Bacterial DNA and live bacteria have been detected in human urine in the absence of clinical infection, challenging the prevailing dogma that urine is normally sterile. Urgency urinary incontinence (UUI) is a poorly understood urinary condition characterized by symptoms that overlap urinary infection, including urinary urgency and increased frequency with urinary incontinence. The recent discovery of the urinary microbiome warrants investigation into whether bacteria contribute to UUI. In this study, we used 16S rRNA gene sequencing to classify bacterial DNA and expanded quantitative urine culture (EQUC) techniques to isolate live bacteria in urine collected by using a transurethral catheter from women with UUI and, in comparison, a cohort without UUI. For these cohorts, we demonstrated that the UUI and non-UUI urinary microbiomes differ by group based on both sequence and culture evidences. Compared to the non-UUI microbiome, sequencing experiments revealed that the UUI microbiome was composed of increased Gardnerella and decreased Lactobacillus. Nine genera (Actinobaculum, Actinomyces, Aerococcus, Arthrobacter, Corynebacterium, Gardnerella, Oligella, Staphylococcus, and Streptococcus) were more frequently cultured from the UUI cohort. Although Lactobacillus was isolated from both cohorts, distinctions existed at the species level, with Lactobacillus gasseri detected more frequently in the UUI cohort and Lactobacillus crispatus most frequently detected in controls. Combined, these data suggest that potentially important differences exist in the urinary microbiomes of women with and without UUI, which have strong implications in prevention, diagnosis, or treatment of UUI.

Our previous study showed that bacterial genomes can be identified using 16S rRNA sequencing in urine specimens of both symptomatic and asymptomatic patients who are culture negative according to standard urine culture protocols. In the present study, we used a modified culture protocol that included plating larger volumes of urine, incubation under varied atmospheric conditions, and prolonged incubation times to demonstrate that many of the organisms identified in urine by 16S rRNA gene sequencing are, in fact, cultivable using an expanded quantitative urine culture (EQUC) protocol. Sixty-five urine specimens (from 41 patients with overactive bladder and 24 controls) were examined using both the standard and EQUC culture techniques. Fifty-two of the 65 urine samples (80%) grew bacterial species using EQUC, while the majority of these (48/52 [92%]) were reported as no growth at 10 3 CFU/ml by the clinical microbiology laboratory using the standard urine culture protocol. Thirty-five different genera and 85 different species were identified by EQUC. The most prevalent genera isolated were Lactobacillus (15%), followed by Corynebacterium (14.2%), Streptococcus (11.9%), Actinomyces (6.9%), and Staphylococcus (6.9%). Other genera commonly isolated include Aerococcus, Gardnerella, Bifidobacterium, and Actinobaculum. Our current study demonstrates that urine contains communities of living bacteria that comprise a resident female urine microbiota. Overactive bladder (OAB) is a highly prevalent syndrome characterized by urinary urgency with or without urge urinary incontinence and is often associated with frequency and nocturia (1). The etiology of OAB is often unclear and antimuscarinic treatments aimed at relaxing the bladder are ineffective in a large percentage of OAB sufferers, thereby suggesting etiologies outside neuromuscular dysfunction (2). One possibility is that OAB symptoms are influenced by microbes that inhabit the lower urinary tract (urinary microbiota).The microbiota of the female urinary tract has been poorly described; primarily, because a "culture-negative" status has been equated with the dogma that normal urine is sterile. Yet, emerging evidence indicates that the lower urinary tract can have a urinary microbiota (3-8). For example, our group previously reported the use of 16S rRNA gene sequencing to identify bacterial DNA (urinary microbiome) in culture-negative urine specimens collected from women diagnosed with pelvic prolapse and/or urinary incontinence, as well as from urine of women without urinary symptoms (4). Other investigators also have used culture-independent 16S rRNA gene sequencing to obtain evidence of diverse bacteria that are not routinely cultivated by clinical microbiology laboratories in the urine of both women and men (3, 6, 9, 10).Most of our previously sequenced urine specimens underwent standard clinical urine cultures that were reported as "no growth" at a 1:1000 dilution by our diagnostic microbiology laboratory (4). On the basis of this sequence-based evidence, which su...

Objectives To characterize the urinary microbiota in women planning treatment for urgency urinary incontinence and to describe clinical associations with urinary symptoms, urinary tract infection and treatment outcomes. Study Design Catheterized urine samples were collected from female multi-site randomized trial participants without clinical evidence of urinary tract infection and 16S rRNA gene sequencing was used to dichotomize participants as either DNA sequence-positive or sequence-negative. Associations with demographics, urinary symptoms, urinary tract infection risk, and treatment outcomes were determined. In sequence-positive samples, microbiotas were characterized on the basis of their dominant microorganisms. Results Over half [51.1% (93/182)] of the participants’ urine samples were sequence-positive. Sequence-positive participants were younger (55.8 vs. 61.3, p=0.0007), had a higher body mass index (33.7 vs. 30.1, p=0.0009), had a higher mean baseline daily urgency urinary incontinence episodes (5.7 vs. 4.2, p<0.0001), responded better to treatment (decrease in urgency urinary incontinence episodes −4.4 vs. −3.3, p=0.0013) and were less likely to develop urinary tract infection (9% vs. 27%, p=0.0011). In sequence-positive samples, eight major bacterial clusters were identified; seven clusters were dominated by a single genus, most commonly Lactobacillus (45%) or Gardnerella (17%), but also other taxa (25%). The remaining cluster had no dominant genus (13%). Conclusions DNA sequencing confirmed urinary bacterial DNA in many women without signs of infection and with urgency urinary incontinence. Sequence status was associated with baseline urgency urinary incontinence episodes, treatment response and post-treatment urinary tract infection risk.

Various databases have harnessed the wealth of publicly available microarray data to address biological questions ranging from across-tissue differential expression to homologous gene expression. Despite their practical value, these databases rely on relative measures of expression and are unable to address the most fundamental question—which genes are expressed in a given cell type. The Gene Expression Barcode is the first database to provide reliable absolute measures of expression for most annotated genes for 131 human and 89 mouse tissue types, including diseased tissue. This is made possible by a novel algorithm that leverages information from the GEO and ArrayExpress public repositories to build statistical models that permit converting data from a single microarray into expressed/unexpressed calls for each gene. For selected platforms, users may upload data and obtain results in a matter of seconds. The raw data, curated annotation, and code used to create our resource are also available at http://rafalab.jhsph.edu/barcode.

Introduction Many adult women have resident urinary bacteria (urinary microbiome/microbiota). In adult women affected by urinary urgency incontinence (UUI), the etiologic and/or therapeutic role of the urinary microbiome/microbiota remains unknown. Hypothesis Microbiome/microbiota characteristics will relate to clinically relevant treatment response to oral UUI medication. Methods Adult women initiating oral medication treatment for UUI and a comparator group of unaffected women were recruited in a tertiary care health care system. All participants provided baseline clinical data and urine. Women with UUI were given 5mg solifenacin with potential dose escalation to 10mg for inadequate UUI symptoms control at 4 weeks. Additional data and urine samples were collected from women with UUI at 4 and 12 weeks. The samples were assessed by 16S rRNA gene sequencing and enhanced quantitative urine culturing. The primary outcome was treatment response as measured by the validated Patient Global Symptom Control (PGSC) questionnaire. Clinically relevant UUI symptom control was defined as a 4 or 5 score on the PGSC. Results The diversity and composition of the urinary microbiome/microbiota of women with and without UUI differed at baseline. Women with UUI had more bacteria and a more diverse microbiome/microbiota. The clinical response to solifenacin in UUI participants was related to baseline microbiome/microbiota, with responders more likely to have fewer bacteria and a less diverse community at baseline. Non-responders had a more diverse community that often included bacteria not typically found in responders. Conclusions Knowledge of an individual’s urinary microbiome/microbiota may help refine UUI treatment. Complementary tools, DNA sequencing and expanded urine culture, provide information about bacteria that appear related to UUI incontinence status and UUI treatment response in this population of adult women.

T cell dysfunction is an important feature of many chronic viral infections. In particular, it was shown that programmed death-1 (PD-1) regulates T cell dysfunction during chronic lymphocytic choriomeningitis virus infection in mice, and PD-1hi cells exhibit an intense exhausted gene signature. These findings were extended to human chronic infections such as HIV, hepatitis C virus, and hepatitis B virus. However, it is not known if PD-1hi cells of healthy humans have the traits of exhausted cells. In this study, we provide a comprehensive description of phenotype, function, and gene expression profiles of PD-1hi versus PD-1lo CD8 T cells in the peripheral blood of healthy human adults as follows: 1) the percentage of naive and memory CD8 T cells varied widely in the peripheral blood cells of healthy humans, and PD-1 was expressed by the memory CD8 T cells; 2) PD-1hi CD8 T cells in healthy humans did not significantly correlate with the PD-1hi exhausted gene signature of HIV-specific human CD8 T cells or chronic lymphocytic choriomeningitis virus-specific CD8 T cells from mice; 3) PD-1 expression did not directly affect the ability of CD8 T cells to secrete cytokines in healthy adults; 4) PD-1 was expressed by the effector memory compared with terminally differentiated effector CD8 T cells; and 5) finally, an interesting inverse relationship between CD45RA and PD-1 expression was observed. In conclusion, our study shows that most PD-1hi CD8 T cells in healthy adult humans are effector memory cells rather than exhausted cells.

Myocarditis in humans is often associated with an autoimmune process in which cardiac myosin (CM) is a major autoantigen. Experimental autoimmune myocarditis (EAM) is induced in mice by immunization with CM. We found that EAM in A/J mice exhibits a Th2-like phenotype demonstrated by the histological picture of the heart lesions (eosinophils and giant cells) and by the humoral response (association of IgG1 response with disease and up-regulation of total IgE). Blocking interleukin (IL)-4 with anti-IL-4 monoclonal antibody (mAb) reduced the severity of EAM. This reduction in severity was associated with a shift from a Th2-like to a Th1-like phenotype represented by a reduction in CM-specific IgG1; an increase in CM-specific IgG2a; an abrogation of total IgE response; a decrease in IL-4, IL-5, and IL-13; as well as a dramatic increase in interferon (IFN)-gamma production in vitro. Based on the latter finding, we hypothesized that IFN-gamma limits disease. Indeed, IFN-gamma blockade with a mAb exacerbated disease. The ameliorating effect of IL-4 blockade was abrogated by co-administration of anti-IFN-gamma mAb. Thus, EAM represents a model of an organ-specific autoimmune disease associated with a Th2 phenotype, in which IL-4 promotes the disease and IFN-gamma limits it. Suppression of IFN-gamma represents at least one of the mechanisms by which IL-4 promotes EAM.

The ability to measure genome-wide expression holds great promise for characterizing cells and distinguishing diseased from normal tissues. Thus far, microarray technology has only been useful for measuring relative expression between two or more samples, which has handicapped its ability to classify tissue types. This paper presents the first method that can successfully predict tissue type based on data from a single hybridization. A preliminary web-tool is available at http://rafalab.jhsph.edu/barcode/ The high throughput analysis of cells and tissues is revolutionizing biological research. The ability of microarrays to measure thousands of RNA transcripts at one time allows for the characterization of cells and tissues in greater depth than was previously possible, but has not yet led to big advances in diagnosis or treatment. The main reason for this is that feature characteristics, such as probe sequence, can cloud the relationship between observed intensity and actual expression. Although this probe effect is large, it is also very consistent across different hybridizations, which implies that relative measures of expression are substantially more useful than absolute ones 1, 2 . To understand this, consider that when comparing intensities from different hybridizations for the same gene, the probe effect is very similar and cancels out. On the other hand, when comparing intensities for two genes from the same hybridization, the different probe effects can alter the observed differences. For this reason the overwhelming majority of results based on microarray data rely on measures of relative expression: genes are reported to be differentially expressed rather than expressed or unexpressed.Approaches for thresholding noisy data have been successfully used in many applications including microarray studies 3, 4 . We used this as motivation to develop the first method that can accurately demarcate expressed from unexpressed genes and therefore defines a unique gene expression barcode for each tissue type. To do this we took advantage of the vast amount of publicly available datasets. These data were also used to assess the algorithm. With clinical data, we find near perfect predictability of normal from diseased tissue for three cancer studies and one Alzheimer's disease study. The barcode method also discovers new tumor subsets in previously published breast cancer studies that can be used for the prognosis of tumor recurrence and survival time.