Sortase enzymes are cysteine transpeptidases that embellish the surface of Gram-positive bacteria with various proteins thereby allowing these microorganisms to interact with their neighboring environment. It is known that several of their substrates can cause pathological implications, so researchers have focused on the development of sortase inhibitors. Currently, six different classes of sortases (A-F) are recognized. However, with the extensive application of bacterial genome sequencing projects, the number of potential sortases in the public databases has exploded, presenting considerable challenges in annotating these sequences. It is very laborious and time-consuming to characterize these sortase classes experimentally. Therefore, this study developed the first machine-learning-based two-layer predictor called SortPred, where the first layer predicts the sortase from the given sequence and the second layer predicts their class from the predicted sortase. To develop SortPred, we constructed an original benchmarking dataset and investigated 31 feature descriptors, primarily on five feature encoding algorithms. Afterward, each of these descriptors were trained using a random forest classifier and their robustness was evaluated with an independent dataset. Finally, we selected the final model independently for both layers depending on the performance consistency between cross-validation and independent evaluation. SortPred is expected to be an effective tool for identifying bacterial sortases, which in turn may aid in designing sortase inhibitors and exploring their functions. The SortPred webserver and a standalone version are freely accessible at: https://procarb.org/sortpred.

Dorid nudibranchs are a large group of mollusks with approximately 2,000 recorded species. Although agreement exists on the monophyletic nature of the dorid nudibranch group, the interfamily relationships of the suborder are subject to debate. Despite efforts to elucidate this issue using short molecular markers, the conclusiveness of the findings has been hindered by branching polytomy. Mitogenomes are known to be effective markers for use in phylogenetic investigations. In this study, eight mitogenomes of dorid nudibranchs were decoded and analyzed. Gene content and structure showed little change among species, reflecting the conserved mitogenomes of dorid nudibranchs. For most genes, the direction was typical for nudibranchs; nevertheless, tRNA^Cyshad an inverse direction in Cadlinidae species. Phylogenetic trees based on nucleotide and amino acid datasets revealed a relatively consistent pattern of interfamily relationships with little difference for positions of Phyllidiidae and Cadlinidae. Species of Cadlinidae were clustered together and did not form a clade with Chromododidae. Additionally, Goniodorididae was sister to Aegiridae, whereas Discodoridae was sister to Dorididae. This finding was supported by tree topology test based on mitogenome data. The results of the present study indicate that complete mitogenomes are promising markers for investigating interfamily relationships among dorid nudibranchs.

The crustacean Daphnia pulex is one of the best model organisms for studying inducible defense mechanisms due to their inducible morphology in response to the predator Chaoborus larvae. In this study, multiple developmental stages of D. pulex were exposed to C. flavicans larvae and transcriptome profiles of samples from late embryo to fifth instar were sequenced by the RNA-seq technique to investigate the genetic background underlying inducible defenses. In comparison, differentially expressed genes between defensive and normal morphs were identified, including 908 genes in late embryo, 1383 genes in the first-third (1–3) instar, and 1042 genes in fourth-fifth (4–5) instar. Gene ontology enrichment analysis showed that structural constituents of the cuticle and structural molecule activity genes were prominent up-regulated genes in late embryos. Down-regulated genes in late embryos and 1–3 instar comprised metabolic process, hydrolase activity, and peptidase activity gene classes. Pathway analysis indicated that small molecule neurotransmitter pathways were potentially involved in the development of inducible defenses. The characterization of genes and pathways in multiple developmental stages can improve our understanding of inducible defense responses of D. pulex to predation at the molecular level.

Background: DNA barcoding provides a rapid, accurate, and standardized method for species-level identification using short DNA sequences. Such a standardized identification method is useful for mapping all the species on Earth, particularly when DNA sequencing technology is cheaply available. There are many nations in Asia with many biodiversity resources that need to be mapped and registered in databases.Results: We have built a general DNA barcode data processing system, BioBarcode, with open source software - which is a general purpose database and server. It uses mySQL RDBMS 5.0, BLAST2, and Apache httpd server. An exemplary database of BioBarcode has around 11,300 specimen entries (including GenBank data) and registers the biological species to map their genetic relationships. The BioBarcode database contains a chromatogram viewer which improves the performance in DNA sequence analyses.Conclusion: Asia has a very high degree of biodiversity and the BioBarcode database server system aims to provide an efficient bioinformatics protocol that can be freely used by Asian researchers and research organizations interested in DNA barcoding. The BioBarcode promotes the rapid acquisition of biological species DNA sequence data that meet global standards by providing specialized services, and provides useful tools that will make barcoding cheaper and faster in the biodiversity community such as standardization, depository, management, and analysis of DNA barcode data. The system can be downloaded upon request, and an exemplary server has been constructed with which to build an Asian biodiversity systemhttp://www.asianbarcode.org.

Fishes are ecologically important organisms that have long lifespans, high mobilities, and diverse trophic levels. Due to their importance, fishes are used as bioindicators for monitoring aquatic environments. One method for monitoring fishes is based on environmental DNA (eDNA), which are the deoxynucleic acids released by organisms into the environment. However, there has been a problem with false positives because eDNA is relatively stable in the environment and could even likely represent dead or non-inhabiting organisms. To address this weakness, environmental RNA (eRNA), which degrades more rapidly than eDNA in the environment, can be utilized to complement eDNA. But, to date, few studies have used eRNA for freshwater fish monitoring. In this study, to determine the relative usefulness of eDNA and eRNA metabarcoding in freshwater fishes, we performed eDNA and eRNA metabarcoding on 12S rRNA targeting fish using water samples that were collected from three locations in the Han River. We then calculated the sensitivity and positive predictivity of this approach by comparing our data to the previous specimen capture survey (PSCS) data from the last six years. The results showed that 42 species were detected by eDNA and 19 by eRNA at the three locations. At all locations, compared to the PSCS data, the average sensitivity was higher for eDNA (46.1%) than for eRNA (34.6%), and the average positive predictivity was higher for eRNA (31.7%) than for eDNA (20.7%). This confirmed that eDNA metabarcoding has the advantage of broadly determining species presence or absence (including those that are no longer present or dead), but it also generates false positives; meanwhile, eRNA metabarcoding reports living fish species, but detects fewer species than eDNA. Combining eDNA and eRNA therefore emphasizes their advantages and compensates for their disadvantages, and conducting this may therefore be useful for identifying false positives and monitoring the fish species that are actually present in the environment. This metabarcoding technique can be used in the future to provide insights into the aquatic environment and the monitoring of fisheries.