In this study, we compared the composition of parasitoid species and parasitism rates between rearing and DNA metabarcoding of host eggs and larvae of the millet head miner, Heliocheilus albipunctella De Joannis Lepidoptera, Noctuidae , collected from millet fields in Senegal. We first assessed the detection threshold for the main ten endoparasitoids, by sequencing PCR products obtained from artificial dilution gradients of the parasitoid DNAs in the host moth.
We then assessed the potential of DNA metabarcoding for diagnosing parasitism rates in samples collected from the field. Under controlled conditions, our results showed that relatively small quantities of parasitoid DNA 0. Parasitoid diversity and parasitism rate estimates were always higher for DNA metabarcoding than for host rearing. Furthermore, metabarcoding detected multi-parasitism, cryptic parasitoid species and differences in parasitism rates between two different sampling sites. Metabarcoding shows promise for gaining a clearer understanding of the importance and complexity of host-parasitoid interactions in agro-ecosystems, with a view to improving pest biocontrol strategies.
Insect parasitoids are usually defined as species whose larvae develop by feeding in or on the body of an arthropod host, eventually killing it 1. Insect parasitoids herein, parasitoids display great species diversity and a wide variety of biological and ecological traits. They can play an important role in the natural regulation of arthropod populations 2 , 3. Biological control of agricultural insect pests using natural enemies, such as parasitoids, is a successful way of reducing the crop yield losses caused by these pests 6 , 7 , 8 , 9 and is an ecologically-based alternative to insecticide use Alternatively, native parasitoids can be mass-reared and periodically released in the field augmentative biological control , when population sizes are not sufficient to provide effective control An abundance of native parasitoids can also be promoted through adequate manipulation of their habitats i.
A fast and reliable diagnostic of parasitism in target pests is critical for assessing the efficacy of biological control programs, but also for ecological studies dealing with host-parasitoid interactions and trophic webs 13 , Traditional methods used to identify parasitoids and assess parasitism rates in a pest population rely on rearing the host up to the emergence of adult parasitoids, or the dissection of host material. However, results from host rearing can often be biased by the differential mortality of hosts due to diseases or other common stresses occurring during the rearing process.
In addition, identifying parasitoid species obtained by host rearing calls for the expertise of a taxonomist, which often reaches its limits for the identification of morphologically cryptic species.
For the two conventional methods rearing or dissection , the workload limits the number of samples that can be analyzed. Consequently, these methods are difficult to scale up to large sampling designs Molecular methods have opened up new prospects for identifying parasitoids and evaluating host-parasitoid interactions, early in the host egg stage, taking a Restriction Fragment Length Polymorphism approach PCR-RFLP, see Papura et al. The two methods have been shown to detect higher parasitism rates than traditional insect rearing methods 18 , but they were only applied using Sanger sequencing 13 , 19 , often limited by PCR success and sampling size.
In a current context of increasing use of DNA metabarcoding via high-throughput sequencing HTS , there is a need to operate a transition toward more efficient versions of these approaches. DNA metabarcoding is efficiently used for the detection of host-parasite interactions, as illustrated in a wide range of organisms 20 , 21 , 22 , including insects 23 , This approach provides reliable, rapid and accessible identification of both immature and adult specimens, even for non-taxonomists, and without a priori knowledge on the specific composition of the food web In addition, DNA metabarcoding can provide information that is not easily obtained through conventional host rearing and conventional DNA barcoding, such as multiparasitism 26 , since it consists in co-amplifying and co-sequencing several taxa in a single PCR reaction Lastly, DNA metabarcoding can be used to sequence a large number of samples at limited cost 28 , 29 , 30 , opening up the possibility of undertaking large-scale analyses.
However, DNA metabarcoding may be subject to technical bias, which needs to be properly taken in account when studying host-parasitoid interactions 31 , such as potential DNA contamination in the laboratory , or non-detection related to PCR biases The latter can be due to mismatches between primers and particular DNA targets, and to competition for co-amplification of a small proportion of parasitoid DNA in a large quantity of host DNA. Although adequate technical practice makes it possible to reduce biases inducing false positive or negative results in metabarcoding experiments 31 , 32 , 33 , an evaluation of the efficiency of DNA metabarcoding is lacking in systems other than soils 34 , and marine and freshwater environments 35 , 36 , Yet, it is crucial to evaluate detection sensitivity for an accurate and reliable diagnostic of pest parasitism in agro-ecosystems.
The aim of this study was to assess the relevance of DNA metabarcoding in identifying parasitoid species and their relative contribution to the natural control of a crop pest. Crop losses due to this pest are greatly mitigated by natural enemies, including predators and parasitoids 38 , 39 , 40 , 41 , making it a relevant model for exploring the functional biodiversity involved in trophic webs and biological control.
The relevance of this model is also supported by the fact that assemblages of parasitoids associated with MHM have been morphologically and genetically documented 41 , and that significant larval mortality generally occurs during rearing processes e. Then, the parasitism rate was estimated by concurrently applying the DNA metabarcoding and rearing methods to MHM eggs and larvae collected in the field from two contrasting agricultural landscapes.
We first conducted an Illumina MiSeq run to sequence dilution test samples. We then conducted another Illumina MiSeq run to sequence 1, moth samples collected in the field. After filtering according to the recommendation made by Galan et al. The metabarcoding approach was calibrated in two stages, 1 we first assessed the detection sensitivity of the DNA metabarcoding protocol by testing the amplification of artificial dilution gradients of the parasitoid DNAs in the host moth, and 2 we then evaluated detection variability between different stages of host development by sequencing samples collected in the field.
All the parasitoid taxa were detected except Trichogrammatoidea armigera the main parasitoid of MHM eggs Fig. Such a downward bias of the final proportion of the target species had already been observed in the metabarcoding of arthropod mock communities 43 , Proportion of parasitoid sequences observed from metabarcoding y-axis of controlled dilutions of parasitoid DNA in host DNA x-axis for each of the 10 major parasitoid species. For each parasitoid species, we mixed 7, 0.
The dashed line represents the expectation. Axes are in a log-scale. The three bars per dilution account for the three technical PCR replicates. NA: data is not available because of a lack of DNA availability for the parasitoid.
Proportion of parasitoid sequences observed from metabarcoding y-axis of controlled dilutions of parasitoid DNA in host DNA x-axis averaged over the 10 major parasitoid species. Bars represent the standard deviation. Overall, there was a strong concordance between the proportion of parasitoid sequences observed and the abundance of parasitoid DNA relative to the quantity of host DNA Fig. The number of sequences obtained among technical replicates was remarkably stable. When considering as positive those samples with at least two of the three technical replicates that were positive, the detection threshold was 0.
Habrobracon hebetor , Schoelandella sp.
Pattern and process in host-parasitoid interactions.
The exceptions were Pristomerus pallidus and Copidosoma primulum , with a detection threshold of 0. At the highest relative abundances 0. At the detection threshold for most species 0.
Four parasitoid species, namely T. The proportion of sequences of T. The proportion of sequences of C. The proportion of sequences of S.
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No difference was observed for parasitism between early- and late-instar larvae for Schoelandella sp. Proportion of sequences of four parasitoid species observed from DNA metabarcoding from individual field samples of the millet head miner Heliocheilus albipunctella at different stages of development eggs, early instar larvae, late instar larvae. Trichogrammatoidea armigera is an egg parasitoid, Copidosoma primulum is an ovo-larval parasitoid, Schoelandella sahelensis and Schoelandella sp.
Values above each bar represent the number of positive samples for each stage of the four parasitoid species. Following the evaluation steps, the detection of parasitism rates was compared between traditional rearing and DNA metabarcoding. The parasitism rates obtained with the two approaches were compared for overall parasitism estimates, but also for eggs and larvae parasitized by each species of parasitoid. A high mortality rate was recorded for eggs The egg parasitism rate obtained with rearing was significantly lower 3. The larval parasitism rate obtained with rearing was also lower The parasitism rate estimated by metabarcoding was significantly higher in Nioro compared to Bambey, with respectively Multiparasitism was observed on 1.
No case of multiparasitism was observed for rearing. RIM Rearing Including Mortality : the parasitism rate calculated including unhatched eggs or dead larvae. REM Rearing Excluding Mortality : the parasitism rate calculated excluding unhatched eggs or dead larvae. Significant difference represented by the different letters a and b. Overall parasitism rate of millet head miner Heliocheilus albipunctella parasitoids estimated by DNA metabarcoding and rearing methods according to the sample sites: Bambey and Nioro Senegal. Significant difference represented by the different letters a, b and c.
The mean proportions of eggs parasitized by T. The parasitoid C. The prevalence of C. When taking mortality into account in the calculation, the prevalence of C. The mean proportion of S. To understand host-parasitoid interactions, it is necessary to estimate parasitism rates and identify parasitoid species accurately 24 , 45 , 46 , 47 , Molecular approaches can provide more information than conventional methods, for a better understanding of interactions between host or prey species and their natural enemies, including parasitoids 18 , 24 and predators A better understanding of these interactions is a fundamental basis for successful biological control programs based on the introduction or enhancement of parasitoids 6 , 8 , This study showed that metabarcoding is a reliable support for assessing the specific and functional diversity of the parasitoids of insect pests in an agro-ecosystem, and that it performs better than rearing.
Recent studies showed the effectiveness of DNA metabarcoding for identifying individuals involved in host-parasitoid interactions at different trophic levels 23 , 41 , in comparison to standard DNA barcoding and morphological approaches However, little attention has been paid to the sensitivity detection threshold of this method, particularly regarding the importance of more effectively taking into account PCR biases for an accurate and reliable diagnostic of parasitism. Our results showed that the universal primers 43 used for DNA metabarcoding were effective for the detection of parasitoid DNA, even when present in very small quantities in host tissues.
Under controlled conditions, we were able to detect parasitoid DNA up to a dilution ratio of 0. For the single exception excluding T. Therefore, a dilution ratio of 0. Given the absence of major PCR bias highlighted in the dilution tests , it is reasonable to assume that these ratios correspond to the ratio of parasitoid tissues in the host larva encountered in the field.
Pattern And Process In Host-Parasitoid Interactions
Consequently, we argue that there is little risk of missing parasitoids in host eggs and larvae collected in the field. Liang et al. In addition, our detection threshold appeared sensitive enough to detect all the developmental stages of our parasitoids, including embryonic stages. This point is essential for estimating parasitism rates by DNA metabarcoding, because it suggests that even the earliest stages of parasitoids which can be one egg in the host larva can be effectively detected. Metabarcoding recovered parasitoid tissues in the majority of host parasitoid pairs, but two cases were problematic, likely due to competition due to PCR bias or manipulation error.
Competition related to PCR bias between Lepidoptera and Hymenoptera was not apparent, except for the egg parasitoid T.
Interestingly, while T. Furthermore, in these detection cases, the host DNA was not amplified at all i. This indicates that only egg parasitoids that are at very advanced stages of development i. This limit of our method resulted in an under-estimation of the parasitism rate of egg parasitoids. However, it can be easily lifted using one base degeneracy for the problematic position of the reverse primer. The high detection threshold for C. The metabarcoding molecular approach is an increasingly promising alternative to conventional methods in parasitism diagnostics.
In our case study of a complex of ten parasitoid species recorded from MHM, the three main key parasitoid species were detected by metabarcoding and rearing T.
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In addition to these, the metabarcoding has also detected Schoelandella sp. These species are key parasitoids of MHM, i. Other species are rare or very rare and are usually not detected in surveys conducted on a reduced number of sites and samples. DNA metabarcoding resulted in significantly higher estimates of parasitism rates than rearing, at both sampling sites, when excluding mortality from the calculation. No significant difference between DNA metabarcoding and rearing was observed when mortality was included. This information is interesting because it suggests that much of the mortality of host larvae is apparently related to parasitism.
In host eggs, we detected two egg parasitoid species, C. This was predictable because C. However, even though this parasitoid largely dominates egg parasitism in DNA metabarcoding, it does not have a direct impact on egg mortality. The mismatches detected between the voucher sequence of T. The larval parasitism rate obtained with rearing may have been underestimated due to host larva and parasitoid mortality which reached a high level in our case.
Host larva mortality remains the main limitation for an accurate and reproducible estimation of parasitism rates in the rearing laboratory 52 , In this case, DNA metabarcoding is useful for estimating parasitism rates because it can be used to detect parasitoids in the host body, whether the larval parasitoid is alive or dead For example, we can take the case of S. With DNA metabarcoding, the proportion of larval hosts parasitized by this species was quadrupled compared to rearing.
In addition, this parasitoid largely dominated larval parasitism compared to C. In contrast, with rearing, the proportion of larval hosts parasitized by C. However, it does not predict the survival of parasitoids as a result of host defense mechanisms. Our results also showed that the parasitism rate estimated by DNA metabarcoding was significantly higher at Nioro than at Bambey, while no difference was observed between sites with rearing.
Interestingly, Nioro has a typical savanna vegetation type displaying many spontaneous plants that could serve as reservoirs of alternative lepidopteran hosts.
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This could explain the higher density of parasitoids observed in this area. Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article. Related Information. Close Figure Viewer. Browse All Figures Return to Figure. Previous Figure Next Figure. Parasitoid impact on host densities 6. Primary parasitoid species richness. Herbivore feeding niche.
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