The quest for absolute abundance: The use of internal standards for DNA-based community ecology

PCR bias in 16S rRNA genes caused by GC content leads to insufficient detection of some abundant species in amplicon sequencing analyses of thermophilic microbial communities

Amplicon sequencing is a widely used method for surveying biological diversity. However, the technique is disturbed by PCR bias leading to errors in community composition analyses. In this study, microbial community composition was evaluated in twenty-eight locations of hot spring water with temperatures between 87-48°C at Nakabusa Hot Springs, Japan, using amplicon sequencing analysis with the V4 region of the 16S rRNA gene. In discrepancy with the greenish color and the absorption spectra of the microbial samples, the relative abundance of amplicon sequence variants (ASVs) in the major photosynthetic organisms, Chloroflexus spp., were scarce in any sample when using the annealing temperature of 50°C in amplicon PCR. Changing the annealing temperature to 68ºC significantly improved the detection efficiency of Chloroflexus ASVs, and the obtained numbers were consistent with the presence of the photosynthetic pigments. The abundance of many other microbial ASVs was also dependent on the annealing temperature. The log ratio in the abundance of major ASVs between two annealing temperatures was correlated with the GC content of the 16S rRNA gene, suggesting that even some other major ASVs in the community are seriously affected by PCR bias due to the GC content. Combined usage of results from two different annealing temperatures, rather than a result using a single annealing temperature, seems to be a better way to obtain community structure information with less PCR bias in thermophilic organisms of high 16S rRNA GC content.

Robust phylogenetic tree-based microbiome association test using repeatedly measured data for composition bias

BACKGROUND

The effects of microbiota on the host phenotypes can differ substantially depending on their age. Longitudinally measured microbiome data allow for the detection of the age modification effect and are useful for the detection of microorganisms related to the progression of disease whose identification change over time. Moreover, longitudinal analysis facilitates the estimation of the within-subject covariate effect, is robust to the between-subject confounders, and provides better evidence for the causal relationship than cross-sectional studies. However, this method of analysis is limited by compositional bias, and few statistical methods can estimate the effect of microbiota on host diseases with repeatedly measured 16S rRNA gene data. Herein, we propose mTMAT, which is applicable to longitudinal microbiome data and is robust to compositional bias.

RESULTS

mTMAT normalized the microbial abundance and utilized the ratio of the pooled abundance for association analysis. mTMAT is based on generalized estimating equations with a robust variance estimator and can be applied to repeatedly measured microbiome data. The robustness of mTMAT against compositional bias is underscored by its utilization of abundance ratios.

CONCLUSIONS

With extensive simulation studies, we showed that mTMAT is statistically relatively powerful and is robust to compositional bias. mTMAT enables detection of microbial taxa associated with host diseases using repeatedly measured 16S rRNA gene data and can provide deeper insights into bacterial pathology.

The quest for environmental analytical microbiology: absolute quantitative microbiome using cellular internal standards

BACKGROUND

High-throughput sequencing has revolutionized environmental microbiome research, providing both quantitative and qualitative insights into nucleic acid targets in the environment. The resulting microbial composition (community structure) data are essential for environmental analytical microbiology, enabling characterization of community dynamics and assessing microbial pollutants for the development of intervention strategies. However, the relative abundances derived from sequencing impede comparisons across samples and studies.

RESULTS

This review systematically summarizes various absolute quantification (AQ) methods and their applications to obtain the absolute abundance of microbial cells and genetic elements. By critically comparing the strengths and limitations of AQ methods, we advocate the use of cellular internal standard-based high-throughput sequencing as an appropriate AQ approach for studying environmental microbiome originated from samples of complex matrices and high heterogeneity. To minimize ambiguity and facilitate cross-study comparisons, we outline essential reporting elements for technical considerations, and provide a checklist as a reference for environmental microbiome research.

CONCLUSIONS

In summary, we propose absolute microbiome quantification using cellular internal standards for environmental analytical microbiology, and we anticipate that this approach will greatly benefit future studies. Video Abstract.

Bacteriome of the Middle Ear in Children and Young Adults With Cholesteatoma and Retraction Pocket: A Pilot Study

Objective

Chronic otitis media (COM) is a common middle ear disease in children and young adults. Dysfunction of the Eustachian tube and bacterial infection are the main causes. This pilot study aimed to describe and compare bacteriomes of the middle ear in children and young adults with serious forms of COM, such as cholesteatoma and retraction pocket (RP) of the tympanic membrane, with bacteriomes in healthy middle ears.

Study Design

Observational study.

Setting

Clinical practice in a tertiary center. From January 1, 2021 to August 31, 2022. Patients aged 0 to 20 years.

Methods

In this case-control study, middle ears were swabbed during surgery on children with cholesteatoma (N = 23) or RP (N = 26) and on children indicated for cochlear implant (N = 15, controls). Genomic DNA extraction was followed by creation of a 16S ribosomal DNA gene library and sequencing on a MiSeq instrument. Samples with relative abundance of at least one bacterial genus >20% were considered positive for the specific genus.

Results

Bacterial diversity was generally low in the middle ear samples from patients with COM, with DNA content from 1 or 2 bacteria usually dominating in the sample. A significant difference in positivity for one or more bacterial genera was observed between patients with cholesteatoma or RP (38.8%) versus patients indicated for cochlear implants (6.7%).

Conclusion

While middle ear bacteriomes in cases of cholesteatoma and RP differed from those of controls, findings in the 2 pathological conditions were similar. These results support the statement that the RP could be a precholesteatoma stage.

Synthetic DNA spike-in standards for cross-domain absolute quantification of microbiomes by rRNA gene amplicon sequencing

Microbiome studies using high-throughput sequencing are increasingly incorporating absolute quantitative approaches to overcome the inherent limitations of relative abundances. In this study, we have designed and experimentally validated a set of 12 unique synthetic rRNA operons, which we refer to as rDNA-mimics, to serve as spike-in standards for quantitative profiling of fungal/eukaryotic and bacterial microbiomes. The rDNA-mimics consist of conserved sequence regions from natural rRNA genes to act as binding sites for common universal PCR primers, and bioinformatically designed variable regions that allow their robust identification in any microbiome sample. All constructs cover multiple rRNA operon regions commonly targeted in fungal/eukaryotic microbiome studies (SSU-V9, ITS1, ITS2, and LSU-D1D2) and two of them also include an artificial segment of the bacterial 16S rRNA gene (SSU-V4) for cross-domain application. We validated the quantitative performance of the rDNA-mimics using defined mock communities and representative environmental samples. In particular, we show that rDNA-mimics added to extracted DNA or directly to the samples prior to DNA extraction precisely reflects the total amount of fungal and/or bacterial rRNA genes in the samples. We demonstrate that this allows accurate estimation of differences in microbial loads between samples, thereby confirming that the rDNA-mimics are suitable for absolute quantitative analyses of differential microbial abundances.

Co-metabolic growth and microbial diversity: Keys for the depletion of the α, δ, β and γ-HCH isomers

The objective of this study was the isolation and enrichment of microbiomes capable of degrading the main hexachlorocyclohexane isomers quantified in environmental matrices, e.g.: the α, δ, β and γ-HCH isomers. Four microbiomes were isolated and enriched from an HCH-contaminated dumpsite in Italy, both in the presence of HCH isomers (1:1:1:1) as the sole carbon sources and under co-metabolic growth conditions in presence of glucose (0.1 % v/v). The microbiomes were assessed for their relevant metabolic capabilities. A quantitative metabarcoding approach was employed to analyze the compositional evolution of the four microbiomes during the enrichment phase and the phase of testing of the HCH isomers degradation kinetics. The use of a co-metabolic substrate during enrichment process was essential for selecting microbiomes with higher biodiversity. All microbiomes efficiently degraded the α, δ, and γ-HCH isomers. The highest efficiency in the β-HCH degradation capacity was positively correlated to the highest biodiversity of the microbiome, and the involvement of Chryseobacterium and Asinibacterium sps. have been proposed for a recorded increment in bacterial load during the HCH degradation process.

Towards precision parasite management for livestock gastrointestinal nematodes in 2030

The management of parasitic nematodes calls for a shift from conventional, indiscriminate, anthelmintic use to a more precise approach, directed by diagnostics. We should accept those parasite infection intensities that have minimal impact on production and welfare rather than attempt to eliminate them. The diagnostic toolbox for gastrointestinal nematodes (GINs) faces challenges due to anthelmintic resistance (AR), which is species-specific, drug-class-specific, and varies by region. We discuss which traditional tools may become obsolete and which tools need development to gain widespread use. Social science research highlights the need for dialogue between farmers and veterinarians that emphasises effective parasite management and upskilling the veterinary workforce for more sustainable practices centred on diagnostics to be adopted in practice by 2030.

Implementing high-throughput insect barcoding in microbiome studies: impact of non-destructive DNA extraction on microbiome reconstruction

Background

Symbiotic relationships with diverse microorganisms are crucial for many aspects of insect biology. However, while our understanding of insect taxonomic diversity and the distribution of insect species in natural communities is limited, we know much less about their microbiota. In the era of rapid biodiversity declines, as researchers increasingly turn towards DNA-based monitoring, developing and broadly implementing approaches for high-throughput and cost-effective characterization of both insect and insect-associated microbial diversity is essential. We need to verify whether approaches such as high-throughput barcoding, a powerful tool for identifying wild insects, would permit subsequent microbiota reconstruction in these specimens.

Methods

High-throughput barcoding ("megabarcoding") methods often rely on non-destructive approaches for obtaining template DNA for PCR amplification by leaching DNA out of insect specimens using alkaline buffers such as HotSHOT. This study investigated the impact of HotSHOT on microbial abundance estimates and the reconstructed bacterial community profiles. We addressed this question by comparing quantitative 16S rRNA amplicon sequencing data for HotSHOT-treated or untreated specimens of 16 insect species representing six orders and selected based on the expectation of limited variation among individuals.

Results

We find that in 13 species, the treatment significantly reduced microbial abundance estimates, corresponding to an estimated 15-fold decrease in amplifiable 16S rRNA template on average. On the other hand, HotSHOT pre-treatment had a limited effect on microbial community composition. The reconstructed presence of abundant bacteria with known significant effects was not affected. On the other hand, we observed changes in the presence of low-abundance microbes, those close to the reliable detection threshold. Alpha and beta diversity analyses showed compositional differences in only a few species.

Conclusion

Our results indicate that HotSHOT pre-treated specimens remain suitable for microbial community composition reconstruction, even if abundance may be hard to estimate. These results indicate that we can cost-effectively combine barcoding with the study of microbiota across wild insect communities. Thus, the voucher specimens obtained using megabarcoding studies targeted at characterizing insect communities can be used for microbiome characterizations. This can substantially aid in speeding up the accumulation of knowledge on the microbiomes of abundant and hyperdiverse insect species.

Advances in environmental DNA monitoring: standardization, automation, and emerging technologies in aquatic ecosystems

Environmental DNA (eDNA) monitoring, a rapidly advancing technique for assessing biodiversity and ecosystem health, offers a noninvasive approach for detecting and quantifying species from various environmental samples. In this review, a comprehensive overview of current eDNA collection and detection technologies is provided, emphasizing the necessity for standardization and automation in aquatic ecological monitoring. Furthermore, the intricacies of water bodies, from streams to the deep sea, and the associated challenges they pose for eDNA capture and analysis are explored. The paper delineates three primary eDNA survey methods, namely, bringing back water, bringing back filters, and bringing back data, each with specific advantages and constraints in terms of labor, transport, and data acquisition. Additionally, innovations in eDNA sampling equipment, including autonomous drones, subsurface samplers, and in-situ filtration devices, and their applications in monitoring diverse taxa are discussed. Moreover, recent advancements in species-specific detection and eDNA metabarcoding are addressed, highlighting the integration of novel techniques such as CRISPR-Cas and nanopore sequencing that enable precise and rapid detection of biodiversity. The implications of environmental RNA and epigenetic modifications are considered for future applications in providing nuanced ecological data. Lastly, the review stresses the critical role of standardization and automation in enhancing data consistency and comparability for robust long-term biomonitoring. We propose that the amalgamation of these technologies represents a paradigm shift in ecological monitoring, aligning with the urgent call for biodiversity conservation and sustainable management of aquatic ecosystems.

Three steps towards comparability and standardization among molecular methods for characterizing insect communities

Molecular methods are currently some of the best-suited technologies for implementation in insect monitoring. However, the field is developing rapidly and lacks agreement on methodology or community standards. To apply DNA-based methods in large-scale monitoring, and to gain insight across commensurate data, we need easy-to-implement standards that improve data comparability. Here, we provide three recommendations for how to improve and harmonize efforts in biodiversity assessment and monitoring via metabarcoding: (i) we should adopt the use of synthetic spike-ins, which will act as positive controls and internal standards; (ii) we should consider using several markers through a multiplex polymerase chain reaction (PCR) approach; and (iii) we should commit to the publication and transparency of all protocol-associated metadata in a standardized fashion. For (i), we provide a ready-to-use recipe for synthetic cytochrome c oxidase spike-ins, which enable between-sample comparisons. For (ii), we propose two gene regions for the implementation of multiplex PCR approaches, thereby achieving a more comprehensive community description. For (iii), we offer guidelines for transparent and unified reporting of field, wet-laboratory and dry-laboratory procedures, as a key to making comparisons between studies. Together, we feel that these three advances will result in joint quality and calibration standards rather than the current laboratory-specific proof of concepts. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

A new spike-in-based method for quantitative metabarcoding of soil fungi and bacteria

Metabarcoding is a powerful tool to characterize biodiversity in biological samples. The interpretation of taxonomic profiles from metabarcoding data has been hindered by their compositional nature. Several strategies have been proposed to transform compositional data into quantitative data, but they have intrinsic limitations. Here, I propose a workflow based on bacterial and fungal cellular internal standards (spike-ins) for absolute quantification of the microbiota in soil samples. These standards were added to the samples before DNA extraction in amounts estimated after qPCRs, to target around 1-2% coverage in the sequencing run. In bacteria, proportions of spike-in reads in the sequencing run were very similar (< 2-fold change) to those predicted by the qPCR assessment, and for fungi they differed up to 40-fold. The low variation among replicates highlights the reproducibility of the method. Estimates based on multiple bacterial spike-ins were highly correlated (r = 0.99). Procrustes analysis evidenced significant biological effects on the community composition when normalizing compositional data. A protocol based on qPCR estimation of input amounts of cellular spikes is proposed as a cheap and reliable strategy for quantitative metabarcoding of biological samples.

Implementing high-throughput insect barcoding in microbiome studies: impact of non-destructive DNA extraction on microbiome reconstruction

Background

Symbiotic relationships with diverse microorganisms are crucial for many aspects of insect biology. However, while our understanding of insect taxonomic diversity and the distribution of insect species in natural communities is limited, we know much less about their microbiota. In the era of rapid biodiversity declines, as researchers increasingly turn towards DNA-based monitoring, developing and broadly implementing approaches for high-throughput and cost-effective characterization of both insect and insect-associated microbial diversity is essential. We need to verify whether approaches such as high-throughput barcoding, a powerful tool for identifying wild insects, would permit subsequent microbiota reconstruction in these specimens.

Methods

High-throughput barcoding ("megabarcoding") methods often rely on non-destructive approaches for obtaining template DNA for PCR amplification by leaching DNA out of insect specimens using alkaline buffers such as HotSHOT. This study investigated the impact of HotSHOT on microbial abundance estimates and the reconstructed bacterial community profiles. We addressed this question by comparing quantitative 16S rRNA amplicon sequencing data for HotSHOT-treated or untreated specimens of 16 insect species representing six orders and selected based on the expectation of limited variation among individuals.

Results

We find that in 13 species, the treatment significantly reduced microbial abundance estimates, corresponding to an estimated 15-fold decrease in amplifiable 16S rRNA template on average. On the other hand, HotSHOT pre-treatment had a limited effect on microbial community composition. The reconstructed presence of abundant bacteria with known significant effects was not affected. On the other hand, we observed changes in the presence of low-abundance microbes, those close to the reliable detection threshold. Alpha and beta diversity analyses showed compositional differences in only a few species.

Conclusion

Our results indicate that HotSHOT pre-treated specimens remain suitable for microbial community composition reconstruction, even if abundance may be hard to estimate. These results indicate that we can cost-effectively combine barcoding with the study of microbiota across wild insect communities. Thus, the voucher specimens obtained using megabarcoding studies targeted at characterizing insect communities can be used for microbiome characterizations. This can substantially aid in speeding up the accumulation of knowledge on the microbiomes of abundant and hyperdiverse insect species.

Exploitation of environmental DNA (eDNA) for ecotoxicological research: A critical review on eDNA metabarcoding in assessing marine pollution

The rise in worldwide population has led to a noticeable spike in the production, consumption, and transportation of energy and food, contributing to elevated environmental pollution. Marine pollution is a significant global environmental issue with ongoing challenges, including plastic waste, oil spills, chemical pollutants, and nutrient runoff, threatening marine ecosystems, biodiversity, and human health. Pollution detection and assessment are crucial to understanding the state of marine ecosystems. Conventional approaches to pollution evaluation usually represent laborious and prolonged physical and chemical assessments, constraining their efficacy and expansion. The latest advances in environmental DNA (eDNA) are valuable methods for the detection and surveillance of pollution in the environment, offering enhanced sensibility, efficacy, and involvement. Molecular approaches allow genetic information extraction from natural resources like water, soil, or air. The application of eDNA enables an expanded evaluation of the environmental condition by detecting both identified and unidentified organisms and contaminants. eDNA methods are valuable for assessing community compositions, providing indirect insights into the intensity and quality of marine pollution through their effects on ecological communities. While eDNA itself is not direct evidence of pollution, its analysis offers a sensitive tool for monitoring changes in biodiversity, serving as an indicator of environmental health and allowing for the indirect estimation of the impact and extent of marine pollution on ecosystems. This review explores the potential of eDNA metabarcoding techniques for detecting and identifying marine pollutants. This review also provides evidence for the efficacy of eDNA assessment in identifying a diverse array of marine pollution caused by oil spills, harmful algal blooms, heavy metals, ballast water, and microplastics. In this report, scientists can expand their knowledge and incorporate eDNA methodologies into ecotoxicological research.

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

Amplicon sequencing with internal standards yields accurate picocyanobacteria cell abundances as validated with flow cytometry

To understand ecosystem state and function, marine microbial ecologists seek measurements of organismal abundance and diversity at high taxonomic resolution. Conventional flow cytometry accurately estimates microbial cell abundance but only discerns broad groups with distinct optical properties. While amplicon sequencing resolves more comprehensive diversity within microbiomes, it typically only provides relative organismal abundances within samples, not absolute abundance changes. Internal genomic standards offer a solution for absolute amplicon-based measures. Here, we spiked genomic standards into plankton samples from surface seawater, gathered at 46-km intervals along a cruise transect spanning the southern California Current System and the oligotrophic North Pacific Subtropical Gyre. This enabled evaluation of the absolute volumetric gene copy abundances of 16S rRNA amplicon sequence variants (amplified with 515Y-926R universal primers, quantitatively validated with mock communities) and cell abundances of picocyanobacteria with known genomic 16S copy numbers. Comparison of amplicon-derived cell abundances of Prochlorococcus and Synechococcus with flow cytometry data from nearby locations yielded nearly identical results (slope = 1.01; Pearson's r = 0.9942). Our findings show that this amplicon sequencing protocol combined with genomic internal standards accurately measures absolute cell counts of marine picocyanobacteria in complex field samples. By extension, we expect this approach to reasonably estimate volumetric gene copies for other amplified taxa in these samples.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome

Purpose

The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes.

Methods

Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2.

Results

The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied.

Conclusion

The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.

Spatiotemporal and ontogenetic variation, microbial selection, and predicted Bd-inhibitory function in the skin-associated microbiome of a Rocky Mountain amphibian

Host-associated microbiomes play important roles in host health and pathogen defense. In amphibians, the skin-associated microbiota can contribute to innate immunity with potential implications for disease management. Few studies have examined season-long temporal variation in the amphibian skin-associated microbiome, and the interactions between bacteria and fungi on amphibian skin remain poorly understood. We characterize season-long temporal variation in the skin-associated microbiome of the western tiger salamander (Ambystoma mavortium) for both bacteria and fungi between sites and across salamander life stages. Two hundred seven skin-associated microbiome samples were collected from salamanders at two Rocky Mountain lakes throughout the summer and fall of 2018, and 127 additional microbiome samples were collected from lake water and lake substrate. We used 16S rRNA and ITS amplicon sequencing with Bayesian Dirichlet-multinomial regression to estimate the relative abundances of bacterial and fungal taxa, test for differential abundance, examine microbial selection, and derive alpha diversity. We predicted the ability of bacterial communities to inhibit the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd), a cutaneous fungal pathogen, using stochastic character mapping and a database of Bd-inhibitory bacterial isolates. For both bacteria and fungi, we observed variation in community composition through time, between sites, and with salamander age and life stage. We further found that temporal trends in community composition were specific to each combination of salamander age, life stage, and lake. We found salamander skin to be selective for microbes, with many taxa disproportionately represented relative to the environment. Salamander skin appeared to select for predicted Bd-inhibitory bacteria, and we found a negative relationship between the relative abundances of predicted Bd-inhibitory bacteria and Bd. We hope these findings will assist in the conservation of amphibian species threatened by chytridiomycosis and other emerging diseases.

Applications of environmental DNA (eDNA) in agricultural systems: Current uses, limitations and future prospects

Global food production, food supply chains and food security are increasingly stressed by human population growth and loss of arable land, becoming more vulnerable to anthropogenic and environmental perturbations. Numerous mutualistic and antagonistic species are interconnected with the cultivation of crops and livestock and these can be challenging to identify on the large scales of food production systems. Accurate identifications to capture this diversity and rapid scalable monitoring are necessary to identify emerging threats (i.e. pests and pathogens), inform on ecosystem health (i.e. soil and pollinator diversity), and provide evidence for new management practices (i.e. fertiliser and pesticide applications). Increasingly, environmental DNA (eDNA) is providing rapid and accurate classifications for specific organisms and entire species assemblages in substrates ranging from soil to air. Here, we aim to discuss how eDNA is being used for monitoring of agricultural ecosystems, what current limitations exist, and how these could be managed to expand applications into the future. In a systematic review we identify that eDNA-based monitoring in food production systems accounts for only 4 % of all eDNA studies. We found that the majority of these eDNA studies target soil and plant substrates (60 %), predominantly to identify microbes and insects (60 %) and are biased towards Europe (42 %). While eDNA-based monitoring studies are uncommon in many of the world's food production systems, the trend is most pronounced in emerging economies often where food security is most at risk. We suggest that the biggest limitations to eDNA for agriculture are false negatives resulting from DNA degradation and assay biases, as well as incomplete databases and the interpretation of abundance data. These require in silico, in vitro, and in vivo approaches to carefully design, test and apply eDNA monitoring for reliable and accurate taxonomic identifications. We explore future opportunities for eDNA research which could further develop this useful tool for food production system monitoring in both emerging and developed economies, hopefully improving monitoring, and ultimately food security.

Fishing for fish environmental DNA: Ecological applications, methodological considerations, surveying designs, and ways forward

Vast global declines of freshwater and marine fish diversity and population abundance pose serious threats to both ecosystem sustainability and human livelihoods. Environmental DNA (eDNA)-based biomonitoring provides robust, efficient, and cost-effective assessment of species occurrences and population trends in diverse aquatic environments. Thus, it holds great potential for improving conventional surveillance frameworks to facilitate fish conservation and fisheries management. However, the many technical considerations and rapid developments underway in the eDNA arena can overwhelm researchers and practitioners new to the field. Here, we systematically analysed 416 fish eDNA studies to summarize research trends in terms of investigated targets, research aims, and study systems, and reviewed the applications, rationales, methodological considerations, and limitations of eDNA methods with an emphasis on fish and fisheries research. We highlighted how eDNA technology may advance our knowledge of fish behaviour, species distributions, population genetics, community structures, and ecological interactions. We also synthesized the current knowledge of several important methodological concerns, including the qualitative and quantitative power eDNA has to recover fish biodiversity and abundance, and the spatial and temporal representations of eDNA with respect to its sources. To facilitate ecological applications implementing fish eDNA techniques, recent literature was summarized to generate guidelines for effective sampling in lentic, lotic, and marine habitats. Finally, we identified current gaps and limitations, and pointed out newly emerging research avenues for fish eDNA. As methodological optimization and standardization improve, eDNA technology should revolutionize fish monitoring and promote biodiversity conservation and fisheries management that transcends geographic and temporal boundaries.

Antibiotic-resistant bacteria and antibiotic resistance genes in uranium mine: Distribution and influencing factors

Both heavy metals and radiation could affect the proliferation and dissemination of emerging antibiotic resistance pollutants. As an environmental medium rich in radioactive metals, the profile of antibiotic resistance in uranium mine remains largely unknown. A uranium mine in Guangdong province, China was selected to investigate the distribution and influencing factors of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) including intracellular ARGs (iARGs), adsorbed-extracellular ARGs (aeARGs), and free extracellular ARGs (feARGs). The result indicated that sulfonamide and tetracycline ARB could be generally detected in mining area with the absolute concentrations of 7.70 × 10²-5.18 × 10⁵ colony forming unit/g. The abundances of aeARGs in mine soil were significantly higher than those of iARGs (p < 0.05), highlighting the critical contribution of aeARGs to ARGs spread. The feARGs in mine drainage and its receiving river were abundant (3.38 × 10⁴-1.86 × 10⁷ copies/mL). ARB, aeARGs, and iARGs may correlate with nitrogen species and heavy metals (e.g., U and Mn), and feARGs presented a significant correlation with chemical oxygen demand (p < 0.05). These findings demonstrate the occurrence of ARB and ARGs in uranium mine for the first time, thereby contributing to the assessment and control of the ecological risk of antibiotic resistance in radioactive environments.

The relative abundances of yeasts attractive to Drosophila suzukii differ between fruit types and are greatest on raspberries

Fungal metabolic volatiles attract Drosophila suzukii which oviposits in ripening fruits, but there are few data describing the fungal microbiomes of commercial fruits susceptible to this insect pest. We tested the hypothesis that fruit type and ripening stage have a significant effect on fruit surface fungal communities using DNA metabarcoding approaches and found strong support for differences in all three fungal community biodiversity metrics analysed (numbers, types, and abundances of taxa). There was an average fivefold greater difference in fungal communities between sites with different fruit types (strawberry, cherry, raspberry, and blueberry) than across fruit developmental stages, demonstrating site and/or fruit type is the greater factor defining fungal community assemblage. The addition of a fungal internal standard (Plectosphaerella cucumerina) showed cherry had relatively static fungal populations across ripening. Raspberry had a greater prevalence of Saccharomycetales yeasts attractive to D. suzukii, including Hanseniaspora uvarum, which aligns with reports that raspberry is among the fruits with greatest susceptibility and attraction to D. suzukii. Greater knowledge of how yeast communities change during fruit maturation and between species or sites may be valuable for developing methods to manipulate fruit microbiomes for use in integrated pest management strategies to control D. suzukii.

Brassicaceae host plants mask the feedback from the previous year's soil history on bacterial communities, except when they experience drought

Soil history operates through time to influence the structure and biodiversity of soil bacterial communities. Examining how different soil histories endure will help clarify the rules of bacterial community assembly. In this study, we established three different soil histories in field trials; the following year these plots were planted with five different Brassicaceae species. We hypothesized that the previously established soil histories would continue to structure the subsequent Brassicaceae bacterial root and rhizosphere communities. We used a MiSeq 16S rRNA metabarcoding strategy to determine the impact of different soil histories on the structure and biodiversity of the bacterial root and rhizosphere communities from the five different Brassicaceae host plants. We found that the Brassicaceae hosts were consistently significant factors in structuring the bacterial communities. Four host plants (Sinapis alba, Brassica napus, B. juncea, B. carinata) formed similar bacterial communities, regardless of different soil histories. Camelina sativa host plants structured phylogenetically distinct bacterial communities compared to the other hosts, particularly in their roots. Soil history established the previous year was only a significant factor for bacterial community structure when the feedback of the Brassicaceae host plants was weakened, potentially due to limited soil moisture during a dry year. Understanding how soil history is involved in the structure and biodiversity of bacterial communities through time is a limitation in microbial ecology and is required for employing microbiome technologies in improving agricultural systems. This article is protected by copyright. All rights reserved.

Development and evaluation of a meat mitochondrial metagenomic (3MG) method for composition determination of meat from fifteen mammalian and avian species

BACKGROUND

Bioassessment and biomonitoring of meat products are aimed at identifying and quantifying adulterants and contaminants, such as meat from unexpected sources and microbes. Several methods for determining the biological composition of mixed samples have been used, including metabarcoding, metagenomics and mitochondrial metagenomics. In this study, we aimed to develop a method based on next-generation DNA sequencing to estimate samples that might contain meat from 15 mammalian and avian species that are commonly related to meat bioassessment and biomonitoring.

RESULTS

In this project, we found the meat composition from 15 species could not be identified with the metabarcoding approach because of the lack of universal primers or insufficient discrimination power. Consequently, we developed and evaluated a meat mitochondrial metagenomics (3MG) method. The 3MG method has four steps: (1) extraction of sequencing reads from mitochondrial genomes (mitogenomes); (2) assembly of mitogenomes; (3) mapping of mitochondrial reads to the assembled mitogenomes; and (4) biomass estimation based on the number of uniquely mapped reads. The method was implemented in a python script called 3MG. The analysis of simulated datasets showed that the method can determine contaminant composition at a proportion of 2% and the relative error was < 5%. To evaluate the performance of 3MG, we constructed and analysed mixed samples derived from 15 animal species in equal mass. Then, we constructed and analysed mixed samples derived from two animal species (pork and chicken) in different ratios. DNAs were extracted and used in constructing 21 libraries for next-generation sequencing. The analysis of the 15 species mix with the method showed the successful identification of 12 of the 15 (80%) animal species tested. The analysis of the mixed samples of the two species revealed correlation coefficients of 0.98 for pork and 0.98 for chicken between the number of uniquely mapped reads and the mass proportion.

CONCLUSION

To the best of our knowledge, this study is the first to demonstrate the potential of the non-targeted 3MG method as a tool for accurately estimating biomass in meat mix samples. The method has potential broad applications in meat product safety.

Efficiency of eDNA and iDNA in assessing vertebrate diversity and its abundance

Environmental DNA (eDNA) and invertebrate-derived DNA (iDNA) have been increasingly recognized as powerful tools for biodiversity assessment and conservation management. However, eDNA/iDNA efficiency for vertebrate diversity assessment remains uncertain, and comparisons to conventional methods are still rare. Through a meta-analysis of previously published vertebrate diversity surveys, we compared the efficiency of eDNA/iDNA against conventional methods across several types of samplers, vertebrate groups, and locations (tropical vs. temperate zones). We also assess eDNA/iDNA efficiency to estimate relative abundance or biomass over different molecular methods (qPCR and metabarcoding) and type of experiment (in the laboratory or in the field). We showed that for water sampler, fish as a target species, and studies achieved in temperate zones, eDNA presents lower risk of not detecting a species or a site with a target species than conventional methods. These results show that eDNA is an efficient tool to assess fish diversity. Moreover, eDNA data presents positive correlation with fish abundance or biomass. However, such correlation was higher in laboratory experiments than in the field. For the other samplers, vertebrate groups, and in tropical zones we were not able to draw general conclusion, highlighting the urgency of conducting more comparative studies.

Fungal biodiversity and conservation mycology in light of new technology, big data, and changing attitudes

Fungi have successfully established themselves across seemingly every possible niche, substrate, and biome. They are fundamental to biogeochemical cycling, interspecies interactions, food production, and drug bioprocessing, as well as playing less heroic roles as difficult to treat human infections and devastating plant pathogens. Despite community efforts to estimate and catalog fungal diversity, we have only named and described a minute fraction of the fungal world. The identification, characterization, and conservation of fungal diversity is paramount to preserving fungal bioresources, and to understanding and predicting ecosystem cycling and the evolution and epidemiology of fungal disease. Although species and ecosystem conservation are necessarily the foundation of preserving this diversity, there is value in expanding our definition of conservation to include the protection of biological collections, ecological metadata, genetic and genomic data, and the methods and code used for our analyses. These definitions of conservation are interdependent. For example, we need metadata on host specificity and biogeography to understand rarity and set priorities for conservation. To aid in these efforts, we need to draw expertise from diverse fields to tie traditional taxonomic knowledge to data obtained from modern -omics-based approaches, and support the advancement of diverse research perspectives. We also need new tools, including an updated framework for describing and tracking species known only from DNA, and the continued integration of functional predictions to link genetic diversity to functional and ecological diversity. Here, we review the state of fungal diversity research as shaped by recent technological advancements, and how changing viewpoints in taxonomy, -omics, and systematics can be integrated to advance mycological research and preserve fungal biodiversity.

Ecological and Evolutionary responses to Antibiotic Treatment in the Human Gut Microbiota

The potential for antibiotics to affect the ecology and evolution of the human gut microbiota is well recognised and has wide-ranging implications for host health. Here, we review the findings of key studies that surveyed the human gut microbiota during antibiotic treatment. We find several broad patterns including the loss of diversity, disturbance of community composition, suppression of bacteria in the Actinobacteria phylum, amplification of bacteria in the Bacteroidetes phylum, and promotion of antibiotic resistance. Such changes to the microbiota were often, but not always, recovered following the end of treatment. However, many studies reported unique and/or contradictory results, which highlights our inability to meaningfully predict or explain the effects of antibiotic treatment on the human gut microbiome. This problem arises from variation between existing studies in three major categories: differences in dose, class and combinations of antibiotic treatments used; differences in demographics, lifestyles, and locations of subjects; and differences in measurements, analyses and reporting styles used by researchers. To overcome this, we suggest two integrated approaches: (i) a top-down approach focused on building predictive models through large sample sizes, deep metagenomic sequencing, and effective collaboration; and (ii) a bottom-up reductionist approach focused on testing hypotheses using model systems.

A suite of rare microbes interacts with a dominant, heritable, fungal endophyte to influence plant trait expression

Endophytes are microbes that live, for at least a portion of their life history, within plant tissues. Endophyte assemblages are often composed of a few abundant taxa and many infrequently observed, low-biomass taxa that are, in a word, rare. The ways in which most endophytes affect host phenotype are unknown; however, certain dominant endophytes can influence plants in ecologically meaningful ways-including by affecting growth and immune system functioning. In contrast, the effects of rare endophytes on their hosts have been unexplored, including how rare endophytes might interact with abundant endophytes to shape plant phenotype. Here, we manipulate both the suite of rare foliar endophytes (including both fungi and bacteria) and Alternaria fulva-a vertically transmitted and usually abundant fungus-within the fabaceous forb Astragalus lentiginosus. We report that rare, low-biomass endophytes affected host size and foliar %N, but only when the heritable fungal endophyte (A. fulva) was not present. A. fulva also reduced plant size and %N, but these deleterious effects on the host could be offset by a negative association we observed between this heritable fungus and a foliar pathogen. These results demonstrate how interactions among endophytic taxa determine the net effects on host plants and suggest that the myriad rare endophytes within plant leaves may be more than a collection of uninfluential, commensal organisms, but instead have meaningful ecological roles.

Measuring the absolute abundance of the microbiome by adding yeast containing 16S rRNA gene from a hyperthermophile

High-throughput sequencing (HTS) of 16S rRNA gene amplicons provides compositional information regarding the microbial community, but not the absolute abundance of the bacteria. We aimed to develop a standardized method for quantifying the absolute abundance of bacteria in microbiome studies. To demonstrate the utility of our approach, we quantified the number of bacteria from the compositional data of the fecal and cecal microbiomes. The 16S rRNA gene of a hyperthermophile, Thermus aquaticus, was cloned into Pichia pastoris (yeast) genome, and an equivalent amount of the yeast was added to the stool and cecal samples of mice before DNA extraction. 16S rRNA gene library construction and HTS were performed after DNA extraction. The absolute abundances of bacteria were calculated using T. aquaticus reads. The average relative abundances of T. aquaticus in the five stool and five cecal samples were 0.95% and 0.33%, respectively, indicating that the number of bacteria in a cecum sample is 2.9 times higher than that in a stool sample. The method proposed for quantifying the absolute abundance of the bacterial population in this study is expected to overcome the limitation of showing only compositional data in most microbiome studies.

Characterizing Microbiomes via Sequencing of Marker Loci: Techniques To Improve Throughput, Account for Cross-Contamination, and Reduce Cost

New approaches to characterizing microbiomes via high-throughput sequencing provide impressive gains in efficiency and cost reduction compared to approaches that were standard just a few years ago. However, the speed of method development has been such that staying abreast of the latest technological advances is challenging. Moreover, shifting laboratory protocols to include new methods can be expensive and time consuming. To facilitate adoption of new techniques, we provide a guide and review of recent advances that are relevant for single-locus sequence-based study of microbiomes—from extraction to library preparation—including a primer regarding the use of liquid-handling automation in small-scale academic settings. Additionally, we describe several amendments to published techniques to improve throughput, track contamination, and reduce cost. Notably, we suggest adding synthetic DNA molecules to each sample during nucleic acid extraction, thus providing a method of documenting incidences of cross-contamination. We also describe a dual-indexing scheme for Illumina sequencers that allows multiplexing of many thousands of samples with minimal PhiX input. Collectively, the techniques that we describe demonstrate that laboratory technology need not impose strict limitations on the scale of molecular microbial ecology studies.

IMPORTANCE New methods to characterize microbiomes reduce technology-imposed limitations to study design, but many new approaches have not been widely adopted. Here, we present techniques to increase throughput and reduce contamination alongside a thorough review of current best practices.

Experimental infrastructure requirements for quantitative research on microbial communities

Natural microbial communities are composed of a large diversity of interacting microorganisms, each with a specific role in the functional properties of the ecosystem. The objectives in microbial ecology research are related to identifying, understanding and exploring the role of these different microorganisms. Because of the rapidly increasing power of DNA sequencing and the rapid increase of genomic data, main attention of microbial ecology research shifted from cultivation-oriented studies towards metagenomic studies. Despite these efforts, the direct link between the molecular properties and the measurable changes in the functional performance of the ecosystem is often poorly documented. A quantitative understanding of functional properties in relation to the molecular changes requires effective integration, standardization, and parallelization of experiments. High-resolution functional characterization is a prerequisite for interpretation of changes in metagenomic properties, and will improve our understanding of microbial communities and facilitate their exploration for health and circular economy related objectives.

DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions

Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.

The human respiratory tract microbial community structures in healthy and cystic fibrosis infants

The metagenome development of the human respiratory tract was investigated by shotgun metagenome metagenomic sequencing of cough swabs from healthy children and children with cystic fibrosis (CF) between 3 weeks and 6 years of age. A healthy microbial community signature was associated with increased absolute abundances in terms of bacterial–human cell ratios of core and rare species across all age groups, with a higher diversity of rare species and a tightly interconnected species co-occurrence network, in which individual members were found in close proximity to each other and negative correlations were absent. Even without typical CF pathogens, the CF infant co-occurrence network was found to be less stable and prone to fragmentation due to fewer connections between species, a higher number of bridging species and the presence of negative species correlations. Detection of low-abundant DNA of the CF hallmark pathogen Pseudomonas aeruginosa was neither disease- nor age-associated in our cohort. Healthy and CF children come into contact with P. aeruginosa on a regular basis and from early on.