Capturing variation in metagenomic assembly graphs with MetaCortex.

MOTIVATION: The assembly of contiguous sequence from metagenomic samples presents a particular challenge, due to the presence of multiple species, often closely related, at varying levels of abundance. Capturing diversity within species, for example, viral haplotypes, or bacterial strain-level diversity, is even more challenging. RESULTS: We present MetaCortex, a metagenome assembler that captures intra-species diversity by searching for signatures of local variation along assembled sequences in the underlying assembly graph and outputting these sequences in sequence graph format. We show that MetaCortex produces accurate assemblies with higher genome coverage and contiguity than other popular metagenomic assemblers on mock viral communities with high levels of strain-level diversity and on simulated communities containing simulated strains. AVAILABILITY AND IMPLEMENTATION: Source code is freely available to download from https://github.com/SR-Martin/metacortex, is implemented in C and supported on MacOS and Linux. The version used for the results presented in this article is available at doi.org/10.5281/zenodo.7273627. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Plants, pollinators and their interactions under global ecological change: The role of pollen DNA metabarcoding.

Anthropogenic activities are triggering global changes in the environment, causing entire communities of plants, pollinators and their interactions to restructure, and ultimately leading to species declines. To understand the mechanisms behind community shifts and declines, as well as monitoring and managing impacts, a global effort must be made to characterize plant-pollinator communities in detail, across different habitat types, latitudes, elevations, and levels and types of disturbances. Generating data of this scale will only be feasible with rapid, high-throughput methods. Pollen DNA metabarcoding provides advantages in throughput, efficiency and taxonomic resolution over traditional methods, such as microscopic pollen identification and visual observation of plant-pollinator interactions. This makes it ideal for understanding complex ecological networks and their responses to change. Pollen DNA metabarcoding is currently being applied to assess plant-pollinator interactions, survey ecosystem change and model the spatiotemporal distribution of allergenic pollen. Where samples are available from past collections, pollen DNA metabarcoding has been used to compare contemporary and past ecosystems. New avenues of research are possible with the expansion of pollen DNA metabarcoding to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high-throughput methods such as pollen DNA metabarcoding are critical for understanding the evolutionary and ecological processes that support biodiversity, and predicting and responding to the impacts of change.

New approaches for metagenome assembly with short reads.

In recent years, the use of longer range read data combined with advances in assembly algorithms has stimulated big improvements in the contiguity and quality of genome assemblies. However, these advances have not directly transferred to metagenomic data sets, as assumptions made by the single genome assembly algorithms do not apply when assembling multiple genomes at varying levels of abundance. The development of dedicated assemblers for metagenomic data was a relatively late innovation and for many years, researchers had to make do using tools designed for single genomes. This has changed in the last few years and we have seen the emergence of a new type of tool built using different principles. In this review, we describe the challenges inherent in metagenomic assemblies and compare the different approaches taken by these novel assembly tools.

Methods of improving brain dose estimates for internally deposited radionuclides.

The US National Council on Radiation Protection and Measurements (NCRP) convened Scientific Committee 6-12 (SC 6-12) to examine methods for improving dose estimates for brain tissue for internally deposited radionuclides, with emphasis on alpha emitters. This Memorandum summarises the main findings of SC 6-12 described in the recently published NCRP Commentary No. 31, 'Development of Kinetic and Anatomical Models for Brain Dosimetry for Internally Deposited Radionuclides'. The Commentary examines the extent to which dose estimates for the brain could be improved through increased realism in the biokinetic and dosimetric models currently used in radiation protection and epidemiology. A limitation of most of the current element-specific systemic biokinetic models is the absence of brain as an explicitly identified source region with its unique rate(s) of exchange of the element with blood. The brain is usually included in a large source region calledOtherthat contains all tissues not considered major repositories for the element. In effect, all tissues inOtherare assigned a common set of exchange rates with blood. A limitation of current dosimetric models for internal emitters is that activity in the brain is treated as a well-mixed pool, although more sophisticated models allowing consideration of different activity concentrations in different regions of the brain have been proposed. Case studies for 18 internal emitters indicate that brain dose estimates using current dosimetric models may change substantially (by a factor of 5 or more), or may change only modestly, by addition of a sub-model of the brain in the biokinetic model, with transfer rates based on results of published biokinetic studies and autopsy data for the element of interest. As a starting place for improving brain dose estimates, development of biokinetic models with explicit sub-models of the brain (when sufficient biokinetic data are available) is underway for radionuclides frequently encountered in radiation epidemiology. A longer-term goal is development of coordinated biokinetic and dosimetric models that address the distribution of major radioelements among radiosensitive brain tissues.

Alvis: a tool for contig and read ALignment VISualisation and chimera detection.

BACKGROUND: The analysis of long reads or the assessment of assembly or target capture data often necessitates running alignments against reference genomes or gene sets. The aligner outputs are often parsed automatically by scripts, but many kinds of analysis can benefit from the understanding that can follow human inspection of individual alignments. Additionally, diagrams are a useful means of communicating assembly results to others. RESULTS: We developed Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in a variety of alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies. CONCLUSION: Alvis diagrams facilitate improved understanding of assembly quality, enable read coverage to be visualised and potential errors to be identified. Additionally, we found that splitting chimeric reads using the output provided by Alvis can improve the contiguity of assemblies, while maintaining correctness.

Biokinetic models for group IVB elements.

The International Commission on Radiological Protection (ICRP) is updating its biokinetic models in a series of reports titled Occupational Intakes of Radionuclides (OIR series). This paper provides an overview of biokinetic data for the group IVB elements hafnium (Hf) and titanium (Ti), compares these data with findings for the more extensively studied Group IVB element zirconium (Zr), and proposes biokinetic models for systemic Hf and Ti for use in the OIR series. The biokinetic model for systemic Zr adopted in OIR Part 2 (ICRP, 2016a) is proposed for application to Hf in view of the nearly identical chemical and physical properties of these two elements, their closely similar behavior in the environment, and their nearly identical biokinetic properties suggested by available comparative data. The model structure applied to Zr and Hf is also applied to Ti, but a separate set of transfer coefficients is proposed for Ti.

NanoOK: multi-reference alignment analysis of nanopore sequencing data, quality and error profiles.

MOTIVATION: The Oxford Nanopore MinION sequencer, currently in pre-release testing through the MinION Access Programme (MAP), promises long reads in real-time from an inexpensive, compact, USB device. Tools have been released to extract FASTA/Q from the MinION base calling output and to provide basic yield statistics. However, no single tool yet exists to provide comprehensive alignment-based quality control and error profile analysis--something that is extremely important given the speed with which the platform is evolving. RESULTS: NanoOK generates detailed tabular and graphical output plus an in-depth multi-page PDF report including error profile, quality and yield data. NanoOK is multi-reference, enabling detailed analysis of metagenomic or multiplexed samples. Four popular Nanopore aligners are supported and it is easily extensible to include others. AVAILABILITY AND IMPLEMENTATION: NanoOK is an open-source software, implemented in Java with supporting R scripts. It has been tested on Linux and Mac OS X and can be downloaded from https://github.com/TGAC/NanoOK. A VirtualBox VM containing all dependencies and the DH10B read set used in this article is available from http://opendata.tgac.ac.uk/nanook/. A Docker image is also available from Docker Hub--see program documentation https://documentation.tgac.ac.uk/display/NANOOK. CONTACT: richard.leggett@tgac.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A world of opportunities with nanopore sequencing.

Oxford Nanopore Technologies' MinION sequencer was launched in pre-release form in 2014 and represents an exciting new sequencing paradigm. The device offers multi-kilobase reads and a streamed mode of operation that allows processing of reads as they are generated. Crucially, it is an extremely compact device that is powered from the USB port of a laptop computer, enabling it to be taken out of the lab and facilitating previously impossible in-field sequencing experiments to be undertaken. Many of the initial publications concerning the platform focused on provision of tools to access and analyse the new sequence formats and then demonstrating the assembly of microbial genomes. More recently, as throughput and accuracy have increased, it has been possible to begin work involving more complex genomes and metagenomes. With the release of the high-throughput GridION X5 and PromethION platforms, the sequencing of large genomes will become more cost efficient, and enable the leveraging of extremely long (>100 kb) reads for resolution of complex genomic structures. This review provides a brief overview of nanopore sequencing technology, describes the growing range of nanopore bioinformatics tools, and highlights some of the most influential publications that have emerged over the last 2 years. Finally, we look to the future and the potential the platform has to disrupt work in human, microbiome, and plant genomics.

Imaging of compartmentalised intracellular nitric oxide, induced during bacterial phagocytosis, using a metalloprotein-gold nanoparticle conjugate.

Nitric oxide (NO) plays an essential role within the immune system since it is involved in the break-down of infectious agents such as viruses and bacteria. The ability to measure the presence of NO in the intracellular environment would provide a greater understanding of the pathophysiological mechanism of this important molecule. Here we report the detection of NO from the intracellular phagolysosome using a fluorescently tagged metalloprotein-gold nanoparticle conjugate. The metalloprotein cytochrome c, fluorescently tagged with an Alexa Fluor dye, was self-assembled onto gold nanoparticles to produce a NO specific nanobiosensor. Upon binding of NO, the cytochrome c protein changes conformation which induces an increase of fluorescence intensity of the tagged protein proportional to the NO concentration. The nanobiosensor was sensitive to NO in a reversible and selective manner, and exhibited a linear response at NO concentrations between 1 and 300 µM. In RAW264.7γ NO- macrophage cells, the nanobiosensor was used to detect the presence of NO that had been endogenously generated upon stimulation of the cells with interferon-γ and lipopolysaccharide, or spontaneously released following treatment of the cells with a NO donor. Significantly, the nanobiosensor was shown to be taken up by the macrophages within phagolysosomes, i.e., the precise location where the NO, together with other species, destroys bacterial infection. The nanobiosensor measured, for the first time, increasing concentrations of NO produced during combined stimulation and phagocytosis of Escherichia coli bacteria from within localised intracellular phagolysosomes, a key part of the immune system.

Coiled-coil protein Scy is a key component of a multiprotein assembly controlling polarized growth in Streptomyces.

Polarized growth in eukaryotes requires polar multiprotein complexes. Here, we establish that selection and maintenance of cell polarity for growth also requires a dedicated multiprotein assembly in the filamentous bacterium, Streptomyces coelicolor. We present evidence for a tip organizing center and confirm two of its main components: Scy (Streptomyces cytoskeletal element), a unique bacterial coiled-coil protein with an unusual repeat periodicity, and the known polarity determinant DivIVA. We also establish a link between the tip organizing center and the filament-forming protein FilP. Interestingly, both deletion and overproduction of Scy generated multiple polarity centers, suggesting a mechanism wherein Scy can both promote and limit the number of emerging polarity centers via the organization of the Scy-DivIVA assemblies. We propose that Scy is a molecular "assembler," which, by sequestering DivIVA, promotes the establishment of new polarity centers for de novo tip formation during branching, as well as supporting polarized growth at existing hyphal tips.

NextClip: an analysis and read preparation tool for Nextera Long Mate Pair libraries.

SUMMARY: Illumina's recently released Nextera Long Mate Pair (LMP) kit enables production of jumping libraries of up to 12 kb. The LMP libraries are an invaluable resource for carrying out complex assemblies and other downstream bioinformatics analyses such as the characterization of structural variants. However, LMP libraries are intrinsically noisy and to maximize their value, post-sequencing data analysis is required. Standardizing laboratory protocols and the selection of sequenced reads for downstream analysis are non-trivial tasks. NextClip is a tool for analyzing reads from LMP libraries, generating a comprehensive quality report and extracting good quality trimmed and deduplicated reads. AVAILABILITY AND IMPLEMENTATION: Source code, user guide and example data are available from https://github.com/richardmleggett/nextclip/.

Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations.

RenSeq is a NB-LRR (nucleotide binding-site leucine-rich repeat) gene-targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB-LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB-LRRs and can be accessed through a genome browser that we provide. We compared these NB-LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ~80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum 'Heinz 1706' extended the NB-LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co-segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi-ber2) and S. ruiz-ceballosii (Rpi-rzc1), we were able to apply RenSeq successfully to identify markers that co-segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy-to-adapt Galaxy pipelines.

Reference-free SNP detection: dealing with the data deluge.

Reference-free SNP detection, that is identifying SNPs between samples directly from comparison of primary sequencing data with other primary sequencing data and not to a pre-assembled reference genome is an emergent and potentially disruptive technology that is beginning to open up new vistas in variant identification that reveals new applications in non-model organisms and metagenomics. The modern, efficient data structures these tools use enables researchers with a reference sequence to sample many more individuals with lower computing storage and processing overhead. In this article we will discuss the technologies and tools implementing reference-free SNP detection and the potential impact on studies of genetic variation in model and non-model organisms, metagenomics and personal genomics and medicine.

Assemblathon 1: a competitive assessment of de novo short read assembly methods.

Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/.

Measuring air metagenomic diversity in an agricultural ecosystem.

All species shed DNA during life or in death, providing an opportunity to monitor biodiversity via environmental DNA (eDNA). In recent years, combining eDNA, high-throughput sequencing technologies, bioinformatics, and increasingly complete sequence databases has promised a non-invasive and non-destructive environmental monitoring tool. Modern agricultural systems are often large monocultures and so are highly vulnerable to disease outbreaks. Pest and pathogen monitoring in agricultural ecosystems is key for efficient and early disease prevention, lower pesticide use, and better food security. Although the air is rich in biodiversity, it has the lowest DNA concentration of all environmental media and yet is the route for windborne spread of many damaging crop pathogens. Our work suggests that ecosystems can be monitored efficiently using airborne nucleic acid information. Here, we show that the airborne DNA of microbes can be recovered, shotgun sequenced, and taxonomically classified, including down to the species level. We show that by monitoring a field growing key crops we can identify the presence of agriculturally significant pathogens and quantify their changing abundance over a period of 1.5 months, often correlating with weather variables. We add to the evidence that aerial eDNA can be used as a source for biomonitoring in terrestrial ecosystems, specifically highlighting agriculturally relevant species and how pathogen levels correlate with weather conditions. Our ability to detect dynamically changing levels of species and strains highlights the value of airborne eDNA in agriculture, monitoring biodiversity changes, and tracking taxa of interest.

Third mortality follow-up of the Mallinckrodt uranium processing workers, 1942-2019.

INTRODUCTION: Mallinckrodt Chemical Works was a uranium processing facility during the Manhattan Project from 1942 to 1966. Thousands of workers were exposed to low-dose-rates of ionizing radiation from external and internal sources. This third follow-up of 2514 White male employees updates cancer and noncancer mortality potentially associated with radiation and silica dust. MATERIALS AND METHODS: Individual, annualized organ doses were estimated from film badge records (n monitored = 2514), occupational chest x-rays (n = 2514), uranium urinalysis (n = 1868), radium intake through radon breath measurements (n = 487), and radon ambient measurements (n = 1356). Silica dust exposure from pitchblende processing was estimated (n = 1317). Vital status and cause of death determination through 2019 relied upon the National Death Index and Social Security Administration Epidemiological Vital Status Service. The analysis included standardized mortality ratios (SMRs), Cox proportional hazards, and Poisson regression models. RESULTS: Vital status was confirmed for 99.4% of workers (84.0% deceased). For a dose weighting factor of 1 for intakes of uranium, radium, and radon decay products, the mean and median lung doses were 65.6 and 29.9 mGy, respectively. SMRs indicated a difference in health outcomes between salaried and hourly workers, and more brain cancer deaths than expected [SMR: 1.79; 95% confidence interval (CI): 1.14, 2.70]. No association was seen between radiation and lung cancer [hazard ratio (HR) at 100 mGy: 0.93; 95%CI: 0.78, 1.11]. The relationship between radiation and kidney cancer observed in the previous follow-up was maintained (HR at 100 mGy: 2.07; 95%CI: 1.12, 3.79). Cardiovascular disease (CVD) also increased significantly with heart dose (HR at 100 mGy: 1.11; 95%CI: 1.02, 1.21). Exposures to dust ≥23.6 mg/m3-year were associated with nonmalignant kidney disease (NMKD) (HR: 3.02; 95%CI: 1.12, 8.16) and kidney cancer combined with NMKD (HR: 2.46; 95%CI: 1.04, 5.81), though without evidence of a dose-response per 100 mg/m3-year. CONCLUSIONS: This third follow-up of Mallinckrodt uranium processors reinforced the results of the previous studies. There was an excess of brain cancers compared with the US population, although no radiation dose-response was detected. The association between radiation and kidney cancer remained, though potentially due to few cases at higher doses. The association between levels of silica dust ≥23.6 mg/m3-year and NMKD also remained. No association was observed between radiation and lung cancer. A positive dose-response was observed between radiation and CVD; however, this association may be confounded by smoking, which was unmeasured. Future work will pool these data with other uranium processing worker cohorts within the Million Person Study.

A Million Person Study Innovation: Evaluating Cognitive Impairment and other Morbidity Outcomes from Chronic Radiation Exposure Through Linkages with the Centers for Medicaid and Medicare Services Assessment and Claims Data.

The study of One Million U.S. Radiation Workers and Veterans, the Million Person Study (MPS), examines the health consequences, both cancer and non-cancer, of exposure to ionizing radiation received gradually over time. Recently the MPS has focused on mortality patterns from neurological and behavioral conditions, e.g., Parkinson's disease, Alzheimer's disease, dementia, and motor neuron disease such as amyotrophic lateral sclerosis. A fuller picture of radiation-related late effects comes from studying both mortality and the occurrence (incidence) of conditions not leading to death. Accordingly, the MPS is identifying neurocognitive diagnoses from fee-for-service insurance claims from the Centers for Medicare and Medicaid Services (CMS), among Medicare beneficiaries beginning in 1999 (the earliest date claims data are available). Linkages to date have identified ∼540,000 workers with available health information. Such linkages provide individual information on important co-factor and confounding variables such as smoking, alcohol consumption, blood pressure, obesity, diabetes and many other health and demographic characteristics. The total person-level set of time-dependent variables, outcomes, organ-specific dose measures, co-factors, and demographics will be massive and much too large to be evaluated with standard software. Thus, development of specialized open-source software designed for large datasets (Colossus) is nearly complete. The wealth of information available from CMS claims data, coupled with individual dose reconstructions, will thus greatly enhance the quality and precision of health evaluations for this new field of low-dose radiation and neurocognitive effects.

Dataset of 143 metagenome-assembled genomes from the Arctic and Atlantic Oceans, including 21 for eukaryotic organisms.

This article presents metagenome-assembled genomes (MAGs) for both eukaryotic and prokaryotic organisms originating from the Arctic and Atlantic oceans, along with gene prediction and functional annotation for MAGs from both domains. Eleven samples from the chlorophyll-a maximum layer of the surface ocean were collected during two cruises in 2012; six from the Arctic in June-July on ARK-XXVII/1 (PS80), and five from the Atlantic in November on ANT-XXIX/1 (PS81). Sequencing and assembly was carried out by the Joint Genome Institute (JGI), who provide annotation of the assembled sequences, and 122 MAGs for prokaryotic organisms. A subsequent binning process identified 21 MAGs for eukaryotic organisms, mostly identified as Mamiellophyceae or Bacillariophyceae. The data for each MAG includes sequences in FASTA format, and tables of functional annotation of genes. For eukaryotic MAGs, transcript and protein sequences for predicted genes are available. A spreadsheet is provided summarising quality measures and taxonomic classifications for each MAG. These data provide draft genomes for uncultured marine microbes, including some of the first MAGs for polar eukaryotes, and can provide reference genetic data for these environments, or used in genomics-based comparison between environments.

Mortality among Tennessee Eastman Corporation (TEC) uranium processing workers, 1943-2019.

BACKGROUND: There are few occupational studies of women exposed to ionizing radiation. During World War II, the Tennessee Eastman Corporation (TEC) operated an electromagnetic field separation facility of 1152 calutrons to obtain enriched uranium (235U) used for the Hiroshima atomic bomb. Thousands of women were involved in these operations. MATERIALS AND METHODS: A new study was conducted of 13,951 women and 12,699 men employed at TEC between 1943 and 1947 for at least 90 days. Comprehensive dose reconstruction techniques were used to estimate lung doses from the inhalation of uranium dust based on airborne measurements. Vital status through 2018/2019 was obtained from the National Death Index, Social Security Death Index, Tennessee death records and online public record databases. Analyses included standardized mortality ratios (SMRs) and Cox proportional hazards models. RESULTS: Most workers were hourly (77.7%), white (95.6%), born before 1920 (58.3%), worked in dusty environments (57.0%), and had died (94.9%). Vital status was confirmed for 97.4% of the workers. Women were younger than men when first employed: mean ages 25.0 years and 33.0 years, respectively. The estimated mean absorbed dose to the lung was 32.7 mGy (max 1048 mGy) for women and 18.9 mGy (max 501 mGy) for men. The mean dose to thoracic lymph nodes (TLNs) was 127 mGy. Statistically significant SMRs were observed for lung cancer (SMR 1.25; 95% CI 1.19, 1.31; n = 1654), nonmalignant respiratory diseases (NMRDs) (1.23; 95% CI 1.19, 1.28; n = 2585), and cerebrovascular disease (CeVD) (1.13; 95% CI 1.08, 1.18; n = 1945). For lung cancer, the excess relative rate (ERR) at 100 mGy (95% CI) was 0.01 (-0.10, 0.12; n = 652) among women, and -0.15 (-0.38, 0.07; n = 1002) among men based on a preferred model for men with lung doses <300 mGy. NMRD and non-Hodgkin lymphoma were not associated with estimated absorbed dose to the lung or TLN. CONCLUSIONS: There was little evidence that radiation increased the risk of lung cancer, suggesting that inhalation of uranium dust and the associated high-LET alpha particle exposure to lung tissue experienced over a few years is less effective in causing lung cancer than other types of exposures. There was no statistically significant difference in the lung cancer risk estimates between men and women. The elevation of certain causes of death such as CeVD is unexplained and will require additional scrutiny of workplace or lifestyle factors given that radiation is an unlikely contributor since only the lung and lymph nodes received appreciable dose.