A vision for ubiquitous sequencing

SituSeq: an offline protocol for rapid and remote Nanopore 16S rRNA amplicon sequence analysis

Microbiome analysis through 16S rRNA gene sequencing is a crucial tool for understanding the microbial ecology of any habitat or ecosystem. However, workflows require large equipment, stable internet, and extensive computing power such that most of the work is performed far away from sample collection in both space and time. Performing amplicon sequencing and analysis at sample collection would have positive implications in many instances including remote fieldwork and point-of-care medical diagnoses. Here we present SituSeq, an offline and portable workflow for the sequencing and analysis of 16S rRNA gene amplicons using Nanopore sequencing and a standard laptop computer. SituSeq was validated by comparing Nanopore 16S rRNA gene amplicons, Illumina 16S rRNA gene amplicons, and Illumina metagenomes, sequenced using the same environmental DNA. Comparisons revealed consistent community composition, ecological trends, and sequence identity across platforms. Correlation between the abundance of taxa in each taxonomic level in Illumina and Nanopore data sets was high (Pearson's r > 0.9), and over 70% of Illumina 16S rRNA gene sequences matched a Nanopore sequence with greater than 97% sequence identity. On board a research vessel on the open ocean, SituSeq was used to analyze amplicon sequences from deep sea sediments less than 2 h after sequencing, and 8 h after sample collection. The rapidly available results informed decisions about subsequent sampling in near real-time while the offshore expedition was still underway. SituSeq is a portable and user-friendly workflow that helps to bring the power of microbial genomics and diagnostics to many more researchers and situations.

Emerging Approaches to DNA Data Storage: Challenges and Prospects

With the total amount of worldwide data skyrocketing, the global data storage demand is predicted to grow to 1.75 × 10¹⁴ GB by 2025. Traditional storage methods have difficulties keeping pace given that current storage media have a maximum density of 10³ GB/mm³. As such, data production will far exceed the capacity of currently available storage methods. The costs of maintaining and transferring data, as well as the limited lifespans and significant data losses associated with current technologies also demand advanced solutions for information storage. Nature offers a powerful alternative through the storage of information that defines living organisms in unique orders of four bases (A, T, C, G) located in molecules called deoxyribonucleic acid (DNA). DNA molecules as information carriers have many advantages over traditional storage media. Their high storage density, potentially low maintenance cost, ease of synthesis, and chemical modification make them an ideal alternative for information storage. To this end, rapid progress has been made over the past decade by exploiting user-defined DNA materials to encode information. In this review, we discuss the most recent advances of DNA-based data storage with a major focus on the challenges that remain in this promising field, including the current intrinsic low speed in data writing and reading and the high cost per byte stored. Alternatively, data storage relying on DNA nanostructures (as opposed to DNA sequence) as well as on other combinations of nanomaterials and biomolecules are proposed with promising technological and economic advantages. In summarizing the advances that have been made and underlining the challenges that remain, we provide a roadmap for the ongoing research in this rapidly growing field, which will enable the development of technological solutions to the global demand for superior storage methodologies.

Leapfrogging laboratories: the promise and pitfalls of high-tech solutions for antimicrobial resistance surveillance in low-income settings

The scope and trajectory of today’s escalating antimicrobial resistance (AMR) crisis is inadequately captured by existing surveillance systems, particularly those of lower income settings. AMR surveillance systems typically collate data from routine culture and susceptibility testing performed in diagnostic bacteriology laboratories to support healthcare. Limited access to high quality culture and susceptibility testing results in the dearth of AMR surveillance data, typical of many parts of the world where the infectious disease burden and antimicrobial need are high. Culture and susceptibility testing by traditional techniques is also slow, which limits its value in infection management. Here, we outline hurdles to effective resistance surveillance in many low-income settings and encourage an open attitude towards new and evolving technologies that, if adopted, could close resistance surveillance gaps. Emerging advancements in point-of-care testing, laboratory detection of resistance through or without culture, and in data handling, have the potential to generate resistance data from previously unrepresented locales while simultaneously supporting healthcare. Among them are microfluidic, nucleic acid amplification technology and next-generation sequencing approaches. Other low tech or as yet unidentified innovations could also rapidly accelerate AMR surveillance. Parallel advances in data handling further promise to significantly improve AMR surveillance, and new frameworks that can capture, collate and use alternate data formats may need to be developed. We outline the promise and limitations of such technologies, their potential to leapfrog surveillance over currently available, conventional technologies in use today and early steps that health systems could take towards preparing to adopt them.

The impact of cross-kingdom molecular forensics on genetic privacy

Recent advances in metagenomic technology and computational prediction may inadvertently weaken an individual's reasonable expectation of privacy. Through cross-kingdom genetic and metagenomic forensics, we can already predict at least a dozen human phenotypes with varying degrees of accuracy. There is also growing potential to detect a "molecular echo" of an individual's microbiome from cells deposited on public surfaces. At present, host genetic data from somatic or germ cells provide more reliable information than microbiome samples. However, the emerging ability to infer personal details from different microscopic biological materials left behind on surfaces requires in-depth ethical and legal scrutiny. There is potential to identify and track individuals, along with new, surreptitious means of genetic discrimination. This commentary underscores the need to update legal and policy frameworks for genetic privacy with additional considerations for the information that could be acquired from microbiome-derived data. The article also aims to stimulate ubiquitous discourse to ensure the protection of genetic rights and liberties in the post-genomic era. Video abstract.

Whole-genome sequencing of clinical Clostridioides difficile isolates reveals molecular epidemiology and discrepancies with conventional laboratory diagnostic testing

BACKGROUND

The high clinical burden of Clostridioides difficile infections merits rapid and sensitive identification of affected individuals. However, effective diagnosis remains challenging. Current best practice guidelines recommend molecular and/or direct toxin detection-based screening for symptomatic individuals, but previous work has called into question the concordance and performance of extant clinical assays.

AIM

To better correlate the genomic and phenotypic properties of clinical C. difficile isolates with laboratory testing outcomes in both C. difficile-infected patients and asymptomatic carriers.

METHODS

Whole-genome sequencing of clinical C. difficile isolates collected from an inpatient population at a single healthcare institution was performed, enabling examination of their molecular epidemiology and toxigenic gene content. Genomic findings were compared with clinical testing outcomes, identifying multiple diagnostic discrepancies.

FINDINGS

Toxigenic culture, considered a 'reference standard', provided perfect sensitivity and specificity in predicting toxigenic gene content, whereas reduced performance was observed for Simplexa C. difficile Direct Assay (100% specificity, 88% sensitivity), Gene Xpert CD/Epi Assay (86% specificity, 83% sensitivity), and Quick Check Complete Tox A/B (100% specificity, 30% sensitivity). Genomic analysis additionally revealed variability in toxin gene sequences among C. difficile strains, phylogenomic equivalency between isolates from affected patients and carriers, and patient carriage with uncommon environmentally derived C. difficile lineages, as well as presenting opportunities for tracing pathogen transmission events.

CONCLUSION

These results highlight the variable performance of clinical stool-based testing approaches as well as the potential diagnostic utility of whole-genome sequencing as an alternative to conventional testing algorithms.

Rapid mitochondrial genome sequencing based on Oxford Nanopore Sequencing and a proxy for vertebrate species identification

Molecular information is crucial for species identification when facing challenging morphology-based specimen identifications. The use of DNA barcodes partially solves this problem, but in some cases when PCR is not an option (i.e., primers are not available, problems in reaction standardization), amplification-free approaches could be an optimal alternative. Recent advances in DNA sequencing, like the MinION device from Oxford Nanopore Technologies (ONT), allow to obtain genomic data with low laboratory and technical requirements, and at a relatively low cost. In this study, we explore ONT sequencing for molecular species identification from a total DNA sample obtained from a neotropical rodent and we also test the technology for complete mitochondrial genome reconstruction via genome skimming. We were able to obtain "de novo" the complete mitogenome of a specimen from the genus Melanomys (Cricetidae: Sigmodontinae) with average depth coverage of 78X using ONT-only data and by combining multiple assembly routines. Our pipeline for an automated species identification was able to identify the sample using unassembled sequence data (raw) in a reasonable computing time, which was substantially reduced when a priori information related to the organism identity was known. Our findings suggest ONT sequencing as a suitable candidate to solve species identification problems in metazoan nonmodel organisms and generate complete mtDNA datasets.

A DNA-of-things storage architecture to create materials with embedded memory

DNA storage offers substantial information density^1-7 and exceptional half-life³. We devised a 'DNA-of-things' (DoT) storage architecture to produce materials with immutable memory. In a DoT framework, DNA molecules record the data, and these molecules are then encapsulated in nanometer silica beads⁸, which are fused into various materials that are used to print or cast objects in any shape. First, we applied DoT to three-dimensionally print a Stanford Bunny⁹ that contained a 45 kB digital DNA blueprint for its synthesis. We synthesized five generations of the bunny, each from the memory of the previous generation without additional DNA synthesis or degradation of information. To test the scalability of DoT, we stored a 1.4 MB video in DNA in plexiglass spectacle lenses and retrieved it by excising a tiny piece of the plexiglass and sequencing the embedded DNA. DoT could be applied to store electronic health records in medical implants, to hide data in everyday objects (steganography) and to manufacture objects containing their own blueprint. It may also facilitate the development of self-replicating machines.

Next-Generation Sequencing Strategies

More than a decade ago, the term "next-generation" sequencing was coined to describe what was, at the time, revolutionary new methods to sequence RNA and DNA at a faster pace and cheaper cost than could be performed by standard bench-top protocols. Since then, the field of DNA sequencing has evolved at a rapid pace, with new breakthroughs allowing capacity to exponentially increase and cost to dramatically decrease. As genome-scale sequencing has become routine, a paradigm shift is occurring in genomics, which uses the power of high-throughput, rapid sequencing power with large-scale studies. These new approaches to genetic discovery will provide direct impact to fields such as personalized medicine, evolution, and biodiversity. This work reviews recent technology advances and methods in next-generation sequencing and highlights current large-scale sequencing efforts driving the evolution of the genomics space.

Non-invasive prenatal testing as a valuable source of population specific allelic frequencies

Low-coverage massively parallel genome sequencing for non-invasive prenatal testing (NIPT) of common aneuploidies is one of the most rapidly adopted and relatively low-cost DNA tests. Since aggregation of reads from a large number of samples allows overcoming the problems of extremely low coverage of individual samples, we describe the possible re-use of the data generated during NIPT testing for genome scale population specific frequency determination of small DNA variants, requiring no additional costs except of those for the NIPT test itself. We applied our method to a data set comprising of 1501 original NIPT test results and evaluated the findings on different levels, from in silico population frequency comparisons up to wet lab validation analyses using a gold-standard method based on Sanger sequencing. The revealed high reliability of variant calling and allelic frequency determinations suggest that these NIPT data could serve as valuable alternatives to large scale population studies even for smaller countries around the world.

On the critical evaluation and confirmation of germline sequence variants identified using massively parallel sequencing

Although massively parallel sequencing (MPS) is becoming common practice in both research and routine clinical care, confirmation requirements of identified DNA variants using alternative methods are still topics of debate. When evaluating variants directly from MPS data, different read depth statistics, together with specialized genotype quality scores are, therefore, of high relevance. Here we report results of our validation study performed in two different ways: 1) confirmation of MPS identified variants using Sanger sequencing; and 2) simultaneous Sanger and MPS analysis of exons of selected genes. Detailed examination of false-positive and false-negative findings revealed typical error sources connected to low read depth/coverage, incomplete reference genome, indel realignment problems, as well as microsatellite associated amplification errors leading to base miss-calling. However, all these error types were identifiable with thorough manual revision of aligned reads according to specific patterns of distributions of variants and their corresponding reads. Moreover, our results point to dependence of both basic quantitative metrics (such as total read counts, alternative allele read counts and allelic balance) together with specific genotype quality scores on the used bioinformatics pipeline, stressing thus the need for establishing of specific thresholds for these metrics in each laboratory and for each involved pipeline independently.

Long Range Sequencing and Validation of Insect Genome Assemblies

Advances in long read and long range sequencing technologies have enabled chromosome length resolution for de novo genome assemblies even in the absence of complementary resources such as physical maps. Herein, I introduce a few methods for quality control and discuss potential pitfalls when assembling insect genomes with long reads.

Network Analysis as a Grand Unifier in Biomedical Data Science

Biomedical data scientists study many types of networks, ranging from those formed by neurons to those created by molecular interactions. People often criticize these networks as uninterpretable diagrams termed hairballs; however, here we show that molecular biological networks can be interpreted in several straightforward ways. First, we can break down a network into smaller components, focusing on individual pathways and modules. Second, we can compute global statistics describing the network as a whole. Third, we can compare networks. These comparisons can be within the same context (e.g., between two gene regulatory networks) or cross-disciplinary (e.g., between regulatory networks and governmental hierarchies). The latter comparisons can transfer a formalism, such as that for Markov chains, from one context to another or relate our intuitions in a familiar setting (e.g., social networks) to the relatively unfamiliar molecular context. Finally, key aspects of molecular networks are dynamics and evolution, i.e., how they evolve over time and how genetic variants affect them. By studying the relationships between variants in networks, we can begin to interpret many common diseases, such as cancer and heart disease.

Comprehensive benchmarking and ensemble approaches for metagenomic classifiers

BACKGROUND

One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited.

RESULTS

In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages.

CONCLUSIONS

This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

Field-based species identification of closely-related plants using real-time nanopore sequencing

Advances in DNA sequencing and informatics have revolutionised biology over the past four decades, but technological limitations have left many applications unexplored. Recently, portable, real-time, nanopore sequencing (RTnS) has become available. This offers opportunities to rapidly collect and analyse genomic data anywhere. However, generation of datasets from large, complex genomes has been constrained to laboratories. The portability and long DNA sequences of RTnS offer great potential for field-based species identification, but the feasibility and accuracy of these technologies for this purpose have not been assessed. Here, we show that a field-based RTnS analysis of closely-related plant species (Arabidopsis spp.) has many advantages over laboratory-based high-throughput sequencing (HTS) methods for species level identification and phylogenomics. Samples were collected and sequenced in a single day by RTnS using a portable, “al fresco” laboratory. Our analyses demonstrate that correctly identifying unknown reads from matches to a reference database with RTnS reads enables rapid and confident species identification. Individually annotated RTnS reads can be used to infer the evolutionary relationships of A. thaliana. Furthermore, hybrid genome assembly with RTnS and HTS reads substantially improved upon a genome assembled from HTS reads alone. Field-based RTnS makes real-time, rapid specimen identification and genome wide analyses possible.

International Standards for Genomes, Transcriptomes, and Metagenomes

Challenges and biases in preparing, characterizing, and sequencing DNA and RNA can have significant impacts on research in genomics across all kingdoms of life, including experiments in single-cells, RNA profiling, and metagenomics (across multiple genomes). Technical artifacts and contamination can arise at each point of sample manipulation, extraction, sequencing, and analysis. Thus, the measurement and benchmarking of these potential sources of error are of paramount importance as next-generation sequencing (NGS) projects become more global and ubiquitous. Fortunately, a variety of methods, standards, and technologies have recently emerged that improve measurements in genomics and sequencing, from the initial input material to the computational pipelines that process and annotate the data. Here we review current standards and their applications in genomics, including whole genomes, transcriptomes, mixed genomic samples (metagenomes), and the modified bases within each (epigenomes and epitranscriptomes). These standards, tools, and metrics are critical for quantifying the accuracy of NGS methods, which will be essential for robust approaches in clinical genomics and precision medicine.

High Throughput Sequencing: An Overview of Sequencing Chemistry

In the present century sequencing is to the DNA science, what gel electrophoresis was to it in the last century. From 1977 to 2016 three generation of the sequencing technologies of various types have been developed. Second and third generation sequencing technologies referred commonly to as next generation sequencing technology, has evolved significantly with increase in sequencing speed, decrease in sequencing cost, since its inception in 2004. GS FLX by 454 Life Sciences/Roche diagnostics, Genome Analyzer, HiSeq, MiSeq and NextSeq by Illumina, Inc., SOLiD by ABI, Ion Torrent by Life Technologies are various type of the sequencing platforms available for second generation sequencing. The platforms available for the third generation sequencing are Helicos™ Genetic Analysis System by SeqLL, LLC, SMRT Sequencing by Pacific Biosciences, Nanopore sequencing by Oxford Nanopore's, Complete Genomics by Beijing Genomics Institute and GnuBIO by BioRad, to name few. The present article is an overview of the principle and the sequencing chemistry of these high throughput sequencing technologies along with brief comparison of various types of sequencing platforms available.

Linking genomics and population genetics with R

Population genetics and genomics have developed and been treated as independent fields of study despite having common roots. The continuous progress of sequencing technologies is contributing to (re-)connect these two disciplines. We review the challenges faced by data analysts and software developers when handling very big genetic data sets collected on many individuals. We then expose how r, as a computing language and development environment, proposes some solutions to meet these challenges. We focus on some specific issues that are often encountered in practice: handling and analysing single-nucleotide polymorphism data, handling and reading variant call format files, analysing haplotypes and linkage disequilibrium and performing multivariate analyses. We illustrate these implementations with some analyses of three recently published data sets that contain between 60 000 and 1 000 000 loci. We conclude with some perspectives on future developments of r software for population genomics.

On the study of microbial transcriptomes using second- and third-generation sequencing technologies

Second-generation sequencing technologies transformed the study of microbial transcriptomes. They helped reveal the transcription start sites and antisense transcripts of microbial species, improving the microbial genome annotation. Quantification of genome-wide gene expression levels allowed for functional studies of microbial research. Ever-evolving sequencing technologies are reshaping approaches to studying microbial transcriptomes. Recently, Oxford Nanopore Technologies delivered a sequencing platform called MinION, a third-generation sequencing technology, to the research community. We expect it to be the next sequencing technology that enables breakthroughs in life science fields. The studies of microbial transcriptomes will be no exception. In this paper, we review microbial transcriptomics studies using second- generation sequencing technology. We also discuss the prospect of microbial transcriptomics studies with thirdgeneration sequencing.

Embedded CMOS basecalling for nanopore DNA sequencing

DNA sequencing based on nanopore sensors is now entering the marketplace. The ability to interface this technology to established CMOS microelectronics promises significant improvements in functionality and miniaturization. Among the key functions to benefit from this interface will be basecalling, the conversion of raw electronic molecular signatures to nucleotide sequence predictions. This paper presents the design and performance potential of custom CMOS base-callers embedded alongside nanopore sensors. A basecalliing architecture implemented in 32-nm technology is discussed with the ability to process the equivalent of 20 human genomes per day in real-time at a power density of 5 W/cm2 assuming a 3-mer nanopore sensor.

Using mobile sequencers in an academic classroom

The advent of mobile DNA sequencers has made it possible to generate DNA sequencing data outside of laboratories and genome centers. Here, we report our experience of using the MinION, a mobile sequencer, in a 13-week academic course for undergraduate and graduate students. The course consisted of theoretical sessions that presented fundamental topics in genomics and several applied hackathon sessions. In these hackathons, the students used MinION sequencers to generate and analyze their own data and gain hands-on experience in the topics discussed in the theoretical classes. The manuscript describes the structure of our class, the educational material, and the lessons we learned in the process. We hope that the knowledge and material presented here will provide the community with useful tools to help educate future generations of genome scientists.

DOI:http://dx.doi.org/10.7554/eLife.14258.001

Investigation of various fluorescent protein–DNA binding peptides for effectively visualizing large DNA molecules

Single-molecule DNA visualization with fluorescent protein DNA binding peptides.