Endogenous retroelement expression in the gut microenvironment of people living with HIV-1

BACKGROUND

Endogenous retroelements (EREs), including human endogenous retroviruses (HERVs) and long interspersed nuclear elements (LINEs), comprise almost half of the human genome. Our previous studies of the interferome in the gut suggest potential mechanisms regarding how IFNb may drive HIV-1 gut pathogenesis. As ERE activity is suggested to partake in type 1 immune responses and is incredibly sensitive to viral infections, we sought to elucidate underlying interactions between ERE expression and gut dynamics in people living with HIV-1 (PLWH).

METHODS

ERE expression profiles from bulk RNA sequencing of colon biopsies and PBMC were compared between a cohort of PLWH not on antiretroviral therapy (ART) and uninfected controls.

FINDINGS

59 EREs were differentially expressed in the colon of PLWH when compared to uninfected controls (padj <0.05 and FC ≤ -1 or ≥ 1) [Wald's Test]. Of these 59, 12 EREs were downregulated in PLWH and 47 were upregulated. Colon expression of the ERE loci LTR19_12p13.31 and L1FLnI_1q23.1s showed significant correlations with certain gut immune cell subset frequencies in the colon. Furthermore L1FLnI_1q23.1s showed a significant upregulation in peripheral blood mononuclear cells (PBMCs) of PLWH when compared to uninfected controls suggesting a common mechanism of differential ERE expression in the colon and PBMC.

INTERPRETATION

ERE activity has been largely understudied in genomic characterizations of human pathologies. We show that the activity of certain EREs in the colon of PLWH is deregulated, supporting our hypotheses that their underlying activity could function as (bio)markers and potential mediators of pathogenesis in HIV-1 reservoirs.

FUNDING

US NIH grants NCI CA260691 (DFN) and NIAID UM1AI164559 (DFN).

Ribosomal profiling of human endogenous retroviruses in healthy tissues

Human endogenous retroviruses (HERVs) are the germline embedded proviral fragments of ancient retroviral infections that make up roughly 8% of the human genome. Our understanding of HERVs in physiology primarily surrounds their non-coding functions, while their protein coding capacity remains virtually uncharacterized. Therefore, we applied the bioinformatic pipeline "hervQuant" to high-resolution ribosomal profiling of healthy tissues to provide a comprehensive overview of translationally active HERVs. We find that HERVs account for 0.1-0.4% of all translation in distinct tissue-specific profiles. Collectively, our study further supports claims that HERVs are actively translated throughout healthy tissues to provide sequences of retroviral origin to the human proteome.

A single-cell transposable element atlas of human cell identity

Single cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex biological systems. However, most sequencing studies overlook the contribution of transposable element (TE) expression to the transcriptome. In both scRNA-seq and bulk tissue RNA sequencing (RNA-seq), quantification of TE expression is challenging due to repetitive sequence content and poorly characterized TE gene models. Here, we developed a tool and analysis pipeline for Single cell Transposable Element Locus Level Analysis of scRNA Sequencing (Stellarscope) that reassigns multi-mapped reads to specific genomic loci using an expectation-maximization algorithm. Using Stellarscope, we built an atlas of TE expression in human PBMCs. We found that locus-specific TEs delineate cell types and define new cell subsets not identified by standard mRNA expression profiles. Altogether, this study provides comprehensive insights into the influence of transposable elements in human biology.

Transposable elements may enhance antiviral resistance in HIV-1 elite controllers

Less than 0.5% of people living with HIV-1 are elite controllers (ECs) - individuals who have a replication-competent viral reservoir in their CD4+ T cells but maintain undetectable plasma viremia without the help of antiretroviral therapy. While the EC CD4+ T cell transcriptome has been investigated for gene expression signatures associated with disease progression (or, in this case, a lack thereof), the expression and regulatory activity of transposable elements (TEs) in ECs has not been explored. Yet previous studies have established that TEs can directly impact the immune response to pathogens, including HIV-1. Thus, we hypothesize that the regulatory activities of TEs could contribute to the natural resistance of ECs against HIV-1. We perform a TE-centric analysis of previously published multi-omics data derived from EC individuals and other populations. We find that the CD4+ T cell transcriptome and retrotranscriptome of ECs are distinct from healthy controls, treated patients, and viremic progressors. However, there is a substantial level of transcriptomic heterogeneity among ECs. We categorize individuals with distinct chromatin accessibility and expression profiles into four clusters within the EC group, each possessing unique repertoires of TEs and antiviral factors. Notably, several TE families with known immuno-regulatory activity are differentially expressed among ECs. Their transcript levels in ECs positively correlate with their chromatin accessibility and negatively correlate with the expression of their KRAB zinc-finger (KZNF) repressors. This coordinated variation is seen at the level of individual TE loci likely acting or, in some cases, known to act as cis-regulatory elements for nearby genes involved in the immune response and HIV-1 restriction. Based on these results, we propose that the EC phenotype is driven in part by the reduced availability of specific KZNF proteins to repress TE-derived cis-regulatory elements for antiviral genes, thereby heightening their basal level of resistance to HIV-1 infection. Our study reveals considerable heterogeneity in the CD4+ T cell transcriptome of ECs, including variable expression of TEs and their KZNF controllers, that must be taken into consideration to decipher the mechanisms enabling HIV-1 control.

Retroelement-Age Clocks: Epigenetic Age Captured by Human Endogenous Retrovirus and LINE-1 DNA methylation states

Human endogenous retroviruses (HERVs), the remnants of ancient viral infections embedded within the human genome, and long interspersed nuclear elements 1 (LINE-1), a class of autonomous retrotransposons, are silenced by host epigenetic mechanisms including DNA methylation. The resurrection of particular retroelements has been linked to biological aging. Whether the DNA methylation states of locus specific HERVs and LINEs can be used as a biomarker of chronological age in humans remains unclear. We show that highly predictive epigenetic clocks of chronological age can be constructed from retroelement DNA methylation states in the immune system, across human tissues, and pan-mammalian species. We found retroelement epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, responsive to antiretroviral therapy, and accurate in estimating long-term culture ages of human brain organoids. Our findings support the hypothesis of epigenetic dysregulation of retroelements as a potential contributor to the biological hallmarks of aging.

Oncogenic Transformation Drives DNA Methylation Loss and Transcriptional Activation at Transposable Element Loci

Transposable elements (TE) are typically silenced by DNA methylation and repressive histone modifications in differentiated healthy human tissues. However, TE expression increases in a wide range of cancers and is correlated with global hypomethylation of cancer genomes. We assessed expression and DNA methylation of TEs in fibroblast cells that were serially transduced with hTERT, SV40, and HRASR24C to immortalize and then transform them, modeling the different steps of the tumorigenesis process. RNA sequencing and whole-genome bisulfite sequencing were performed at each stage of transformation. TE expression significantly increased as cells progressed through transformation, with the largest increase in expression after the final stage of transformation, consistent with data from human tumors. The upregulated TEs were dominated by endogenous retroviruses [long terminal repeats (LTR)]. Most differentially methylated regions (DMR) in all stages were hypomethylated, with the greatest hypomethylation in the final stage of transformation. A majority of the DMRs overlapped TEs from the RepeatMasker database, indicating that TEs are preferentially demethylated. Many hypomethylated TEs displayed a concordant increase in expression. Demethylation began during immortalization and continued into transformation, while upregulation of TE transcription occurred in transformation. Numerous LTR elements upregulated in the model were also identified in The Cancer Genome Atlas datasets of breast, colon, and prostate cancer. Overall, these findings indicate that TEs, specifically endogenous retroviruses, are demethylated and transcribed during transformation.

SIGNIFICANCE

Analysis of epigenetic and transcriptional changes in a transformation model reveals that transposable element expression and methylation are dysregulated during oncogenic transformation.

Locus specific human endogenous retroviruses reveal new lymphoma subtypes

The heterogeneity of cancers are driven by diverse mechanisms underlying oncogenesis such as differential 'cell-of-origin' (COO) progenitors, mutagenesis, and viral infections. Classification of B-cell lymphomas have been defined by considering these characteristics. However, the expression and contribution of transposable elements (TEs) to B cell lymphoma oncogenesis or classification have been overlooked. We hypothesized that incorporating TE signatures would increase the resolution of B-cell identity during healthy and malignant conditions. Here, we present the first comprehensive, locus-specific characterization of TE expression in benign germinal center (GC) B-cells, diffuse large B-cell lymphoma (DLBCL), Epstein-Barr virus (EBV)-positive and EBV-negative Burkitt lymphoma (BL), and follicular lymphoma (FL). Our findings demonstrate unique human endogenous retrovirus (HERV) signatures in the GC and lymphoma subtypes whose activity can be used in combination with gene expression to define B-cell lineage in lymphoid malignancies, highlighting the potential of retrotranscriptomic analyses as a tool in lymphoma classification, diagnosis, and the identification of novel treatment groups.

Naso-oropharyngeal microbiome from breast cancer patients diagnosed with COVID-19

Due to immunosuppressive cancer therapies, cancer patients diagnosed with COVID-19 have a higher chance of developing severe symptoms and present a higher mortality rate in comparison to the general population. Here we show a comparative analysis of the microbiome from naso-oropharyngeal samples of breast cancer patients with respect to SARS-CoV-2 status and identified bacteria associated with symptom severity. Total DNA of naso-oropharyngeal swabs from 74 women with or without breast cancer, positive or negative for SARS-CoV-2 were PCR-amplified for 16S-rDNA V3 and V4 regions and submitted to massive parallel sequencing. Sequencing data were analyzed with QIIME2 and taxonomic identification was performed using the q2-feature-classifier QIIME2 plugin, the Greengenes Database, and amplicon sequence variants (ASV) analysis. A total of 486 different bacteria were identified. No difference was found in taxa diversity between sample groups. Cluster analysis did not group the samples concerning SARS-CoV-2 status, breast cancer diagnosis, or symptom severity. Three taxa (Pseudomonas, Moraxella, and Klebsiella,) showed to be overrepresented in women with breast cancer and positive for SARS-CoV-2 when compared to the other women groups, and five bacterial groups were associated with COVID-19 severity among breast cancer patients: Staphylococcus, Staphylococcus epidermidis, Scardovia, Parasegitibacter luogiensis, and Thermomonas. The presence of Staphylococcus in COVID-19 breast cancer patients may possibly be a consequence of nosocomial infection.

Specific human endogenous retroviruses predict metastatic potential in uveal melanoma

Uveal melanoma (UM) is a unique disease in that patients with primary UM are well stratified based on their risk of developing metastasis, yet there are limited effective treatments once metastases occur. There is an urgent need to better understand the distinct molecular pathogenesis of UM and the characteristics of patients at high risk for metastasis to identify neoantigenic targets that can be used in immunotherapy and to develop novel therapeutic strategies that may effectively target this lethal transition. An important and overlooked area of molecular pathogenesis and neoantigenic targets in UM comes from human endogenous retroviruses (HERVs). We investigated the HERV expression landscape in primary UM and found that tumors were stratified into 4 HERV-based subsets that provide clear delineation of risk outcome and support subtypes identified by other molecular indicators. Specific HERV loci are associated with the risk of uveal melanoma metastasis and may offer mechanistic insights into this process, including dysregulation of HERVs on chromosomes 3 and 8. A HERV signature composed of 17 loci was sufficient to classify tumors according to subtype with greater than 95% accuracy, including at least 1 intergenic HERV with coding potential (HERVE_Xp11.23) that could represent a potential HERV E target for immunotherapy.

SARS-CoV-2 infection mediates differential expression of human endogenous retroviruses and long interspersed nuclear elements

SARS-CoV-2 promotes an imbalanced host response that underlies the development and severity of COVID-19. Infections with viruses are known to modulate transposable elements (TEs), which can exert downstream effects by modulating host gene expression, innate immune sensing, or activities encoded by their protein products. We investigated the impact of SARS-CoV-2 infection on TE expression using RNA-Seq data from cell lines and from primary patient samples. Using a bioinformatics tool, Telescope, we showed that SARS-CoV-2 infection led to upregulation or downregulation of TE transcripts, a subset of which differed from cells infected with SARS, Middle East respiratory syndrome coronavirus (MERS-CoV or MERS), influenza A virus (IAV), respiratory syncytial virus (RSV), and human parainfluenza virus type 3 (HPIV3). Differential expression of key retroelements specifically identified distinct virus families, such as Coronaviridae, with unique retroelement expression subdividing viral species. Analysis of ChIP-Seq data showed that TEs differentially expressed in SARS-CoV-2 infection were enriched for binding sites for transcription factors involved in immune responses and for pioneer transcription factors. In samples from patients with COVID-19, there was significant TE overexpression in bronchoalveolar lavage fluid and downregulation in PBMCs. Thus, although the host gene transcriptome is altered by infection with SARS-CoV-2, the retrotranscriptome may contain the most distinctive features of the cellular response to SARS-CoV-2 infection.

HAPHPIPE: Haplotype Reconstruction and Phylodynamics for Deep Sequencing of Intrahost Viral Populations

Deep sequencing of viral populations using next-generation sequencing (NGS) offers opportunities to understand and investigate evolution, transmission dynamics, and population genetics. Currently, the standard practice for processing NGS data to study viral populations is to summarize all the observed sequences from a sample as a single consensus sequence, thus discarding valuable information about the intrahost viral molecular epidemiology. Furthermore, existing analytical pipelines may only analyze genomic regions involved in drug resistance, thus are not suited for full viral genome analysis. Here, we present HAPHPIPE, a HAplotype and PHylodynamics PIPEline for genome-wide assembly of viral consensus sequences and haplotypes. The HAPHPIPE protocol includes modules for quality trimming, error correction, de novo assembly, alignment, and haplotype reconstruction. The resulting consensus sequences, haplotypes, and alignments can be further analyzed using a variety of phylogenetic and population genetic software. HAPHPIPE is designed to provide users with a single pipeline to rapidly analyze sequences from viral populations generated from NGS platforms and provide quality output properly formatted for downstream evolutionary analyses.

Locus-Specific Characterization of Human Endogenous Retrovirus Expression in Prostate, Breast, and Colon Cancers

Human endogenous retroviruses (HERV) have been implicated in a variety of diseases including cancers. Recent research implicates HERVs in epigenetic gene regulation. Here we utilize a recently developed bioinformatics tool for identifying HERV expression at the locus-specific level to identify differential expression of HERVs in matched tumor-normal RNA-sequencing (RNA-seq) data from The Cancer Genome Atlas. Data from 52 prostate cancer, 111 breast cancer, and 24 colon cancer cases were analyzed. Locus-specific analysis identified active HERV elements and differentially expressed HERVs in prostate cancer, breast cancer, and colon cancer. In addition, differentially expressed host genes were identified across prostate, breast, and colon cancer datasets, respectively, including several involved in demethylation and antiviral response pathways, supporting previous findings regarding the pathogenic mechanisms of HERVs. A majority of differentially expressed HERVs intersected protein coding genes or lncRNAs in each dataset, and a subset of differentially expressed HERVs intersected differentially expressed genes in prostate, breast, and colon cancers, providing evidence towards regulatory function. Finally, patterns in HERV expression were identified in multiple cancer types, with 155 HERVs differentially expressed in all three cancer types. This analysis extends previous results identifying HERV transcription in cancer RNA-seq datasets to a locus-specific level, and in doing so provides a foundation for future studies investigating the functional role of HERV in cancers and identifies a number of novel targets for cancer biomarkers and immunotherapy. SIGNIFICANCE: Expressed human endogenous retroviruses are mapped at locus-specific resolution and linked to specific pathways to identify potential biomarkers and therapeutic targets in prostate, breast, and colon cancers.

Expression of Human Endogenous Retroviruses in Systemic Lupus Erythematosus: Multiomic Integration With Gene Expression

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by the production of autoantibodies predominantly to nuclear material. Many aspects of disease pathology are mediated by the deposition of nucleic acid containing immune complexes, which also induce the type 1interferon response, a characteristic feature of SLE. Notably, SLE is remarkably heterogeneous, with a variety of organs involved in different individuals, who also show variation in disease severity related to their ancestries. Here, we probed one potential contribution to disease heterogeneity as well as a possible source of immunoreactive nucleic acids by exploring the expression of human endogenous retroviruses (HERVs). We investigated the expression of HERVs in SLE and their potential relationship to SLE features and the expression of biochemical pathways, including the interferon gene signature (IGS). Towards this goal, we analyzed available and new RNA-Seq data from two independent whole blood studies using Telescope. We identified 481 locus specific HERV encoding regions that are differentially expressed between case and control individuals with only 14% overlap of differentially expressed HERVs between these two datasets. We identified significant differences between differentially expressed HERVs and non-differentially expressed HERVs between the two datasets. We also characterized the host differentially expressed genes and tested their association with the differentially expressed HERVs. We found that differentially expressed HERVs were significantly more physically proximal to host differentially expressed genes than non-differentially expressed HERVs. Finally, we capitalized on locus specific resolution of HERV mapping to identify key molecular pathways impacted by differential HERV expression in people with SLE.

Human Endogenous Retrovirus Expression Is Upregulated in the Breast Cancer Microenvironment of HIV Infected Women: A Pilot Study

In people living with HIV (PLWH), chronic inflammation can lead to cancer initiation and progression, besides driving a dysregulated and diminished immune responsiveness. HIV infection also leads to increased transcription of Human Endogenous Retroviruses (HERVs), which could increase an inflammatory environment and create a tumor growth suppressive environment with high expression of pro-inflammatory cytokines. In order to determine the impact of HIV infection to HERV expression on the breast cancer microenvironment, we sequenced total RNA from formalin-fixed paraffin-embedded (FFPE) breast cancer samples of women HIV-negative and HIV-positive for transcriptome and retrotranscriptome analyses. We performed RNA extraction from FFPE samples, library preparation and total RNA sequencing (RNA-seq). The RNA-seq analysis shows 185 differentially expressed genes: 181 host genes (178 upregulated and three downregulated) and four upregulated HERV transcripts in HIV-positive samples. We also explored the impact of HERV expression in its neighboring breast cancer development genes (BRCA1, CCND1, NBS1/NBN, RAD50, KRAS, PI3K/PIK3CA) and in long non-coding RNA expression (AC060780.1, also known as RP11-242D8.1). We found a significant positive association of HERV expression with RAD50 and with AC060780.1, which suggest a possible role of HERV in regulating breast cancer genes from PLWH with breast cancer. In addition, we found immune system, extracellular matrix organization and metabolic signaling genes upregulated in HIV-positive breast cancer. In conclusion, our findings provide evidence of transcriptional and retrotranscriptional changes in breast cancer from PLWH compared to non-HIV breast cancer, including dysregulation of HERVs, suggesting an indirect effect of the virus on the breast cancer microenvironment.

Evaluation of haplotype callers for next-generation sequencing of viruses

Currently, the standard practice for assembling next-generation sequencing (NGS) reads of viral genomes is to summarize thousands of individual short reads into a single consensus sequence, thus confounding useful intra-host diversity information for molecular phylodynamic inference. It is hypothesized that a few viral strains may dominate the intra-host genetic diversity with a variety of lower frequency strains comprising the rest of the population. Several software tools currently exist to convert NGS sequence variants into haplotypes. Previous benchmarks of viral haplotype reconstruction programs used simulation scenarios that are useful from a mathematical perspective but do not reflect viral evolution and epidemiology. Here, we tested twelve NGS haplotype reconstruction methods using viral populations simulated under realistic evolutionary dynamics. We simulated coalescent-based populations that spanned known levels of viral genetic diversity, including mutation rates, sample size and effective population size, to test the limits of the haplotype reconstruction methods and to ensure coverage of predicted intra-host viral diversity levels (especially HIV-1). All twelve investigated haplotype callers showed variable performance and produced drastically different results that were mainly driven by differences in mutation rate and, to a lesser extent, in effective population size. Most methods were able to accurately reconstruct haplotypes when genetic diversity was low. However, under higher levels of diversity (e.g., those seen intra-host HIV-1 infections), haplotype reconstruction quality was highly variable and, on average, poor. All haplotype reconstruction tools, except QuasiRecomb and ShoRAH, greatly underestimated intra-host diversity and the true number of haplotypes. PredictHaplo outperformed, in regard to highest precision, recall, and lowest UniFrac distance values, the other haplotype reconstruction tools followed by CliqueSNV, which, given more computational time, may have outperformed PredictHaplo. Here, we present an extensive comparison of available viral haplotype reconstruction tools and provide insights for future improvements in haplotype reconstruction tools using both short-read and long-read technologies.

Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.

A cross-sectional study to characterize local HIV-1 dynamics in Washington, DC using next-generation sequencing

Washington, DC continues to experience a generalized HIV-1 epidemic. We characterized the local phylodynamics of HIV-1 in DC using next-generation sequencing (NGS) data. Viral samples from 68 participants from 2016 through 2017 were sequenced and paired with epidemiological data. Phylogenetic and network inferences, drug resistant mutations (DRMs), subtypes and HIV-1 diversity estimations were completed. Haplotypes were reconstructed to infer transmission clusters. Phylodynamic inferences based on the HIV-1 polymerase (pol) and envelope genes (env) were compared. Higher HIV-1 diversity (n.s.) was seen in men who have sex with men, heterosexual, and male participants in DC. 54.0% of the participants contained at least one DRM. The 40-49 year-olds showed the highest prevalence of DRMs (22.9%). Phylogenetic analysis of pol and env sequences grouped 31.9-33.8% of the participants into clusters. HIV-TRACE grouped 2.9-12.8% of participants when using consensus sequences and 9.0-64.2% when using haplotypes. NGS allowed us to characterize the local phylodynamics of HIV-1 in DC more broadly and accurately, given a better representation of its diversity and dynamics. Reconstructed haplotypes provided novel and deeper phylodynamic insights, which led to networks linking a higher number of participants. Our understanding of the HIV-1 epidemic was expanded with the powerful coupling of HIV-1 NGS data with epidemiological data.

Telescope: Characterization of the retrotranscriptome by accurate estimation of transposable element expression

Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software tool that provides accurate estimation of transposable element expression (retrotranscriptome) resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through single locus analysis of HERV expression in 13 ENCODE cell types. When examined at this resolution, we find that the magnitude and breadth of the retrotranscriptome can be vastly different among cell types. Furthermore, our approach is robust to differences in sequencing technology and demonstrates that the retrotranscriptome has potential to be used for cell type identification. We compared our tool with other approaches for quantifying transposable element (TE) expression, and found that Telescope has the greatest resolution, as it estimates expression at specific TE insertions rather than at the TE subfamily level. Telescope performs highly accurate quantification of the retrotranscriptomic landscape in RNA-seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed. Telescope is available at https://github.com/mlbendall/telescope.

Almost half of the human genome is composed of transposable elements (TEs), but their contribution to the transcriptome, their cell-type specific expression patterns, and their role in disease remains poorly understood. Recent studies have found many elements to be actively expressed and involved in key cellular processes. For example, human endogenous retroviruses (HERVs) are reported to be involved in human embryonic stem cell differentiation. Discovering which exact HERVs are differentially expressed in RNA-seq data would be a major advance in understanding such processes. However, because HERVs have a high level of sequence similarity it is hard to identify which exact HERV is differentially expressed. To solve this problem, we developed a computer program which addressed uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We call this program, “Telescope”. We then used Telescope to identify HERV expression in 13 well-studied cell types from the ENCODE consortium and found that different cell types could be characterized by enrichment for different HERV families, and for locus specific expression. We also showed that Telescope performed better than other methods currently used to determine TE expression. The use of this computational tool to examine new and existing RNA-seq data sets may lead to new understanding of the roles of TEs in health and disease.

Benchmark Evaluation of True Single Molecular Sequencing to Determine Cystic Fibrosis Airway Microbiome Diversity

Cystic fibrosis (CF) is an autosomal recessive disease associated with recurrent lung infections that can lead to morbidity and mortality. The impact of antibiotics for treatment of acute pulmonary exacerbations on the CF airway microbiome remains unclear with prior studies giving conflicting results and being limited by their use of 16S ribosomal RNA sequencing. Our primary objective was to validate the use of true single molecular sequencing (tSMS) and PathoScope in the analysis of the CF airway microbiome. Three control samples were created with differing amounts of Burkholderia cepacia, Pseudomonas aeruginosa, and Prevotella melaninogenica, three common bacteria found in cystic fibrosis lungs. Paired sputa were also obtained from three study participants with CF before and >6 days after initiation of antibiotics. Antibiotic resistant B. cepacia and P. aeruginosa were identified in concurrently obtained respiratory cultures. Direct sequencing was performed using tSMS, and filtered reads were aligned to reference genomes from NCBI using PathoScope and Kraken and unique clade-specific marker genes using MetaPhlAn. A total of 180–518 K of 6–12 million filtered reads were aligned for each sample. Detection of known pathogens in control samples was most successful using PathoScope. In the CF sputa, alpha diversity measures varied based on the alignment method used, but similar trends were found between pre- and post-antibiotic samples. PathoScope outperformed Kraken and MetaPhlAn in our validation study of artificial bacterial community controls and also has advantages over Kraken and MetaPhlAn of being able to determine bacterial strains and the presence of fungal organisms. PathoScope can be confidently used when evaluating metagenomic data to determine CF airway microbiome diversity.

Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations

Multiple models describe the formation and evolution of distinct microbial phylogenetic groups. These evolutionary models make different predictions regarding how adaptive alleles spread through populations and how genetic diversity is maintained. Processes predicted by competing evolutionary models, for example, genome-wide selective sweeps vs gene-specific sweeps, could be captured in natural populations using time-series metagenomics if the approach were applied over a sufficiently long time frame. Direct observations of either process would help resolve how distinct microbial groups evolve. Here, from a 9-year metagenomic study of a freshwater lake (2005-2013), we explore changes in single-nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in 30 bacterial populations. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied by >1000-fold among populations. SNP allele frequencies also changed dramatically over time within some populations. Interestingly, nearly all SNP variants were slowly purged over several years from one population of green sulfur bacteria, while at the same time multiple genes either swept through or were lost from this population. These patterns were consistent with a genome-wide selective sweep in progress, a process predicted by the 'ecotype model' of speciation but not previously observed in nature. In contrast, other populations contained large, SNP-free genomic regions that appear to have swept independently through the populations prior to the study without purging diversity elsewhere in the genome. Evidence for both genome-wide and gene-specific sweeps suggests that different models of bacterial speciation may apply to different populations coexisting in the same environment.

Composition, taxonomy and functional diversity of the oropharynx microbiome in individuals with schizophrenia and controls

The role of the human microbiome in schizophrenia remains largely unexplored. The microbiome has been shown to alter brain development and modulate behavior and cognition in animals through gut-brain connections, and research in humans suggests that it may be a modulating factor in many disorders. This study reports findings from a shotgun metagenomic analysis of the oropharyngeal microbiome in 16 individuals with schizophrenia and 16 controls. High-level differences were evident at both the phylum and genus levels, with Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria dominating both schizophrenia patients and controls, and Ascomycota being more abundant in schizophrenia patients than controls. Controls were richer in species but less even in their distributions, i.e., dominated by fewer species, as opposed to schizophrenia patients. Lactic acid bacteria were relatively more abundant in schizophrenia, including species of Lactobacilli and Bifidobacterium, which have been shown to modulate chronic inflammation. We also found Eubacterium halii, a lactate-utilizing species. Functionally, the microbiome of schizophrenia patients was characterized by an increased number of metabolic pathways related to metabolite transport systems including siderophores, glutamate, and vitamin B12. In contrast, carbohydrate and lipid pathways and energy metabolism were abundant in controls. These findings suggest that the oropharyngeal microbiome in individuals with schizophrenia is significantly different compared to controls, and that particular microbial species and metabolic pathways differentiate both groups. Confirmation of these findings in larger and more diverse samples, e.g., gut microbiome, will contribute to elucidating potential links between schizophrenia and the human microbiota.

Dual Transcriptomic Profiling of Host and Microbiota during Health and Disease in Pediatric Asthma

BACKGROUND

High-throughput sequencing (HTS) analysis of microbial communities from the respiratory airways has heavily relied on the 16S rRNA gene. Given the intrinsic limitations of this approach, airway microbiome research has focused on assessing bacterial composition during health and disease, and its variation in relation to clinical and environmental factors, or other microbiomes. Consequently, very little effort has been dedicated to describing the functional characteristics of the airway microbiota and even less to explore the microbe-host interactions. Here we present a simultaneous assessment of microbiome and host functional diversity and host-microbe interactions from the same RNA-seq experiment, while accounting for variation in clinical metadata.

METHODS

Transcriptomic (host) and metatranscriptomic (microbiota) sequences from the nasal epithelium of 8 asthmatics and 6 healthy controls were separated in silico and mapped to available human and NCBI-NR protein reference databases. Human genes differentially expressed in asthmatics and controls were then used to infer upstream regulators involved in immune and inflammatory responses. Concomitantly, microbial genes were mapped to metabolic databases (COG, SEED, and KEGG) to infer microbial functions differentially expressed in asthmatics and controls. Finally, multivariate analysis was applied to find associations between microbiome characteristics and host upstream regulators while accounting for clinical variation.

RESULTS AND DISCUSSION

Our study showed significant differences in the metabolism of microbiomes from asthmatic and non-asthmatic children for up to 25% of the functional properties tested. Enrichment analysis of 499 differentially expressed host genes for inflammatory and immune responses revealed 43 upstream regulators differentially activated in asthma. Microbial adhesion (virulence) and Proteobacteria abundance were significantly associated with variation in the expression of the upstream regulator IL1A; suggesting that microbiome characteristics modulate host inflammatory and immune systems during asthma.

Phylogenomically guided identification of industrially relevant GH1 β-glucosidases through DNA synthesis and nanostructure-initiator mass spectrometry

Harnessing the biotechnological potential of the large number of proteins available in sequence databases requires scalable methods for functional characterization. Here we propose a workflow to address this challenge by combining phylogenomic guided DNA synthesis with high-throughput mass spectrometry and apply it to the systematic characterization of GH1 β-glucosidases, a family of enzymes necessary for biomass hydrolysis, an important step in the conversion of lignocellulosic feedstocks to fuels and chemicals. We synthesized and expressed 175 GH1s, selected from over 2000 candidate sequences to cover maximum sequence diversity. These enzymes were functionally characterized over a range of temperatures and pHs using nanostructure-initiator mass spectrometry (NIMS), generating over 10,000 data points. When combined with HPLC-based sugar profiling, we observed GH1 enzymes active over a broad temperature range and toward many different β-linked disaccharides. For some GH1s we also observed activity toward laminarin, a more complex oligosaccharide present as a major component of macroalgae. An area of particular interest was the identification of GH1 enzymes compatible with the ionic liquid 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]), a next-generation biomass pretreatment technology. We thus searched for GH1 enzymes active at 70 °C and 20% (v/v) [C2mim][OAc] over the course of a 24-h saccharification reaction. Using our unbiased approach, we identified multiple enzymes of different phylogentic origin with such activities. Our approach of characterizing sequence diversity through targeted gene synthesis coupled to high-throughput screening technologies is a broadly applicable paradigm for a wide range of biological problems.

Phylogenetic relationships and molecular adaptation dynamics of human rhinoviruses

Human rhinoviruses (HRVs) are responsible for nearly 50% of all common cold infections. Ordinarily, HRV infections are mild and self-limiting; nonetheless, every year they result in significant loss of economic productivity and substantial inappropriate antibiotic use. Development of effective vaccine and antiviral prophylaxis against HRV has been hampered by the extensive antigenic diversity present among the nearly 100 serotypes. To gain new insights into the evolutionary processes that create the genetic diversity present among HRVs, we tested for recombination and selection for individual genes and the coding genome for 45 HRV serotypes using estimated phylogenetic relationships. Although the structural capsid genes and nonstructural genes recovered incongruent tree topologies, no recombination was detected using substitution methods. Therefore, the coding genome was determined to be appropriate for phylogenetic tests. Results of the Shimodaira-Hasegawa (SH) test support the hypothesis that the capsid genes recover a different evolutionary history than the nonstructural genes. Our best phylogenetic estimate based on the coding genome suggests that HRV-B is more closely related to enterovirus than to HRV-A; however, several alternative phylogenetic hypotheses were not rejected by the SH test. Positive selection was examined by using two different approaches; d(N)/d(S) rate ratio and the physicochemical phenotypes for 31 amino acid properties. Analyses using d(N)/d(S) failed to detect positive selection. However, protein phenotypic expression appears to be a more sensitive approach. There was extensive stabilizing and destabilizing positive selection in HRV-A major and HRV-B serotypes for all proteins, except in 3A in HRV-B, which overlapped with functional, structural, and to a greater extent in uncharacterized genomic regions. In contrast, the evolution of HRV-A minor serotypes appears to be driven primarily by destabilizing selection. Our results demonstrate that HRV-A major, HRV-A minor, and HRV-B serotypes have not been similarly influenced by purifying selection.