Using strain-resolved analysis to identify contamination in metagenomics data.

BACKGROUND: Metagenomics analyses can be negatively impacted by DNA contamination. While external sources of contamination such as DNA extraction kits have been widely reported and investigated, contamination originating within the study itself remains underreported. RESULTS: Here, we applied high-resolution strain-resolved analyses to identify contamination in two large-scale clinical metagenomics datasets. By mapping strain sharing to DNA extraction plates, we identified well-to-well contamination in both negative controls and biological samples in one dataset. Such contamination is more likely to occur among samples that are on the same or adjacent columns or rows of the extraction plate than samples that are far apart. Our strain-resolved workflow also reveals the presence of externally derived contamination, primarily in the other dataset. Overall, in both datasets, contamination is more significant in samples with lower biomass. CONCLUSION: Our work demonstrates that genome-resolved strain tracking, with its essentially genome-wide nucleotide-level resolution, can be used to detect contamination in sequencing-based microbiome studies. Our results underscore the value of strain-specific methods to detect contamination and the critical importance of looking for contamination beyond negative and positive controls. Video Abstract.

Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies.

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

Optimization of Low-Biomass Sample Collection and Quantitative PCR-Based Titration Impact 16S rRNA Microbiome Resolution.

The major aquatic interface between host and environment in teleost finfish species is the gill. The diversity of this infraclass, high complexity of the organ, and its direct exposure to the surrounding environment make it an ideal candidate for furthering our understanding of the intertwined relationships between host and microbiome. Capturing the structure and diversity of bacterial communities from this low-biomass, inhibitor-rich tissue can, however, prove challenging. Lessons learned in doing so are directly applicable to similar sample types in other areas of microbiology. Through the development of a quantitative PCR assay for both host material and 16S rRNA genes, we tested and developed a robust method for low-biomass sample collection which minimized host DNA contamination. Quantification of 16S rRNA facilitated not only the screening of samples prior to costly library construction and sequencing but also the production of equicopy libraries based on 16S rRNA gene copies. A significant increase in diversity of bacteria captured was achieved, providing greater information on the true structure of the microbial community. Such findings offer important information for determining functional processes. Results were confirmed across fresh, brackish, and marine environs with four different fish species, with results showing broad homology between samples, demonstrating the robustness of the approach. Evidence presented is widely applicable to samples similar in composition, such as sputum or mucus, or those that are challenging due to the inherent inclusion of inhibitors. IMPORTANCE The interaction between the fish gill and surrounding bacteria-rich water provides an intriguing model for examining the interaction between the fish, free-floating bacteria, and the bacterial microbiome on the gill surface. Samples that are inherently low in bacteria, or that have components that inhibit the ability to produce libraries that identify the components of microbial communities, present significant challenges. Gill samples present both of these types of challenges. We developed methods for quantifying both the bacterial and host DNA material and established a sampling method which both reduced inhibitor content and maximized bacterial diversity. By quantifying and normalizing bacteria prior to library construction, we showed significant improvements with regards to the fidelity of the final data. Our results support wide-ranging applications for analyzing samples of similar composition, such as mucus and sputum, in other microbiological spheres.

Genes expressed at low levels raise false discovery rates in RNA samples contaminated with genomic DNA.

BACKGROUND: RNA preparations contaminated with genomic DNA (gDNA) are frequently disregarded by RNA-seq studies. Such contamination may generate false results; however, their effect on the outcomes of RNA-seq analyses is unknown. To address this gap in our knowledge, here we added different concentrations of gDNA to total RNA preparations and subjected them to RNA-seq analysis. RESULTS: We found that the contaminating gDNA altered the quantification of transcripts at relatively high concentrations. Differentially expressed genes (DEGs) resulting from gDNA contamination may therefore contribute to higher rates of false enrichment of pathways compared with analogous samples lacking numerous DEGs. A strategy was developed to correct gene expression levels in gDNA-contaminated RNA samples, which assessed the magnitude of contamination to improve the reliability of the results. CONCLUSIONS: Our study indicates that caution must be exercised when interpreting results associated with low-abundance transcripts. The data provided here will likely serve as a valuable resource to evaluate the influence of gDNA contamination on RNA-seq analysis, particularly related to the detection of putative novel gene elements.

Human DNA contamination of postmortem examination facilities: Impact of COVID-19 cleaning procedure.

The DNA contamination of evidentiary trace samples, included those collected in the autopsy room, has significant detrimental consequences for forensic genetics investigation. After the COVID-19 pandemic, methods to prevent environmental contamination in the autopsy room have been developed and intensified. This study aimed to evaluate the level of human DNA contamination of a postmortem examination facility before and after the introduction of COVID-19-related disinfection and cleaning procedures. Ninety-one swabs were collected from the surfaces and the dissecting instruments, analyzed by real-time quantitative PCR (q-PCR) and typed for 21 autosomal STRs. Sixty-seven out of 91 samples resulted in quantifiable human DNA, ranging from 1 pg/µl to 12.4 ng/µl, including all the samples collected before the implementation of COVID-19 cleaning procedures (n = 38) and 29 out of 53 (54.7%) samples taken afterward. All samples containing human DNA were amplified, resulting in mixed (83.6%), single (13.4%), and incomplete (3%) profiles. A statistically significant decrease in DNA contamination was found for dissecting instruments after treatment with chlorhexidine and autoclave (p < 0.05). Environmental decontamination strategies adopted during COVID-19 pandemic only partially solved the long-standing issue of DNA contamination of postmortem examination facilities. The pandemic represents an opportunity to further stress the need for standardized evidence-based protocols targeted to overcome the problem of DNA contamination in the autopsy room.

A metagenomic DNA sequencing assay that is robust against environmental DNA contamination.

Metagenomic DNA sequencing is a powerful tool to characterize microbial communities but is sensitive to environmental DNA contamination, in particular when applied to samples with low microbial biomass. Here, we present Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) a metagenomic sequencing assay that is robust against environmental DNA contamination introduced during sample preparation. The core idea of SIFT-seq is to tag the DNA in the sample prior to DNA isolation and library preparation with a label that can be recorded by DNA sequencing. Any contaminating DNA that is introduced in the sample after tagging can then be bioinformatically identified and removed. We applied SIFT-seq to screen for infections from microorganisms with low burden in blood and urine, to identify COVID-19 co-infection, to characterize the urinary microbiome, and to identify microbial DNA signatures of sepsis and inflammatory bowel disease in blood.

Examining potential confounding factors in gene expression analysis of human saliva and identifying potential housekeeping genes.

Isolation of RNA from whole saliva, a non-invasive and easily accessible biofluid that is an attractive alternative to blood for high-throughput biodosimetry of radiological/nuclear victims might be of clinical significance for prediction and diagnosis of disease. In a previous analysis of 12 human samples we identified two challenges to measuring gene expression from total RNA: (1) the fraction of human RNA in whole saliva was low and (2) the bacterial contamination was overwhelming. To overcome these challenges, we performed selective cDNA synthesis for human RNA species only by employing poly(A)+-tail primers followed by qRT-PCR. In the current study, this approach was independently validated on 91 samples from 61 healthy donors. Additionally, we used the ratio of human to bacterial RNA to adjust the input RNA to include equal amounts of human RNA across all samples before cDNA synthesis, which then ensured comparable analysis using the same base human input material. Furthermore, we examined relative levels of ten known housekeeping genes, and assessed inter- and intra-individual differences in 61 salivary RNA isolates, while considering effects of demographical factors (e.g. sex, age), epidemiological factors comprising social habits (e.g. alcohol, cigarette consumption), oral hygiene (e.g. flossing, mouthwash), previous radiological diagnostic procedures (e.g. number of CT-scans) and saliva collection time (circadian periodic). Total human RNA amounts appeared significantly associated with age only (P ≤ 0.02). None of the chosen housekeeping genes showed significant circadian periodicity and either did not associate or were weakly associated with the 24 confounders examined, with one exception, 60% of genes were altered by mouthwash. ATP6, ACTB and B2M represented genes with the highest mean baseline expression (Ct-values ≤ 30) and were detected in all samples. Combining these housekeeping genes for normalization purposes did not decrease inter-individual variance, but increased the robustness. In summary, our work addresses critical confounders and provides important information for the successful examination of gene expression in human whole saliva.

Evaluation of Different Cleaning Strategies for Removal of Contaminating DNA Molecules.

Decontamination strategies and their efficiencies are crucial when performing routine forensic analysis, and many factors influence the choice of agent to use. In this study, the effects of ten different cleaning strategies were evaluated to compare their ability to remove contaminating DNA molecules. Cell-free DNA or blood was deposited on three surfaces (plastic, metal, and wood) and decontaminated with various treatments. The quantities of recovered DNA, obtained by swabbing the surfaces after cleaning using the different strategies, was analyzed by real-time PCR. Large differences in the DNA removal efficiencies were observed between different cleaning strategies, as well as between different surfaces. The most efficient cleaning strategies for cell-free DNA were the different sodium hypochlorite solutions and Trigene®, for which a maximum of 0.3% DNA was recovered on all three surfaces. For blood, a maximum of 0.8% of the deposited DNA was recovered after using Virkon® for decontamination. The recoveries after using these cleaning strategies correspond to DNA from only a few cells, out of 60 ng of cell-free DNA or thousands of deposited blood cells.

Removal effect of DNA contamination by hydrogen peroxide plasma compared to ethylene-oxide gas.

We examined the ability of hydrogen peroxide plasma (HPP) to remove DNA contamination, to evaluate whether it is a suitable forensic-grade treatment under ISO 18385. HPP treatment was compared to ethylene-oxide gas (EOG) treatment, which is required by ISO 18385. For the evaluation, commercial control DNA solution and cultured cells sprinkled on Petri dishes were used, and the DNA fragments (214 and 80 bp autosomal DNA fragments and 75 bp Y chromosome fragment) were quantified. HPP treatment was performed up to four times and EOG treatment was performed once. Performing HPP treatment three times was as effective as EOG treatment, with all fragments decreasing to below 1/1,000 in DNA solution. With STR and Y-STR typing, no alleles were detected for three HPP treatments of control DNA using the original amount, i.e., 1 ng. Therefore, HPP appears useful for removing DNA contamination. For cells sprinkled on Petri dishes, the DNA degradation abilities of the HPP and EOG were comparable. However, less DNA was degraded with the HPP and EOG and neither met the ISO criteria. Although the current version of ISO 18385 recommends an evaluation method using cultured cells sprinkled on Petri dishes, it needs to be revised. These findings should be considered when revising ISO 18385.

Inline index helped in cleaning up data contamination generated during library preparation and the subsequent steps.

BACKGROUND: High-throughput sequencing involves library preparation and amplification steps, which may induce contamination across samples or between samples and the environment. METHODS: We tested the effect of applying an inline-index strategy, in which DNA indices of 6 bp were added to both ends of the inserts at the ligation step of library prep for resolving the data contamination problem. RESULTS: Our results showed that the contamination ranged from 0.29 to 1.25% in one experiment and from 0.83 to 27.01% in the other. We also found that contamination could be environmental or from reagents besides cross-contamination between samples. CONCLUSIONS: Inline-index method is a useful experimental design to clean up the data and address the contamination problem which has been plaguing high-throughput sequencing data in many applications.

Transcriptomic signatures of tumors undergoing T cell attack.

BACKGROUND: Studying tumor cell-T cell interactions in the tumor microenvironment (TME) can elucidate tumor immune escape mechanisms and help predict responses to cancer immunotherapy. METHODS: We selected 14 pairs of highly tumor-reactive tumor-infiltrating lymphocytes (TILs) and autologous short-term cultured cell lines, covering four distinct tumor types, and co-cultured TILs and tumors at sub-lethal ratios in vitro to mimic the interactions occurring in the TME. We extracted gene signatures associated with a tumor-directed T cell attack based on transcriptomic data of tumor cells. RESULTS: An autologous T cell attack induced pronounced transcriptomic changes in the attacked tumor cells, partially independent of IFN-γ signaling. Transcriptomic changes were mostly independent of the tumor histological type and allowed identifying common gene expression changes, including a shared gene set of 55 transcripts influenced by T cell recognition (Tumors undergoing T cell attack, or TuTack, focused gene set). TuTack scores, calculated from tumor biopsies, predicted the clinical outcome after anti-PD-1/anti-PD-L1 therapy in multiple tumor histologies. Notably, the TuTack scores did not correlate to the tumor mutational burden, indicating that these two biomarkers measure distinct biological phenomena. CONCLUSIONS: The TuTack scores measure the effects on tumor cells of an anti-tumor immune response and represent a comprehensive method to identify immunologically responsive tumors. Our findings suggest that TuTack may allow patient selection in immunotherapy clinical trials and warrant its application in multimodal biomarker strategies.

What's on the bag? The DNA composition of evidence bags pre- and post-exhibit examination.

Current forensic DNA profiling kits and techniques enable the detection of trace amounts of DNA. With advancements in kit sensitivity, there is an increased probability of detecting DNA from contamination. Research into DNA transfer within operational forensic laboratories provides insight into the possible mechanisms that may lead to exhibit contamination. To gain a greater understanding of the potential for evidence bags to act as DNA transfer vectors, the level of DNA accumulating on the exterior of evidence bags during the exhibit examination process was investigated. The exterior of 60 evidence bags were tapelifted before and after the examination of the exhibit inside of the bag resulting in 120 DNA profiles. These DNA profiles were compared to DNA profiles of staff working within the building and samples taken from the exhibit inside the bag. Common DNA profile contributors from each sample were also identified through STRmix™ mixture to mixture analysis. The average DNA quantity and number of profile contributors was higher in samples taken from the bag before exhibit examination than after examination. Fifty six percent of all samples taken identified a match between DNA recovered from the evidence bag and at least one staff member. On 11 bags, a common contributor was identified between the exhibit in the bag and the exhibit package post-examination. In one instance a DNA profile, matching that of a donor, on the exhibit bag before examination was also detected on a sample taken from the exhibit, raising the possibility of outer bag-to-exhibit DNA contamination. This study demonstrates that operational forensic laboratories must consider exhibit packages as a potential source of DNA contamination and evaluate their exhibit handling and storage procedures accordingly.

When to suspect contamination rather than colonization - lessons from a putative fetal sheep microbiome.

There is an ongoing controversy around the existence of a prenatal, fetal microbiome in humans, livestock, and other animals. The 'in utero microbial colonization' hypothesis challenges the clinical paradigm of the 'sterile womb' but has been criticized for its reliance on DNA-based evidence to detect microbiomes and the failure to conciliate the routine experimental derivation of germ-free animals from surgically resected embryos with a thriving fetal microbiome. In order to avoid the propagation of misinformation in the scientific literature, a critical assessment and careful review of newly published studies, particularly those that challenge the convincing current clinical dogma of the sterile womb, is of critical importance.We read with interest a recent publication that postulated the presence of a fetal microbiome in sheep, but questioned the plausibility of the reported findings and their meaningfulness to prove "microbial colonisation of the fetal gut […] in utero". We reanalyzed the published metagenomic and metatranscriptomic sequence data from the original publication and identified evidence for different types of contamination that affected all samples alike and could explain the reported findings without requiring the existence of a fetal microbiome.Our reanalysis challenges the reported findings as supportive of a prenatal fetal lamb microbiome. The shortcomings of the original analysis and data interpretation highlight common problems of low-biomass microbiome projects. We propose genomic independence of separate biological samples, i.e. distinctive profiles at the microbial strain level, as a potential new microbiome marker to increase confidence in metagenomics analyses of controversial low-biomass microbiomes.

Estimation of intrafamilial DNA contamination in family trio genome sequencing using deviation from Mendelian inheritance.

With the increasing number of sequencing projects involving families, quality control tools optimized for family genome sequencing are needed. However, accurately quantifying contamination in a DNA mixture is particularly difficult when genetically related family members are the sources. We developed TrioMix, a maximum likelihood estimation (MLE) framework based on Mendel's law of inheritance, to quantify DNA mixture between family members in genome sequencing data of parent-offspring trios. TrioMix can accurately deconvolute any intrafamilial DNA contamination, including parent-offspring, sibling-sibling, parent-parent, and even multiple familial sources. In addition, TrioMix can be applied to detect genomic abnormalities that deviate from Mendelian inheritance patterns, such as uniparental disomy (UPD) and chimerism. A genome-wide depth and variant allele frequency plot generated by TrioMix facilitates tracing the origin of Mendelian inheritance deviations. We showed that TrioMix could accurately deconvolute genomes in both simulated and real data sets.

Precision DNA Mixture Interpretation with Single-Cell Profiling.

Wet-lab based studies have exploited emerging single-cell technologies to address the challenges of interpreting forensic mixture evidence. However, little effort has been dedicated to developing a systematic approach to interpreting the single-cell profiles derived from the mixtures. This study is the first attempt to develop a comprehensive interpretation workflow in which single-cell profiles from mixtures are interpreted individually and holistically. In this approach, the genotypes from each cell are assessed, the number of contributors (NOC) of the single-cell profiles is estimated, followed by developing a consensus profile of each contributor, and finally the consensus profile(s) can be used for a DNA database search or comparing with known profiles to determine their potential sources. The potential of this single-cell interpretation workflow was assessed by simulation with various mixture scenarios and empirical allele drop-out and drop-in rates, the accuracies of estimating the NOC, the accuracies of recovering the true alleles by consensus, and the capabilities of deconvolving mixtures with related contributors. The results support that the single-cell based mixture interpretation can provide a precision that cannot beachieved with current standard CE-STR analyses. A new paradigm for mixture interpretation is available to enhance the interpretation of forensic genetic casework.

Contamination-resistant, rapid emulsion-based isothermal nucleic acid amplification with Mie-scatter inspired light scatter analysis for bacterial identification.

An emulsion loop-mediated isothermal amplification (eLAMP) platform was developed to reduce the impact that contamination has on assay performance. Ongoing LAMP reactions within the emulsion droplets cause a decrease in interfacial tension, causing a decrease in droplet size, which results in decreased light scatter intensity due to Mie theory. Light scatter intensity was monitored via spectrophotometers and fiber optic cables placed at 30° and 60°. Light scatter intensities collected at 3 min, 30° were able to statistically differentiate 103 and 106 CFU/µL initial Escherichia coli O157:H7 concentrations compared to NTC (0 CFU/µL), while the intensity at 60° were able to statistically differentiate 106 CFU/µL initial concentrations and NTC. Control experiments were conducted to validate nucleic acid detection versus bacterial adsorption, finding that the light scatter intensities change is due specifically to ongoing LAMP amplification. After inducing contamination of bulk LAMP reagents, specificity lowered to 0% with conventional LAMP, while the eLAMP platform showed 87.5% specificity. We have demonstrated the use of angle-dependent light scatter intensity as a means of real-time monitoring of an emulsion LAMP platform and fabricated a smartphone-based monitoring system that showed similar trends as spectrophotometer light scatter data, validating the technology for a field deployable platform.

Laboratory-Generated DNA Can Cause Anomalous Pathogen Diagnostic Test Results.

The coronavirus disease 2019 (COVID-19) pandemic has brought about the unprecedented expansion of highly sensitive molecular diagnostics as a primary infection control strategy. At the same time, many laboratories have shifted focus to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research and diagnostic development, leading to large-scale production of SARS-CoV-2 nucleic acids that can interfere with these tests. We have identified multiple instances, in independent laboratories, in which nucleic acids generated in research settings are suspected to have caused researchers to test positive for SARS-CoV-2 in surveillance testing. In some cases, the affected individuals did not work directly with these nucleic acids but were exposed via a contaminated surface or object. Though researchers have long been vigilant of DNA contaminants, the transfer of these contaminants to SARS-CoV-2 testing samples can result in anomalous test results. The impact of these incidents stretches into the public sphere, placing additional burdens on public health resources, placing affected researchers and their contacts in isolation and quarantine, removing them from the testing pool for 3 months, and carrying the potential to trigger shutdowns of classrooms and workplaces. We report our observations as a call for increased stewardship over nucleic acids with the potential to impact both the use and development of diagnostics. IMPORTANCE To meet the challenges imposed by the COVID-19 pandemic, research laboratories shifted their focus and clinical diagnostic laboratories developed and utilized new assays. Nucleic acid-based testing became widespread and, for the first time, was used as a prophylactic measure. We report 15 cases of researchers at two institutes testing positive for SARS-CoV-2 on routine surveillance tests, in the absence of any symptoms or transmission. These researchers were likely contaminated with nonhazardous nucleic acids generated in the laboratory in the course of developing new SARS-CoV-2 diagnostics. These contaminating nucleic acids were persistent and widespread throughout the laboratory. We report these findings as a cautionary tale to those working with nucleic acids used in diagnostic testing and as a call for careful stewardship of diagnostically relevant molecules. Our conclusions are especially relevant as at-home COVID-19 testing gains traction in the marketplace and these amplicons may impact on the general public.

STAT: a fast, scalable, MinHash-based k-mer tool to assess Sequence Read Archive next-generation sequence submissions.

Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k-mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k-mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms.