Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples

A New Age in Molecular Diagnostics for Invasive Fungal Disease: Are We Ready?

Invasive fungal diseases (IFDs) present an increasing global burden in immunocompromised and other seriously ill populations, including those caused by pathogens which are inherently resistant or less susceptible to antifungal drugs. Early diagnosis encompassing accurate detection and identification of the causative agent and of antifungal resistance is critical for optimum patient outcomes. Many molecular-based diagnostic approaches have good clinical utility although interpretation of results should be according to clinical context. Where an IFD is in the differential diagnosis, panfungal PCR assays allow the rapid detection/identification of fungal species directly from clinical specimens with good specificity; sensitivity is also high when hyphae are seen in the specimen including in paraffin-embedded tissue. Aspergillus PCR assays on blood fractions have good utility in the screening of high risk hematology patients with high negative predictive value (NPV) and positive predictive value (PPV) of 94 and 70%, respectively, when two positive PCR results are obtained. The standardization, and commercialization of Aspergillus PCR assays has now enabled direct comparison of results between laboratories with commercial assays also offering the simultaneous detection of common azole resistance mutations. Candida PCR assays are not as well standardized with the only FDA-approved commercial system (T2Candida) detecting only the five most common species; while the T2Candida outperforms blood culture in patients with candidemia, its role in routine Candida diagnostics is not well defined. There is growing use of Mucorales-specific PCR assays to detect selected genera in blood fractions. Quantitative real-time Pneumocystis jirovecii PCRs have replaced microscopy and immunofluorescent stains in many diagnostic laboratories although distinguishing infection may be problematic in non-HIV-infected patients. For species identification of isolates, DNA barcoding with dual loci (ITS and TEF1α) offer optimal accuracy while next generation sequencing (NGS) technologies offer highly discriminatory analysis of genetic diversity including for outbreak investigation and for drug resistance characterization. Advances in molecular technologies will further enhance routine fungal diagnostics.

Metagenomic sequencing with spiked primer enrichment for viral diagnostics and genomic surveillance

Metagenomic next-generation sequencing (mNGS), the shotgun sequencing of RNA and DNA from clinical samples, has proved useful for broad-spectrum pathogen detection and the genomic surveillance of viral outbreaks. An additional target enrichment step is generally needed for high-sensitivity pathogen identification in low-titre infections, yet available methods using PCR or capture probes can be limited by high cost, narrow scope of detection, lengthy protocols and/or cross-contamination. Here, we developed metagenomic sequencing with spiked primer enrichment (MSSPE), a method for enriching targeted RNA viral sequences while simultaneously retaining metagenomic sensitivity for other pathogens. We evaluated MSSPE for 14 different viruses, yielding a median tenfold enrichment and mean 47% (±16%) increase in the breadth of genome coverage over mNGS alone. Virus detection using MSSPE arboviral or haemorrhagic fever viral panels was comparable in sensitivity to specific PCR, demonstrating 95% accuracy for the detection of Zika, Ebola, dengue, chikungunya and yellow fever viruses in plasma samples from infected patients. Notably, sequences from re-emerging and/or co-infecting viruses that have not been specifically targeted a priori, including Powassan and Usutu, were successfully enriched using MSSPE. MSSPE is simple, low cost, fast and deployable on either benchtop or portable nanopore sequencers, making this method directly applicable for diagnostic laboratory and field use.

This study describes a new method that improves the sensitivity of viral detection compared with next-generation sequencing and enables the detection of emerging flaviviruses not specifically targeted a priori. Metagenomic sequencing with spiked primer enrichment is simple, low cost, fast and deployable on either benchtop or portable nanopore sequencers, making it applicable for diagnostic laboratory and field use.

Evaluation of a portable nanopore-based sequencer for detection of viruses in water

The newly emerged nanopore sequencing technology such as MinION™ allows for real-time detection of long DNA/RNA fragments on a portable device, yet few have examined its performance for environmental viromes. Here we seeded one RNA virus bacteriophage MS2 and one DNA virus bacteriophage PhiX174 into 10 L well water at three levels ranging from 1 to 21,100 plaque-forming units (PFU)/mL. Two workflows were established to maximize the number of sequencing reads of RNA and DNA viruses using MinION™. With dead-end ultrafiltration, PEG precipitation, and random amplification, MinION™ was capable of detecting MS2 at 155 PFU/mL and PhiX174 at 1-2 PFU/mL. While the DNA workflow only detected PhiX174, the RNA workflow detected both MS2 and PhiX174. The virus concentration, or relative abundance of viral nucleic acids in total nucleic acids, is critical to the proportion of viral reads in sequencing results. Our findings also highlight the importance of including control samples in sequencing runs for environmental water samples with low virus abundance.

MinION sequencing of Streptococcus suis allows for functional characterization of bacteria by multilocus sequence typing and antimicrobial resistance profiling

In recent years, high-throughput sequencing has revolutionized disease diagnosis by its powerful ability to provide high resolution genomic information. The Oxford Nanopore MinION sequencer has unparalleled potential as a rapid disease diagnostic tool due to its high mobility, accessibility, and short turnaround time. However, there is a lack of rigorous quality assessment and control processes standardizing the testing on the MinION, which is necessary for incorporation into a diagnostic workflow. Thus, our study examined the use of the MinION sequencer for bacterial whole genome generation and characterization. Using Streptococcus suis as a model, we optimized DNA isolation and treatments to be used for MinION sequencing and standardized de novo assembly to quickly generate a full-length consensus sequence achieving a 99.4% average accuracy. The consensus genomes from MinION sequencing were able to accurately predict the multilocus sequence type in 8 out of 10 samples and identified antimicrobial resistance profiles for 100% of the samples, despite the concern of a high error rate. The inability to unequivocally predict sequence types was due to difficulty in differentiating high identity alleles, which was overcome by applying additional error correction methods to increase consensus accuracy. This manuscript provides methods for the use of MinION sequencing for identification of S. suis genome sequence, sequence type, and antibiotic resistance profile that can be used as a framework for identification and classification of other pathogens.

Contaminations in (meta)genome data: An open issue for the scientific community

In recent years, the high throughput and the low cost of next-generation sequencing (NGS) technologies have led to an increase of the amount of (meta)genomic data, revolutionizing genomic research studies. However, the quality of sequencing data could be affected by experimental errors derived from defective methods and protocols. This represents a serious problem for the scientific community with a negative impact on the correctness of studies that involve genomic sequence analysis. As a countermeasure, several alignment and taxonomic classification tools have been developed to uncover and correct errors. In this critical review some of these integrated software tools and pipelines used to detect contaminations in reference genome databases and sequenced samples are reported. In particular, case studies of bacterial contaminations, contaminations of human origin, mitochondrial contaminations of ancient DNA, and cross contaminations are examined.

Comparative analysis of small RNAs released by the filarial nematode Litomosoides sigmodontis in vitro and in vivo

Background

The release of small non-coding RNAs (sRNAs) has been reported in parasitic nematodes, trematodes and cestodes of medical and veterinary importance. However, little is known regarding the diversity and composition of sRNAs released by different lifecycle stages and the portion of sRNAs that persist in host tissues during filarial infection. This information is relevant to understanding potential roles of sRNAs in parasite-to-host communication, as well as to inform on the location within the host and time point at which they can be detected.

Methodology and principal findings

We have used small RNA (sRNA) sequencing analysis to identify sRNAs in replicate samples of the excretory-secretory (ES) products of developmental stages of the filarial nematode Litomosoides sigmodontis in vitro and compare this to the parasite-derived sRNA detected in host tissues. We show that all L. sigmodontis developmental stages release RNAs in vitro, including ribosomal RNA fragments, 5’-derived tRNA fragments (5’-tRFs) and, to a lesser extent, microRNAs (miRNAs). The gravid adult females (gAF) produce the largest diversity and abundance of miRNAs in the ES compared to the adult males or microfilariae. Analysis of sRNAs detected in serum and macrophages from infected animals reveals that parasite miRNAs are preferentially detected in vivo, compared to their low levels in the ES products, and identifies miR-92-3p and miR-71-5p as L. sigmodontis miRNAs that are stably detected in host cells in vivo.

Conclusions

Our results suggest that gravid adult female worms secrete the largest diversity of extracellular sRNAs compared to adult males or microfilariae. We further show differences in the parasite sRNA biotype distribution detected in vitro versus in vivo. We identify macrophages as one reservoir for parasite sRNA during infection, and confirm the presence of parasite miRNAs and tRNAs in host serum during patent infection.

Lymphatic and visceral filariasis, as well as loiasis and onchocerciasis, are parasitic infections caused by filarial nematodes that can cause extensive and diverse clinical manifestations, including edemas of the lower limbs and visual impairment. These parasites successfully maintain a crosstalk with the immune system of their host and one potential mediator of this communication is extracellular small non-coding RNAs (sRNAs) released by the parasite. However, little is known of the mechanisms of sRNA export, how the exported sRNAs differ between lifecycle stages, and how the parasite microenvironment (e.g. in vitro vs. in vivo) contributes to the composition of sRNAs that can be detected. In this report, we show that all the developmental stages of the filarial parasite Litomosoides sigmodontis release sRNAs, which include tRNA fragments and miRNAs, in vitro. A subset of the miRNAs are differentially represented in the ES products between adult stages (males and gravid females) and larval stages (microfilariae) in vitro, however all of the miRNAs detected in serum or macrophages in vivo are present in the ES from all life stages. We show that the parasite-derived miRNAs are protected from degradation in vitro and are stable in vivo, as they are readily detectable in the serum of infected jirds. Several parasite miRNAs are also detected within macrophages purified from infected hosts, consistent with parasite RNAs having a yet unidentified functional role in host cells.

GenBank is a reliable resource for 21st century biodiversity research

Traditional methods of characterizing biodiversity are increasingly being supplemented and replaced by approaches based on DNA sequencing alone. These approaches commonly involve extraction and high-throughput sequencing of bulk samples from biologically complex communities or samples of environmental DNA (eDNA). In such cases, vouchers for individual organisms are rarely obtained, often unidentifiable, or unavailable. Thus, identifying these sequences typically relies on comparisons with sequences from genetic databases, particularly GenBank. While concerns have been raised about biases and inaccuracies in laboratory and analytical methods, comparatively little attention has been paid to the taxonomic reliability of GenBank itself. Here we analyze the metazoan mitochondrial sequences of GenBank using a combination of distance-based clustering and phylogenetic analysis. Because of their comparatively rapid evolutionary rates and consequent high taxonomic resolution, mitochondrial sequences represent an invaluable resource for the detection of the many small and often undescribed organisms that represent the bulk of animal diversity. We show that metazoan identifications in GenBank are surprisingly accurate, even at low taxonomic levels (likely <1% error rate at the genus level). This stands in contrast to previously voiced concerns based on limited analyses of particular groups and the fact that individual researchers currently submit annotated sequences to GenBank without significant external taxonomic validation. Our encouraging results suggest that the rapid uptake of DNA-based approaches is supported by a bioinformatic infrastructure capable of assessing both the losses to biodiversity caused by global change and the effectiveness of conservation efforts aimed at slowing or reversing these losses.

Draft Genome Sequence of Microbacterium sp. Gd 4-13, Isolated from Gydanskiy Peninsula Permafrost Sediments of Marine Origin

Here, we report the draft genome sequence of Microbacterium sp. strain Gd 4-13, isolated from late Pleistocene permafrost of marine origin located on the Gydanskiy Peninsula. Genome sequence analysis was performed to understand strain survivability mechanisms under permafrost conditions and to expand biotechnology applications.

Here, we report the draft genome sequence of Microbacterium sp. strain Gd 4-13, isolated from late Pleistocene permafrost of marine origin located on the Gydanskiy Peninsula. Genome sequence analysis was performed to understand strain survivability mechanisms under permafrost conditions and to expand biotechnology applications.

Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples

Dysbiotic configurations of the human gut microbiota have been linked to colorectal cancer (CRC). Human small noncoding RNAs are also implicated in CRC, and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis, but their role has been less extensively explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens from patients with CRC or with adenomas and from healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We observed considerable overlap and a correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. We identified a combined predictive signature composed of 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC samples separately from healthy and adenoma samples (area under the curve [AUC] = 0.87). In the present study, we report evidence that host-microbiome dysbiosis in CRC can also be observed by examination of altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more-accurate tools for diagnostic purposes.IMPORTANCE The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

A systematic sequencing-based approach for microbial contaminant detection and functional inference

BACKGROUND

Microbial contamination poses a major difficulty for successful data analysis in biological and biomedical research. Computational approaches utilizing next-generation sequencing (NGS) data offer promising diagnostics to assess the presence of contaminants. However, as host cells are often contaminated by multiple microorganisms, these approaches require careful attention to intra- and interspecies sequence similarities, which have not yet been fully addressed.

RESULTS

We present a computational approach that rigorously investigates the genomic origins of sequenced reads, including those mapped to multiple species that have been discarded in previous studies. Through the analysis of large-scale synthetic and public NGS samples, we estimate that 1000-100,000 contaminating microbial reads are detected per million host reads sequenced by RNA-seq. The microbe catalog we established included Cutibacterium as a prevalent contaminant, suggesting that contamination mostly originates from the laboratory environment. Importantly, by applying a systematic method to infer the functional impact of contamination, we revealed that host-contaminant interactions cause profound changes in the host molecular landscapes, as exemplified by changes in inflammatory and apoptotic pathways during Mycoplasma infection of lymphoma cells.

CONCLUSIONS

We provide a computational method for profiling microbial contamination on NGS data and suggest that sources of contamination in laboratory reagents and the experimental environment alter the molecular landscape of host cells leading to phenotypic changes. These findings reinforce the concept that precise determination of the origins and functional impacts of contamination is imperative for quality research and illustrate the usefulness of the proposed approach to comprehensively characterize contamination landscapes.

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities - a proof of concept under laboratory conditions

High-throughput sequencing (HTS) enables the generation of large amounts of genome sequence data at a reasonable cost. Organisms in mixed microbial communities can now be sequenced and identified in a culture-independent way, usually using amplicon sequencing of a DNA barcode. Bulk RNA-seq (metatranscriptomics) has several advantages over DNA-based amplicon sequencing: it is less susceptible to amplification biases, it captures only living organisms, and it enables a larger set of genes to be used for taxonomic identification. Using a model mock community comprising 17 fungal isolates, we evaluated whether metatranscriptomics can accurately identify fungal species and subspecies in mixed communities. Overall, 72.9% of the RNA transcripts were classified, from which the vast majority (99.5%) were correctly identified at the species level. Of the 15 species sequenced, 13 were retrieved and identified correctly. We also detected strain-level variation within the Cryptococcus species complexes: 99.3% of transcripts assigned to Cryptococcus were classified as one of the four strains used in the mock community. Laboratory contaminants and/or misclassifications were diverse, but represented only 0.44% of the transcripts. Hence, these results show that it is possible to obtain accurate species- and strain-level fungal identification from metatranscriptome data as long as taxa identified at low abundance are discarded to avoid false-positives derived from contamination or misclassifications. This study highlights both the advantages and current challenges in the application of metatranscriptomics in clinical mycology and ecological studies.

High-Throughput Sequence Analysis of Peripheral T-Cell Lymphomas Indicates Subtype-Specific Viral Gene Expression Patterns and Immune Cell Microenvironments

Certain peripheral T-cell lymphomas (PTCLs) have been associated with viral infection, particularly infection with Epstein-Barr virus (EBV). However, a comprehensive virome analysis across PTCLs has not previously been reported. Here we utilized published whole-transcriptome RNA sequencing (RNA-seq) data sets from seven different PTCL studies and new RNA-seq data from our laboratory to screen for virus association, to analyze viral gene expression, and to assess B- and T-cell receptor diversity paradigms across PTCL subtypes. In addition to identifying EBV in angioimmunoblastic T-cell lymphoma (AITL) and extranodal NK/T-cell lymphoma (ENKTL), two PTCL subtypes with well-established EBV associations, we also detected EBV in several cases of anaplastic large-cell lymphoma (ALCL), and we found evidence of infection by the oncogenic viruses Kaposi's sarcoma-associated herpesvirus and human T-cell leukemia virus type 1 in isolated PTCL cases. In AITLs, EBV gene expression analysis showed expression of immediate early, early, and late lytic genes, suggesting either low-level lytic gene expression or productive infection in a subset of EBV-infected B-lymphocyte stromal cells. Deconvolution of immune cell subpopulations demonstrated a greater B-cell signal in AITLs than in other PTCL subtypes, consistent with a larger role for B-cell support in the pathogenesis of AITL. Reconstructed T-cell receptor (TCR) and B-cell receptor (BCR) repertoires demonstrated increased BCR diversity in AITLs, consistent with a possible EBV-driven polyclonal response. These findings indicate potential alternative roles for EBV in PTCLs, in addition to the canonical oncogenic mechanisms associated with EBV latent infection. Our findings also suggest the involvement of other viruses in PTCL pathogenesis and demonstrate immunological alterations associated with these cancers.IMPORTANCE In this study, we utilized next-generation sequencing data from 7 different studies of peripheral T-cell lymphoma (PTCL) patient samples to globally assess viral associations, provide insights into the contributions of EBV gene expression to the tumor phenotype, and assess the unique roles of EBV in modulating the immune cell tumor microenvironment. These studies revealed potential roles for EBV replication genes in some PTCL subtypes, the possible role of additional human tumor viruses in rare cases of PTCLs, and a role for EBV in providing a unique immune microenvironmental niche in one subtype of PTCLs. Together, these studies provide new insights into the understudied role of tumor viruses in PTCLs.

Using QC-Blind for Quality Control and Contamination Screening of Bacteria DNA Sequencing Data Without Reference Genome

Quality control for next generation sequencing (NGS) has become increasingly important with the ever increasing importance of sequencing data for omics studies. Tools have been developed for filtering possible contaminants from species with known reference genome. Unfortunately, reference genomes for all the species involved, including the contaminants, are required for these tools to work. This precludes many real-life samples that have no information about the complete genome of the target species, and are contaminated with unknown microbial species. In this work we proposed QC-Blind, a novel quality control pipeline for removing contaminants without any use of reference genomes. The pipeline merely requires the information about a few marker genes of the target species. The entire pipeline consists of unsupervised read assembly, contig binning, read clustering, and marker gene assignment. When evaluated on in silico, ab initio and in vivo datasets, QC-Blind proved effective in removing unknown contaminants with high specificity and accuracy, while preserving most of the genomic information of the target bacterial species. Therefore, QC-Blind could serve well in situations where limited information is available for both target and contamination species.

Clinical metagenomics

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health.

Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid

Metagenomic next-generation sequencing (mNGS) for pan-pathogen detection has been successfully tested in proof-of-concept case studies in patients with acute illness of unknown etiology but to date has been largely confined to research settings. Here, we developed and validated a clinical mNGS assay for diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF) in a licensed microbiology laboratory. A customized bioinformatics pipeline, SURPI+, was developed to rapidly analyze mNGS data, generate an automated summary of detected pathogens, and provide a graphical user interface for evaluating and interpreting results. We established quality metrics, threshold values, and limits of detection of 0.2-313 genomic copies or colony forming units per milliliter for each representative organism type. Gross hemolysis and excess host nucleic acid reduced assay sensitivity; however, spiked phages used as internal controls were reliable indicators of sensitivity loss. Diagnostic test accuracy was evaluated by blinded mNGS testing of 95 patient samples, revealing 73% sensitivity and 99% specificity compared to original clinical test results, and 81% positive percent agreement and 99% negative percent agreement after discrepancy analysis. Subsequent mNGS challenge testing of 20 positive CSF samples prospectively collected from a cohort of pediatric patients hospitalized with meningitis, encephalitis, and/or myelitis showed 92% sensitivity and 96% specificity relative to conventional microbiological testing of CSF in identifying the causative pathogen. These results demonstrate the analytic performance of a laboratory-validated mNGS assay for pan-pathogen detection, to be used clinically for diagnosis of neurological infections from CSF.

From trash to treasure: detecting unexpected contamination in unmapped NGS data

Background

Next Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This ’misalignment’ can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Investigating the source of the unmapped reads is definitely important to better assess the quality of the whole experiment and to check for possible downstream or upstream ’contamination’ from exogenous nucleic acids.

Results

Here we propose DecontaMiner, a tool to unravel the presence of contaminating sequences among the unmapped reads. It uses a subtraction approach to identify bacteria, fungi and viruses genome contamination. DecontaMiner generates several output files to track all the processed reads, and to provide a complete report of their characteristics. The good quality matches on microorganism genomes are counted and compared among samples. DecontaMiner builds an offline HTML page containing summary statistics and plots. The latter are obtained using the state-of-the-art D3 javascript libraries. DecontaMiner has been mainly used to detect contamination in human RNA-Seq data. The software is freely available at http://www-labgtp.na.icar.cnr.it/decontaminer.

Conclusions

DecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2684-x) contains supplementary material, which is available to authorized users.

Defending Our Public Biological Databases as a Global Critical Infrastructure

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world's primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly "retrofitted" mitigations. This Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

A virome-wide clonal integration analysis platform for discovering cancer viral etiology

Oncoviral infection is responsible for 12%–15% of cancer in humans. Convergent evidence from epidemiology, pathology, and oncology suggests that new viral etiologies for cancers remain to be discovered. Oncoviral profiles can be obtained from cancer genome sequencing data; however, widespread viral sequence contamination and noncausal viruses complicate the process of identifying genuine oncoviruses. Here, we propose a novel strategy to address these challenges by performing virome-wide screening of early-stage clonal viral integrations. To implement this strategy, we developed VIcaller, a novel platform for identifying viral integrations that are derived from any characterized viruses and shared by a large proportion of tumor cells using whole-genome sequencing (WGS) data. The sensitivity and precision were confirmed with simulated and benchmark cancer data sets. By applying this platform to cancer WGS data sets with proven or speculated viral etiology, we newly identified or confirmed clonal integrations of hepatitis B virus (HBV), human papillomavirus (HPV), Epstein-Barr virus (EBV), and BK Virus (BKV), suggesting the involvement of these viruses in early stages of tumorigenesis in affected tumors, such as HBV in TERT and KMT2B (also known as MLL4) gene loci in liver cancer, HPV and BKV in bladder cancer, and EBV in non-Hodgkin's lymphoma. We also showed the capacity of VIcaller to identify integrations from some uncharacterized viruses. This is the first study to systematically investigate the strategy and method of virome-wide screening of clonal integrations to identify oncoviruses. Searching clonal viral integrations with our platform has the capacity to identify virus-caused cancers and discover cancer viral etiologies.

Plasmid DNA contaminant in molecular reagents

Background noise in metagenomic studies is often of high importance and its removal requires extensive post-analytic, bioinformatics filtering. This is relevant as significant signals may be lost due to a low signal-to-noise ratio. The presence of plasmid residues, that are frequently present in reagents as contaminants, has not been investigated so far, but may pose a substantial bias. Here we show that plasmid sequences from different sources are omnipresent in molecular biology reagents. Using a metagenomic approach, we identified the presence of the (pol) of equine infectious anemia virus in human samples and traced it back to the expression plasmid used for generation of a commercial reverse transcriptase. We found fragments of multiple other expression plasmids in human samples as well as commercial polymerase preparations. Plasmid contamination sources included production chain of molecular biology reagents as well as contamination of reagents from environment or human handling of samples and reagents. Retrospective analyses of published metagenomic studies revealed an inaccurate signal-to-noise differentiation. Hence, the plasmid sequences that seem to be omnipresent in molecular biology reagents may misguide conclusions derived from genomic/metagenomics datasets and thus also clinical interpretations. Critical appraisal of metagenomic data sets for the possibility of plasmid background noise is required to identify reliable and significant signals.

Screening human cell lines for viral infections applying RNA-Seq data analysis

Monitoring viral infections of cell cultures is largely neglected although the viruses may have an impact on the physiology of cells and may constitute a biohazard regarding laboratory safety and safety of bioactive agents produced by cell cultures. PCR, immunological assays, and enzyme activity tests represent common methods to detect virus infections. We have screened more than 300 Cancer Cell Line Encyclopedia RNA sequencing and 60 whole exome sequencing human cell lines data sets for specific viral sequences and general viral nucleotide and protein sequence assessment applying the Taxonomer bioinformatics tool developed by IDbyDNA. The results were compared with our previous findings from virus specific PCR analyses. Both, the results obtained from the direct alignment method and the Taxonomer alignment method revealed a complete concordance with the PCR results: twenty cell lines were found to be infected with five virus species. Taxonomer further uncovered a bovine polyomavirus infection in the breast cancer cell line SK-BR-3 most likely introduced by contaminated fetal bovine serum. RNA-Seq data sets were more sensitive for virus detection although a significant proportion of cell lines revealed low numbers of virus specific alignments attributable to low level nucleotide contamination during RNA preparation or sequencing procedure. Low quality reads leading to Taxonomer false positive results can be eliminated by trimming the sequence data before analysis. One further important result is that no viruses were detected that had never been shown to occur in cell cultures. The results prove that the currently applied testing of cell cultures is adequate for the detection of contamination and for the risk assessment of cell cultures. The results emphasize that next generation sequencing is an efficient tool to determine the viral infection status of human cells.

MetaMap: an atlas of metatranscriptomic reads in human disease-related RNA-seq data

Background

With the advent of the age of big data in bioinformatics, large volumes of data and high-performance computing power enable researchers to perform re-analyses of publicly available datasets at an unprecedented scale. Ever more studies imply the microbiome in both normal human physiology and a wide range of diseases. RNA sequencing technology (RNA-seq) is commonly used to infer global eukaryotic gene expression patterns under defined conditions, including human disease-related contexts; however, its generic nature also enables the detection of microbial and viral transcripts.

Findings

We developed a bioinformatic pipeline to screen existing human RNA-seq datasets for the presence of microbial and viral reads by re-inspecting the non-human-mapping read fraction. We validated this approach by recapitulating outcomes from six independent, controlled infection experiments of cell line models and compared them with an alternative metatranscriptomic mapping strategy. We then applied the pipeline to close to 150 terabytes of publicly available raw RNA-seq data from  more than 17,000 samples from more than 400 studies relevant to human disease using state-of-the-art high-performance computing systems. The resulting data from this large-scale re-analysis are made available in the presented MetaMap resource.

Conclusions

Our results demonstrate that common human RNA-seq data, including those archived in public repositories, might contain valuable information to correlate microbial and viral detection patterns with diverse diseases. The presented MetaMap database thus provides a rich resource for hypothesis generation toward the role of the microbiome in human disease. Additionally, codes to process new datasets and perform statistical analyses are made available.

Diagnostic Testing of Neurologic Infections

Neuroinfectious diseases continue to cause morbidity and mortality worldwide, with many emerging or reemerging infections resulting in neurologic sequelae. Careful clinical evaluation coupled with appropriate laboratory investigations still forms the bedrock for making the correct etiologic diagnosis and implementing appropriate management. The treating physician needs to understand the individual test characteristics of each of the many conventional candidate-based diagnostics: culture, pathogen-specific polymerase chain reaction, antigen, antibody tests, used to diagnose the whole array of neuroinvasive infections. In addition, there is a growing need for more comprehensive, agnostic testing modalities that can identify a diversity of infections with a single assay.

Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection

Nearly all infectious agents contain DNA or RNA genomes, making sequencing an attractive approach for pathogen detection. The cost of high-throughput or next-generation sequencing has been reduced by several orders of magnitude since its advent in 2004, and it has emerged as an enabling technological platform for the detection and taxonomic characterization of microorganisms in clinical samples from patients. This review focuses on the application of untargeted metagenomic next-generation sequencing to the clinical diagnosis of infectious diseases, particularly in areas in which conventional diagnostic approaches have limitations. The review covers ( a) next-generation sequencing technologies and common platforms, ( b) next-generation sequencing assay workflows in the clinical microbiology laboratory, ( c) bioinformatics analysis of metagenomic next-generation sequencing data, ( d) validation and use of metagenomic next-generation sequencing for diagnosing infectious diseases, and ( e) significant case reports and studies in this area. Next-generation sequencing is a new technology that has the promise to enhance our ability to diagnose, interrogate, and track infectious diseases.

Profiling the B/T cell receptor repertoire of lymphocyte derived cell lines

BACKGROUND

Clonal VDJ rearrangement of B/T cell receptors (B/TCRs) occurring during B/T lymphocyte development has been used as a marker to track the clonality of B/T cell populations.

METHODS

We systematically profiled the B/T cell receptor repertoire of 936 cancer cell lines across a variety of cancer types as well as 462 Epstein-Barr Virus (EBV) transformed normal B lymphocyte lines using RNA sequencing data.

RESULTS

Rearranged B/TCRs were readily detected in cell lines derived from lymphocytes, and subclonality or potential biclonality were found in a number of blood cancer cell lines. Clonal BCR/TCR rearrangements were detected in several blast phase CML lines and unexpectedly, one gastric cancer cell line (KE-97), reflecting a lymphoid origin of these cells. Notably, clonality was highly prevalent in EBV transformed B lymphocytes, suggesting either transformation only occurred in a few B cells or those with a growth advantage dominated the transformed population through clonal evolution.

CONCLUSIONS

Our analysis reveals the complexity and heterogeneity of the BCR/TCR rearrangement repertoire and provides a unique insight into the clonality of lymphocyte derived cell lines.

Metagenomic Composition Analysis of an Ancient Sequenced Polar Bear Jawbone from Svalbard

The sequencing of ancient DNA samples provides a novel way to find, characterize, and distinguish exogenous genomes of endogenous targets. After sequencing, computational composition analysis enables filtering of undesired sources in the focal organism, with the purpose of improving the quality of assemblies and subsequent data analysis. More importantly, such analysis allows extinct and extant species to be identified without requiring a specific or new sequencing run. However, the identification of exogenous organisms is a complex task, given the nature and degradation of the samples, and the evident necessity of using efficient computational tools, which rely on algorithms that are both fast and highly sensitive. In this work, we relied on a fast and highly sensitive tool, FALCON-meta, which measures similarity against whole-genome reference databases, to analyse the metagenomic composition of an ancient polar bear (Ursus maritimus) jawbone fossil. The fossil was collected in Svalbard, Norway, and has an estimated age of 110,000 to 130,000 years. The FASTQ samples contained 349 GB of nonamplified shotgun sequencing data. We identified and localized, relative to the FASTQ samples, the genomes with significant similarities to reference microbial genomes, including those of viruses, bacteria, and archaea, and to fungal, mitochondrial, and plastidial sequences. Among other striking features, we found significant similarities between modern-human, some bacterial and viral sequences (contamination) and the organelle sequences of wild carrot and tomato relative to the whole samples. For each exogenous candidate, we ran a damage pattern analysis, which in addition to revealing shallow levels of damage in the plant candidates, identified the source as contamination.

Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing

Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis since synovial fluid cultures are not universally positive and since synovial fluid is easily obtained preoperatively. We applied a metagenomics-based approach to synovial fluid in an attempt to detect microorganisms in 168 failed total knee arthroplasties. Genus- and species-level analyses of metagenomic sequencing yielded the known pathogen in 74 (90%) and 68 (83%) of the 82 culture-positive PJIs analyzed, respectively, with testing of two (2%) and three (4%) samples, respectively, yielding additional pathogens not detected by culture. For the 25 culture-negative PJIs tested, genus- and species-level analyses yielded 19 (76%) and 21 (84%) samples with insignificant findings, respectively, and 6 (24%) and 4 (16%) with potential pathogens detected, respectively. Genus- and species-level analyses of the 60 culture-negative aseptic failure cases yielded 53 (88%) and 56 (93%) cases with insignificant findings and 7 (12%) and 4 (7%) with potential clinically significant organisms detected, respectively. There was one case of aseptic failure with synovial fluid culture growth; metagenomic analysis showed insignificant findings, suggesting possible synovial fluid culture contamination. Metagenomic shotgun sequencing can detect pathogens involved in PJI when applied to synovial fluid and may be particularly useful for culture-negative cases.

Horizontally transferred genes in the ctenophore Mnemiopsis leidyi

Horizontal gene transfer (HGT) has had major impacts on the biology of a wide range of organisms from antibiotic resistance in bacteria to adaptations to herbivory in arthropods. A growing body of literature shows that HGT between non-animals and animals is more commonplace than previously thought. In this study, we present a thorough investigation of HGT in the ctenophore Mnemiopsis leidyi. We applied tests of phylogenetic incongruence to identify nine genes that were likely transferred horizontally early in ctenophore evolution from bacteria and non-metazoan eukaryotes. All but one of these HGTs (an uncharacterized protein) are homologous to characterized enzymes, supporting previous observations that genes encoding enzymes are more likely to be retained after HGT events. We found that the majority of these nine horizontally transferred genes were expressed during development, suggesting that they are active and play a role in the biology of M. leidyi. This is the first report of HGT in ctenophores, and contributes to an ever-growing literature on the prevalence of genetic information flowing between non-animals and animals.

Potential of cell-free DNA as a screening marker for parasite infections in dog

Parasitic infections are common in stray dogs and accurate knowledge of parasite communities in dogs would provide insight into the epidemiology of parasitic diseases. In this study, we used Illumina sequencing technology to evaluate cell-free DNA (cfDNA) as a marker for screening of parasitic infections in dogs. Plasma samples from 14 stray dogs captured in Bangladesh were used in the experiments. An average of 2.3 million reads was obtained for each sample. BLASTn analysis identified 150 reads with high similarity with parasites from 19 different genera. In particular, we detected sequences of Babesia spp. in five dogs; consistent with this, a previous study using conventional PCR showed that four of these dogs were positive for B. gibsoni. Several reads with similarity to Leishmania and filarial nematodes were also identified. These findings indicate that cfDNA in blood can be a potential screening marker for identifying parasite diversity in dogs.

Transcriptome analysis in whole blood reveals increased microbial diversity in schizophrenia

The role of the human microbiome in health and disease is increasingly appreciated. We studied the composition of microbial communities present in blood across 192 individuals, including healthy controls and patients with three disorders affecting the brain: schizophrenia, amyotrophic lateral sclerosis, and bipolar disorder. By using high-quality unmapped RNA sequencing reads as candidate microbial reads, we performed profiling of microbial transcripts detected in whole blood. We were able to detect a wide range of bacterial and archaeal phyla in blood. Interestingly, we observed an increased microbial diversity in schizophrenia patients compared to the three other groups. We replicated this finding in an independent schizophrenia case-control cohort. This increased diversity is inversely correlated with estimated cell abundance of a subpopulation of CD8+ memory T cells in healthy controls, supporting a link between microbial products found in blood, immunity and schizophrenia.

Viromic Analysis of Wastewater Input to a River Catchment Reveals a Diverse Assemblage of RNA Viruses

Detection of viruses in the environment is heavily dependent on PCR-based approaches that require reference sequences for primer design. While this strategy can accurately detect known viruses, it will not find novel genotypes or emerging and invasive viral species. In this study, we investigated the use of viromics, i.e., high-throughput sequencing of the biosphere's viral fraction, to detect human-/animal-pathogenic RNA viruses in the Conwy river catchment area in Wales, United Kingdom. Using a combination of filtering and nuclease treatment, we extracted the viral fraction from wastewater and estuarine river water and sediment, followed by high-throughput RNA sequencing (RNA-Seq) analysis on the Illumina HiSeq platform, for the discovery of RNA virus genomes. We found a higher richness of RNA viruses in wastewater samples than in river water and sediment, and we assembled a complete norovirus genotype GI.2 genome from wastewater effluent, which was not contemporaneously detected by conventional reverse transcription-quantitative PCR (qRT-PCR). The simultaneous presence of diverse rotavirus signatures in wastewater indicated the potential for zoonotic infections in the area and suggested runoff from pig farms as a possible origin of these viruses. Our results show that viromics can be an important tool in the discovery of pathogenic viruses in the environment and can be used to inform and optimize reference-based detection methods provided appropriate and rigorous controls are included. IMPORTANCE Enteric viruses cause gastrointestinal illness and are commonly transmitted through the fecal-oral route. When wastewater is released into river systems, these viruses can contaminate the environment. Our results show that we can use viromics to find the range of potentially pathogenic viruses that are present in the environment and identify prevalent genotypes. The ultimate goal is to trace the fate of these pathogenic viruses from origin to the point where they are a threat to human health, informing reference-based detection methods and water quality management.

Viromic Analysis of Wastewater Input to a River Catchment Reveals a Diverse Assemblage of RNA Viruses

Detection of viruses in the environment is heavily dependent on PCR-based approaches that require reference sequences for primer design. While this strategy can accurately detect known viruses, it will not find novel genotypes or emerging and invasive viral species. In this study, we investigated the use of viromics, i.e., high-throughput sequencing of the biosphere's viral fraction, to detect human-/animal-pathogenic RNA viruses in the Conwy river catchment area in Wales, United Kingdom. Using a combination of filtering and nuclease treatment, we extracted the viral fraction from wastewater and estuarine river water and sediment, followed by high-throughput RNA sequencing (RNA-Seq) analysis on the Illumina HiSeq platform, for the discovery of RNA virus genomes. We found a higher richness of RNA viruses in wastewater samples than in river water and sediment, and we assembled a complete norovirus genotype GI.2 genome from wastewater effluent, which was not contemporaneously detected by conventional reverse transcription-quantitative PCR (qRT-PCR). The simultaneous presence of diverse rotavirus signatures in wastewater indicated the potential for zoonotic infections in the area and suggested runoff from pig farms as a possible origin of these viruses. Our results show that viromics can be an important tool in the discovery of pathogenic viruses in the environment and can be used to inform and optimize reference-based detection methods provided appropriate and rigorous controls are included. IMPORTANCE Enteric viruses cause gastrointestinal illness and are commonly transmitted through the fecal-oral route. When wastewater is released into river systems, these viruses can contaminate the environment. Our results show that we can use viromics to find the range of potentially pathogenic viruses that are present in the environment and identify prevalent genotypes. The ultimate goal is to trace the fate of these pathogenic viruses from origin to the point where they are a threat to human health, informing reference-based detection methods and water quality management.

Tumour virology in the era of high-throughput genomics

With the advent of massively parallel sequencing, oncogenic viruses in tumours can now be detected in an unbiased and comprehensive manner. Additionally, new viruses or strains can be discovered based on sequence similarity with known viruses. Using this approach, the causative agent for Merkel cell carcinoma was identified. Subsequent studies using data from large collections of tumours have confirmed models built during decades of hypothesis-driven and low-throughput research, and a more detailed and comprehensive description of virus-tumour associations have emerged. Notably, large cohorts and high sequencing depth, in combination with newly developed bioinformatical techniques, have made it possible to rule out several suggested virus-tumour associations with a high degree of confidence. In this review we discuss possibilities, limitations and insights gained from using massively parallel sequencing to characterize tumours with viral content, with emphasis on detection of viral sequences and genomic integration events.This article is part of the themed issue 'Human oncogenic viruses'.

A novel approach to wildlife transcriptomics provides evidence of disease-mediated differential expression and changes to the microbiome of amphibian populations

Ranaviruses are responsible for a lethal, emerging infectious disease in amphibians and threaten their populations throughout the world. Despite this, little is known about how amphibian populations respond to ranaviral infection. In the United Kingdom, ranaviruses impact the common frog (Rana temporaria). Extensive public engagement in the study of ranaviruses in the UK has led to the formation of a unique system of field sites containing frog populations of known ranaviral disease history. Within this unique natural field system, we used RNA sequencing (RNA-Seq) to compare the gene expression profiles of R. temporaria populations with a history of ranaviral disease and those without. We have applied a RNA read-filtering protocol that incorporates Bloom filters, previously used in clinical settings, to limit the potential for contamination that comes with the use of RNA-Seq in nonlaboratory systems. We have identified a suite of 407 transcripts that are differentially expressed between populations of different ranaviral disease history. This suite contains genes with functions related to immunity, development, protein transport and olfactory reception among others. A large proportion of potential noncoding RNA transcripts present in our differentially expressed set provide first evidence of a possible role for long noncoding RNA (lncRNA) in amphibian response to viruses. Our read-filtering approach also removed significantly more bacterial reads from libraries generated from positive disease history populations. Subsequent analysis revealed these bacterial read sets to represent distinct communities of bacterial species, which is suggestive of an interaction between ranavirus and the host microbiome in the wild.

ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues

High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki.

Next-generation sequencing diagnostics of bacteremia in sepsis (Next GeneSiS-Trial): Study protocol of a prospective, observational, noninterventional, multicenter, clinical trial

BACKGROUND

Sepsis remains a major challenge, even in modern intensive care medicine. The identification of the causative pathogen is crucial for an early optimization of the antimicrobial treatment regime. In this context, culture-based diagnostic procedures (e.g., blood cultures) represent the standard of care, although they are associated with relevant limitations. Accordingly, culture-independent molecular diagnostic procedures might be of help for the identification of the causative pathogen in infected patients. The concept of an unbiased sequence analysis of circulating cell-free DNA (cfDNA) from plasma samples of septic patients by next-generation sequencing (NGS) has recently been identified to be a promising diagnostic platform for critically ill patients suffering from bloodstream infections. Although this new approach might be more sensitive and specific than culture-based state-of-the-art technologies, additional clinical trials are needed to exactly define the performance as well as clinical value of a NGS-based approach.

METHODS

Next GeneSiS is a prospective, observational, noninterventional, multicenter study to assess the diagnostic performance of a NGS-based approach for the detection of relevant infecting organisms in patients with suspected or proven sepsis [according to recent sepsis definitions (sepsis-3)] by the use of the quantitative sepsis indicating quantifier (SIQ) score in comparison to standard (culture-based) microbiological diagnostics. The clinical value of this NGS-based approach will be estimated by a panel of independent clinical specialists, retrospectively identifying potential changes in patients' management based on NGS results. Further subgroup analyses will focus on the clinical value especially for patients suffering from a failure of empiric treatment within the first 3 days after onset [as assessed by death of the patient or lack of improvement of the patient's clinical condition (in terms of an inadequate decrease of SOFA-score) or persistent high procalcitonin levels].

DISCUSSION

This prospective, observational, noninterventional, multicenter study for the first time investigates the performance as well as the clinical value of a NGS-based approach for the detection of bacteremia in patients with sepsis and may therefore be a pivotal step toward the clinical use of NGS in this indication.

TRIAL REGISTRATION

DRKS-ID: DRKS00011911 (registered October 9, 2017) https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011911; ClinicalTrials.gov Identifier: NCT03356249 (registered November 29, 2017) https://clinicaltrials.gov/ct2/show/NCT03356249.

Recent insights into the tick microbiome gained through next-generation sequencing

The tick microbiome comprises communities of microorganisms, including viruses, bacteria and eukaryotes, and is being elucidated through modern molecular techniques. The advent of next-generation sequencing (NGS) technologies has enabled the genes and genomes within these microbial communities to be explored in a rapid and cost-effective manner. The advantages of using NGS to investigate microbiomes surpass the traditional non-molecular methods that are limited in their sensitivity, and conventional molecular approaches that are limited in their scalability. In recent years the number of studies using NGS to investigate the microbial diversity and composition of ticks has expanded. Here, we provide a review of NGS strategies for tick microbiome studies and discuss the recent findings from tick NGS investigations, including the bacterial diversity and composition, influential factors, and implications of the tick microbiome.

Decontaminating eukaryotic genome assemblies with machine learning

BACKGROUND

High-throughput sequencing has made it theoretically possible to obtain high-quality de novo assembled genome sequences but in practice DNA extracts are often contaminated with sequences from other organisms. Currently, there are few existing methods for rigorously decontaminating eukaryotic assemblies. Those that do exist filter sequences based on nucleotide similarity to contaminants and risk eliminating sequences from the target organism.

RESULTS

We introduce a novel application of an established machine learning method, a decision tree, that can rigorously classify sequences. The major strength of the decision tree is that it can take any measured feature as input and does not require a priori identification of significant descriptors. We use the decision tree to classify de novo assembled sequences and compare the method to published protocols.

CONCLUSIONS

A decision tree performs better than existing methods when classifying sequences in eukaryotic de novo assemblies. It is efficient, readily implemented, and accurately identifies target and contaminant sequences. Importantly, a decision tree can be used to classify sequences according to measured descriptors and has potentially many uses in distilling biological datasets.

Towards a Universal Molecular Microbiological Test

The standard paradigm for microbiological testing is dependent on the presentation of a patient to a clinician. Tests are then requested based on differential diagnoses using the patient's symptoms as a guide. The era of high-throughput genomic methods has the potential to replace this model for the first time with what could be referred to as "hypothesis-free testing." This approach utilizes one of a variety of methodologies to obtain a sequence from potentially any nucleic acid in a clinical sample, without prior knowledge of its content. We discuss the advantages of such an approach and the challenges in making this a reality.

Three distinct pneumotypes characterize the microbiome of the lung in BALB/cJ mice

Bacteria can rarely be isolated from normal healthy lungs using conventional culture techniques, supporting the traditional belief that the lungs are sterile. Yet recent studies using next generation sequencing report that bacterial DNA commonly found in the upper respiratory tract (URT) is present at lower levels in the lungs. Interpretation of that finding is complicated by the technical limitations and potential for contamination introduced when dealing with low biomass samples. The current work sought to overcome those limitations to clarify the number, type and source of bacteria present in the lungs of normal mice. Results showed that the oral microbiome is diverse and highly conserved whereas murine lung samples fall into three distinct patterns. 33% of the samples were sterile, as they lacked culturable bacteria and their bacterial DNA content did not differ from background. 9% of samples contained comparatively higher amounts of bacterial DNA whose composition mimicked that detected in the URT. A final group (58%) contained smaller amounts of microbial DNA whose composition was correlating to that of rodent chow and cage bedding, likely acquired by inspiration of food and bedding fragments. By analyzing each sample independently rather than working with group averages, this work eliminated the bias introduced by aspiration-contaminated samples to establish that three distinct microbiome pneumotypes are present in normal murine lungs.

Viral Encephalitis of Unknown Cause: Current Perspective and Recent Advances

Viral encephalitis causes acute inflammation of the brain parenchyma and is a significant cause of human morbidity and mortality. Although Herpes Simplex encephalitis is the most frequent known cause of fatal sporadic encephalitis in humans, an increasingly wide range of viruses and other microbial pathogens are implicated. Up to 60% of cases of presumed viral encephalitis remain unexplained due to the failure of conventional laboratory techniques to detect an infectious agent. High-throughput DNA sequencing technologies have the potential to detect any microbial nucleic acid present in a biological specimen without any prior knowledge of the target sequence. While there remain challenges intrinsic to these technologies, they have great promise in virus discovery in unexplained encephalitis.

Culture-Independent Diagnostics for Health Security

The past decade has seen considerable development in the diagnostic application of nonculture methods, including nucleic acid amplification-based methods and mass spectrometry, for the diagnosis of infectious diseases. The implications of these new culture-independent diagnostic tests (CIDTs) include bypassing the need to culture organisms, thus potentially affecting public health surveillance systems, which continue to use isolates as the basis of their surveillance programs and to assess phenotypic resistance to antimicrobial agents. CIDTs may also affect the way public health practitioners detect and respond to a bioterrorism event. In response to a request from the Department of Homeland Security, Los Alamos National Laboratory and the Centers for Disease Control and Prevention cosponsored a workshop to review the impact of CIDTs on the rapid detection and identification of biothreat agents. Four panel discussions were held that covered nucleic acid amplification-based diagnostics, mass spectrometry, antibody-based diagnostics, and next-generation sequencing. Exploiting the extensive expertise available at this workshop, we identified the key features, benefits, and limitations of the various CIDT methods for providing rapid pathogen identification that are critical to the response and mitigation of a bioterrorism event. After the workshop we conducted a thorough review of the literature, investigating the current state of these 4 culture-independent diagnostic methods. This article combines information from the literature review and the insights obtained at the workshop.

The blood DNA virome in 8,000 humans

The characterization of the blood virome is important for the safety of blood-derived transfusion products, and for the identification of emerging pathogens. We explored non-human sequence data from whole-genome sequencing of blood from 8,240 individuals, none of whom were ascertained for any infectious disease. Viral sequences were extracted from the pool of sequence reads that did not map to the human reference genome. Analyses sifted through close to 1 Petabyte of sequence data and performed 0.5 trillion similarity searches. With a lower bound for identification of 2 viral genomes/100,000 cells, we mapped sequences to 94 different viruses, including sequences from 19 human DNA viruses, proviruses and RNA viruses (herpesviruses, anelloviruses, papillomaviruses, three polyomaviruses, adenovirus, HIV, HTLV, hepatitis B, hepatitis C, parvovirus B19, and influenza virus) in 42% of the study participants. Of possible relevance to transfusion medicine, we identified Merkel cell polyomavirus in 49 individuals, papillomavirus in blood of 13 individuals, parvovirus B19 in 6 individuals, and the presence of herpesvirus 8 in 3 individuals. The presence of DNA sequences from two RNA viruses was unexpected: Hepatitis C virus is revealing of an integration event, while the influenza virus sequence resulted from immunization with a DNA vaccine. Age, sex and ancestry contributed significantly to the prevalence of infection. The remaining 75 viruses mostly reflect extensive contamination of commercial reagents and from the environment. These technical problems represent a major challenge for the identification of novel human pathogens. Increasing availability of human whole-genome sequences will contribute substantial amounts of data on the composition of the normal and pathogenic human blood virome. Distinguishing contaminants from real human viruses is challenging.

Novel sequencing technologies offer insight into the virome in human samples. Here, we identify the viral DNA sequences in blood of over 8,000 individuals undergoing whole genome sequencing. This approach serves to identify 94 viruses; however, many are shown to reflect widespread DNA contamination of commercial reagents or of environmental origin. While this represents a significant limitation to reliably identify novel viruses infecting humans, we could confidently detect sequences and quantify abundance of 19 human viruses in 42% of individuals. Ancestry, sex, and age were important determinants of viral prevalence. This large study calls attention on the challenge of interpreting next generation sequencing data for the identification of novel viruses. However, it serves to categorize the abundance of human DNA viruses using an unbiased technique.

Validation of Metagenomic Next-Generation Sequencing Tests for Universal Pathogen Detection

CONTEXT

- Metagenomic sequencing can be used for detection of any pathogens using unbiased, shotgun next-generation sequencing (NGS), without the need for sequence-specific amplification. Proof-of-concept has been demonstrated in infectious disease outbreaks of unknown causes and in patients with suspected infections but negative results for conventional tests. Metagenomic NGS tests hold great promise to improve infectious disease diagnostics, especially in immunocompromised and critically ill patients.

OBJECTIVE

- To discuss challenges and provide example solutions for validating metagenomic pathogen detection tests in clinical laboratories. A summary of current regulatory requirements, largely based on prior guidance for NGS testing in constitutional genetics and oncology, is provided.

DATA SOURCES

- Examples from 2 separate validation studies are provided for steps from assay design, and validation of wet bench and bioinformatics protocols, to quality control and assurance.

CONCLUSIONS

- Although laboratory and data analysis workflows are still complex, metagenomic NGS tests for infectious diseases are increasingly being validated in clinical laboratories. Many parallels exist to NGS tests in other fields. Nevertheless, specimen preparation, rapidly evolving data analysis algorithms, and incomplete reference sequence databases are idiosyncratic to the field of microbiology and often overlooked.

Optimisation of methods for bacterial skin microbiome investigation: primer selection and comparison of the 454 versus MiSeq platform

Background

The composition of the skin microbiome is predicted to play a role in the development of conditions such as atopic eczema and psoriasis. 16S rRNA gene sequencing allows the investigation of bacterial microbiota. A significant challenge in this field is development of cost effective high throughput methodologies for the robust interrogation of the skin microbiota, where biomass is low. Here we describe validation of methodologies for 16S rRNA (ribosomal ribonucleic acid) gene sequencing from the skin microbiome, using the Illumina MiSeq platform, the selection of primer to amplify regions for sequencing and we compare results with the current standard protocols..

Methods

DNA was obtained from two low density mock communities of 11 diverse bacterial strains (with and without human DNA supplementation) and from swabs taken from the skin of healthy volunteers. This was amplified using primer pairs covering hypervariable regions of the 16S rRNA gene: primers 63F and 519R (V1-V3); and 347F and 803R (V3-V4). The resultant libraries were indexed for the MiSeq and Roche454 and sequenced. Both data sets were denoised, cleaned of chimeras and analysed using QIIME.

Results

There was no significant difference in the diversity indices at the phylum and the genus level observed between the platforms. The capture of diversity using the low density mock community samples demonstrated that the primer pair spanning the V3-V4 hypervariable region had better capture when compared to the primer pair for the V1-V3 region and was robust to spiking with human DNA. The pilot data generated using the V3-V4 region from the skin of healthy volunteers was consistent with these results, even at the genus level (Staphylococcus, Propionibacterium, Corynebacterium, Paracoccus, Micrococcus, Enhydrobacter and Deinococcus identified at similar abundances on both platforms).

Conclusions

The results suggest that the bacterial community diversity captured using the V3-V4 16S rRNA hypervariable region from sequencing using the MiSeq platform is comparable to the Roche454 GS Junior platform. These findings provide evidence that the optimised method can be used in human clinical samples of low bacterial biomass such as the investigation of the skin microbiota.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-017-0927-4) contains supplementary material, which is available to authorized users.

Parasite infection of public databases: a data mining approach to identify apicomplexan contaminations in animal genome and transcriptome assemblies

Background

Contaminations from various exogenous sources are a common problem in next-generation sequencing. Another possible source of contaminating DNA are endogenous parasites. On the one hand, undiscovered contaminations of animal sequence assemblies may lead to erroneous interpretation of data; on the other hand, when identified, parasite-derived sequences may provide a valuable source of information.

Results

Here we show that sequences deriving from apicomplexan parasites can be found in many animal genome and transcriptome projects, which in most cases derived from an infection of the sequenced host specimen. The apicomplexan sequences were extracted from the sequence assemblies using a newly developed bioinformatic pipeline (ContamFinder) and tentatively assigned to distinct taxa employing phylogenetic methods. We analysed 920 assemblies and found 20,907 contigs of apicomplexan origin in 51 of the datasets. The contaminating species were identified as members of the apicomplexan taxa Gregarinasina, Coccidia, Piroplasmida, and Haemosporida. For example, in the platypus genome assembly, we found a high number of contigs derived from a piroplasmid parasite (presumably Theileria ornithorhynchi). For most of the infecting parasite species, no molecular data had been available previously, and some of the datasets contain sequences representing large amounts of the parasite’s gene repertoire.

Conclusion

Our study suggests that parasite-derived contaminations represent a valuable source of information that can help to discover and identify new parasites, and provide information on previously unknown host-parasite interactions. We, therefore, argue that uncurated assembly data should routinely be made available in addition to the final assemblies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3504-1) contains supplementary material, which is available to authorized users.

Validation of picogram- and femtogram-input DNA libraries for microscale metagenomics

High-throughput sequencing libraries are typically limited by the requirement for nanograms to micrograms of input DNA. This bottleneck impedes the microscale analysis of ecosystems and the exploration of low biomass samples. Current methods for amplifying environmental DNA to bypass this bottleneck introduce considerable bias into metagenomic profiles. Here we describe and validate a simple modification of the Illumina Nextera XT DNA library preparation kit which allows creation of shotgun libraries from sub-nanogram amounts of input DNA. Community composition was reproducible down to 100 fg of input DNA based on analysis of a mock community comprising 54 phylogenetically diverse Bacteria and Archaea. The main technical issues with the low input libraries were a greater potential for contamination, limited DNA complexity which has a direct effect on assembly and binning, and an associated higher percentage of read duplicates. We recommend a lower limit of 1 pg (∼100-1,000 microbial cells) to ensure community composition fidelity, and the inclusion of negative controls to identify reagent-specific contaminants. Applying the approach to marine surface water, pronounced differences were observed between bacterial community profiles of microliter volume samples, which we attribute to biological variation. This result is consistent with expected microscale patchiness in marine communities. We thus envision that our benchmarked, slightly modified low input DNA protocol will be beneficial for microscale and low biomass metagenomics.