Comparing the performance of three ancient DNA extraction methods for high‐throughput sequencing

The DNA molecules that can be extracted from archaeological and palaeontological remains are often degraded and massively contaminated with environmental microbial material. This reduces the efficacy of shotgun approaches for sequencing ancient genomes, despite the decreasing sequencing costs of high‐throughput sequencing (HTS). Improving the recovery of endogenous molecules from the DNA extraction and purification steps could, thus, help advance the characterization of ancient genomes. Here, we apply the three most commonly used DNA extraction methods to five ancient bone samples spanning a ~30 thousand year temporal range and originating from a diversity of environments, from South America to Alaska. We show that methods based on the purification of DNA fragments using silica columns are more advantageous than in solution methods and increase not only the total amount of DNA molecules retrieved but also the relative importance of endogenous DNA fragments and their molecular diversity. Therefore, these methods provide a cost‐effective solution for downstream applications, including DNA sequencing on HTS platforms.     

Metagenomic microbial community profiling using unique clade-specific marker genes

Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large data sets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50× faster than current approaches. We validated our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads and provide the largest metagenomic profiling to date of the human gut. It can be accessed at http://huttenhower.sph.harvard.edu/metaphlan/.     

Shotgun microbial profiling of fossil remains

Millions to billions of DNA sequences can now be generated from ancient skeletal remains thanks to the massive throughput of next‐generation sequencing platforms. Except in cases of exceptional endogenous DNA preservation, most of the sequences isolated from fossil material do not originate from the specimen of interest, but instead reflect environmental organisms that colonized the specimen after death. Here, we characterize the microbial diversity recovered from seven c. 200‐ to 13 000‐year‐old horse bones collected from northern Siberia. We use a robust, taxonomy‐based assignment approach to identify the microorganisms present in ancient DNA extracts and quantify their relative abundance. Our results suggest that molecular preservation niches exist within ancient samples that can potentially be used to characterize the environments from which the remains are recovered. In addition, microbial community profiling of the seven specimens revealed site‐specific environmental signatures. These microbial communities appear to comprise mainly organisms that colonized the fossils recently. Our approach significantly extends the amount of useful data that can be recovered from ancient specimens using a shotgun sequencing approach. In future, it may be possible to correlate, for example, the accumulation of postmortem DNA damage with the presence and/or abundance of particular microbes.     

An improved method for utilizing high‐throughput amplicon sequencing to determine the diets of insectivorous animals

DNA analysis of predator faeces using high‐throughput amplicon sequencing (HTS) enhances our understanding of predator–prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (COI). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair “ZBJ” to results using the novel primer pair “ANML.” To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single‐copy (cloned) COI sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre‐ and post‐PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%), whereas ZBJ amplified 24–40 of 59 taxa (41%–68%). Furthermore, in an HTS comparison of field‐collected samples, the ANML primers detected nearly fourfold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.     

Prevention,diagnosis and treatment of high‐throughput sequencing data pathologies

High‐throughput sequencing (HTS) technologies generate millions of sequence reads from DNA/RNA molecules rapidly and cost‐effectively, enabling single investigator laboratories to address a variety of ‘omics’ questions in nonmodel organisms, fundamentally changing the way genomic approaches are used to advance biological research. One major challenge posed by HTS is the complexity and difficulty of data quality control (QC). While QC issues associated with sample isolation, library preparation and sequencing are well known and protocols for their handling are widely available, the QC of the actual sequence reads generated by HTS is often overlooked. HTS‐generated sequence reads can contain various errors, biases and artefacts whose identification and amelioration can greatly impact subsequent data analysis. However, a systematic survey on QC procedures for HTS data is still lacking. In this review, we begin by presenting standard ‘health check‐up’ QC procedures recommended for HTS data sets and establishing what ‘healthy’ HTS data look like. We next proceed by classifying errors, biases and artefacts present in HTS data into three major types of ‘pathologies’, discussing their causes and symptoms and illustrating with examples their diagnosis and impact on downstream analyses. We conclude this review by offering examples of successful ‘treatment’ protocols and recommendations on standard practices and treatment options. Notwithstanding the speed with which HTS technologies – and consequently their pathologies – change, we argue that careful QC of HTS data is an important – yet often neglected – aspect of their application in molecular ecology, and lay the groundwork for developing a HTS data QC ‘best practices’ guide.     

Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes

Shotgun metagenomic sequencing does not depend on gene-targeted primers or PCR amplification; thus, it is not affected by primer bias or chimeras. However, searching rRNA genes from large shotgun Illumina data sets is computationally expensive, and no approach exists for unsupervised community analysis of small-subunit (SSU) rRNA gene fragments retrieved from shotgun data. We present a pipeline, SSUsearch, to achieve the faster identification of short-subunit rRNA gene fragments and enabled unsupervised community analysis with shotgun data. It also includes classification and copy number correction, and the output can be used by traditional amplicon analysis platforms. Shotgun metagenome data using this pipeline yielded higher diversity estimates than amplicon data but retained the grouping of samples in ordination analyses. We applied this pipeline to soil samples with paired shotgun and amplicon data and confirmed bias against Verrucomicrobia in a commonly used V6-V8 primer set, as well as discovering likely bias against Actinobacteria and for Verrucomicrobia in a commonly used V4 primer set. This pipeline can utilize all variable regions in SSU rRNA and also can be applied to large-subunit (LSU) rRNA genes for confirmation of community structure. The pipeline can scale to handle large amounts of soil metagenomic data (5 Gb memory and 5 central processing unit hours to process 38 Gb [1 lane] of trimmed Illumina HiSeq2500 data) and is freely available at https://github.com/dib-lab/SSUsearch under a BSD license.     

Microbial community analysis using high-throughput sequencing technology: a beginner’s guide for microbiologists

Microbial communities present in diverse environments from deep seas to human body niches play significant roles in the complex ecosystem and human health. Characterizing their structural and functional diversities is indispensable, and many approaches, such as microscopic observation, DNA fingerprinting, and PCR-based marker gene analysis, have been successfully applied to identify microorganisms. Since the revolutionary improvement of DNA sequencing technologies, direct and high-throughput analysis of genomic DNA from a whole environmental community without prior cultivation has become the mainstream approach, overcoming the constraints of the classical approaches. Here, we first briefly review the history of environmental DNA analysis applications with a focus on profiling the taxonomic composition and functional potentials of microbial communities. To this end, we aim to introduce the shotgun metagenomic sequencing (SMS) approach, which is used for the untargeted (“shotgun”) sequencing of all (“meta”) microbial genomes (“genomic”) present in a sample. SMS data analyses are performed in silico using various software programs; however, in silico analysis is typically regarded as a burden on wet-lab experimental microbiologists. Therefore, in this review, we present microbiologists who are unfamiliar with in silico analyses with a basic and practical SMS data analysis protocol. This protocol covers all the bioinformatics processes of the SMS analysis in terms of data preprocessing, taxonomic profiling, functional annotation, and visualization.     

Accurate multiplexing and filtering for high-throughput amplicon-sequencing

Tagging amplicons with tag sequences appended to PCR primers allow the multiplexing of numerous samples for high-throughput sequencing (HTS). This approach is routinely used in HTS-based diversity analyses, especially in microbial ecology and biomedical diagnostics. However, amplicon library preparation is subject to pervasive sample sequence cross-contaminations as a result of tag switching events referred to as mistagging. Here, we sequenced seven amplicon libraries prepared using various multiplexing designs in order to measure the magnitude of this phenomenon and its impact on diversity analyses. Up to 28.2% of the unique sequences correspond to undetectable (critical) mistags in single- or saturated double-tagging libraries. We show the advantage of multiplexing samples following Latin Square Designs in order to optimize the detection of mistags and maximize the information on their distribution across samples. We use this information in designs incorporating PCR replicates to filter the critical mistags and to recover the exact composition of mock community samples. Being parameter-free and data-driven, our approach can provide more accurate and reproducible HTS data sets, improving the reliability of their interpretations.     

Robustness of Massively Parallel Sequencing Platforms

The improvements in high throughput sequencing technologies (HTS) made clinical sequencing projects such as ClinSeq and Genomics England feasible. Although there are significant improvements in accuracy and reproducibility of HTS based analyses, the usability of these types of data for diagnostic and prognostic applications necessitates a near perfect data generation. To assess the usability of a widely used HTS platform for accurate and reproducible clinical applications in terms of robustness, we generated whole genome shotgun (WGS) sequence data from the genomes of two human individuals in two different genome sequencing centers. After analyzing the data to characterize SNPs and indels using the same tools (BWA, SAMtools, and GATK), we observed significant number of discrepancies in the call sets. As expected, the most of the disagreements between the call sets were found within genomic regions containing common repeats and segmental duplications, albeit only a small fraction of the discordant variants were within the exons and other functionally relevant regions such as promoters. We conclude that although HTS platforms are sufficiently powerful for providing data for first-pass clinical tests, the variant predictions still need to be confirmed using orthogonal methods before using in clinical applications.     

Ancient DNA sheds new light on the Svalbard foraminiferal fossil record of the last millennium

Recent palaeogenetic studies have demonstrated the occurrence of preserved ancient DNA (aDNA) in various types of fossilised material. Environmental aDNA sequences assigned to modern species have been recovered from marine sediments dating to the Pleistocene. However, the match between the aDNA and the fossil record still needs to be evaluated for the environmental DNA approaches to be fully exploited. Here, we focus on foraminifera in sediments up to one thousand years old retrieved from the Hornsund fjord (Svalbard). We compared the diversity of foraminiferal microfossil assemblages with the diversity of aDNA sequenced from subsurface sediment samples using both cloning and high‐throughput sequencing (HTS). Our study shows that 57% of the species archived in the fossil record were also detected in the aDNA data. However, the relative abundance of aDNA sequence reads and fossil specimens differed considerably. We also found a limited match between the stratigraphic occurrence of some fossil species and their aDNA sequences, especially in the case of rare taxa. The aDNA data comprised a high proportion of non‐fossilised monothalamous species, which are known to dominate in modern foraminiferal communities of the Svalbard region. Our results confirm the relevance of HTS for studying past micro‐eukaryotic diversity and provide insight into its ability to reflect fossil assemblages. Palaeogenetic studies including aDNA analyses of non‐fossilised groups expand the range of palaeoceanographical proxies and therefore may increase the accuracy of palaeoenvironmental reconstructions.     

OTU Analysis Using Metagenomic Shotgun Sequencing Data

Because of technological limitations, the primer and amplification biases in targeted sequencing of 16S rRNA genes have veiled the true microbial diversity underlying environmental samples. However, the protocol of metagenomic shotgun sequencing provides 16S rRNA gene fragment data with natural immunity against the biases raised during priming and thus the potential of uncovering the true structure of microbial community by giving more accurate predictions of operational taxonomic units (OTUs). Nonetheless, the lack of statistically rigorous comparison between 16S rRNA gene fragments and other data types makes it difficult to interpret previously reported results using 16S rRNA gene fragments. Therefore, in the present work, we established a standard analysis pipeline that would help confirm if the differences in the data are true or are just due to potential technical bias. This pipeline is built by using simulated data to find optimal mapping and OTU prediction methods. The comparison between simulated datasets revealed a relationship between 16S rRNA gene fragments and full-length 16S rRNA sequences that a 16S rRNA gene fragment having a length >150 bp provides the same accuracy as a full-length 16S rRNA sequence using our proposed pipeline, which could serve as a good starting point for experimental design and making the comparison between 16S rRNA gene fragment-based and targeted 16S rRNA sequencing-based surveys possible.     

Genotypic Microbial Community Profiling: A Critical Technical Review

Microbial ecology has undergone a profound change in the last two decades with regard to methods employed for the analysis of natural communities. Emphasis has shifted from culturing to the analysis of signature molecules including molecular DNA-based approaches that rely either on direct cloning and sequencing of DNA fragments (shotgun cloning) or often rely on prior amplification of target sequences by use of the polymerase chain reaction (PCR). The pool of PCR products can again be either cloned and sequenced or can be subjected to an increasing variety of genetic profiling methods, including amplified ribosomal DNA restriction analysis, automated ribosomal intergenic spacer analysis, terminal restriction fragment length polymorphism, denaturing gradient gel electrophoresis, temperature gradient gel electrophoresis, single strand conformation polymorphism, and denaturing high-performance liquid chromatography. In this document, we present and critically compare these methods commonly used for the study of microbial diversity.     

On the use of high‐throughput sequencing for the study of cyanobacterial diversity in Antarctic aquatic mats

The study of Antarctic cyanobacterial diversity has been mostly limited to morphological identification and traditional molecular techniques. High‐throughput sequencing (HTS) allows a much better understanding of microbial distribution in the environment, but its application is hampered by several methodological and analytical challenges. In this work, we explored the use of HTS as a tool for the study of cyanobacterial diversity in Antarctic aquatic mats. Our results highlight the importance of using artificial communities to validate the parameters of the bioinformatics procedure used to analyze natural communities, since pipeline‐dependent biases had a strong effect on the observed community structures. Analysis of microbial mats from five Antarctic lakes and an aquatic biofilm from the Sub‐Antarctic showed that HTS is a valuable tool for the assessment of cyanobacterial diversity. The majority of the operational taxonomic units retrieved were related to filamentous taxa such as Leptolyngbya and Phormidium, which are common genera in Antarctic lacustrine microbial mats. However, other phylotypes related to different taxa such as Geitlerinema, Pseudanabaena, Synechococcus, Chamaesiphon, Calothrix, and Coleodesmium were also found. Results revealed a much higher diversity than what had been reported using traditional methods and also highlighted remarkable differences between the cyanobacterial communities of the studied lakes. The aquatic biofilm from the Sub‐Antarctic had a distinct cyanobacterial community from the Antarctic lakes, which in turn displayed a salinity‐dependent community structure at the phylotype level.     

Ancient DNA analysis identifies marine mollusc shells as new metagenomic archives of the past

Marine mollusc shells enclose a wealth of information on coastal organisms and their environment. Their life history traits as well as (palaeo‐) environmental conditions, including temperature, food availability, salinity and pollution, can be traced through the analysis of their shell (micro‐) structure and biogeochemical composition. Adding to this list, the DNA entrapped in shell carbonate biominerals potentially offers a novel and complementary proxy both for reconstructing palaeoenvironments and tracking mollusc evolutionary trajectories. Here, we assess this potential by applying DNA extraction, high‐throughput shotgun DNA sequencing and metagenomic analyses to marine mollusc shells spanning the last ~7,000 years. We report successful DNA extraction from shells, including a variety of ancient specimens, and find that DNA recovery is highly dependent on their biomineral structure, carbonate layer preservation and disease state. We demonstrate positive taxonomic identification of mollusc species using a combination of mitochondrial DNA genomes, barcodes, genome‐scale data and metagenomic approaches. We also find shell biominerals to contain a diversity of microbial DNA from the marine environment. Finally, we reconstruct genomic sequences of organisms closely related to the Vibrio tapetis bacteria from Manila clam shells previously diagnosed with Brown Ring Disease. Our results reveal marine mollusc shells as novel genetic archives of the past, which opens new perspectives in ancient DNA research, with the potential to reconstruct the evolutionary history of molluscs, microbial communities and pathogens in the face of environmental changes. Other future applications include conservation of endangered mollusc species and aquaculture management.     

Assessing insect biodiversity with automatic light traps in Brazil: Pearls and pitfalls of metabarcoding samples in preservative ethanol

Automated species identification based on data produced with metabarcoding offers an alternative for assessing biodiversity of bulk insect samples obtained with traps. We used a standard two‐step PCR approach to amplify a 313 bp fragment of the barcoding region of the mitochondrial COI gene. The PCR products were sequenced on an Illumina MiSeq platform, and the OTUs production and taxonomic identifications were performed with a customized pipeline and database. The DNA used in the PCR procedures was extracted directly from the preservative ethanol of bulk insect samples obtained with automatic light traps in 12 sampling areas located in different biomes of Brazil, during wet and dry seasons. Agricultural field and forest edge habitats were collected for all sampling areas. A total of 119 insect OTUs and nine additional OTUs assigned to other arthropod taxa were obtained at a ≥97% sequence similarity level. The alpha and beta diversity analyses comparing biomes, habitats, and seasons were mostly inconclusive, except for a significant difference in beta diversity between biomes. In this study, we were able to metabarcode and HTS adult insects from their preservative medium. Notwithstanding, our results underrepresent the true magnitude of insect diversity expected from samples obtained with automatic light traps in Brazil. Although biological and technical factors might have impacted our results, measures to optimize and standardize eDNA HTS should be in place to improve taxonomic coverage of samples of unknown diversity and stored in suboptimal conditions, which is the case of most eDNA samples.     

Unexpected biodiversity of ciliates in marine samples from below the photic zone

Marine microbial eukaryotes play critical roles in planktonic food webs and have been described as most diverse in the photic zone where productivity is high. We used high‐throughput sequencing (HTS) to analyse the spatial distribution of planktonic ciliate diversity from shallow waters (<30 m depth) to beyond the continental shelf (>800 m depth) along a 163 km transect off the coast of New England, USA. We focus on ciliates in the subclasses Oligotrichia and Choreotrichia (class Spirotrichea), as these taxa are major components of marine food webs. We did not observe the decrease of diversity below the photic zone expected based on productivity and previous analyses. Instead, we saw an increase of diversity with depth. We also observed that the ciliate communities assessed by HTS cluster by depth layer and degree of water column stratification, suggesting that community assembly is driven by environmental factors. Across our samples, abundant OTUs tend to match previously characterized morphospecies while rare OTUs are more often undescribed, consistent with the idea that species in the rare biosphere remain to be characterized by microscopy. Finally, samples taken below the photic zone also reveal the prevalence of two uncharacterized (i.e. lacking sequenced morphospecies) clades – clusters X₁ and X₂ – that are enriched within the nano‐sized fraction (2–10 μm) and are defined by deletions within the region of the SSU‐rDNA analysed here. Together, these data reinforce that we still have much to learn about microbial diversity in marine ecosystems, especially in deep‐waters that may be a reservoir for rare species and uncharacterized taxa.     

High‐throughput microsatellite genotyping in ecology: improved accuracy,efficiency, standardization and success with low‐quantity and degraded DNA

Microsatellite markers have played a major role in ecological, evolutionary and conservation research during the past 20 years. However, technical constrains related to the use of capillary electrophoresis and a recent technological revolution that has impacted other marker types have brought to question the continued use of microsatellites for certain applications. We present a study for improving microsatellite genotyping in ecology using high‐throughput sequencing (HTS). This approach entails selection of short markers suitable for HTS, sequencing PCR‐amplified microsatellites on an Illumina platform and bioinformatic treatment of the sequence data to obtain multilocus genotypes. It takes advantage of the fact that HTS gives direct access to microsatellite sequences, allowing unambiguous allele identification and enabling automation of the genotyping process through bioinformatics. In addition, the massive parallel sequencing abilities expand the information content of single experimental runs far beyond capillary electrophoresis. We illustrated the method by genotyping brown bear samples amplified with a multiplex PCR of 13 new microsatellite markers and a sex marker. HTS of microsatellites provided accurate individual identification and parentage assignment and resulted in a significant improvement of genotyping success (84%) of faecal degraded DNA and costs reduction compared to capillary electrophoresis. The HTS approach holds vast potential for improving success, accuracy, efficiency and standardization of microsatellite genotyping in ecological and conservation applications, especially those that rely on profiling of low‐quantity/quality DNA and on the construction of genetic databases. We discuss and give perspectives for the implementation of the method in the light of the challenges encountered in wildlife studies.     

StreamingTrim 1.0: a Java software for dynamic trimming of 16S rRNA sequence data from metagenetic studies

Next‐generation sequencing technologies are extensively used in the field of molecular microbial ecology to describe taxonomic composition and to infer functionality of microbial communities. In particular, the so‐called barcode or metagenetic applications that are based on PCR amplicon library sequencing are very popular at present. One of the problems, related to the utilization of the data of these libraries, is the analysis of reads quality and removal (trimming) of low‐quality segments, while retaining sufficient information for subsequent analyses (e.g. taxonomic assignment). Here, we present StreamingTrim, a DNA reads trimming software, written in Java, with which researchers are able to analyse the quality of DNA sequences in fastq files and to search for low‐quality zones in a very conservative way. This software has been developed with the aim to provide a tool capable of trimming amplicon library data, retaining as much as taxonomic information as possible. This software is equipped with a graphical user interface for a user‐friendly usage. Moreover, from a computational point of view, StreamingTrim reads and analyses sequences one by one from an input fastq file, without keeping anything in memory, permitting to run the computation on a normal desktop PC or even a laptop. Trimmed sequences are saved in an output file, and a statistics summary is displayed that contains the mean and standard deviation of the length and quality of the whole sequence file. Compiled software, a manual and example data sets are available under the BSD‐2‐Clause License at the GitHub repository at https://github.com/GiBacci/StreamingTrim/ .     

The phylogenetic diversity of metagenomes

Phylogenetic diversity--patterns of phylogenetic relatedness among organisms in ecological communities--provides important insights into the mechanisms underlying community assembly. Studies that measure phylogenetic diversity in microbial communities have primarily been limited to a single marker gene approach, using the small subunit of the rRNA gene (SSU-rRNA) to quantify phylogenetic relationships among microbial taxa. In this study, we present an approach for inferring phylogenetic relationships among microorganisms based on the random metagenomic sequencing of DNA fragments. To overcome challenges caused by the fragmentary nature of metagenomic data, we leveraged fully sequenced bacterial genomes as a scaffold to enable inference of phylogenetic relationships among metagenomic sequences from multiple phylogenetic marker gene families. The resulting metagenomic phylogeny can be used to quantify the phylogenetic diversity of microbial communities based on metagenomic data sets. We applied this method to understand patterns of microbial phylogenetic diversity and community assembly along an oceanic depth gradient, and compared our findings to previous studies of this gradient using SSU-rRNA gene and metagenomic analyses. Bacterial phylogenetic diversity was highest at intermediate depths beneath the ocean surface, whereas taxonomic diversity (diversity measured by binning sequences into taxonomically similar groups) showed no relationship with depth. Phylogenetic diversity estimates based on the SSU-rRNA gene and the multi-gene metagenomic phylogeny were broadly concordant, suggesting that our approach will be applicable to other metagenomic data sets for which corresponding SSU-rRNA gene sequences are unavailable. Our approach opens up the possibility of using metagenomic data to study microbial diversity in a phylogenetic context.     

Picoeukaryotic sequences in the Sargasso Sea metagenome

Background  

With genome sequencing becoming more and more affordable, environmental shotgun sequencing of the microorganisms present in an environment generates a challenging amount of sequence data for the scientific community. These sequence data enable the diversity of the microbial world and the metabolic pathways within an environment to be investigated, a previously unthinkable achievement when using traditional approaches. DNA sequence data assembled from extracts of 0.8 μm filtered Sargasso seawater unveiled an unprecedented glimpse of marine prokaryotic diversity and gene content. Serendipitously, many sequences representing picoeukaryotes (cell size <2 μm) were also present within this dataset. We investigated the picoeukaryotic diversity of this database by searching sequences containing homologs of eight nuclear anchor genes that are well conserved throughout the eukaryotic lineage, as well as one chloroplastic and one mitochondrial gene.