The First Report of Sphaerirostris picae Infection in the Oriental Magpie (Pica serica) in Beijing, China.

Background: Sphaerirostris picae is a parasitic species known for its ability to infect and transmit between hosts in the gastrointestinal tracts of wild avian species. However, there is limited information on its presence and impact on urban avian populations, particularly in China. Materials and Methods: In this study, morphological observations were conducted to detect the presence of Sphaerirostris sp. within the intestinal tract of the Oriental Magpie (Pica serica) collected in Beijing, China. Further confirmation of the parasite's identity was achieved through phylogenetic analysis using COX1 gene sequencing to compare with previously documented Sphaerirostris picae isolates. Results: The morphological and molecular analyses confirmed the presence of Sphaerirostris picae in the Oriental Magpie. Phylogenetic analysis indicated a close relationship with known Sphaerirostris picae isolates. This represents the first reported case of Sphaerirostris picae infection in magpies from Beijing, China. Conclusion: The findings highlight the potential health hazards posed by Sphaerirostris picae to urban avian populations and public health. The study suggests that additional research and surveillance efforts are necessary to better understand the risks associated with this parasite and to develop effective mitigation strategies.

FloraNER: A new dataset for species and morphological terms named entity recognition in French botanical text.

FloraNER is a distantly supervised named entity recognition dataset (NER). The dataset is built from botanical French literature extracted from the OCR-preprocessed flora of New Caledonia, provided by the National Museum of Natural History in France (MNHN), and distantly annotated with a botanical French corpus created by merging botanical lexicons available online. FloraNER comprises separate sub-datasets for the recognition of plant species names, as well as coarse-grained and fine-grained botanical morphological terms. The resulting datasets are in CSV format, displaying textual data, identified named entities, and their annotations, covering one named entity type "Species" (Espèce in French) for species name identification, two named entity types "Organ" and "Descriptor" for coarse-grained morphological term identification, and eight named entity types for fine-grained morphological term identification: Organ, Descriptor, Form, Color, Development, Structure, Surface, Position, Disposition, and Measure. This dataset can be utilized to train and evaluate named entity recognition models for extracting information from botanical French literature.

Identification and prevalence of ixodid ticks of cattle in case of Aleltu district, Oromia regional state, northern Ethiopia.

BACKGROUND: In Ethiopia, ticks are the major threat to cattle productivity and production, leading to considerable economic losses. The current study was designed to estimate the prevalence of ixodid tick infestation, identify species, assess major risk factors associated with tick infestation and assess public awareness. METHODS: A cross-sectional and questionnaire-based study was conducted from January 2022 to June 2022 in the Aleltu district. The study animals were selected using a simple random sampling method. RESULTS: Of the 400 cattle examined, 303 (75.8%) were found to be infested by one or more tick species. Six species of ticks were identified that belonged to three genera: Amblyomma, Hyalomma and Rhipicephalus, and the subgenus Rhipicephalus (Boophilus). The most common tick species identified in terms of their prevalence and dominance were Rh. (Bo) decoloratus, Rh. evertsi, Am. variegatum, Hy. rufipes, Rh. bergeoni and Rh. praetextatus. In the present study, Rh. (Bo) decoloratus was the most prevalent (56.8%) in the study area. Among the risk factors considered, the prevalence of tick species had a statistically significant (p < 0.05) association with the age, production systems and body condition of animals. Out of 110 people interviewed, 107 (97.3%) believed there was a tick infestation in their village, and almost all farmers 103(93.6%) in the study area were unaware that ticks serve as vectors. CONCLUSIONS: The present study provides preliminary information on the prevalence of tick infestation and the composition of ticks in the Aleltu district. Ticks are a major problem for the cattle in the study area. Therefore, the problem observed in the study area alarms the district and calls for a comprehensive control strategy.

Real-time PCR for malaria diagnosis and identification of Plasmodium species in febrile patients in Cubal, Angola.

BACKGROUND: Malaria is the parasitic disease with the highest morbimortality worldwide. The World Health Organization (WHO) estimates that there were approximately 249 million cases in 2022, of which 3.4% were in Angola. Diagnosis is based on parasite identification by microscopy examination, antigen detection, and/or molecular tests, such as polymerase chain reaction (PCR). This study aimed to evaluate the usefulness of real-time PCR as a diagnostic method for malaria in an endemic area (Cubal, Angola). METHODS: A cross-sectional study was carried out at the Hospital Nossa Senhora da Paz in Cubal, Angola, including 200 patients who consulted for febrile syndrome between May and July 2022. From each patient, a capillary blood sample was obtained by finger prick for malaria field diagnosis [microscopy and rapid diagnostic test (RDT)] and venous blood sample for real-time PCR performed at the Hospital Universitario Vall d'Hebron in Barcelona, Spain. Any participant with a positive result from at least one of these three methods was diagnosed with malaria. RESULTS: Of the 200 participants included, 54% were female and the median age was 7 years. Malaria was diagnosed by at least one of the three techniques (microscopy, RDT, and/or real-time PCR) in 58% of the participants, with RDT having the highest percentage of positivity (49%), followed by real-time PCR (39.5%) and microscopy (33.5%). Of the 61 discordant samples, 4 were only positive by microscopy, 13 by real-time PCR, and 26 by RDT. Plasmodium falciparum was the most frequent species detected (90.63%), followed by P. malariae (17.19%) and P. ovale (9.38%). Coinfections were detected in ten participants (15.63%): six (60%) were caused by P. falciparum and P. malariae, three (30%) by P. falciparum and P. ovale, and one (10%) triple infection with these three species. In addition, it was observed that P. falciparum and P. malariae coinfection significantly increased the parasite density of the latter. CONCLUSIONS: RDT was the technique with the highest positivity rate, followed by real-time PCR and microscopy. The results of the real-time PCR may have been underestimated due to suboptimal storage conditions during the transportation of the DNA eluates. However, real-time PCR techniques have an important role in the surveillance of circulating Plasmodium species, given the epidemiological importance of the increase in non-falciparum species in the country, and can provide an estimate of the intensity of infection.

Epidemiology and laboratory detection of non-tuberculous mycobacteria.

The global incidence of non-tuberculous mycobacteria (NTM) infections is on the rise. This study systematically searched several databases, including PubMed, Web of Science, Google Scholar, and two Chinese libraries (Chinese National Knowledge Infrastructure and Wanfang) to identify relevant published between 2013 and 2023 related to the isolation of NTM in clinical specimens from various countries and provinces of China. Furthermore, a comprehensive literature review was conducted in PubMed and Google Scholar to identify randomized clinical trials, meta-analyses, systematic reviews, and observational studies that evaluated the diagnostic accuracy and impact of laboratory detection methods on clinical outcomes. This review presented the most recent epidemiological data and species distributions of NTM isolates in several countries and provinces of China. Moreover, it provided insights into laboratory bacteriological detection, including the identified strains, advantages and disadvantages, recent advancements, and the commercial Mycobacterium identification kits available for clinical use. This review aimed to aid healthcare workers in understanding this aspect, enhance the standards of clinical diagnosis and treatment, and enlighten them on the existing gaps and future research priorities.

Description of five larvae of the genus Gnaptorina Reitter, 1887 from Xizang, China (Coleoptera, Tenebrionidae, Blaptinae), with molecular species delimitation and diagnoses.

With 39 described species in three subgenera, the Gnaptorina is the second most species-rich genus in the subtribe Gnaptorinina (Tenebrionidae: Blaptinae). In this study, a phylogeny of Gnaptorina was reconstructed based on one nuclear (28S-D2) and three mitochondrial (COI, Cytb, and 16S) gene fragments; multiple molecular species delimitation approaches were also implemented to assess the taxonomic status of larval specimens based on COI gene fragment. Larvae of five known species of the subgenus Hesperoptorina are described and illustrated for the first time: Gnaptorinanigera Shi, Ren & Merkl, 2007, Gnaptorinatishkovi Medvedev, 1998, Gnaptorinabrucei Blair, 1923, Gnaptorinahimalaya Shi, Ren & Merkl, 2007, Gnaptorinakangmar Shi, Ren & Merkl, 2007. A key to larvae of four genera of the tribe Blaptini and a key to the known larvae of the genus Gnaptorina are provided. This study provides valuable morphological data for larval studies of the tribe Blaptini.

Analysis of Whole-Genome for Identification of Seven Penicillium Species with Significant Economic Value.

The Penicillium genus exhibits a broad global distribution and holds substantial economic value in sectors including agriculture, industry, and medicine. Particularly in agriculture, Penicillium species significantly impact plants, causing diseases and contamination that adversely affect crop yields and quality. Timely detection of Penicillium species is crucial for controlling disease and preventing mycotoxins from entering the food chain. To tackle this issue, we implement a novel species identification approach called Analysis of whole GEnome (AGE). Here, we initially applied bioinformatics analysis to construct specific target sequence libraries from the whole genomes of seven Penicillium species with significant economic impact: P. canescens, P. citrinum, P. oxalicum, P. polonicum, P. paneum, P. rubens, and P. roqueforti. We successfully identified seven Penicillium species using the target we screened combined with Sanger sequencing and CRISPR-Cas12a technologies. Notably, based on CRISPR-Cas12a technology, AGE can achieve rapid and accurate identification of genomic DNA samples at a concentration as low as 0.01 ng/µL within 30 min. This method features high sensitivity and portability, making it suitable for on-site detection. This robust molecular approach provides precise fungal species identification with broad implications for agricultural control, industrial production, clinical diagnostics, and food safety.

Performance of convolutional neural network (CNN) and performance influencing factors for wood species classification of Lepidobalanus growing in Korea.

This study aimed to investigate the performance and factors affecting the species classification of convolutional neural network (CNN) architecture using whole-part and earlywood-part cross-sectional datasets of six Korean Quercus species. The accuracy of species classification for each condition was analyzed using the datasets, data augmentation, and optimizers-stochastic gradient descent (SGD), adaptive moment estimation (Adam), and root mean square propagation (RMSProp)-based on a CNN architecture with three to four convolutional layers. The model trained with the augmented dataset yielded significantly superior results in terms of classification accuracy compared to the model trained with the non-augmented dataset. The augmented dataset was the only factor affecting classification accuracy in the final five epochs. In contrast, four factors in the entire epoch, such as the Adam and SGD optimizers and the earlywood-part and whole-part datasets, affected species classification. The arrangement of earlywood vessels, broad rays, and axial parenchyma was identified as a major influential factor in the CNN species classification using gradient-weighted class activation mapping (Grad-CAM) analysis. The augmented whole-part dataset with the Adam optimizer achieved the highest classification accuracy of 85.7% during the final five epochs of the test phase.

Genomic oropharyngeal Neisseria surveillance detects MALDI-TOF MS species misidentifications and reveals a novel Neisseria cinerea clade.

Introduction. Commensal Neisseria spp. are highly prevalent in the oropharynx as part of the healthy microbiome. N. meningitidis can colonise the oropharynx too from where it can cause invasive meningococcal disease. To identify N. meningitidis, clinical microbiology laboratories often rely on Matrix Assisted Laser Desorption/Ionisation Time of Flight Mass Spectrometry (MALDI-TOF MS).Hypothesis/Gap statement. N. meningitidis may be misidentified by MALDI-TOF MS.Aim. To conduct genomic surveillance of oropharyngeal Neisseria spp. in order to: (i) verify MALDI-TOF MS species identification, and (ii) characterize commensal Neisseria spp. genomes.Methodology. We analysed whole genome sequence (WGS) data from 119 Neisseria spp. isolates from a surveillance programme for oropharyngeal Neisseria spp. in Belgium. Different species identification methods were compared: (i) MALDI-TOF MS, (ii) Ribosomal Multilocus Sequence Typing (rMLST) and (iii) rplF gene species identification. WGS data were used to further characterize Neisseria species found with supplementary analyses of Neisseria cinerea genomes.Results. Based on genomic species identification, isolates from the oropharyngeal Neisseria surveilence study were composed of the following species: N. meningitidis (n=23), N. subflava (n=61), N. mucosa (n=15), N. oralis (n=8), N. cinerea (n=5), N. elongata (n=3), N. lactamica (n=2), N. bacilliformis (n=1) and N. polysaccharea (n=1). Of these 119 isolates, four isolates identified as N. meningitidis (n=3) and N. subflava (n=1) by MALDI-TOF MS, were determined to be N. polysaccharea (n=1), N. cinerea (n=2) and N. mucosa (n=1) by rMLST. Phylogenetic analyses revealed that N. cinerea isolates from the general population (n=3, cluster one) were distinct from those obtained from men who have sex with men (MSM, n=2, cluster two). The latter contained genomes misidentified as N. meningitidis using MALDI-TOF MS. These two N. cinerea clusters persisted after the inclusion of published N. cinerea WGS (n=42). Both N. cinerea clusters were further defined through pangenome and Average Nucleotide Identity (ANI) analyses.Conclusion. This study provides insights into the importance of genomic genus-wide Neisseria surveillance studies to improve the characterization and identification of the Neisseria genus.

DNA Barcoding Unveils Novel Discoveries in Authenticating High-Value Snow Lotus Seed Food Products.

Snow Lotus Seed (SLS), esteemed for its nutritional and market value, faces challenges of authentication due to the absence of appropriate testing standards and methods. This results in frequent adulteration of SLS sourced from Gleditsia sinensis (G. sinensis) with other plant seeds endosperm. Traditional chloroplast DNA barcoding methods are inadequate for species identification due to the absence of chloroplasts in G. sinensis seeds endosperm. In this study, the homology of 11 ITS genes among 6 common Gleditsia species was analyzed. Universal primers suitable for these species were designed and screened. A DNA barcoding method for distinguishing SLS species was developed using Sanger sequencing technology, leveraging existing GenBank and Barcode of Life Data System (BOLD) databases. Optimized sample pretreatment facilitated effective DNA extraction from phytopolysaccharide-rich SLS. Through testing of commercial SLS products, the species origin has been successfully identified. Additionally, a novel instance of food fraud was uncovered, where the Caesalpinia spinosa endosperm was used to counterfeit SLS for the first time. The study established that the developed DNA barcoding method is effective for authenticating SLS species. It is of great significance for combating food fraud related to SLS, ensuring food safety, and promoting the healthy development of the SLS industry.

Identification of Diptera Puparia in Forensic and Archeo-Funerary Contexts.

Diptera identification is fundamental in forensic entomology as well as in funerary archeoentomology, where the challenge is exacerbated by the presence of immature stages such as larvae and puparia. In these two developmental stages, specimens possess a very limited number of diagnostic features, and for puparia, there is also a lack of identification tools such as descriptions and identification keys. Morphological analysis, DNA-based techniques, and cuticular chemical analyses all show good potential for species identification; however, they also have some limitations. DNA-based identification is primarily hindered by the incompleteness of genetic databases and the presence of PCR inhibitors often co-extracted from the puparial cuticle. Chemical analysis of the cuticle is showing promising results, but this approach is also limited by the insufficient profile database and requires specific, expensive equipment, as well as trained personnel. Additionally, to ensure the repeatability of the analysis-a critical aspect in forensic investigations-and to preserve precious and unique specimens from museum collections, non-invasive protocols and techniques must be prioritized for species identification.

Deciphering the Plastome and Molecular Identities of Six Medicinal "Doukou" Species.

The genus Amomum includes over 111 species, 6 of which are widely utilized as medicinal plants and have already undergone taxonomic revision. Due to their morphological similarities, the presence of counterfeit and substandard products remains a challenge. Accurate plant identification is, therefore, essential to address these issues. This study utilized 11 newly sequenced samples and extensive NCBI data to perform molecular identification of the six medicinal "Doukou" species. The plastomes of these species exhibited a typical quadripartite structure with a conserved gene content. However, independent variation shifts of the SC/IR boundaries existed between and within species. The comprehensive set of genetic sequences, including ITS, ITS1, ITS2, complete plastomes, matK, rbcL, psbA-trnH, and ycf1, showed varying discrimination of the six "Doukou" species based on both distance and phylogenetic tree methods. Among these, the ITS, ITS1, and complete plastome sequences demonstrated the highest identification success rate (3/6), followed by ycf1 (2/6), and then ITS2, matK, and psbA-trnH (1/6). In contrast, rbcL failed to identify any species. This research established a basis for a reliable molecular identification method for medicinal "Doukou" plants to protect wild plant resources, promote the sustainable use of medicinal plants, and restrict the exploitation of these resources.

Establishment and Validation of a Multiplex PCR Detection System for the Identification of Six Common Edible Meat Components.

OBJECTIVES: To establish a rapid, accurate, and sensitive multiplex PCR detection method for the simultaneous identification of the six common edible meats (beef, lamp, chicken, pork, goose, duck), and to evaluate its application value in meat adulteration identification. METHODS: Based on complete mitochondrial genomic sequences of six species in the GenBank database, DNA sequences (cattle：16S rRNA; sheep：COX-1; chickens：Cytb; pig：COX-1; goose：NADH2; duck：16S rRNA) with intra-species conservation and inter-species specificity were screened, and species-specific primers were designed to construct a multiplex PCR detection system that can simultaneously detect the meat of six common species. The species specificity, sensitivity and reproducibility of the system were studied, and the simulated mixture sample detection was performed. RESULTS: This study successfully constructed a multiplex PCR detection system that can detect the meats of six common species simultaneously. The system was not effective in DNA amplification of non-target species. When the DNA template sizes were 0.062 5-2 ng/µL, the amplified products of all six species could be detected. The duck component was still detected when the mixing ratio of duck and beef was as low as 0.5%. CONCLUSIONS: This study constructs and establishes a multiplex PCR detection system with strong specificity, high sensitivity, and good reproducibility. It can accurately identify the components of animal origin in common edible meats and provide a simple and practical method for identifying adulteration of common edible meats and meat products in China.

BioEncoder: A metric learning toolkit for comparative organismal biology.

In the realm of biological image analysis, deep learning (DL) has become a core toolkit, for example for segmentation and classification. However, conventional DL methods are challenged by large biodiversity datasets characterized by unbalanced classes and hard-to-distinguish phenotypic differences between them. Here we present BioEncoder, a user-friendly toolkit for metric learning, which overcomes these challenges by focussing on learning relationships between individual data points rather than on the separability of classes. BioEncoder is released as a Python package, created for ease of use and flexibility across diverse datasets. It features taxon-agnostic data loaders, custom augmentation options, and simple hyperparameter adjustments through text-based configuration files. The toolkit's significance lies in its potential to unlock new research avenues in biological image analysis while democratizing access to advanced deep metric learning techniques. BioEncoder focuses on the urgent need for toolkits bridging the gap between complex DL pipelines and practical applications in biological research.

Metapresence: a tool for accurate species detection in metagenomics based on the genome-wide distribution of mapping reads.

Shotgun metagenomics allows comprehensive sampling of the genomic information of microbes in a given environment and is a tool of choice for studying complex microbial systems. Mapping sequencing reads against a set of reference or metagenome-assembled genomes is in principle a simple and powerful approach to define the species-level composition of the microbial community under investigation. However, despite the widespread use of this approach, there is no established way to properly interpret the alignment results, with arbitrary relative abundance thresholds being routinely used to discriminate between present and absent species. Such an approach can be affected by significant biases, especially in the identification of rare species. Therefore, it is important to develop new metrics to overcome these biases. Here, we present Metapresence, a new tool to perform reliable identification of the species in metagenomic samples based on the distribution of mapped reads on the reference genomes. The analysis is based on two metrics describing the breadth of coverage and the genomic distance between consecutive reads. We demonstrate the high precision and wide applicability of the tool using data from various synthetic communities, a real mock community, and the gut microbiome of healthy individuals and antibiotic-associated-diarrhea patients. Overall, our results suggest that the proposed approach has a robust performance in hard-to-analyze microbial communities containing contaminated or closely related genomes in low abundance.IMPORTANCEDespite the prevalent use of genome-centric alignment-based methods to characterize microbial community composition, there lacks a standardized approach for accurately identifying the species within a sample. Currently, arbitrary relative abundance thresholds are commonly employed for this purpose. However, due to the inherent complexity of genome structure and biases associated with genome-centric approaches, this practice tends to be imprecise. Notably, it introduces significant biases, particularly in the identification of rare species. The method presented here addresses these limitations and contributes significantly to overcoming inaccuracies in precisely defining community composition, especially when dealing with rare members.

Use of Biomolecular Tools to Control the Labels of Ethnic Food Coming from Eastern Europe.

In recent years, due to the large Romanian community present in Italy, the retail of foods coming from Eastern Europe has increased. The most common type of violation detected in these foods consists of incorrect labeling and species-replacement frauds. In this paper, the compliance of labels of 43 ethnic processed food coming from Eastern Europe and commercialized in Italy was evaluated by means of PCR and Sanger sequencing. Our data revealed 33% of non-compliant labels in samples containing swine, ruminants, and avian ingredients. These results demonstrate that PCR can be easily used for the identification of species in highly processed products, proving to be a rapid, effective, and economic method. On the other hand, samples reporting fish as ingredients highlighted the ineffectiveness of the applied sequencing protocol, due to the low informative property of targeted fragments or to the lack of consensus sequences in the case of uncommon species.

Biogeography of larval trematodes in the freshwater snail, Semisulcospira libertina: a comparison of the morphological and molecular approaches.

While biogeographic patterns of free-living organisms are well documented, the biogeography of parasitic fauna remains largely unclear. Due to morphological similarities, parasites are often difficult to identify without the aid of molecular genetics, further complicating the interpretation of their biogeographic patterns. We investigated trematode parasites infecting the East Asian freshwater snail Semisulcospira libertina to understand their biogeography and to evaluate how molecular approaches influence the interpretation of biogeographic patterns of the trematode fauna. We identified 46 genetically delimited species from 19 morphologically distinguishable trematodes infecting S. libertina and found that their species richness was negatively correlated to latitude. We also found that potential definitive host (fishes) richness and host body size were positively correlated with trematode species richness, suggesting that host attributes are essential factors shaping the biogeographic pattern in trematodes. These trends were observed irrespective of species identification methods, demonstrating that classical morphological identification can also effectively identify the latitudinal gradient pattern in trematodes. We further detected the distance decay of similarity in trematode communities, although this trend was only detectable in the biogeographic dataset based on molecular identification. Our study showed that morphological identification sufficiently reflects the latitudinal richness gradient while molecular identification is essential to estimate accurate local species richness and increase the resolution of the large-scale pattern of population similarities in the trematode communities.

Forensic species identification: practical guide for animal and plant DNA analysis.

The importance of non-human DNA in the forensic field has increased greatly in recent years, together with the type of applications. The molecular species identification of animal and botanical material may be crucial both for wildlife trafficking and crime scene investigation. However, especially for forensic botany, several challenges slow down the implementation of the discipline in the routine.Although the importance of molecular analysis of animal origin samples is widely recognized and the same value is acknowledged to the botanical counterpart, the latter does not find the same degree of application.The availability of molecular methods, especially useful in cases where the material is fragmented, scarce or spoiled preventing the morphological identification, is not well known. This work is intended to reaffirm the relevance of non-human forensic genetics (NHFG), highlighting differences, benefits and pitfalls of the current most common molecular analysis workflow for animal and botanical samples, giving a practical guide. A flowchart describing the analysis paths, divided in three major working areas (inspection and sampling, molecular analysis, data processing and interpretation), is provided. More real casework examples of the utility of non-human evidence in forensic investigations should be shared by the scientific community, especially for plants. Moreover, concrete efforts to encourage initiatives in order to promote quality and standardization in the NHFG field are also needed.

Organic-Acid-Sensitive Visual Sensor Array Based on Fenton Reagent-Phenol/Aniline for the Rapid Species and Adulteration Assessment of Baijiu.

Baijiu is an ancient, distilled spirit with a complicated brewing process, unique taste, and rich trace components. These trace components play a decisive role in the aroma, taste, and especially the quality of baijiu. In this paper, the redox reaction between the Fenton reagent and four reducing agents, including o-phenylenediamine (OPD), p-phenylenediamine (PPD), 4-aminophenol (PAP), and 2-aminophenol (OAP), was adopted to construct a four-channel visual sensor array for the rapid detection of nine kinds of common organic acids in baijiu and the identification of baijiu and its adulteration. By exploiting the color-changing fingerprint response brought by organic acids, each organic acid could be analyzed accurately when combined with an optimized variable-weighted least-squares support vector machine based on a particle swarm optimization (PSO-VWLS-SVM) model. What is more, this novel sensor also could achieve accurate semi-quantitative analysis of the mixed organic acid samples via partial least squares discriminant analysis (PLSDA). Most importantly, the sensor array could be further used for the identification of baijiu with different species through the PLSDA model and the adulteration assessment with the one-class partial least squares (OCPLS) model simultaneously.

DNA barcoding is currently unreliable for species identification in most crayfishes.

DNA barcoding is commonly used for species identification. Despite this, there has not been a comprehensive assessment of the utility of DNA barcoding in crayfishes (Decapoda: Astacidea). Here we examined the extent to which local barcoding gaps (used for species identification) and global barcoding gaps (used for species discovery) exist among crayfishes, and whether global gaps met a previously suggested 10× threshold (mean interspecific difference being 10× larger than mean intra specific difference). We examined barcoding gaps using publicly available mitochondrial COI sequence data from the National Center for Biotechnology Information's nucleotide database. We created two versions of the COI datasets used for downstream analyses: one focused on the number of unique haplotypes (N H) per species, and another that focused on total number of sequences (N S; i.e., including redundant haplotypes) per species. A total of 81 species were included, with 58 species and five genera from the family Cambaridae and 23 species from three genera from the family Parastacidae. Local barcoding gaps were present in only 30 species (20 Cambaridae and 10 Parastacidae species). We detected global barcoding gaps in only four genera (Cambarus, Cherax, Euastacus, and Tenuibranchiurus), which were all below (4.2× to 5.2×) the previously suggested 10× threshold. We propose that a ~5× threshold would be a more appropriate working hypothesis for species discovery. While the N H and N S datasets yielded largely similar results, there were some discrepant inferences. To understand why some species lacked a local barcoding gap, we performed species delimitation analyses for each genus using the N H dataset. These results suggest that current taxonomy in crayfishes may be inadequate for the majority of examined species, and that even species with local barcoding gaps present may be in need of taxonomic revisions. Currently, the utility of DNA barcoding for species identification and discovery in crayfish is quite limited, and caution should be exercised when mitochondrial-based approaches are used in place of taxonomic expertise. Assessment of the evidence for local and global barcoding gaps is important for understanding the reliability of molecular species identification and discovery, but outcomes are dependent on the current state of taxonomy. As this improves (e.g., via resolving species complexes, possibly elevating some subspecies to the species-level status, and redressing specimen misidentifications in natural history and other collections), so too will the utility of DNA barcoding.