A new molecular diagnostic tool for surveying and monitoring Triops cancriformis populations

© 2017 Sellers et al. The tadpole shrimp, Triops cancriformis, is a freshwater crustacean listed as endangered in the UK and Europe living in ephemeral pools. Populations are threatened by habitat destruction due to land development for agriculture and increased urbanisation. Despite this, there is a lack of efficient methods for discovering and monitoring populations. Established macroinvertebrate monitoring methods, such as net sampling, are unsuitable given the organism's life history, that include long lived diapausing eggs, benthic habits and ephemerally active populations. Conventional hatching methods, such as sediment incubation, are both time consuming and potentially confounded by bet-hedging hatching strategies of diapausing eggs. Here we develop a new molecular diagnostic method to detect viable egg banks of T. cancriformis, and compare its performance to two conventional monitoring methods involving diapausing egg hatching. We apply this method to a collection of pond sediments from the Wildfowl & Wetlands Trust Caerlaverock National Nature Reserve, which holds one of the two remaining British populations of T. cancriformis. DNA barcoding of isolated eggs, using newly designed species-specific primers for a large region of mtDNA, was used to estimate egg viability. These estimates were compared to those obtained by the conventional methods of sediment and isolation hatching. Our method outperformed the conventional methods, revealing six ponds holding viable T. cancriformis diapausing egg banks in Caerlaverock. Additionally, designed species-specific primers for a short region of mtDNA identified degraded, inviable eggs and were used to ascertain the levels of recent mortality within an egg bank. Together with efficient sugar flotation techniques to extract eggs from sediment samples, our molecular method proved to be a faster and more powerful alternative for assessing the viability and condition of T. cancriformis diapausing egg banks

Mu-DNA: a modular universal DNA extraction method adaptable for a wide range of sample types

Efficient DNA extraction is fundamental to molecular studies. However, commercial kits are expensive when a large number of samples need to be processed. Here we present a simple, modular and adaptable DNA extraction ‘toolkit’ for the isolation of high purity DNA from multiple sample types (modular universal DNA extraction method or Mu-DNA). We compare the performance of our method to that of widely used commercial kits across a range of soil, stool, tissue and water samples. Mu-DNA produced DNA extractions of similar or higher yield and purity to that of the commercial kits. As a proof of principle, we carried out replicate fish metabarcoding of aquatic eDNA extractions, which confirmed that the species detection efficiency of our method is similar to that of the most frequently used commercial kit. Our results demonstrate the reliability of Mu-DNA along with its modular adaptability to challenging sample types and sample collection methods. Mu-DNA can substantially reduce the costs and increase the scope of experiments in molecular studies

DNA metabarcoding reveals the dietary profiles of a benthic marine crustacean,Nephrops norvegicus

Norwegian lobster, Nephrops norvegicus, are a generalist scavenger and predator capable of short foraging excursions but can also suspension feed. Existing knowledge about their diet relies on a combination of methods including morphology-based stomach content analysis and stable isotopes, which often lack the resolution to distinguish prey items to species level particularly in species that thoroughly masticate their prey. DNA metabarcoding overcomes many of the challenges associated with traditional methods and it is an attractive approach to study the dietary profiles of animals. Here, we present the diet of the commercially valuable Nephrops norvegicus using DNA metabarcoding of gut contents. Despite difficulties associated with host amplification, our cytochrome oxidase I (COI) molecular assay successfully achieves higher resolution information than traditional approaches. We detected taxa that were likely consumed during different feeding strategies. Dinoflagellata, Chlorophyta and Bacillariophyta accounted for almost 50% of the prey items consumed, and are associated with suspension feeding, while fish with high fisheries discard rates were detected which are linked to active foraging. In addition, we were able to characterise biodiversity patterns by considering Nephrops as natural samplers, as well as detecting parasitic dinoflagellates (e.g., Hematodinium sp.), which are known to influence burrow related behaviour in infected individuals in over 50% of the samples. The metabarcoding data presented here greatly enhances a better understanding of a species’ ecological role and could be applied as a routine procedure in future studies for proper consideration in the management and decision-making of fisheries

Identification of individual root-knot nematodes using low coverage long-read sequencing

Root-knot nematodes (RKN; genus Meloidogyne) are polyphagous plant pathogens of great economic importance to agriculturalists globally. These species are small, diverse, and can be challenging for accurate taxonomic identification. Many of the most important crop pests confound analysis with simple genetic marker loci as they are polyploids of likely hybrid origin. Here we take a low-coverage, long-read genome sequencing approach to characterisation of individual root-knot nematodes. We demonstrate library preparation for Oxford Nanopore Technologies Flongle sequencing of low input DNA from individual juveniles and immature females, multiplexing up to twelve samples per flow cell. Taxonomic identification with Kraken 2 (a k-mer-based taxonomic assignment tool) is shown to reliably identify individual nematodes to species level, even within the very closely related Meloidogyne incognita group. Our approach forms a robust, low-cost, and scalable method for accurate RKN species diagnostics

Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds.

The sampling of environmental DNA (eDNA) coupled with cost-efficient and ever-advancing sequencing technology is propelling changes in biodiversity monitoring within aquatic ecosystems. Despite the increasing number of eDNA metabarcoding approaches, the ability to quantify species biomass and abundance in natural systems is still not fully understood. Previous studies have shown positive but sometimes weak correlations between abundance estimates from eDNA metabarcoding data and from conventional capture methods. As both methods have independent biases a lack of concordance is difficult to interpret. Here we tested whether read counts from eDNA metabarcoding provide accurate quantitative estimates of the absolute abundance of fish in holding ponds with known fish biomass and number of individuals. Environmental DNA samples were collected from two fishery ponds with high fish density and broad species diversity. In one pond, two different DNA capture strategies (on-site filtration with enclosed filters and three different preservation buffers versus lab filtration using open filters) were used to evaluate their performance in relation to fish community composition and biomass/abundance estimates. Fish species read counts were significantly correlated with both biomass and abundance, and this result, together with information on fish diversity, was repeatable when open or enclosed filters with different preservation buffers were used. This research demonstrates that eDNA metabarcoding provides accurate qualitative and quantitative information on fish communities in small ponds, and results are consistent between different methods of DNA capture. This method flexibility will be beneficial for future eDNA-based fish monitoring and their integration into fisheries management

From the animal house to the field : are there consistent individual differences in immunological profile in wild populations of field voles (Microtus agrestis)?

Inbred mouse strains, living in simple laboratory environments far removed from nature, have been shown to vary consistently in their immune response. However, wildlife populations are typically outbreeding and face a multiplicity of challenges, parasitological and otherwise. In this study we seek evidence of consistent difference in immunological profile amongst individuals in the wild. We apply a novel method in this context, using longitudinal (repeated capture) data from natural populations of field voles, Microtus agrestis, on a range of life history and infection metrics, and on gene expression levels. We focus on three immune genes, IFN-γ, Gata3, and IL-10, representing respectively the Th1, Th2 and regulatory elements of the immune response. Our results show that there was clear evidence of consistent differences between individuals in their typical level of expression of at least one immune gene, and at most all three immune genes, after other measured sources of variation had been taken into account. Furthermore, individuals that responded to changing circumstances by increasing expression levels of Gata3 had a correlated increase in expression levels of IFN-γ. Our work stresses the importance of acknowledging immunological variation amongst individuals in studies of parasitological and infectious disease risk in wildlife populations

Does diet affect breast cancer risk?

The role of specific dietary factors in breast cancer causation is not completely resolved. Results from prospective studies do not support the concept that fat intake in middle life has a major relation to breast cancer risk. However, weight gain in middle life contributes substantially to breast cancer risk. Alcohol is the best established dietary risk factor, probably by increasing endogenous estrogen levels. Hypotheses relating diet during youth to risk decades later will be difficult to test. Nevertheless, available evidence is strong that breast cancer risk can be reduced by avoiding weight gain during adult years, and by limiting alcohol consumption

American Thyroid Association Guide to Investigating Thyroid Hormone Economy and Action in Rodent and Cell Models

Background: An in-depth understanding of the fundamental principles that regulate thyroid hormone homeostasis is critical for the development of new diagnostic and treatment ap-proaches for patients with thyroid disease. Summary: Important clinical practices in use today for the treatment of patients with hypothy-roidism, hyperthyroidism, or thyroid cancer, are the result of laboratory discoveries made by scientists investigating the most basic aspects of thyroid structure and molecular biology. In this document, a panel of experts commissioned by the American Thyroid Association makes a se-ries of recommendations related to the study of thyroid hormone economy and action. These recommendations are intended to promote standardization of study design, which should in turn increase the comparability and reproducibility of experimental findings. Conclusions: It is expected that adherence to these recommendations by investigators in the field will facilitate progress towards a better understanding of the thyroid gland and thyroid hormone dependent processes

AA9int: SNP interaction pattern search using non-hierarchical additive model set.

MOTIVATION: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. RESULTS: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. AVAILABILITY AND IMPLEMENTATION: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online