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Hartop, E.

Publications and source records attributed to Hartop, E..

9 recordsLinked to original sources

Accuracy of occurrence and abundance estimates from insect metabarcoding

1. DNA metabarcoding--high-throughput sequencing of barcode regions from bulk samples--has become a key tool for insect biodiversity assessment. Yet, how methodological choices affect the accuracy of metabarcoding data remains insufficiently explored. In this paper, we ask: (1) How does the lysis method (non-destructive lysis vs. destructive homogenization) affect community recovery? (2) How comprehensively does metabarcoding capture species richness? (3) To what extent can spike-ins improve abundance estimates? (4) How accurately can species abundances be estimated? 2. We evaluated the accuracy of insect metabarcoding using 4,749 bulk samples from a large-scale biodiversity survey subjected to mild lysis. Of these samples, 856 were also homogenized, allowing a systematic comparison of the effect of alternative treatments. To potentially improve abundance estimates, we added six biological spike-ins (i.e., foreign insects) to all samples, and two synthetic spike-ins (artificial DNA fragments) to the homogenization treatment. In addition, we established the contents of 15 samples by individually barcoding all specimens, enabling direct assessment of occurrence and abundance estimates. 3. Our results revealed consistent differences between destructive and non-destructive treatments. While both methods reliably detected the majority of species, small and soft-bodied taxa were more often recovered after mild lysis than after homogenization, while the reverse was true for heavily sclerotized, hairy, and large taxa. Using biological spike-ins for calibration reduced the variance in read numbers per specimen considerably, especially in homogenized samples, while synthetic spike-ins were less effective. In a Bayesian analysis, where species data were matched to the best-fitting spike-in calibration curve, accurate abundance estimates (+/-1 individual) were obtained for 72.9% of species occurrences. 4. Our results show that it is possible to obtain reasonably accurate abundance estimates from metabarcoding data, and that mild lysis and homogenization result in different taxon-specific biases in terms of occurrence data, with neither method outperforming the other. Accuracy is improved by homogenization rather than mild lysis of samples, and by the use of biological rather than synthetic spike-ins. Together, these findings provide a major step towards robust, quantitative biodiversity monitoring using DNA-metabarcoding.

zoology↗

Automated Specimen Triage for Dark Taxa: Deep Learning Enables Orientation, Sex Identification, and Anatomical Segmentation from Robotic Imaging

Robotic specimen processing is transforming biodiversity discovery by replacing labor-intensive handling with scalable systems that can simultaneously generate high-quality specimen images. We demonstrate that these images can be leveraged by deep learning to efficiently extract key biological information and guide targeted specimen processing. Using a model dark taxon, the Phoridae (Diptera), the workflow performs three core tasks: sex identification, specimen orientation classification, and anatomical segmentation. Sex identification allows selective retention of diagnostically informative specimens, avoiding wasted effort on non-diagnostic individuals. Orientation classification enables specimens in the desired orientation to proceed immediately, while suboptimally oriented specimens can be repositioned for informative processing. Anatomical segmentation allows targeted processing of specimens displaying diagnostic characters or targeted analysis of specific anatomical regions in subsequent workflow steps. Comparative analysis of model architectures shows task-specific selection is crucial: a Convolutional Neural Network achieved an accuracy of 0.94 for orientation, a Vision Transformer achieved 0.88 for sex, and a U-Net precisely segmented nine anatomical regions with a mean IoU of 0.78. These results demonstrate that robotic imaging combined with deep learning provides a validated foundation for high-throughput, targeted specimen processing, maximising efficiency and utility for taxonomic and trait-based analyses, and supporting scalable, sustainable biodiversity workflows.

bioinformatics↗

What lurks beneath the humped back? - The patterns of bacterial abundance, diversity and distribution across communities of a dipteran family

Symbiotic microorganisms can profoundly impact insects, their life history traits, population dynamics, and evolutionary trajectories. However, microbiota remain poorly understood in natural insect communities, especially in dark taxa - i.e., hyperdiverse, yet understudied clades. Here, we implemented a novel multi-target amplicon sequencing approach to study microbiota in complex, species-rich communities. It combines four methodological innovations: (1) To establish a host taxonomic framework, we sequenced amplicons of the host marker gene (COI) and reconstructed barcodes alongside microbiota characterisation. (2) To assess microbiota abundance, we incorporated spike-in-based quantification. (3) To improve the phylogenetic resolution for the dominant endosymbiont, Wolbachia, we analysed bycatch data from the COI amplicon sequencing. (4) To investigate the primary drivers of host-microbe associations in massive multi-dimensional datasets, we performed HMSC modelling. Applying this approach to 1,842 wild-caught scuttle flies (Diptera: Phoridae) from northern Sweden, we organised them into 480 genotypes and 186 species and gained unprecedented insights into their microbiota. We found orders-of-magnitude differences in bacterial abundance and massive within-population variation in microbiota composition. Patterns and drivers differed among microbial functional categories: the distribution and abundance of facultative endosymbionts (Wolbachia, Rickettsia, Spiroplasma) were shaped by host species, genotype and sex. In contrast, many other bacterial taxa were broadly distributed across species and sites. This study highlights facultative endosymbionts as key players in insect microbiota and reveals striking variations in distributional patterns of microbial clades. It also demonstrates the power of integrative sequencing approaches in uncovering the ecological complexity and significance of symbiotic microorganisms in multi-species natural communities.

ecology↗

RESOLVING BIOLOGY'S DARK MATTER: SPECIES RICHNESS, SPATIOTEMPORAL DISTRIBUTION, AND COMMUNITY COMPOSITION OF A DARK TAXON

BackgroundZoologys dark matter comprises hyperdiverse, poorly known taxa that are numerically dominant but largely unstudied, even in temperate regions where charismatic taxa are well understood. It is everywhere, but high diversity, abundance, and small size have historically stymied its study. We demonstrate how entomological dark matter can be elucidated using high-throughput DNA barcoding ("megabarcoding"). We reveal the high abundance and diversity of scuttle flies (Diptera: Phoridae) in Sweden using 31,800 specimens from 37 sites across four seasonal periods. We investigate the number of scuttle fly species in Sweden and the environmental factors driving community changes across time and space. ResultsSwedish scuttle fly diversity is much higher than previously known, with 549 mOTUs (putative species) detected, compared to 374 previously recorded species. Hierarchical Modelling of Species Communities reveals that scuttle fly communities are highly structured by latitude and strongly driven by climatic factors. Large dissimilarities between sites and seasons are driven by turnover rather than nestedness. Climate changes are predicted to significantly affect the 47% of species that show significant responses to mean annual temperature. Results were robust whether using haplotype diversity or species-proxies (mOTUs) as response variables. Additionally, species-level models of common taxa adequately predict overall species richness. ConclusionsUnderstanding the bulk of the diversity around us is imperative during an era of biodiversity loss. We show that dark insect taxa can be efficiently characterized and surveyed with megabarcoding. Undersampling of rare taxa and choice of operational taxonomic units do not alter the main ecological inferences, making it an opportune time to tackle zoologys dark matter.

ecology↗

Express barcoding with NextGenPCR and MinION for species-level sorting of ecological samples

O_LIDNA barcodes are useful for species-level sorting of specimen samples, but rarely used in time-sensitive projects that require species richness estimates or identification of pest or invasive species within hours. The main reason is that existing express barcoding workflows are either too expensive or can only be carried out in very well equipped laboratories by highly trained staff. C_LIO_LIWe here introduce a simple workflow that combines rapid DNA extraction with HotSHOT, amplicon production with the aid of NextGenPCR(R) thermocyclers, and sequencing with low-cost MinION sequencers. C_LIO_LIWe demonstrate the power of the approach by generating and identifying 250 barcodes for 285 specimens within 6 hours. The workflow only required the following major equipment that easily fits onto a lab bench: Conventional thermocycler, NextGenPCR(R) thermocycler, microplate sealer, Qubit, and MinION. C_LIO_LIWe argue that species-level sorting with simplified barcoding workflows is now faster, more accurate, and sufficiently cost-effective that it can and should replace morphospecies sorting in many projects. C_LI

ecology↗

A re-analysis of the data in Sharkey et al.'s (2021) minimalist revision reveals that BINs do not deserve names, but BOLD Systems needs a stronger commitment to open science

Halting biodiversity decline is one of the most critical challenges for humanity, but monitoring biodiversity is hampered by taxonomic impediments. One impediment is the large number of undescribed species (here called "dark taxon impediment") while another is caused by the large number of superficial species descriptions which can only be resolved by consulting type specimens ("superficial description impediment"). Recently, Sharkey et al. (2021) proposed to address the dark taxon impediment for Costa Rican braconid wasps by describing 403 species based on barcode clusters ("BINs") computed by BOLD Systems. More than 99% of the BINs (387 of 390) are converted into species by assigning binominal names (e.g., BIN "BOLD:ACM9419" becomes Bracon federicomatarritai) and adding a minimal diagnosis (usually consisting only of a consensus barcode). We here show that many of Sharkey et al.s species are unstable when the underlying data are analyzed using different species delimitation algorithms. Add the insufficiently informative diagnoses, and many of these species will become the next "superficial description impediment" for braconid taxonomy because they will have to be tested and redescribed after obtaining sufficient evidence for confidently delimiting species. We furthermore show that Sharkey et al.s approach of using consensus barcodes as diagnoses is not functional because it cannot be consistently applied. Lastly, we reiterate that COI alone is not suitable for delimiting and describing species and voice concerns over Sharkey et al.s uncritical use of BINs because they are calculated by a proprietary algorithm (RESL) that uses a mixture of public and private data. We urge authors, reviewers, and editors to maintain high standards in taxonomy by only publishing new species that are rigorously delimited with open-access tools and supported by publicly available evidence.

evolutionary biology↗

Large-scale Integrative Taxonomy (LIT): resolving the data conundrum for dark taxa

New, rapid, accurate, scalable, and cost-effective species discovery and delimitation methods are needed for tackling "dark taxa", that we here define as clades for which <10% of all species are described and the estimated diversity exceeds 1000 species. Species delimitation for these taxa should be based on multiple data sources ("integrative taxonomy") but collecting multiple types of data risks impeding a discovery process that is already too slow. We here develop explicit methods to avoid this by applying Large-scale Integrative Taxonomy (LIT). Preliminary species hypotheses are generated based on inexpensive data that are obtained quickly and cost-effectively in a technical exercise. The validation step is then based on a more expensive type of data that are only obtained for specimens selected based on objective criteria. We here use this approach to sort 18 000 scuttle flies (Diptera: Phoridae) from Sweden into 315 preliminary species hypotheses based on NGS barcode (313bp) clusters. These clusters were subsequently tested with morphology and used to develop quantitative indicators for predicting which barcode clusters are in conflict with morphospecies. For this purpose, we first randomly selected 100 clusters for in-depth validation with morphology. Afterwards, we used a linear model to demonstrate that the best predictors for conflict between barcode clusters and morphology are maximum p-distance within the cluster and cluster stability across different clustering thresholds. A test of these indicators using the 215 remaining clusters reveals that these predictors correctly identify all clusters that conflict with morphology. The morphological validation step in our study involved only 1 039 specimens (5.8% of all specimens), but a newly proposed simplified protocol would only require the study of 915 (5.1%: 2.5 specimens per species), as we show that clusters without signatures of incongruence can be validated by only studying two specimens representing the most divergent haplotypes. To test the generality of our results across different barcode clustering techniques, we establish that the levels of conflict are similar across Objective Clustering (OC), Automatic Barcode Gap Discovery (ABGD), Poisson Tree Processes (PTP) and Refined Single Linkage (RESL) (used by Barcode of Life Data System (BOLD) to assign Barcode Index Numbers (BINs)). OC and ABGD achieved a maximum congruence score with morphology of 89% while PTP was slightly less effective (84%). RESL could only be tested for a subset of the specimens because the algorithm is not public. BINs based on 277 of the original 1 714 haplotypes were 86% congruent with morphology while the values were 89% for OC, 74% for PTP, and 72% for ABGD.

evolutionary biology↗

MinION barcodes: biodiversity discovery and identification by everyone, for everyone

BackgroundDNA barcodes are a useful tool for discovering, understanding, and monitoring biodiversity which are critical tasks at a time of rapid biodiversity loss. However, widespread adoption of barcodes requires cost-effective and simple barcoding methods. We here present a workflow that satisfies these conditions. It was developed via "innovation through subtraction" and thus requires minimal lab equipment, can be learned within days, reduces the barcode sequencing cost to <10 cents, and allows fast turnaround from specimen to sequence by using the portable, real-time sequencer MinION. ResultsWe describe cost-effective and rapid procedures for barcoding individual specimens with MinION sequencing. We illustrate how tagged amplicons can be obtained and sequenced with the portable, real-time MinION sequencer in many settings (field stations, biodiversity labs, citizen science labs, schools). We also provide amplicon coverage recommendations that are based on several runs of the latest generation of MinION flow cells ("R10.3") which suggest that each run can generate barcodes for >10,000 specimens. Next, we present a novel software, ONTbarcoder, which overcomes the bioinformatics challenges posed by MinION reads. The software is compatible with Windows 10, Macintosh, and Linux, has a graphical user interface (GUI), and can generate thousands of barcodes on a standard laptop within hours based on only two input files (FASTQ, demultiplexing file). We document that MinION barcodes are virtually identical to Sanger and Illumina barcodes for the same specimens (>99.99%) and provide evidence that MinION flow cells and reads have improved rapidly since 2018. ConclusionsWe propose that barcoding with MinION is the way forward for government agencies, universities, museums, and schools because it combines low consumable and capital cost with scalability. Small projects can use the flow cell dongle ("Flongle") while large projects can rely on MinION flow cells that can be stopped and re-used after collecting sufficient data for a given project.

ecology↗

1D MinION sequencing for large-scale species discovery: 7000 scuttle flies (Diptera: Phoridae) from one site in Kibale National Park (Uganda) revealed to belong to >650 species

BackgroundMore than 80% of all animal species remain unknown to science. Most of these species live in the tropics and belong to animal taxa that combine small body size with high specimen abundance and large species richness. For such clades, using morphology for species discovery is slow because large numbers of specimens must be sorted using detailed microscopic investigations. Fortunately, species discovery could be greatly accelerated if DNA sequences could be used for sorting specimens to species. Morphological verification of such \"molecular Operational Taxonomic Units\" (mOTUs) could then be based on dissection of a small subset of specimens. However, this approach requires cost-effective and low-tech DNA barcoding techniques because well equipped, well-funded molecular laboratories are not readily available in many biodiverse countries.\n\nResultsWe here document how MinION sequencing can be used for large-scale species discovery in a specimen- and species-rich taxon like the hyper-diverse fly family Phoridae (Diptera). We sequenced 7,059 specimens collected in a single Malaise trap in Kibale National Park, Uganda over the short period of eight weeks. We discovered >650 species which exceeded the number of phorid species currently described for the entire Afrotropical region. The barcodes were obtained using an improved low-cost MinION pipeline that increased the barcoding capacity sevenfold from 500 to 3,500 barcodes per flowcell. This was achieved by adopting 1D sequencing, re-sequencing weak amplicons on a used flowcell, and improving demultiplexing. Comparison with Illumina data revealed that the MinION barcodes were very accurate (99.99% accuracy, 0.46% Ns) and thus yielded very similar species units (match ratio: 0.991). Morphological examination of 100 mOTUs also confirmed good congruence with morphology (93% of mOTUs; >99% of specimens) and revealed that 90% of the putative species belong to a neglected, megadiverse genus (Megaselia). We demonstrate for one Megaselia species how the molecular data can guide the description of a new species (Megaselia sepsioides sp. nov.).\n\nConclusionsWe document that one field site in Africa can be home to an estimated 1000 species of phorids and speculate that the Afrotropical diversity could exceed 100,000 species. We furthermore conclude that low-cost MinION sequencers are very suitable for reliable, rapid, and large-scale species discovery in hyperdiverse taxa. MinION sequencing could quickly reveal the extent of the unknown diversity and is especially suitable for biodiverse countries with limited access to capital-intensive sequencing facilities.

evolutionary biology↗