Explore the vast range of titles available.

Background High-throughput sequencing technologies offer new perspectives for biomedical, agronomical and evolutionary research. Promising progresses now concern the application of these technologies to large-scale studies of genetic variation. Such studies require the genotyping of high numbers of samples. This is theoretically possible using 454 pyrosequencing, which generates billions of base pairs of sequence data. However several challenges arise: first in the attribution of each read produced to its original sample, and second, in bioinformatic analyses to distinguish true from artifactual sequence variation. This pilot study proposes a new application for the 454 GS FLX platform, allowing the individual genotyping of thousands of samples in one run. A probabilistic model has been developed to demonstrate the reliability of this method. Results DNA amplicons from 1,710 rodent samples were individually barcoded using a combination of tags located in forward and reverse primers. Amplicons consisted in 222 bp fragments corresponding to DRB exon 2, a highly polymorphic gene in mammals. A total of 221,789 reads were obtained, of which 153,349 were finally assigned to original samples. Rules based on a probabilistic model and a four-step procedure, were developed to validate sequences and provide a confidence level for each genotype. The method gave promising results, with the genotyping of DRB exon 2 sequences for 1,407 samples from 24 different rodent species and the sequencing of 392 variants in one half of a 454 run. Using replicates, we estimated that the reproducibility of genotyping reached 95%. Conclusions This new approach is a promising alternative to classical methods involving electrophoresis-based techniques for variant separation and cloning-sequencing for sequence determination. The 454 system is less costly and time consuming and may enhance the reliability of genotypes obtained when high numbers of samples are studied. It opens up new perspectives for the study of evolutionary and functional genetics of highly polymorphic genes like major histocompatibility complex genes in vertebrates or loci regulating self-compatibility in plants. Important applications in biomedical research will include the detection of individual variation in disease susceptibility. Similarly, agronomy will benefit from this approach, through the study of genes implicated in productivity or disease susceptibility traits.

Better knowledge of food webs and related ecological processes is fundamental to understanding the functional role of biodiversity in ecosystems. This is particularly true for pest regulation by natural enemies in agroecosystems. However, it is generally difficult to decipher the impact of predators, as they often leave no direct evidence of their activity. Metabarcoding via high-throughput sequencing (HTS) offers new opportunities for unraveling trophic linkages between generalist predators and their prey, and ultimately identifying key ecological drivers of natural pest regulation. Here, this approach proved effective in deciphering the diet composition of key predatory arthropods (nine species.; 27 prey taxa), insectivorous birds (one species, 13 prey taxa) and bats (one species; 103 prey taxa) sampled in a millet-based agroecosystem in Senegal. Such information makes it possible to identify the diet breadth and preferences of predators (e.g., mainly moths for bats), to design a qualitative trophic network, and to identify patterns of intraguild predation across arthropod predators, insectivorous vertebrates and parasitoids. Appropriateness and limitations of the proposed molecular-based approach for assessing the diet of crop pest predators and trophic linkages are discussed.

An accurate estimation of parasitism rates and diversity of parasitoids of crop insect pests is a prerequisite for exploring processes leading to efficient natural biocontrol. Traditional methods such as rearing have been often limited by taxonomic identification, insect mortality and intensive work, but the advent of high-throughput sequencing (HTS) techniques, such as DNA metabarcoding, is increasingly seen as a reliable and powerful alternative approach. Little has been done to explore the benefits of such an approach for estimating parasitism rates and parasitoid diversity in an agricultural context. In this study, we compared the composition of parasitoid species and parasitism rates between rearing and DNA metabarcoding of host eggs and larvae of the millet head miner, Heliocheilus albipunctella De Joannis (Lepidoptera, Noctuidae), collected from millet fields in Senegal. We first assessed the detection threshold for the main ten endoparasitoids, by sequencing PCR products obtained from artificial dilution gradients of the parasitoid DNAs in the host moth. We then assessed the potential of DNA metabarcoding for diagnosing parasitism rates in samples collected from the field. Under controlled conditions, our results showed that relatively small quantities of parasitoid DNA (0.07 ng) were successfully detected within an eight-fold larger quantity of host DNA. Parasitoid diversity and parasitism rate estimates were always higher for DNA metabarcoding than for host rearing. Furthermore, metabarcoding detected multi-parasitism, cryptic parasitoid species and differences in parasitism rates between two different sampling sites. Metabarcoding shows promise for gaining a clearer understanding of the importance and complexity of host-parasitoid interactions in agro-ecosystems, with a view to improving pest biocontrol strategies.

Several recent public health crises have shown that the surveillance of zoonotic agents in wildlife is important to prevent pandemic risks. High-throughput sequencing (HTS) technologies are potentially useful for this surveillance, but rigorous experimental processes are required for the use of these effective tools in such epidemiological contexts. In particular, HTS introduces biases into the raw data set that might lead to incorrect interpretations. We describe here a procedure for cleaning data before estimating reliable biological parameters, such as positivity, prevalence, and coinfection, using 16S rRNA amplicon sequencing on an Illumina MiSeq platform. This procedure, applied to 711 rodents collected in West Africa, detected several zoonotic bacterial species, including some at high prevalence, despite their never before having been reported for West Africa. In the future, this approach could be adapted for the monitoring of other microbes such as protists, fungi, and even viruses. The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculus domesticus , 189 Rattus rattus , 93 Mastomys natalensis , and 221 Mastomys erythroleucus , collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia , Bartonella , Mycoplasma , Ehrlichia , Rickettsia , Streptobacillus , and Orientia . Mycoplasma , Ehrlichia , Rickettsia , Streptobacillus , and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs. IMPORTANCE Several recent public health crises have shown that the surveillance of zoonotic agents in wildlife is important to prevent pandemic risks. High-throughput sequencing (HTS) technologies are potentially useful for this surveillance, but rigorous experimental processes are required for the use of these effective tools in such epidemiological contexts. In particular, HTS introduces biases into the raw data set that might lead to incorrect interpretations. We describe here a procedure for cleaning data before estimating reliable biological parameters, such as positivity, prevalence, and coinfection, using 16S rRNA amplicon sequencing on an Illumina MiSeq platform. This procedure, applied to 711 rodents collected in West Africa, detected several zoonotic bacterial species, including some at high prevalence, despite their never before having been reported for West Africa. In the future, this approach could be adapted for the monitoring of other microbes such as protists, fungi, and even viruses.

Rodentia is the most diverse order among mammals, with more than 2,000 species currently described. Most of the time, species assignation is so difficult based on morphological data solely that identifying rodents at the specific level corresponds to a real challenge. In this study, we compared the applicability of 100 bp mini-barcodes from cytochrome b and cytochrome c oxidase 1 genes to enable rodent species identification. Based on GenBank sequence datasets of 115 rodent species, a 136 bp fragment of cytochrome b was selected as the most discriminatory mini-barcode, and rodent universal primers surrounding this fragment were designed. The efficacy of this new molecular tool was assessed on 946 samples including rodent tissues, feces, museum samples and feces/pellets from predators known to ingest rodents. Utilizing next-generation sequencing technologies able to sequence mixes of DNA, 1,140 amplicons were tagged, multiplexed and sequenced together in one single 454 GS-FLX run. Our method was initially validated on a reference sample set including 265 clearly identified rodent tissues, corresponding to 103 different species. Following validation, 85.6% of 555 rodent samples from Europe, Asia and Africa whose species identity was unknown were able to be identified using the BLASTN program and GenBank reference sequences. In addition, our method proved effective even on degraded rodent DNA samples: 91.8% and 75.9% of samples from feces and museum specimens respectively were correctly identified. Finally, we succeeded in determining the diet of 66.7% of the investigated carnivores from their feces and 81.8% of owls from their pellets. Non-rodent species were also identified, suggesting that our method is sensitive enough to investigate complete predator diets. This study demonstrates how this molecular identification method combined with high-throughput sequencing can open new realms of possibilities in achieving fast, accurate and inexpensive species identification.

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo-mock community (33 arthropod taxa from 16 orders), and guano-based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano-based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one-third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.

Orientia bacterium is the agent of the scrub typhus, a seriously neglected life-threatening disease in Asia. Here, we report the detection of DNA of Orientia in rodents from Europe and Africa. These findings have important implications for public health. Surveillance outside Asia, where the disease is not expected by sanitary services, needs to be improved.

Dietary plasticity can be a determining factor allowing species to cope with environmental changes. Consequently, it is an important issue to consider in conservation biology. Despite this, it remains rarely addressed in the literature, potentially due to methodologies which were until recently rather limited. The advent of molecular approaches now makes it possible to get a precise picture of diet and its plasticity, even for endangered and elusive species. Here, we focused on the greater horseshoe bat (Rhinolophus ferrumequinum) in Western France, where this insectivorous species has been classified as “Vulnerable” on the Regional Red List in 2016. We applied an eDNA metabarcoding approach to 1986 fecal samples collected in six maternity colonies on three sampling dates. We described the diet and investigated whether the landscape surrounding colonies and the different phases of the maternity cycle influenced the diversity and the composition of this diet. We showed that R. ferrumequinum feed on a much more diverse prey spectrum than expected from previous studies, highlighting how eDNA metabarcoding can improve our knowledge on the dietary habits of elusive species. Our approach also revealed that the diet of R. ferrumequinum seems to be composed of two distinct features: the core diet consisting of a few preferred taxa shared by all the colonies (25% of the occurrences) and the secondary diet consisting of numerous rare prey taxa that were highly different between colonies and sampling dates (75% of the occurrences). Constraints associated with the greater horseshoe bat life cycle, as well as insect phenology and landscape features, strongly influenced the diversity and composition of both the core diet and the diet as a whole. Further research should now explore the relationships between R. ferrumequinum dietary plasticity and fitness, to better assess the impact of core prey decline on R. ferrumequinum population viability. Here, we focused on the greater horseshoe bat (Rhinolophus ferrumequinum) in Western France, where this insectivorous species has been classified as “Vulnerable” on the Regional Red List in 2016. We applied an eDNA metabarcoding approach to 1986 fecal samples collected in six maternity colonies on three sampling dates. We revealed that the diet of R. ferrumequinum seems to be composed of two distinct features: the core diet consisting in a few preferred taxa shared by all the colonies (25% of the occurrences) and the secondary diet consisting of numerous rare prey taxa that were highly different between colonies and sampling dates (75% of the occurrences). Constraints associated with the greater horseshoe bat life cycle, as well as insect phenology and landscape features, strongly influenced the diversity and composition of both the core diet and the diet as a whole.

Large carnivores play a pivotal regulating role in maintaining healthy and balanced ecosystems; however, most of them are rare and elusive, and knowledge about their resource consumption is scarce. Traditional methods based on morphological identification of undigested remains are labor intensive and often not sufficiently accurate, leading to errors and biased ecological inferences. Here, we developed a multi‐marker DNA metabarcoding approach to analyze the dietary diversity of giant otters (Pteronura brasiliensis) from fecal DNA while controlling predator species identity. We combined two mitochondrial markers, 12S rRNA and cytochrome c oxidase 1 (COI) gene, that target the full range of potential vertebrate and invertebrate prey. We compiled a local reference database of DNA barcodes for most potentially ingested fish, which were used to evaluate the specificity of the metabarcoding primers in silico. Most prey are identified at the species level (>90%) and the dietary profiles provided independently by the two markers are highly similar, whether in terms of list of prey or frequency of occurrences, hence validating the approach. We detected a higher number of rare fish prey with the 12S primers that amplified solely Teleost species while the degenerate COI primers revealed non‐fish prey (e.g., amphibians, snakes, birds, and earthworms) and confirmed predator species identity. This study demonstrated that scat DNA metabarcoding is particularly useful to provide in‐depth information on elusive carnivorous dietary profile. Our methodology opens up new opportunities to understand how top carnivores diet cope with the effects of anthropogenic alteration of ecosystems and identify conflicts with humans and livestock. A multi‐marker scat DNA metabarcoding approach was used to examine the dietary diversity of the world's largest and rarest otter, the iconic giant otter (Pteronura brasiliensis) from fecal DNA. The combined use of highly discriminant markers (COI and 12S) and of local reference databases of DNA barcodes offered a high accuracy of taxonomic assignments with >90% of prey taxa assigned to the species level while controlling predator species identity. The dietary profiles provided by the two markers are highly similar, whether in terms of list of prey or frequency of occurrences, hence validating the approach.

Background: In France as elsewhere in Europe the most prevalent TBD in humans is Lyme borreliosis, caused by different bacterial species belonging to Borrelia burgdorferi sensu lato complex and transmitted by the most important tick species in France, Ixodes ricinus. However, the diagnosis of Lyme disease is not always confirmed and unexplained syndromes occurring after tick bites have become an important issue. Recently, B. miyamotoi belonging to the relapsing fever group and transmitted by the same Ixodes species has been involved in human disease in Russia, the USA and the Netherlands. In the present study, we investigate the presence of B. miyamotoi along with other Lyme Borreliosis spirochetes, in ticks and possible animal reservoirs collected in France. Methods: We analyzed 268 ticks (Ixodes ricinus) and 72 bank voles (Myodes glareolus) collected and trapped in France for the presence of DNA from B. miyamotoi as well as from Lyme spirochetes using q-PCR and specific primers and probes. We then compared the French genotypes with those found in other European countries. Results: We found that 3% of ticks and 5.55% of bank voles were found infected by the same B. miyamotoi genotype, while co-infection with other Lyme spirochetes (B. garinii) was identified in 12% of B. miyamotoi infected ticks. Sequencing showed that ticks and rodents carried the same genotype as those recently characterized in a sick person in the Netherlands. Conclusions: The genotype of B. miyamotoi circulating in ticks and bank voles in France is identical to those already described in ticks from Western Europe and to the genotype isolated from a sick person in The Netherlands. This results suggests that even though no human cases have been reported in France, surveillance has to be improved. Moreover, we showed that ticks could simultaneously carry B. miyamotoi and Lyme disease spirochetes, increasing the problem of co-infection in humans.