An rbcL reference library to aid in the identification of plant species mixtures by DNA metabarcoding

Plant-pollinator network architecture does not impact intraspecific microbiome variability

Variation in how individuals interact with food resources can directly impact, and be affected by, their microbial interactions due to the potential for transmission. The degree to which this transmission occurs, however, may depend on the structure of forager networks, which determine the community-scale transmission opportunities. In particular, how the community-scale opportunity for transfer balances individual-scale barriers to transmission is unclear. Examining the bee-flower and bee-microbial interactions of over 1000 individual bees, we tested (1) the degree to which individual floral visits predicted microbiome composition and (2) whether plant-bee networks with increased opportunity for microbial transmission homogenized the microbiomes of bees within that network. The pollen community composition carried by bees was associated with microbiome composition at some sites, suggesting that microbial transmission at flowers occurred. Contrary to our predictions, however, microbiome variability did not differ based on transfer opportunity: bee microbiomes in asymmetric networks with high opportunity for microbial transfer were similarly variable compared to microbiomes in networks with more evenly distributed links. These findings suggest that microbial transmission at flowers is frequent enough to be observed at the community level, but that community network structure did not substantially change the dynamics of this transmission, perhaps due to filtering processes in host guts.

Identification of nectar sources foraged by female mosquitoes in Canada

For many mosquito species, the females must obtain vertebrate blood to complete a gonotrophic cycle. These blood meals are frequently supplemented by feeding on sugary plant nectar, which sustains energy reserves needed for flight, mating, and overall fitness. Our understanding of mosquito nectar foraging behaviors is mostly limited to laboratory experiments and direct field observations, with little research into natural mosquito-host plant relationships done in North America. In this study, we collected nectar-fed female mosquitoes over a 2-year period in Manitoba, Canada, and amplified a fragment of the chloroplast rbcL gene to identify the plant species fed upon. We found that mosquitoes foraged from diverse plant families (e.g., grasses, trees, ornamentals, and legumes), but preferred certain species, most notably soybean and Kentucky blue grass. Moreover, there appeared to be some associations between plant feeding preferences and mosquito species, date of collection, landscape, and geographical region. Overall, this study implemented DNA barcoding to identify nectar sources forage by mosquitoes in the Canadian Prairies.

How reliable is metabarcoding for pollen identification? An evaluation of different taxonomic assignment strategies by cross-validation

Metabarcoding is a powerful tool, increasingly used in many disciplines of environmental sciences. However, to assign a taxon to a DNA sequence, bioinformaticians need to choose between different strategies or parameter values and these choices sometimes seem rather arbitrary. In this work, we present a case study on ITS2 and rbcL databases used to identify pollen collected by bees in Belgium. We blasted a random sample of sequences from the reference database against the remainder of the database using different strategies and compared the known taxonomy with the predicted one. This in silico cross-validation (CV) approach proved to be an easy yet powerful way to (1) assess the relative accuracy of taxonomic predictions, (2) define rules to discard dubious taxonomic assignments and (3) provide a more objective basis to choose the best strategy. We obtained the best results with the best blast hit (best bit score) rather than by selecting the majority taxon from the top 10 hits. The predictions were further improved by favouring the most frequent taxon among those with tied best bit scores. We obtained better results with databases containing the full sequences available on NCBI rather than restricting the sequences to the region amplified by the primers chosen in our study. Leaked CV showed that when the true sequence is present in the database, blast might still struggle to match the right taxon at the species level, particularly with rbcL. Classical 10-fold CV-where the true sequence is removed from the database-offers a different yet more realistic view of the true error rates. Taxonomic predictions with this approach worked well up to the genus level, particularly for ITS2 (5-7% of errors). Using a database containing only the local flora of Belgium did not improve the predictions up to the genus level for local species and made them worse for foreign species. At the species level, using a database containing exclusively local species improved the predictions for local species by ∼12% but the error rate remained rather high: 25% for ITS2 and 42% for rbcL. Foreign species performed worse even when using a world database (59-79% of errors). We used classification trees and GLMs to model the % of errors vs. identity and consensus scores and determine appropriate thresholds below which the taxonomic assignment should be discarded. This resulted in a significant reduction in prediction errors, but at the cost of a much higher proportion of unassigned sequences. Despite this stringent filtering, at least 1/5 sequences deemed suitable for species-level identification ultimately proved to be misidentified. An examination of the variability in prediction accuracy between plant families showed that rbcL outperformed ITS2 for only two of the 27 families examined, and that the % correct species-level assignments were much better for some families (e.g. 95% for Sapindaceae) than for others (e.g. 35% for Salicaceae).

Semi-automated sequence curation for reliable reference datasets in ITS2 vascular plant DNA (meta-)barcoding

One of the most critical steps for accurate taxonomic identification in DNA (meta)-barcoding is to have an accurate DNA reference sequence dataset for the marker of choice. Therefore, developing such a dataset has been a long-term ambition, especially in the Viridiplantae kingdom. Typically, reference datasets are constructed with sequences downloaded from general public databases, which can carry taxonomic and other relevant errors. Herein, we constructed a curated (i) global dataset, (ii) European crop dataset, and (iii) 27 datasets for the EU countries for the ITS2 barcoding marker of vascular plants. To that end, we first developed a pipeline script that entails (i) an automated curation stage comprising five filters, (ii) manual taxonomic correction for misclassified taxa, and (iii) manual addition of newly sequenced species. The pipeline allows easy updating of the curated datasets. With this approach, 13% of the sequences, corresponding to 7% of species originally imported from GenBank, were discarded. Further, 259 sequences were manually added to the curated global dataset, which now comprises 307,977 sequences of 111,382 plant species.

Stepping towards pollen DNA metabarcoding: A breakthrough in forensic sciences

This review is engaged in determining the capability of plant pollen as a significant source of evidence for the linkage between suspects and crime location in forensic sciences. Research and review articles were collected from Google Scholar, the Web of Science, and PubMed. Articles were searched using specific keywords such as "Forensic Palynology," "Pollen metabarcoding," "Plant forensics," and "Pollen" AND "criminal investigation." Boolean logic was also utilized to narrow the articles to be included in this review article. Through the literature and exploratory research, it has been observed in the current study that with advancements in technology, forensic palynology has found its application in creating an association between the crime scene and suspected individuals to have a link to it, as pollen DNA is a long-lasting investigative tool that can effectively help forensic investigations. Moreover, the literature shows that the DNA of pollen and spores has helped forensic scientists link suspects to crime scenes, and the introduction of pollen DNA metabarcoding tools has eased the efforts of palynologists to analyze pollen DNA. The introduction of DNA metabarcoding techniques to analyze pollen from plants has helped identify the geological locations of the plants and ultimately identify the culprit.

Unraveling the potential of environmental DNA for deciphering recent advances in plant-animal interactions: a systematic review

MAIN CONCLUSION

Environmental DNA-based monitoring provides critical insights for enhancing our understanding of plant-animal interactions in the context of worldwide biodiversity decrease for developing a global framework for effective plant biodiversity conservation. To understand the ecology and evolutionary patterns of plant-animal interactions (PAI) and their pivotal roles in ecosystem functioning advances in molecular ecology tools such as Environmental DNA (eDNA) provide unprecedented research avenues. These methods being non-destructive in comparison to traditional biodiversity monitoring methods, enhance the discernment of ecosystem health, integrity, and complex interactions. This review intends to offer a systematic and critical appraisal of the prospective of eDNA for investigating PAI. The review thoroughly discusses and analyzes the recent reports (2015-2022) employing preferred reporting items for systematic reviews and meta-analyses (PRISMA) to outline the recent progression in eDNA approaches for elucidating PAI. The current review envisages that eDNA has a significant potential to monitor both plants and associated cohort of prospective pollinators (avian species and flowering plants, bees and plants, arthropods and plants, bats and plants, etc.). Furthermore, a brief description of the factors that influence the utility and interpretation of PAI eDNA is also presented. The review establishes that factors such as biotic and abiotic, primer selection and taxonomic resolution, and indeterminate spatio-temporal scales impact the availability and longevity of eDNA. The study also identified the limitations that influence PAI detection and suggested possible solutions for better execution of these molecular approaches. Overcoming these research caveats will augment the assortment of PAI analysis through eDNA that could be vital for ecosystem health and integrity. This review forms a critical guide and offers prominent insights for ecologists, environmental managers and researchers to assess and evaluate plant-animal interaction through environmental DNA.

Validating a multi-locus metabarcoding approach for characterizing mixed-pollen samples

BACKGROUND

The mutualistic interaction between entomophilous plants and pollinators is fundamental to the structure of most terrestrial ecosystems. The sensitive nature of this relationship has been disrupted by anthropogenic modifications to natural landscapes, warranting development of new methods for exploring this trophic interaction. Characterizing the composition of pollen collected by pollinators, e.g. Apis mellifera, is a common means of exploring this relationship, but traditional methods of microscopic pollen assessment are laborious and limited in their scope. The development of pollen metabarcoding as a method of rapidly characterizing the abundance and diversity of pollen within mixed samples presents a new frontier for this type of work, but metabarcoding may have limitations, and validation is warranted before any suite of primers can be confidently used in a research program. We set out to evaluate the utility of an integrative approach, using a set of established primers (ITS2 and rbcL) versus melissopalynological analysis for characterizing 27 mixed-pollen samples from agricultural sites across Canada.

RESULTS

Both individual markers performed well relative to melissopalynology at the family level with decreases in the strength of correlation and linear model fits at the genus level. Integrating data from both markers together via a multi-locus approach provided the best rank-based correlation between metagenetic and melissopalynological data at both the genus (ρ = 0.659; p < 0.001) and family level (ρ = 0.830; p < 0.001). Species accumulation curves indicated that, after controlling for sampling effort, melissopalynological characterization provides similar or higher species richness estimates than either marker. The higher number of plant species discovered via the metabarcoding approach simply reflects the vastly greater sampling effort in comparison to melissopalynology.

CONCLUSIONS

Pollen metabarcoding performed well at characterizing the composition of mixed pollen samples relative to a traditional melissopalynological approach. Limitations to the quantitative application of this method can be addressed by adopting a multi-locus approach that integrates information from multiple markers.

Rapid and accurate taxonomic classification of cpn60 amplicon sequence variants

The "universal target" region of the gene encoding the 60 kDa chaperonin protein (cpn60, also known as groEL or hsp60) is a proven sequence barcode for bacteria and a useful target for marker gene amplicon-based studies of complex microbial communities. To date, identification of cpn60 sequence variants from microbiome studies has been accomplished by alignment of queries to a reference database. Naïve Bayesian classifiers offer an alternative identification method that provides variable rank classification and shorter analysis times. We curated a set of cpn60 barcode sequences to train the RDP classifier and tested its performance on data from previous human microbiome studies. Results showed that sequences accounting for 79%, 86% and 92% of the observations (read counts) in saliva, vagina and infant stool microbiome data sets were classified to the species rank. We also trained the QIIME 2 q2-feature-classifier on cpn60 sequence data and demonstrated that it gives results consistent with the standalone RDP classifier. Successful implementation of a naïve Bayesian classifier for cpn60 sequences will facilitate future microbiome studies and open opportunities to integrate cpn60 amplicon sequence identification into existing analysis pipelines.

Native solitary bee reproductive success depends on early season precipitation and host plant richness

Spring-emerging bees depend upon the synchronized bloom times of angiosperms that provide pollen and nectar for offspring. The emergence of such bees and bloom times are linked to weather but can be phenologically mismatched, which could limit bee developmental success. However, it remains unclear how such phenologically asynchrony could affect spring-emerging pollinators, and especially for those that forage over a relatively short time period. We examined the relationship between weather and host plant selection on the native spring-foraging solitary bee, Osmia lignaria, across 3 years at urban and rural sites in and around Seattle, Washington, USA. We used community science weather data to test the effects of precipitation, wind, and temperature on O. lignaria oviposition and developmental success. We also collected pollen data over two distinct foraging periods, early and late spring, and used Next-Generation Sequencing to identify plant genera from pollen. Among the weather variables, precipitation during the early foraging period adversely affected larval developmental success and adult bee emergence success, but not oviposition. Using DNA metabarcoding, we observed that increases in the number of plant genera in pollen increased adult emergence in both foraging periods, but not oviposition or larval development. We also observed that foraging bees consistently visited certain genera during each foraging period, especially Acer, Salix, and Rubus. However, pollen collected by O. lignaria over different years varied in the number of total genera visited, highlighting the importance of multi-year studies to ascertain bee foraging preferences and its link to developmental success.

A primer on pollen assignment by nanopore-based DNA sequencing

The possibility to identify plants based on the taxonomic information coming from their pollen grains offers many applications within various biological disciplines. In the past and depending on the application or research in question, pollen origin was analyzed by microscopy, usually preceded by chemical treatment methods. This procedure for identification of pollen grains is both time-consuming and requires expert knowledge of morphological features. Additionally, these microscopically recognizable features usually have a low resolution at species-level. Since a few decades, DNA has been used for the identification of pollen taxa, as sequencing technologies evolved both in their handling and affordability. We discuss advantages and challenges of pollen DNA analyses compared to traditional methods. With readers with little experience in this field in mind, we present a hands-on primer for genetic pollen analysis by nanopore sequencing. As our lab mainly works with pollen collected within agroecological research projects, we focus on pollen collected by pollinating insects. We briefly consider sample collection, storage and processing in the laboratory as well as bioinformatic aspects. Currently, pollen metabarcoding is mostly conducted with next-generation sequencing methods that generate short sequence reads (&lt;1 kb). Increasingly, however, pollen DNA analysis is carried out using the long-read generating (several kb), low-budget and mobile MinION nanopore sequencing platform by Oxford Nanopore Technologies. Therefore, we are focusing on aspects for palynology with the MinION DNA sequencing device.

Environmental DNA as an emerging tool in botanical research

Over the past quarter century, environmental DNA (eDNA) has been ascendant as a tool to detect, measure, and monitor biodiversity (species and communities), as a means of elucidating biological interaction networks, and as a window into understanding past patterns of biodiversity. However, only recently has the potential of eDNA been realized in the botanical world. Here we synthesize the state of eDNA applications in botanical systems with emphases on aquatic, ancient, contemporary sediment, and airborne systems, and focusing on both single-species approaches and multispecies community metabarcoding. Further, we describe how abiotic and biotic factors, taxonomic resolution, primer choice, spatiotemporal scales, and relative abundance influence the utilization and interpretation of airborne eDNA results. Lastly, we explore several areas and opportunities for further development of eDNA tools for plants, advancing our knowledge and understanding of the efficacy, utility, and cost-effectiveness, and ultimately facilitating increased adoption of eDNA analyses in botanical systems.

Metabarcoding of soil environmental DNA to estimate plant diversity globally

Introduction

Traditional approaches to collecting large-scale biodiversity data pose huge logistical and technical challenges. We aimed to assess how a comparatively simple method based on sequencing environmental DNA (eDNA) characterises global variation in plant diversity and community composition compared with data derived from traditional plant inventory methods.

Methods

We sequenced a short fragment (P6 loop) of the chloroplast trnL intron from from 325 globally distributed soil samples and compared estimates of diversity and composition with those derived from traditional sources based on empirical (GBIF) or extrapolated plant distribution and diversity data.

Results

Large-scale plant diversity and community composition patterns revealed by sequencing eDNA were broadly in accordance with those derived from traditional sources. The success of the eDNA taxonomy assignment, and the overlap of taxon lists between eDNA and GBIF, was greatest at moderate to high latitudes of the northern hemisphere. On average, around half (mean: 51.5% SD 17.6) of local GBIF records were represented in eDNA databases at the species level, depending on the geographic region.

Discussion

eDNA trnL gene sequencing data accurately represent global patterns in plant diversity and composition and thus can provide a basis for large-scale vegetation studies. Important experimental considerations for plant eDNA studies include using a sampling volume and design to maximise the number of taxa detected and optimising the sequencing depth. However, increasing the coverage of reference sequence databases would yield the most significant improvements in the accuracy of taxonomic assignments made using the P6 loop of the trnL region.

Bacterial and Fungal Symbionts in Pollen Provisions of a Native Solitary Bee in Urban and Rural Environments

Among insects, symbionts such as bacteria and fungi can be linked to their physiology and immature development, and in some cases are part of a defense system against parasites and diseases. Current bacterial and fungal symbiont associations in solitary bees are understudied, especially in the Pacific Northwest region of the USA. We collected pollen provisions from the native spring-foraging solitary bee, Osmia lignaria Say, across two distinct foraging periods over 2 years at 22 sites along an urban-to-rural gradient in western Washington. We then used next-generation sequencing to identify bacterial and fungi within pollen provisions and assessed the effect of their richness and diversity on O. lignaria larval development success and adult emergence. We detected a significantly positive relationship between bacterial diversity in pollen with O. lignaria larval developmental success, and higher bacterial richness and diversity during the later foraging period. Fungal generic richness and diversity decreased with increasing plant richness. Although neither was associated with O. lignaria developmental success, we did detect Ascosphaera spp. known to be pathogenic to O. lignaria and other bee species. Neither bacterial or fungal richness or diversity was affected by site type when classified as urban or rural. This study provides new information on bacterial and fungal symbionts present in pollen provisions of a native solitary bee when foraging across urban and rural areas of the Pacific Northwest.

A detailed workflow to develop QIIME2-formatted reference databases for taxonomic analysis of DNA metabarcoding data

Background

The DNA metabarcoding approach has become one of the most used techniques to study the taxa composition of various sample types. To deal with the high amount of data generated by the high-throughput sequencing process, a bioinformatics workflow is required and the QIIME2 platform has emerged as one of the most reliable and commonly used. However, only some pre-formatted reference databases dedicated to a few barcode sequences are available to assign taxonomy. If users want to develop a new custom reference database, several bottlenecks still need to be addressed and a detailed procedure explaining how to develop and format such a database is currently missing. In consequence, this work is aimed at presenting a detailed workflow explaining from start to finish how to develop such a curated reference database for any barcode sequence.

Results

We developed DB4Q2, a detailed workflow that allowed development of plant reference databases dedicated to ITS2 and rbcL, two commonly used barcode sequences in plant metabarcoding studies. This workflow addresses several of the main bottlenecks connected with the development of a curated reference database. The detailed and commented structure of DB4Q2 offers the possibility of developing reference databases even without extensive bioinformatics skills, and avoids ‘black box’ systems that are sometimes encountered. Some filtering steps have been included to discard presumably fungal and misidentified sequences. The flexible character of DB4Q2 allows several key sequence processing steps to be included or not, and downloading issues can be avoided. Benchmarking the databases developed using DB4Q2 revealed that they performed well compared to previously published reference datasets.

Conclusion

This study presents DB4Q2, a detailed procedure to develop custom reference databases in order to carry out taxonomic analyses with QIIME2, but also with other bioinformatics platforms if desired. This work also provides ready-to-use plant ITS2 and rbcL databases for which the prediction accuracy has been assessed and compared to that of other published databases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01067-5.

Endangered Nectar-Feeding Bat Detected by Environmental DNA on Flowers

Leptonycteris nivalis (the Mexican long-nosed bat) is an endangered nectar-feeding bat species that follows "nectar corridors" as it migrates from Mexico to the southwestern United States. Locating these nectar corridors is key to their conservation and may be possible using environmental DNA (eDNA) from these bats. Hence, we developed and tested DNA metabarcoding and qPCR eDNA assays to determine whether L. nivalis could be detected by sampling the agave flowers on which it feeds. We sampled plants with known bat visitations in the Sierra Madre Oriental in Laguna de Sanchez (LS), Nuevo León, Mexico, and in the Chisos Mountains in Big Bend National Park, TX, USA (CB). A total of 13 samples included both swabs of agave umbels and cuttings of individual flowers. DNA metabarcoding was performed as a PCR multiplex that targeted bats (SFF-COI), arthropods (ANML-COI), and plants (ITS2 and rbcL). We targeted arthropods and plants in parallel with bats because future metabarcoding studies may wish to examine all the pollinators and plants within the nectar corridor. We developed and tested the sensitivity and specificity of two qPCR assays. We found that both DNA metabarcoding and qPCR were highly successful at detecting L. nivalis (11 of 13 for DNA metabarcoding and 12 of 13 for qPCR). Swabs and flower cuttings and both qPCR assays detected the species over four replicates. We suggest that L. nivalis leaves substantial DNA behind as it forages for nectar. We also suggest that future studies examine the time since sampling to determine its effect on detection success. The DNA metabarcoding multiplex will be useful for parallel questions regarding pollination ecology, while, with further testing, the qPCR assays will be effective for large-scale sampling for the detection of migration corridors and foraging areas. This work may be relevant to other nectar-feeding bat species, which can likely be detected with similar methodologies.

DNA barcoding: an efficient technology to authenticate plant species of traditional Chinese medicine and recent advances

Traditional Chinese medicine (TCM) plays an important role in the global traditional health systems. However, adulterated and counterfeit TCM is on the rise. DNA barcoding is an effective, rapid, and accurate technique for identifying plant species. In this study, we collected manuscripts on DNA barcoding published in the last decade and summarized the use of this technique in identifying 50 common Chinese herbs listed in the Chinese pharmacopoeia. Based on the dataset of the major seven DNA barcodes of plants in the NCBI database, the strengths and limitations of the barcodes and their derivative barcoding technology, including single-locus barcode, multi-locus barcoding, super-barcoding, meta-barcoding, and mini-barcoding, were illustrated. In addition, the advances in DNA barcoding, particularly identifying plant species for TCM using machine learning technology, are also reviewed. Finally, the selection process of an ideal DNA barcoding technique for accurate identification of a given TCM plant species was also outlined.

Biomonitoring via DNA metabarcoding and light microscopy of bee pollen in rainforest transformation landscapes of Sumatra

BACKGROUND

Intense conversion of tropical forests into agricultural systems contributes to habitat loss and the decline of ecosystem functions. Plant-pollinator interactions buffer the process of forest fragmentation, ensuring gene flow across isolated patches of forests by pollen transfer. In this study, we identified the composition of pollen grains stored in pot-pollen of stingless bees, Tetragonula laeviceps, via dual-locus DNA metabarcoding (ITS2 and rbcL) and light microscopy, and compared the taxonomic coverage of pollen sampled in distinct land-use systems categorized in four levels of management intensity (forest, shrub, rubber, and oil palm) for landscape characterization.

RESULTS

Plant composition differed significantly between DNA metabarcoding and light microscopy. The overlap in the plant families identified via light microscopy and DNA metabarcoding techniques was low and ranged from 22.6 to 27.8%. Taxonomic assignments showed a dominance of pollen from bee-pollinated plants, including oil-bearing crops such as the introduced species Elaeis guineensis (Arecaceae) as one of the predominant taxa in the pollen samples across all four land-use types. Native plant families Moraceae, Euphorbiaceae, and Cannabaceae appeared in high proportion in the analyzed pollen material. One-way ANOVA (p > 0.05), PERMANOVA (R² values range from 0.14003 to 0.17684, for all tests p-value > 0.5), and NMDS (stress values ranging from 0.1515 to 0.1859) indicated a lack of differentiation between the species composition and diversity of pollen type in the four distinct land-use types, supporting the influx of pollen from adjacent areas.

CONCLUSIONS

Stingless bees collected pollen from a variety of agricultural crops, weeds, and wild plants. Plant composition detected at the family level from the pollen samples likely reflects the plant composition at the landscape level rather than the plot level. In our study, the plant diversity in pollen from colonies installed in land-use systems with distinct levels of forest transformation was highly homogeneous, reflecting a large influx of pollen transported by stingless bees through distinct land-use types. Dual-locus approach applied in metabarcoding studies and visual pollen identification showed great differences in the detection of the plant community, therefore a combination of both methods is recommended for performing biodiversity assessments via pollen identification.

Using Metabarcoding to Investigate the Strength of Plant-Pollinator Interactions From Surveys of Visits to DNA Sequences

The ongoing decline in pollinators and increasing concerns about pollination services require a better understanding of complex pollination networks, particularly their response to global climate change. While metabarcoding is increasingly used for the identification of taxa in DNA mixtures, its reliability in providing quantitative information on plant-pollinator interactions is still the subject of debate. Combining metabarcoding and microscopy, we investigated the relationships between the number and composition of sequences and the abundance and composition of pollen in insect pollen loads (IPL) and how the two are linked to insect visits. Our findings confirm that metabarcoding is more effective than microscopy in identifying plant species in IPL. For a given species, we found a strong positive relationship between the amount of pollen in IPL and the number of sequences. The relationship was stable across species even if the abundance of co-occurring species in IPL (hereafter “co-occurring pollen”) tended to reduce the sequence yield (number of sequences obtained from one pollen grain) of a given species. We also found a positive relationship between the sequence count and the frequency of visits, and between the frequency and the amounts of pollen in IPL. Our results demonstrate the reliability of metabarcoding in assessing the strength of plant-pollinator interactions and in providing a broader perspective for the analyses of plant-pollinator interactions and pollination networks.

Imaging Flow Cytometry as a Quick and Effective Identification Technique of Pollen Grains from Betulaceae, Oleaceae, Urticaceae and Asteraceae

Despite the continuous and intensive development of laboratory techniques, a light microscope is still the most common tool used in pollen grains differentiation. However, microscopy is time-consuming and needs well-educated and experienced researchers. Other currently used techniques can be categorised as images and non-images analysis, but each has certain limitations. We propose a new approach to differentiate pollen grains using the Imaging Flow Cytometry (IFC) technique. It allows for high-throughput fluorescence data recording, which, in contrast to the standard FC, also enables real-time control of the results thanks to the possibility of digital image recording of cells flowing through the measuring capillary. The developed method allows us to determine the characteristics of the pollen grains population based on the obtained fluorescence data, using various combinations of parameters available in the IDEAS software, which can be analysed on different fluorescence channels. On this basis, we distinguished pollen grains both between and within different genera belonging to the Betulaceae, Oleaceae, Urticaceae and Asteraceae families. Thereby, we prove that the proposed methodology is sufficient for accurate, fast, and cost-effective identification and potentially can be used in the routine analysis of allergenic pollen grains.

DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trnL and nrITS2 provides highly improved taxonomic resolution for pollen from aerobiological samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families were detected, while using a microscope only 23 genera and 22 plant families were identified. NrITS2 produced almost double the number of OTUs and a much higher percentage of identifications to species level (80.1%) than trnL (27.6%). Furthermore, regressing relative read abundances against the relative abundances of microscopically obtained pollen concentrations showed a better correlation for nrITS2 (R2 = 0.821) than for trnL (R2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands (Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that all three taxa were dominated by one or two species (Alnus glutinosa/incana, Taxus baccata and Urtica dioica). Highly allergenic as well as artificial hybrid species were found using nrITS2 that could not be identified using trnL or microscopic investigation (Alnus × spaethii, Cupressus arizonica, Parietaria spp.). Furthermore, perMANOVA analysis indicated spatiotemporal patterns in airborne pollen trends that could be more clearly distinguished for all taxa using nrITS2 rather than trnL. All results indicate that nrITS2 should be the preferred marker of choice for molecular airborne pollen monitoring.

Reference-free discovery of nuclear SNPs permits accurate, sensitive identification of Carya (hickory) species and hybrids

PREMISE

DNA-based species identification is critical when morphological identification is restricted, but DNA-based identification pipelines typically rely on the ability to compare homologous sequence data across species. Because many clades lack robust genomic resources, we present here a bioinformatics pipeline capable of generating genome-wide single-nucleotide polymorphism (SNP) data while circumventing the need for any reference genome or annotation data.

METHODS

Using the SISRS bioinformatics pipeline, we generated de novo ortholog data for the genus Carya, isolating sites where genetic variation was restricted to a single Carya species (i.e., species-informative SNPs). We leveraged these SNPs to identify both full-species and hybrid Carya specimens, even at very low sequencing depths.

RESULTS

We identified between 46,000 and 476,000 species-identifying SNPs for each of eight diploid Carya species, and all species identifications were concordant with the species of record. For all putative F1 hybrid specimens, both parental species were correctly identified in all cases, and more punctate patterns of introgression were detectable in more cryptic crosses.

DISCUSSION

Bioinformatics pipelines that use only short-read sequencing data provide vital new tools enabling rapid expansion of DNA identification assays for model and non-model clades alike.

Morphological and Molecular Characterization of Some Egyptian Six-Rowed Barley (Hordeum vulgare L.)

Barley production is essential in Egypt. In the present study, 15 different six-rowed Egyptian barley cultivars were studied. To differentiate between the different cultivars under study in terms of morphological characteristics and ISSR, molecular characterization reactions were carried out. Moreover, four cultivars (Giza 123, Giza 126, Giza 136, and Giza 138) were selected for further studies using scanning electron microscopy (SEM). Computational analysis of the DNA barcoding sequences of the two plastid markers rbcL and matK was executed, and the results were deposited in the NCBI database. The morphological traits showed low statistical significance among the different cultivars under study via the data collected from two seasons, suggesting that the mean field performance of these Egyptian cultivars may be equal under these conditions. The results showed that the phylogenetic tree was divided into four groups, one of which contained the most closely related genotypes in the genetic distance, including Giza 124, Giza 130, Giza 138, Giza 136, and Giza 137, which converge in the indicative uses of farmers. The seed coat of the studied cultivars was "rugose". The elevation folding of the rugose pattern ranged from 11 ± 1.73 µm (Giza 126) to 14.67 ± 2.43 µm (Giza 123), suggesting variation in seed quality and its uses in feed and the food industry. According to the similarity matrix of ISSR analysis, the highest similarity value (93%) was recorded between Giza 133 and Giza 132, as well as between Giza 2000 and Giza 126. On the other hand, the lowest similarity value (80%) was recorded between Giza 130 and (Giza 133 and Giza 132), indicating that these cultivars were distantly related. Polymorphism information content (PIC) ranged from 0.26 for the primer ISSR UBC 835 to 0.37 for the primers ISSR UBC 814 and ISSR UBC 840. The current study showed that the matK gene is more mutable than the rbcL gene among the tested cultivars.

Comparing whole-genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Molecular identification of mixed-species pollen samples has a range of applications in various fields of research. To date, such molecular identification has primarily been carried out via amplicon sequencing, but whole-genome shotgun (WGS) sequencing of pollen DNA has potential advantages, including (1) more genetic information per sample and (2) the potential for better quantitative matching. In this study, we tested the performance of WGS sequencing methodology and publicly available reference sequences in identifying species and quantifying their relative abundance in pollen mock communities. Using mock communities previously analyzed with DNA metabarcoding, we sequenced approximately 200Mbp for each sample using Illumina HiSeq and MiSeq. Taxonomic identifications were based on the Kraken k-mer identification method with reference libraries constructed from full-genome and short read archive data from the NCBI database. We found WGS to be a reliable method for taxonomic identification of pollen with near 100% identification of species in mixtures but generating higher rates of false positives (reads not identified to the correct taxon at the required taxonomic level) relative to rbcL and ITS2 amplicon sequencing. For quantification of relative species abundance, WGS data provided a stronger correlation between pollen grain proportion and sequence read proportion, but diverged more from a 1:1 relationship, likely due to the higher rate of false positives. Currently, a limitation of WGS-based pollen identification is the lack of representation of plant diversity in publicly available genome databases. As databases improve and costs drop, we expect that eventually genomics methods will become the methods of choice for species identification and quantification of mixed-species pollen samples.

Visualization of the seasonal shift of a variety of airborne pollens in western Tokyo

Airborne pollens cause pollinosis and have the potential to affect microphysics in clouds; however, the number of monitored species has been very limited due to technical difficulties for the morphotype identification. In this study, we applied an eDNA approach to the airborne pollen communities in the suburbs of the Tokyo metropolitan area in Japan, within a mixed urban, rural, and mountain landscape, revealing pollen seasonality of various taxa (a total of 78 families across the period) in the spring season (February to May). Those taxa distinctly shifted in the season, especially in the beginning of February and the middle of April. Air temperature shift was an obvious key factor to affect the airborne pollen community, while the influence of other meteorological factors, such as wind speed, humidity, and precipitation, was not clear. Taxonomic classification of major Amplicon Sequence Variants (ASVs) indicates multiple pollen sources, including natural forest, planted forest, roadside, park lands, and horticultural activities. Most major ASV belongs to Japanese cedar (Cryptomeria japonica), which is the most notable allergen that causes pollinosis in Japan, peaking in mid-February to March. Backward trajectory analysis of air masses suggests that the Japanese cedar and other Cupressaceae plantation forests in the western mountains were a significant source of airborne pollen communities detected at our sampling site. Other major plant pollen sources, including Japanese zelkova (Zelkova serrata) and ginkgo (Ginkgo biloba), emanated from the nearby parks or roadside regions. This study's approach enables us to visualize the phenology of multiple pollen, including timing and duration. Long-term monitoring of this type would provide additional insight into understanding the role of climate change on pollen transmission and links to flowering events.

Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches

Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable.

HPLC-UV, Metabarcoding and Genome Skims of Botanical Dietary Supplements: A Case Study in Echinacea

The use of DNA-based methods to authenticate botanical dietary supplements has been vigorously debated for a variety of reasons. More comparisons of DNA-based and chemical methods are needed, and concordant evaluation of orthogonal approaches on the same products will provide data to better understand the strengths and weaknesses of both approaches. The overall application of DNA-based methods is already firmly integrated into a wide array of continually modernizing stand alone and complementary authentication protocols. Recently, the use of full-length chloroplast genome sequences provided enhanced discriminatory capacity for closely related species of Echinacea compared to traditional DNA barcoding approaches (matK and rbcL). Here, two next-generation sequencing approaches were used: (1) genome skimming and (2) PCR amplicon (metabarcoding). The two genetic approaches were then combined with HPLC-UV to evaluate 20 commercially available dietary supplements of Echinacea representing "finished" products. The trade-offs involved in different DNA approaches were discussed, with a focus on how DNA methods support existing, accepted chemical methods. In most of the products (19/20), HPLC-UV suggested the presence of Echinacea spp. While metabarcoding was not useful with this genus and instead only resolved 7 products to the family level, genome skimming was able to resolve to species (9) or genus (1) with the 10/20 products where it was successful. Additional ingredients that HPLC-UV was unable to identify were also found in four products along with the relative sequence proportion of the constituents. Additionally, genome skimming was able to identify one product that was a different Echinacea species entirely.

DNA traces the origin of honey by identifying plants, bacteria and fungi

The regional origin of a food product commonly affects its value. To this, DNA-based identification of tissue remains could offer fine resolution. For honey, this would allow the usage of not only pollen but all plant tissue, and also that of microbes in the product, for discerning the origin. Here we examined how plant, bacterial and fungal taxa identified by DNA metabarcoding and metagenomics differentiate between honey samples from three neighbouring countries. To establish how the taxonomic contents of honey reflect the country of origin, we used joint species distribution modelling. At the lowest taxonomic level by metabarcoding, with operational taxonomic units, the country of origin explained the majority of variation in the data (70-79%), with plant and fungal gene regions providing the clearest distinction between countries. At the taxonomic level of genera, plants provided the most separation between countries with both metabarcoding and metagenomics. The DNA-based methods distinguish the countries more than the morphological pollen identification and the removal of pollen has only a minor effect on taxonomic recovery by DNA. As we find good resolution among honeys from regions with similar biota, DNA-based methods hold great promise for resolving honey origins among more different regions.

Generation of Chloroplast Molecular Markers to Differentiate Sophora toromiro and Its Hybrids as a First Approach to Its Reintroduction in Rapa Nui (Easter Island)

Sophora toromiro is an endemic tree of Rapa Nui with religious and cultural relevance that despite being extinct in the wild, still persists in botanical gardens and private collections around the world. The authenticity of some toromiro trees has been questioned because the similarities among hybrid lines leads to misclassification of the species. The conservation program of toromiro has the objective of its reinsertion into Rapa Nui, but it requires the exact genotyping and certification of the selected plants in order to efficiently reintroduce the species. In this study, we present for the first time the complete chloroplast genome of S. toromiro and four other Sophora specimens, which were sequenced de-novo and assembled after mapping the raw reads to a chloroplast database. The length of the chloroplast genomes ranges from 154,239 to 154,473 bp. A total of 130-143 simple sequence repeats (SSR) loci and 577 single nucleotide polymorphisms (SNPs) were identified.

Testing the effect of pollen exine rupture on metabarcoding with Illumina sequencing

Pollen metabarcoding has received much attention recently for its potential to increase taxonomic resolution of the identifications of pollen grains necessary for various public health, ecological and environmental inquiry. However, methodologies implemented are widely varied across studies confounding comparisons and casting uncertainty on the reliability of results. In this study, we investigated part of the methodology, the effects of level of exine rupture and lysis incubation time, on the performance of DNA extraction and Illumina sequencing. We examined 15 species of plants from 12 families with pollen that varies in size, shape, and aperture number to evaluate effort necessary for exine rupture. Then created mock communities of 14 of the species from DNA extractions at 4 levels of exine rupture (0, 33, 67, and 100%) and two levels of increased lysis incubation time without exine rupture (2 or 24 hours). Quantities of these DNA extractions displayed a positive correlation between increased rupture and DNA yield, however increasing time of lysis incubation was associated with decreased DNA yield. Illumina sequencing was performed with these artificial community treatments with three common plant DNA barcode regions (rbcL, ITS1, ITS2) with two different primer pairings for ITS2 and rbcL. We found decreased performance in treatments with 0% or 100% exine rupture compared to 33% and 67% rupture, based on deviation from expected proportions and species retrieval, and increased lysis incubation was found to be detrimental to results.

Microbiome and environment explain the absence of correlations between consumers and their diet in Bornean microsnails

Classical ecological theory posits that species partition resources such that each species occupies a unique resource niche. In general, the availability of more resources allows more species to co-occur. Thus, a strong relationship between communities of consumers and their resources is expected. However, correlations may be influenced by other layers in the food web, or by the environment. Here we show, by studying the relationship between communities of consumers (land snails) and individual diets (from seed plants), that there is in fact no direct, or at most a weak but negative, relationship. However, we found that the diversity of the individual microbiome positively correlates with both consumer community diversity and individual diet diversity in three target species. Moreover, these correlations were affected by various environmental variables, such as anthropogenic activity, habitat island size, and a possibly important nutrient source, guano runoff from nearby caves. Our results suggest that the microbiome and the environment explain the absence of correlations between diet and consumer community diversity. Hence, we advocate that microbiome inventories are routinely added to any community dietary analysis, which our study shows can be done with relatively little extra effort. Our approach presents the tools to quickly obtain an overview of the relationships between consumers and their resources. We anticipate our approach to be useful for ecologists and environmentalists studying different communities in a local food web.

Progress in the use of DNA barcodes in the identification and classification of medicinal plants

DNA barcoding is an emerging molecular identification and classification technology that has been applied to medicinal plants since 2008. The application of this technique has greatly ensured the safety and effectiveness of medicinal materials. In this paper, we review the application of DNA barcoding and some related technologies over the past 10 years with respect to improving our knowledge of medicinal plant identification and authentication. From single locus-based DNA barcodes to combined markers to genome-scale levels, DNA barcodes contribute more and more genetic information. At the same time, other technologies, such as high-resolution melting (HRM), have been combined with DNA barcoding. With the development of next-generation sequencing (NGS), metabarcoding technology has also been shown to identify species in mixed samples successfully. As a widely used and effective tool, DNA barcoding will become more useful over time in the field of medicinal plants.

Identifying the scene of a crime through pollen analysis

The forensic analysis of pollen involves the comparison of crime scene and reference pollen samples. Successful matches are frequently used to solve time- or location-related crimes. Despite its prospects in criminal investigation, forensic palynology is still underused in casework due to inherent shortcomings such as its limited evidential weighting, scarcity of skilled palynologists dedicated to forensic casework and the laborious nature of analytical procedures. To address these challenges, the current state-of-the-art in forensic palynology is transiting from the traditional light microscopic methods that dominated the early days of palynology to more contemporary approaches like Raman spectroscopy, stable isotope analysis and DNA metabarcoding. The major challenges of these methods, however, include a lack of optimisation to forensic expectations and the unavailability of robust databases to permit accurate data interpretation, and quests to resolve these problems constitute the theme of current research. While reiterating the usefulness of pollen analysis in criminal investigation, this report recommends orthogonal testing as a way of improving the evidential weighting of forensic palynology.

PLANiTS: a curated sequence reference dataset for plant ITS DNA metabarcoding

DNA metabarcoding combines DNA barcoding with high-throughput sequencing to identify different taxa within environmental communities. The ITS has already been proposed and widely used as universal barcode marker for plants, but a comprehensive, updated and accurate reference dataset of plant ITS sequences has not been available so far. Here, we constructed reference datasets of Viridiplantae ITS1, ITS2 and entire ITS sequences including both Chlorophyta and Streptophyta. The sequences were retrieved from NCBI, and the ITS region was extracted. The sequences underwent identity check to remove misidentified records and were clustered at 99% identity to reduce redundancy and computational effort. For this step, we developed a script called 'better clustering for QIIME' (bc4q) to ensure that the representative sequences are chosen according to the composition of the cluster at a different taxonomic level. The three datasets obtained with the bc4q script are PLANiTS1 (100 224 sequences), PLANiTS2 (96 771 sequences) and PLANiTS (97 550 sequences), and all are pre-formatted for QIIME, being this the most used bioinformatic pipeline for metabarcoding analysis. Being curated and updated reference databases, PLANiTS1, PLANiTS2 and PLANiTS are proposed as a reliable, pivotal first step for a general standardization of plant DNA metabarcoding studies. The bc4q script is presented as a new tool useful in each research dealing with sequences clustering. Database URL: https://github.com/apallavicini/bc4q; https://github.com/apallavicini/PLANiTS.

Plant DNA barcoding necessitates marker-specific efforts to establish more comprehensive reference databases

The problem of low species-level identification rates in plants by DNA barcoding is exacerbated by the fact that reference databases are far from being comprehensive. We investigate the impact of increased sampling depth on identification success by analyzing the efficacy of established plant barcode marker sequences (rbcL, matK, trnL-trnF, psbA-trnH, ITS). Adding sequences of the same species to the reference database led to an increase in correct species assignment of +10.9% for rbcL and +19.0% for ITS. Simultaneously, erroneous identification dropped from ∼40% to ∼12.5%. Despite its evolutionary constraints, ITS showed the highest identification rate and identification gain by increased sampling effort, which makes it a very suitable marker in the planning phase of a barcode study. The limited sequence availability of trnL-trnF is problematic for an otherwise very promising plastid plant barcoding marker. Future developments in machine learning algorithms have the potential to give new impetus to plant barcoding, but are dependent on extensive reference databases. We expect that our results will be incorporated into future plans for the development of DNA barcoding reference databases and will lead to these being developed with greater depth and taxonomic coverage.

Experimental quantification of pollen with DNA metabarcoding using ITS1 and trnL

Although the use of metabarcoding to identify taxa in DNA mixtures is widely approved, its reliability in quantifying taxon abundance is still the subject of debate. In this study we investigated the relationships between the amount of pollen grains in mock solutions and the abundance of high-throughput sequence reads and how the relationship was affected by the pollen counting methodology, the number of PCR cycles, the type of markers and plant species whose pollen grains have different characteristics. We found a significant positive relationship between the number of DNA sequences and the number of pollen grains in the mock solutions. However, better relationships were obtained with light microscopy as a pollen grain counting method compared with flow cytometry, with the chloroplastic trnL marker compared with ribosomal ITS1 and with 30 when compared with 25 or 35 PCR cycles. We provide a list of recommendations to improve pollen quantification.

Optimisation of a pollen DNA metabarcoding method for diet analysis of flying-foxes (Pteropus spp.)

Determining the diet of flying-foxes can increase understanding of how they function as pollinators and seed dispersers, as well as managing any negative impacts of large roosts. Traditional methods for diet analysis are time consuming, and not feasible to conduct for hundreds of animals. In this study, we optimised a method for diet analysis, based on DNA metabarcoding of environmental DNA (eDNA) from pollen and other plant parts in the faeces. We found that existing eDNA metabarcoding protocols are suitable, with the most useful results being obtained using a commercial food DNA extraction kit, and sequencing 350–450 base pairs of a DNA barcode from the internally transcribed spacer region (ITS2), with ~550 base pairs of the chloroplast rubisco large subunit (rbcL) as a secondary DNA barcode. A list of forage plants was generated for the little red flying-fox (Pteropus scapulatus), the black flying-fox (Pteropus alecto) and the spectacled flying-fox (Pteropus conspicillatus) from our collection sites across Queensland. The diets were determined to comprise predominantly Myrtaceae species, particularly those in the genera Eucalyptus, Melaleuca and Corymbia. With more plant genomes becoming publicly available in the future, there are likely to be further applications of eDNA methods in understanding the role of flying-foxes as pollinators and seed dispersers.

Categorization of species as native or nonnative using DNA sequence signatures without a complete reference library

New genetic diagnostic approaches have greatly aided efforts to document global biodiversity and improve biosecurity. This is especially true for organismal groups in which species diversity has been underestimated historically due to difficulties associated with sampling, the lack of clear morphological characteristics, and/or limited availability of taxonomic expertise. Among these methods, DNA sequence barcoding (also known as "DNA barcoding") and by extension, meta-barcoding for biological communities, has emerged as one of the most frequently utilized methods for DNA-based species identifications. Unfortunately, the use of DNA barcoding is limited by the availability of complete reference libraries (i.e., a collection of DNA sequences from morphologically identified species), and by the fact that the vast majority of species do not have sequences present in reference databases. Such conditions are critical especially in tropical locations that are simultaneously biodiversity rich and suffer from a lack of exploration and DNA characterization by trained taxonomic specialists. To facilitate efforts to document biodiversity in regions lacking complete reference libraries, we developed a novel statistical approach that categorizes unidentified species as being either likely native or likely nonnative based solely on measures of nucleotide diversity. We demonstrate the utility of this approach by categorizing a large sample of specimens of terrestrial insects and spiders (collected as part of the Moorea BioCode project) using a generalized linear mixed model (GLMM). Using a training data set of known endemic (n = 45) and known introduced species (n = 102), we then estimated the likely native/nonnative status for 4,663 specimens representing an estimated 1,288 species (412 identified species), including both those specimens that were either unidentified or whose endemic/introduced status was uncertain. Using this approach, we were able to increase the number of categorized specimens by a factor of 4.4 (from 794 to 3,497), and the number of categorized species by a factor of 4.8 from (147 to 707) at a rate much greater than chance (77.6% accuracy). The study identifies phylogenetic signatures of both native and nonnative species and suggests several practical applications for this approach including monitoring biodiversity and facilitating biosecurity.

Wild Bee Pollen Usage and Microbial Communities Co-vary Across Landscapes

Bees forage for pollen and nectar at flowers but simultaneously acquire pathogenic, commensal, and likely beneficial microbes from these same flowers. Characterizing pollen usage of wild bees is therefore crucial to their conservation yet remains a challenging task. To understand pollen usage across landscapes and how this affects microbial communities found in the pollen provisions collected from flowers, we studied the generalist small carpenter bee Ceratina australensis. We collected C. australensis nests from three different climatic zones across eastern and southern Australia. To characterize the plant, fungal, and bacterial composition of these pollen provisions, we used a metabarcoding and next-generation sequencing approach. We found that the species richness of plant types, fungi, and bacteria was highest in a subtropical zone compared to a temperate or a grassland zone. The composition of these communities also differentiated by zone, particularly in pollen composition and fungal communities. Moreover, pollen composition strongly correlated with fungal community composition, suggesting that variation in pollen usage across landscapes results in variation in microbial communities. While how these pollen usage and microbial community patterns affect bee health merits additional work, these data further our understanding of how flowering plant community composition affects not only the pollen usage of a generalist bee but also its associated microbial communities.

Generalisation and specialisation in hoverfly (Syrphidae) grassland pollen transport networks revealed by DNA metabarcoding

Pollination by insects is a key ecosystem service and important to wider ecosystem function. Most species-level pollination networks studied have a generalised structure, with plants having several potential pollinators, and pollinators in turn visiting a number of different plant species. This is in apparent contrast to a plant's need for efficient conspecific pollen transfer. The aim of this study was to investigate the structure of pollen transport networks at three levels of biological hierarchy: community, species and individual. We did this using hoverflies in the genus Eristalis, a key group of non-Hymenopteran pollinators. We constructed pollen transport networks using DNA metabarcoding to identify pollen. We captured hoverflies in conservation grasslands in west Wales, UK, removed external pollen loads, sequenced the pollen DNA on the Illumina MiSeq platform using the standard plant barcode rbcL, and matched sequences using a pre-existing plant DNA barcode reference library. We found that Eristalis hoverflies transport pollen from 65 plant taxa, more than previously appreciated. Networks were generalised at the site and species level, suggesting some degree of functional redundancy, and were more generalised in late summer compared to early summer. In contrast, pollen transport at the individual level showed some degree of specialisation. Hoverflies defined as "single-plant visitors" varied from 40% of those captured in early summer to 24% in late summer. Individual hoverflies became more generalised in late summer, possibly in response to an increase in floral resources. Rubus fruticosus agg. and Succisa pratensis were key plant species for hoverflies at our sites Our results contribute to resolving the apparent paradox of how generalised pollinator networks can provide efficient pollination to plant species. Generalised hoverfly pollen transport networks may result from a varied range of short-term specialised feeding bouts by individual insects. The generalisation and functional redundancy of Eristalis pollen transport networks may increase the stability of the pollination service they deliver.

Minimizing polymerase biases in metabarcoding

DNA metabarcoding is an increasingly popular method to characterize and quantify biodiversity in environmental samples. Metabarcoding approaches simultaneously amplify a short, variable genomic region, or "barcode," from a broad taxonomic group via the polymerase chain reaction (PCR), using universal primers that anneal to flanking conserved regions. Results of these experiments are reported as occurrence data, which provide a list of taxa amplified from the sample, or relative abundance data, which measure the relative contribution of each taxon to the overall composition of amplified product. The accuracy of both occurrence and relative abundance estimates can be affected by a variety of biological and technical biases. For example, taxa with larger biomass may be better represented in environmental samples than those with smaller biomass. Here, we explore how polymerase choice, a potential source of technical bias, might influence results in metabarcoding experiments. We compared potential biases of six commercially available polymerases using a combination of mixtures of amplifiable synthetic sequences and real sedimentary DNA extracts. We find that polymerase choice can affect both occurrence and relative abundance estimates and that the main source of this bias appears to be polymerase preference for sequences with specific GC contents. We further recommend an experimental approach for metabarcoding based on results of our synthetic experiments.

Pollination implications of the diverse diet of tropical nectar-feeding bats roosting in an urban cave

Background

Intense landscaping often alters the plant composition in urban areas. Knowing which plant species that pollinators are visiting in urban areas is necessary for understanding how landscaping impacts biodiversity and associated ecosystem services. The cave nectar bat, Eonycteris spelaea, is an important pollinator for many plants and is often recorded in human-dominated habitats. Previous studies of the diet of E. spelaea relied on morphological identification of pollen grains found in faeces and on the body of bats and by necessity disregarded other forms of digested plant material present in the faeces (i.e., plant juice and remnants). The main objective of this study was to examine the diet of the nectarivorous bat, E. spelaea, roosting in an urban cave at Batu Caves, Peninsular Malaysia by identifying the plant material present in the faeces of bats using DNA metabarcoding.

Methods

Faeces were collected under the roost of E. spelaea once a week from December 2015 to March 2016. Plant DNA was extracted from the faeces, Polymerase chain reaction (PCR) amplified at ITS2 and rbcL regions and mass sequenced. The resultant plant operational taxonomic units were searched against NCBI GenBank for identification.

Results

A total of 55 species of plants were detected from faeces of E. spelaea including Artocarpus heterophyllus, Duabanga grandiflora and Musa spp. which are likely to be important food resources for the cave nectar bat.

Discussion

Many native plant species that had not been reported in previous dietary studies of E. spelaea were detected in this study including Bauhinia strychnoidea and Urophyllum leucophlaeum, suggesting that E. spelaea remains a crucial pollinator for these plants even in highly disturbed habitats. The detection of many introduced plant species in the bat faeces indicates that E. spelaea are exploiting them, particularly Xanthostemon chrysanthus, as food resources in urban area. Commercial food crops were detected from all of the faecal samples, suggesting that E. spelaea feed predominantly on the crops particularly jackfruit and banana and play a significant role in pollination of economically important plants. Ferns and figs were also detected in the faeces of E. spelaea suggesting future research avenues to determine whether the 'specialised nectarivorous' E. spelaea feed opportunistically on other parts of plants.

Pollen sleuthing for terrestrial plant surveys: Locating plant populations by exploiting pollen movement

PREMISE OF THE STUDY

We present an innovative technique for sampling, identifying, and locating plant populations that release pollen, without extensive ground surveys. This method (1) samples pollen at random locations within the target species' habitat, (2) detects species' presence using morphological pollen analysis, and (3) uses kriging to predict likely locations of populations to focus future search efforts.

METHODS

To demonstrate, we applied the pollen sleuthing system to search for artificially constructed populations of Brassica rapa in an old field. Population size varied from 0-100 flowers labeled with artificial pollen (paint pellets). After characterizing the landscape, we pan-trapped 2762 potential insect vectors from random locations across the field and washed particulate matter from their bodies to assess artificial pollen abundance with a microscope.

RESULTS

Population size greatly influenced artificial pollen detection success; following random pollen trap sampling and interpolation, ground surveys would be best focused on identified areas with high pollen density and low variation in pollen density. Sampling sites most successfully detected artificial pollen when they were located at higher elevations, near showy flowering plants that were not grasses.

DISCUSSION

Detection of nascent populations using the proposed system is possible but accuracy will depend on local environmental factors (e.g., wind, elevation). Conservation and invasive species control programs may be improved by using this approach.

DNA metabarcoding data unveils invisible pollination networks

Animal pollination, essential for both ecological services and ecosystem functioning, is threatened by ongoing global changes. New methodologies to decipher their effects on pollinator composition to ecosystem health are urgently required. We compare the main structural parameters of pollination networks based on DNA metabarcoding data with networks based on direct observations of insect visits to plants at three resolution levels. By detecting numerous additional hidden interactions, metabarcoding data largely alters the properties of the pollination networks compared to visit surveys. Molecular data shows that pollinators are much more generalist than expected from visit surveys. However, pollinator species were composed of relatively specialized individuals and formed functional groups highly specialized upon floral morphs. We discuss pros and cons of metabarcoding data relative to data obtained from traditional methods and their potential contribution to both current and future research. This molecular method seems a very promising avenue to address many outstanding scientific issues at a resolution level which remains unattained to date; especially for those studies requiring pollinator and plant community investigations over macro-ecological scales.

Using herbarium-derived DNAs to assemble a large-scale DNA barcode library for the vascular plants of Canada

PREMISE OF THE STUDY

Constructing complete, accurate plant DNA barcode reference libraries can be logistically challenging for large-scale floras. Here we demonstrate the promise and challenges of using herbarium collections for building a DNA barcode reference library for the vascular plant flora of Canada.

METHODS

Our study examined 20,816 specimens representing 5076 of 5190 vascular plant species in Canada (98%). For 98% of the specimens, at least one of the DNA barcode regions was recovered from the plastid loci rbcL and matK and from the nuclear ITS2 region. We used beta regression to quantify the effects of age, type of preservation, and taxonomic affiliation (family) on DNA sequence recovery.

RESULTS

Specimen age and method of preservation had significant effects on sequence recovery for all markers, but influenced some families more (e.g., Boraginaceae) than others (e.g., Asteraceae).

DISCUSSION

Our DNA barcode library represents an unparalleled resource for metagenomic and ecological genetic research working on temperate and arctic biomes. An observed decline in sequence recovery with specimen age may be associated with poor primer matches, intragenomic variation (for ITS2), or inhibitory secondary compounds in some taxa.

Applying pollen DNA metabarcoding to the study of plant-pollinator interactions

PREMISE OF THE STUDY

To study pollination networks in a changing environment, we need accurate, high-throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative to field observations. DNA metabarcoding potentially allows for faster and finer-scale taxonomic resolution of pollen compared to traditional approaches (e.g., light microscopy), but has not been applied to pollination networks.

METHODS

We sampled pollen from 38 bee species collected in Florida from sites differing in forest management. We isolated DNA from pollen mixtures and sequenced rbcL and ITS2 gene regions from all mixtures in a single run on the Illumina MiSeq platform. We identified species from sequence data using comprehensive rbcL and ITS2 databases.

RESULTS

We successfully built a proof-of-concept quantitative pollination network using pollen metabarcoding.

DISCUSSION

Our work underscores that pollen metabarcoding is not quantitative but that quantitative networks can be constructed based on the number of interacting individuals. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. DNA metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen, and we expect that it will have broad utility for future studies of plant-pollinator interactions.