Liquid Glycan Array.

The M13 phage platform is a stable and monodisperse nanoscale carrier, which can be modified with different molecules by chemical conjugation strategies. Here, we describe M13 phage acylated on pVIII protein with a dibenzocyclooctyne reacting with azido glycan to yield 30-1500 copy numbers of glycan per phage and monitored by MALDI-TOF spectrometry to generate multivalent glycoconjugates that contain desired densities of glycans. We prepared the liquid glycan arrays (LiGA) such that both the structure and density of glycans were encoded in the DNA of the bacteriophage. The LiGA can be used to validate the binding properties of glycans to purified lectins and explore the effect of glycan density on such binding. From a mixture of multivalent glycan probes, LiGAs can also identify the glycoconjugates with optimal avidity necessary for binding to lectins on living cells in vitro and live animals in vivo.

Chemoenzymatic synthesis of genetically-encoded multivalent liquid N-glycan arrays.

Cellular glycosylation is characterized by chemical complexity and heterogeneity, which is challenging to reproduce synthetically. Here we show chemoenzymatic synthesis on phage to produce a genetically-encoded liquid glycan array (LiGA) of complex type N-glycans. Implementing the approach involved by ligating an azide-containing sialylglycosyl-asparagine to phage functionalized with 50-1000 copies of dibenzocyclooctyne. The resulting intermediate can be trimmed by glycosidases and extended by glycosyltransferases yielding a phage library with different N-glycans. Post-reaction analysis by MALDI-TOF MS allows rigorous characterization of N-glycan structure and mean density, which are both encoded in the phage DNA. Use of this LiGA with fifteen glycan-binding proteins, including CD22 or DC-SIGN on cells, reveals optimal structure/density combinations for recognition. Injection of the LiGA into mice identifies glycoconjugates with structures and avidity necessary for enrichment in specific organs. This work provides a quantitative evaluation of the interaction of complex N-glycans with GBPs in vitro and in vivo.

Differential Treatment of Sexual Assault Cases by US Army Law Enforcement Personnel.

Using data received through the Freedom of Information Act, this observational study explores whether Army law enforcement personnel do not find probable cause in sexual assault cases at higher rates than in other serious crimes. The study compares sexual assaults, homicides, robberies, and assaults in the Army from 2008 to 2014 and July 2015 to 2017. For the first period, the study finds that the odds are 5.30 times greater that Army law enforcement will not find probable cause in a sexual assault case when compared to other crimes, and for the second period the odds are 4.39 times greater.

The effect of changing the military's sexual assault laws on law enforcement investigative findings in the U.S. Army.

OBJECTIVE: In 2007, Congress changed the military's sexual assault laws as part of an effort to improve sexual assault case processing. This study looked at the U.S. Army law enforcement investigative finding for every sexual assault reported to the Army from 2004 through June 2012, along with every nonsexual assault. Our objective was to measure whether the legal intervention affected the investigative findings made by Army law enforcement officers in sexual assault cases (penetrative, nonpenetrative, and combined) as compared to assault cases (aggravated, simple, and combined). HYPOTHESES: We hypothesized that we would not find evidence that the legal intervention affected the rate of sexual assault cases labeled as "founded" by Army law enforcement, such that for the best-fitting time-series models, any difference in the residuals of the means before and after the intervention would not be statistically significant. METHOD: We received data from the U.S. Army on all sexual assaults and nonsexual assaults from 2004 through June 2012. The data comprised 47,058 observations. We used time-series analysis with autoregressive integrated moving average modeling. The variable tracked over time was the ratio of the proportion of founded sexual assault cases to the proportion of founded nonsexual assault cases. We then conducted t tests of the means of the residuals before and after the legal intervention. RESULTS: The difference in the means of the residuals before and after the intervention was not statistically significant for combined sexual assaults versus combined assaults, penetrative sexual assaults versus aggravated assaults, or nonpenetrative sexual assaults versus simple assaults. CONCLUSIONS: This reform to sexual assault laws does not appear to have affected sexual assault case processing by U.S. Army law enforcement. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

GlyNet: a multi-task neural network for predicting protein-glycan interactions.

Advances in diagnostics, therapeutics, vaccines, transfusion, and organ transplantation build on a fundamental understanding of glycan-protein interactions. To aid this, we developed GlyNet, a model that accurately predicts interactions (relative binding strengths) between mammalian glycans and 352 glycan-binding proteins, many at multiple concentrations. For each glycan input, our model produces 1257 outputs, each representing the relative interaction strength between the input glycan and a particular protein sample. GlyNet learns these continuous values using relative fluorescence units (RFUs) measured on 599 glycans in the Consortium for Functional Glycomics glycan arrays and extrapolates these to RFUs from additional, untested glycans. GlyNet's output of continuous values provides more detailed results than the standard binary classification models. After incorporating a simple threshold to transform such continuous outputs the resulting GlyNet classifier outperforms those standard classifiers. GlyNet is the first multi-output regression model for predicting protein-glycan interactions and serves as an important benchmark, facilitating development of quantitative computational glycobiology.

Isolation of a Human Betaretrovirus from Patients with Primary Biliary Cholangitis.

A human betaretrovirus (HBRV) has been linked with the autoimmune liver disease, primary biliary cholangitis (PBC), and various cancers, including breast cancer and lymphoma. HBRV is closely related to the mouse mammary tumor virus, and represents the only exogenous betaretrovirus characterized in humans to date. Evidence of infection in patients with PBC has been demonstrated through the identification of proviral integration sites in lymphoid tissue, the major reservoir of infection, as well as biliary epithelium, which is the site of the disease process. Accordingly, we tested the hypothesis that patients with PBC harbor a transmissible betaretrovirus by co-cultivation of PBC patients' lymph node homogenates with the HS578T breast cancer line. Because of the low level of HBRV replication, betaretrovirus producing cells were subcloned to optimize viral isolation and production. Evidence of infection was provided by electron microscopy, RT-PCR, in situ hybridization, cloning of the HBRV proviral genome and demonstration of more than 3400 integration sites. Further evidence of viral transmissibility was demonstrated by infection of biliary epithelial cells. While HBRV did not show a preference for integration proximal to specific genomic features, analyses of common insertion sites revealed evidence of integration proximal to cancer associated genes. These studies demonstrate the isolation of HBRV with features similar to mouse mammary tumor virus and confirm that patients with PBC display evidence of a transmissible viral infection.

Metagenomics Versus Metatranscriptomics of the Murine Gut Microbiome for Assessing Microbial Metabolism During Inflammation.

Shotgun metagenomics studies have improved our understanding of microbial population dynamics and have revealed significant contributions of microbes to gut homeostasis. They also allow in silico inference of the metagenome. While they link the microbiome with metabolic abnormalities associated with disease phenotypes, they do not capture microbial gene expression patterns that occur in response to the multitude of stimuli that constantly ambush the gut environment. Metatranscriptomics closes that gap, but its implementation is more expensive and tedious. We assessed the metabolic perturbations associated with gut inflammation using shotgun metagenomics and metatranscriptomics. Shotgun metagenomics detected changes in abundance of bacterial taxa known to be SCFA producers, which favors gut homeostasis. Bacteria in the phylum Firmicutes were found at decreased abundance, while those in phyla Bacteroidetes and Proteobacteria were found at increased abundance. Surprisingly, inferring the coding capacity of the microbiome from shotgun metagenomics data did not result in any statistically significant difference, suggesting functional redundancy in the microbiome or poor resolution of shotgun metagenomics data to profile bacterial pathways, especially when sequencing is not very deep. Obviously, the ability of metatranscriptomics libraries to detect transcripts expressed at basal (or simply low) levels is also dependent on sequencing depth. Nevertheless, metatranscriptomics informed about contrasting roles of bacteria during inflammation. Functions involved in nutrient transport, immune suppression and regulation of tissue damage were dramatically upregulated, perhaps contributed by homeostasis-promoting bacteria. Functions ostensibly increasing bacteria pathogenesis were also found upregulated, perhaps as a consequence of increased abundance of Proteobacteria. Bacterial protein synthesis appeared downregulated. In summary, shotgun metagenomics was useful to profile bacterial population composition and taxa relative abundance, but did not inform about differential gene content associated with inflammation. Metatranscriptomics was more robust for capturing bacterial metabolism in real time. Although both approaches are complementary, it is often not possible to apply them in parallel. We hope our data will help researchers to decide which approach is more appropriate for the study of different aspects of the microbiome.

Associations between weather-related data and influenza reports: A pilot study and related policy implications.

AIM: The purpose of this retrospective, correlational pilot study was to explore the relationship between historical weekly weather data including temperature, dew point, humidity, barometric pressure, visibility, and cloud cover compared to weekly influenza-like illness reports over a four year period. BACKGROUND: Climate and weather-related conditions may affect the viral activity and transmission of influenza, although this relationship has not been widely studied in nursing. Some research suggests that there are causal links between cold temperatures, low indoor humidity, minimal sun exposure, and influenza outbreaks. Additionally, rapid weather variability in a warming climate can increase influenza epidemic risk. METHODS: Data from a local public health district were extracted and used to correlate with weekly weather averages for the area. RESULTS: Findings showed that current influenza reports are significantly associated with temperature and visibility, both lagged two weeks. CONCLUSIONS: Though more research is needed, nurses must understand, recognize, and act upon weather and climate factors that affect the health of populations. With a greater understanding of the relationship between weather and influenza-like illness, nurses and other healthcare providers can potentially work to respond to and mitigate the consequences of weather-related illness as well as anticipate and prepare for increased flu burden. Furthermore, nurses can remain engaged in climate protective initiatives and policy development at their local community and/or organizational levels to underscore and advocate for the needs of populations and groups they serve.

Cation and Anion Channelrhodopsins: Sequence Motifs and Taxonomic Distribution.

Cation and anion channelrhodopsins (CCRs and ACRs, respectively) primarily from two algal species, Chlamydomonas reinhardtii and Guillardia theta, have become widely used as optogenetic tools to control cell membrane potential with light. We mined algal and other protist polynucleotide sequencing projects and metagenomic samples to identify 75 channelrhodopsin homologs from four channelrhodopsin families, including one revealed in dinoflagellates in this study. We carried out electrophysiological analysis of 33 natural channelrhodopsin variants from different phylogenetic lineages and 10 metagenomic homologs in search of sequence determinants of ion selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins. Our results show that association of a reduced number of glutamates near the conductance path with anion selectivity depends on a wider protein context, because prasinophyte homologs with a glutamate pattern identical to that in cryptophyte ACRs are cation selective. Desensitization is also broadly context dependent, as in one branch of stramenopile ACRs and their metagenomic homologs, its extent roughly correlates with phylogenetic relationship of their sequences. Regarding spectral tuning, we identified two prasinophyte CCRs with red-shifted spectra to 585 nm. They exhibit a third residue pattern in their retinal-binding pockets distinctly different from those of the only two types of red-shifted channelrhodopsins known (i.e., the CCR Chrimson and RubyACRs). In cryptophyte ACRs we identified three specific residue positions in the retinal-binding pocket that define the wavelength of their spectral maxima. Lastly, we found that dinoflagellate rhodopsins with a TCP motif in the third transmembrane helix and a metagenomic homolog exhibit channel activity. IMPORTANCE Channelrhodopsins are widely used in neuroscience and cardiology as research tools and are considered prospective therapeutics, but their natural diversity and mechanisms remain poorly characterized. Genomic and metagenomic sequencing projects are producing an ever-increasing wealth of data, whereas biophysical characterization of the encoded proteins lags behind. In this study, we used manual and automated patch clamp recording of representative members of four channelrhodopsin families, including a family in dinoflagellates that we report in this study. Our results contribute to a better understanding of molecular determinants of ionic selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins.

Genetically encoded multivalent liquid glycan array displayed on M13 bacteriophage.

The central dogma of biology does not allow for the study of glycans using DNA sequencing. We report a liquid glycan array (LiGA) platform comprising a library of DNA 'barcoded' M13 virions that display 30-1,500 copies of glycans per phage. A LiGA is synthesized by acylation of the phage pVIII protein with a dibenzocyclooctyne, followed by ligation of azido-modified glycans. Pulldown of the LiGA with lectins followed by deep sequencing of the barcodes in the bound phage decodes the optimal structure and density of the recognized glycans. The LiGA is target agnostic and can measure the glycan-binding profile of lectins, such as CD22, on cells in vitro and immune cells in a live mouse. From a mixture of multivalent glycan probes, LiGAs identify the glycoconjugates with optimal avidity necessary for binding to lectins on living cells in vitro and in vivo.

Access to RNA-sequencing data from 1,173 plant species: The 1000 Plant transcriptomes initiative (1KP).

BACKGROUND: The 1000 Plant transcriptomes initiative (1KP) explored genetic diversity by sequencing RNA from 1,342 samples representing 1,173 species of green plants (Viridiplantae). FINDINGS: This data release accompanies the initiative's final/capstone publication on a set of 3 analyses inferring species trees, whole genome duplications, and gene family expansions. These and previous analyses are based on de novo transcriptome assemblies and related gene predictions. Here, we assess their data and assembly qualities and explain how we detected potential contaminations. CONCLUSIONS: These data will be useful to plant and/or evolutionary scientists with interests in particular gene families, either across the green plant tree of life or in more focused lineages.

Impact of sequencing depth and technology on de novo RNA-Seq assembly.

BACKGROUND: RNA-Seq data is inherently nonuniform for different transcripts because of differences in gene expression. This makes it challenging to decide how much data should be generated from each sample. How much should one spend to recover the less expressed transcripts? The sequencing technology used is another consideration, as there are inevitably always biases against certain sequences. To investigate these effects, we first looked at high-depth libraries from a set of well-annotated organisms to ascertain the impact of sequencing depth on de novo assembly. We then looked at libraries sequenced from the Universal Human Reference RNA (UHRR) to compare the performance of Illumina HiSeq and MGI DNBseq™ technologies. RESULTS: On the issue of sequencing depth, the amount of exomic sequence assembled plateaued using data sets of approximately 2 to 8 Gbp. However, the amount of genomic sequence assembled did not plateau for many of the analyzed organisms. Most of the unannotated genomic sequences are single-exon transcripts whose biological significance will be questionable for some users. On the issue of sequencing technology, both of the analyzed platforms recovered a similar number of full-length transcripts. The missing "gap" regions in the HiSeq assemblies were often attributed to higher GC contents, but this may be an artefact of library preparation and not of sequencing technology. CONCLUSIONS: Increasing sequencing depth beyond modest data sets of less than 10 Gbp recovers a plethora of single-exon transcripts undocumented in genome annotations. DNBseq™ is a viable alternative to HiSeq for de novo RNA-Seq assembly.

Insights into the Evolution of Hydroxyproline-Rich Glycoproteins from 1000 Plant Transcriptomes.

The carbohydrate-rich cell walls of land plants and algae have been the focus of much interest given the value of cell wall-based products to our current and future economies. Hydroxyproline-rich glycoproteins (HRGPs), a major group of wall glycoproteins, play important roles in plant growth and development, yet little is known about how they have evolved in parallel with the polysaccharide components of walls. We investigate the origins and evolution of the HRGP superfamily, which is commonly divided into three major multigene families: the arabinogalactan proteins (AGPs), extensins (EXTs), and proline-rich proteins. Using motif and amino acid bias, a newly developed bioinformatics pipeline, we identified HRGPs in sequences from the 1000 Plants transcriptome project (www.onekp.com). Our analyses provide new insights into the evolution of HRGPs across major evolutionary milestones, including the transition to land and the early radiation of angiosperms. Significantly, data mining reveals the origin of glycosylphosphatidylinositol (GPI)-anchored AGPs in green algae and a 3- to 4-fold increase in GPI-AGPs in liverworts and mosses. The first detection of cross-linking (CL)-EXTs is observed in bryophytes, which suggests that CL-EXTs arose though the juxtaposition of preexisting SPn EXT glycomotifs with refined Y-based motifs. We also detected the loss of CL-EXT in a few lineages, including the grass family (Poaceae), that have a cell wall composition distinct from other monocots and eudicots. A key challenge in HRGP research is tracking individual HRGPs throughout evolution. Using the 1000 Plants output, we were able to find putative orthologs of Arabidopsis pollen-specific GPI-AGPs in basal eudicots.

Diversity of ABC transporter genes across the plant kingdom and their potential utility in biotechnology.

BACKGROUND: The ATP-binding cassette (ABC) transporter gene superfamily is ubiquitous among extant organisms and prominently represented in plants. ABC transporters act to transport compounds across cellular membranes and are involved in a diverse range of biological processes. Thus, the applicability to biotechnology is vast, including cancer resistance in humans, drug resistance among vertebrates, and herbicide and other xenobiotic resistance in plants. In addition, plants appear to harbor the highest diversity of ABC transporter genes compared with any other group of organisms. This study applied transcriptome analysis to survey the kingdom-wide ABC transporter diversity in plants and suggest biotechnology applications of this diversity. RESULTS: We utilized sequence similarity-based informatics techniques to infer the identity of ABC transporter gene candidates from 1295 phylogenetically-diverse plant transcriptomes. A total of 97,149 putative (approximately 25 % were full-length) ABC transporter gene members were identified; each RNA-Seq library (plant sample) had 88 ± 30 gene members. As expected, simpler organisms, such as algae, had fewer unique members than vascular land plants. Differences were also noted in the richness of certain ABC transporter subfamilies. Land plants had more unique ABCB, ABCC, and ABCG transporter gene members on average (p < 0.005), and green algae, red algae, and bryophytes had significantly more ABCF transporter gene members (p < 0.005). Ferns had significantly fewer ABCA transporter gene members than all other plant groups (p < 0.005). CONCLUSIONS: We present a transcriptomic overview of ABC transporter gene members across all major plant groups. An increase in the number of gene family members present in the ABCB, ABCC, and ABCD transporter subfamilies may indicate an expansion of the ABC transporter superfamily among green land plants, which include all crop species. The striking difference between the number of ABCA subfamily transporter gene members between ferns and other plant taxa is surprising and merits further investigation. Discussed is the potential exploitation of ABC transporters in plant biotechnology, with an emphasis on crops.

Gamma-Retrovirus Integration Marks Cell Type-Specific Cancer Genes: A Novel Profiling Tool in Cancer Genomics.

Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types.

Functional and topological diversity of LOV domain photoreceptors.

Light-oxygen-voltage sensitive (LOV) flavoproteins are ubiquitous photoreceptors that mediate responses to environmental cues. Photosensory inputs are transduced into signaling outputs via structural rearrangements in sensor domains that consequently modulate the activity of an effector domain or multidomain clusters. Establishing the diversity in effector function and sensor-effector topology will inform what signaling mechanisms govern light-responsive behaviors across multiple kingdoms of life and how these signals are transduced. Here, we report the bioinformatics identification of over 6,700 candidate LOV domains (including over 4,000 previously unidentified sequences from plants and protists), and insights from their annotations for ontological function and structural arrangements. Motif analysis identified the sensors from ∼42 million ORFs, with strong statistical separation from other flavoproteins and non-LOV members of the structurally related Per-aryl hydrocarbon receptor nuclear translocator (ARNT)-Sim family. Conserved-domain analysis determined putative light-regulated function and multidomain topologies. We found that for certain effectors, sensor-effector linker length is discretized based on both phylogeny and the preservation of α-helical heptad repeats within an extended coiled-coil linker structure. This finding suggests that preserving sensor-effector orientation is a key determinant of linker length, in addition to ancestry, in LOV signaling structure-function. We found a surprisingly high prevalence of effectors with functions previously thought to be rare among LOV proteins, such as regulators of G protein signaling, and discovered several previously unidentified effectors, such as lipases. This work highlights the value of applying genomic and transcriptomic technologies to diverse organisms to capture the structural and functional variation in photosensory proteins that are vastly important in adaptation, photobiology, and optogenetics.

Occurrence, structure, and evolution of nitric oxide synthase-like proteins in the plant kingdom.

Nitric oxide (NO) signaling regulates various physiological processes in both animals and plants. In animals, NO synthesis is mainly catalyzed by NO synthase (NOS) enzymes. Although NOS-like activities that are sensitive to mammalian NOS inhibitors have been detected in plant extracts, few bona fide plant NOS enzymes have been identified. We searched the data set produced by the 1000 Plants (1KP) international consortium for the presence of transcripts encoding NOS-like proteins in over 1000 species of land plants and algae. We also searched for genes encoding NOS-like enzymes in 24 publicly available algal genomes. We identified no typical NOS sequences in 1087 sequenced transcriptomes of land plants. In contrast, we identified NOS-like sequences in 15 of the 265 algal species analyzed. Even if the presence of NOS enzymes assembled from multipolypeptides in plants cannot be conclusively discarded, the emerging data suggest that, instead of generating NO with evolutionarily conserved NOS enzymes, land plants have evolved finely regulated nitrate assimilation and reduction processes to synthesize NO through a mechanism different than that in animals.

Peptidomics of Circular Cysteine-Rich Plant Peptides: Analysis of the Diversity of Cyclotides from Viola tricolor by Transcriptome and Proteome Mining.

Cyclotides are plant-derived mini proteins. They are genetically encoded as precursor proteins that become post-translationally modified to yield circular cystine-knotted molecules. Because of this structural topology cyclotides resist enzymatic degradation in biological fluids, and hence they are considered as promising lead molecules for pharmaceutical applications. Despite ongoing efforts to discover novel cyclotides and analyze their biodiversity, it is not clear how many individual peptides a single plant specimen can express. Therefore, we investigated the transcriptome and cyclotide peptidome of Viola tricolor. Transcriptome mining enabled the characterization of cyclotide precursor architecture and processing sites important for biosynthesis of mature peptides. The cyclotide peptidome was explored by mass spectrometry and bottom-up proteomics using the extracted peptide sequences as queries for database searching. In total 164 cyclotides were discovered by nucleic acid and peptide analysis in V. tricolor. Therefore, violaceous plants at a global scale may be the source to as many as 150 000 individual cyclotides. Encompassing the diversity of V. tricolor as a combinatorial library of bioactive peptides, this commercially available medicinal herb may be a suitable starting point for future bioactivity-guided screening studies.

The Origin and Evolution of the Plant Cell Surface: Algal Integrin-Associated Proteins and a New Family of Integrin-Like Cytoskeleton-ECM Linker Proteins.

The extracellular matrix of scaly green flagellates consists of small organic scales consisting of polysaccharides and scale-associated proteins (SAPs). Molecular phylogenies have shown that these organisms represent the ancestral stock of flagellates from which all green plants (Viridiplantae) evolved. The molecular characterization of four different SAPs is presented. Three SAPs are type-2 membrane proteins with an arginine/alanine-rich short cytoplasmic tail and an extracellular domain that is most likely of bacterial origin. The fourth protein is a filamin-like protein. In addition, we report the presence of proteins similar to the integrin-associated proteins α-actinin (in transcriptomes of glaucophytes and some viridiplants), LIM-domain proteins, and integrin-associated kinase in transcriptomes of viridiplants, glaucophytes, and rhodophytes. We propose that the membrane proteins identified are the predicted linkers between scales and the cytoskeleton. These proteins are present in many green algae but are apparently absent from embryophytes. These proteins represent a new protein family we have termed gralins for green algal integrins. Gralins are absent from embryophytes. A model for the evolution of the cell surface proteins in Plantae is discussed.

Metagenomic analysis of microbiome in colon tissue from subjects with inflammatory bowel diseases reveals interplay of viruses and bacteria.

Inflammatory bowel diseases (IBD), Crohn's disease and ulcerative colitis, are poorly understood disorders affecting the intestinal tract. The current model for disease suggests that genetically susceptible patients develop intolerance to gut microflora, and chronic inflammation develops as a result of environmental insults. Although interest has mainly focused on studying genetic variants and gut bacterial flora, little is known about the potential of viral infection to contribute to disease. Accordingly, we conducted a metagenomic analysis to document the baseline virome in colonic biopsy samples from patients with IBD in order to assess the contribution of viral infection to IBD. Libraries were generated from colon RNA to create approximately 2 GB sequence data per library. Using a bioinformatic pipeline designed to detect viral sequences, more than 1000 viral reads were derived directly from tissue without any coculture or isolation procedure. Herein, we describe the complexity and abundance of viruses, bacteria/bacteriophage, and human endogenous retroviral sequences from 10 patients with IBD and 5 healthy subjects undergoing surveillance colonoscopy. Differences in gut microflora and the abundance of mammalian viruses and human endogenous retroviruses were readily detected in the metagenomic analyses. Specifically, patients with herpesviridae sequences in their colon demonstrated increased expression of human endogenous viral sequences and differences in the diversity of their microbiome. This study provides a promising metagenomic approach to describe the colonic microbiome that can be used to better understand virus-host and phage-bacteria interactions in IBD.