Benchmarking taxonomic classifiers with Illumina and Nanopore sequence data for clinical metagenomic diagnostic applications

Culture-independent metagenomic detection of microbial species has the potential to provide rapid and precise real-time diagnostic results. However, it is potentially limited by sequencing and classification errors. We use simulated and real-world data to benchmark rates of species misclassification using 100 reference genomes for each of ten common bloodstream pathogens and six frequent blood culture contaminants (n=1600). Simulating both with and without sequencing error for both the Illumina and Oxford Nanopore platforms, we evaluated commonly used classification tools including Kraken2, Bracken, and Centrifuge, utilising mini (8GB) and standard (30-50GB) databases. Bracken with the standard database performed best, the median percentage of reads across both sequencing platforms identified correctly to the species level was 98.46% (IQR 93.0:99.3) [range 57.1:100]. For Kraken2 with a mini database, a commonly used combination, median species-level identification was 79.3% (IQR 39.1:88.8) [range 11.2:100]. Classification performance varied by species, with E. coli being more challenging to classify correctly (59.4% to 96.4% reads with correct species, varying by tool used). By filtering out shorter Nanopore reads (<3500bp) we found performance similar or superior to Illumina sequencing, despite higher sequencing error rates. Misclassification was more common when the misclassified species had a higher average nucleotide identity to the true species. Our findings highlight taxonomic misclassification of sequencing data occurs and varies by sequencing and analysis workflow. This “bioinformatic contamination” should be accounted for in metagenomic pipelines to ensure accurate results that can support clinical decision making.

Proteomics-based screening and antibiotic resistance assessment of clinical and sub-clinical Brucella species: An evolution of brucellosis infection control

Brucellae are intracellular sneaky bacteria and they can elude the host’s defensive mechanisms, resulting in therapeutic failure. Therefore, the goal of this investigation was to rapid identification of Brucella species collected from animals and humans in Saudi Arabia, as well as to evaluate their resistance to antibiotics. On selective media, 364 animal samples as well as 70 human blood samples were cultured. Serological and biochemical approaches were initially used to identify a total of 25 probable cultured isolates. The proteomics of Brucella species were identified using the MALDI Biotyper (MBT) system, which was subsequently verified using real-time polymerase chain reaction (real-time PCR) and microfluidic electrophoresis assays. Both Brucella melitensis (B. melitensis) and Brucella abortus (B. abortus) were tested for antimicrobial susceptibility using Kirby Bauer method and the E-test. In total, 25 samples were positive for Brucella and included 11 B. melitensis and 14 B. abortus isolates. Twenty-two out of 25 (88%) and 24/25 (96%) of Brucella strains were recognized through the Vitek 2 Compact system. While MBT was magnificently identified 100% of the strains at the species level with a score value more than or equal to 2.00. Trimethoprim-sulfamethoxazole, rifampin, ampicillin-sulbactam, and ampicillin resistance in B. melitensis was 36.36%, 31.82%, 27.27%, and 22.70%, respectively. Rifampin, trimethoprim-sulfamethoxazole, ampicillin, and ampicillin-sulbactam resistance was found in 35.71%, 32.14%, 32.14%, and 28.57% of B. abortus isolates, correspondingly. MBT confirmed by microfluidic electrophoresis is a successful approach for identifying Brucella species at the species level. The resistance of B. melitensis and B. abortus to various antibiotics should be investigated in future studies.

New Hyperspectral Procedure to Discriminate Intertidal Macroalgae

The recent development and miniaturization of hyperspectral sensors embedded in drones has allowed the acquisition of hyperspectral images with high spectral and spatial resolution. The characteristics of both the embedded sensors and drones (viewing angle, flying altitude, resolution) create opportunities to consider the use of hyperspectral imagery to map and monitor macroalgae communities. In general, the overflight of the areas to be mapped is conconmittently associated accompanied with measurements carried out in the field to acquire the spectra of previously identified objects. An alternative to these simultaneous acquisitions is to use a hyperspectral library made up of pure spectra of the different species in place, that would spare field acquisition of spectra during each flight. However, the use of such a technique requires developed appropriate procedure for testing the level of species classification that can be achieved, as well as the reproducibility of the classification over time. This study presents a novel classification approach based on the use of reflectance spectra of macroalgae acquired in controlled conditions. This overall approach developed is based on both the use of the spectral angle mapper (SAM) algorithm applied on first derivative hyperspectral data. The efficiency of this approach has been tested on a hyperspectral library composed of 16 macroalgae species, and its temporal reproducibility has been tested on a monthly survey of the spectral response of different macro-algae species. In addition, the classification results obtained with this new approach were also compared to the results obtained through the use of the most recent and robust procedure published. The classification obtained shows that the developed approach allows to perfectly discriminate the different phyla, whatever the period. At the species level, the classification approach is less effective when the individuals studied belong to phylogenetically close species (i.e., Fucus spiralis and Fucus serratus).

MT-MAG: Accurate and interpretable machine learning based taxonomic assignment of metagenome-assembled genomes, with a partial classification option

We propose MT-MAG, a novel machine learning-based taxonomic assignment tool for hierarchically-structured local classification of metagenome-assembled genomes (MAGs). MT-MAG is capable of classifying large and diverse real metagenomic datasets, having analyzed for this study a total of 240 Gbp of data in the training set, and 7 Gbp of data in the test set. MT-MAG is, to the best of our knowledge, the first machine learning method for taxonomic assignment of metagenomic data that offers a "partial classification" option. MT-MAG outputs complete or a partial classification paths, and interpretable numerical classification confidences of its classifications, at all taxonomic ranks. MT-MAG is able to completely classify 48% more sequences than DeepMicrobes to the Species level (the only comparable taxonomic rank for DeepMicrobes), and it outperforms DeepMicrobes by an average of 33% in weighted accuracy, and by 89% in constrained accuracy.

Integrating voice and phenotype in a revision of the brush cuckoo Cacomantis variolosus (Aves: Cuculidae) complex

Brush cuckoos of the Cacomantis variolosus complex, which range from Southeast Asia to Australia and the Solomon Islands, have undergone much taxonomic upheaval. Here we examine 389 vocal recordings, 832 skins, and records of brood parasitism and habitat partitioning to shed light on their species and subspecies taxonomy. Bioacoustic analysis revealed seven distinct vocal groups. Among morphological markers, shape and proportions of the tail were found to be supporting indicators, in addition to plumage tone and pattern. Integration of the resulting data set distinguished six species-level taxa within the complex: sepulcralis in the Philippines and Sundaland east to central Nusa Tenggara, virescens in Sulawesi and the Sula Archipelago, aeruginosus in the Moluccas, variolosus in east Nusa Tenggara, the Moluccas, north and east Australia, New Guinea and Bismarck Archipelago, blandus in the Admiralty Islands, and addendus in the Solomon Islands. Our review of infra-specific differentiation among species leads us to distinguish 13 subspecies. All taxa identified are listed in a summary classification of the complex. Taxon diversity is greatest in the Moluccas, where two habitat-partitioned species and five allopatric subspecies occur, of which one species and three subspecies are endemic to this region.

Pragmatic Applications and Universality of DNA Barcoding for Substantial Organisms at Species Level: A Review to Explore a Way Forward

DNA barcodes are regarded as hereditary succession codes that serve as a recognition marker to address several queries relating to the identification, classification, community ecology, and evolution of certain functional traits in organisms. The mitochondrial cytochrome c oxidase 1 (CO1) gene as a DNA barcode is highly efficient for discriminating vertebrate and invertebrate animal species. Similarly, different specific markers are used for other organisms, including ribulose bisphosphate carboxylase (rbcL), maturase kinase (matK), transfer RNA-H and photosystem II D1-ApbsArabidopsis thaliana (trnH-psbA), and internal transcribed spacer (ITS) for plant species; 16S ribosomal RNA (16S rRNA), elongation factor Tu gene (Tuf gene), and chaperonin for bacterial strains; and nuclear ITS for fungal strains. Nevertheless, the taxon coverage of reference sequences is far from complete for genus or species-level identification. Applying the next-generation sequencing approach to the parallel acquisition of DNA barcode sequences could greatly expand the potential for library preparation or accurate identification in biodiversity research. Overall, this review articulates on the DNA barcoding technology as applied to different organisms, its universality, applicability, and innovative approach to handling DNA-based species identification.

Fast and pervasive diagenetic isotope exchange in foraminifera tests is species-dependent

Oxygen isotope compositions of fossil foraminifera tests are commonly used proxies for ocean paleotemperatures, with reconstructions spanning the last 112 million years. However, the isotopic composition of these calcitic tests can be substantially altered during diagenesis without discernible textural changes. Here, we investigate fluid-mediated isotopic exchange in pristine tests of three modern benthic foraminifera species (Ammonia sp., Haynesina germanica, and Amphistegina lessonii) following immersion into an 18O-enriched artificial seawater at 90 °C for hours to days. Reacted tests remain texturally pristine but their bulk oxygen isotope compositions reveal rapid and species-dependent isotopic exchange with the water. NanoSIMS imaging reveals the 3-dimensional intra-test distributions of 18O-enrichment that correlates with test ultra-structure and associated organic matter. Image analysis is used to quantify species level differences in test ultrastructure, which explains the observed species-dependent rates of isotopic exchange. Consequently, even tests considered texturally pristine for paleo-climatic reconstruction purposes may have experienced substantial isotopic exchange; critical paleo-temperature record re-examination is warranted.

Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae)

Certain species within the genus Panax L. (Araliaceae) contain pharmacological precious ginsenosides, also known as ginseng saponins. Species containing these compounds are of high commercial value and are thus of particular urgency for conservation. However, within this genus, identifying the particular species that contain these compounds by morphological means is challenging. DNA barcoding is one method that is considered promising for species level identification. However, in an evolutionarily complex genus such as Panax, commonly used DNA barcodes such as nrITS, matK, psbA-trnH, rbcL do not provide species-level resolution. A recent in silico study proposed a set of novel chloroplast markers, trnQ-rps16, trnS-trnG, petB, and trnE-trnT for species level identification within Panax. In the current study, the discriminatory efficiency of these molecular markers is assessed and validated using 91 reference barcoding sequences and 38 complete chloroplast genomes for seven species, one unidentified species and one sub-species of Panax, and two outgroup species of Aralia L. along with empirical data of Panax taxa present in Vietnam via both distance-based and tree-based methods. The obtained results show that trnQ-rps16 can classify with species level resolution every clade tested here, including the highly valuable Panax vietnamensis Ha et Grushv. We thus propose that this molecular marker to be used for identification of the species within Panax to support both its conservation and commercial trade.

Unveiling biogeographical patterns of the ichthyofauna in the Tuichi basin, a biodiversity hotspot in the Bolivian Amazon, using environmental DNA

To date, more than 2400 valid fish species have been recorded in the Amazon basin. However, some regions remain poorly documented. This is the case in the Beni basin and in particular in one of its main sub-basins, the Tuichi, an Andean foothills rivers flowing through the Madidi National Park in the Bolivian Amazonia. The knowledge of its ichthyological diversity is, however, essential for the management and protection of aquatic ecosystems, which are threatened by the development of infrastructures (dams, factories and cities), mining and deforestation. Environmental DNA (eDNA) has been relatively little used so far in the Amazon basin. We sampled eDNA from water in 34 sites in lakes and rivers in the Beni basin including 22 sites in the Tuichi sub-basin, during the dry season. To assess the biogeographical patterns of the amazonian ichthyofauna, we implemented a metabarcoding approach using two pairs of specific primers designed and developed in our laboratory to amplify two partially overlapping CO1 fragments, one of 185bp and another of 285bp. We detected 252 fish taxa (207 at species level) among which 57 are newly identified for the Beni watershed. Species compositions are significantly different between lakes and rivers but also between rivers according to their hydrographic rank and altitude. Furthermore, the diversity patterns are related to the different hydro-ecoregions through which the Tuichi flows. The eDNA approach makes it possible to identify and complete the inventory of the ichthyofauna in this still poorly documented Amazon basin. However, taxonomic identification remains constrained by the lack of reference barcodes in public databases and does not allow the assignment of all OTUs. Our results can be taken into account in conservation and management strategies and could serve as a baseline for future studies, including on other Andean tributaries.

An Analysis of the Accuracy of Photo-Based Plant Identification Applications on Fifty-Five Tree Species

Background: With the creation of photo-based plant identification applications (apps), the ability to attain basic identifications of plants in the field is seemingly available to anyone who has access to a smartphone. The use of such apps as an educational tool for students and as a major identification resource for some community science projects calls into question the accuracy of the identifications they provide. We created a study based on the context of local tree species in order to offer an informed response to students asking for guidance when choosing a tool for their support in classes. Methods: This study tested 6 mobile plant identification apps on a set of 440 photographs representing the leaves and bark of 55 tree species common to the state of New Jersey (USA). Results: Of the 6 apps tested, PictureThis was the most accurate, followed by iNaturalist, with PlantSnap failing to offer consistently accurate identifications. Overall, these apps are much more accurate in identifying leaf photos as compared to bark photos, and while these apps offer accurate identifications to the genus-level, there seems to be little accuracy in successfully identifying photos to the species-level. Conclusions: While these apps cannot replace traditional field identification, they can be used with high confidence as a tool to assist inexperienced or unsure arborists, foresters, or ecologists by helping to refine the pool of possible species for further identification.