Molecular Ecology Resources最新文献

Linking meta-omics and biogeochemistry approaches in soils has remained challenging. This study evaluates the use of an internal RNA extraction standard and its potential for making quantitative estimates of a given microbial community size (biomass) in soil metatranscriptomics. We evaluate commonly used laboratory protocols for RNA processing, metatranscriptomic sequencing and quantitative reverse transcription polymerase chain reaction (qRT-PCR). Metatranscriptomic profiles from soil samples were generated using two library preparation protocols and prepared in triplicates. RNA extracted from pure cultures of Saccharolobus solfataricus was added to the samples as an internal nucleic acid extraction standard (NAE_std). RNA reads originating from NAE_std were identified with a 99.9% accuracy. A remarkable replication consistency between triplicates was seen (average Bray–Curtis dissimilarity 0.03 ± 0.02), in addition to a clear library preparation bias. Nevertheless, the between-sample pattern was not affected by library type. Estimates of 16S rRNA transcript abundance derived from qRT-PCR experiments, NAE_std and a previously published quantification method of metatranscriptomics (hereafter qMeTra) were compared with microbial biomass carbon (MBC) and nitrogen (MBN) extracts. The derived biomass estimates differed by orders of magnitude. While most estimates were significantly correlated with each other, no correlation was observed between NAE_std and MBC extracts. We discuss how simultaneous changes in community size and the soils nucleic acid retention strength might hamper accurate biomass estimation. Adding NAE_std has the potential to shed important light on nucleic acid retention in the substance matrix (e.g., soil) during extraction.

The vertebrate gut houses diverse microbial communities that provide insights into their host's ecological and evolutionary histories. Nevertheless, microbiome research has not been distributed equally across host taxonomy, geography and timescales. The millions of fluid-preserved specimens stored in natural history museums worldwide represent a potentially untapped resource for microbiome information. However, it is unknown how fluid preservation and long-term storage change the composition and diversity of the original microbial community across a variety of host taxa. Here, we present the largest study to date aimed at addressing this question. Specifically, we identified an optimal method for extracting DNA from preserved samples using commercially available kits. Next, for 11 host species representing four vertebrate classes, we compared the gut microbiomes between animals dissected freshly and those collected simultaneously but subsequently fixed in formalin and stored in 70% ethanol for 1 year, similar to museum conditions. In a secondary analysis in amphibians, we compared our collected samples with those from decades-old historical museum specimens. We found that while fluid preservation altered the community composition and reduced the diversity of the recovered microbiome inventories, host species identity predominated in shaping the gut microbiome, and differences across species and geographic localities were retained after preservation. Historical specimens had microbiomes that were the most different from fresh specimens, suggesting that over time, changes in the microbiome of populations have occurred, or preservation effects have compounded. Considering these findings, we discuss the potential for use of fluid-preserved museum specimens in future microbiome studies.

Numerous specimens stored in natural history collections have been involuntarily preserved together with their associated microbiomes. We propose exploiting century-old soils occasionally found on the roots of herbarium plants to assess the diversity of ancient soil microbial communities originally associated with these plants. We extracted total DNA and sequenced libraries produced from rhizospheric soils and roots of four plants preserved in herbaria for more than 120 years in order to characterise the preservation and taxonomic diversity that can be recovered in such contexts. Extracted DNA displayed typical features of ancient DNA, with cytosine deamination at the ends of fragments predominantly shorter than 50 bp. When compared to extant microbiomes, herbarium microbial communities clustered with soil communities and were distinct from communities from other environments. Herbarium communities also displayed biodiversity features and assembly rules typical of soil and plant-associated ones. Soil communities were richer than root-associated ones with which they shared most taxa. Regarding community turnover, we detected collection site, soil versus root and plant species effects. Eukaryotic taxa that displayed a higher abundance in roots were mostly plant pathogens that were not identified among soil-enriched ones. Conservation of these biodiversity features and assembly rules in herbarium-associated microbial communities indicates that herbarium-extracted DNA might reflect the composition of the original plant-associated microbial communities and that preservation in herbaria seemingly did not dramatically alter these characteristics. Using this approach, it should be possible to investigate historical soils and herbarium plant roots to explore the diversity and temporal dynamics of soil microbial communities.

Gawehns, F., Postuma, M., van Antro, M., Nunn, A., Sepers, B., Fatma, S., van Gurp, T. P., Wagemaker, N. C. A. M., Mateman, A. C., Milanovic-Ivanovic, S., Groβe, I., van Oers, K., Vergeer, P., and Verhoeven, K. J. F. 2022. “epiGBS2: Improvements and evaluation of highly multiplexed, epiGBS-based reduced representation bisulfite sequencing.” Molecular Ecology Resources 22: 2087–2104. https://doi.org/10.1111/1755-0998.13597

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Viral diseases represent a threat to global food production. Managing the impact of viruses on crop production requires the ability to monitor viruses, study their ecology and anticipate outbreaks. Double-stranded RNA (dsRNA) sequencing is a well-established and reliable method of detecting viruses and studying virome-host interactions and ecology. Compared to total RNA extraction, dsRNA extraction eliminates the majority of host RNAs, improving the recovery of viral RNAs. In this study, we developed and evaluated a novel dsRNA extraction method for high-throughput sequencing (HTS) applications based on the Flock House virus (FHV) B2 protein (B2-based method), and compared its performance with that of established cellulose-based and DRB4-based methods (commercial kit), as well as total RNA extraction techniques. The electrostatic properties of B2 have been instrumental in developing a bead-free and resin-free dsRNA extraction method. The B2-based method demonstrated high viral read recovery, achieving proportions exceeding 20% in most samples, and provided better dsRNA purity with less low weight molecule co-extracted RNA than the DRB4-based method and cellulose-based methods. Despite producing overall fewer total reads than the DRB4-based method, the B2-based enrichment for viral-derived dsRNA was better, with a higher percentage of viral reads, making it effective in virome profiling. Furthermore, it had an excellent detection specificity (0.97) and a good detection sensitivity (0.71), minimising false positives and false negatives. In addition, the B2-based method proved to be highly cost-effective, with a per-reaction cost of $4.47, compared to $35.34 for the DRB4-based method. This method offers a practical solution for laboratories with limited resources or for large-scale sampling for viral ecology studies. Future improvements to the B2-based method should focus on optimising sensitivity to Vitivirus species and developing scalable, automated workflows for high-throughput viral detection.

DNA metabarcoding is subject to observation bias associated with PCR and sequencing, which can result in observed read proportions differing from actual species proportions in the DNA extract. Here, we amplify and sequence a mock community of known composition containing marine fishes and cetaceans using four different primer sets and a variety of PCR conditions. We first compare metabarcoding observations to two different sets of expected species proportions based on total genomic DNA and on target mitochondrial template DNA. We find that calibrating observed read proportions based on template DNA concentration is most appropriate as it isolates PCR amplification bias; calibration with total genomic DNA results in bias that can be attributed to both PCR amplification bias and differing ratios of template to total genomic DNA. We then model the remaining amplification bias and find that approximately 60% can be explained by inherent species-specific DNA characteristics. These include primer-template mismatches, amplicon fragment length, and GC content, which vary somewhat across Taq polymerases. Finally, we investigate how different PCR protocols influence community composition regardless of expected proportions and find that changing protocols most strongly influence the amplification of templates with primer mismatches. Our findings suggest that using primer-template pairs without mismatches and targeting a narrow taxonomic group can yield more repeatable and accurate estimates of species' true, underlying DNA template proportions. These findings identify key factors that should be considered when designing studies that aim to apply metabarcoding data quantitatively.

The applications of epigenetic clocks – statistical models that predict an individual's age based on DNA methylation patterns – are expanding in wildlife conservation and management. This growing interest highlights the need for field-specific design best practices. Here, we provide recommendations for two main applications of wildlife epigenetic clocks: estimating the unknown ages of individuals and assessing their biological ageing rates. Epigenetic clocks were originally developed to measure biological ageing rates of human tissues, which presents challenges for their adoption in wildlife research. Most notably, the estimated chronological ages of sampled wildlife can be unreliable, and sampling restrictions limit the number and variety of tissues with which epigenetic clocks can be constructed, reducing their accuracy. To address these challenges, we present a detailed workflow for designing, validating applying accurate wildlife epigenetic clocks. Using simulations and analyses applied to an extensive polar bear dataset from across the Canadian Arctic, we demonstrate that accurate epigenetic clocks for wildlife can be constructed and validated using a limited number of samples, accommodating projects with small budgets and sampling constraints. The concerns we address are critical for clock design, whether researchers or third-party service providers perform the bioinformatics. With our workflow and examples, we hope to support the accessible and widespread use of epigenetic clocks in wildlife conservation and management.