To culture or not to culture: careful assessment of metabarcoding data is necessary when evaluating the microbiota of a modified-atmosphere-packaged vegetarian meat alternative throughout its shelf-life period.

BACKGROUND: As the increased consumption of ready-to-eat meat alternatives is a fairly recent trend, little is known about the composition and dynamics of the microbiota present on such products. Such information is nonetheless valuable in view of spoilage and food safety prevention. Even though refrigeration and modified-atmosphere-packaging (MAP) can extend the shelf-life period, microbial spoilage can still occur in these products. In the present study, the microbiota of a vegetarian alternative to poultry-based charcuterie was investigated during storage, contrasting the use of a culture-dependent method to a culture-independent metagenetic method. RESULTS: The former revealed that lactic acid bacteria (LAB) were the most abundant microbial group, specifically at the end of the shelf-life period, whereby Latilactobacillus sakei was the most abundant species. Metabarcoding analysis, in contrast, revealed that DNA of Xanthomonas was most prominently present, which likely was an artifact due to the presence of xanthan gum as an ingredient, followed by Streptococcus and Weissella. CONCLUSIONS: Taken together, these results indicated that Lb. sakei was likely the most prominent specific spoilage organisms (SSO) and, additionally, that the use of metagenetic analysis needs to be interpreted with care in this specific type of product. In order to improve the performance of metagenetics in food samples with a high DNA matrix but a low bacterial DNA load, selective depletion techniques for matrix DNA could be explored.

Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments.

The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as 'Amplicon Sequence Variants' (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.

Mapping biodiversity hotspots of fish communities in subtropical streams through environmental DNA.

Large tropical and subtropical rivers are among the most biodiverse ecosystems worldwide, but also suffer from high anthropogenic pressures. These rivers are hitherto subject to little or no routine biomonitoring, which would be essential for identification of conservation areas of high importance. Here, we use a single environmental DNA multi-site sampling campaign across the 200,000 km2 Chao Phraya river basin, Thailand, to provide key information on fish diversity. We found a total of 108 fish taxa and identified key biodiversity patterns within the river network. By using hierarchical clustering, we grouped the fish communities of all sites across the catchment into distinct clusters. The clusters not only accurately matched the topology of the river network, but also revealed distinct groups of sites enabling informed conservation measures. Our study reveals novel opportunities of large-scale monitoring via eDNA to identify relevant areas within whole river catchments for conservation and habitat protection.

Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions.

Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.

Use of a Plasmodium vivax genetic barcode for genomic surveillance and parasite tracking in Sri Lanka.

BACKGROUND: Sri Lanka was certified as a malaria-free nation in 2016; however, imported malaria cases continue to be reported. Evidence-based information on the genetic structure/diversity of the parasite populations is useful to understand the population history, assess the trends in transmission patterns, as well as to predict threatening phenotypes that may be introduced and spread in parasite populations disrupting elimination programmes. This study used a previously developed Plasmodium vivax single nucleotide polymorphism (SNP) barcode to evaluate the population dynamics of P. vivax parasite isolates from Sri Lanka and to assess the ability of the SNP barcode for tracking the parasites to its origin. METHODS: A total of 51 P. vivax samples collected during 2005-2011, mainly from three provinces of the country, were genotyped for 40 previously identified P. vivax SNPs using a high-resolution melting (HRM), single-nucleotide barcode method. Minor allele frequencies, linkage disequilibrium, pair-wise FST values, and complexity of infection (COI) were evaluated to determine the genetic diversity. Structure analysis was carried out using STRUCTURE software (Version 2.3.4) and SNP barcode was used to identify the genetic diversity of the local parasite populations collected from different years. Principal component analysis (PCA) was used to determine the clustering according to global geographic regions. RESULTS: The proportion of multi-clone infections was significantly higher in isolates collected during an infection outbreak in year 2007. The minor allele frequencies of the SNPs changed dramatically from year to year. Significant linkage was observed in sample sub-sets from years 2005 and 2007. The majority of the isolates from 2007 consisted of at least two genetically distinct parasite strains. The overall percentage of multi-clone infections for the entire parasite sample was 39.21%. Analysis using STRUCTURE software (Version 2.3.4) revealed the high genetic diversity of the sample sub-set from year 2007. In-silico analysis of these data with those available from other global geographical regions using PCA showed distinct clustering of parasite isolates according to geography, demonstrating the usefulness of the barcode in determining an isolate to be indigenous. CONCLUSIONS: Plasmodium vivax parasite isolates collected during a disease outbreak in year 2007 were more genetically diverse compared to those collected from other years. In-silico analysis using the 40 SNP barcode is a useful tool to track the origin of an isolate of uncertain origin, especially to differentiate indigenous from imported cases. However, an extended barcode with more SNPs may be needed to distinguish highly clonal populations within the country.

Inference and effects of barcode multiplets in droplet-based single-cell assays.

A widespread assumption for single-cell analyses specifies that one cell's nucleic acids are predominantly captured by one oligonucleotide barcode. Here, we show that ~13-21% of cell barcodes from the 10x Chromium scATAC-seq assay may have been derived from a droplet with more than one oligonucleotide sequence, which we call "barcode multiplets". We demonstrate that barcode multiplets can be derived from at least two different sources. First, we confirm that approximately 4% of droplets from the 10x platform may contain multiple beads. Additionally, we find that approximately 5% of beads may contain detectable levels of multiple oligonucleotide barcodes. We show that this artifact can confound single-cell analyses, including the interpretation of clonal diversity and proliferation of intra-tumor lymphocytes. Overall, our work provides a conceptual and computational framework to identify and assess the impacts of barcode multiplets in single-cell data.

DNA barcode reference libraries for the monitoring of aquatic biota in Europe: Gap-analysis and recommendations for future work.

Effective identification of species using short DNA fragments (DNA barcoding and DNA metabarcoding) requires reliable sequence reference libraries of known taxa. Both taxonomically comprehensive coverage and content quality are important for sufficient accuracy. For aquatic ecosystems in Europe, reliable barcode reference libraries are particularly important if molecular identification tools are to be implemented in biomonitoring and reports in the context of the EU Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). We analysed gaps in the two most important reference databases, Barcode of Life Data Systems (BOLD) and NCBI GenBank, with a focus on the taxa most frequently used in WFD and MSFD. Our analyses show that coverage varies strongly among taxonomic groups, and among geographic regions. In general, groups that were actively targeted in barcode projects (e.g. fish, true bugs, caddisflies and vascular plants) are well represented in the barcode libraries, while others have fewer records (e.g. marine molluscs, ascidians, and freshwater diatoms). We also found that species monitored in several countries often are represented by barcodes in reference libraries, while species monitored in a single country frequently lack sequence records. A large proportion of species (up to 50%) in several taxonomic groups are only represented by private data in BOLD. Our results have implications for the future strategy to fill existing gaps in barcode libraries, especially if DNA metabarcoding is to be used in the monitoring of European aquatic biota under the WFD and MSFD. For example, missing species relevant to monitoring in multiple countries should be prioritized for future collaborative programs. We also discuss why a strategy for quality control and quality assurance of barcode reference libraries is needed and recommend future steps to ensure full utilisation of metabarcoding in aquatic biomonitoring.

DNA barcoding validates species labelling of certified seafood.

Seafood is one of the most traded food commodities in the world with demand steadily increasing [1]. There is, however, a rising concern over the vulnerability of seafood supply chains to species mislabelling and fraud [1,2]. DNA methods have been widely used to detect species mislabelling and a recent meta-analysis of 4500 seafood product tests from 51 publications found an average of 30 percent were not the species stated on the label or menu [3]. This high rate poses a serious threat to consumer trust, reputations of seafood businesses and the sustainability of fishery resources. Seafood certification schemes may help reduce this problem. Here, we use DNA barcoding [4] to validate the species identity of 1402 certified seafood products derived from 27 species across 18 countries and find that in over 99% of cases species labelling was correct.

ERASE-Seq: Leveraging replicate measurements to enhance ultralow frequency variant detection in NGS data.

The accurate detection of ultralow allele frequency variants in DNA samples is of interest in both research and medical settings, particularly in liquid biopsies where cancer mutational status is monitored from circulating DNA. Next-generation sequencing (NGS) technologies employing molecular barcoding have shown promise but significant sensitivity and specificity improvements are still needed to detect mutations in a majority of patients before the metastatic stage. To address this we present analytical validation data for ERASE-Seq (Elimination of Recurrent Artifacts and Stochastic Errors), a method for accurate and sensitive detection of ultralow frequency DNA variants in NGS data. ERASE-Seq differs from previous methods by creating a robust statistical framework to utilize technical replicates in conjunction with background error modeling, providing a 10 to 100-fold reduction in false positive rates compared to published molecular barcoding methods. ERASE-Seq was tested using spiked human DNA mixtures with clinically realistic DNA input quantities to detect SNVs and indels between 0.05% and 1% allele frequency, the range commonly found in liquid biopsy samples. Variants were detected with greater than 90% sensitivity and a false positive rate below 0.1 calls per 10,000 possible variants. The approach represents a significant performance improvement compared to molecular barcoding methods and does not require changing molecular reagents.

The effect of DNA degradation bias in passive sampling devices on metabarcoding studies of arthropod communities and their associated microbiota.

PCR amplification bias is a well-known problem in metagenomic analysis of arthropod communities. In contrast, variation of DNA degradation rates is a largely neglected source of bias. Differential degradation of DNA molecules could cause underrepresentation of taxa in a community sequencing sample. Arthropods are often collected by passive sampling devices, like malaise traps. Specimens in such a trap are exposed to varying periods of suboptimal storage and possibly different rates of DNA degradation. Degradation bias could thus be a significant issue, skewing diversity estimates. Here, we estimate the effect of differential DNA degradation on the recovery of community diversity of Hawaiian arthropods and their associated microbiota. We use a simple DNA size selection protocol to test for degradation bias in mock communities, as well as passively collected samples from actual Malaise traps. We compare the effect of DNA degradation to that of varying PCR conditions, including primer choice, annealing temperature and cycle number. Our results show that DNA degradation does indeed bias community analyses. However, the effect of this bias is of minor importance compared to that induced by changes in PCR conditions. Analyses of the macro and microbiome from passively collected arthropod samples are thus well worth pursuing.

Pay Attention to the Overlooked Cryptic Diversity in Existing Barcoding Data: the Case of Mollusca with Character-Based DNA Barcoding.

With the global biodiversity crisis, DNA barcoding aims for fast species identification and cryptic species diversity revelation. For more than 10 years, large amounts of DNA barcode data have been accumulating in publicly available databases, most of which were conducted by distance or tree-building methods that have often been argued, especially for cryptic species revelation. In this context, overlooked cryptic diversity may exist in the available barcoding data. The character-based DNA barcoding, however, has a good chance for detecting the overlooked cryptic diversity. In this study, marine mollusk was as the ideal case for detecting the overlooked potential cryptic species from existing cytochrome c oxidase I (COI) sequences with character-based DNA barcode. A total of 1081 COI sequences of mollusks, belonging to 176 species of 25 families of Gastropoda, Cephalopoda, and Lamellibranchia, were conducted by character analysis. As a whole, the character-based barcoding results were consistent with previous distance and tree-building analysis for species discrimination. More importantly, quite a number of species analyzed were divided into distinct clades with unique diagnostical characters. Based on the concept of cryptic species revelation of character-based barcoding, these species divided into separate taxonomic groups might be potential cryptic species. The detection of the overlooked potential cryptic diversity proves that the character-based barcoding mode possesses more advantages of revealing cryptic biodiversity. With the development of DNA barcoding, making the best use of barcoding data is worthy of our attention for species conservation.

Bacterial metabarcoding by 16S rRNA gene ion torrent amplicon sequencing.

Ion Torrent is a next generation sequencing technology based on the detection of hydrogen ions produced during DNA chain elongation; this technology allows analyzing and characterizing genomes, genes, and species. Here, we describe an Ion Torrent procedure applied to the metagenomic analysis of 16S rRNA gene amplicons to study the bacterial diversity in food and environmental samples.

An example of how barcodes can clarify cryptic species: the case of the calanoid copepod Mastigodiaptomus albuquerquensis (Herrick).

BACKGROUND: The freshwater calanoid Mastigodiaptomus is a genus with high richness in the Americas and is composed of nine species, seven recorded in Mexico and four that are apparently endemic to small areas. Mastigodiaptomus albuquerquensis is a common, widely distributed species ranging from the southern USA to Central America. This species can be easily identified by a notable butterfly-like sclerotization on the basis of the right fifth leg of males. Nevertheless, morphological differences observed among populations throughout this species distributional range have led to the description of several related species or subspecies, such as M. albuquerquensis patzcuarensis from Lake Pátzcuaro in the Central Plateau of Mexico. METHODS: Genetic results based on barcodes, morphology based on scanning electron and light microscopy images, and morphometric analyses were used to describe cryptic species within the M. albuquerquensis complex. RESULTS: The morphological analyses coincided partially with the genetic markers, suggesting the existence of at least two sibling species: M. albuquerquensis s. str. and M. patzcuarensis. A third species was genetically separated but was morphologically indistinguishable from the M. patzcuarensis group. CONCLUSIONS: Hidden diversity has been a major problem in establishing real patterns of species distribution and genetic acquisition from megadiverse hotspots such as Mexico, where the Nearctic and the Neotropical regions of the Americas meet. Barcodes can help taxonomists to reveal and formally name these new species. Here, we describe two of three potential species highlighted by the use of barcodes: M. albuquerquensis s. str. in the northern semi-desert and M. patzcuarensis on the Central Plateau at more than 2000 m above sea level.

Barcoding in the dark? A critical view of the sufficiency of zoological DNA barcoding databases and a plea for broader integration of taxonomic knowledge.

The functionality of standard zoological DNA barcoding practice (the identification of unknown specimens by comparison of COI sequences) is contingent on working barcode databases with sufficient taxonomic coverage. It has already been established that the main barcoding repositories, NCBI and BOLD, are devoid of data for many animal groups but the specific taxonomic coverage of the repositories across animal biodiversity remains unexplored. Here, I shed light on this mystery by contrasting the number of unique taxon labels in the two databases with the number of currently recognized species for each animal phylum. The numbers reveal an overall paucity of COI sequence data in the repositories (15.13% total coverage across the recognized biodiversity on Earth, and 20.76% average taxonomic coverage for each phylum) and, more importantly, bear witness to the idleness towards numerous phyla, rendering current barcoding efforts either ineffective or inaccurate. The importance of further integrating taxonomic expertise into barcoding practice is briefly discussed and some guidelines, previously mentioned in the barcoding literature, are suggested anew. Finally, the asserted values concerning the taxonomic coverage in barcoding databases for Animalia are contrasted with those of Plantae and Fungi.

Heterogeneity of young and aged murine hematopoietic stem cells revealed by quantitative clonal analysis using cellular barcoding.

The number of hematopoietic stem cells (HSCs) that contributes to blood formation and the dynamics of their clonal contribution is a matter of ongoing discussion. Here, we use cellular barcoding combined with multiplex high-throughput sequencing to provide a quantitative and sensitive analysis of clonal behavior of hundreds of young and old HSCs. The majority of transplanted clones steadily contributes to hematopoiesis in the long-term, although clonal output in granulocytes, T cells, and B cells is substantially different. Contributions of individual clones to blood are dynamically changing; most of the clones either expand or decline with time. Finally, we demonstrate that the pool of old HSCs is composed of multiple small clones, whereas the young HSC pool is dominated by fewer, but larger, clones.

Sequence-based molecular phylogenetics and phylogeography of the American box turtles (Terrapene spp.) with support from DNA barcoding.

The classification of the American box turtles (Terrapene spp.) has remained enigmatic to systematists. Previous comprehensive phylogenetic studies focused primarily on morphology. The goal of this study was to re-assess the classification of Terrapene spp. by obtaining DNA sequence data from a broad geographic range and from all four recognized species and 11 subspecies within the genus. Tissue samples were obtained for all taxa except for Terrapene nelsoni klauberi. DNA was extracted, and the mitochondrial DNA (mtDNA) cytochrome b (Cytb) and nuclear DNA (nucDNA) glyceraldehyde-3-phosphate-dehydrogenase (GAPD) genes were amplified via polymerase chain reaction and sequenced. In addition, the mtDNA gene commonly used for DNA barcoding (cytochrome oxidase c subunit I; COI) was amplified and sequenced to calculate pairwise percent DNA sequence divergence comparisons for each Terrapene taxon. The sequence data were analyzed using maximum likelihood and Bayesian phylogenetic inference, a molecular clock, AMOVAs, SAMOVAs, haplotype networks, and pairwise percent sequence divergence comparisons. Terrapene carolina mexicana and T. c. yucatana formed a monophyletic clade with T. c. triunguis, and this clade was paraphyletic to the rest of T. carolina. Terrapene ornata ornata and T. o. luteola lacked distinction phylogenetically, and Terrapene nelsoni was confirmed to be the sister taxon of T. ornata. Terrapene c. major, T. c. bauri, and Terrapene coahuila were not well resolved for some of the analyses. The DNA barcoding results indicated that all taxa were different species (>2% sequence divergence) except for T. c. triunguis - T. c. mexicana and T. o. ornata - T. o. luteola. The results suggest that T. c. triunguis should be elevated to species status (Terrapene mexicana), and mexicana and yucatana should be included in this group as subspecies. In addition, T. o. ornata and T. o. luteola should not be considered separate subspecies. The DNA barcoding data support these recommended taxonomic revisions. Because conservation efforts are typically species-based, these results will be important for facilitating successful conservation management strategies.

Taxonomic classification of bacterial 16S rRNA genes using short sequencing reads: evaluation of effective study designs.

Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naïve Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ∼8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.

COI barcode versus morphological identification of Culex (Culex) (Diptera: Culicidae) species: a case study using samples from Argentina and Brazil.

Sequences of the cytochrome c oxidase subunit I (COI) mitochondrial gene from adults of 22 Culex (Culex) species from Argentina and Brazil were employed to assess species identification and to test the usefulness of COI for barcoding using the best close match (BCM) algorithm. A pairwise Kimura two-parameter distance matrix including the mean intra and interspecific distances for 71 COI barcode sequences was constructed. Of the 12 COI lineages recovered in the Neighbour-joining topology, five confirmed recognised morphological species (Cx. acharistus, Cx. chidesteri, Cx. dolosus, Cx. lygrus and Cx. saltanensis) with intraspecific divergences lower than 1.75%. Cx. bilineatus is formally resurrected from the synonymy of Cx. dolosus. Cx. maxi , Cx. surinamensis and the Coronator group species included were clustered into an unresolved lineage. The intraspecific distance of Cx. pipiens (3%) was almost twice the interspecific between it and Cx. quinquefasciatus (1.6%). Regarding the BCM criteria, the COI barcode successfully identified 69% of all species. The rest of the sequences, approximately 10%, 18% and 3%, remained as ambiguously, mis and unidentified, respectively. The COI barcode does not contain enough information to distinguish Culex (Cux.) species.

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.