s2fieldsofstudy: Biology Medicine

text:
Immunomodulation by memantine in therapy of Alzheimer's disease is mediated through inhibition of Kv1.3 channels and T cell responsiveness

Memantine is approved for the treatment of advanced Alzheimer's disease (AD) and reduces glutamate-mediated neuronal excitotoxicity by antagonism of N-methyl-D-aspartate receptors. In the pathophysiology of AD immune responses deviate and infectious side effects are observed during memantine therapy. However, the particular effects of memantine on human T lymphocytes are unresolved. Here, we provide evidence that memantine blocks Kv1.3 potassium channels, inhibits CD3-antibody- and alloantigen-induced proliferation and suppresses chemokine-induced migration of peripheral blood T cells of healthy donors. Concurrent with the in vitro data, CD4+ T cells from AD patients receiving therapeutic doses of memantine show a transient decline of Kv1.3 channel activity and a long-lasting reduced proliferative response to alloantigens in mixed lymphocyte reactions. Furthermore, memantine treatment provokes a profound depletion of peripheral blood memory CD45RO+ CD4+ T cells. Thus, standard doses of memantine profoundly reduce T cell responses in treated patients through blockade of Kv1.3 channels. This may normalize deviant immunopathology in AD and contribute to the beneficial effects of memantine, but may also account for the enhanced infection rate.

INTRODUCTION
The non-competitive N-methyl-D-aspartate (NMDA) receptor antagonist memantine (Axura ® , Ebixa ® , Namenda ® ) is approved for the treatment of moderate to severe Alzheimer´s disease (AD). Memantine is clinically well tolerated; it facilitates normal neuronal function due to its low affinity and fast off-rate and seems to be efficacious only under pathological conditions [1,2]. Undesired neuronal side effects include somnolence, confusion and headache [3,4]. Side effects on the hematopoietic and immune system have been reported with regard to infections of the respiratory and urinary tract and pancytopenia, and fungi infections were observed in 1-10 out of 1000 treated patients during post-marketing experience [5,6].
Emerging evidence suggests that altered immune responses contribute to the pathophysiology of AD. For instance, T cell proliferation induced by amyloid beta (A-beta) or alloantigens in mixed lymphocyte reactions (MLRs) and transendothelial migration of T cells via the blood brain barrier are enhanced in AD patients compared to age-matched controls [7][8][9][10][11][12][13]. It was also demonstrated that an aberrant, glutamate-dependent modulation increases the activity of K v 1.3 potassium channels on T lymphocytes of AD patients [14]. The key targets of memantine are NMDA receptors and the reduction of glutamatemediated NMDA receptor excitotoxicity is the major mechanism whereby memantine confers neuroprotection in the treatment of advanced AD. However, NMDA receptors seem also to be expressed on non-neuronal cells, Research Paper www.impactjournals.com/oncotarget including human peripheral blood lymphocytes (PBLs) and leukemic Jurkat T cells [15][16][17][18][19][20]. In addition, memantine cross-targets other ligand-gated ion channels like K ir 2.1 channels expressed on macrophages and microglia [21] and suppresses murine lymphocyte function through crossinhibition of K v 1.3 and K Ca 3.1 potassium channels [22,23]. The particular effects of memantine on human T cells, however, are unresolved.
Here, we provide first evidence that application of memantine blocks K v 1.3 channel conductivity, inhibits proliferation and migration of human peripheral blood T cells and induces a strong depletion of the memory CD45RO + CD4 + T cell pool. The data suggest that memantineʼs effect on human T cells suppresses adaptive immune responses and, thereby, contributes to the drugʼs beneficial and unwanted side effects in AD therapy.

Memantine blocks K v 1.3 channels and suppresses the proliferation and migration of primary human T cells
To assess the impact of memantine on the proliferation of human T cells, DNA synthesis of CD3 + cells isolated from peripheral blood mononuclear cells (PBMCs) of healthy donors was evaluated by 3 [H]-Thymidine incorporation in the presence or absence of memantine. Memantine inhibited CD3 Ab-induced T cell proliferation in a concentration dependent manner with an IC 50 of ~40 µM ( Figure 1A, left panel), whereas PMA/ IO-activated T cells were hardly affected ( Figure 1A, middle panel). Memantine doses up to 100 μM did not significantly impair the viability of human T cells (data not shown). Furthermore, we co-cultured T cells with CD3depleted PBMCs of HLA incompatible healthy donors in MLRs. Under these more physiological stimulatory conditions, 1-10 µM memantine reduced T cell proliferation by 10-30% with an IC 50 of ~20 µM ( Figure  1A, right panel). Above results indicate that memantineʼs inhibitory effect on T cell proliferation inversely correlates with the strength of T cell activation.
T-bet is the critical transcription factor induced in differentiating T H 1 cells which are responsive in alloreactive settings [24]. Using intracellular FACS staining and flow cytometry, we found that the percentage of T-bet + T cells reacting to alloantigens in MLRs was profoundly diminished upon memantine treatment ( Figure 1B), which substantiates memantineʼs suppressive effect on human T cell activation and T H 1 cell formation.
Since memory T cells display a lower activation threshold than naïve T cells [25], we analyzed whether memantine has differential effects on those T cell subsets. In MLRs, naïve CD45RO -CD4 + T cells were more sensitive to inhibition at lower memantine concentrations than memory CD45RO + CD4 + T cells, which showed a significant proliferative inhibition only at 30-50 μM memantine ( Figure 1C).
In murine lymphocytes memantine cross-inhibits voltage-gated K v 1.3 potassium channels, which regulate the membrane potential and represent the driving force for Ca 2+ -influx and lymphocyte activation [22,23,26]. Using voltage-clamp recordings, we show here that memantine dose-dependently blocks maximal transient K v 1.3 channel currents of primary human CD3 + T cells. The obtained IC 50 values for memantine were 20 µM and 40 µM for resting and CD3 Ab-activated human T cells, and Hill slope values were 1.2 and 1.6, respectively ( Figure 2A). Memory T cells express higher levels of K v 1.3 channels than naïve T cells [27] and are less dependent on K v 1.3 activity for IL-2 production [28]. Accordingly, memory CD45RO + CD4 + T cells were less sensitive to inhibition of K v 1.3 channel currents by memantine than naïve CD45RO -CD4 + T cells, but only at lower drug concentrations ( Figure 2B). Thus, memantine blocks K v 1.3 channel currents and proliferation of both naïve and memory CD4 + T cells, but in line with a lower activation threshold memory CD4 + T cells require higher drug concentrations.
Effective immune responses depend on the migration of T cells to the sites of inflammation which is driven by chemokines like SDF-1α (CXCL12), which binds to its receptor CXCR4 expressed on T cells. Pretreatment of human CD3 + cells from healthy donors with 20 μM memantine reduced SDF-1α-induced migration of CD4 + and CD8 + T cells through fibronectin-coated as well as uncoated transwells by 50% ( Figure 3). The latter suggests that memantine´s inhibitory effect on T cell migration is not due to a grossly altered adhesive capacity of T cells upon drug treatment. Hence, in vitro application of memantine inhibits K v 1.3 channels and two important T cell responses, proliferation and migration.

Memantine treatment of AD patients depletes memory T cells and suppresses T cell reactivity by inactivation of K v 1.3 channels
To elucidate possible side effects of memantine on adaptive immune responses during therapeutic drug administration, we studied T cell function of AD patients being treated with memantine (Axura ® ). Patients were neuro-physiologically evaluated, diagnosed, treated, and accompanied by physicians of the psychiatric department. Peripheral blood of AD patients was taken after informed consent at three time points: at Z1 before the onset of drug treatment, at Z2 after 1 week of treatment with memantine (Axura ® , 10 mg/d) and at Z3 after additional 11 weeks of treatment with memantine (Axura ® , 20 mg/d, i.e. in total after 12 weeks of daily drug treatment) ( Figure 4A). The effect of memantine therapy on AD patientsʼ T cell responsiveness was analyzed by alloantigen-specific T cell proliferation in MLRs. CD4 + T cells were isolated www.impactjournals.com/oncotarget

Figure 1: Memantine abrogates T-bet expression and proliferation of human T cells. A.
Human peripheral blood CD3 + T cells were stimulated with CD3 Abs (left), PMA/IO (middle) or irradiated, CD3-depleted PBMCs from another healthy donor in MLRs (right) +/-memantine. DNA synthesis was determined by 3 [H]-Thymidine incorporation (cpm). Upper graphs represent a single experiment and lower graphs the mean relative proliferation + SD; n=4-6 and MLR n=3. B. T-bet expression in T cells reacting in MLRs +/-memantine was determined by flow cytometry. The histogram displays a representative experiment and data in the graph the mean + SD percentage of T-bet + cells; n=5. C. The proliferation of naïve CD45ROand memory CD45RO + CD4 + human T cells was analyzed in MLRs +/memantine. Graphs show the data of a representative experiment (left) and the mean relative proliferation + SD of 5 experiments (right). The significance of data was determined with Student´s t test; p*<0.05, p**<0.01, and p***<0.001. from the same AD individual at Z1-Z3 and co-cultured with HLA-incompatible irradiated PBMCs from the same respective healthy donor to evaluate CD4 + T cell reactivity of the same person to the same alloantigens before and during memantine therapy. At time point Z2, CD4 + T cells of most AD patients proliferated less well (10 out of 13 patients, group 1) showing a 46% reduction in DNA synthesis compared to their respective individual proliferation at Z1. For three patients CD4 + T cell proliferation was enhanced at Z2 (group 2). At time point Z3, alloresponses of CD4 + T cells from patient group 1 were further inhibited showing a 5-fold reduction of DNA synthesis compared to Z1 values. CD4 + T cells of patient group 2 now also showed a proliferative inhibition, but it was not significant. Considering all patients, memantine treatment led to a substantial inhibition of T cell alloreactivity with DNA synthesis being suppressed to 32% of pre-therapy values at Z3 ( Figure 4B).
Since immune-pathological studies in AD patients found an increase in memory T cells compared to agematched controls [29][30][31], we determined the distribution of CD45RO + CD4 + T cells within PBMCs of AD patients at time points Z1-Z3. Whereas the percentage of total CD4 + T cells within PBMCs was stable, CD4 + T cells were significantly depleted of CD45RO + cells by 22% at Z2 and by 56% at Z3 compared to Z1 pre-treatment conditions ( Figure 4C). This suggests that memantine mainly affects the CD45RO + T cell pool and may ʻnormalizeʼ the pathological CD4 + subset composition found in AD.
Given that memantine inhibits K v 1.3 channels of human T cells of healthy donors in vitro ( Figure 2) and a possible role of those channels in AD immunepathogenesis [14,21], we determined K v 1.3 channel currents of CD4 + T cells from AD patients at time points Z1-Z3. Interestingly, K v 1.3 currents at Z2 were 40% lower than those recorded at Z1, i.e. before memantine treatment, whereas at Z3 recorded K v 1.3 currents were only reduced by 7% ( Figure 5A). Thus, therapeutic application of memantine suppresses T cell function in AD patients through blockade of K v 1.3 channel activity. Furthermore, analyzing CD4 + T cells of the same AD patient at Z1-Z3, we found an increased K v 1.3 surface expression on naïve and memory CD4 + T cells at Z2 (60% and 55%, respectively) compared to Z1. At Z3, K v 1.3 expression was also enhanced (by 29% and 18%), but it was not significant ( Figure 5B). Thus, blockade of K v 1.3 channel activity by memantine provokes a transient compensatory  therapy were analyzed at time points Z1 (after initial diagnosis and before treatment), Z2 (after one week) and Z3 (after a total of 12 weeks of daily memantine treatment). B. The alloresponse of CD4 + T cells isolated from AD patients at Z1-Z3 was determined in MLRs by 3 [H]-Thymidine incorporation; cpm values at Z1 were set as 100%. The graphs show the mean relative proliferation + SD of T cells from two groups of patients (group 1: 5-10 patients, group 2: 3 patients) responding to memantine treatment in a different manner, and for all (8)(9)(10)(11)(12)(13) patients. C. PBMCs of memantine-treated patients were isolated at Z1-Z3 and analyzed for the content of CD45RO + CD4 + T cells by flow cytometry. The left panel shows representative dot plots for CD4 expression and histograms for CD45RO levels on gated CD4 + T cells. The right graphs display the mean percentage + SD of CD4 + and CD45RO + cells and the number of analyzed patients. The significance of data was determined with Student´s t test with p*<0.05, p**<0.01, and p***<0.001. www.impactjournals.com/oncotarget

DISCUSSION
In this report, we show that memantine suppresses the reactivity of human T lymphocytes of healthy individuals in vitro and of AD patients undergoing memantine (Axura ® ) therapy. The inhibitory effect of memantine on T cell proliferation directly correlated with the drug concentration and inversely with the strength of TCR stimulation, in line with the co-localization of CD3 and K v 1.3 channels in the immunological synapse [32]. A significant inhibition of alloreactive T cell responses in vitro was observed with 1 µM memantine and naïve CD45RO -T cells were more responsive to low memantine concentrations than memory CD45RO + cells or CD3Abactivated T cells. As memantine inhibited the induction of T-bet, which plays a pivotal role in graft rejection [24] and T H 1 migratory programs [33], memantine may also exert potent immunosuppressive function in the prevention of transplant rejection [34,35]. The used standard dose of memantine in the treatment of AD (10-20 mg/d) correlates with memantine serum concentrations below 1 µM [5]. T cells required much higher memantine concentrations for inhibition in vitro. However, standard doses of memantine given to AD patients profoundly reduced ex vivo T cell proliferation to 32% of initial values after 12 weeks of treatment. Thus, even low steady-state doses of memantine have substantial inhibitory side effects on T cell reactivity in vivo as found for higher drug concentration in vitro. It has also to be taken into account that in our experiments memantine was applied only once at the beginning of culture, whereas AD patients received daily medication. For immunosuppressive therapies higher drug doses of memantine may be needed, but memantine doses up to 200 mg/d seem to be tolerated concerning severe central nervous effects [5].
In line with the reported mechanism for NMDA receptor antagonists on murine T cells [22], it is conclusive that memantine significantly reduced K v 1.3 potassium channel currents in human T cells. Compared to resting CD3 + and naïve CD4 + T cells, blockade of K v 1.3 channels on CD3 Ab-stimulated CD3 + and memory T cells required higher memantine concentrations, probably due to an upregulation of K v 1.3 channels upon T cell activation and on memory T cells [27,36,37]. Memantine also suppressed T cell migration towards the chemokine SDF1-α. In view that T cell migration across the blood brain barrier is enhanced in AD patients [8], it is tempting to speculate that memantineʼs beneficial effect in AD treatment involves a reduced migration of inflammatory or A-beta-reactive T cells into the brain [38]. Deregulated T cell responses in the immune-pathogenesis of AD were reported to include an increased percentage of memory versus naïve T cells [29][30][31]. Notably, memantine given in the standard dose to newly diagnosed AD patients, substantially reduced CD45RO + CD4 + T cells. In agreement with reports showing that K v 1.3 channels associate with beta1 integrins [39] and are needed for effector memory T cell migration [40], the depletion of CD45RO + CD4 + T cells may result from a reduced migration of memory cells into the blood stream or an enhanced egression.
Consistent with the in vitro results, K v 1.3 potassium channel currents were significantly lower in CD4 + T cells of AD patients being treated with memantine for 7 days (Z2). However, the inhibition was transient as K v 1.3 channel activity was very similar to untreated cells at 12 weeks of medication (Z3). This correlated with an enhanced surface expression of K v 1.3 channels at Z2, probably representing a compensatory up-regulation of channel expression as a mechanism of tolerance [41]. It is important to emphasize that despite ʻrestorationʼ of K v 1.3 channel activity and surface expression of K v 1.3 channels to pre-treatment conditions at Z3, CD4 + T cells of most AD patients displayed progressively attenuated alloresponses at Z2 and Z3. Therefore, a transient inactivation of K v 1.3 channel activity can correlate with a prolonged T cell unresponsiveness.
In conclusion, our data show that memantine has profound inhibitory effects on human T cells and imply that the beneficial effects of memantine in the treatment of AD may involve immunomodulation of T cells and a normalization of deviant immune functions. The drugʼs inhibitory side effects on T cells may also account for the enhanced infection rate during memantine application [5]. Since K v 1.3 channel inhibitors are still quested for clinical use [42,43], it seems worthwhile to further evaluate memantine´s potential as an immune-modulating drug in the treatment of AD, autoimmune diseases or transplant rejection [44,45].

Ethics statement
Investigation has been conducted in accordance with the ethical standards and according to the Declaration of Helsinki and German guidelines and has been approved by the authorsʼ local institutional review board (MD133/13). Written consent was obtained from all AD patients.

Isolation of human T cells and proliferation assay
PBMCs were isolated with Biocoll Separating Solution (Biochrom AG, Berlin, Germany) and density gradient centrifugation. Isolation of CD3 + cells from PBMCs was performed with the human Pan T Cell Isolation Kit 2 and AutoMACS (Miltenyi Biotec, Bergisch-Gladbach, Germany). Naïve and memory CD4 + T cells were isolated from PBMCs with human Naïve CD4 + T Cell Isolation Kit 2 and human Memory CD4 + T Cell Isolation Kit (both Miltenyi Biotec). For patch-clamp analyses, isolation of naïve and memory CD4 + T cells was performed with EasySep™ Human Naïve and Human Memory CD4+ T Cell Enrichment Kits (STEMCELL, Vancouver, Canada). Purity of isolated naïve or memory CD4 + T cells was 80-90%. For proliferation assays, isolated T cells were cultured in AIM-V medium (Gibco, Life Technologies, Darmstadt, Germany) and stimulated with MEM92 (CD3 IgM Ab supernatant) or PMA and ionomycin (IO; each 100 ng/ml, Sigma-Aldrich, Hamburg, Germany) in the presence or absence of memantine (R&D Systems, Minneapolis, USA; Tocris Bioscience, Wiesbaden-Nordenstadt, Germany) in the indicated concentrations. 96-well plates were pre-coated with AffiniPure goat antimouse IgG+IgM (H+L) (Jackson ImmunoResearch Europe Ltd., Suffolk, UK) over night at 4°C, washed and incubated with MEM92 supernatant. DNA synthesis was determined in triplicates at 72 h of culture by 3 [H]-Thymidine incorporation (0.2 µCi/ well, MP Biomedicals Europe, Heidelberg, Germany) for 16 h. For MLRs, isolated CD4 + T cells were stimulated with T cell-depleted and irradiated (30 Gy) PBMCs from another healthy donor in 1:3 ratios. Cells were co-cultured for 120 h and DNA synthesis was determined by 3 [H]-Thymidine incorporation for 16 h. In MLRs, the expression of T-bet in responding T cells of healthy donors was analyzed with the intracellular staining kit (Foxp3 Staining Buffer Set, eBioscience, San Diego, USA) using T-bet-PE Ab (clone 4B10, eBioscience) and flow cytometry.

Migration assay
Isolated CD3 + cells (4x10 6 ) remained untreated or were pre-incubated with memantine (20 and 50 µM) for 30 min in AIM-V medium (Gibco ® , Life Technologies) supplemented with 0.1% bovine serum albumin and 10 mM HEPES (pH 7.4) and then transferred unto uncoated or fibronectin-coated (6.5 µg/ml; Roche Diagnostics, Basel, Switzerland) transwell chambers (6.5 mm diameter and 3.0 µm pore; Corning Costar, Tewksbury, MA). Cells were allowed to migrate towards human SDF-1α (100 ng/ml; PeproTech, Hamburg, Germany) for 150 min at 37°C. Migration in the absence of chemokine served as a control. Migration was stopped by the addition of 0.1 M EDTA. Migrated cells were stained with CD4-PE and CD8-FITC Abs (BD Pharmingen, Heidelberg, Germany) and acquired for 30 sec at a FACSFortessa TM (BD Bioscience, Heidelberg, Germany). Relative migration was determined by defining the number of cells that migrated in the absence of memantine (mem. 0 µM) as 100%.

Patch-clamp analysis
Whole-cell configuration patch-clamp analysis of human peripheral blood T cells was performed as described (22). In brief, K v 1.3 currents were recorded with an external solution containing 160 mM NaCl, 4.5 mM KCl, 5 mM HEPES, 1 mM MgCl 2 , 2 mM CaCl 2 , pH 7.4. The pipette solution was 162 mM KF, 11 mM EGTA, 10 mM HEPES, 1 mM CaCl 2 , 2 mM MgCl 2 , pH 7.2. Osmolarity was set to 300-340 mOsm. K v 1.3 currents were measured every 30 s with depolarizing voltage steps up to +60 mV from a holding potential of -80 mV. Sampling rate during the measurement of K v 1.3 currents was 50 kHz. The analysis of transient currents was done with HEKA FitMaster v2x53 and dose-response curves and Hill slopes were determined from amplitude values in GraphPad Prism 5.0.

Analysis of T cells from AD patients
18 ml of blood, with heparin as anti-coagulant, was collected from AD patients for T cell proliferation and FACS analyses. In addition, routine blood analyses were performed, including determination of differential blood cell counts, levels of C-reactive protein, glucose, lipids, liver enzymes, and thyroid hormones. None of the subjects was excluded due to changes in these routine blood parameters. Also, no person had a history of autoimmune disorders, immuno-modulating treatment, cancer, chronic terminal disease, severe cardiovascular disorder, substance abuse or severe trauma. Peripheral blood samples were taken at three time points: before drug treatment (Z1), after 1 week of treatment with memantine (Axura ® , 10 mg/d, Z2) and after 12 weeks of drug treatment (Z2 plus Axura ® , 20 mg/d for another 11 weeks, Z3). Isolation of CD4 + T cells from PBMCs of patients was performed with the human CD4 + T Cell Isolation Kit (Miltenyi Biotec) and AutoMACS. Cells were cultured in AIM-V medium. For MLR experiments at Z1-Z3, isolated CD4 + T cells were cocultured with irradiated (30 Gy) total PBMCs from healthy donors for 5 days. Proliferation of CD4 + T cells from the same AD patient was analyzed at Z1-Z3 to compare individual proliferation values before and after drug treatment. PBMCs from the same healthy donor were used as stimulator cells at time points Z1-Z3. DNA synthesis was determined by 3 [H]-Thymidine incorporation at 120 h. For FACS analyses, patientsʼ PBMCs were stained with K v 1.3 (extracellular)-FITC (polyclonal, Sigma-Aldrich), CD45RO-PE (clone UCHL1, eBioscience) and CD4-APC Abs (clone OKT4, BioLegend, San Diego, USA) and analyzed on a FACSFortessa TM . K v 1.3 expression on T cells was analyzed for the same patient at Z1-Z3. The percentage of total CD4 + and CD45RO + CD4 + T cells and patch-clamp analyses at Z1-Z3 were determined on blood samples taken from different patients as drug pretreatment values at Z1 did not significantly differ between individuals.

Statistical analysis
Flow cytometry data were analyzed with Cell Quest Pro (Becton Dickinson, San Jose, CA, USA) or Flow Jo V3.6.1 (Tree Star, Ashland, OR, USA) software.


extfieldsofstudy: Biology Medicine

text:
Probiotic lactic acid bacteria – the fledgling cuckoos of the gut?

It is tempting to look at bacteria from our human egocentric point of view and label them as either ‘good’ or ‘bad’. However, a microbial society has its own system of government – ‘microcracy’ – and its own rules of play. Lactic acid bacteria are often referred to as representatives of the good ones, and there is little doubt that those belonging to the normal intestinal flora are beneficial for human health. But we should stop thinking of lactic acid bacteria as always being ‘friendly’ – they may instead behave like fledgling cuckoos.

L actic acid bacteria, particularly the rod-shaped lactobacilli, are generally regarded as being of a friendly disposition. They are members of the normal microbial ecosystem in the intestinal tract and seem to play a key role in maintaining stability and diversity of the gut microbiome (1).
Lactic acid bacteria protect their own ecological niches by producing lactic acid, antibacterial peptides (bacteriocins), and H 2 O 2 , and this is how they counteract infections in the vagina (2). If the abundance of lactic acid bacteria for some reasons is declining, their protective function will inevitably be reduced, and epithelial tissues become more prone to staphylococcal infection and to overgrowth of Candida albicans (2). We envisage that something similar is taking place in the intestines of irritable bowel syndrome (IBS) patients (3).
In the presence of oxygen, lactic acid bacteria produce H 2 O 2 that chemically and enzymatically will be converted into oxygen radicals with more potent antimicrobial activity than H 2 O 2 itself. These reactive oxygen species may also act as signal molecules in the communication between gut microbiota and the intestinal mucosa (4). Like aerobic and facultative anaerobic bacteria, lactic acid bacteria are very tolerant to H 2 O 2 and to reactive oxygen species. Anaerobic bacteria are, however, highly sensitive.
Lactic acid bacteria will efficiently capture remaining oxygen in the otherwise oxygen-starved environment distally in the intestine, thereby supporting the strictly anaerobic colonic bacteria in their production of shortchain fatty acids by anaerobic fermentation of unabsorbed food components Á highly beneficial for human health (5). At the same time, they will, unlike facultative anaerobic bacteria that also consume oxygen, produce H 2 O 2 and reactive oxygen species and thereby create a microenvironment around their aerobic niches that is more toxic for anaerobic bacteria than oxygen itself. Even in the strict anaerobic gut environment, oxygen may still be available in close vicinity of epithelial cells. Is so, that is, the most likely ecological niche for lactic acid bacteria in the anaerobic sections of the gut.
Imbalances of the gut microbial community (dysbiosis) are associated with various clinical conditions, including IBS (6). Earlier culture-based studies indicated low fecal levels of lactobacilli in patients with IBS (7), although newer studies using molecular techniques do not always agree (6). Failing anaerobicity within the colon may be a pathogenicity mechanism, since it may result in reduced diversity of the gut microbiota, increased aerobic glycolysis within human cells, toxin production (methylglyoxal), and oxidative stress (8,9).  believed that such products are beneficial for human health. However, there are few well-documented clinical benefits (2) and hardly any benefits persisting after termination of probiotics intake (10).
Species and strains of lactic acid bacteria used as probiotics and starter cultures for food preservation are selected on basis of their ability to produce antimicrobial substances (11Á13). Is this the reason why probiotic lactic acid bacteria do not succeed to colonize the intestine? Do they behave like fledgling cuckoos that push their fellow nestlings out of the nest ( Fig. 1) before they fly the nest themselves?

Weight gain and obesity
Excessive weight gain and obesity have become a global epidemic that may have a microbial cause (14,15), albeit not infectious. The condition is associated with changes within the intestinal flora and can be transmitted through fecal transplantation in animals Á and perhaps also in people (16). Commercial supplements of lactic acid bacteria stimulate weight gain in chicken and pigs, and some reports have suggested that the same may be the case also in humans (17). On the basis of a meta-analysis, Raoult and his team concluded that some lactic acid bacteria cause weight gain while others do not (18). That depends on the bacterial strain. It should also be kept in mind that species and strains causing weight gain in chicken and pigs not necessarily will do the same in humans, hence limiting the relevance of animal testing in order to screen for weight-gaining properties of specific probiotics for human use (19).
There are papers showing that probiotic lactic acid bacteria may prevent and treat obesity (20). However, the general limitations of all the referred trials have been small sample sizes and absence of follow-up studies demonstrating that the anti-obesity effects persist after termination of probiotics administration.
Antibiotics may cause weight gain in animals as well as in humans (21), and antibiotics have been used for many years as growth promoters for pigs and poultry (22). Following banning of such use of antibiotics in animal husbandry, growth-promoting probiotics have been taking their place. It may be that the effects of antibiotics and probiotics have a common ground, namely, affecting the ecological condition of the microbiota (23), favouring an 'obesogenic' microflora. Antibiotics administered in early life to animals may cause long-lasting changes in gut microbiota and obesity (24). It cannot be ruled out that this may also apply in humans (25), and accordingly, there are reasons to restrict using bacteriocin/antibioticsproducing lactic acid bacteria as probiotics Á in particular to young children (11,26).

Killing of fellow nestlings
Lactic acid bacteria occurring naturally in milk are killed during the pasteurization process. As a consequence, pasteurized milk will not curdle in the same way as nonpasteurized milk. Today, starter cultures of specific lactic acid bacteria, grown in fermenters, are used in the manufacturing of soured milk products, such as yoghurts. If such starter culture bacteria are selected based on their ability to produce bacteriocins and antibiotics (12), it should not be disregarded that they behave like fledgling cuckoos.
Lactic acid bacteria produce bacteriocins that kill closely related gram-positive bacteria (1). Only a few days after last oral intake of lactic acid bacteria in probiotic preparations, it is normally not possible to detect them within the gut, and permanent colonization of added probiotics has never been documented (1).
Clinical experience by two of us (AB, JV) has convinced us about the validity of the fledgling cuckoos analogy. We have observed that the total number of lactic acid bacteria in feces of patients with IBS does not increase after probiotics use Á quite the opposite. Our experience is in line with published data showing that the already sparse numbers of lactic acid bacteria in patients suffering from IBS are further reduced after treatment with probiotics (27). This is a logical consequence, as we see it, of adding bacteria that kill their closest relatives within the gut.
On the other hand, there are patients who have experienced positive effects of using probiotics, for instance, against IBS and other gastrointestinal discomforts. This may depend on species of probiotics and on subgroups of IBS tested (6). In general, however, effects are marginal and meta-analyses generally conclude that more and better studies are needed to confirm results from controlled clinical studies (28). It should also be taken into account that there may be a certain publication bias in this area, since negative results with commercial products not necessarily have been published. Farup and his team have, however, demonstrated that IBS patients had increased abdominal pain when treated with probiotic lactic acid bacteria (29).
It is a commonly held view that bacteriocins produced by lactic acid bacteria inhibit only closely related species and that bacteriocins therefore will not likely change the gross composition of the gut microbiota, at least not to the same extent as conventional antibiotics. This view is supported by studies showing that the microbial composition of feces is not largely altered after administration of probiotics (30). But this does not necessarily apply for all probiotic preparations. For example, Lactobacillus rhamnosus produces a 'bacteriocin' that inhibits bacterial species belonging to other families (13), and there are lactic acid bacteria producing antimicrobial substances that inhibit many different microbial species (11,12). Probiotic lactic acid bacteria may therefore combat not only their closest relatives, but also other bacterial species in the healthy gut microbiota. We have not found any published papers on the effects of such bacteriocins on anaerobic intestinal bacteria, the most important players in maintaining ecological stability of gut microbiota.
Tilapia, the world's second largest fish species in aquaculture, has its biological origin in eutrophic lakes in East Africa where it feeds on planktonic algae and detritus. It is a very hardy species in its natural environment, but in aquaculture it is susceptible to opportunistic pathogens like other cultured fish species. Tilapia has been used as a very interesting organism for model studies on dysbiotic gut conditions of relevance for humans (31) and has elegantly confirmed our 'fledgling cuckoos' hypothesis. The fish stayed healthy on the addition of a probiotic containing Lactobacillus strains, but upon termination of the treatment the fish developed gut microbiota dysbiosis similar to that caused by antibiotics, resulting in reduced resistance to infection. Moreover, the probiotic bacteria disappeared from the gut after termination of probiotics use.
It is established knowledge that interfering with the intestinal flora may have harmful consequences for human health, but there are not yet reliable biomarkers for a healthy gut microbiota, with the possible exception of indole. Indole is produced by microbial tryptophan catabolism in the colon, and a normal indole concentration seems to indicate a healthy intestinal flora (32). Indole is metabolized and excreted within urine as indoxyl sulfate. In cases of chronic kidney failure, there are increased concentrations of indoxyl sulfate in the blood, and since this metabolite works as a uremic toxin, interventions seek to reduce its urinary excretion, for instance, by administering probiotics (33). It is noteworthy that there is a clear correlation between reduced urinary excretion of indoxyl sulfate and scarcity of lactic acid bacteria in the feces (34). And more importantly, low perioperative levels of indoxyl sulfate in the urine constitute the principal predictor of a fatal outcome for bone-marrow transplants (35).

Rare side effects
In special circumstances, probiotic bacteria may translocate into the blood and cause bacteraemia/sepsis, liver abscess, endocarditis, and death (2). In one study, mortality increased in patients with acute pancreatitis who were tube fed with probiotics (36). The use of probiotics should therefore be considered with care, at least in such cases, hence in line with the advice from The Norwegian Scientific Committee for Food Safety (VKM) against the use of probiotics for critically ill patients (www.vkm.no/dav/009488e0b8.pdf).

Concluding comments
When they are members of a stable gut microbiota, lactic acid bacteria undoubtedly play an important role in maintaining good health. The mechanisms involved are apparently quite complex, involving immune modulation, production of peroxides, acid and bacteriocins, and also proteins that alter epithelial permeability and bind to intestinal receptors for pathogen (37). Their immunomodulating properties may, for example, be of fundamental importance in the development of mucosal and systemic immune tolerance (38). Therefore, if they for some reasons are outnumbered in the gut microbial ecosystem, resulting in disease conditions, it is a tempting strategy to replace them by oral administration of lactic acid bacteria produced in fermentation culture. The idea has proved to be good in the prevention of allergy and asthma (39), and it seems to be a very good idea to select strains of probiotic bacteria that will survive in the intestine and produce GABA (g-aminobutyric acid) (40), an inhibitory neurotransmitter deficient in children suffering from ADHD (41). Lactic acid bacteria with strong bacteriocidal effects have been exploited in the eradication of methicillin-resistant Staphylococcus aureus infections (42). But use of probiotics may have its downsides. Strains of lactobacilli producing bacteriocins and other antimicrobial substances may have an 'antibiotic-like' effect for short duration, but at the same time they may eradicate their closest relatives and pave the way for a dysbiotic gut microbiota, resulting in other health problems. Furthermore, we do not know what might be the implications of overwhelming the complex gut microbiota by introducing very high numbers of one or a few alien bacterial species.
The warning of the author Edith Wharton (1862Á 1937) is apparently relevant also in our case: 'Beware of monotony; it's the mother of all the deadly sins'.


extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy: Biology Psychology

text:
Administration of orexin receptor 1 antagonist into the rostral ventromedial medulla increased swim stress-induced antinociception in rat.

Objective(s): Intracerebroventricular injection of orexin-A (hypocretin-1) antagonist has been shown to inhibit stress-induced analgesia. However the locations of central sites that may mediate these effects have not been totally demonstrated. This study was performed to investigate the role of rostral ventromedial medulla (RVM) orexin receptor 1 in stress-induced analgesia (SIA). Materials and Methods: Forced swim stress in water was employed to adult male rats (200-250 g). Nociceptive responses were measured by formalin test (50 µl injection of formalin 2% subcutaneously into hind paw) and, pain related behaviors were monitored for 90 min following intra-microinjection of SB-334867 (orexin receptor 1 antagonist) into RVM. Results: Exposure to swimming stress test after administration of SB-334867 into RVM significantly reduces the formalin-induced nociceptive behaviors in phase1, interphase, and phase 2 in rats. Conclusion: The result demonstrated the involvement of OXR1 in antinociceptive behaviors induced by swim stress in RVM.

Introduction
Pain inhibition reaction that happens after exposure to a stressful situation called stressinduced analgesia SIA (1). Experimental animal models of this phenomena help to find potential therapeutic agent for disorders associated to pain and stress (1). Stress is shown to activate a neural and hormonal cascade that induced analgesia in animals and humans (2,3). Analgesic responses to stress are mediated by opioid and non-opioid mechanisms (1,4). It has been shown that blocking of endogens opioid system induced SIA, supporting that endogenous opioid system is involved in SIA. Some experiments have been shown that blockade of endogens opioid system cannot reverse SIA, it may be concluded that non-opioid mechanisms might be involved in SIA regulation (1,5,6). Consist with this, it has been shown that hypocretins 1 and 2 (orexin A and B) is synthesized by neurons in lateral hypothalamus and this neuropeptide represent a significant role in pain transmission (1,7,8).
Rostral ventromedial medulla (RVM) (includes the raphe nuclei and adjacent reticular formation) can be viewed as the brainstem output for pain modulation system (PAG-RVM) (22,23). In addition, several studies indicated that non opioid neuropeptide (orexin) in RVM has some roles in pain modulations (24,25). In this study, we were interested to investigate the role of RVM OX1 receptors in modulation of SIA.

Subjects
Adult male Wistar rats (200-250 g) were housed in temperature controlled cages, under a 12 hr Light/dark cycle with light on at 7 am to 7 pm and given ad libitum food and water. All behavioral tests started at approximately the same time each day. We did all experimental procedures followed the guidelines of the committee for Research and Ethical Issues of the International Association for the Study of Pain. In addition, experimental protocols were approved by animal ethic committee of Rafsanjan University of Medical Sciences.

General procedure
Initially rats were anaesthetized with ketamine (100 mg/kg) and xylazine (10 mg/kg) and then animal , s head was shaved and cleaned after that rat was placed in surgery apparatus, skin was cut and connective tissues removed. For direct Intra-RVM administration, we used standard stereotaxic equipment, stainless and cannula (23 Gauge) was implanted according to coordinates from the atlas of Paxinos and Watson (anteroposterior -11.0 mm from bregma, lateral 0 from midline, dorsoventral -8.5 mm from the cranium) (26). The guide cannula was anchored to two screws in skull by dental cement.
Testing began 7 days following surgery and rats were transferred to experimental room 60 min before drug injection to get used to new situation. Stainless steel cannula (30 Gauge, 0.3 mm outer diameter) as injection cannula that connected through a polyethylene tube to Hamilton syringe, inserted through the guide cannula and extended 2 mm beyond the tip of the guide cannula to reach the RVM. Microinjection was in a volume of 0.5 µl while the rat was gently restrained by hand over a period of 60 sec. Injection cannula removed 1 min later.
Testing was followed by stress procedures (6 min forced swim stress) and drying animals and then (not later of 10 min) formalin was injected into planter surface of right hand paw to induce nociception.

Swim stress test procedure
Firstly rats were transferred to experimental room to habituate and then swim stress occurred immediately after drug or vehicle injection. For swim stress, rats were forced to swim in a plastic pool containing 50 cm of water at 20 ºC during 6 min. Immediately rats were dried to follow the testing (27).

Formalin test
Before the commencement of this part of testing, to minimize environmental stress, rats were acclimatized for 30 min in formalin box. During the test, temperature was maintained at 24-26 °C. Then formalin 2٪ was injected subcutaneously into the planter surface of the right hind paw. Formalin injected was in volume of 50 µl with a 30 Gauge needle. Immediately rats returned to Plexiglas formalin box that is measured 34˟34˟34 and a mirror below the floor of box with angle 45º to permit observing of rats nociceptive responses. The formalin test was carried out according to weighed scores or rating scale method. Nociceptive were rated as followed: 0, the injected paw was not favoured; 1, the injected paw had little or no weight placed on it; 2, the injected paw was elevated and not in contact with any surface; and 3, the injected paw was licking or biting of the injected paw. The score obtained from nociceptive behaviours for each 3 min interval was calculated as the weighted average of the number of seconds spent in each behaviour, from the beginning of the experiment. In each group, the behavioural responses of each rat was evaluated during 90 min that divided to the first phase (1-7 min), inter-phase (8-14 min) and the second phases (15-90 min) (28,29).

Experimental protocols
Three sets of experiments in this study were considered: 1) Rats were just given formalin injection as control group and in sham group, animals (after stereotaxic surgery) were given formalin 6 min after exposing to swim stress 2) Rats were RVM microinjected drugs (SB-334867 / saline) followed by formalin injection. 3) Rats first had RVM microinjected drugs (SB-334867 /saline) then performed forced swim stress (for 6min) and then received formalin.

Histology
At the end of the experiment rats were deeply anaesthetized with overdose of ketamine followed by injecting a volume of 0.5 μl of pontamine sky blue (0.2%) into the cannula site. Later, rats were transcardially perfused with 100 ml of 4% formalin solution and then animals sacrificed. The brains were removed and sectioned. Only those rats whose microinjection and diffusion site were located within the RVM were included in the results (29).

Statistics
Data were presented as mean±SEM. The formalin pain score in all groups were analyzed by one-way analysis of variance followed by Dunnett's test for multiple comparisons as needed. The first phase (1-7 min), interphase (8-14 min), and second phase (15-90 min) of the formalin test were analyzed separately while using one time point for each phase: a time course of 7 min for phase 1 and interphase, and a 75 min-duration for phase 2. The defined level for statistical significance was (P<0.05).

Nociceptive behaviors following injection of formalin into rats' hind paw
Injection of formalin produced typical biphasic pain responses that were monitored for 90 min ( Figure 2). The first and second phases were separated by brief interphase with little nociceptive behavior. The second phase was further subdivided into two sub phases (phase 2a and phase 2b).

The effect of SB-334867 (0.1 and 1 mmol) microinjected into RVM on formalin-induced nociceptive behaviors
To evaluate the effect of SB-334867 on formalin test, we microinjected 2 different doses of SB-334867 (0.1 mmol and 1 mmol) into RVM and followed by hind paw formalin injection (Figure 1). Both doses of SB-334867 failed to produce significant effect on formalin induced nociceptive behaviors in the phase 1, interphase, phase 2A and phase 2B (P>0.5).

The effect of swim stress on nociceptive behaviors in formalin test
To evaluate the effect of swim stress on formalin induced nociceptive responses, swim stress was applied for 6 minutes before formalin injection. Results demonstrated that swim stress could attenuated nociceptive behaviors in the phase1 and phase 2A (all P<0.05) and in interphase (P<0.01) of formalin test. However, in phase 2B, Appling swim stress potentiated nociceptive responses in formalin test (P<0.01) (Figure 3 and 4).

The effect of 0.1 mM SB-334867 microinjection into RVM on antinociceptive behaviors induced by swim stress in formalin test
Intra-RVM microinjection of SB-334867 (0.1 mmol) before exposing the animals to swim stress could attenuate formalin induced nociceptive behaviors in phase1 (P<0.05), phase 2A (P<0.01) and phase 2B (P<0.05) compared to the group that received saline and then exposed to swim stress (swim stress group). However, nociceptive behaviors were not affected by SB-334867 (0.1 mmol) in the interphase of formalin test (P>0.05) (Figure 3).

The effect of 1 mmol SB-334867 microinjection into RVM on antinociceptive behaviors induced by swim stress in formalin test
Intra-RVM microinjection of SB-334867 (1 mmol) before exposing the animals to swim stress also could attenuate formalin induced nociceptive behaviors in phase1, phase 2A and phase 2B (all P<0.05) compared to the group that received saline and then exposed to swim stress (swim stress group). However, nociceptive behaviors were not affected by SB-334867 (1 mmol) in the interphase of formalin test (P>0.05) (Figure 4).

Discussion
In this study we investigated the role of Orexin-A receptor in the RVM (Rostral Ventromedial Medulla) in stress-induced analgesia. Our results demonstrated that antinociceptive responses which induced by swim stress were significantly potentiated by a prior microinjection of OX1R antagonist (SB-334867) in phase 1, 2a and 2b of formalin test.
Also we clearly demonstrated that application of forced swim stress during 6 min as acute stress reduced the formalin-evoked nociceptive behaviors in phase 1, inter phase and initial part of phase2. Abundant studies have shown that acute exposure of animals to stressful situation produce antinociception measured by different pain models (1,30,31). Formalin injection induces nociceptive bahaviour in phase I and II, with a quiescent phase between them. While active inhibitory mechanisms are proposed to be responsible for initiation of interphase termination of the nociceptive response in phase 2 (32). However, some stress parameters could also give rise to raise pain sensitivity, called stress-induced hyperalgesia (33). Several studies have indicated that SIA mediated by top-down inhibitory pain pathway to spinal cord (1).
Although opioid system appears to be pivotal mediators in antinociception response in SIA (1,4,34), numerous studies now support that inhibition of pain in SIA don't depend on the endogenous opiates (i.e. it is not reversed by the opioid antagonist and is not produced a change in morphine-tolerance animals) (30). Orexin-A microinjection into the lateral ventricle produced tolerance to the anti-nociceptive effect of this peptide (35). Since the administration of OX1R antagonist into RVM led to increase antinociception response in SIA we hypothesized that OX1R might mediate non-opioid inhibitory pain role in RVM in SIA. There are limited evidences that orexinergic system might be connected with induction of analgesia in stress. For example Gerashchenko et al indicated that direct block orexin neurons in lateral hypothalamus by nociceptin/orphanin FQ prevents stress-induced analgesia development in rat (36). Consist with this OXR knockout mice show higher degree of hyperalgesia caused by peripheral inflammation and reduced degree of SIA than the wild type mice (37). Recently Azhdari-Zarmehri et al indicated that direct ICV administration of OX1R antagonist attenuates swim-and restraint stressinduced analgesia in formalin test (28). Taking our previous result together with current results, one can conclude that the effects of Orexin-1 in SIA might be depend on location of drug administration. So that administration of orexin-1 antagonist in cerebral ventricles reduce SIA while administration of this drug in RVM increase SIA .
The RVM consist of nucleus raphe magnus and adjacent reticular nuclei which play bidirectional role in top-down pain control system (1,(38)(39)(40)(41).The neuronal population within the RVM is divided to three classes: on-cells, off-cells and neutral cells (33,34). On-cells are characterized by a burst of activity during noxious reflexes and they are inhibited by µopioid agonists (42,43). Conversely, Off-cells as pain-inhibiting neurons are identified by a pause of activity during noxious reflexes and their activity are increased with morphine (44,45). The remaining cells, neutral-cells don't show any change in firing activity associated with nociception (46).
There are reports demonstrating that orexin-A can modulate on and off-cells in RVM. For on-cells, it was reported that both spontaneous and ongoing activity of these cells were inhibited by orexin-A following thermal analgesia.
For off-cells, it was reported that spontaneous activity of these cells were increased by orexin-A following thermal analgesia, whereas the neutralcells were unaffected (47,48).
The decrease in on-cell firing rate by Orexin-A and the increase in off-cell spontaneous firing rate might be involved in Orexin-A induced analgesia.
The reduction in the nociceptive behaviors during stress was not significant when orexin-A as agonist OXR1 were microinjected into RVM. Multiple lines of evidence indicate that a potential involvement of orexinergic system in pain modulation and in stressrelated behaviors (28,35,36,48). The role of orexin in generation of SIA was first indicated by Watanabe and his colleagues (37). More recent work suggests that during arousal and stress-like conditions, orexinergic system is activated (20,49). Initial support for involvement of orexin in pain modulation came from an experiment in which intracerebroventicular (ICV) administration of Orexin-A caused a dose-related antinociceptive behaviors in the hot plate test in rats (50). In agreement with this, it was reported that the intra-PAG administration of Orexin-A attenuate the inter phase and phase 2 in formalin-induced nociceptive responses in rats without any significant effect on tail-flick latency (29).
SB-334867 as putative Orexin receptor antagonist just adheres to type1 Orexin receptors (28,29). But, Orexin-A as agonist OXR have an affinity to type2 orexin receptors (51,52). Some testing has shown OXR1 and OXR2 exhibited strikingly different distribution in rat brain. Within RVM (8,29), OXR1 mRNA is more abundant than OXR2 mRNA (21). Although some experimental studies have demonstrated that OXR1 activation produces analgesic effect rather than OXR2. Even OXR2 activation elicits an excitatory effect on pain modulation (53). It is thus possible that application of OXR2 may be effective in our result. However, more experiments is needed to confirm this hypothesis.
More recently, some studies have demonstrated that descending pain-inhibitory system in RVM is more compatible than descending pain-facilitator system especially during abnormal situation such as chronic inflammation (54,55). We could hypothesize SIA (stress induced analgesia) as abnormal situation could trigger pain-inhibitory system. Consist with this, several old studies have revealed that a majority of neuronal population of the RVM is made of GABAergic neurons that are involved the locally projecting (56,57) or reticulospinal neurons (58). During normal situation intrinsic GABAergic neurons elicit inhibitory effect on the inhibitory descending control of dorsal horn from RVM (56,59). On the other hand, in unusual situation leading to a block of GABAergic neurons and consequently decreasing effects on descending inhibitory system (54). In the previous studies we showed the role of the RVM in formalin-induced nociceptive behaviors and inactivation of RVM modulated stress-induced analgesia in formalin test (60-63).
A limitation of study described above is restricted doses of antagonist of OXR1 that we used. It will be of interest, to survefazhdy on-cells and off-cells in RVM novel methods such as optogenetics.

Conclusion
This study is suggested that OXR1might be involved in stress-induced analgesia phenomenon within RVM, hence blocking of OXR1 in RVM led to exaggerate SIA. from the thesis prepared by Neda Soleimani to fulfill the requirements for the Master degree in physiology.


text:
hMYH and hMTH1 cooperate for survival in mismatch repair defective T-cell acute lymphoblastic leukemia

hMTH1 is an 8-oxodGTPase that prevents mis-incorporation of free oxidized nucleotides into genomic DNA. Base excision and mismatch repair pathways also restrict the accumulation of oxidized lesions in DNA by removing the mis-inserted 8-oxo-7,8-dihydro-2'-deoxyguanosines (8-oxodGs). In this study, we aimed to investigate the interplay between hMYH DNA glycosylase and hMTH1 for cancer cell survival by using mismatch repair defective T-cell acute lymphoblastic leukemia (T-ALL) cells. To this end, MYH and MTH1 were silenced individually or simultaneously using small hairpin RNAs. Increased sub-G1 population and apoptotic cells were observed upon concurrent depletion of both enzymes. Elevated cell death was consistent with cleaved caspase 3 accumulation in double knockdown cells. Importantly, overexpression of the nuclear isoform of hMYH could remove the G1 arrest and partially rescue the toxicity observed in hMTH1-depleted cells. In addition, expression profiles of human DNA glycosylases were generated using quantitative reverse transcriptase–PCR in MTH1 and/or MYH knockdown cells. NEIL1 DNA glycosylase, involved in repair of oxidized nucleosides, was found to be significantly downregulated as a cellular response to MTH1–MYH co-suppression. Overall, the results suggest that hMYH and hMTH1 functionally cooperate for effective repair and survival in mismatch repair defective T-ALL Jurkat A3 cells.

INTRODUCTION
Genomic DNA is under constant attack by reactive oxygen species that occur naturally as by-products of aerobic metabolism. Increased production of reactive oxygen species is widely considered to be a consequence of malignant transformation in many cancer types, 1,2 and thus efficient repair of oxidized DNA lesions is considered critical for cancer cell survival. 3,4 Perhaps the most abundant and extensively studied oxidized DNA lesion is 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG). 5 Three major DNA repair pathways are thought to be responsible for preventing the accumulation of oxidized lesions in genomic DNA (Supplementary Figure S1). Oxidation can occur in the deoxyribonucleotide (dNTP) pool where the MutT homolog-1 (hMTH1) enzyme, encoded by the NUDT1/MTH1 gene, hydrolyses 8-oxodGTP and other oxidized dNTPs into the monophosphate form. 6 hMTH1 thus sanitizes the dNTP pool to avoid misincorporation of 8-oxodGTP into DNA during replication. 7,8 When 8-oxodG is already present in the DNA strand, replicative polymerases could incorporate either deoxycytidine triphosphate (dCTP) or deoxyadenosine triphosphate (dATP) opposite the lesion in the next round of replication, where 8-oxodG is in anti or syn conformation, respectively. 9,10 The 8-oxodG:C pairs are thought to be mainly detected and further processed by 8-oxoguanine DNA glycosylase (OGG1) that performs the first step of base excision repair (BER), removing the oxidized guanine paired with cytosine. 11 The 8-oxodG:A mispairs are recognized by another DNA glycosylase called MutY homolog (hMYH, encoded by MYH gene) that excises the mis-incorporated dA in the nascent DNA strand. This provides the BER polymerases with an opportunity to correctly insert dCTP opposite 8-oxodG and thus create a substrate for OGG1. 12,13 On the other hand, the activity of hMYH on 8-oxodG:A where dA is in the template strand can potentially lead to T:A 4 4G:C mutations, and in this case, it has been hypothesized that the mismatch repair (MMR) pathway could contribute to the removal of the 8-oxodG in the nascent strand. [14][15][16] In order to investigate the interplay between hMTH1-and hMYH-dependent BER, we utilized MMR defective T-cell acute lymphoblastic leukemia (T-ALL) cells. 17 Malfunctioned MMR and the consequent microsatellite instability are highly frequent in T-ALL and thus simplify our study model. [18][19][20][21] In addition, RNA-sequencing analysis of over 900 human cancer cell lines revealed that T-ALL cells have the highest expression for both MTH1 and MYH, making them an ideal model for this study 22 (Supplementary Figure S2). To achieve simultaneous silencing of both genes, small hairpin RNA (shRNA) sequences from The RNA Consortium (TRC) library were cloned into doxycycline (Dox)-inducible vectors containing different fluorescent reports (green fluorescent protein (GFP) or RFP670), followed by lentiviral transduction of Jurkat A3 cells. Next, the top 15% double positive cells were sorted using fluorescence-activated cell sorting (FACS). The cells were cultured in the presence of Dox and samples were harvested after 96 h for downstream assays.
Here, we observed higher cell death following MTH1 and MYH double knockdown (KD) compared with individual KD. Expression profiling of human DNA glycosylases revealed their responses to the lack of hMTH1 and hMYH enzymes. Taken together, our results indicated that hMTH1 and hMYH functionally cooperate for cell survival in T-ALL Jurkat A3 cells.

Efficient individual and simultaneous KD of MYH and MTH1
To study the potential functional interactions between hMYH and hMTH1, two different shRNA sequences for each gene were cloned into separate inducible vectors containing either GFP or RFP670 fluorescent reporters. T-ALL Jurkat A3 cells were then co-transduced with lentiviral particles to establish stable cell lines concurrently expressing two different hairpins. Puromycin selected cells were subsequently sorted for the highest expression of both reporters ( Figure 1a) and KD efficiency of each hairpin was analyzed using quantitative reverse transcriptase-PCR (qRT-PCR) (Figures 1b and c). Under these conditions, both MYH shRNAs were able to significantly suppress the expression of their target gene when co-expressed with a not-targeting hairpin. Similarly, MTH1 was also significantly down regulated by its respective shRNAs. Furthermore, simultaneous silencing of both genes was successfully achieved when MTH1 and MYH hairpins were used in combination. Interestingly, following 96 h of KD, MTH1-shRNA1 showed a suppressive effect on MYH expression (Figure 1b). In contrast, MTH1-shRNA2 resulted in a slight increase in MYH mRNA level (Figure 1c). We next validated hairpin activities at protein level using western blot analysis (Figures 1d and e), and obtained results comparable to the gene expression data. At both time-points, hMYH protein level was considerably reduced in cells expressing MYH-shRNAs separately or in combination with MTH1-shRNAs. Similar to qRT-PCR results, the hMTH1 protein KD was more efficient compared with hMYH, regardless of whether its corresponding shRNAs were used individually or co-expressed with MYH hairpins. Interestingly, in the cells containing single MTH1-shRNA2, a dramatically increased hMYH level was observed ( Figure 1e). Possibly because of this effect, hMYH depletion level after 96 h was not statistically significant when the MYH hairpin was combined with MTH1-shRNA2. Thus, hMYH protein KD 96 h post treatment was more efficient when MYH-shRNA2 was used separately rather than in combination with MTH1-shRNA2. Collectively, these results demonstrate highly efficient individual and combinatorial KD of the both genes.
hMYH and hMTH1 functionally collaborate to sustain cell survival in a T-ALL cell line We first investigated the effect of MTH1 and MYH double KD on survival of Jurkat A3 cells. On one hand, high DNA 8-oxodG caused by MTH1 KD could lead to more putative DNA strand breaks mediated by hMYH, causing cell death. Therefore, based on this hypothesis, hMYH depletion would rescue the toxicity induced by the lack of hMTH1. 23 On the other hand, hMYH hyperactivation could be a compensatory mechanism in the context of hMTH1 inhibition. Accordingly, a synergistic lethality would be expected as a consequence of combinatorial suppression of both enzymes. To test these hypotheses, we measured the percentage of sub-G1 cells upon Dox treatment in the cells with shRNA-set1 and shRNA-set2 at 96 h time-point. We observed concurrent KD of both proteins induced more cell death compared with individual depletions in both hairpin sets ( Figure 2). These observations support the hypothesis that hMYH function is required for cell survival when hMTH1 activity is suppressed.
To further understand how simultaneous KD of both genes influences survival in T-ALL cells, we studied induction of apoptosis using specific markers such as Annexin V and cleaved caspase 3 ( Figure 3). We observed that the percentage of Annexin V-positive cells was higher in combined KD shRNA set1 compared with single KD of either genes ( Figure 3a). Intriguingly, there was no significant difference in apoptosis level between the cells with combined KD and the ones expressing MTH1-shRNA2 (Figure 3b), and this could be owing to the increased hMYH level following MTH1-shRNA2 KD. As total cell death is also increased in the MTH1/MYH-shRNA2 KD, a more likely explanation is that the timing of apoptosis is such that the number of actively apoptotic cells at 96 h is lower. In addition, measurement of cleaved caspase 3 confirmed the results of Annexin V analysis (Figures 3c and d).
Taken together, these results support the hypothesis that hMYH is required for cell survival in the absence of hMTH1.
hMYH overexpression can rescue G1 arrest and cell death in MTH1 KD cells To further test our hypothesis that hMYH is required for cell survival in the absence of hMTH1, we speculated that hMYH overexpression could rescue the phenotypes observed following hMTH1 depletion. To test this, we transduced the individual MTH1-shRNA cell lines with a Dox-inducible construct overexpressing a nuclear isoform of hMYH (γ3) and performed cell cycle analysis following 96 h of treatment with Dox ( Figure 4). We observed that hMYH overexpression could remove the G1 block introduced by hMTH1 depletion. Furthermore, increased γ3-hMYH activity was shown to partially rescue the cell death mediated by MTH1 suppression. These data further support that hMYH levels dictate the cell survival to hMTH1 depletion, and suggest a protective role for hMYH.
NEIL1 expression was suppressed upon combined depletion of hMYH and hMTH1 MTH1 and MYH double KD, in a MMR-defective background, would presumably lead to high levels of oxidized DNA lesions. Here we wanted to investigate potential compensatory transcriptional response of the DNA glycosylase family to reduced levels of hMTH1 or hMYH protein levels. We speculated that MTH1 and MYH double KD would lead to increased genomic oxidized lesions, and this may lead to compensational changes in expression of BER enzymes. To investigate this we performed qRT-PCR following single or double KD, and measured the expression level of all known human DNA glycosylases. MTH1 and MYH double KD led to decreased NEIL1 expression level to ∼ 30% in both hairpin sets (Figures 5a and b). No considerable changes were observed in the expression of other DNA glycosylases ( Figure 5a). These results implicate NEIL1 in the cellular response to excess genomic oxidized lesions, caused here by MTH1 and MYH double KD.

DISCUSSION
It has been suggested that processing of mis-incorporated 8-oxodG opposite dA is mainly mediated by post-replicative MMR in mammalian cells. 13 In addition, hMYH activity has been shown to be required for removal of dA from the nascent strand when mispaired with 8-oxodG, 14 and there is also cumulative evidence suggesting hMYH has physical interactions as well as functional cooperation with MMR. 14,24 Using data base mining, we observed MYH and MTH1 expression levels are particularly high in T-ALL (Supplementary Figure S2). It has been reported that primary cells obtained from adult T-ALL patients are MMR inactive. 21,25,26 Hence, this may reflect that hMYH and hMTH1 proteins are particularly important in the absence of MMR. Moreover, the majority of established T-ALL cell lines appeared to contain defects in MMR. 20,27 Therefore, we used MMR-defective T-ALL Jurkat A3 cells to study the interplay between hMYH and hMTH1. Supporting the involvement of MMR, hMTH1 overexpression has been reported to significantly decrease spontaneous mutation rate in MMR-defective cells, indicating an oxidized dNTP pool critically contributes to their genomic instability. 28 Using two separate inducible vectors, we succeeded in knocking down MTH1 and MYH separately or simultaneously (Figures 1b and c). showed a downregulation at 96 h that was also reported earlier. 8 The upregulation of hMYH protein level in MTH1-shRNA2expressing cells was confirmed using western blotting (Figure 1e). The varying response may be a reflection of the intricate relationship likely existing between the hMTH1 and hMYH proteins. We found that simultaneous MTH1 and MYH suppression increased the sub-G1 population significantly using both shRNA sets, showing that the two proteins collaborate for survival in T-ALL Jurkat A3 line. Interestingly, ongoing apoptosis, measured by Annexin V and cleaved caspase 3, at the 96 h time-point was different between the two treatments (Figure 3), likely a reflection of the different degrees of knockdown and timing of cell death between the conditions used. However, the specific role of hMYH in promoting survival was established by overexpression of the γ3-hMYH into MTH1-shRNA-containing cells that decreased overall cell death (Figure 4). These results support the hypothesis that hMYH and hMTH1 cooperate to avoid the accumulation of genomic DNA damage and consequent cell death.
To understand how MYH and/ or MTH1 suppression can modulate the DNA repair pathways we analyzed the expression levels of human DNA glycosylases after 96 h of Dox treatment. Interestingly, we found that NEIL1 expression was significantly reduced when both enzymes were depleted ( Figure 5). Hydantoin lesions arising from oxidation of 8-oxodG are known substrates for NEIL1. 29 In addition, NEIL1 exhibited pre-replicative repair of oxidized lesions preventing the progression of the nascent strands containing NEIL1 substrates. Accordingly, hyperactivation of NEIL1 has been reported to cause replication fork stalling. 30 Based on this, we speculate that cells, with potential increased 8-oxodG levels caused by hMTH1 or hMYH loss, may suppress NEIL1 expression to avoid incised hydantoin lesions (converted to DNA single-strand breaks) to cause replication fork collapse and DNA double-strand breaks. A speculative hypothesis, still to be tested, could be that the hydantoin lesion is less toxic and 'better' for survival than conversion to potentially toxic BER intermediates.
In conclusion, this study provides evidence for the functional collaboration between hMYH and hMTH1 to maintain survival in cancer cells with MMR defective backgrounds, in particular T-ALL Jurkat A3 cells.

Molecular cloning and DNA constructs
The shRNA plasmids were generated by cloning oligonucleotide from TRC library (Supplementary Table S1 (c, d). The γ3-hMYH overexpression was validated after 96 h of Dox treatment by western blotting. One representative membrane is displayed in e. The results are presented as mean ± s.e.m. from at least two independent experiments in duplicate. P-values were calculated using one-way analysis of variance (ANOVA). *P o0.05, **P o0.01, NS, not significant.

Western blotting analysis
Cells were washed once with cold phosphate-buffered saline (PBS) and then resuspended in a lysis buffer (50 mM Tris-Cl, pH 7.5, 150 mM NaCl,

Flow cytometry
For DNA content measurement, cells were washed with PBS and fixated in cold 70% ethanol overnight. After resuspension of cell pellets in PBS with 1% bovine serum albumin, samples were incubated in DNA staining solution (10 μg/ml DAPI (D9542; Sigma), 0.1 mg/ml RNase A (EN0531; Thermo Fisher) and 1% bovine serum albumin in PBS) for 20 min at room temperature, followed by flow cytometry analysis on a Navios Flow Cytometer (Beckman Coulter, Brea, CA, USA). Data were analyzed using Kaluza Flow Analysis Software (Beckman Coulter). For apoptosis detection, cells were washed with PBS and resuspended in Annexin V Binding Buffer (556454; BD Biosciences) containing 1:100 diluted Annexin V, Alexa Fluor 555 conjugate (A35108; Thermo Fisher) and 10 μg/ml DAPI (D9542; Sigma), incubated for 20 min at room temperature in the dark before flow cytometry analysis. The flow cytometry experiments were performed independently at least three times in technical duplicate.

Statistical analysis
Multiple comparison between groups was performed by analysis of variance test using Prism 6 (GraphPad Software, La Jolla, CA, USA). Data are presented as mean ± s.e.m. and differences with values of Po 0.05 were considered to be statistically significant.


extfieldsofstudy:
Biology
Computer Science
Medicine

text:
The human-induced pluripotent stem cell initiative—data resources for cellular genetics

The Human Induced Pluripotent Stem Cell Initiative (HipSci) isf establishing a large catalogue of human iPSC lines, arguably the most well characterized collection to date. The HipSci portal enables researchers to choose the right cell line for their experiment, and makes HipSci's rich catalogue of assay data easy to discover and reuse. Each cell line has genomic, transcriptomic, proteomic and cellular phenotyping data. Data are deposited in the appropriate EMBL-EBI archives, including the European Nucleotide Archive (ENA), European Genome-phenome Archive (EGA), ArrayExpress and PRoteomics IDEntifications (PRIDE) databases. The project will make 500 cell lines from healthy individuals, and from 150 patients with rare genetic diseases; these will be available through the European Collection of Authenticated Cell Cultures (ECACC). As of August 2016, 238 cell lines are available for purchase. Project data is presented through the HipSci data portal (http://www.hipsci.org/lines) and is downloadable from the associated FTP site (ftp://ftp.hipsci.ebi.ac.uk/vol1/ftp). The data portal presents a summary matrix of the HipSci cell lines, showing available data types. Each line has its own page containing descriptive metadata, quality information, and links to archived assay data. Analysis results are also available in a Track Hub, allowing visualization in the context of public genomic annotations (http://www.hipsci.org/data/trackhubs).

INTRODUCTION
The Human Induced Pluripotent Stem Cell Initiative (Hip-Sci) was established in 2012 to address the community requirement for a large, well-characterized collection of human-induced pluripotent stem cells (iPSCs) for use in research. Human iPSCs are an invaluable system for mod-elling human disease (1), and are a useful tool for conducting research into the function of genetic variants both associated with complex disease and also normal human phenotypic variation. Previous research has suggested that interline variability may be high (2,3), making the subtle effects of common genetic variants difficult to detect. There have been previous large-scale efforts to generate and characterize pluripotent stem cells (4) (https://www.cirm.ca.gov/ researchers/ipsc-initiative), but these other projects have either not systematically derived human iPSCs at the scale of HipSci or have not focused on characterizing the phenotypes related to natural genetic variation (5). The HipSci project fulfils a pressing need within the community to provide a large, well-characterized collection of human iPSCs that are systematically generated using a single experimental pipeline.
As of August 2016, the HipSci project has created 477 cell lines from healthy donors, and 86 lines from donors with a rare genetic disease. All of these lines have been characterized with a diverse range of assay data including exome-seq, RNA-seq, 450K methylation arrays and proteomic assays. The cell line catalogue, together with the extensive characterization data, provides the scientific community with a great opportunity to investigate cellular function and the impact that common genetic variation has on this function. Here we present the data access and presentation services that the HipSci project provides, which enable the community to both discover and to reuse the cell lines and data that the project has generated.

Assay data and archival strategy
The HipSci project's strategy is to derive two or three candidate iPSC cell lines from each donor, and to generate an initial set of genetic and phenotyping assays on all candidate lines ( Figure 1). This initial set of data includes array-based genotyping and gene expression profiling on the iPSCs and on their progenitor cells, which are either fibroblasts or erythroblasts. The most appropriate cell line is selected for expansion, banking and further profiling using RNA-seq, exome-seq, DNA methylation profiling, proteomics in the Figure 1. HipSci data flow. Sample metadata is collected from healthy donors and donors with rare genetic disease who each provide a skin biopsy. Sample metadata is also collected on the Fibroblasts and iPSC cell lines derived from these biopsies. This sample metadata is registered immediately upon creation and before any assays are performed in EMBL-EBI's BioSamples database. For each cell line a range of data is generated including quality control and genomics assays conducted by the Wellcome Trust Sanger Institute, proteomics assays by the University of Dundee, and cellular phenotyping by Kings College London. The quality control, genomics, and proteomics data is deposited in the relevant EMBL-EBI archive, and the cellular phenotyping data is released to the HipSci public FTP site. Table 1 lists the specific archive that assay data is submitted to and shows the distinction in destination between open and managed access data. Our web portal infrastructure is based upon an Elasticsearch engine to which the sample and assay data is loaded. The public json API uses standard Elasticsearch query syntax and through an intermediary web server allows any appropriate search query to be passed through to the search engine. The web portal app displays data fed from the public API creating searchable and filterable views of all of HipSci's rich data.
form of mass spectrometry and high content cellular phenotyping (6).
The HipSci project follows a rapid pre-publication data release strategy, through submission to EMBL-EBI data archives and, in the case of preliminary data and files not appropriate for an official archive, through release via the project FTP site. EMBL-EBI's BioSamples (7) database is used to register sample metadata for all tissue donors, tissue samples, and iPSC lines generated by the project. The samples are registered immediately upon creation and before any assays are performed. The project follows this registration strategy so that all assay data produced for every iPSC line is linked to a single stable cell line identifier. The use of BioSamples ensures that these lines are well described as it supports ontology annotation, which allows the project to unambiguously annotate attributes such as disease and cell type. BioSamples also supports rich relationships between samples, which allows us to track the connection between cell lines and the tissue sample and donor from which they were derived. When assay data is submitted to other EMBL-EBI archives, the BioSamples accession is used to link to the appropriate sample record, ensuring that all archived cell line data is discoverable using this single identifier. Table 1 lists the assay data that are generated for each HipSci cell line. The assay data is submitted to the appropriate EMBL-EBI assay archive, which ensures that data is stored using well-established infrastructure, is distributed to users efficiently, and can be easily found in the most commonly used data repositories. Our data portal (http: //www.hipsci.org/lines/#/lines) links to the assay datasets in each archive, removing the need for replicating files between the HipSci resource and the individual archives.
The HipSci tissue samples were collected under different participant consents. This mixed-consent mode was both a consequence of timing and the health status of the individuals participating. Both the 'healthy' samples that were collected early in the project, and all of the rare disease samples, were collected using managed-access consent. In order to facilitate broad re-use, the consent policy for the healthy samples was updated to allow for a more open mode of data release.
The types of consent affect our strategy for archiving and distributing the data. For example, data from openly consented healthy samples that is uniquely associated with the sample donor, such as genotype or genomic sequence data, can be made freely available to all users through the European Nucleotide Archive (ENA) (8) and ArrayExpress (9). In order to meet the conditions of the managed-access consent signed by other donors, the equivalent data types are submitted to the European Genome Phenome Archive (EGA) (10), where the data is only accessible to bona fide researchers who have been granted permission to access the data by the HipSci Data Access Committee (http://www.sanger.ac.uk/about/who-weare/policies/open-access-science). Proteomics and cellular phenotyping data are not uniquely linkable to the sample donor, so for all cell lines these data are distributed openly without managedaccess restrictions. Proteomics mass spectrometry data is deposited in the PRoteomics IDEntifications (PRIDE) database (11). HipSci's high content cellular phenotyping data is a relatively new data type, for which there is no wellestablished public archive. We therefore distribute these data via our project FTP site (ftp://ftp.hipsci.ebi.ac.uk/vol1/ ftp). We are working with the archives hosted at EMBL-EBI to establish the best location for this data.

Data access
The HipSci cell lines and data can be explored and downloaded through several different mechanisms.

Website
The HipSci website (http://www.hipsci.org) provides summary information about the HipSci project. Information includes assay descriptions, our data reuse policy and announcements about the project. The website also acts as the entry point to our data portal. The content is designed to provide users with context about the project, the data we hold, and to help them find and use our data. All news announcements are also made on our twitter feed (@hipsci).

Cell lines and data browser
The browser presented in HipSci's dedicated web portal is designed for users to browse cell lines and their related data (http://www.hipsci.org/lines) (Figure 2). Our primary user group is biologists who want to select cell lines meeting certain criteria, such as donor disease, age, iPSC derivation method. This user group will ultimately want to either purchase the lines through ECACC, or download the associated assay data for use in their own experiments.
EMBL-EBI is currently working on projects to unify both archival submission and display; in the meantime, there is no central solution to provide the community with a coherent view of all the HipSci project data and cell lines. The HipSci data portal serves this need, by providing the iPSC community with a unified view of the HipSci collection, enabling them to discover cell lines they want to purchase and by giving them a consolidated view of all the data associated with a particular cell line. The portal also hosts data that does not have a current home in any of EMBL-EBI's archives, such as the cellular phenotyping and cell line QC data. The portal points users to the archive location for all other data types.
The cell line and data browser is the primary point of access for users wishing to query the cell lines and assay data that HipSci has produced. As of August 2016, there are 2668 cell lines and 7589 individually archived assay results displayed in the data browser.
There are three main entry points into the data from the browser's navigation bar: 'search cell lines', 'donors' or 'files' (Figure 2). Each of these entry points shows a table with high-level information about the cell line, sample donor or archived file, respectively. Users can customize their view by adding specific columns to the table display, by sorting the row order by clicking on the columns, or by exporting the table as a text file that can be loaded into a spreadsheet. A search box allows users to restrict the table to lines that match particular criteria, for example, cell line name 'HPSI0114i-eipl 1 , or assay type, for example 'proteomics' or 'RNA-seq', or disease state, for example 'Bardet-Biedl'. A list of filters allows the user to refine their search for cell lines or assay files that meet their criteria, such as disease, banking availability, and available assay data. The search box and filters reduce the table contents to lines that match the user's selection. The cell line table has columns for each of the assay types, with clickable dots, which take the user to more information about the available assay data (Figure 2).
The browser also has a cell line detail view, which displays comprehensive information about a single chosen cell line, for example http://www.hipsci.org/lines/#/lines/HPSI0114ieipl 1. This detail can be reached by clicking on the cell line name in the cell line table. Each cell line page presents disease and demographic information about the sample donor; the clinic who provided the tissue; the method of iPSC derivation; characterization of the line; archived assay data for that cell line; and a link to ECACC in order to purchase a line, if it has been released to the bank.
The cell line characterization section includes results of the pluritest assay (12) and an analysis of copy number variations from genotyping array data (13). This section provides the user with a view of the summary statistics the project used to select which lines should be expanded, banked, and distributed. The cell line detail view contains a link to the certificate of analysis that a customer will receive when purchasing a cell line. These documents demonstrate to a recipient that the batch has passed all the HipSci project QC tests. It lists the tests that the cell line has passed to ensure sterility, viability, pluripotency, identity, morphology and clearance of reprogramming factors.

Application programming interface (API)
The data presented in the HipSci browser is pulled into the website using a RESTful Application Programming Interface (API). This API is publicly accessible and allows searching, filtering, and sorting of cell lines, of sample donors, and of archived data files. Programmatic users access the same information as a user of the web interface. This API is used by ECACC to acquire and update cell line data on commercially available lines.
The API (Figure 1) is powered by Elasticsearch, a popular search engine with extensive online documentation describing many different types of search query over http using a JSON syntax. A web server sits between the user and the search engine, to protect the search engine from inappropriate actions (such as deleting a record), but for all other cases a user's search request is forwarded directly to the Elasticsearch infrastructure. This allows users to compose many complex queries with no restrictions; for example, to search for cell lines matching a query string 'diabetes', whilst filtering for lines from female donors in the age range 35-39. The HipSci website has documentation describing use of the API (http://www.hipsci.org/lines/#/api).

FTP site
The HipSci project is committed to early data access, and our rapid archiving strategy ensures that data are available for download by FTP directly from the relevant EMBL-EBI archive. HipSci also has its own FTP site (ftp://ftp.hipsci. ebi.ac.uk/vol1/ftp) to facilitate the download of preliminary data and of new data types, such as high content cellular phenotyping, for which there is no well-established assay archive (ftp://ftp.hipsci.ebi.ac.uk/vol1/ftp/data/). In providing the raw data via FTP we ensure that all users can access specific data types and support those who wish to use data from many different cell lines and assay types at once.
The HipSci FTP site provides index files that list all of the assay data available from EMBL-EBI archives (ftp: //ftp.hipsci.ebi.ac.uk/vol1/ftp/archive datasets/). These tabdelimited index files enable users to locate all the data quickly and to understand the relationship of all data files to their respective cell line. These index files also make it much easier for users to download in bulk all of the HipSci project data.

Browsing the HipSci analysis results
Visualizing the analysis results associated with the HipSci lines alongside a broader range of genomic annotation allows our users to put the HipSci results in genomic context alongside information such as the GENCODE annotation (14), Ensembl regulatory annotation (15) or genomic sequence variants from projects such as the 1000 Genomes Project (16) or COSMIC (17). We enable this contextual visualization by using Track Hub technology (18); these hubs allow users to attach analysis files to either the UCSC (19) or Ensembl (20) genome browsers with a single URL, and to explore the HipSci results. The hub files themselves are text files which contain pointers to the publicly mounted location of the results files and to the associated metadata such as the cell line name, disease state and analysis type. By default, results from only a few lines will be displayed when the hub is first attached to the browser. Both UCSC and Ensembl have powerful configuration menus that allow users to change the currently viewed selection of cell lines and analysis file tracks within the hub. Our hub is registered in the Track Hub registry (http://trackhubregistry.org/) to enable broad discovery and reuse. The hub itself is hosted from our FTP site (ftp://ftp.hipsci.ebi.ac.uk/vol1/ftp/track hub/ hipsci hub/) and we provide users with direct links to the UCSC and Ensembl genome browsers along with instructions for use from our website. The trackhub published in August 2016 only contains exome sequencing alignment data. As more analysis results are released by the consortium, in a trackhub suitable format, they will be added to the hub.

Data reuse
The HipSci project data is released early, prior to publication, in the expectation that it will be valuable for many researchers. In keeping with Fort Lauderdale principles, the public community of users may utilise the data for their own research, but are expected to allow the HipSci consortium to make the first presentations and to publish the first papers with global analyses of the data. After the HipSci consortium has published analyses, then researchers outside the project are free to present and publish using the project data for their analyses.
Prior to the first major HipSci paper, other researchers may still present methods development posters that include small amounts of HipSci data, provided the quantity of HipSci data is sufficiently small, and the project is properly acknowledged. A more thorough description of these data use conditions is available on the website (http://www. hipsci.org/data/policy).

Future
Moving forward we will continue to gather together all of the data generated by the HipSci project, and to enable the research community to discover data of interest to them. The depth of genomic sequence variation data available for these cell lines means that the data sets can be challenging to search because of the volume of samples and genomic variant sites which need to be queried: currently, the only solution to this requires a user to download all of the VCF files we present and to query across all of them. We are working with the European Variation Archive (EVA) to take advantage of their 'variant search' API (http://www.ebi.ac.uk/eva/ ?API), and once the openly consented HipSci genotype data is loaded into the EVA variation database, we will build the relevant search tools into the HipSci data portal. This will allow users to query across all the openly consented HipSci sample genomic variants and genotypes, allowing users to issue queries such as 'which HipSci cell line is homozygous for allele X at genome position Y?' iPSCs provide a compelling model for human biology because it is possible to differentiate them into many types of human cells. HipSci is now generating assay data on differentiated cells, such as macrophages and sensory neurons. These data will be integrated into the HipSci data portal, and we will work to build tools that allow users to intuitively search across sample, cell, and tissue type. The HipSci project has produced a valuable catalogue of cell lines. This article presents the current tools, which can be used to explore and visualize the HipSci data. As the project moves forward, we expect to continue extending and expanding these tools to ensure that the HipSci data remains useful to the community.

Contact details
General questions about the HipSci project and its resources should be addressed to hipsci@ebi.ac.uk. Specific questions about purchasing HipSci cell lines should be sent to ECACC using culturecollections.technical@phe.gov.uk. The source code supporting our data portal and website can be found on Github https://github.com/hipsci/hipsci. github.io. You can also follow us on twitter @hipsci.