Comparative genomics of Edwardsiella anguillarum and Edwardsiella piscicida isolated in Taiwan enables the identification of distinctive features and potential virulence factors using Oxford-Nanopore MinION® sequencing

Edwardsiella tarda (ET) and Edwardsiella anguillarum (EA) are the most harmful bacterial fish pathogens in Taiwan. However, there is confusion regarding the genotypic identification of E. tarda and E. piscicida (EP). Therefore, we used a novel Nanopore MinION MK1C platform to sequence and compare the complete genomes of E. piscicida and E. anguillarum. The number of coding genes, rRNA, and tRNA recorded for E. anguillarum and E. piscicida were 8322, 25, and 98, and 5458, 25, and 98, respectively. Ribosomal multilocus sequence typing (rMLST) for E. piscicida indicated 35 rps. The shared clusters between E. anguillarum and E. piscicida indicated several unique clusters for the individual genomes. The phylogenetic tree analysis for all complete genomes indicated that E. anguillarum and E. piscicida were placed into two species-specific genotypes. Distribution of subsystems for annotated genomes found that genes related to virulence, defence, and disease for E. anguillarum were 103 and those for E. piscicida were 60 and pathogenic islands (PI) were 498 and 225, respectively. Vaccine candidates were identified in silico from the core genes using high antigenic, solubility, and secretion probabilities. Altogether, the genome data revealed distinctive features between E. anguillarum and E. piscicida, which suggest different pathogenicity and thus the need for separate preventive strategies.

Integrative taxonomy using the plant core DNA barcodes in Sumatra's Burseraceae

The high diversity and limited floral information in tropical forests often pose a challenge for species identification. However, over the past decade, DNA barcoding has been employed in tropical forests, including Sumatran forests, to enhance floristic surveys. This technique facilitates the discrimination of morphologically similar species and addresses the limitations of conventional species identification, which relies on short-lived reproductive structures. This study aimed to evaluate the efficiency of matK, rbcL, and the combination of both chloroplast markers for species identification in Burseraceae by employing genetic distance and species tree inference. In this study, we collected 197 specimens representing 20 species from five genera of Burseraceae. The highest percentage of specimens' identification (36%) at the species level was obtained using matK + rbcL, followed by matK (31%), and rbcL (7%). The matK dataset presented the highest interspecific divergence with a mean of 0.008. In addition, a lack of barcode gap was observed in both markers, suggesting potential limitations of the core barcodes for distinguishing Sumatran species within Burseraceae. The monophyly test confirmed five species as monophyletic using Bayesian species tree inferences for matK. Overall, our results demonstrate that matK outperforms rbcL in species identification of Burseraceae, whereas their combination did not enhance species delimitation. To improve the molecular species assignments of this family, future studies may consider including more DNA markers in conjuction with matK, and broadening the availability of reference sequences for species that have not yet been included in the databases. The outcomes of molecular species identification vary depending on the taxonomic group under investigation. Implementation of phylogenomics for species delimitation and diagnostic marker development is strongly recommended for tropical biodiversity assessments, especially for poorly studied clades.

TSMC-Net: Deep-Learning Multigas Classification Using THz Absorption Spectra

The identification of gas mixture speciation from a complex multicomponent absorption spectrum is a problem in gas sensing that can be addressed using machine-learning approaches. Here, we report on a deep convolutional neural network for multigas classification using terahertz (THz) absorption spectra, THz spectra mixture classifier network or TSMC-Net. TSMC-Net has been developed to identify eight volatile organic compounds in mixtures based on their fingerprint rotational absorption spectra in the 220-330 GHz frequency range. A data set consisting of simulated absorption spectra for randomly generated mixtures, with absorption greater than thresholds representing detectable limits and annotated with multiple labels, was prepared for model development. The supervised multilabel classification problem, i.e., the identification of individual gases in a mixture, is converted to a supervised multiclass classification problem via label powerset conversion. The trained model is validated and tested against simulated spectra for gas mixtures, with and without white Gaussian noise. The trained model exhibits high precision, recall, and accuracy for each pure compound. Class activation maps illustrate the complex decision-making process of the model and highlight relevant frequency regions that are needed to identify unique mixtures. Finally, the model was demonstrated against measured THz absorption spectra for pure species and mixtures, acquired using a microelectronics-based THz absorption spectrometer. The data set generation strategy and deep convolutional neural network approach are generalized and can be extrapolated to other spectroscopy types, frequency ranges, and sensors.

Development of a DNA Metabarcoding Method for the Identification of Insects in Food

Insects have the potential to become an efficient and reliable food source for humans in the future and could contribute to solving problems with the current food chain. Analytical methods to verify the authenticity of foods are essential for consumer acceptance. We present a DNA metabarcoding method that enables the identification and differentiation of insects in food. The method, developed on Illumina platforms, is targeting a 200 bp mitochondrial 16S rDNA fragment, which we found to be suitable for distinguishing more than 1000 insect species. We designed a novel universal primer pair for a singleplex PCR assay. Individual DNA extracts from reference samples, DNA extracts from model foods and food products commercially available were investigated. In all of the samples investigated, the insect species were correctly identified. The developed DNA metabarcoding method has a high potential to identify and differentiate insect DNA in the context of food authentication in routine analysis.

Two Newly Identified Colletotrichum Species Associated with Mango Anthracnose in Central Thailand

Anthracnose caused by Colletotrichum spp. is one of the major problems in mango production worldwide, including Thailand. All mango cultivars are susceptible, but Nam Dok Mai See Thong (NDMST) is the most vulnerable. Through a single spore isolation method, a total of 37 isolates of Colletotrichum spp. were obtained from NDMST showing anthracnose symptoms. Identification was performed using a combination of morphology characteristics, Koch's postulates, and phylogenetic analysis. The pathogenicity assay and Koch's postulates on leaves and fruit confirmed that all Colletotrichum spp. tested were causal agents of mango anthracnose. Multilocus analysis using DNA sequences of internal transcribed spacer (ITS) regions, β-tubulin (TUB2), actin (ACT), and chitin synthase (CHS-1) was performed for molecular identification. Two concatenated phylogenetic trees were constructed using either two-loci of ITS and TUB2, or four-loci of ITS, TUB2, ACT, and CHS-1. Both phylogenetic trees were indistinguishable and showed that these 37 isolates belong to C. acutatum, C. asianum, C. gloeosporioides, and C. siamense. Our results indicated that using at least two loci of ITS and TUB2, were sufficient to infer Colletotrichum species complexes. Of 37 isolates, C. gloeosporioides was the most dominant species (19 isolates), followed by C. asianum (10 isolates), C. acutatum (5 isolates), and C. siamense (3 isolates). In Thailand, C. gloeosporioides and C. acutatum have been reported to cause anthracnose in mango, however, this is the first report of C. asianum and C. siamense associated with mango anthracnose in central Thailand.

DNA barcoding of Cymbidium by genome skimming: Call for next-generation nuclear barcodes

Cymbidium is an orchid genus that has undergone rapid radiation and has high ornamental, economic, ecological and cultural importance, but its classification based on morphology is controversial. The plastid genome (plastome), as an extension of plant standard DNA barcodes, has been widely used as a potential molecular marker for identifying recently diverged species or complicated plant groups. In this study, we newly generated 237 plastomes of 50 species (at least two individuals per species) by genome skimming, covering 71.4% of members of the genus Cymbidium. Sequence-based analyses (barcoding gaps and automatic barcode gap discovery) and tree-based analyses (maximum likelihood, Bayesian inference and multirate Poisson tree processes model) were conducted for species identification of Cymbidium. Our work provides a comprehensive DNA barcode reference library for Cymbidium species identification. The results show that compared with standard DNA barcodes (rbcL + matK) as well as the plastid trnH-psbA, the species identification rate of the plastome increased moderately from 58% to 68%. At the same time, we propose an optimized identification strategy for Cymbidium species. The plastome cannot completely resolve the species identification of Cymbidium, the main reasons being incomplete lineage sorting, artificial cultivation, natural hybridization and chloroplast capture. To further explore the potential use of nuclear data in identifying species, the Skmer method was adopted and the identification rate increased to 72%. It appears that nuclear genome data have a vital role in species identification and are expected to be used as next-generation nuclear barcodes.

Rapid Identification of Infectious Pathogens at the Single-Cell Level via Combining Hyperspectral Microscopic Images and Deep Learning

Identifying infectious pathogens quickly and accurately is significant for patients and doctors. Identifying single bacterial strains is significant in eliminating culture and speeding up diagnosis. We present an advanced optical method for the rapid detection of infectious (including common and uncommon) pathogens by combining hyperspectral microscopic imaging and deep learning. To acquire more information regarding the pathogens, we developed a hyperspectral microscopic imaging system with a wide wavelength range and fine spectral resolution. Furthermore, an end-to-end deep learning network based on feature fusion, called BI-Net, was designed to extract the species-dependent features encoded in cell-level hyperspectral images as the fingerprints for species differentiation. After being trained based on a large-scale dataset that we built to identify common pathogens, BI-Net was used to classify uncommon pathogens via transfer learning. An extensive analysis demonstrated that BI-Net was able to learn species-dependent characteristics, with the classification accuracy and Kappa coefficients being 92% and 0.92, respectively, for both common and uncommon species. Our method outperformed state-of-the-art methods by a large margin and its excellent performance demonstrates its excellent potential in clinical practice.

Application of chloroplast genome in the identification of Phyllanthus urinaria and its common adulterants

BACKGROUND

Phyllanthus urinaria L. is extensively used as ethnopharmacological material in China. In the local marketplace, this medicine can be accidentally contaminated, deliberately substituted, or mixed with other related species. The contaminants in herbal products are a threat to consumer safety. Due to the scarcity of genetic information on Phyllanthus plants, more molecular markers are needed to avoid misidentification.

METHODS

In this study, the complete chloroplast genome of nine species of the genus Phyllanthus was de novo assembled and characterized.

RESULTS

This study revealed that all of these species exhibited a conserved quadripartite structure, which includes a large single copy (LSC) region and small single copy (SSC) region, and two copies of inverted repeat regions (IRa and IRb), which separate the LSC and SSC regions. And the genome structure, codon usage, and repeat sequences were highly conserved and showed similarities among the nine species. Three highly variable regions (trnS-GCU-trnG-UCC, trnT-UGU-trnL-UAA, and petA-psbJ) might be helpful as potential molecular markers for identifying P. urinaria and its contaminants. In addition, the molecular clock analysis results showed that the divergence time of the genus Phyllanthus might occur at ~ 48.72 Ma.

CONCLUSION

This study provides valuable information for further species identification, evolution, and phylogenetic research of Phyllanthus.

Identification of Fish Species and Targeted Genetic Modifications Based on DNA Analysis: State of the Art

Food adulteration is one of the most serious problems regarding food safety and quality worldwide. Besides misleading consumers, it poses a considerable health risk associated with the potential non-labeled allergen content. Fish and fish products are one of the most expensive and widely traded commodities, which predisposes them to being adulterated. Among all fraud types, replacing high-quality or rare fish with a less valuable species predominates. Because fish differ in their allergen content, specifically the main one, parvalbumin, their replacement can endanger consumers. This underlines the need for reliable, robust control systems for fish species identification. Various methods may be used for the aforementioned purpose. DNA-based methods are favored due to the characteristics of the target molecule, DNA, which is heat resistant, and the fact that through its sequencing, several other traits, including the recognition of genetic modifications, can be determined. Thus, they are considered to be powerful tools for identifying cases of food fraud. In this review, the major DNA-based methods applicable for fish meat and product authentication and their commercial applications are discussed, the possibilities of detecting genetic modifications in fish are evaluated, and future trends are highlighted, emphasizing the need for comprehensive and regularly updated online database resources.

First tiger shark Galeocerdo cuvier bite in 75 years in French Polynesia (Eastern Central Pacific)

We analyzed a tiger shark (estimated 2.8 m total length) bite on a snorkeler. The removal of the terminal part of the leg suggests a predatory motivation for the bite. This is the first documented bite by a tiger shark in French Polynesia waters for the past 75 years.

Genomic investigation refutes record of most diverged avian hybrid

The most diverged avian hybrid that has been documented (Numida meleagris × Penelope superciliaris) was reported in 1957. This identification has yet to be confirmed, and like most contemporary studies of hybridization, the identification was based on phenotype, which can be misleading. In this study, we sequenced the specimen in question and performed analyses to validate the specimen's parentage. We extracted DNA from the specimen in a dedicated ancient DNA facility and performed whole-genome short-read sequencing. We used BLAST to find Galliformes sequences similar to the hybrid specimen reads. We found that the proportion of BLAST hits mapped overwhelmingly to two species, N. meleagris and Gallus gallus. Additionally, we constructed phylogenies using avian orthologs and parsed the species placed as sister to the hybrid. Again, the hybrid specimen was placed as a sister to N. meleagris and G. gallus. Despite not being a hybrid between N. meleagris and P. superciliaris, the hybrid still represents the most diverged avian hybrid confirmed with genetic data. In addition to correcting the "record" of the most diverged avian hybrid, these findings support recent assertions that morphological and behavioral-based identifications of avian hybrids can be error-prone. Consequently, this study serves as a cautionary tale to researchers of hybridization.

Species identification, antibiotic resistance, and virulence in Enterobacter cloacae complex clinical isolates from South Korea

This study aimed to identify the species of Enterobacter cloacae complex (ECC) isolates and compare the genotype, antibiotic resistance, and virulence among them. A total of 183 ECC isolates were collected from patients in eight hospitals in South Korea. Based on partial sequences of hsp60 and phylogenetic analysis, all ECC isolates were identified as nine species and six subspecies. Enterobacter hormaechei was the predominant species (47.0%), followed by Enterobacter kobei, Enterobacter asburiae, Enterobacter ludiwigii, and Enterobacter roggenkampii. Multilocus sequence typing analysis revealed that dissemination was not limited to a few clones, but E. hormaechei subsp. xiangfangensis, E. hormaechei subsp. steigerwaltii, and E. ludwigii formed large clonal complexes. Antibiotic resistance rates were different between the ECC species. In particular, E. asburiae, E. kobei, E. roggenkampii, and E. cloacae isolates were highly resistant to colistin, whereas most E. hormaechei and E. ludwigii isolates were susceptible to colistin. Virulence was evaluated through serum bactericidal assay and the Galleria mellonella larvae infection model. Consistency in the results between the serum resistance and the G. mellonella larvae infection assay was observed. Serum bactericidal assay showed that E. hormaechei, E. kobei, and E. ludwigii were significantly more virulent than E. asburiae and E. roggenkampii. In this study, we identified the predominant ECC species in South Korea and observed the differences in antibiotic resistance and virulence between the species. Our findings suggest that correct species identification, as well as continuous monitoring is crucial in clinical settings.

Super-Mitobarcoding in Plant Species Identification? It Can Work! The Case of Leafy Liverworts Belonging to the Genus Calypogeia

Molecular identification of species is especially important where traditional taxonomic methods fail. The genus Calypogeia belongs to one of the tricky taxons. The simple morphology of these species and a tendency towards environmental plasticity make them complicated in identification. The finding of the universal single-locus DNA barcode in plants seems to be 'the Holy Grail'; therefore, researchers are increasingly looking for multiloci DNA barcodes or super-barcoding. Since the mitochondrial genome has low sequence variation in plants, species delimitation is usually based on the chloroplast genome. Unexpectedly, our research shows that super-mitobarcoding can also work! However, our outcomes showed that a single method of molecular species delimitation should be avoided. Moreover, it is recommended to interpret the results of molecular species delimitation alongside other types of evidence, such as ecology, population genetics or comparative morphology. Here, we also presented genetic data supporting the view that C. suecica is not a homogeneous species.

Changes in and Recognition of Electrochemical Fingerprints of Acer spp. in Different Seasons

Electroanalytical chemistry is a metrological analysis technique that provides information feedback by measuring the voltammetric signal that changes when a molecule is involved in an electrochemical reaction. There is variability in the type and content of electrochemically active substances among different plants, and the signal differences presented by such differences in electrochemical reactions can be used for plant identification and physiological monitoring. This work used electroanalytical chemistry to monitor the growth of three Acer spp. This work explores the feasibility of the electrochemical analysis technique for the physiological monitoring of highly differentiated plants within the genus and further validates the technique. Changes in the electrochemical fingerprints of A. cinnamomifolium, A. sinopurpurascens and A. palmatum 'Matsumurae' were recorded during the one-year developmental cycle. The results show that the differences in the electrochemical fingerprint profiles of Acer spp. can be used to distinguish different species and identify the growth status in each season. This work also concludes with an identification flowchart based on electrochemical fingerprinting.

Comparative and phylogenetic analysis of complete chloroplast genomes from five Artemisia species

Artemisia Linn. is a large genus within the family Asteraceae that includes several important medicinal plants. Because of their similar morphology and chemical composition, traditional identification methods often fail to distinguish them. Therefore, developing an effective identification method for Artemisia species is an urgent requirement. In this study, we analyzed 15 chloroplast (cp) genomes, including 12 newly sequenced genomes, from 5 Artemisia species. The cp genomes from the five Artemisia species had a typical quadripartite structure and were highly conserved across species. They had varying lengths of 151,132-151,178 bp, and their gene content and codon preferences were similar. Mutation hotspot analysis identified four highly variable regions, which can potentially be used as molecular markers to identify Artemisia species. Phylogenetic analysis showed that the five Artemisia species investigated in this study were sister branches to each other, and individuals of each species formed a monophyletic clade. This study shows that the cp genome can provide distinguishing features to help identify closely related Artemisia species and has the potential to serve as a universal super barcode for plant identification.

Comparative analysis of medicinal plant Isodon rubescens and its common adulterants based on chloroplast genome sequencing

Isodon rubescens (Hemsley) H. Hara is the source of Donglingcao under the monograph Rabdosiae Rubescentis Herba in Chinese Pharmacopoeia. In the local marketplace, this medicine can be accidentally contaminated, deliberately substituted, or mixed with other related species. The contaminants of herbal products are a threat to consumer safety. Due to the scarcity of genetic information on Isodon plants, more molecular markers are needed to avoid misidentification. In the present study, the complete chloroplast (cp) genome of seven species of Isodon was sequenced, de novo assembled and characterized. The cp genomes of these species universally exhibited a conserved quadripartite structure, i.e., two inverted repeats (IRs) containing most of the ribosomal RNA genes and two unique regions (large single copy and small single copy). Moreover, the genome structure, codon usage, and repeat sequences were highly conserved and showed similarities among the seven species. Five highly variable regions (trnS-GCU-trnT-CGU, atpH-atpI, trnE-UUC-trnT-GGU, ndhC-trnM-CAU, and rps15-ycf1) might be potential molecular markers for identifying I. rubescens and its contaminants. These findings provide valuable information for further species identification, evolution, and phylogenetic research of Isodon.

From development to taxonomy: the case of Sciaenacotyle pancerii (Monogenea: Microcotylidae) in the Mediterranean meagre

The microcotylid Sciaenacotyle pancerii is a pathogenic monogenean infecting Argyrosomus regius, a candidate for species diversification in the Mediterranean aquaculture. Life-history stages of S. pancerii commonly co-occur in field infections, but to date, morphological data have only been provided for oncomiracidia and adults although identifying life-history stages can be useful in infection management. A total of 114 specimens of S. pancerii were analysed to characterize the developmental events and to assess morphological and morphometric variations before and after maturity. The post-larval development of S. pancerii is characterized by: expansion and bifurcation of the gut, loss of the larval haptor, protandrous development of the genitalia and vitellaria formation. The size variability of larval hooks, hamuli and germanium of S. pancerii is firstly reported and dimensional ranges of parasite body, haptor, testes, posteriormost clamps and eggs are widened. The size of most of the diagnostic features of S. pancerii significantly increases after parasite maturity and therefore, only those specimens with more than 116 clamps should be considered for minimising development-related variability in size. The high number of clamps, their fast development and the asymmetry in their size and arrangement suggest that S. pancerii may use a mixed attachment strategy between the closely related microcotylids and heteraxinids. This combination of features may be host related and linked to the gill structure of the sciaenid fish and the phylogenetic position of the genus Sciaenacotyle; distant from other microcotylids while close to heteraxinid species.

Lapillus otolith shape, a useful taxonomic feature for the identification of sea catfishes (Ariidae: Siluriformes) from the north-eastern Pacific

Otolith shape is widely used as a taxonomic feature in fish systematics. In Siluriformes, the lapillus otolith is the most relevant character for taxonomic purposes, although its discriminant potential has not been assessed quantitatively. Our study model were sea catfishes of the family Ariidae from the north-eastern Pacific as representatives of Siluriformes, a taxon with increased taxonomic complexity. The lapillus otolith shape obtained by geometric morphometrics showed high discrimination potential both at the genus and species levels with an overall classification accuracy of c. 93% (K = 0.92). Due to the strong species delimitation exhibited by lapillus otolith shape, the descriptions and identification keys provided here are the most useful materials to recognize the eight sea catfish species evaluated. The shared similarities in lapillus otolith shape among species seem to be more influenced by phylogenetic relationships than other factors such as habitat. The lapillus otolith shape is the most powerful taxonomic feature discovered so far for the identification of sea catfishes from the north-eastern Pacific.

Chloroplast genome characterization of Rubus arcticus L

Rubus arcticus Linnaeus (1753) is a medicinal and edible plant in the Rosaceae with wide distribution in northeast China. The total length of the genome was 156,668 bp with a GC content of 37.1%, including a large single-copy (LSC, 85,958 bp) region, a small single-copy region (SSC, 18,756 bp), and inverted repeat (IR, 51,954 bp) regions. A total of 129 genes were identified. The numbers of protein genes tRNAs and rRNAs were 85, 36, and 8, respectively. Phylogenetic analysis indicated that R. arcticus belongs to the Rubus genus. Published R. arcticus chloroplast genomes have yielded insights into the closely related species identification, phylogenetic position and Rubus evolution.

Species identification by MALDI-TOF MS and gap PCR-RFLP of non-aureus Staphylococcus, Mammaliicoccus, and Streptococcus spp. associated with sheep and goat mastitis

Staphylococci and streptococci are common causes of intramammary infection in small ruminants, and reliable species identification is crucial for understanding epidemiology and impact on animal health and welfare. We applied MALDI-TOF MS and gap PCR–RFLP to 204 non-aureus staphylococci (NAS) and mammaliicocci (NASM) and to 57 streptococci isolated from the milk of sheep and goats with mastitis. The top identified NAS was Staphylococcus epidermidis (28.9%) followed by Staph. chromogenes (27.9%), haemolyticus (15.7%), caprae, and simulans (6.4% each), according to both methods (agreement rate, AR, 100%). By MALDI-TOF MS, 13.2% were Staph. microti (2.9%), xylosus (2.0%), equorum, petrasii and warneri (1.5% each), Staph. sciuri (now Mammaliicoccus sciuri, 1.0%), arlettae, capitis, cohnii, lentus (now M. lentus), pseudintermedius, succinus (0.5% each), and 3 isolates (1.5%) were not identified. PCR–RFLP showed 100% AR for Staph. equorum, warneri, arlettae, capitis, and pseudintermedius, 50% for Staph. xylosus, and 0% for the remaining NASM. The top identified streptococcus was Streptococcus uberis (89.5%), followed by Strep. dysgalactiae and parauberis (3.5% each) and by Strep. gallolyticus (1.8%) according to both methods (AR 100%). Only one isolate was identified as a different species by MALDI-TOF MS and PCR–RFLP. In conclusion, MALDI-TOF MS and PCR–RFLP showed a high level of agreement in the identification of the most prevalent NAS and streptococci causing small ruminant mastitis. Therefore, gap PCR–RFLP can represent a good identification alternative when MALDI-TOF MS is not available. Nevertheless, some issues remain for Staph. haemolyticus, minor NAS species including Staph. microti, and species of the novel genus Mammaliicoccus.

Current Analytical Methods and Research Trends Are Used to Identify Domestic Pig and Wild Boar DNA in Meat and Meat Products

The pig, one of the most important livestock species, is a meaningful source of global meat production. It is necessary, however, to prove whether a food product that a discerning customer selects in a store is actually made from pork or venison, or does not contain it at all. The problem of food authenticity is widespread worldwide, and cases of meat adulteration have accelerated the development of food and the identification methods of feed species. It is worth noting that several different molecular biology techniques can identify a porcine component. However, the precise differentiation between wild boar and a domestic pig in meat products is still challenging. This paper presents the current state of knowledge concerning the species identification of the domestic pig and wild boar DNA in meat and its products.

First detection of Trichothecium roseum causing leaf spots on tomato in Germany

Tomato (Solanum lycopersicum L.) is one of the most popular vegetables in Germany and the demand for organically grown tomatoes in particular is growing steadily. In seasonal low-cost organic tomato cultivation, the leaf mould disease caused by Fulvia fulva is an increasing problem (Meyer et al. 2021). In 2020-2021, during a survey for F. fulva infected tomato leaves in Germany, untypical, circular, and dark brown necrotic spots were observed. To identify the pathogen, symptomatic leaves were collected from three different geographic locations in the north and south of Germany. Specimens were observed under a stereomicroscope and immediately processed. After surface disinfection of symptomatic leaf material, the leaf tissues were placed on potato dextrose agar (PDA) and subsequently incubated at 25 °C in the dark allowing mycelium to grow. Single spore isolates from each location were prepared for morphological and molecular analyses, as well as for pathogenicity determination. Three single spore isolates (JKI-GFP-22-010 - 012) showed moderate to rapid growth rates that reached 4 cm in diameter after 7 days. Based solely on morphology (S1), they were identified as Trichothecium roseum (Pers.) Link (Link 1809) by having pink dense mycelium with circular and rough edge colonies. The conidiophores were simple or branched (105 - 254 × 2 - 4 μm). Conidia were 2-celled, smooth, thick-walled, hyaline, ellipsoid to pyriform with slanting and truncate basal mark, and were produced in clusters, (10 - 18 × 7 - 9.5 μm). To afford the genetic data of these fungi, fungal DNA was extracted using a DNAeasy® Kit Plant Mini Kit (QIAGEN®, Germany) and then subjected to PCR using the primer sets as follows, ITS1/ITS4 (White et al. 1990) and LROR/LR6 (Vilgalys et al. 1990). The consensus sequences generated in this study were deposited in GenBank under the accession numbers ON787818 - 20 and ON787821 - 23, for ITS and LSU, respectively, and compared via NCBI-BLAST. Initial BLAST searches of both ITS and LSU regions revealed that the isolates share 99 - 100% homology with T. roseum. The morphology and phylogeny (S2) supported assignment of all isolates to T. roseum. To fulfil Koch's postulate, the pathogenicity of selected isolates (JKI-GFP-22-010 and 012) were tested by spraying spore suspensions (105 conidia ml-1) on adaxial surface of 21-day-old tomato plants cv. 'Moneymaker' (n=10). Plants sprayed with sterile water served as controls. All tomato plants were grown under greenhouse conditions (average 25 °C, 98% relative humidity). After 21 days, symptoms were identical to those of the originally infected leaves associated with T. roseum. As the disease progressed, necrotic lesions reached approximately 35 mm in diameter. The fungus was re-isolated and identified as T. roseum. No symptoms developed in the control plants. Trichothecium roseum has been detected infecting fruit, particularly on tomatoes, e.g. in Argentina (Dal et al. 2008), Brazil (Inácio et al. 2011), Korea (Yun et al. 2013), and Pakistan (Hamid et al. 2014). To our knowledge, this is the first report of T. roseum infecting tomato in Germany. As the pathogen was found in several locations in the south and north, it is likely already well established in Germany. To date, it seems to play a minor role in pathogenicity of tomatoes but should be monitored, especially with regard to climate change as there are now several recent reports from the temperate region. The disease development and interaction between susceptible host and pathogen should be concerned.

An Efficient Model for a Vast Number of Bird Species Identification Based on Acoustic Features

Birds have been widely considered crucial indicators of biodiversity. It is essential to identify bird species precisely for biodiversity surveys. With the rapid development of artificial intelligence, bird species identification has been facilitated by deep learning using audio samples. Prior studies mainly focused on identifying several bird species using deep learning or machine learning based on acoustic features. In this paper, we proposed a novel deep learning method to better identify a large number of bird species based on their call. The proposed method was made of LSTM (Long Short-Term Memory) with coordinate attention. More than 70,000 bird-call audio clips, including 264 bird species, were collected from Xeno-Canto. An evaluation experiment showed that our proposed network achieved 77.43% mean average precision (mAP), which indicates that our proposed network is valuable for automatically identifying a massive number of bird species based on acoustic features and avian biodiversity monitoring.

Development of a Rapid, Accurate, and On-Site Detection Protocol for Red Imported Fire Ants, Solenopsis invicta (Hymenoptera: Formicidae)

A rapid, accurate, and on-site molecular diagnostic protocol for red imported fire ants (Solenopsis invicta, Si) was developed using loop-mediated isothermal amplification (LAMP) assays. Si11977 (GenBank accession no. MK986826) was confirmed to be a Si-specific gene. Four-primer Si11977-LAMP (4pSi-LAMP) and six-primer Si11977-LAMP (6pSi-LAMP) assays specifically detected Si. The reaction time of 6pSi-LAMP assays was reduced by 5 min compared with 4pSi-LAMP assays. The optimal amount of polymerase and the detection limit for the 6pSi-LAMP assays were 0.1 unit/μL and 5 fg/μL, respectively. In addition, a method for extracting genomic DNA from ant tissues within 2 to 3 min and a protocol for performing on-site LAMP assays using a car heating mug and a LAMP observation box were described. The on-site Si detection protocol used in this study was possible within 30 min from DNA extraction to species identification.