Morphology-based Identification Research Articles

The anthropogenic threat for insular microcrustacean fauna (Copepoda and Cladocera) – the case of Madeira Island

Substantial loss of biodiversity and the proliferation of invasive alien species can occur due to land cover anthropogenic transformations on islands. However, the effect of anthropogenic habitat modifications on the distribution of insular freshwater microcrustaceans is unknown. In the present paper, we examine the consequences of human activity on the insular diversity of microcrustaceans in the context of the theories of island biogeography and intermediate disturbances. The samples were collected in Madeira Island at 38 freshwater sampling sites with different anthropopressure. Morphology-based species identification of the copepods and cladocerans was supplemented with genetic analysis (COI) in some species. To estimate the species richness of the island, rarefaction, and extrapolation methods were used. Canonical Correspondence Analysis (CCA) was applied to assess the influence of geospatial and environmental variables on the species distribution. A total of 20 species belonging to six families were identified, of which 16 species are new to Madeira. There was low similarity between the fauna recorded and known previously on the island. The observed species richness was higher than the predictions by the island biogeography models for Madeira. CCA revealed a strong influence of anthropogenic land use on crustaceans. Anthropogenic transformations locally led to the depletion of fauna, but on the island scale they contributed to the increase of species richness including seven putative alien species. An increase in the artificial land cover and a decrease in the forest areas could lead to a further shift in the domination of non-indigenous microcrustaceans.

Integrative description of two new species and two new subspecies of Lamprospilus Geyer (Lepidoptera: Lycaenidae)

Lamprospilus stegmaier Prieto & Faynel sp. nov. is described from five specimens collected in sympatry with L. nicetus C. Felder & R. Felder on the northern central range of the Colombian Andes. Lamprospilus bicolor Faynel & Prieto sp. nov. is described from specimens collected in Colombia, Peru and Bolivia. Lamprospilus bicolor mirador Faynel & Prieto ssp. nov. is described from specimens collected in Peru and Bolivia. Lamprospilus decorata valluna Prieto & Faynel ssp. nov. is described from specimens collected in Western Colombia. Male and female phenotypes are associated, and we present morphological and molecular diagnostic characters for the new species. We also evaluate the congruence between a priori morphology-based species identifications and Molecular Operational Taxonomic Units (MOTUs) delimitations based on Barcode Index Numbers (BINs) in the genus. DNA barcodes are in perfect agreement with morphology in 64% of the species. Interspecific distances were found to range from 3.22% to 8.42% (average 5.48%), whilst their mean intraspecific variation ranges from 0.0% to 4.30% (average 1.78%). Based on DNA barcodes evidence of topotypic individuals, the study of original descriptions and illustrations of the holotypes, we consider here that Lamprospilus occidentalis Johnson & Salazar 2004 is a new junior subjective synonym of L. draudti Lathy, 1932.

Mandibular shape as a proxy for the identification of functional feeding traits of midge larvae (Diptera: Chironomidae)

The identification of functional feeding traits in aquatic macroinvertebrates often requires a morphology-based identification of species, which is important for trait-based methods of biological assessment. The extent of functional homogenization is compared along scales of impairment, where trait-based information is used as an input in models that examine degradation pathways. However, trait-based information is not always readily available for all groups of aquatic insects, especially for species diverse families, such as chironomids (Diptera: Chironomidae). Taxonomic challenges and ambiguous traits complicate the use of chironomid larvae in trait-based bioassessment. Here, we examine the use of geometric morphometric analysis (GMA), deep learning (Convolutional Neural Networks), and computer vision (deep CNN) applied to the mouthparts (mandibles) of chironomid larvae as a proxy for identifying the relationship between the functional morphology and food acquisition behaviour. We determined the variability in morphology of mandibles for 23 taxa of chironomid larvae from different genera, subfamilies, and their Functional Feeding Group (FFG). Analysis using GMA showed that the five different FFGs examined had different mandibular traits that significantly varied in shape and size. A deep CNN model was then built that was able to classify the 23 taxa into their respective FFG automatically with 92.31 % accuracy. A gradient-weighted Class Activation Mapping (Grad-CAM) algorithm found that the most important part of mandibles for classification were the gula and mandibular joint. We introduced three additional species to the deep CNN models to test whether automatic classification would directly and automatically identify traits of the specimens independently from taxonomic identification. The deep CNN process avoids issues surrounding both taxonomic identification and previous knowledge of a specific taxon’s feeding trait, and in all cases the model classified taxa correctly based on their mandibular traits. The use of deep learning approaches could substantially enhance the use of trait-based approaches and increase the reliability and use of chironomids in bioassessment.

Comparing earthworm biodiversity estimated by DNA metabarcoding and morphology-based approaches

Conventional identification based on morphology is today's tool of choice for monitoring earthworm diversity. However, it requires skills to distinguish specific features, which can become the bottleneck in soil ecological studies. DNA-based metabarcoding is increasingly used to monitor diversity of soil organisms. Few studies have compared this method with conventional methods. The aim of the study was to compare metabarcoding based on the mitochondrial 16S rRNA region with conventional morphology-based identification, where metabarcoding captured more species (eight) than identified by conventional method (five). Additionally, we tested the effects of two commercial DNA extraction kits: PowerSoil based on 0.25 g of soil and PowerMax based on 10 g of soil (both from Qiagen), where the PowerMax covered higher richness than PowerSoil.

High-throughput sequencing and marker pigment analysis of freshwater phytoplankton: A direct comparison with microscopic count data in the tropical crater lakes of Western Uganda

High-throughput DNA sequencing (HTS) and photosynthetic marker-pigment analysis can provide cost-and time-efficient alternatives for morphology-based microscopic identification and counting of lacustrine phytoplankton. However, application of particularly HTS in tropical lakes is still uncommon. We analyzed the community composition of cyanobacterial and eukaryotic phytoplankton in relation to trophic status and other environmental factors in 15 tropical crater lakes in western Uganda, using both high-performance liquid chromatography (HPLC) of photosynthetic marker pigments and HTS of 16 S and 18 S small subunit rRNA genes. We then compared the results with phytoplankton composition data based on microscopic identification and cell counting to evaluate whether the two former methods can be alternative or complementary approaches to analyze these lakes’ phytoplankton communities. HTS recorded 105 operational taxonomic units (OTUs) of cyanobacteria, and 197 OTUs of autotrophic eukaryotes mainly from dinoflagellates, cryptophytes and green algae. Ochrophyta (chrysophytes and diatoms) were present in low abundances only, and the few remaining sequences belonged to Streptophyta and Haptophyta. Marker pigment distribution among samples reflected the widespread and often dominant presence of cyanobacteria (primarily zeaxanthin, myxoxanthophyll and echinenone), followed by green algae (chlorophyll b, lutein, antheraxanthin, neoxanthin) and diatoms (fucoxanthin, diato-diadinoxanthin), and with cryptophyta (alloxanthin) important in some of the lakes. Direct and indirect ordinations of the OTUs and marker pigments revealed that, similar to patterns observed in cell counts, phytoplankton community composition differed between deep oligotrophic lakes and shallower more productive lakes, even though the distribution of cyanobacterial OTUs was more related to lake water conductivity and season than to trophic status. Procrustes analyses of the composition of green algae and Ochrophyta, the two dominant eukaryotic groups, based on HTS data showed patterns significantly similar to composition data based on cell counts, but no significant correlations were found between the complete eukaryotic or cyanobacterial HTS data and cell count data. While the latter discrepancies can be attributed to method-related biases in both HTS and microscopy, in contrast to the microscopic approach HTS failed to identify trophic indicator species and did not assign all lakes to the correct trophic category. Composition data based on marker pigments clustered the 15 lakes according to their trophic level only when pigment abundances were expressed as absolute concentrations, not when expressed as fractional abundances. We attribute this lower discriminating power partly to the wide distribution of cyanobacteria in these tropical crater lakes, besides the pigments’ low taxonomic resolution. Nevertheless, as the compositional patterns in relation to environmental variation observed in marker pigments and OTUs of the dominant eukaryotic phytoplankton groups are similar to those in cell count data, both methods hold potential for ecosystem-level monitoring of tropical crater lakes. However, the high-resolution HTS approach is handicapped by non-uniform amplification of gene sequences, while the low-resolution marker-pigment approach is handicapped by the widespread dominance of cyanobacteria in these systems irrespective of their trophic status.

Trichoderma yunnanense and T. asperellum as potential biological agents for control of basal stem rot disease in oil palm

Basal Stem Rot (BSR) disease is a main constrain in oil palm cultivation. Ganoderma boninense is known as a causal agent of this disease. The intensity of BSR disease continues to increase in both the vegetative and generative phases of oil palm plantations and causes significant losses. Biological control is one of the BSR disease control techniques and is believed to be able to support sustainable oil palm cultivation. Trichoderma spp. is a group of fungal biological agents commonly used to control BSR disease. This study aims to obtain Trichoderma spp. isolates to be developed further as biocontrol agents for BSR disease. The research stages included isolation, morphology-based identification, antagonist potency testing, characterization, and identification with molecular technique. The results in this research obtained one isolate of Trichoderma strain TSU from oil palm plantation at Pematang Siantar Regency, and one isolate of Trichoderma strain TGLP from oil palm plantation at Musi Banyu Asin Regency, which inhibited the growth of G. boninense was 90.9 and 93.9% respectively through dual culture test. Inhibition tests by volatile compounds showed growth inhibition of G. boninense by both isolates were 55.2 and 70.6%. Both Trichoderma strains have the characteristics of producing chitinase, glucanase, and indole acetic acid. Furthermore, molecular identification showed that the Trichoderma strain TSU was similar to the Trichoderma yunnanense strain CBS121219 with an identity percentage of 99.11%, and Trichoderma TGLP as Trichoderma asperellum strain 1A4 with a percent identity of 99.65%. With their antagonistic ability and characteristics, the two Trichoderma spp. isolates have the potential to be further developed as biological agents for controlling BSR caused by G. boninense.

Rust on Hosta longipes caused by Puccinia oncospora in Korea

Hosta longipes (Liliaceae), widely distributed throughout Korea, China, Japan, and eastern Russia, is one of the most popular ornamental perennials in public and private gardens. In Korea, this species has long been used as a traditional medicine for the treatment of coughs, phlegm, burns, swelling and asthma (Kim et al., 2014), and its young leaves are also consumed as a salad vegetable. In June 2016, rust disease was observed on H. longipes plants growing naturally around a stream at Mount Gongjaksan in Hongcheon-gun, Korea (Fig. 1). The disease incidence rate was c. 10%. Symptoms appeared as yellowish, round, chlorotic spots on the upper surface of the infected leaves (Fig. 2) and yellow to orange-coloured aecia on the corresponding lower surface and petiole (Fig. 3). After the first findings, the same disease was observed in 2017, 2019 and 2020. Herbarium specimens of infected material were deposited in the Korea University Herbarium (Accession Nos. KUS-F29182, F29810, F30967, and F31685). Leaves affected by the rust infection were examined under a dissecting microscope (M205C; Leica, Germany), a DIC microscope (Axio Imager 2; Carl Zeiss, Germany), and a scanning electron microscope (S-4800+EDS; Hitachi, Japan). Spermogonia were mostly epiphyllous but rarely hypophyllous, densely grouped, pale brown, and subepidermal. Aecia were hypophyllous, often densely grouped, yellow, cupulate with peridia, and 196–300 μm in diameter (Fig. 4). Aeciospores were hyaline, globose to subglobose, angular, and (20.2-)22.0-24.9(-27.4) × (17.0-)19.6-22.5(-24.2) μm (mean 23.4 × 21.0 μm) (Fig. 5). Aeciospore wall was densely verrucose and 0.6-1.6 μm (mean 1.0 μm) in thickness (Fig. 6). Uredinial and telial stages were not observed. These morphological characteristics were consistent with those of Puccinia oncospora (Ji et al., 2022). To confirm the morphology-based identification, genomic DNA was extracted from four specimens using a MagListo 5M plant Genomic DNA Extraction Kit (Bioneer, Korea). Two ribosomal DNA regions were amplified: the internal transcribed spacer (ITS) with primers ITS5u and ITS4rust (Pfunder et al., 2001) and the large subunit (LSU) rDNA with primers LRust1R and LRust3 (Beenken et al., 2012). The resulting sequences were deposited in GenBank (Accession Nos. OQ061206-9 for ITS and OQ073721-4 for LSU) and compared to other reference sequences using BLASTn. The ITS sequences of Korean specimens were identical to those of P. oncospora ex Trillium kamtschaticum and Phalaris arundinacea for ITS (MW404821-5) and LSU sequences (MW404981-5). In maximum-likelihood phylogenetic trees for ITS (Fig. 7A) and LSU (Fig. 7B) sequences, the Korean samples were grouped with the reference sequences of P. oncospora with high bootstrap supporting values of 93% in ITS and 96% in LSU. Puccinia oncospora is a recently described rust species that is so far only known from China, where it completes its life cycle by forming an aecial stage on Trillium kamtschaticum (Melanthiaceae, previously Liliaceae) and a telial stage on Phalaris arundinacea (Poaceae; Ji et al., 2022). So far, three species of Puccinia have been recorded on Hosta longipes, namely, P. funkiae, P. hemerocallidis, and P. majanthemi (Hiratsuka & Sato, 1951; Farr & Rossman, 2022). Also, a species complex P. sessilis was considered parasitic on H. longipes (Hiratsuka & Sato, 1951), but it is phylogenetically and morphologically distinguishable from P. oncospora. To our knowledge, this is the first record of rust disease on Hosta longipes and this rust pathogen in Korea. As there have been no records of rust on P. arundinacea, a telial host plant of P. oncospora, in Korea, finding an alternative host for that rust is necessary to develop effective control measures. This work was supported by the National Academy of Agricultural Science grant (PJ0149560112020) from the Rural Development Administration, Korea.

High-Throughput DNA Metabarcoding as an Approach for Ichthyoplankton Survey in Oujiang River Estuary, China

High-throughput DNA metabarcoding of mitochondrial 12S rRNA and Cyt b gene sequences was coupled with a morphology-based identification tool to assess ichthyoplankton community structure in Oujiang River Estuary, China. The performances of 12S and Cyt b barcoding markers were compared in terms of taxonomic resolution, detection and coverage, and their suitability was established for use as a quick and powerful ichthyoplankton assessment tool. A total of 30,138 ichthyoplankton (2462 eggs and 27,676 larvae) samples were collected from April to August 2015 and identified to 145 taxa belonging to 57 families and 105 genera. June and July were the main spawning months. Ichthyoplankton were more abundant around Lingkun and Qidu Islands and the upper parts of Oujiang River Estuary. The 12S gene marker presented higher species coverage and detection rate than Cyt b. DNA metabarcoding exhibited more representative species identification power than morphology. The findings reported in this study provided a key attempt towards the development of time-efficient and cost-effective ichthyoplankton identification and assessment tool.

Maximising signal-to-noise ratios in environmental DNA-based monitoring

Man's impacts on global ecosystems are increasing and there is a growing demand that these activities be appropriately monitored. Monitoring requires measurement of a response metric (‘signal’) that changes maximally and consistently in response to the monitored activity irrespective of other factors (‘noise’), thus maximising the signal-to-noise ratio. Indices derived from time-consuming morphology-based taxonomic identification of organisms are a core part of many monitoring programmes. Metabarcoding is an alternative to morphology-based identification and involves the sequencing of short fragments of DNA (‘markers’) from multiple taxa simultaneously. DNA suitable for metabarcoding includes that extracted from environmental samples (eDNA). Metabarcoding outputs DNA sequences that can be identified (annotated) by matching them against archived annotated sequences. However, sequences from most organisms are not archived - preventing annotation and potentially limiting metabarcoding in monitoring applications. Consequently, there is growing interest in using unannotated sequences as response metrics in monitoring programmes.We compared the sequences from three commonly used markers (16S (V3/V4 regions), 18S (V1/V2 regions) and COI) and, sampling along steep impact gradients, showed that the 16S and COI sequences were associated with the largest and smallest signal-to-noise ratio respectively. We trialled four separate, intuitive, noise-reduction approaches and demonstrated that removing less frequent sequences improved the signal-to-noise ratio, partitioning an additional 25 % from noise to explanatory factors in non-parametric ANOVA (NPA) and reducing dispersion in the data. For the 16S marker, retaining only the most frequently observed sequence, per sample, resulting in nine sequences across 150 samples, generated a near-maximal signal-to-noise ratio (95 % of the variance explained in NPA). We recommend that NPA, combined with rigorous elimination of less frequent sequences, be used to pre-filter sequences/taxa being used in monitoring applications. Our approach will simplify downstream analysis, for example the identification of key taxa and functional associations.

Geometric morphometric and molecular techniques for discriminating among three cryptic species of the Anopheles barbirostris complex (Diptera: Culicidae) in Thailand

Anopheles members of the Barbirostris complex are important vectors of malaria in Thailand. However, they are morphologically indistinguishable because they are closely related species. In this study, wing geometric morphometrics (GM) and DNA barcoding based on the cytochrome c oxidase subunit 1 (COI) gene were applied to differentiate cryptic species of the Barbirostris complex in Thailand. Three cryptic species of the Barbirostris complex, Anopheles dissidens (19.44%), Anopheles saeungae (24.54%), and Anopheles wejchoochotei (56.02%) were initially identified using the multiplex polymerase chain reaction assay. DNA barcoding analyses showed low intraspecific distances (range, 0.27%–0.63%) and high interspecific distances (range, 1.92%–3.68%), consistent with the phylogenetic analyses that showed clear species groups. While wing size and shape analyses based on landmark-based GM indicated differences between three species (p < 0.05). The cross-validated reclassification revealed that the overall efficacy of wing size analysis for species identification of the Barbirostris complex was less than the wing shape analysis (56.43% vs. 74.29% total performance). Therefore, this study's results are guidelines for applying modern techniques to identify members within the Barbirostris complex, which are still difficult to distinguish by morphology-based identification and contribute to further appropriate malaria control.

Methods Employed in the Determining Nectar and Pollen Sources for Bees: A Review of the Global Scenario

Abstract Flowering plants and pollinators are in a mutualistic association, where pollinators collect floral resources and plants receive pollination services. Bees and other pollinators are declining in many parts of the world, and their loss affects the functional composition of fauna, flora, and habitats. Different strategies are being deployed to improve pollinator services, including the management of bees. Sustainable management of a bee species strongly depends on floral resource availability. Therefore, beekeepers need to have adequate knowledge about the surrounding vegetation (especially nectar and pollen sources for the bee species). Diverse methodologies are used around the world to determine floral resources for bees. Field surveys and pollen analysis of honey, corbicular/scopal pollen loads, residual pollens in brood cells, forager’s body surface pollen content, and internal organs (gut, intestine, crop, etc.) were used by the researchers. For pollen identification, most researchers carried out microscopy-based methods. However, pollen DNA-based methods were also used by researchers in recent years. Regarding the morphology-based identification, most researchers processed pollen samples according to Erdtman’s acetolysis method to increase the visibility of diagnostic characteristics of the pollen grains. The method specified by the International Commission for Bee Botany was used to conduct qualitative and quantitative pollen analysis on honey samples. For quantitative pollen load analysis, researchers used numerous techniques that may have been the most effective. Our discussion about the different techniques utilized to determine floral resources of a bee species will be helpful for researchers in selecting a suitable protocol and may assist in developing superior methodologies.

DNA Barcoding of Stingless Bees (Hymenoptera: Meliponini) in Northern Peruvian Forests: A Plea for Integrative Taxonomy

Stingless bees (Hymenoptera: Meliponini) are among the most important pollinators of tropical forests. Peru is considered a hotspot of biodiversity of Meliponini, but many areas of this country (e.g., Peruvian Amazon) remain unexplored. We aimed to produce a first inventory of stingless bee species dwelling in humid and seasonally dry forests of northern Peru by combining traditional (morphologically-based) taxonomy and DNA barcoding. Specimens were collected in 2020 at five sites located in San Martin and Piura regions. We identified 12 genera of Meliponini. Among those, Trigona and Plebeia were the most abundant (45.9% and 12.8% respectively), whereas Nannotrigona and Scaura were the least represented ones (2.3%). We assigned a reliable species identification to about 30% of specimens (Trigona amazonensis, T. muzoensis, T. williana, Partamona testacea, Scaura tenuis, Tetragona goettei, and Tetragonisca angustula). Yet, more than a half of the specimens received a provisional identification (e.g., Geotrigona cf. fulvohirta, T. cf. amalthea, T. cf. fuscipennis, T. cf. hypogea, Melipona cf. cramptoni, Partamona cf. epiphytophila, Ptilotrigona cf. perenae, Scaura cf. latitarsis, Tetragona cf. clavipes, Trigonisca cf. atomaria). We also highlighted an extensive polyphyly that affected a number of currently recognized species (e.g., T. fulviventris, T. guianae, Plebeia franki, P. frontalis, M. eburnea, M. illota), whose members were split into various clades. Finally, 16% of individuals failed to be identified at the species level (Trigona sp. 1, T. sp. 2, Nannotrigona sp., Partamona sp., Scaptotrigona sp. 1, S. sp. 2, Trigonisca sp. 1, and Trigonisca sp. 2). We discuss our findings according to the current faunistic and biogeographic knowledge of Meliponini in Peru and the Neotropical region. We also remark on the importance of conducting a taxonomic revision of stingless bees and improving both their morphology-based identification keys and BOLD repository. Finally, we claim that integrative taxonomy shall be strongly implemented to truly assess the biodiversity of Neotropical stingless bees, allowing conserving these important pollinators and the associated traditional meliponiculture in an effective manner.

Technological features of blast identification in the cerebrospinal fluid: A systematic review of flow cytometry and laboratory haematology methods.

Involvement of the central nervous system (CNS) by acute leukemias (ALs) has important implications for risk stratification and disease outcome. The clinical laboratory plays an essential role in assessment of cerebrospinal fluid (CSF) specimens from patients with ALs at initial diagnosis, at the end of treatment, and when CNS involvement is clinically suspected. The two challenges for the laboratory are 1) to accurately provide a cell count of the CSF and 2) to successfully distinguish blasts from other cell types. These tasks are classically performed using manual techniques, which suffer from suboptimal turnaround time, imprecision, and inconsistent inter-operator performance. Technological innovations in flow cytometry and hematology analyzer technology have provided useful complements and/or alternatives to conventional manual techniques. We performed a PRISMA-compliant systematic review to address the medical literature regarding the development and current state of the art of CSF blast identification using flow cytometry and laboratory hematology technologies. We searched the peer reviewed medical literature using MEDLINE (PubMed interface), Web of Science, and Embase using the keywords "CSF or cerebrospinal" AND "blasts(s)". 108 articles were suitable for inclusion in our systematic review. These articles covered 1) clinical rationale for CSF blast identification; 2) morphology-based CSF blast identification; 3) the role of flow cytometry; 4) use of hematology analyzers for CSF blast identification; and 5) quality issues. 9 /L, which is much lower than the original machine count and platelet transfusion was warranted. 1) Clinical laboratory testing plays a central role in risk stratification and clinical management of patients with acute leukemias, most clearly in pediatric ALs; 2) studies focused on other patient populations, including adults and patients with AML are less prevalent in the literature; 3) improvements in instrumentation may provide better performance for the classification of CSF specimens. Current challenges include: 1) more precisely characterizing the natural history of AL involvement of the CNS, 2) improvements in automated cell count technology of low cellularity specimens, 3) defining the role of flow MRD testing of CSF specimens and 4) improved recognition of specimen quality by clinicians and laboratory personnel.

Advances in Nematode Identification: A Journey from Fundamentals to Evolutionary Aspects

Nematodes are non-segmented roundworms evenly distributed with various habitats ranging to approximately every ecological extremity. These are the least studied organisms despite being the most diversified group. Nematodes are the most critical equilibrium-maintaining factors, having implications on the yield and health of plants as well as well-being of animals. However, taxonomic knowledge about nematodes is scarce. As a result of the lack of precise taxonomic features, nematode taxonomy remains uncertain. Morphology-based identification has proved inefficacious in identifying and exploring the diversity of nematodes, as there are insufficient morphological variations. Different molecular and new evolving methodologies have been employed to augment morphology-based approaches and bypass these difficulties with varying effectiveness. These identification techniques vary from molecular-based targeting DNA or protein-based targeting amino acid sequences to methods for image processing. High-throughput approaches such as next-generation sequencing have also been added to this league. These alternative approaches have helped to classify nematodes and enhanced the base for increased diversity and phylogeny of nematodes, thus helping to formulate increasingly more nematode bases for use as model organisms to study different hot topics about human well-being. Here, we discuss all the methods of nematode identification as an essential shift from classical morphometric studies to the most important modern-day and molecular approaches for their identification. Classification varies from DNA/protein-based methods to the use of new emerging methods. However, the priority of the method relies on the quality, quantity, and availability of nematode resources and down-streaming applications. This paper reviews all currently offered methods for the detection of nematodes and known/unknown and cryptic or sibling species, emphasizing modern-day methods and budding molecular techniques.

Multiple species delimitation approaches with COI barcodes poorly fit each other and morphospecies - An integrative taxonomy case of Sri Lankan Sericini chafers (Coleoptera: Scarabaeidae).

DNA taxonomy including barcoding and metabarcoding is widely used to explore the diversity in biodiversity hotspots. In most of these hotspot areas, chafers are represented by a multitude of species, which are well defined by the complex shape of male genitalia. Here, we explore how well COI barcode data reflect morphological species entities and thus their usability for accelerated species inventorization. We conducted dedicated field surveys in Sri Lanka to collect the species‐rich and highly endemic Sericini chafers (Coleoptera: Scarabaeidae). Congruence among results of a series of protocols for de novo species delimitation and with morphology‐based species identifications was investigated. Different delimitation methods, such as the Poisson tree processes (PTP) model, Statistical Parsimony Analysis (TCS), Automatic Barcode Gap Discovery (ABGD), Assemble Species by Automatic Partitioning (ASAP), and Barcode Index Number (BIN) assignments, resulted in different numbers of molecular operational taxonomic units (MOTUs). All methods showed both over‐splitting and lumping of morphologically identified species. Only 18 of the observed 45 morphospecies perfectly matched MOTUs from all methods. The congruence of delimitation between MOTUs and morphospecies expressed by the match ratio was low, ranging from 0.57 to 0.67. TCS and multirate PTP (mPTP) showed the highest match ratio, while (BIN) assignment resulted in the lowest match ratio and most splitting events. mPTP lumped more species than any other method. Principal coordinate analysis (PCoA) on a match ratio‐based distance matrix revealed incongruent outcomes of multiple DNA delimitation methods, although applied to the same data. Our results confirm that COI barcode data alone are unlikely to correctly delimit all species, in particular, when using only a single delimitation approach. We encourage the integration of various approaches and data, particularly morphology, to validate species boundaries.

Advances in multiplex molecular detection technologies for harmful algae.

As the eutrophication of natural water bodies becomes more and more serious, the frequency of outbreaks of harmful algal blooms (HABs) mainly formed by harmful algae also increases. HABs have become a global ecological problem that poses a serious threat to human health and food safety. Therefore, it is extremely important to establish methods that can rapidly detect harmful algal species for early warning of HABs. The traditional morphology-based identification method is inefficient and inaccurate. In recent years, the rapid development of molecular biology techniques has provided new ideas for the detection of harmful algae and has become a research hotspot. The current molecular detection methods for harmful algal species mainly include fluorescence in situ hybridization, sandwich hybridization, and quantitative PCR (qPCR), but all of these methods can only detect single harmful algal species at a time. The establishment of methods for the simultaneous detection of multiple harmful algal species has become a new trend in the development of molecular detection technology because various harmful algal species may coexist in the natural water environment. The established molecular techniques for multiple detections of harmful algae mainly include gene chip, multiplex PCR, multiplex qPCR, massively parallel sequencing, antibody chip, and multiple isothermal amplification. This review mainly focuses on the principles, advantages and disadvantages, application progress, and application prospects of these multiple detection technologies, aiming at providing effective references not only for the fisheries but also for economic activities, environment, and human health.

Implementation of MALDI-TOF Mass Spectrometry to Identify Fungi From the Indoor Environment as an Added Value to the Classical Morphology-Based Identification Tool.

IntroductionDuring the last decades, molds in the indoor environment have raised concern regarding their potential adverse health effects. The genera Aspergillus, Cladosporium, Penicillium, Alternaria, and yeasts, the most common fungi found indoors, include species with high allergenic and toxigenic potentials. Identification of these molds is generally performed by microscopy. This method has, however, some limitations as it requires mycologists with high expertise while identification is often limited to the genus level. Therefore, it is necessary to seek for fast and accurate tools, such as Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDITOF MS), enabling an identification to the species level and guiding general practitioners in their search for the underlying cause of a health problem.MethodsIn this study, 149 fungal air and dust isolates from 43 dwellings in Brussels were taken in collaboration with Brussels Environment RCIB/CRIPI and identified by both microscopy and MALDI-TOF MS in Sciensano's Indoor Mycology laboratory. Spectra obtained via MALDI-TOF MS were compared with data available in an in-house created reference database containing over 1,700 strains from the BCCM/IHEM fungal collection.ResultsA total of 149 isolates including 18 yeasts and 131 filamentous fungi were analyzed. Microscopic analysis indicated 18 yeast species and allowed identification of 79 isolates (53%) to the genus level. Only 36 isolates (24%) could be identified to the species complex level. Fifteen molds (10%) could not be identified, and one was indicated as sterile mycelia. No isolate was identified to species level. MALDI-TOF MS analysis identified 137 (92%) of the 149 isolates with a logscore > 1.7. Of these 137 isolates, 129 (87%) were identified to the species level (logscore > 2.0). For only 8 isolates (5%), identification was limited to the genus/section level (1.7 < logscore <2.0), and 12 isolates (8%) could not be identified.ConclusionA comparison of results obtained with both methods indicates an increased precision in identifications with MALDI-TOF MS analysis for 92% of the isolates, emphasizing its highly added value to the standard microscopic analysis in routine practice. In addition, MALDI-TOF MS also enables to assess the accuracy of microscopic identifications.

Diversity investigation by application of DNA barcoding: A case study of lepidopteran insects in Xinjiang wild fruit forests, China

To investigate the species diversity of lepidopteran insects in Xinjiang wild fruit forests, establish insect community monitoring systems, and determine the local species pool, we test the applicability of DNA barcoding based on cytochrome c oxidase subunit I (COI) gene for accurate and rapid identification of insect species. From 2017 to 2019, a total of 212 samples with ambiguous morphological identification were selected for DNA barcoding analysis. Five sequence‐based methods for species delimitation (ABGD, BINs, GMYC, jMOTU, and bPTP) were conducted for comparison to traditional morphology‐based identification. In total, 2,422 samples were recorded, representing 143 species of 110 genera in 17 families in Lepidoptera. The diversity analysis showed that the richness indices for Noctuidae was the highest (54 species), and for Pterophoridae, Cossidae, Limacodidae, Lasiocampidae, Pieridae, and Lycaenidae were the lowest (all with 1 species). The Shannon–Wiener species diversity index (H′) and Pielou's evenness (J′) of lepidopteran insects first increased and then decreased across these 3 years, while the Simpson diversity index showed a trend of subtracted then added. For molecular‐based identification, 67 lepidopteran species within 61 genera in 14 families were identified through DNA barcoding. Neighbor‐joining (NJ) analysis showed that conspecific individuals were clustered together and formed monophyletic groups with a high support value, except for Lacanobia contigua (Denis & Schiffermüller, 1775) (Noctuidae: Hadeninae). Sixty‐seven morphospecies were classified into various numbers of MOTUs based on ABGD, BINs, GMYC, jMOTU, and bPTP (70, 96, 2, 71, and 71, respectively). In Xinjiang wild fruit forests, the family with the largest number of species is Noctuidae, followed by Geometridae, Crambidae, and the remaining families. The highest Shannon diversity index is observed for the family Noctuidae. Our results indicate that the distance‐based methods (ABGD and jMOTU) and character‐based method (bPTP) outperform GMYC. BINs is inclined to overestimate species diversity compared to other methods.

Implications of taxonomic and numerical resolution on DNA metabarcoding-based inference of benthic macroinvertebrate responses to river restoration

It is essential to explore and define the level of taxonomic identification and quantification approaches for diversity and biomonitoring studies, given their potential influence on assessing and interpreting ecological outcomes. This study assessed the response of benthic macroinvertebrate communities to restore and construct gravel bars in a dam-impacted river, with non-dam influenced tributaries serving as reference sites. Additionally, we evaluated the performance of different taxonomic and numerical (i.e., abundance vs. presence/absence data) resolutions of DNA metabarcoding with consequent comparison to morphology-based identification and how it affects assessment outcomes. DNA metabarcoding detected 93% of the morphologically identified individuals and provided finer taxonomic resolution. We also detected significant correlations between morphological sample abundance, biomass, and DNA metabarcoding-read abundance. Furthermore, we observed a relatively high and significant congruence in macroinvertebrate community structure and composition between different taxonomic and numerical resolutions of both methods. This indicates a satisfactory surrogacy between the two approaches and their varying identification levels and data transformation. Additionally, community–environmental associations were significant for all datasets but showed significant varying associations with physicochemical parameters. Our observations imply that coarser taxonomic resolution could be highly advantageous for DNA metabarcoding-based applications in situations where the lack of taxonomic information, e.g., poor reference database, might severely affect biological assessment quality.

Discrimination of Tilletia controversa from the T. caries/T. laevis complex by MALDI-TOF MS analysis of teliospores

The fungal genus Tilletia includes a large number of plant pathogens of Poaceae. Only a few of those cause bunt of wheat, but these species can lead to significant yield losses in crop production worldwide. Due to quarantine regulations and specific disease control using appropriate seed treatments for the different disease agents, it is of high importance to distinguish Tilletia caries and Tilletia laevis as causal agents of common bunt accurately from Tilletia controversa, the causal agent of the dwarf bunt. Several studies have shown that matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is a useful tool to differentiate closely related fungal species. The aim of this study was to assess whether MALDI-TOF MS analysis is able to distinguish specimens of the three closely related pathogens T. caries, T. laevis, and T. controversa and whether it may constitute an alternative method to the morphology-based identification or germination tests. Spectral data are available via ProteomeXchange with identifier PXD030401. Spectra-based hierarchical cluster analysis (HCA) and discriminant analysis of principal components (DAPC) of the obtained mass spectra showed two main clusters. One cluster included specimens of T. controversa, whereas the second cluster comprised T. laevis and T. caries specimens. Even though main spectral profiles (MSPs) for species identification are missing, MALDI-TOF MS has proven to be a useful method for distinguishing between T. controversa and the two causal agents of common bunt, using direct analysis of teliospores, but was unable to separate T. caries and T. laevis species.Key points• MALDI-TOF MS was developed to classify Tilletia species causing bunt of wheat.• Best results were achieved when combining HCA and DAPC analysis.• The method resulted in an accuracy of 98.51% testing 67 Tilletia specimens.Graphical abstract