BACKGROUND: Aconitum species, belonging to Ranunculaceae, have high medicinal importance but due to their overexploitation come under IUCN (International Union for Conservation of Nature) red list. The precise identification of the Aconitum species is equally important because they are used in herbal formulations. The present study aimed to develop an efficient DNA barcode system for the authentic identification of Aconitum species.
RESULTS: A set of 92 barcode gene sequences (including 12 developed during the present study and 80 retrieved from NCBI) of 5 Aconitum species (A. heterophyllum, A. vialoceum, A. japonicum, A. napellus, and A. stapfianum) were analyzed using three methods (tree-based, distance-based, and similarity-based) for species discrimination. The PWG-distance method was found most effective for species discrimination. The discrimination rate of PWG- distance ranged from 33.3% (rbcL + trnH-psbA) to 100% (ITS, rbcL + ITS, ITS + trnH-psbA and rbcL + ITS + trnH-psbA). Among DNA barcodes and their combinations, the ITS marker had the highest degree of species discrimination (NJ-40%, PWG-100% and BLAST-40%), followed by trnH-psbA (NJ-20%, PWG-60% and BLAST-20%). ITS also had higher barcoding gap as compared to other individual barcodes and their combinations. Further, we also analyzed six Aconitum species (A. balfourii, A. ferox, A. heterophyllum, A. rotundifolium, A. soongaricum and A. violaceum) existing in Western Himalaya. These species were distinguished clearly through tree-based method using the ITS barcode gene with 100% species resolution.
CONCLUSIONS: ITS showed the best species discrimination power and was used to develop species-specific barcodes for Aconitum species. DNA barcodes developed during the present study can be used to identify Aconitum species.

BACKGROUND: Fritillaria Bulbus (FB), a precious medicinal herb renowned for its heat-clearing, lung-moistening, cough-relieving and phlegm-eliminating effects. In pursuit of profits, unscrupulous merchants have engaged in the substitution or adulteration of valuable varieties with cheaper alternatives. It is, therefore, urgent to develop effective technical approaches to identify FBs from adulterants.
METHODS: This paper employed infrared spectroscopy (IR), thin layer chromatography-image analysis (TLC-IA), and untargeted metabolomics techniques to discriminate ten species of FBs.
RESULTS: Five species of FBs were successfully differentiated using mid-infrared spectroscopy. Furthermore, the power of TLC-IA technology allowed the differentiation of five species of FBs and two origins of FCBs (Fritillariae Cirrhosae Bulbus). Remarkably, through the application of untargeted metabolomics technique, the precise discrimination of five species of FBs, as well as three origins of FCBs were accomplished. Moreover, a comprehensive identification of 101 markers that reliably distinguished diverse FBs was achieved through the employment of untargeted metabolomics technique.
CONCLUSIONS: The investigation presented powerful means of detection for assuring the quality control of Fritillaria herbs.

Otoliths are small calcium carbonate structures found in the inner ear of fish and they, as one of important information carriers, are applied in diverse ecological fields. Otoliths are usually photographed and used to explore many unsolved biological and ecological questions. However, many anomalies may occur in the large volume of otolith image data due to natural or artificial consequences, which brings a huge bias to the aimed study and even misleading results. In this study, we first propose a specific definition of otolith anomalies and provide a dataset of otolith anomalies with Electrona carlsbergi, one of the most abundant species of lanternfishes, as the study subject. We modify a multiresolution knowledge distillation neural network model, the state-of-the-art anomaly detection model to a multiresolution knowledge distillation network model with asymmetric inputs, which uses grayscale maps to align the features of color maps in the feature space, to help improve otolith anomalies detection. Our fine-tuned anomaly detection network obtains a better anomaly identification performance with a Receiving Operating Characteristic Area Under the Curve value of 0.9843. Our result shown that multiresolution knowledge distillation networks can efficiently identify abnormal otolith image sample, which is of great importance for conducting otolith-based science.

暂无摘要。

Insect pests cause tremendous impact to agriculture worldwide. Species identification is crucial for implementing appropriate measures of pest control but can be challenging in closely related species. True fruit flies of the genus Anastrepha Schiner (Diptera: Tephritidae) include some of the most serious agricultural pests in the Americas, with the Anastrepha fraterculus (Wiedemann) complex being one of the most important due to its extreme polyphagy and wide distribution across most of the New World tropics and subtropics. The eight morphotypes described for this complex as well as other closely related species are classified in the fraterculus species group, whose evolutionary relationships are unresolved due to incomplete lineage sorting and introgression. We performed multifaceted phylogenomic approaches using thousands of genes to unravel the evolutionary relationships within the A. fraterculus complex to provide a baseline for molecular diagnosis of these pests. We used a methodology that accommodates variable sources of data (transcriptome, genome, and whole-genome shotgun sequencing) and developed a tool to align and filter orthologs, generating reliable datasets for phylogenetic studies. We inferred 3031 gene trees that displayed high levels of discordance. Nevertheless, the topologies of the inferred coalescent species trees were consistent across methods and datasets, except for one lineage in the A. fraterculus complex. Furthermore, network analysis indicated introgression across lineages in the fraterculus group. We present a robust phylogeny of the group that provides insights into the intricate patterns of evolution of the A. fraterculus complex supporting the hypothesis that this complex is an assemblage of closely related cryptic lineages that have evolved under interspecific gene flow. Despite this complex evolutionary scenario, our subsampling analysis revealed that a set of as few as 80 loci has a similar phylogenetic resolution as the genome-scale dataset, offering a foundation to develop more efficient diagnostic tools in this species group.

Melioidosis is a bacterial infection caused by Burkholderia pseudomallei (B. pseudomallei), posing a significant threat to public health. Rapid and accurate detection of B. pseudomallei is crucial for preventing and controlling melioidosis. However, identifying B. pseudomallei is challenging due to its high similarity to other species in the same genus. To address this issue, this study proposed a dual-target method that can specifically identify B. pseudomallei in less than 40 min. We analyzed 1722 B. pseudomallei genomes to construct large-scale pan-genomes and selected specific sequence tags in their core genomes that effectively distinguish B. pseudomallei from its closely related species. Specifically, we selected two specific tags, LC1 and LC2, which we combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR associated proteins (Cas12a) system and recombinase polymerase amplification (RPA) pre-amplification. Our analysis showed that the dual-target RPA-CRISPR/Cas12a assay has a sensitivity of approximately 0.2 copies/reaction and 10 fg genomic DNA for LC1, and 2 copies/reaction and 20 fg genomic DNA for LC2. Additionally, our method can accurately and rapidly detect B. pseudomallei in human blood and moist soil samples using the specific sequence tags mentioned above. In conclusion, the dual-target RPA-CRISPR/Cas12a method is a valuable tool for the rapid and accurate identification of B. pseudomallei in clinical and environmental samples, aiding in the prevention and control of melioidosis.

DNA barcode databases are increasingly available for a range of organisms, facilitating the wide application of DNA barcode-based studies. Here we announce the development of a comprehensive DNA barcode reference library of Japanese native woody seed plants representing 43 orders, 99 families, 303 genera and 834 species, and comprising 77.3% of the genera and 72.2% of the species of native woody seed plants in Japan. A total of 6216 plant specimens were collected from 223 sites across the subtropical, temperate, boreal and alpine biomes in Japan with most species represented by multiple accessions. This reference library utilized three chloroplast DNA regions (rbcL, trnH-psbA and matK) and consists of 14,403 barcode sequences. Individual regions varied in their identification rates, with species-level and genus-level rates for rbcL, trnH-psbA and matK based on blast being 57.4%/96.2%, 78.5%/99.1% and 67.8%/98.1%, respectively. Identification rates were higher using region combinations, with total species-level rates for two region combinations (rbcL & trnH-psbA, rbcL & matK and trnH-psbA & matK) ranging between 90.6% and 95.8%, and for all three regions being equal to 98.6%. Genus-level identification rates were even higher, ranging between 99.7% and 100% for two region combinations and being 100% for the three regions. These results indicate that this DNA barcode reference library is an effective resource for investigations of native woody seed plants in Japan using DNA barcodes and provides a useful template for the development of libraries for other components of the Japanese flora.

Rapid changes in agricultural environments caused by global warming pose a major challenge to food production and safety. Common wheat (Triticum aestivum) is a hexaploid plant (AABBDD) that shares large numbers of quantitative traits and resistance genes with B and D genomes of Aegilops species, which are responsible for several metabolic functions and biosynthetic processes, particularly in plant adaptation to biotic as well as abiotic stresses. Comparatively, the abundance of the Aegilops gene pool is much higher than that of Triticum. Therefore, we used four universal DNA barcodes for plants (ITS2, matK, rbcL, and psbM-petN) to construct a phylogenetic tree to classify the genus Aegilops. Fourteen species were distinguished among a total of 17 representative species. Aegilops biuncialis, Aegilops juvenalis, and Aegilops umbellulata could not be grouped into any of the clusters in the phylogenetic tree, indicating that these three species could not be distinguished by four DNA barcodes. Therefore, from 2408 SNPs obtained using genotyping by sequencing (GBS), we manually screened 30 SNPs that could be potentially used to classify these three species. The results of gene flow and genetic differentiation index (Fst) showed that the genetic differentiation among the three species was small, and there was bidirectional horizontal gene transfer between the three species, which was consistent with our results that the three species were difficult to classify by DNA barcode.

Bupleuri Radix (BR) is a traditional Chinese medicine and widely used for cold and fever, influenza, inflammation, hepatitis and menstrual diseases. Two authentic medicinal plants of Bupleuri chinense DC. (Beichaihu, BCH) and B. scorzonerifolium Willd. (Nanchiahu, NCH) are recommended by the current Chinese Pharmacopoeia for BR. In the present study, the comparative investigations on the anti-inflammatory effects and gas chromatography-mass spectrometry (GC-MS)-based metabolomics for the species discrimination of BCH and NCH were conducted and reported. The in vitro evaluations indicated that the supercritical fluid extracts (SFEs) (IC50 of 6.39 ± 0.52 and 1.32 ± 0.05 mg (herb)/mL for BCH and NCH) were determined to be more potent than those of the hydro-distillation extracts (HDEs) (IC50 of 203.90 ± 8.08 and 32.32 ± 2.27 mg (herb)/mL for BCH and NCH) against LPS-induced inflammation in RAW264.7 macrophages. The higher anti-inflammatory effects of NCH were associated to its different chemical compositions to the BCH as characterized by the GC-MS analysis. Furthermore, based on the metabolomics and deep chemometric approaches, a minimum combination containing 15 chemical markers was optimized from the identified components and successfully applied for the species discrimination of BCH and NCH. This study not only helps to comparative understand BCH and NCH both in phytochemistry and pharmacology, but also provides the potential chemical markers for improvement of methods for the quality control of BCH and NCH.

Commercial interest in the culinary herb, Eryngium foetidum L., has increased worldwide due to its typical pungency, similar to coriander or cilantro, with immense pharmaceutical components. The molecular delimitation and taxonomic classification of this lesser-known medicinal plant are restricted to conventional phenotyping and DNA-based marker evaluation, which hinders accurate identification, genetic conservation, and safe utilization. This study focused on species discrimination using DNA sequencing with chloroplast-plastid genes (matK, Kim matK, and rbcL) and the nuclear ITS2 gene in two Eryngium genotypes collected from the east coast region of India. The results revealed that matK discriminated between two genotypes, however, Kim matK, rbcL, and ITS2 identified these genotypes as E. foetidum. The ribosomal nuclear ITS2 region exhibited significant inter- and intra-specific divergence, depicted in the DNA barcodes and the secondary structures derived based on the minimum free energy. Although the efficiency of matK genes is better in species discrimination, ITS2 demonstrated polyphyletic phylogeny, and could be used as a reliable marker for genetic divergence studies understanding the mechanisms of RNA molecules. The results of this study provide insights into the scientific basis of species identification, genetic conservation, and safe utilization of this important medicinal plant species.