), and Yuexiu (YX), by 16s rRNA gene sequencing. Functional profiling leveraged PICRUSt2 to predict metabolic pathways against MetaCyc and KEGG databases.
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Table 1. Information about full-length 16s rRNA gene sequencing in different strawberry cultivars of Tetranychus urticae.
Table 1. Information about full-length 16s rRNA gene sequencing in different strawberry cultivars of Tetranychus urticae.
Sample NameInputFilteredDenoisedPhylumSpecies
TSM194549454936949
TSM210,30310,30310,196421
TSM314,99914,99914,876438
TSM415,46315,46315,387516
TSF115,05015,05014,992520
TSF214,56214,56214,55524
TSF314,01914,01913,936620
TSF413,53613,53613,52447
HYM114,52014,52014,486314
HYM214,89214,89214,512425
HYM313,41013,41013,348417
HYM415,63615,63615,502525
HYF112,97912,97912,965410
HYF212,68712,68712,66349
HYF312,35212,35212,28224
HYF414,57314,57314,57024
FYM113,98913,98913,95224
FYM215,75915,75915,593411
FYM315,13815,13815,080421
FYM414,87814,87814,793513
FYF114,91814,91814,862411
FYF212,27712,27712,194422
FYF313,39713,39713,34949
FYF413,53313,53313,457411
YXM115,62415,62415,61449
YXM214,11314,11314,102311
YXM315,44915,44915,061532
YXM414,19114,19114,144524
YXF115,63615,63615,61024
YXF214,35414,35414,291415
YXF313,54013,54013,477411
YXF415,97515,97515,942411
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Zhang, X.; Yang, H.; Yan, Z.; Wang, Y.; Wang, Q.; Huo, S.; Chen, Z.; Cheng, J.; Yang, K. Host-Dependent Variation in Tetranychus urticae Fitness and Microbiota Composition Across Strawberry Cultivars. Insects 2025, 16, 767. https://doi.org/10.3390/insects16080767

AMA Style

Zhang X, Yang H, Yan Z, Wang Y, Wang Q, Huo S, Chen Z, Cheng J, Yang K. Host-Dependent Variation in Tetranychus urticae Fitness and Microbiota Composition Across Strawberry Cultivars. Insects. 2025; 16(8):767. https://doi.org/10.3390/insects16080767

Chicago/Turabian Style

Zhang, Xu, Hongjun Yang, Zhiming Yan, Yuanhua Wang, Quanzhi Wang, Shimei Huo, Zhan Chen, Jialong Cheng, and Kun Yang. 2025. "Host-Dependent Variation in Tetranychus urticae Fitness and Microbiota Composition Across Strawberry Cultivars" Insects 16, no. 8: 767. https://doi.org/10.3390/insects16080767

APA Style

Zhang, X., Yang, H., Yan, Z., Wang, Y., Wang, Q., Huo, S., Chen, Z., Cheng, J., & Yang, K. (2025). Host-Dependent Variation in Tetranychus urticae Fitness and Microbiota Composition Across Strawberry Cultivars. Insects, 16(8), 767. https://doi.org/10.3390/insects16080767

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