Dataset Information

Using metabarcoding to compare the suitability of two blood-feeding leech species for sampling mammalian diversity in North Borneo.

ABSTRACT: The application of high-throughput sequencing (HTS) for metabarcoding of mixed samples offers new opportunities in conservation biology. Recently, the successful detection of prey DNA from the guts of leeches has raised the possibility that these, and other blood-feeding invertebrates, might serve as useful samplers of mammals. Yet little is known about whether sympatric leech species differ in their feeding preferences, and whether this has a bearing on their relative suitability for monitoring local mammalian diversity. To address these questions, we collected spatially matched samples of two congeneric leech species Haemadipsa picta and Haemadipsa sumatrana from lowland rainforest in Borneo. For each species, we pooled ~500 leeches into batches of 10 individuals, performed PCR to target a section of the mammalian 16S rRNA locus and undertook sequencing of amplicon libraries using an Illumina MiSeq. In total, we identified sequences from 14 mammalian genera, spanning nine families and five orders. We found greater numbers of detections, and higher diversity of OTUs, in H. picta compared with H. sumatrana, with rodents only present in the former leech species. However, comparison of samples from across the landscape revealed no significant difference in mammal community composition between the leech species. We therefore suggest that H. picta is the more suitable iDNA sampler in this degraded Bornean forest. We conclude that the choice of invertebrate sampler can influence the detectability of different mammal groups and that this should be accounted for when designing iDNA studies.

SUBMITTER: Drinkwater R

PROVIDER: S-EPMC7379310 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using metabarcoding to compare the suitability of two blood-feeding leech species for sampling mammalian diversity in North Borneo.

Drinkwater Rosie R Schnell Ida Baerholm IB Bohmann Kristine K Bernard Henry H Veron Géraldine G Clare Elizabeth E Gilbert M Thomas P MTP Rossiter Stephen J SJ

Molecular ecology resources 20181016 1

The application of high-throughput sequencing (HTS) for metabarcoding of mixed samples offers new opportunities in conservation biology. Recently, the successful detection of prey DNA from the guts of leeches has raised the possibility that these, and other blood-feeding invertebrates, might serve as useful samplers of mammals. Yet little is known about whether sympatric leech species differ in their feeding preferences, and whether this has a bearing on their relative suitability for monitoring ...[more]

PMID: 30225935

Similar Datasets

Project description:Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are used independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy. We sought to understand how different data types can influence HSMs using three bat species (Lasiurus borealis, Lasiurus cinereus, and Perimyotis subflavus). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias. For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models preformed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias. Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another.

Project description:DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high-throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTUs), losing information on intraspecific diversity in the process. While Cytochrome c oxidase subunit I (COI) haplotype information is limited in resolving intraspecific diversity it is nevertheless often useful e.g. in a phylogeographic context, helping to formulate hypotheses on taxon distribution and dispersal.This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotype information from freshwater macroinvertebrate metabarcoding datasets. This novel approach was added to the R package "JAMP" and can be applied to COI amplicon datasets. We tested our haplotyping method by sequencing (i) a single-species mock community composed of 31 individuals with 15 different haplotypes spanning three orders of magnitude in biomass and (ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates.We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177-200 OTUs, each containing an average of 2.40-3.30 haplotypes per OTU. The derived intraspecific diversity data showed population structures that were consistent between replicates and similar between primer pairs but resolution depended on the primer length. A closer look at abundant taxa in the dataset revealed various population genetic patterns, e.g. the stonefly Taeniopteryx nebulosa and the caddisfly Hydropsyche pellucidula showed a distinct north-south cline with respect to haplotype distribution, while the beetle Oulimnius tuberculatus and the isopod Asellus aquaticus displayed no clear population pattern but differed in genetic diversity.We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate metabarcoding data. It needs to be stressed that at this point this metabarcoding-informed haplotyping is not capable of capturing the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding datasets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about species diversity but also underlying genetic diversity.

Project description:BackgroundThe heterogeneous nature of environmental DNA (eDNA) and its effects on species detection and community composition estimates has been highlighted in several studies in the past decades. Mostly in the context of spatial distribution over large areas, in fewer occasions looking at spatial distribution within a single body of water. Temporal variation of eDNA, similarly, has mostly been studied as seasonality, observing changes over large periods of time, and often only for small groups of organisms such as fish and amphibians.MethodsWe analyzed and compared small-scale spatial and temporal variation by sampling eDNA from two small, isolated dune lakes for 20 consecutive weeks. Metabarcoding was performed on the samples using generic COI primers. Molecular operational taxonomic unit (MOTUs) were used to assess dissimilarities between spatial and temporal replicates.ResultsOur results show large differences between samples taken within one lake at one point in time, but also expose the large differences between temporal replicates, even those taken only 1 week apart. Furthermore, between-site dissimilarities showed a linear correlation with time frame, indicating that between-site differences will be inflated when samples are taken over a period of time. We also assessed the effects of PCR replicates and processing strategies on general patterns of dissimilarity between samples. While more inclusive PCR replicate strategies lead to higher richness estimations, dissimilarity patterns between samples did not significantly change.ConclusionsWe conclude that the dissimilarity of temporal replicates at a 1 week interval is comparable to that of spatial replicate samples. It increases, however, for larger time intervals, which suggests that population turnover effects can be stronger than community heterogeneity. Spatial replicates alone may not be enough for optimal recovery of taxonomic diversity, and cross-comparisons of different locations are susceptible to inflated dissimilarities when performed over larger time intervals. Many of the observed MOTUs could be classified as either phyto- or zooplankton, two groups that have gained traction in recent years as potential novel bio-indicator species. Our results, however, indicate that these groups might be susceptible to large community shifts in relatively short periods of time, highlighting the need to take temporal variations into consideration when assessing their usability as water quality indicators.

Dataset Information

Using metabarcoding to compare the suitability of two blood-feeding leech species for sampling mammalian diversity in North Borneo.

Publications

Using metabarcoding to compare the suitability of two blood-feeding leech species for sampling mammalian diversity in North Borneo.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets