The Barcode of Life Data Portal: bridging the biodiversity informatics divide for DNA barcoding

Characterization of mosquito host-biting networks of potential Rift Valley fever virus vectors in north-eastern KwaZulu-Natal province, South Africa

BACKGROUND

Rift Valley fever virus (RVFV) is a zoonotic mosquito-borne virus with serious implications for livestock health, human health, and the economy in Africa, and is suspected to be endemic in north-eastern KwaZulu-Natal (KZN), South Africa. The vectors of RVFV in this area are poorly known, although several species, such as Aedes (Neomelaniconion) mcintoshi, Aedes (Neomelaniconion) circumluteolus, Aedes (Aedimorphus) durbanensis, and Culex (Lasioconops) poicilipes may be involved. The aim of the study was to determine the vertebrate blood meal sources of potential RVFV mosquito vectors in north-eastern KZN and to characterize the host-biting network.

METHODS

Blood-fed mosquitoes were collected monthly from November 2019 to February 2023 using a backpack aspirator, CO2-baited Centers for Disease Control and Prevention (CDC) miniature light traps and tent traps, in the vicinity of water bodies and livestock farming households. The mosquitoes were morphologically identified. DNA was extracted from individual mosquitoes and used as templates to amplify the vertebrate cytochrome c oxidase I (COI) and cytochrome b (cytb) genes using conventional polymerase chain reaction (PCR). Amplicons were sequenced and queried in GenBank and the Barcode of Life Data systems to identify the vertebrate blood meal sources and confirm mosquito identifications. All mosquitoes were screened for RVFV using real time reverse transcription (RT)-PCR.

RESULTS

We identified the mammalian (88.8%) and avian (11.3%) blood meal sources from 409 blood-fed mosquitoes. Aedes circumluteolus (n = 128) made up the largest proportion of collected mosquitoes. Cattle (n = 195) and nyala (n = 61) were the most frequent domestic and wild hosts, respectively. Bipartite network analysis showed that the rural network consisted of more host-biting interactions than the reserve network. All mosquitoes tested negative for RVFV.

CONCLUSIONS

Several mosquito species, including Ae. circumluteolus, and vertebrate host species, including cattle and nyala, could play a central role in RVFV transmission. Future research in this region should focus on these species to better understand RVFV amplification.

Genetic, haplotype and phylogenetic analysis of Ligula intestinalis by using mt-CO1 gene marker: ecological implications, climate change and eco-genetic diversity

Abstract Ligula intestinalis is a cestode parasite that affects freshwater fish in different countries of the world. The current study aims to reveal the phylogenetic, genetic and haplotype diversity of mt-CO1 gene sequences sent to the NCBI database from different countries by using in-silico analysis. The 105 mt-CO1 (371 bp) gene sequences of L. intestinalis obtained from NCBI were used for bioinformatics analyses. Sequences were subjected to phylogenetic and haplotype analysis. As a result of the haplotype analysis of L. intestinalis, 38 haplotypes were obtained from 13 different countries. Hap24 constituted 44.76% of the obtained haplotype network. Changes in nucleotides between haplotypes occurred at 1-84 different points. China and Turkey have highest fixation index (Fst) values of 0.59761, while the lowest (-0.10526) was found between Russia and Turkey. This study provides a baseline for future studies on extensive scale on the epidemiology, ecological aspects, distribution pattern, transmission dynamics and population dispersion of L. intestinalis worldwide.

Its2vec: Fungal Species Identification Using Sequence Embedding and Random Forest Classification

Fungi play essential roles in many ecological processes, and taxonomic classification is fundamental for microbial community characterization and vital for the study and preservation of fungal biodiversity. To cope with massive fungal barcode data, tools that can implement extensive volumes of barcode sequences, especially the internal transcribed spacer (ITS) region, are necessary. However, high variation in the ITS region and computational requirements for processing high-dimensional features remain challenging for existing predictors. In this study, we developed Its2vec, a bioinformatics tool for the classification of fungal ITS barcodes to the species level. An ITS database covering more than 25,000 species in a broad range of fungal taxa was assembled. For dimensionality reduction, a word embedding algorithm was used to represent an ITS sequence as a dense low-dimensional vector. A random forest-based classifier was built for species identification. Benchmarking results showed that our model achieved an accuracy comparable to that of several state-of-the-art predictors, and more importantly, it could implement large datasets and greatly reduce dimensionality. We expect the Its2vec model to be helpful for fungal species identification and, thus, for revealing microbial community structures and in deepening our understanding of their functional mechanisms.

funbarRF: DNA barcode-based fungal species prediction using multiclass Random Forest supervised learning model

BACKGROUND

Identification of unknown fungal species aids to the conservation of fungal diversity. As many fungal species cannot be cultured, morphological identification of those species is almost impossible. But, DNA barcoding technique can be employed for identification of such species. For fungal taxonomy prediction, the ITS (internal transcribed spacer) region of rDNA (ribosomal DNA) is used as barcode. Though the computational prediction of fungal species has become feasible with the availability of huge volume of barcode sequences in public domain, prediction of fungal species is challenging due to high degree of variability among ITS regions within species.

RESULTS

A Random Forest (RF)-based predictor was built for identification of unknown fungal species. The reference and query sequences were mapped onto numeric features based on gapped base pair compositions, and then used as training and test sets respectively for prediction of fungal species using RF. More than 85% accuracy was found when 4 sequences per species in the reference set were utilized; whereas it was seen to be stabilized at ~88% if ≥7 sequence per species in the reference set were used for training of the model. The proposed model achieved comparable accuracy, while evaluated against existing methods through cross-validation procedure. The proposed model also outperformed several existing models used for identification of different species other than fungi.

CONCLUSIONS

An online prediction server "funbarRF" is established at http://cabgrid.res.in:8080/funbarrf/ for fungal species identification. Besides, an R-package funbarRF ( https://cran.r-project.org/web/packages/funbarRF/ ) is also available for prediction using high throughput sequence data. The effort put in this work will certainly supplement the future endeavors in the direction of fungal taxonomy assignments based on DNA barcode.

The marker choice: Unexpected resolving power of an unexplored CO1 region for layered DNA barcoding approaches

The potential of DNA barcoding approaches to identify single species and characterize species compositions strongly depends on the marker choice. The prominent “Folmer region”, a 648 basepair fragment at the 5’ end of the mitochondrial CO1 gene, has been traditionally applied as a universal DNA barcoding region for metazoans. In order to find a suitable marker for biomonitoring odonates (dragonflies and damselflies), we here explore a new region of the CO1 gene (CO1B) for DNA barcoding in 51 populations of 23 dragonfly and damselfly species. We compare the “Folmer region”, the mitochondrial ND1 gene (NADH dehydrogenase 1) and the new CO1 region with regard to (i) speed and reproducibility of sequence generation, (ii) levels of homoplasy and (iii) numbers of diagnostic characters for discriminating closely related sister taxa and populations. The performances of the gene regions regarding these criteria were quite different. Both, the amplification of CO1B and ND1 was highly reproducible and CO1B showed the highest potential for discriminating sister taxa at different taxonomic levels. In contrast, the amplification of the “Folmer region” using the universal primers was difficult and the third codon positions of this fragment have experienced nucleotide substitution saturation. Most important, exploring this new barcode region of the CO1 gene identified a higher discriminating power between closely related sister taxa. Together with the design of layered barcode approaches adapted to the specific taxonomic “environment”, this new marker will further enhance the discrimination power at the species level.

A comprehensive view of the web-resources related to sericulture

Recent progress in the field of sequencing and analysis has led to a tremendous spike in data and the development of data science tools. One of the outcomes of this scientific progress is development of numerous databases which are gaining popularity in all disciplines of biology including sericulture. As economically important organism, silkworms are studied extensively for their numerous applications in the field of textiles, biomaterials, biomimetics, etc. Similarly, host plants, pests, pathogens, etc. are also being probed to understand the seri-resources more efficiently. These studies have led to the generation of numerous seri-related databases which are extremely helpful for the scientific community. In this article, we have reviewed all the available online resources on silkworm and its related organisms, including databases as well as informative websites. We have studied their basic features and impact on research through citation count analysis, finally discussing the role of emerging sequencing and analysis technologies in the field of seri-data science. As an outcome of this review, a web portal named SeriPort, has been created which will act as an index for the various sericulture-related databases and web resources available in cyberspace.Database URL: http://www.seriport.in/.

Blood meal analysis and virus detection in blood-fed mosquitoes collected during the 2006-2007 Rift Valley fever outbreak in Kenya

BACKGROUND

Rift Valley fever (RVF) is a zoonosis of domestic ruminants in Africa. Blood-fed mosquitoes collected during the 2006-2007 RVF outbreak in Kenya were analyzed to determine the virus infection status and animal source of the blood meals.

MATERIALS AND METHODS

Blood meals from individual mosquito abdomens were screened for viruses using Vero cells and RT-PCR. DNA was also extracted and the cytochrome c oxidase 1 (CO1) and cytochrome b (cytb) genes amplified by PCR. Purified amplicons were sequenced and queried in GenBank and Barcode of Life Database (BOLD) to identify the putative blood meal sources.

RESULTS

The predominant species in Garissa were Aedes ochraceus, (n=561, 76%) and Ae. mcintoshi, (n=176, 24%), and Mansonia uniformis, (n=24, 72.7%) in Baringo. Ae. ochraceus fed on goats (37.6%), cattle (16.4%), donkeys (10.7%), sheep (5.9%), and humans (5.3%). Ae. mcintoshi fed on the same animals in almost equal proportions. RVFV was isolated from Ae. ochraceus that had fed on sheep (4), goats (3), human (1), cattle (1), and unidentified host (1), with infection and dissemination rates of 1.8% (10/561) and 50% (5/10), respectively, and 0.56% (1/176) and 100% (1/1) in Ae. mcintoshi. In Baringo, Ma. uniformis fed on sheep (38%), frogs (13%), duikers (8%), cattle (4%), goats (4%), and unidentified hosts (29%), with infection and dissemination rates of 25% (6/24) and 83.3% (5/6), respectively. Ndumu virus (NDUV) was also isolated from Ae. ochraceus with infection and dissemination rates of 2.3% (13/561) and 76.9% (10/13), and Ae. mcintoshi, 2.8% (5/176) and 80% (4/5), respectively. Ten of the infected Ae. ochraceus had fed on goats, sheep (1), and unidentified hosts (2), and Ae. mcintoshi on goats (3), camel (1), and donkey (1).

CONCLUSION

This study has demonstrated that RVFV and NDUV were concurrently circulating during the outbreak, and sheep and goats were the main amplifiers of these viruses respectively.

Towards the collaborative curation of the registry underlying Identifiers.org

The MIRIAM Registry (http://www.ebi.ac.uk/miriam/) records information about collections of data in the life sciences, as well as where it can be obtained. This information is used, in combination with the resolving infrastructure of Identifiers.org (http://identifiers.org/), to generate globally unique identifiers, in the form of Uniform Resource Identifier. These identifiers are now widely used to provide perennial cross-references and annotations. The growing demand for these identifiers results in a significant increase in curational efforts to maintain the underlying registry. This requires the design and implementation of an economically viable and sustainable solution able to cope with such expansion. We briefly describe the Registry, the current curation duties entailed, and our plans to extend and distribute this workload through collaborative and community efforts.

The Enzyme Portal: a case study in applying user-centred design methods in bioinformatics

User-centred design (UCD) is a type of user interface design in which the needs and desires of users are taken into account at each stage of the design process for a service or product; often for software applications and websites. Its goal is to facilitate the design of software that is both useful and easy to use. To achieve this, you must characterise users' requirements, design suitable interactions to meet their needs, and test your designs using prototypes and real life scenarios.For bioinformatics, there is little practical information available regarding how to carry out UCD in practice. To address this we describe a complete, multi-stage UCD process used for creating a new bioinformatics resource for integrating enzyme information, called the Enzyme Portal (http://www.ebi.ac.uk/enzymeportal). This freely-available service mines and displays data about proteins with enzymatic activity from public repositories via a single search, and includes biochemical reactions, biological pathways, small molecule chemistry, disease information, 3D protein structures and relevant scientific literature.We employed several UCD techniques, including: persona development, interviews, 'canvas sort' card sorting, user workflows, usability testing and others. Our hope is that this case study will motivate the reader to apply similar UCD approaches to their own software design for bioinformatics. Indeed, we found the benefits included more effective decision-making for design ideas and technologies; enhanced team-working and communication; cost effectiveness; and ultimately a service that more closely meets the needs of our target audience.

BLOG 2.0: a software system for character-based species classification with DNA Barcode sequences. What it does, how to use it

BLOG (Barcoding with LOGic) is a diagnostic and character-based DNA Barcode analysis method. Its aim is to classify specimens to species based on DNA Barcode sequences and on a supervised machine learning approach, using classification rules that compactly characterize species in terms of DNA Barcode locations of key diagnostic nucleotides. The BLOG 2.0 software, its fundamental modules, online/offline user interfaces and recent improvements are described. These improvements affect both methodology and software design, and lead to the availability of different releases on the website http://dmb.iasi.cnr.it/blog-downloads.php. Previous and new experimental tests show that BLOG 2.0 outperforms previous versions as well as other DNA Barcode analysis methods.

Assessment of four molecular markers as potential DNA barcodes for red algae Kappaphycus Doty and Eucheuma J. Agardh (Solieriaceae, Rhodophyta)

DNA barcoding has been a major advancement in the field of taxonomy, seeing much effort put into the barcoding of wide taxa of organisms, macro and microalgae included. The mitochondrial-encoded cox1 and plastid-encoded rbcL has been proposed as potential DNA barcodes for rhodophytes, but are yet to be tested on the commercially important carrageenophytes Kappaphycus and Eucheuma. This study gauges the effectiveness of four markers, namely the mitochondrial cox1, cox2, cox2-3 spacer and the plastid rbcL in DNA barcoding on selected Kappaphycus and Eucheuma from Southeast Asia. Marker assessments were performed using established distance and tree-based identification criteria from earlier studies. Barcoding patterns on a larger scale were simulated by empirically testing on the commonly used cox2-3 spacer. The phylogeny of these rhodophytes was also briefly described. In this study, the cox2 marker which satisfies the prerequisites of DNA barcodes was found to exhibit moderately high interspecific divergences with no intraspecific variations, thus a promising marker for the DNA barcoding of Kappaphycus and Eucheuma. However, the already extensively used cox2-3 spacer was deemed to be in overall more appropriate as a DNA barcode for these two genera. On a wider scale, cox1 and rbcL were still better DNA barcodes across the rhodophyte taxa when practicality and cost-efficiency were taken into account. The phylogeny of Kappaphycus and Eucheuma were generally similar to those earlier reported. Still, the application of DNA barcoding has demonstrated our relatively poor taxonomic comprehension of these seaweeds, thus suggesting more in-depth efforts in taxonomic restructuring as well as establishment.

Signal amplification by glyco-qPCR for ultrasensitive detection of carbohydrates: applications in glycobiology

Tiny amounts of carbohydrates (ca. 1 zmol) can be detected quantitatively by a real-time method based on the conjugation of carbohydrates with DNA markers (see picture). The proposed method (glyco-qPCR) provides uniform, ultrasensitive detection of carbohydrates, which can be applied to glycobiology, as well as carbohydrate-based drug discovery.

Bioinformatics opportunities for identification and study of medicinal plants

Plants have been used as a source of medicine since historic times and several commercially important drugs are of plant-based origin. The traditional approach towards discovery of plant-based drugs often times involves significant amount of time and expenditure. These labor-intensive approaches have struggled to keep pace with the rapid development of high-throughput technologies. In the era of high volume, high-throughput data generation across the biosciences, bioinformatics plays a crucial role. This has generally been the case in the context of drug designing and discovery. However, there has been limited attention to date to the potential application of bioinformatics approaches that can leverage plant-based knowledge. Here, we review bioinformatics studies that have contributed to medicinal plants research. In particular, we highlight areas in medicinal plant research where the application of bioinformatics methodologies may result in quicker and potentially cost-effective leads toward finding plant-based remedies.

An emergent science on the brink of irrelevance: a review of the past 8 years of DNA barcoding

DNA barcoding has become a well-funded, global enterprise since its proposition as a technique for species identification, delimitation and discovery in 2003. However, the rapid development of next generation sequencing (NGS) has the potential to render DNA barcoding irrelevant because of the speed with which it generates large volumes of genomic data. To avoid obsolescence, the DNA barcoding movement must adapt to use this new technology. This review examines the DNA barcoding enterprise, its continued resistance to improvement and the implications of this on the future of the discipline. We present the consistent failure of DNA barcoding to recognize its limitations and evolve its methodologies, reducing the usefulness of the data produced by the movement and throwing into doubt its ability to embrace NGS.

DNA barcoding of recently diverged species: relative performance of matching methods

Recently diverged species are challenging for identification, yet they are frequently of special interest scientifically as well as from a regulatory perspective. DNA barcoding has proven instrumental in species identification, especially in insects and vertebrates, but for the identification of recently diverged species it has been reported to be problematic in some cases. Problems are mostly due to incomplete lineage sorting or simply lack of a 'barcode gap' and probably related to large effective population size and/or low mutation rate. Our objective was to compare six methods in their ability to correctly identify recently diverged species with DNA barcodes: neighbor joining and parsimony (both tree-based), nearest neighbor and BLAST (similarity-based), and the diagnostic methods DNA-BAR, and BLOG. We analyzed simulated data assuming three different effective population sizes as well as three selected empirical data sets from published studies. Results show, as expected, that success rates are significantly lower for recently diverged species (∼75%) than for older species (∼97%) (P<0.00001). Similarity-based and diagnostic methods significantly outperform tree-based methods, when applied to simulated DNA barcode data (P<0.00001). The diagnostic method BLOG had highest correct query identification rate based on simulated (86.2%) as well as empirical data (93.1%), indicating that it is a consistently better method overall. Another advantage of BLOG is that it offers species-level information that can be used outside the realm of DNA barcoding, for instance in species description or molecular detection assays. Even though we can confirm that identification success based on DNA barcoding is generally high in our data, recently diverged species remain difficult to identify. Nevertheless, our results contribute to improved solutions for their accurate identification.

Assessment of four molecular markers as potential DNA barcodes for red algae Kappaphycus Doty and Eucheuma J. Agardh (Solieriaceae, Rhodophyta)

DNA barcoding has been a major advancement in the field of taxonomy, seeing much effort put into the barcoding of wide taxa of organisms, macro and microalgae included. The mitochondrial-encoded cox1 and plastid-encoded rbcL has been proposed as potential DNA barcodes for rhodophytes, but are yet to be tested on the commercially important carrageenophytes Kappaphycus and Eucheuma. This study gauges the effectiveness of four markers, namely the mitochondrial cox1, cox2, cox2-3 spacer and the plastid rbcL in DNA barcoding on selected Kappaphycus and Eucheuma from Southeast Asia. Marker assessments were performed using established distance and tree-based identification criteria from earlier studies. Barcoding patterns on a larger scale were simulated by empirically testing on the commonly used cox2-3 spacer. The phylogeny of these rhodophytes was also briefly described. In this study, the cox2 marker which satisfies the prerequisites of DNA barcodes was found to exhibit moderately high interspecific divergences with no intraspecific variations, thus a promising marker for the DNA barcoding of Kappaphycus and Eucheuma. However, the already extensively used cox2-3 spacer was deemed to be in overall more appropriate as a DNA barcode for these two genera. On a wider scale, cox1 and rbcL were still better DNA barcodes across the rhodophyte taxa when practicality and cost-efficiency were taken into account. The phylogeny of Kappaphycus and Eucheuma were generally similar to those earlier reported. Still, the application of DNA barcoding has demonstrated our relatively poor taxonomic comprehension of these seaweeds, thus suggesting more in-depth efforts in taxonomic restructuring as well as establishment.