Aubrey Bailey

Virus-helminth coinfection reveals a microbiota-independent mechanism of immunomodulation

Parasites make it hard to fight viruses Microbial co-infections challenge the immune system—different pathogens often require different flavors of immune responses for their elimination or containment (see the Perspective by Maizels and Gause). Two teams studied what happens when parasitic worms and viruses infect mice at the same time. Reese et al. found that parasite co-infection woke up a dormant virus. Osborne et al. found that mice already infected with parasitic worms were worse at fighting off viruses. In both cases, worms skewed the immune response so that the immune cells and the molecules they secreted created an environment favorable for the worm at the expense of antiviral immunity. Science, this issue p. 573 and p. 578; see also p. 517 Coinfection with intestinal parasites leads to altered antiviral immunity in mice. [Also see Perspective by Maizels and Gause] The mammalian intestine is colonized by beneficial commensal bacteria and is a site of infection by pathogens, including helminth parasites. Helminths induce potent immunomodulatory effects, but whether these effects are mediated by direct regulation of host immunity or indirectly through eliciting changes in the microbiota is unknown. We tested this in the context of virus-helminth coinfection. Helminth coinfection resulted in impaired antiviral immunity and was associated with changes in the microbiota and STAT6-dependent helminth-induced alternative activation of macrophages. Notably, helminth-induced impairment of antiviral immunity was evident in germ-free mice, but neutralization of Ym1, a chitinase-like molecule that is associated with alternatively activated macrophages, could partially restore antiviral immunity. These data indicate that helminth-induced immunomodulation occurs independently of changes in the microbiota but is dependent on Ym1.

Association Between Breast Milk Bacterial Communities and Establishment and Development of the Infant Gut Microbiome

Importance Establishment of the infant microbiome has lifelong implications on health and immunity. Gut microbiota of breastfed compared with nonbreastfed individuals differ during infancy as well as into adulthood. Breast milk contains a diverse population of bacteria, but little is known about the vertical transfer of bacteria from mother to infant by breastfeeding. Objective To determine the association between the maternal breast milk and areolar skin and infant gut bacterial communities. Design, Setting, and Participants In a prospective, longitudinal study, bacterial composition was identified with sequencing of the 16S ribosomal RNA gene in breast milk, areolar skin, and infant stool samples of 107 healthy mother-infant pairs. The study was conducted in Los Angeles, California, and St Petersburg, Florida, between January 1, 2010, and February 28, 2015. Exposures Amount and duration of daily breastfeeding and timing of solid food introduction. Main Outcomes and Measures Bacterial composition in maternal breast milk, areolar skin, and infant stool by sequencing of the 16S ribosomal RNA gene. Results In the 107 healthy mother and infant pairs (median age at the time of specimen collection, 40 days; range, 1-331 days), 52 (43.0%) of the infants were male. Bacterial communities were distinct in milk, areolar skin, and stool, differing in both composition and diversity. The infant gut microbial communities were more closely related to an infant’s mother’s milk and skin compared with a random mother (mean difference in Bray-Curtis distances, 0.012 and 0.014, respectively; P < .001 for both). Source tracking analysis was used to estimate the contribution of the breast milk and areolar skin microbiomes to the infant gut microbiome. During the first 30 days of life, infants who breastfed to obtain 75% or more of their daily milk intake received a mean (SD) of 27.7% (15.2%) of the bacteria from breast milk and 10.3% (6.0%) from areolar skin. Bacterial diversity (Faith phylogenetic diversity, P = .003) and composition changes were associated with the proportion of daily breast milk intake in a dose-dependent manner, even after the introduction of solid foods. Conclusions and Relevance The results of this study indicate that bacteria in mother’s breast milk seed the infant gut, underscoring the importance of breastfeeding in the development of the infant gut microbiome.

Viral Metagenomics Reveal Blooms of Anelloviruses in the Respiratory Tract of Lung Transplant Recipients

Few studies have examined the lung virome in health and disease. Outcomes of lung transplantation are known to be influenced by several recognized respiratory viruses, but global understanding of the virome of the transplanted lung is incomplete. To define the DNA virome within the respiratory tract following lung transplantation we carried out metagenomic analysis of allograft bronchoalveolar lavage (BAL), and compared with healthy and HIV+ subjects. Viral concentrates were purified from BAL and analyzed by shotgun DNA sequencing. All of the BAL samples contained reads mapping to anelloviruses, with high proportions in lung transplant samples. Anellovirus populations in transplant recipients were complex, with multiple concurrent variants. Quantitative polymerase chain reaction quantification revealed that anellovirus sequences were 56‐fold more abundant in BAL from lung transplant recipients compared with healthy controls or HIV+ subjects (p < 0.0001). Anellovirus sequences were also more abundant in upper respiratory tract specimens from lung transplant recipients than controls (p = 0.006). Comparison to metagenomic data on bacterial populations showed that high anellovirus loads correlated with dysbiotic bacterial communities in allograft BAL (p = 0.008). Thus the respiratory tracts of lung transplant recipients contain high levels and complex populations of anelloviruses, warranting studies of anellovirus lung infection and transplant outcome.

Peptidoglycan from the gut microbiota governs the lifespan of circulating phagocytes at homeostasis.

Maintenance of myeloid cell homeostasis requires continuous turnover of phagocytes from the bloodstream, yet whether environmental signals influence phagocyte longevity in the absence of inflammation remains unknown. Here, we show that the gut microbiota regulates the steady-state cellular lifespan of neutrophils and inflammatory monocytes, the 2 most abundant circulating myeloid cells and key contributors to inflammatory responses. Treatment of mice with broad-spectrum antibiotics, or with the gut-restricted aminoglycoside neomycin alone, accelerated phagocyte turnover and increased the rates of their spontaneous apoptosis. Metagenomic analyses revealed that neomycin altered the abundance of intestinal bacteria bearing γ-d-glutamyl-meso-diaminopimelic acid, a ligand for the intracellular peptidoglycan sensor Nod1. Accordingly, signaling through Nod1 was both necessary and sufficient to mediate the stimulatory influence of the flora on myeloid cell longevity. Stimulation of Nod1 signaling increased the frequency of lymphocytes in the murine intestine producing the proinflammatory cytokine interleukin 17A (IL-17A), and liberation of IL-17A was required for transmission of Nod1-dependent signals to circulating phagocytes. Together, these results define a mechanism through which intestinal microbes govern a central component of myeloid homeostasis and suggest perturbations of commensal communities can influence steady-state regulation of cell fate.

Quantitation of HIV DNA integration: Effects of differential integration site distributions on Alu-PCR assays

In many studies of HIV replication, it is useful to quantify the number of HIV proviruses in cells against a background of unintegrated forms of the HIV DNA. A popular method for doing so involves quantitative PCR using one primer complementary to the HIV long terminal repeat (LTR), and a second primer complementary to a cellular Alu repeat, so that PCR product only forms from templates where a provirus is integrated in the human genome near an Alu repeat. However, several recent studies have identified conditions that alter distributions of HIV integration sites relative to genes. Because Alu repeats are enriched in gene rich regions, this raises the question of whether altered integration site distributions might confound provirus abundance measurements using the Alu-PCR method. Here modified versions of the HIV tethering protein LEDGF/p75 were used to retarget HIV integration outside of transcription units, and show that this has a negligible effect on Alu-PCR quantitation of proviral abundance. Thus altered integration targeting, at least to the degree achieved here, is not a major concern when using the Alu-PCR assay.

Bringing it all together: big data and HIV research

A PubMed search for HIV-related publications from 2011 yields a whopping 15 091 total, or over 40 studies a day. No one can read or remember all this; unsettlingly, no one knows the full HIV literature. The explosion of high throughput data makes the deluge even worse. Genome-wide small interfering RNA (siRNA) screens and proteomic scans regularly yield results for all 20 000 human genes. The Solexa/Illumina HiSeq (San Diego, California, USA) instrument can produce more than 100 billion bases of sequence information in a single instrument run, and runs are accumulating addressing questions in HIV research. Data from genome-wide association studies, HIV resistance testing and epidemiological tracking all add to the flood. Given this gigantic volume of data, the development of digestible summaries becomes as important as generating the data itself. Here we briefly list some of the main sources of data and efforts to develop new tools to work with them, particularly focusing on a new tool for analysing genome-wide screens for human genes affecting HIV replication. Links toweb sites mentioned in the article are collected in Table 1. Table 1 Examples of resources for HIV Systems Biology on the Web. Several groups have started to develop data repositories and computational tools for HIV research, providing important starting points. The National Center for Biotechnology Information (NCBI) hosts the largest effort, centralizing data on the scientific literature, DNA sequences, gene structure and many other topics [1]. NCBI serves an important archiving function, but retrieving high-throughput data is often challenging, and few analytical tools are available. The Los Alamos HIV Databases houses HIV sequences and data on mapped epitopes, together with useful alignments and some tools for working with the data [2]. The Stanford University HIV Drug Resistance Database provides a key resource for information on HIV mutations conferring resistance to antiviral agents [3]. GPS-Prot provides an innovative way for starting with an HIV protein, calling up well vetted binding proteins and exploring multiple types of annotation from there [4]. Vince Racaniello’s web show on virology is another favourite. Here we introduce a new web site – HIVsystemsbiology.org – that collects Big Data on HIV and starts to provide tools to distil them (Fig. 1). One tool is the Gene Overlapper, which collects data from genome-wide screens of human gene products affecting HIVand enables analysis of overlap among sets. This is paired with a second resource, the HIV Replication Cycle site, which is accessible through HIVsystemsbiology.org and provides context for the genome-wide data. Unfortunately, large data sets often come with very limited background, greatly reducing their usefulness. Without detailed information on a sample’s origins, it is difficult to follow up with much confidence. Data need to be paired with summaries that are web based, rich in context and as inviting to users as possible, obvious from experience but surprisingly hard to implement. Fig. 1 Progression through the HIV Systems Biology Site The HIV Replication Cycle site presents a review of HIV replication in cells, but linked to extensive web-based resources. Accounts of the HIV proteins are enhanced with movies of HIV protein structures to allow visualization in three dimensions. Numerous web links lead from the site to other resources. One link allows readers to navigate out on to the human genome and surf around, viewing positions of HIV integration sites. All images, movies and other materials are available for free download for use by AIDS researchers and educators. Importantly in this context, simple explanations of different parts of the HIV replication cycle are linked to large data sets available for study in the Gene Overlapper site. The Overlapper site houses 39 lists of genes called in different genome-wide screens for links to HIV, and the number is growing steadily. Included are results from three genome-side siRNA screens [5–7] and a cDNA overexpression screen [8], allowing intersections among these gene sets to be explored. Other types of data may be of interest in further comparisons, for example data from screens for human proteins binding to HIV proteins. Nineteen lists from such screens are included [9]. Additional gene lists describe computational scans for gene products important in HIV replication [10], results of genome-wide association studies [11] and siRNA screens against other viruses (e.g. [12]). Each of these types of data have significant noise in addition to the signal, but filtering over multiple such screens can help clarify the best supported genes (e.g. [6]). Once genes are identified in lists, clicking on the gene name takes the user to detailed annotation at NCBI. For each list, data are housed together with simple descriptions of what is in the list, and what background the genes in the list were drawn from. For published studies, the reference is included as a link to the PubMed entry, allowing easy access to detailed background information. Once genes of interest are identified, lists can be overlapped against additional types of lists for more detailed interpretation. One goal, for example, might be identifying cellular targets for potential antiviral agents. For this, one might want to identify human genes that encode proteins from ‘druggable’ gene families, or genes that are dispensable when knocked out in mice and so might not be toxic when inhibited in humans. Each of these lists are available under ‘Other comparator gene lists’. An important goal of this initiative is to ‘crowd-source’ discovery of human genes important in HIV biology. The Overlapper site currently contains 39 gene lists, which can be formed into more than 500 billion subsets. Obviously no single individual is going to look for overlaps among all the possible subsets by hand. Thus a blog is embedded in the Overlapper site, allowing users to list data sets tested and any interesting results they would like to share. The blog also collects feedback from users on new lists to add or suggestions for improving the site. Last year crowd-sourcing resulted in the solution of the molecular structure of a retroviral protease [13]. X-ray analysis had been performed on crystals of the Mason-Pfizer monkey virus protease, and a low-resolution nuclear magnetic resonance (NMR) structure was available, but the quality of the NMR structure was insufficient to solve the phases in the X-ray data by molecular replacement. Gamers playing Foldit improved the fold inferred from NMR data, allowing researchers to obtain starting phases and ultimately solve the X-ray structure at a high resolution. For genome-wide screens, who knows? Maybe the tools could be made inviting enough that gamers as well as scientists could be lured into playing around with HIV data and identifying some important new host factors.

Human and rat gut microbiome composition is maintained following sleep restriction

Significance It is widely presumed that there is a relationship between sleep and the gut microbiome because both sleep restriction and dysbiosis of the gut microbiome are associated with metabolic diseases such as obesity and diabetes. Here, we report sleep restriction over several consecutive days does not overtly influence the composition of the microbiome of either rats or humans, despite both species showing other changes associated with sleep loss. These analyses suggest that sleep loss and microbial dysbiosis have independent effects on the development of metabolic diseases. Insufficient sleep increasingly characterizes modern society, contributing to a host of serious medical problems. Loss of sleep is associated with metabolic diseases such as obesity and diabetes, cardiovascular disorders, and neurological and cognitive impairments. Shifts in gut microbiome composition have also been associated with the same pathologies; therefore, we hypothesized that sleep restriction may perturb the gut microbiome to contribute to a disease state. In this study, we examined the fecal microbiome by using a cross-species approach in both rat and human studies of sleep restriction. We used DNA from hypervariable regions (V1-V2) of 16S bacteria rRNA to define operational taxonomic units (OTUs) of the microbiome. Although the OTU richness of the microbiome is decreased by sleep restriction in rats, major microbial populations are not altered. Only a single OTU, TM7-3a, was found to increase with sleep restriction of rats. In the human microbiome, we find no overt changes in the richness or composition induced by sleep restriction. Together, these results suggest that the microbiome is largely resistant to changes during sleep restriction.

A Pilot Characterization of the Human Chronobiome

Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome – despite the “noise” attributable to the behavioral differences of free-living human volunteers. The majority (62%) of sensor readouts showed time-specific variability including the expected variation in blood pressure, heart rate, and cortisol. While variance in the multi-omics is dominated by inter-individual differences, temporal patterns are evident in the metabolome (5.4% in plasma, 5.6% in saliva) and in several genera of the oral microbiome. This demonstrates, despite a small sample size and limited sampling, the feasibility of characterizing at scale the human chronobiome “in the wild”. Such reference data at scale are a prerequisite to detect and mechanistically interpret discordant data derived from patients with temporal patterns of disease expression, to develop time-specific therapeutic strategies and to refine existing treatments.

A role for bacterial urease in gut dysbiosis and Crohn’s disease

Bacterial urease activity of the gut microbiota alters nitrogen flux, leading to gut dysbiosis and worsening of colitis in mice. Nitrogen flux and gut dysbiosis Ni et al. used shotgun metagenomic and metabolomic analysis of fecal samples from pediatric patients with Crohn’s disease. They demonstrated an association between disease severity, gut dysbiosis, and free amino acids. A heavy isotope–labeled nitrogen flux analysis showed that bacterial urease activity led to the transfer of host-derived nitrogen to the gut microbiota, boosting amino acid synthesis. Inoculation of a murine host with Escherichia coli engineered to express urease led to dysbiosis associated with worsened immune-mediated colitis and increased amino acid production. A potential role for nitrogen flux in the development of gut dysbiosis suggests that urease may be a potential target for developing treatments for inflammatory bowel diseases. Gut dysbiosis during inflammatory bowel disease involves alterations in the gut microbiota associated with inflammation of the host gut. We used a combination of shotgun metagenomic sequencing and metabolomics to analyze fecal samples from pediatric patients with Crohn’s disease and found an association between disease severity, gut dysbiosis, and bacterial production of free amino acids. Nitrogen flux studies using 15N in mice showed that activity of bacterial urease, an enzyme that releases ammonia by hydrolysis of host urea, led to the transfer of murine host-derived nitrogen to the gut microbiota where it was used for amino acid synthesis. Inoculation of a conventional murine host (pretreated with antibiotics and polyethylene glycol) with commensal Escherichia coli engineered to express urease led to dysbiosis of the gut microbiota, resulting in a predominance of Proteobacteria species. This was associated with a worsening of immune-mediated colitis in these animals. A potential role for altered urease expression and nitrogen flux in the development of gut dysbiosis suggests that bacterial urease may be a potential therapeutic target for inflammatory bowel diseases.

INSPIIRED: A Pipeline for Quantitative Analysis of Sites of New DNA Integration in Cellular Genomes

Integration of new DNA into cellular genomes mediates replication of retroviruses and transposons; integration reactions have also been adapted for use in human gene therapy. Tracking the distributions of integration sites is important to characterize populations of transduced cells and to monitor potential outgrow of pathogenic cell clones. Here, we describe a pipeline for quantitative analysis of integration site distributions named INSPIIRED (integration site pipeline for paired-end reads). We describe optimized biochemical steps for site isolation using Illumina paired-end sequencing, including new technology for suppressing recovery of unwanted contaminants, then software for alignment, quality control, and management of integration site sequences. During library preparation, DNAs are broken by sonication, so that after ligation-mediated PCR the number of ligation junction sites can be used to infer abundance of gene-modified cells. We generated integration sites of known positions in silico, and we describe optimization of sample processing parameters refined by comparison to truth. We also present a novel graph-theory-based method for quantifying integration sites in repeated sequences, and we characterize the consequences using synthetic and experimental data. In an accompanying paper, we describe an additional set of statistical tools for data analysis and visualization. Software is available at https://github.com/BushmanLab/INSPIIRED.