Determination of RNA structural diversity and its role in HIV-1 RNA splicing.

Human immunodeficiency virus 1 (HIV-1) is a retrovirus with a ten-kilobase single-stranded RNA genome. HIV-1 must express all of its gene products from a single primary transcript, which undergoes alternative splicing to produce diverse protein products that include structural proteins and regulatory factors1,2. Despite the critical role of alternative splicing, the mechanisms that drive the choice of splice site are poorly understood. Synonymous RNA mutations that lead to severe defects in splicing and viral replication indicate the presence of unknown cis-regulatory elements3. Here we use dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) to investigate the structure of HIV-1 RNA in cells, and develop an algorithm that we name 'detection of RNA folding ensembles using expectation-maximization' (DREEM), which reveals the alternative conformations that are assumed by the same RNA sequence. Contrary to previous models that have analysed population averages4, our results reveal heterogeneous regions of RNA structure across the entire HIV-1 genome. In addition to confirming that in vitro characterized5 alternative structures for the HIV-1 Rev responsive element also exist in cells, we discover alternative conformations at critical splice sites that influence the ratio of transcript isoforms. Our simultaneous measurement of splicing and intracellular RNA structure provides evidence for the long-standing hypothesis6-8 that heterogeneity in RNA conformation regulates splice-site use and viral gene expression.

Author Correction: Determination of RNA structural diversity and its role in HIV-1 RNA splicing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Towards developing forensically relevant single-cell pipelines by incorporating direct-to-PCR extraction: compatibility, signal quality, and allele detection.

Current analysis of forensic DNA stains relies on the probabilistic interpretation of bulk-processed samples that represent mixed profiles consisting of an unknown number of potentially partial representations of each contributor. Single-cell methods, in contrast, offer a solution to the forensic DNA mixture problem by incorporating a step that separates cells before extraction. A forensically relevant single-cell pipeline relies on efficient direct-to-PCR extractions that are compatible with standard downstream forensic reagents. Here we demonstrate the feasibility of implementing single-cell pipelines into the forensic process by exploring four metrics of electropherogram (EPG) signal quality-i.e., allele detection rates, peak heights, peak height ratios, and peak height balance across low- to high-molecular-weight short tandem repeat (STR) markers-obtained with four direct-to-PCR extraction treatments and a common post-PCR laboratory procedure. Each treatment was used to extract DNA from 102 single buccal cells, whereupon the amplification reagents were immediately added to the tube and the DNA was amplified/injected using post-PCR conditions known to elicit a limit of detection (LoD) of one DNA molecule. The results show that most cells, regardless of extraction treatment, rendered EPGs with at least a 50% true positive allele detection rate and that allele drop-out was not cell independent. Statistical tests demonstrated that extraction treatments significantly impacted all metrics of EPG quality, where the Arcturus® PicoPure™ extraction method resulted in the lowest median allele drop-out rate, highest median average peak height, highest median average peak height ratio, and least negative median values of EPG sloping for GlobalFiler™ STR loci amplified at half volume. We, therefore, conclude the feasibility of implementing single-cell pipelines for casework purposes and demonstrate that inferential systems assuming cell independence will not be appropriate in the probabilistic interpretation of a collection of single-cell EPGs.

Viral RNA structure analysis using DMS-MaPseq.

RNA structure is critically important to RNA viruses in every part of the replication cycle. RNA structure is also utilized by DNA viruses in order to regulate gene expression and interact with host factors. Advances in next-generation sequencing have greatly enhanced the utility of chemical probing in order to analyze RNA structure. This review will cover some recent viral RNA structural studies using chemical probing and next-generation sequencing as well as the advantages of dimethyl sulfate (DMS)-mutational profiling and sequencing (MaPseq). DMS-MaPseq is a robust assay that can easily modify RNA in vitro, in cell and in virion. A detailed protocol for whole-genome DMS-MaPseq from cells transfected with HIV-1 and the structure of TAR as determined by DMS-MaPseq is presented. DMS-MaPseq has the ability to answer a variety of integral questions about viral RNA, including how they change in different environments and when interacting with different host factors.

Structure of anellovirus-like particles reveal a mechanism for immune evasion.

Anelloviruses are nonpathogenic viruses that comprise a major portion of the human virome. Despite being ubiquitous in the human population, anelloviruses (ANVs) remain poorly understood. Basic features of the virus, such as the identity of its capsid protein and the structure of the viral particle, have been unclear until now. Here, we use cryogenic electron microscopy to describe the first structure of an ANV-like particle. The particle, formed by 60 jelly roll domain-containing ANV capsid proteins, forms an icosahedral particle core from which spike domains extend to form a salient part of the particle surface. The spike domains come together around the 5-fold symmetry axis to form crown-like features. The base of the spike domain, the P1 subdomain, shares some sequence conservation between ANV strains while a hypervariable region, forming the P2 subdomain, is at the spike domain apex. We propose that this structure renders the particle less susceptible to antibody neutralization by hiding vulnerable conserved domains while exposing highly diverse epitopes as immunological decoys, thereby contributing to the immune evasion properties of anelloviruses. These results shed light on the structure of anelloviruses and provide a framework to understand their interactions with the immune system.

Comprehensive profiling of antibody responses to the human anellome using programmable phage display.

Anelloviruses represent a major constituent of the commensal human virome; however, little is known about their immunobiology. Here, we present "AnelloScan," a T7 phage library representing the open reading frame 1 (ORF1), ORF2, ORF3, and torque teno virus (TTV)-derived apoptosis-inducing protein (TAIP) sequences of more than 800 human anelloviruses and profile the antibody reactivities of serum samples from a cross-sectional cohort of 156 subjects by using phage-immunoprecipitation sequencing (PhIP-Seq). A majority of anellovirus peptides are not reactive in any of the subjects tested (n = ∼28,000; ∼85% of the library). Antibody-reactive peptides are largely restricted to the C-terminal region of the capsid protein ORF1. Moreover, using a longitudinal cohort of matched blood-transfusion donors and recipients, we find that most transmitted anelloviruses do not elicit a detectable antibody reactivity in the recipient and that the remainder elicit delayed responses appearing ∼100-150 days after transfusion.

DMS-MaPseq for Genome-Wide or Targeted RNA Structure Probing In Vitro and In Vivo.

DMS-MaPseq is a chemical probing method combined with high throughput sequencing used to study RNA structure. Here we present a flexible protocol for adherent and suspension mammalian cells to analyze RNA structure in vitro or in vivo. The protocol provides instruction on either a targeted sequencing of a lncRNA of interest or a transcriptome-wide approach that provides structural data on all expressed RNAs, including lncRNAs. This technique is particularly useful for comparing in vitro and in vivo structure of RNAs, determining how mutations and polymorphisms with phenotypic effects influence RNA structure and analyzing RNA structure across the entire transcriptome.

Global genome analysis reveals a vast and dynamic anellovirus landscape within the human virome.

Anelloviruses are a ubiquitous component of healthy human viromes and remain highly prevalent after being acquired early in life. The full extent of "anellome" diversity and its evolutionary dynamics remain unexplored. We employed in-depth sequencing of blood-transfusion donor(s)-recipient pairs coupled with public genomic resources for a large-scale assembly of anellovirus genomes and used the data to characterize global and personal anellovirus diversity through time. The breadth of the anellome is much greater than previously appreciated, and individuals harbor unique anellomes and transmit lineages that can persist for several months within a diverse milieu of endemic host lineages. Anellovirus sequence diversity is shaped by extensive recombination at all levels of divergence, hindering traditional phylogenetic analyses. Our findings illuminate the transmission dynamics and vast diversity of anelloviruses and set the foundation for future studies to characterize their biology.

Four model variants within a continuous forensic DNA mixture interpretation framework: Effects on evidential inference and reporting.

Continuous mixture interpretation methods that employ probabilistic genotyping to compute the Likelihood Ratio (LR) utilize more information than threshold-based systems. The continuous interpretation schemes described in the literature, however, do not all use the same underlying probabilistic model and standards outlining which probabilistic models may or may not be implemented into casework do not exist; thus, it is the individual forensic laboratory or expert that decides which model and corresponding software program to implement. For countries, such as the United States, with an adversarial legal system, one can envision a scenario where two probabilistic models are used to present the weight of evidence, and two LRs are presented by two experts. Conversely, if no independent review of the evidence is requested, one expert using one model may present one LR as there is no standard or guideline requiring the uncertainty in the LR estimate be presented. The choice of model determines the underlying probability calculation, and changes to it can result in non-negligible differences in the reported LR or corresponding verbal categorization presented to the trier-of-fact. In this paper, we study the impact of model differences on the LR and on the corresponding verbal expression computed using four variants of a continuous mixture interpretation method. The four models were tested five times each on 101, 1-, 2- and 3-person experimental samples with known contributors. For each sample, LRs were computed using the known contributor as the person of interest. In all four models, intra-model variability increased with an increase in the number of contributors and with a decrease in the contributor's template mass. Inter-model variability in the associated verbal expression of the LR was observed in 32 of the 195 LRs used for comparison. Moreover, in 11 of these profiles there was a change from LR > 1 to LR < 1. These results indicate that modifications to existing continuous models do have the potential to significantly impact the final statistic, justifying the continuation of broad-based, large-scale, independent studies to quantify the limits of reliability and variability of existing forensically relevant systems.

Establishing a stable, repeatable platform for measuring changes in sperm DNA methylation.

BACKGROUND: Several independent research groups have shown that alterations in human sperm methylation profiles correlate with decreased fecundity and an increased risk of poor embryo development. Moving these initial findings from the lab into a clinical setting where they can be used to measure male infertility though requires a platform that is stable and robust against batch effects that can occur between sample runs. Operating parameters must be established, performance characteristics determined, and guidelines set to ensure repeatability and accuracy. The standard for technical validation of a lab developed test (LDT) in the USA comes from the Clinical Laboratory Improvement Amendments (CLIA). However, CLIA was introduced in 1988, before the advent of genome-wide profiling and associated computational analysis. This, coupled with its intentionally general nature, makes its interpretation for epigenetic assays non-trivial. RESULTS: Here, we present an interpretation of the CLIA technical validation requirements for profiling DNA methylation and calling aberrant methylation using the Illumina Infinium platform (e.g., the 450HM and MethylationEPIC). We describe an experimental design to meet these requirements, the experimental results obtained, and the operating parameters established. CONCLUSIONS: The CLIA guidelines, although not intended for high-throughput assays, can be interpreted in a way that is consistent with modern epigenetic assays. Based on such an interoperation, Illumina's Infinium platform is quite amenable to usage in a clinical setting for diagnostic work.

Production of high-fidelity electropherograms results in improved and consistent DNA interpretation: Standardizing the forensic validation process.

Samples containing low-copy numbers of DNA are routinely encountered in casework. The signal acquired from these sample types can be difficult to interpret as they do not always contain all of the genotypic information from each contributor, where the loss of genetic information is associated with sampling and detection effects. The present work focuses on developing a validation scheme to aid in mitigating the effects of the latter. We establish a scheme designed to simultaneously improve signal resolution and detection rates without costly large-scale experimental validation studies by applying a combined simulation and experimental based approach. Specifically, we parameterize an in silico DNA pipeline with experimental data acquired from the laboratory and use this to evaluate multifarious scenarios in a cost-effective manner. Metrics such as signal1copy-to-noise resolution, false positive and false negative signal detection rates are used to select tenable laboratory parameters that result in high-fidelity signal in the single-copy regime. We demonstrate that the metrics acquired from simulation are consistent with experimental data obtained from two capillary electrophoresis platforms and various injection parameters. Once good resolution is obtained, analytical thresholds can be determined using detection error tradeoff analysis, if necessary. Decreasing the limit of detection of the forensic process to one copy of DNA is a powerful mechanism by which to increase the information content on minor components of a mixture, which is particularly important for probabilistic system inference. If the forensic pipeline is engineered such that high-fidelity electropherogram signal is obtained, then the likelihood ratio (LR) of a true contributor increases and the probability that the LR of a randomly chosen person is greater than one decreases. This is, potentially, the first step towards standardization of the analytical pipeline across operational laboratories.

Inferring the Number of Contributors to Complex DNA Mixtures Using Three Methods: Exploring the Limits of Low-Template DNA Interpretation.

In forensic DNA casework, the interpretation of an evidentiary profile may be dependent upon the assumption on the number of individuals from whom the evidence arose. Three methods of inferring the number of contributors-NOCIt, maximum likelihood estimator, and maximum allele count, were evaluated using 100 test samples consisting of one to five contributors and 0.5-0.016 ng template DNA amplified with Identifiler® Plus and PowerPlex® 16 HS. Results indicate that NOCIt was the most accurate method of the three, requiring 0.07 ng template DNA from any one contributor to consistently estimate the true number of contributors. Additionally, NOCIt returned repeatable results for 91% of samples analyzed in quintuplicate, while 50 single-source standards proved sufficient to calibrate the software. The data indicate that computational methods that employ a quantitative, probabilistic approach provide improved accuracy and additional pertinent information such as the uncertainty associated with the inferred number of contributors.

CEESIt: A computational tool for the interpretation of STR mixtures.

In forensic DNA interpretation, the likelihood ratio (LR) is often used to convey the strength of a match. Expanding on binary and semi-continuous methods that do not use all of the quantitative data contained in an electropherogram, fully continuous methods to calculate the LR have been created. These fully continuous methods utilize all of the information captured in the electropherogram, including the peak heights. Recently, methods that calculate the distribution of the LR using semi-continuous methods have also been developed. The LR distribution has been proposed as a way of studying the robustness of the LR, which varies depending on the probabilistic model used for its calculation. For example, the LR distribution can be used to calculate the p-value, which is the probability that a randomly chosen individual results in a LR greater than the LR obtained from the person-of-interest (POI). Hence, the p-value is a statistic that is different from, but related to, the LR; and it may be interpreted as the false positive rate resulting from a binary hypothesis test between the prosecution and defense hypotheses. Here, we present CEESIt, a method that combines the twin features of a fully continuous model to calculate the LR and its distribution, conditioned on the defense hypothesis, along with an associated p-value. CEESIt incorporates dropout, noise and stutter (reverse and forward) in its calculation. As calibration data, CEESIt uses single source samples with known genotypes and calculates a LR for a specified POI on a question sample, along with the LR distribution and a p-value. The method was tested on 303 files representing 1-, 2- and 3-person samples injected using three injection times containing between 0.016 and 1 ng of template DNA. Our data allows us to evaluate changes in the LR and p-value with respect to the complexity of the sample and to facilitate discussions regarding complex DNA mixture interpretation. We observed that the amount of template DNA from the contributor impacted the LR--small LRs resulted from contributors with low template masses. Moreover, as expected, we observed a decrease of p-values as the LR increased. A p-value of 10(-9) or lower was achieved in all the cases where the LR was greater than 10(8). We tested the repeatability of CEESIt by running all samples in duplicate and found the results to be repeatable.

NOCIt: a computational method to infer the number of contributors to DNA samples analyzed by STR genotyping.

Repetitive sequences in the human genome called short tandem repeats (STRs) are used in human identification for forensic purposes. Interpretation of DNA profiles generated using STRs is often problematic because of uncertainty in the number of contributors to the sample. Existing methods to identify the number of contributors work on the number of peaks observed and/or allele frequencies. We have developed a computational method called NOCIt that calculates the a posteriori probability (APP) on the number of contributors. NOCIt works on single source calibration data consisting of known genotypes to compute the APP for an unknown sample. The method takes into account signal peak heights, population allele frequencies, allele dropout and stutter-a commonly occurring PCR artifact. We tested the performance of NOCIt using 278 experimental and 40 simulated DNA mixtures consisting of one to five contributors with total DNA mass from 0.016 to 0.25ng. NOCIt correctly identified the number of contributors in 83% of the experimental samples and in 85% of the simulated mixtures, while the accuracy of the best pre-existing method to determine the number of contributors was 72% for the experimental samples and 73% for the simulated mixtures. Moreover, NOCIt calculated the APP for the true number of contributors to be at least 1% in 95% of the experimental samples and in all the simulated mixtures.

Equivalent T cell epitope promiscuity in ecologically diverse human pathogens.

BACKGROUND: The HLA (human leukocyte antigen) molecules that present pathogen-derived epitopes to T cells are highly diverse. Correspondingly, many pathogens such as HIV evolve epitope variants in order to evade immune recognition. In contrast, another persistent human pathogen, Mycobacterium tuberculosis, has highly conserved epitope sequences. This raises the question whether there is also a difference in the ability of these pathogens' epitopes to bind diverse HLA alleles, referred to as an epitope's binding promiscuity. To address this question, we compared the in silico HLA binding promiscuity of T cell epitopes from pathogens with distinct infection strategies and outcomes of human exposure. METHODS: We used computer algorithms to predict the binding affinity of experimentally-verified microbial epitope peptides to diverse HLA-DR, HLA-A and HLA-B alleles. We then analyzed binding promiscuity of epitopes derived from HIV and M. tuberculosis. We also analyzed promiscuity of epitopes from Streptococcus pyogenes, which is known to exhibit epitope diversity, and epitopes of Bacillus anthracis and Clostridium tetani toxins, as these bacteria do not depend on human hosts for their survival or replication, and their toxin antigens are highly immunogenic human vaccines. RESULTS: We found that B. anthracis and C. tetani epitopes were the most promiscuous of the group that we analyzed. However, there was no consistent difference or trend in promiscuity in epitopes contained in HIV, M. tuberculosis, and S. pyogenes. CONCLUSIONS: Our results show that human pathogens with distinct immune evasion strategies and epitope diversities exhibit equivalent levels of T cell epitope promiscuity. These results indicate that differences in epitope promiscuity do not account for the observed differences in epitope variation and conservation.