Interestingly, the electrochemical performance and BOD removal rates were very reproducible throughout MFC operation regardless of the sample variability associated with each wastewater exchange. While MFC performance was very reproducible, the phylogenetic analyses of anode-associated electricity-generating biofilms showed that the microbial populations temporally fluctuated and maintained a high biodiversity throughout the year-long experiment. These results suggest that MFC communities are both self-selecting and self-optimizing, thereby able to develop and maintain functional stability regardless of fluctuations in carbon source(s) and regular introduction of microbial competitors. These results contribute significantly toward the practical application of MFC systems for long-term wastewater treatment as well as demonstrating MFC technology as a useful device to enrich for functionally stable microbial populations.Microbial fuel cells (MFCs) are devices that exploit microorganisms as biocatalysts to recover energy from organic matter in the form of electricity. One of the goals of MFC research is to develop the technology for cost-effective wastewater treatment. However, before practical MFC applications are implemented it is important to gain fundamental knowledge about long-term system performance, reproducibility, and the formation and maintenance of functionally-stable microbial communities. Here we report findings from a MFC operated for over 300 days using only primary clarifier effluent collected from a municipal wastewater treatment plant as the microbial resource and substrate. The system was operated in a repeat-batch mode, where the reactor solution was replaced once every two weeks with new primary effluent that consisted of different microbial and chemical compositions with every batch exchange. The turbidity of the primary clarifier effluent solution notably decreased, and 97% of biological oxygen demand (BOD) was removed after an 8–13 day residence time for each batch cycle. On average, the limiting current density was 1000 mA/m Presently, wastewater treatment is an energy intensive and expensive process. In the USA over 126 billion liters of domestic wastewater are treated daily at an annual cost of over $25 billion Here we address the use of microbial fuel cells (MFCs) for the degradation of carbon sources in primary clarifier effluents from a conventional wastewater treatment plant. MFC treatment may be utilized to replace or supplement conventional secondary treatment systems and minimize the overall costs associated with aeration, secondary clarification, and secondary sludge treatment. MFC technology exploits biological fermentation and respiratory mechanisms to directly recover energy as electricity during the degradation of organic matter contained in wastewater and/or sludge A MFC reactor physically separates the oxidation and reduction reactions Most of the reported evaluations of MFCs have utilized a single carbon source , or homogenous effluents, such as synthetic wastewater or industrial wastewater (e.g. brewery waste) to explore the degradation of organic matter and energy recovery as electricity Sustained microbial catalytic activity and metabolic function are the most important factors to consider for long-term wastewater treatment using MFCs. Effective utilization of biological resources for flexible self-organization and self-regulation is needed to treat heterogeneous mixtures of organic and inorganic substrates contained in municipal wastewater. In particular, the microbial community in a MFC must play two critical roles: 1) rapid and complete degradation of various organic compounds through microbial metabolism; and 2) efficient recovery of energy through microbial energy transduction via extracellular electron transport to the anode. Controlling and optimizing these two biological roles is critical to enhance and stabilize MFC performance. To these ends, it is necessary to elucidate microbial function(s) from the enzyme level to the microbial community level.Here we present the first year-long evaluation of microbial diversity and functionality in a MFC that used municipal primary clarifier effluent as the sole substrate and inoculum source. Microbial functional stability was evaluated by quantifying organic matter degradation and electricity production. Analyses of microbial population dynamics associated with refined statistics were concurrently performed so that we are able to present the first data set that contributes to understanding the population dynamics of a given electricity-generating microbial consortium during long-term MFC operation. Finally, through combined system performance and phylogenetic analyses, we are able to better understand how variable carbon sources and competing microbial communities affect the performance and biodiversity of MFC anode-associated microbial communities.A single-chamber, air-cathode MFC During the long-term MFC operation, current generation was also impacted by biofilm formation on the cathode surface. After three months of operation, a dense biofilm was visibly apparent at the cathode surface and led to a reduction of current generation due to an overall increase in internal resistance . To restThe purpose of repeat-batch cycling was to observe the reproducible organic matter degradation as measured by a decrease in turbidity, removal of chemical oxygen demand (COD), biological oxygen demand (BOD), and inorganic compounds. Although turbidity of the original sample was high, the anolyte solution was almost completely clear after the 8–13 day residence time . OrganicOther components of the primary clarifier effluent sample and treated MFC anolyte are compared in High pressure liquid chromatography (HPLC) analysis of the raw primary clarifier effluent and treated MFC anolytes revealed that various organic chemicals were nearly completely degraded in the MFC process . While t2 , while the maximum power output per reactor volume was 0.3 W/m3. The limiting current density was 84 mA/m2 with 10 Ω of external resistance , indicating that electricity generating microorganisms were further optimized during the repeat-batch operation. However, the limiting current density did not increase again after another 100 days of operation (measured on day 264), suggesting that electricity generating performance had stabilized between day 141 and day 264. This current density of 1,000 mA/m2 represents the limiting anodic biocatalytic activity and may be a function of low ionic conductivity in the anolyte (1.7 mS/cm), increasing the ohmic losses in the system; and/or low substrate concentration at the biofilm surface (the COD was 260 mg/L) as a result of diffusion limitations.In order to better analyze the microbial current generating properties, the anode polarization curves were determined by linear sweep voltammetry (LSV) . Using aEach repeat-batch cycle began with new and different suspensions of chemical compounds and microbes. The anode polarization curves were also measured during the representative single batch-feed from day 139 to day 152 . The pol7 cells/ml at day 139 to 1.2×107 cells/ml at day 152, suggesting that planktonic microbial cells were not contributing to organic matter degradation or electricity generation in the MFC. This is also visibly evident in the turbidity changes shown in 2 on day 152. In order to analyze normalized biocatalytic activity of the anode biofilm, the per-biomass electron-donating rate was calculated to be 52.4 µmol-electron g-protein−1 min−1.The relationship between each new microbial cell suspension and the observed patterns of electricity production and organic matter degradation was also examined. The suspended cell concentrations decreased during the residence time associated with each batch cycle. During a representative cycle, it was found that the suspended cell counts decreased from 7.5×10These data, when taken together, suggest that microbial growth primarily occurred at the electrode surfaces and that the anode consortium was primarily responsible for organic matter degradation and current production in the MFC.To analyze the microbial community composition dynamics of the anode biofilm, we constructed 16 S rRNA gene clone libraries of anode biofilm samples collected at day 44 (W1), day 133 (W2), day 263 (W3), and day 294 (W4). Clone libraries prepared from raw primary clarifier effluent samples collected at day 14 (PC1), day 152 (PC2), and day 304 (PC4) were also analyzed because these samples served as carbon and inoculum sources for each repeat-batch cycle.The rarefaction-curve analysis for the MFC anode and primary clarifier samples showed that the anode biofilm community at any given time was more diverse than the communities of primary clarifier effluents . This reBacteria. The relatively high abundant phyla in the 16 S rRNA clone libraries of both the anode biofilm and primary clarifier effluents were Proteobacteria, Firmicutes, and Bacteroidetes. Those phylotypes are considered as relatively abundant species in the microbial communities. Of the Proteobacteria, members of the class Deltaproteobacteria were abundant in the anode biofilm samples and significantly increased in abundance throughout the long-term MFC operation. In contrast, those of the Betaproteobacteria, Gammaproteobacteria, and Epsilonproteobacteria decreased in abundance within the anode biofilm samples even though these members were abundant in every characterized primary clarifier effluent sample. These results indicate that deltaproteobacterial species are important for electricity generation in the anode biofilm. Furthermore, the frequency of the phylum Bacteroidetes in the anode biofilm was slightly higher than that of primary clarifier effluents, suggesting that Bacteroidetes could also be important for efficient biofilm function.Results from the seven different 16 S rRNA clone library analyses are shown in In order to further compare the microbial communities, a multidimensional scale plot (MDS) was created based on genus level taxonomy . The ploIn the early phases of MFC operation (W1 and W2), the anodic microbial communities had slight similarities to the microbial communities of the primary clarifier effluents. These results suggest that some of the initial bacteria introduced to the MFC reactor attached and then established the electricity-generating microbial community in the anode biofilm. Furthermore, the data indicate that the established biofilm was not susceptible to invasion by new microbial populations introduced with the primary clarifier repeat-batch anolyte replacements.Deltaproteobacteria are potentially important bacteria for extracellular electron transfer in the anode biofilm, however, the dominant phylotypes within this class changed over time. During the early stage of MFC operation  the Deltaproteobacteria were primarily comprised of a phylotype W1_B02, which is closely related to Geobacter sp. Ply1. However, during the following stage  the dominant phylotype was W2_M05, which is more related to Geobacter lovleyi SZ. Over 200 days of operation, the matured biofilm samples represented in W3 (day 263) and W4 (day 294) clone libraries showed that the dominate phylotypes at the early stages had diminished, and another five abundant phylotypes were apparent in the class Deltaproteobacteria. The phylotype W2_A03, which appeared first in the W2 clone library, subsequently became dominant as the biofilm continued to mature, was found to be closely related to Desulfuromonas acetexigens.As mentioned above, Arcobacter cryaerophilus, was highly abundant in only the early stages of anode microbial community development  based on 16 S rRNA gene fragments. However, the microbial community was only analyzed as a function of different anode surfaces within the system and not as a function of time, wastewater inoculum sources, or MFC performance Several reports have recently appeared in the literature exploring MFC performance during treatment of primary clarifier effluents Three distinct microbial communities existed in the MFC system: anode biofilm (anaerobic metabolism), cathode biofilm (aerobic/facultative metabolism), and suspended (planktonic) cells (facultative metabolism) Although it is known that the air-cathode we used allows the diffusion of oxygen into the MFC system In a previously reported study using a cellulose-fed MFC, the diversity of the anode microbial community decreased with time while system performance remained stable Acidovorax sp. and Arcobacter spp., which were present in relatively high abundance in the primary clarifier effluent , four other observed . The mosDeltaproteobacteria class were syntrophically cooperating to produce electricity from the wide varieties of chemical compounds in the primary clarifier effluents. Interestingly, the dominant Deltaproteobacteria species changed with time, but the electricity generating performance and chemical oxidation rates remained stable. This phenomenon clearly suggests that the anode-associated microbial population can be functionally maintained for the treatment of primary clarifier effluents and sustain energy recovery in the process.The prevalence of different electricity generating phylotypes in our primary clarifier MFC implies that several species within the Deltaproteobacteria species were primarily responsible for direct electricity production; however the other highly abundant anode-associated phylotypes were closely related to the phylum Bacteroidetes and observed in all stages of anode biofilm enrichment. While the phylum Bacteroidetes has mainly been described as a fermentor in the human gut et al. recently demonstrated that Bacteroidetes was an abundant phylum correlated with electricity generation from artificial wastewater treatment in a continuous-flow cassette-electrode MFC Bacteroidetes strains including the clone CE38 abundantly observed in the cassette-electrode MFC. These results suggest that MFC enriched Bacteroidetes species may possess diverse functional traits and may thus represent an interesting phylum worthy of further study. To address the potential roles of these dominant phylotypes classified to Bacteroidetes within our MFC system, we will attempt to isolate these strains and analyze their genomic and functional characteristics in future work.We hypothesize that the phylotypes associated with Other less dominant phylotypes observed in the anode-associated biofilm were very diverse and functionally unknown . Some phIn summary, while MFC performance was very reproducible, the phylogenetic analyses of anode-associated electricity-generating biofilms demonstrated that the microbial populations fluctuated temporally while maintaining high biodiversity throughout the year-long experiment. These results suggest that MFC operation induces a self-optimizing process toward functional performance from diverse, heterogeneous microbial communities, and therefore can be used to reproducibly select for functional microbial communities regardless of carbon source. These results contribute significant knowledge toward the practical application of MFC systems for long-term wastewater treatment, while demonstrating the utility of MFCs for enrichment of functionally stable microbial populations capable of organic compound degradation and extracellular electron transfer.Additional impact of the reported results is provided by the ability to observe the metabolic activities and energy transduction within a complex consortium. This has significant benefits to the field of microbial ecology and may yield insight into numerous geochemical cycles that involve biological transformations of extracellular material, such as iron and manganese oxides. Future studies will apply metagenomics and metatranscriptomics to the anode biofilm to describe gene expression profiles associated with carbon metabolism and extracellular electron transfer during the degradation of complex organic substrates. Gene expression data will further elucidate metabolic networks and energy transduction in complex consortia.2 total projected surface area per reactor; TMIL, Japan) 2), Nafion, and PTFE as described elsewhere 2.A single-chamber, air-cathode MFC was used for municipal sewage wastewater treatment with power generation. The MFC was a bottle-type reactor (350 ml in capacity), with two joined anode electrodes made of carbon cloth  without any pretreatment except the mechanical removal of grit, rags and scum. The sole inoculum source consisted of those microorganisms present in the primary clarifier effluents. The MFC was gently mixed with a magnetic stirrer, and incubated at room temperature (22°C±3°C) throughout the duration of testing.The anode and cathode electrodes were connected with an external resistor of 750 Ω. Cell voltages across the resistor were recorded every 30 min using a voltage recorder  and the corresponding electric current was calculated using Ohm's law (V = IR). When the electric current decreased due to depletion of the organic matter in the wastewater, the anode solution was fully discarded and the reactor was refilled with either the fresh wastewater collected that day or with aged wastewater stored at 4°C. This repeat-batch process occurred twice monthly with fresh wastewater, and weekly with aged wastewater, for 300 days. Each wastewater sample introduced to the reactor included the naturally occurring microorganisms and various chemical compounds, no filtration or additional pretreatment was conducted. On days 88 and 195, the biofilm formed on the cathode surface was mechanically removed to recover the cathode performance.To obtain polarization and power density curves, an Ag/AgCl reference electrode  was placed in the side port of the MFC. The external resistance across the circuit was then changed stepwise from 3.3 kΩ to 10 Ω and the cell voltage, the anode potential, and the cathode potential were recorded after they had stabilized over a period of at least 7 min In order to obtain anode polarization curves without cathodic reaction limitation, linear sweep voltammetry analyses were conducted using a potentiostat  p/Cth×100, where Cp (C) is the total charge passed during a single batch, and Cth (C) is the theoretical amount of charge allowable from a complete COD decrease (assuming that reducing one mole of oxygen requires the transfer of four electrons). Biological oxygen demand (BOD), total suspended solid (TSS), turbidity, nitrate-N, nitrite-N, ammonium-N, sulfate, and heavy metal concentrations were determined in accordance with US EPA and state of California requirements by CRG Marine Laboratories, Inc . Conductivity of the solution was determined by portable pH/ORP/DO/ionic meter . Acetate and other volatile fatty acids were determined using a high-pressure liquid chromatography (HPLC) machine equipped with DI detector (Agilent 1200 series) and a packed C18 column . The eluant was 50 mM phosphoric acid (pH 1.87) at a flow rate of 1.0 ml/min.Chemical oxygen demand (COD) was determined using a potassium chromide assay according to the manufacturer's instructions . Coulombic efficiency, CE (%), was calculated as CE = CIn order to determine the total bacterial cell density on the anode surface, part of the anode (7 mm×7 mm) containing cells was removed from the MFC (n = 3). Total protein was extracted from the electrodes as described elsewhere A small portion of carbon cloth was collected from the anode, fixed with 1.25% gultaraldehyde, dehydrated using a graded series of ethanol solutions, and dried using a critical point drier  5′-AGAGTTTGATCCTGGCTCAG-3′) and U1492r (5′-GGTTACCTTGTTACGACTT-3′) Escherichia coli JM109 competent cells. PCR-amplified 16 S rRNA gene fragments were recovered by PCR using primers M13f and M13r (the primers targeted the pGEM-T vector sequences flanking the insertion), then sequenced by ABI 3730xl sequencers using primer U907r (5′-CCGYCAATTCMTTTRAGTTT-3′) Total DNA was extracted from the biofilm associated with the carbon cloth anode or from the suspended cells in the primary clarifier effluent. All DNA extractions were performed using the UltraClean® Soil DNA Isolation Kit (MO bio) according to manufacturer instructions, which employed physical cell disruption. PCR amplification of 16 S rRNA gene fragments was performed using Taq DNA polymerase  with universal primers U27f . A Shannon's index, Simpson diversity index, and Sorensen similarities among the bacterial communities were calculated using Estimate S Sequences of partial 16 S rRNA genes determined in this study were aligned to each other using CLC genomics work bench version 3.6.5 (CLC bio), and assigned to phylotypes . Database searches for related 16 S rRNA gene sequences were conducted using the BLAST program Figure S1Typical batch cycle of current generation and COD concentrations in the primary clarifier effluent-fed MFC. Thin black line, electric current (mA); Thick red line, accumulated electron production expressed as ‘mM equivalent (eq.)’ calculated as the number of total electrons passing across the circuit from the available COD in solution; solid square blue line, total COD (mg/L) in solution.(EPS)Click here for additional data file.Figure S2HPLC chromatographs of wastewater samples before and after MFC treatment. Organic compounds were detected at wavelengths of 210 nm  or 254 nm . The untreated primary clarifier effluent chromatographs indicate the presence of several different compounds , most of which were no longer present in the MFC treated samples .(EPS)Click here for additional data file.Figure S3FE-SEM images for anode biofilms adhering onto carbon cloth anodes (day 152). Bar in panel A is 100 µm, bar in panel B is 10 µm, and bars in panel C and D are 2 µm.(EPS)Click here for additional data file.Table S1All phylotypes obtained from the enriched electricity-generating consortia.(XLS)Click here for additional data file.Table S2All phylotypes obtained from the primary clarifier effluents.(XLS)Click here for additional data file.


Tooth wear in primates is caused by aging and ecological factors. However, comparative data that would allow us to delineate the contribution of each of these factors are lacking. Here, we contrast age-dependent molar tooth wear by scoring percent of dentine exposure (PDE) in two wild African primate populations from Gabonese forest and Kenyan savanna habitats. We found that forest-dwelling mandrills exhibited significantly higher PDE with age than savanna yellow baboons. Mandrills mainly feed on large tough food items, such as hard-shell fruits, and inhabit an ecosystem with a high presence of mineral quartz. By contrast, baboons consume large amounts of exogenous grit that adheres to underground storage organs but the proportion of quartz in the soils where baboons live is low. Our results support the hypothesis that not only age but also physical food properties and soil composition, particularly quartz richness, are factors that significantly impact tooth wear. We further propose that the accelerated dental wear in mandrills resulting in flatter molars with old age may represent an adaptation to process hard food items present in their environment. Phascolarctos cinereus), for example, high rates of tooth wear are associated with an increase in the time spent feeding Capreolus capreolus), individuals showing more hypsodont teeth that wear at a lower pace present a longer life expectancy Propithecus edwardsi), age-related enamel tissue removal decreases individual nutrient intake efficiency, negatively affecting survival and reproduction Chlorocebus aethiops) using controlled diet, animals which feed on more abrasive food items present greater average annual tooth wear Alouatta paliatta), individuals exhibit faster rates of molar wear during the dry season Papio hamadryas and P. cynocephalus) show variation in wear rates according to differences in dietary ecology, ground cover and seasonal food availability Alouatta palliata) Propithecus edwardsi) Gorilla beringei beringei) Tooth morphology and enamel microstructure are linked to the mechanical properties of ingested food There are three main factors that affect tooth wear. First, hard items, such as fruits or parts of the pericarp around the seeds, require high bite forces to be fractured resulting in enamel cracks of the cervical and occlusal surfaces of molar teeth Mandrillus sphinx) and the savanna-living yellow baboons  that show contrasting feeding behavior. Both species are semi-terrestrial and exhibit similar suites of cranio-dental features, including comparable enamel thickness In order to determine whether the environment and feeding ecology are related to tooth wear variability in primates, we examine here the relationship between tooth wear and age in two African papionins, the forest-dwelling mandrills . The research adhered to the legal requirements of Gabon and Kenya, and to the American Society of Primatologists principles for the ethical treatment of nonhuman primates.Mandrillus sphinx) inhabits the Lékédi Park, located 7 km northeast of the village of Bakoumba (Haut-Ogooué province) in Gabon http://www.cefe.cnrs.fr/mandrillus/presentation). The landscape is mainly primary and secondary Marantaceae forest, with patches of humid open savannas. The average annual rainfall is 1,474 mm with a long dry season that spans from June to September The study population of mandrills  study population inhabits a semi-arid, short-grass savanna ecosystem in the Amboseli basin (southern Kenya) at the northwestern base of Mt. Kilimanjaro. This population has been intensively studied for almost four decades http://amboselibaboons.nd.edu). Amboseli is one of the driest habitats of baboons. The average annual rainfall is very low (348 mm), with a seasonal pattern ranging from 150 to 500 mm. A long dry season occurs from June to October during which fruits and forbs are scarce. However, the baboons' diet shows relative stability across seasons. Underground Storage Organs (USOs), such as grass and sedge corms, fruits and blade bases, are the principal food resources for baboons and are consumed year round The yellow baboon  and baboons . In the mandrill population, animals were darted using blowpipes and briefly immobilized (∼30 sec) with a mix of two anaesthetics (400 mg ketamine for 500 mg of xylazine). Animals were then woken using atipamezole . In Amboseli baboons, we used similar methods but animals were anesthetized with Telazol Our sample includes mandibular and maxillary M1-M2 tooth casts of mandrills  were washed and brushed slightly and molded using Coltène Occlusal digital photographs were taken and analyzed using ImageJ Results from linear regressions between PDE and age were complemented with an overall multivariate analysis of variance (MANOVA) to detect changes with age for each molar tooth in both species and analysis of covariance (ANCOVA) to test for the homogeneity of slopes between species (mandrills vs. baboons), sex  and origin (wild vs. captive born) in the case of mandrills. Analyses were conducted using PAST n = 9) and the Lékédi Park (n = 7) locations, in the area where the primate populations live year round. The samples were pulverized and the mineral composition was determined using X Ray Diffraction analysis (XRD) , following the standard Powder Diffraction File of the ICDD-JCPDS . All the analyses were done at the XRD Unit of the Centres Científics i Tecnològics at the University of Barcelona. Statistical differences in mineral composition (t-test) were performed in PAST Regarding the sediment analyses, we collected soil samples in both Amboseli , although quadratic regressions were always more informative, following the Akaike information criterion (AIC)  in mandrills  and baboons . An overall MANOVA test  and baboons .Cross-sectional linear and quadratic regressions of PDE with age in mandrills and baboons for M1 and M2 teeth yielded highly significant positive relationships (on (AIC) . When loOVA test  revealedp = 0.053) (We performed slope comparisons to determine the differences in tooth wear with age in relation to sex (for similar results on baboons see ref. = 0.053) .p = 0.001) and M2 (p = 0.005), indicating a more rapid increase in PDE with age in mandrills compared to baboons (We found significant interspecific differences in the homogeneity of slopes for both M1 ( baboons . For exap<0.0001).Finally, sediment analyses showed different mineral compositions according to the location of origin. Sediments from Amboseli showed a mineral composition mostly composed of calcite, dolomite and ankerite, sepiolite clays, feldspartz, quartz and also an amorphous phase. In contrast, sediments found in the Lékédi park were composed mostly by kaolinite, an amorphous phase and gibbsite, and also quartz and undetermined clay. Quantitative analyses of quartz, the only mineral found in the analyzed samples capable to abrade tooth enamel As in other wild primates Sexes did not differ in tooth wear for both M1 and M2 in the two species see also . MoreoveSex and origin homogeneity allowed us to compare both species, and we found a clear interspecific variation. Mandrills showed higher age-related tooth wear than baboons as well as an accelerated rate of wear with age. These results suggest that there are differences in physical properties of foods and abrasive particles consumed by the two species. Field data indicate that both species are eclectic omnivores, but they rely on different resources. Forest-dwelling mandrills feed year-round a high percentage (>70%) on hard fruits and seeds from the ground The protective casing of nuts or fruit exocarps consumed by mandrills requires very high bite force magnitudes to be processed, increasing the risk of enamel tooth fractures ri = 2 to 20 mm), that mandrills consume year-round Lemur catta from Beza Mahafaly, where animals need an extreme chewing force to break the Tamarindus fruits, resulting in fast enamel cracking ri = 5 to 50 µm), implies that the teeth wear more slowly because these abrasives cause cumulative damage to enamel but not enamel cracking Mandrills should be well adapted to process hard food items because they exhibit narrow dental arcades and large symphyses involving a high adductor force per se, especially in younger animals, it should represent a response to a given environment and feeding ecology that maintain functionality. In order to determine to what extent the differences in tooth wear rates are adaptive, data on fitness are now needed as well as long-term in vivo research on well-known primate populations.The link between molar occlusal topography and food mechanical properties is crucial for food breakdown Table S11: lower M1; M1: upper M1; M2: lower M2; M2: upper M2).Captured mandrills, sex, wild (W) or captive born (C), date of release of captive born individuals, darting date and darting age, and percent of dentine exposure (PDE) for each molars (M (I) Molar was not yet erupted or only partially erupted; (II) Molar cast was of insufficient quality. NA: not applicable.(DOC)Click here for additional data file.


Drosophila provides a model for understanding how chromatin organization can modulate coordinate gene regulation. Male Drosophila increase the transcript levels of genes on the single male X approximately two-fold to equal the gene expression in females, which have two X-chromosomes. Dosage compensation is mediated by the Male-Specific Lethal (MSL) histone acetyltransferase complex. Five core components of the MSL complex were identified by genetic screens for genes that are specifically required for male viability and are dispensable for females. However, because dosage compensation must interface with the general transcriptional machinery, it is likely that identifying additional regulators that are not strictly male-specific will be key to understanding the process at a mechanistic level. Such regulators would not have been recovered from previous male-specific lethal screening strategies. Therefore, we have performed a cell culture-based, genome-wide RNAi screen to search for factors required for MSL targeting or function. Here we focus on the discovery of proteins that function to promote MSL complex recruitment to “chromatin entry sites,” which are proposed to be the initial sites of MSL targeting. We find that components of the NSL  complex, and a previously unstudied zinc-finger protein, facilitate MSL targeting and display a striking enrichment at MSL entry sites. Identification of these factors provides new insight into how MSL complex establishes the specialized hyperactive chromatin required for dosage compensation in Drosophila.Sex chromosome dosage compensation in  Drosophila melanogaster is a chromatin-modifying complex that specifically regulates a large number of genes. The MSL complex targets active genes on the single male X chromosome to upregulate their output to match both female X chromosomes. How the MSL complex specifically targets the X chromosome and upregulates active genes is only partially understood. In order to increase our understanding of gene regulation at a mechanistic level, we performed a genome-wide genetic screen in male cells to identify factors that facilitate MSL targeting and function. Our results identify two chromatin-associated protein complexes and a new candidate DNA binding protein as key factors in MSL–based regulation. We also provide an extensive list of additional candidate genes to be examined in future studies.Gene regulation is essential to all living things. For example, levels of gene expression in individual cells must be fine-tuned during development and in response to changing environmental conditions. Genes are regulated by DNA binding proteins and by factors that influence DNA packaging into chromatin. The MSL complex in  Drosophila provides a model for understanding how a large number of diversely regulated genes along the length of a single chromosome can be targeted for coordinate regulation. In Drosophila, the transcript levels of genes along the length of the single male X-chromosome are upregulated approximately two-fold, a process mediated by the MSL  histone acetyltransferase complex X-chromosome dosage compensation in male While significant progress has been made towards understanding how MSL complex is targeted and functions, much remains to be understood. For example, since MREs are less than two-fold enriched on the X-chromosome Seminal genetic screens identified five core components of the MSL complex by isolating genes that were specifically required for male viability Therefore, we designed a cell-based reporter system that specifically monitors MSL function at chromatin entry sites, and conducted a genome-wide RNAi screen to identify genes required to regulate this reporter. We identified the NSL roX2 gene (370 bp); 2) Firefly luciferase reporter gene; 3) MSL complex binding site for roX2 (DNase I Hypersensitivity Site: 280 bp). The system is based on a similar one that functions as a male-specific MSL-dependent reporter in vivoDrosophila RNAi Screening Center (DRSC) that contains approximately 21,000 dsRNAs was screened in duplicate (www.flyrnai.org). To eliminate off-target effects, secondary screens were conducted using a set of validation RNAi constructs in addition to rescreening the original constructs.In order to identify genes that regulate MSL complex recruitment or function, we performed a genome-wide RNAi screen using an MSL-dependent cell-based reporter system for which we previously reported functionality roX2 promoter and specific CES used in the genome-wide screen; 3) We then used known functional information about the genes to narrow the list to those that have potential direct activating roles; 4) We determined whether new proteins affect MSL complex recruitment at endogenous sites without altering transcription of MSL complex components; 5) We performed genome-wide localization analysis to determine whether new proteins are enriched at CES loci.In addition to direct regulators of MSL complex recruitment or function, several additional types of genes could be identified by our RNAi screen. Therefore, we used the following steps to identify potential direct activators of MSL complex targeting: 1) To reduce the number of non-specific regulators of luciferase gene transcription and protein stability that were identified, we calculated the ratio of activity from our MSL-dependent Firefly luciferase reporter to a heterologous Renilla luciferase reporter. 2) We used multiple MSL-dependent reporters to further narrow the list of genes to those that function independently of the As briefly described above, we first normalized the MSL-dependent Firefly luciferase reporter activity to an MSL-independent reporter including the Renilla luciferase gene that can be independently assayed using a different substrate. This dual Firefly/Renilla approach also controls for technical variation in transfection efficiencies among wells and differences in cell number caused by altered viability after RNAi treatments. We used a Renilla construct that was regulated by an Actin promoter as previously described msl2 RNAi) and two negative control (GFP RNAi) constructs, that were previously validated. After confirming that at least a 5-fold dynamic range was observed in the expected activity of positive and negative controls on each plate, the Firefly/Renilla ratios of the two plates were averaged and screening hits were identified relative to the median Firefly/Renilla ratio for each plate  Ribosomal protein genes that are identified by many RNAi screens (41 genes); 2) Genes with a large number of predicted RNAi off targets using 17 bp as an overlap cutoff Class 1 (18 genes): General transcriptional regulators that activate our reporter; 2) Class 2 (6 genes): Proteins that have potential sequence-specific DNA binding activity and activate our reporter; 3) Class 3 (7 genes): General transcriptional regulators that repress our reporter; 4) Class 4 (3 genes): Proteins that have potential sequence-specific DNA binding activity and repress our reporter; 5) Class 5 (7 genes): Proteins that regulate RNA metabolism ; 6) Class 6 (26 genes): Proteins that are previously unstudied and/or have functions unrelated to transcription or RNA metabolism. The remaining genes are known MSL complex components. Members of each of these classes could directly modulate MSL recruitment or activity or indirectly effect MSL complex by altering complex levels.To narrow our list of candidate genes, we classified genes into categories based on their activity in our assay and previously determined functional information about the gene products as follows : 1) ClasDue to the large number of genes identified, we focused on potential direct regulators of MSL complex recruitment or function that had known roles in transcriptional regulation or potential DNA binding domains (Classes 1–4). This analysis identified 34 potential transcriptional regulators. We validated the activity of these candidate genes using our MSL-dependent reporter assay in a more accurate 96-well format . OverallroX gene transcription in vivoroX1 CES In addition to identifying all core components of MSL complex as activators of our reporter system , we idenThe transcription of MSL complex components could be modulated and thus indirectly affect its function. Therefore, we selected candidates and examined whether they function directly to recruit MSL complex to CES loci using several approaches: 1) Determine whether RNAi against candidate genes affects recruitment of MSL complex to endogenous CES; 2) Define whether RNAi knockdown of candidates alters transcription of MSL complex components; 3) Examine the recruitment of candidate proteins to CES loci. We hypothesized that direct regulators of MSL complex recruitment will be recruited to CES loci and alter MSL complex recruitment but not transcription of MSL complex components. Using these approaches, we examined the function of three factors: 1) the NSL complex; 2) the PAF complex; and 3) CG1832.We selected NSL complex for further study because six of its components  were identified in our screen and NSL and MSL complexes share the MOF catalytic component. NSL1 is one of the structural components of NSL complex that directly contacts MOF using a similar protein-protein interaction surface as MSL1 S. cerevisiae SAGA complex component Ubp8 Drosophila) We also examined the PAF transcription complex that associates with RNAP II across gene bodies to promote transcription elongation in vivo.The previously-unstudied CG1832 zinc finger protein was chosen for further study because it was identified three independent times using different double-stranded RNA constructs and exhibits a very strong reporter activation phenotype. Furthermore, unlike other potential DNA binding proteins, CG1832 RNAi does not decrease cell viability significantly and was not identified by other RNAi screens. Similarly, loss of MSL complex components does not significantly alter cell viability although it causes male-specific lethality in flies. The CG1832 protein has a glutamine rich N-terminus and a seven zinc finger domain at its C-terminus. Because each finger is likely to recognize three bases in vivo  of the MSL2 core component in male SL2 cells. We found that both NSL1 and CG1832 RNAi knockdowns significantly reduce MSL2 recruitment to several CES loci in vivo . Next, win vivo .roX1 is not expressed at significant levels in SL2 cells roX2 RNA levels as expected because roX2 is activated by MSL complex, but little effect on the mRNA levels of other MSL complex components. Also, NSL1 and CG1832 RNAi treatments do not affect mRNA splicing of MLE as reported for the Znf72D zinc finger protein (data not shown) To examine whether NSL1 and CG1832 RNAi treatments disrupt MSL complex recruitment due to regulation of MSL complex component mRNA levels, we assayed these by qRT-PCR . roX1 iswww.modENCODE.org). Therefore, we analyzed the enrichment of these proteins at CES loci compared with other sites that contain MRE sequences. Results indicate that there is a broad enrichment of NSL complex components within a 10 kb region surrounding CES compared to additional genomic loci on the X and autosomes that contain MREs  or on more laborious assays for MSL occupancy. Many of the regulators that we have identified are likely to have additional functions in both male and female flies and therefore could not have been recovered from classical male-specific lethal genetic screens. In addition to direct regulators of MSL complex recruitment, it is possible that transcriptional regulators identified from our screening approach could function indirectly to regulate transcription of MSL complex components themselves. Therefore, we used chromatin immunoprecipitation and existing modEncode data to demonstrate that two factors, the NSL complex and CG1832, are likely to have local roles in MSL complex recruitment to CES. Moreover, CG1832 is a strong candidate to recruit MSL complex directly to CES due to its strong enrichment at MRE sequences.Using a novel cell-based RNAi screening approach, we have identified new candidate regulators of MSL complex function. The screen took advantage of the ∼five fold regulation of a Interestingly, we identified a previously unstudied function of the highly-conserved NSL complex at CES loci. NSL and MSL complex share the MOF histone acetyltransferase as their catalytic component S. cerevisiae SAGA complex component Ubp8 Many additional activators were identified from our RNAi screening approach including all components of the PAF transcription complex that associates with RNAP II across gene bodies to promote transcription elongation and polyadenylation roX CES loci In addition to identifying activators of MSL-dependent reporter activity, we identified several repressors including NURF301, a known repressor of MSL complex function at the Our most exciting new candidate is CG1832, a previously unstudied zinc-finger protein that is strongly and precisely enriched at MRE sequences within CES and facilitates MSL complex recruitment to these sites. This protein has seven zinc-fingers at its C-terminus that could potentially bind DNA and a glutamine-rich N-terminus that may interact with MSL complex. Therefore, future analyses will focus on the exciting possibility that CG1832 functions as a previously unknown link between MSL complex and MRE sequences.In summary, our novel screening approach identified two regulators that facilitate MSL complex recruitment at CES: NSL complex and CG1832. Furthermore, our genetic screen provides an extensive dataset of additional candidate genes that may facilitate MSL targeting and function. We expect that future genetic, genomic, and biochemical approaches will define new mechanisms by which many of these candidate genes modulate coordinate gene regulation.www.flyrnai.org) A genome-wide RNAi screen was performed in duplicate using the version 2 RNAi libraries generated by the Drosophila RNAi Screening Center . All RNAi treatments were conducted for 5 days in SL2 cells as previously described mRNA analysis and qRT-PCR was performed after the following RNAi treatments: 1) DRSC03718 to target CG1832; 2) DRSC15625 to target NSL1 (CG4699); and 3) DRSC27502 to target PAF1  was used at a 1∶10,000 dilution, and the histone H3 antibody (Abcam) was used at a 1∶1000 dilution.Western blotting was conducted as previously described using standard protocols www.flyrnai.org): 1) DRSC03718 to target CG1832; 2) DRSC15625 to target NSL1 (CG4699); and 3) DRSC27502 to target PAF1 (atms). To assure reproducibility, large scale RNAi experiments were performed in which 225 ug of each dsRNA was added to a T225 flask containing 45 mls of SL2 cells. An additional CG1832 RNAi construct (DRSC 29935) was also tested with similar results (data not shown).Chromatin immunoprecipitation from SL2 cells was conducted as described previously Three independent chromatin preparations were performed for each experiment and qPCR was performed on input and IP samples using primers that are specific for MSL target genes and CES loci. Primer sequences were previously described www.illumina.com). To obtain sufficient starting material, three IPs were pooled and concentrated using Qiagen MinElute columns such that 15 ng of starting material were obtained prior to library preparation. Libraries from matching input samples were also prepared for each chromatin preparation. Each enzyme reaction was followed by purification using AMPure XP Beads (Agilent). The fragmented DNA was 3′ end repaired and 5′ phosphorylated using End-it Kit (Epicentre). A 3′ adenosine was added using Klenow Fragment (3′→5′ exo) (NEB). The annealed adapters were ligated in a 1∶50 dilution of the 10 mM stock using T4 DNA Ligase Quick Ligase Kit (Enzymatics). The libraries were PCR amplified using Phusion high fidelity polymerase (NEB) for 15 cycles. The libraries were then size selected on a 2% agarose gel using the E-Gel system (Invitrogen) selecting a range from 200 bp to 500 bp followed by concentration on a MinElute Column (Qiagen). Sequencing was performed on the Illumina GaIIx platform.Duplicate ChIP-seq libraries from independent chromatin preparations were generated using a protocol adapted from the Illumina ChIP-seq sample preparation guide as follows Replicate #1 CG1832 IP: 27820142 raw reads, 19210177 aligned reads (69.1%)Replicate #2 input: 22498098 raw reads, 13510882 aligned reads (60.1%)Replicate #2 CG1832 IP: 28231400 raw reads, 15194724 aligned reads (53.8%)Pearson R value for CG1832 ChIP-seq replicates, 1 kb bins: 0.95Reads aligned with more than one mismatch, and reads that did not align uniquely were discarded. Peaks were called in each ChIP-seq sample using the SPP software package with an FDR threshold of 0.05 The average enrichment profiles of proteins around the MREs (+/−5 kb) are shown in www.modencode.org). Data analysis was performed in R statistical programming environment (http://www.r-project.org). For the visualization of the heatmap  are publicly accessible online through the modENCODE project  qRT-PCR was used to assay the expression levels of all MSL complex components present in SL2 cells. roX2 levels are decreased likely because targeting of MSL complex to the roX2 CES locus is altered by the RNAi treatments as expected. Expression levels of other MSL complex components are unchanged. All data were normalized to the control RNAi treatment and are the average of two replicates. B) Effective RNAi treatments were validated by qRT-PCR and the results shown are the average of two replicates.(TIF)Click here for additional data file.Figure S2Western blots for CG1832 RNAi treatment and antibody validation. A) Westerns on whole cell and nuclear extracts indicate that CG1832 is a nuclear protein and the CG1832 RNAi treatment reduces CG1832 protein levels. The arrow indicates the location of the CG1832 protein (60 kDa) and tubulin was used as a loading control. B) Nuclear extraction was performed on protein samples from SL2  and Kc  cells followed by Western blotting. The histone H3 antibody was used as a loading control. Levels of CG1832 are similar in males and females.(TIF)Click here for additional data file.Figure S3Validation of CG1832 antibody by ChIP at CES loci. qPCR was performed on CG1832 ChIP samples before and after CG1832 RNAi treatment. Three independent CES loci were assayed and CG1832 RNAi strongly reduced the levels of CG1832 protein on chromatin at all three loci. An average of two independent experiments is shown.(TIF)Click here for additional data file.Figure S4Immunostaining of polytene chromosomes. Polytene staining using the CG1832 antibody (red) in male (A) and female (B) larvae. Co-staining was performed with an anti-MSL3 antibody (green). Co-localization of the two proteins is shown in yellow.(TIF)Click here for additional data file.Table S1Initial candidates identified from a genome-wide RNAi screen to identify novel regulators of dosage compensation.(XLSX)Click here for additional data file.Table S2Final candidates identified from a genome-wide RNAi screen. Candidates are color-coded and divided into functional categories described at the bottom of the table.(PDF)Click here for additional data file.


Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs.Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the  Xanthomonas genus of plant pathogens. TALEs are translocated into plant cells via the bacterial type III secretion system (T3SS). They operate by mimicking the activity of plant transcription factors and bind to promoter regions of host plant genes. When TALEs contribute to virulence, the induction of their cognate target gene, referred to as a susceptibility gene, enhances the fitness of the bacteria in plant tissues Transcription activator-like effectors (TALEs) belong to a family of bacterial proteins initially identified in the TALEs have highly conserved amino acid sequences containing T3SS secretion and translocation signals in their N-terminal region, a central DNA-binding domain, nuclear localization signals and a transcriptional activation domain in their C-terminal region e.g, disease resistance) in plants and animals, and the potential applications of this technology are remarkable The discovery of the TALE-DNA code was a milestone not only in plant-pathology but also in biotechnology. By using the binding specificities of the best characterized RVDs  and taking advantage of the modular nature of TALEs, researchers have been able to engineer artificial TALE proteins with any desired specificity to induce the expression of individual genes, not only in plants but also in other eukaryotes Xanthomonas genus comprises 27 species that collectively cause major diseases on more than 400 plant hosts, including a wide variety of economically important crops, such as rice, citrus, banana, cassava, cabbage, tomato, pepper and beans Xanthomonas genome sequences available from 11 species (http://www.xanthomonas.org/) and this number is likely to increase dramatically in the near future. Xanthomonas strains harbor quantitatively and qualitatively different repertoires of TALEs, and the total number of sequenced TALEs available in databases reaches roughly 100 (http://www.xanthomonas.org/). Despite great advances in TALE-based biotechnology, the collective role of TALEs during infection has not been systematically investigated and only a few transcriptional targets have been validated in host plants Xanthomonas on agriculture worldwide The Currently, a single TALE target prediction algorithm based on the published TALE-DNA code X. oryzae strains. Because we had access to TALE repertoires of both the xylem vessel-associated X. oryzae pv. oryzae (Xoo), the causative agent of the bacterial leaf blight, and the mesophyll-associated X. oryzae pv. oryzicola (Xoc), the causative agent of the bacterial leaf streak, we could also compare the plant candidate target sets of these pathovars with contrasting tissue specificity. The resulting predictions reveal a putative network for TALE-gene interactions with several examples of functional convergence within and across strains.In this work, we used the available literature on TALE-RVD specificities from experimentally validated TALE-DNA interactions to develop new programs for TALE binding sites prediction. Our software outperformed the TALE-target finder module of the TALE-NT suite in differentiating positive and negative TALE-DNA interactions. It was subsequently employed to predict rice microarray data-supported new binding sites for TALEs from various see Materials and Methods, program descriptions).In this work, two programs named Talvez and Storyteller were designed to predict TAL effectors binding sites in plant genomes. Similar to the reference target finder program from the TALE-NT suite To compare the performances of the EBE prediction programs, a validation set was first established . It is cX. oryzae strains; Hax2 from X. campestris pv. armoraciae) that have at least one genuine gene target and associated EBE in the genome of the host plants Oryza sativa cv. Nipponbare or Arabidopsis thaliana Col0 (OsTFIIAγ1), Talent performed the best  those instances of RVD-nucleotide matches that conform to the most probable pairing specified in the updated RVD-nucleotide association matrix  and incompatible (resistance) interactions X. oryzae pathovars (e.g. 17 for Xoo PXO99A and up to 32 for Xoc BLS256) X. oryzae strains as well as numerous TALE sequences from a variety of other strains prompted us to use our prediction algorithm in order to comprehensively investigate the sets of high quality candidate TALE targets in the Oryza sativa cv. Nipponbare genome. To this end, we cross checked Talvez predictions with experimental evidence of candidate target gene induction during compatible interactions in publicly available microarray data as a good estimate of true direct up-regulation of a gene by a TALE in a rice susceptible background.TALEs are central to the interaction between many Xoo and Xoc strains with associated microarray data of rice gene responses to infection in databases  in a set of five relevant microarray data comparisons. In all examined comparisons, these genes displayed very high fold change ratios which, as shown in 2 fold change ≥1, adjusted p-value ≤0.1). We therefore adopted a differential expression rank threshold of 100 which was sufficient to capture all control TALE targets, and applied this threshold to select Talvez predictions exhibiting an induction pattern similar to genuine TALE targets.Talvez was used to identify candidate target genes for all sequenced TALEs from Asian Xoo PXO99A and Xoc BLS256 strains  and the distribution of the prediction ranks was significantly different from the original network  showing no prevalence of high ranking genes . This inOs11N3 and LOC_Os04g19960 . To support this notion with more discriminatory expression data, we identified Talvez-predicted genes specifically induced by individual TALEs by comparing the expression profiles of plants inoculated with wild-type bacteria and mutants for PthXo1  and both PthXo6 and AvrXa27 . For the PthXo1 experiments, from the top 100 most induced genes, only the known Os8N3 target had a predicted EBE (A versus PXO99A T3SS mutant microarray data comparison on Nipponbare (OsTFX1 (LOC_Os09g29820), up to six genes were significantly induced in the wild type versus double mutant strain comparison on at least one rice variety and had a high-scoring Talvez-predicted EBE for PthXo6  Os8N3 and Os11N3, another MtN3/SWEET (LOC_Os12g29220) was found to be putatively targeted by a TALE (YP_451027.1) from MAFF311018  and LOC_Os05g31620 (OsCML15) genes which both encode calmodulin-like proteins may represent another case of convergence towards a gene family  was induced in Nipponbare inoculated with Xoo strain PXO99A versus the T3SS mutant ME7, and contained a predicted EBE for PthXo7. In rice, Calmodulin-like proteins are known to be necessary for colonization of plants by both pathogenic and symbiotic organisms Various TALEs from unrelated FF311018 . This get Os11N3 . Altogetd Os12N3 , indicate family . OsCML5 Os11N3 precedent Os11N3, five genes were found to be targeted by multiple TALEs in distinct EBEs . They therefore represent prime candidates for novel plant susceptibility factors. One of these loci corresponds to OsHen1 (LOC_Os07g06970) which is probably targeted by the Xoc TALE Tal1c from BLS256 and the Xoo TALE Tal9A from PXO99AOsHen1 was recently claimed to be the avirulence factor avrXa5OsHen1, the only other apparent case of convergence between Xoc and Xoo strains  probably determines for the most part the target DNA recognition and activity. In contrast, downstream positions seem to hold little information for identifying legitimate EBEs. In agreement with this, Kay et al. ions 3–4  which exXa27 (LOC_Os06g39810) and Hax2-PAP1 (AT1G56650). Our preliminary attempts to incorporate a matrix with higher scores for strong RVDs yielded no prediction improvement in our validation set (data not shown). Another feature that could improve predictions is a better knowledge about the effect of the genomic context of the EBE on TALE binding or activity . Yet, this aspect remains poorly explored.The control targets of four TALEs, namely AvrXa7, PthXo3, AvrXa27 and Hax2, were hard to predict with any of the programs and ranked very low in whole genome searches. AvrXa7 and PthXo3 are particularly long TALEs with a high number of RVD-nucleotide mismatches in the DNA-binding sequence upstream of their respective target. The predictions for these TALEs were however largely improved when a position correction was applied to Talvez. In contrast, AvrXa27 and Hax2 retained relatively low rankings, despite a slight improvement in the detection of their respective EBEs upon applying the position correction. These TALE-EBE pairs probably correspond to atypical interactions that cannot be explained solely on the basis of the standard rules of RVD-nucleotide association. Clearly, the current model of TALE-EBE specificity is not perfect and does not yet account for less characterized or unsuspected aspects of TALE-DNA interactions. For example, it was recently demonstrated that different RVDs have different contributions to DNA binding X. oryzae strains. Putative targets for a total of 69 TALE sequences from four strains were identified in the O.sativa japonica genome using a combination of software predictions and expression data analysis. On top of this high-quality TALE-candidate rice target gene network, Talvez predictions for 29 additional TALEs identified genes that may be repeatedly targeted by X. oryzae strains.Because of the key role of T3SS substrates in the infection process, identification of type III effector host targets may be the fastest route to the molecular dissection of virulence strategies of pathogenic bacteria relying on such systems, and on the host biological processes that are perturbed to create disease-promoting conditions. In this respect, TALEs are interesting type III effectors because they manipulate the host physiology by direct transcriptional up-regulation of susceptibility genes. Hence, the ability to accurately predict TALE-binding elements in rice promoters enables a straightforward comparative perspective on individual TALEs targets as well as on the organization of TALE repertoires: how they are functionally structured with respect to their virulence target genes and how these repertoires may evolve. The performance of Talvez allowed a systemic insight into the sets of candidate target genes of Xoo PXO86 and its secondary target LOC_Os04g19960 While it has been previously reported that individual TALEs can induce the expression of multiple genes On a contrasting note, it is worth pointing out that our microarray-supported Talvez EBE predictions did not identify any targets in the Nipponbare genome for 22 out of the 69 TALEs in the query set. This apparent absence of candidate targets might stem from an intrinsic inability of our algorithm to predict accurate targets for this specific set of TALEs as discussed above. Relevant EBEs for these TALEs may also have been missed because they are located outside of the 500-bp upstream regions of annotated objects represented in the Affymetrix chip. On the other hand, it is likely that cognate EBEs are genuinely absent from the Nipponbare genome and that searching other genomes, e.g. from indica varieties, may ultimately identify true targets. Alternatively, as proposed by Yang and Gabriel Xoo and Xoc strains provides a novel perspective on genes or gene families that repeatedly appear to be induced by TALEs. The observed overlap of our high-quality rice candidate target sets across strains is relatively limited and rather unexpected, especially for the PXO99A and MAFF311018 strains which belong to the same Xoo pathovar but share only six common targets (OsHen1 (LOC_Os07g06970) stands out as being putatively targeted by 5 distinct TALEs from all Xoo and Xoc strains with a complete TALE inventory, plus the alleged X. oryzae strains regardless of their respective tissue tropism but a role of OsHen1 as a susceptibility gene has not been described yet. Similarly, LOC_Os03g03034 annotated as a flavanone 3-hydroxylase (F3H) with potential roles in plant-bacteria interactions could belong to the same universal target category. However, no cognate TALE was found for this F3H in the KACC10331 genome. In rice, F3H proteins have been found to be induced in multiple resistant interactions Our comparative analysis of the sets of rice genes potentially targeted by the complete TALE repertoires from  targets . One intXoo strains to successfully colonize rice xylem vessels. Indeed, it was previously shown that three unrelated Xoo strains require TALE-mediated transcriptional induction of a MtN3/SWEET family member for full virulence on susceptible rice varieties Os12N3, another member of the MtN3/SWEET family which corresponds to the responsive allele (Xa25) of the xa25 resistance gene Os12N3 susceptibility allele (Xa25) is induced by PXO339 in susceptible varieties, including Nipponbare Os12N3 shows various polymorphic sites possibly associated with resistance (including two polymorphic sites in the predicted EBE for YP_451027.1) Os12N3. Interestingly, based on our predictions for TALEs of Xoc strain BLS256 and an earlier genetic screen with BLS303 Xoc TALE targeting a MtN3/SWEET family member, Xoc strains may not require relocation of sucrose to the apoplast or may rely on other sugar efflux mechanisms for infection of the leaf mesophyll. It is noteworthy however that heterologous TALEs targeting MtN3/SWEET family members do confer an increased virulence to XocOsTFX1  has also been reported to be “universally” induced by Xoo strains from diverse geographical origins OsTFX1. However, this gene ranks in the 100 most induced genes 24 hours post inoculation with this strain (data not shown), revealing a possible false negative prediction or pointing to an erroneous TALE DNA sequence in databases.Remarkably, our work and earlier studies of others provide strong evidence that induction of a member of the MtN3/SWEET family, presumably as a way to extort carbon sources from the host, is an absolute requirement for X. oryzae TALE repertoires that emerges from our study is an apparent tendency of individual repertoires to maintain several TALEs capable of redundantly targeting the same or functionally equivalent genes. This seems to be true for the plethora of TALEs in the Xoc BLS256 genome, but perhaps the most edifying example of functional convergence involves again the MtN3/SWEET gene family. We discovered that strains MAFF311018 and most likely KACC10331 possess a couple of RVD sequence-unrelated but functionally redundant TALEs, each putatively capable of inducing a separate MtN3/SWEET gene , xa25 , or the ones engineered in the Os11N3 gene promoter Xoo on MtN3/SWEET susceptibility genes to cause disease, it is therefore advisable to pyramide several unresponsive MtN3/SWEET genes alleles in a single genetic background, thus likely conferring broad spectrum resistance to bacterial leaf blight. It is important to note however that this strategy could be defeated by strains that have acquired TALEs recognizing novel EBEs, such as TalC for Os11N3Another original feature of EET gene . It is aO. sativa, and for predicting artificial TALEs off-target binding sites in biotechnological applications. Our understanding of the global contribution of TALEs to pathogenicity in the X. oryzae–rice pathosystem will benefit from the identification of conserved plant targets which tend to be highly connected hubs in functional networks and which may play a major role in susceptibility. The identification of redundant TALEs within individual effector repertoires provides guidelines for their inactivation and for breeding and engineering resistant plant varieties. In the future, Talvez in conjunction with gene expression data will greatly facilitate the identification of candidate TALE-dependant immunity loci in the genomes of resistant accessions in the germplasm of major crops.In conclusion, this work provides a more accurate tool for mining TALEs virulence targets in the genomes of host plants, as performed here for http://bioinfo.mpl.ird.fr/cgi-bin/talvez/talvez.cgi) allows scanning of 25 preloaded complete promoters sets from plant genomes such as O. sativa, A. thaliana, Vitis vinifera or Populus trichocarpa downloaded from Phytozome (http://www.phytozome.net/).Talvez is implemented in the Perl and Java programming languages and is based in part on a method for transcription factor binding sites identification relying on Positional Weight Matrices (PWM) that shows great accuracy when accompanied with a log-likelihood scoring system taking into account nucleotide distributions in scanned sequences Storyteller was written in the Perl programming language. It relies on hidden Markov models and works as follows: (i) The program converts a TALE RVD sequence into a PWM and uses this matrix to generate a set of possible binding sequences (rounds). (ii) While generating the sequences, an error function introduces “noise” to allow the creation of mismatching sequences. The noise is reflected in the probability of generating any nucleotide for a possible binding sequence regardless of the RVD specificities. The probability can be zero, if the error function is set to “none”, or kept constant if the error function is set to “constant”. The noise can also be set to depend on the position. It can either linearly increase or decrease along the sequence if the error function is set to “linear”, or it can be set to “parabolic” to allow more noise at both ends, or it can be “Hvaa or RVD dependent” resulting in less noise for the best characterized RVDs. In addition to the noise function, the PWM also allows the use of pseudocounts. (iii) The generated sequences are converted into a HMM using hmmbuild from the HMMER2 software To encode RVD-nucleotide association specificities, the values of the counts matrix originally assembled by Moscou and Bogdanove −1 to allow comparisons with the other programs. EBE screenings were made against the promoter regions (500 bp upstream of the translation start site) of predicted genes in the A. thaliana (TAIR v 10) and O. sativa (MSU 7.0). Promoter sequences were extracted using the BioMart tool at www.phytozome.comPredictions for Talvez used the following parameters: pseudocounts ‘1e-05’, minimum score ‘9’, number of reported TALEs ‘all’ and various position corrections. Predictions for Storyteller used the following parameters: rounds ‘1e5’, noise ‘0.5’, noise-shape ‘hvaa-dependent’, max e-value ‘700’, minscore ‘2’, gap probability ‘1e-3’. Predictions for Tale-NT Arabidopsis genome was used for whole-genome screenings  were manually extracted from the available protein sequences at NCBI. Sequences from pseudogenes or TALEs with less than two RVDs were not included. When two database entries corresponded to the same RVD sequence in the same strain only one entry was kept. All RVD sequences for TALEs in our validation set were confirmed with those in the corresponding literature. These sequences as well as other information relative to the TALEs included in the analysis  can be found in A comprehensive validation set of negative and positive interactions was build based on published TALE-DNA pairs that have been tested experimentally by GUS assays, electrophoretic mobility shift assay and/or QRT-PCR reenings . RVD seqThe outputs of the prediction softwares obtained after screening the validation set of experimentally tested positive and negative interactions were analyzed as follows: for each TALE and each program, a minimum classifying threshold was defined as the lowest score for a genuine positive EBE, all EBEs scored above or equal to that threshold were considered positive predictions and all EBEs scored below that threshold were considered negative predictions. In this way a true positive corresponded to a genuine positive EBE scored equal or above the minimum threshold , and a false positive corresponded to a genuine negative EBE scored equal or above the minimum threshold . For construction of the ROC graphs, the true and false positive rates were calculated as specified in X. oryzae pv. oryzae or by X. oryzae pv. oryzicola” (GSE16793), “Comparison of transcriptional responses of two susceptible rice cultivars to strains of Xanthomonas oryzae” (GSE36272). The Affymetrix probe-level expression data in CEL files was processed separately for each dataset using the Bioconductor affy package 2-transformed fold change (logFC) equal or above 1 and an associated adjusted p-value (Benjamini and Hochberg’s adjustment method) equal or below 0.1 in a treatment comparison were deemed as differentially expressed. Their expression data (logFC and logFC rank) and associated limma statistics in that comparison were recorded in a custom sqlite database. This database also stored the Talvez predictions on the corresponding 500 bp promoters set and was queried to retrieve TALE targets satisfying specific criteria as described in the results section. The mapping of Affymetrix probe sets on MSU6 Gene Model IDs was obtained from the www.ricechip.org website.Routine computational tasks were performed in R with facilities provided by packages from the Bioconductor project X. oryzae TALE encoded in PXO99A, MAFF311018, PXO86 and BLS256 strains by shuffling their RVD sequence. Next, 100 random networks were assembled iteratively by randomly selecting one of the six shuffled TALE derivative for each initial natural TALE and querying the database for its associated Talvez-predicted targets that also met the microarray expression criteria. The distributions of node properties such as Talvez rank and connectivity measures (TALE and rice gene degrees) were computed in R with facilities from the graph package of Bioconductor.Random TALEs – rice genes networks were constructed by first generating six random TALEs for each natural http://www.functionalnet.org/ricenet/search.html) and retrieving the complete output network . TALE-gene network and functional networks for TALE targets obtained from RiceNet were visualized using Cytoscape O. sativa MSU7 nonTE background and by testing with Fisher and hypergeometric methods at 0.05 significance. Other advanced options were left unchanged. Statistical tests for distribution and mean comparisons were performed in R.Perfect matches (PMs) in the validation set of positive and negative interactions were identified using an in-house Perl script that identified PMs in each position based on the RVD-nucleotide specificities used by Talvez. Connectivity of TALE target or random gene sets in was assessed by querying the Ricenet http://bioinfo.mpl.ird.fr/cgi-bin/talvez/talvez.cgi, and http://bioinfo-prod.mpl.ird.fr/xantho/tales, respectively. Finally, the source code of the Talvez and Storyteller is also available for download on Sourceforge at https://sourceforge.net/projects/talvez/andhttps://sourceforge.net/projects/storytellr/respectively.Packages containing the source code of the Talvez and Storyteller programs are available in Figure S1Distribution of the relative expression ranks of control TALE target genes in microarray data. The x-axis values correspond to a decimal log transform of the rank of the log2 fold change (logFCRank) of the Affymetrix probeset(s) corresponding to a control gene in a specific treatment comparison. For all bacterial strain-rice cultivar combinations (see legend), the logFCRank data correspond to a wild type strain versus mock comparison. For PXO99A, a wild type strain versus mutant strain defective for type III secretion comparison was also included.(TIF)Click here for additional data file.Figure S2Relevance of candidate TALE target genes in available rice functional prediction data. (A) Singular Enrichment Analyses for GO terms associated with candidate TALE target genes (input list) compared to background annotations in rice performed with AgriGO. No significant differences were found . (B) Predicted functional network for candidate TALE target genes in the probabilistic functional gene network RiceNet. Candidate TALE target genes are shown in red, non-TALE targets are shown in green (C) Frequency of highly connected genes in RiceNet among candidate TALE targets compared to randomly selected sets of rice genes.(TIF)Click here for additional data file.Figure S3A survey of possible association between in-network TALE degree and TALE RVD sequence features. Dispersion plots showing the relation between TALE degree  and TALE length (in number of repetitions) or TALE common RVDs frequency (percentage) in the predicted TALE-target gene network. Spearman correlation values are shown between parentheses.(TIF)Click here for additional data file.Figure S4Representation of the “conserved target” network. See the legend of (TIF)Click here for additional data file.Table S1Updated RVD-nucleotide association matrix used by Storyteller and Talvez to produce PWMs. Darker gray shading indicates increasing binding preferences for each RVD. Higher counts were assigned to well-studied RVDs .(XLSX)Click here for additional data file.Table S2X. campestis pv. armoriaceae, Xcv = X. campestris pv. vesicatoria, Xg = X. gardnerii, Xoc = X. oryzae pv. oryzicola, Xoo = X. oryzae pv. oryzae. The subset of interactions that were used for genomic screenings and that correspond to genuine targets in the rice or Arabidopsis genome are highlighted in green and underlined.Validation set of controls used to test EBE prediction programs. RVDs and promoter sequences were extracted from the indicated references. Interaction class indicate the experimental results,+(positive) = the TALE binds to the EBE or is able to induce the expression of a gene located downstream of the EBE, − (negative) = the TALE is unable to induce the expression of a gene located downstream of the EBE. Raw prediction scores from each program are reported. Each prediction is classified as a true positive (TP), true negative, (TN), false positive (FP) and false negative (FN). Xca = (XLSX)Click here for additional data file.Table S3. All perfect matches were assigned a value of 1.5 and all non-preferred matches a value of 1.0.Scaled-down RVD-nucleotide association matrix. This matrix is used by Talvez to produce PWMs after a specified position when the position correction is applied(XLSX)Click here for additional data file.Table S4X.oryzae strains used in this work.Supplementary information on TALEs from (XLSX)Click here for additional data file.Table S5Description of the microarray data comparisons performed to identify TALE-regulated genes. Each row corresponds to a pair-wise treatment comparison used in this work to calculate Log Fold changes and select up-regulated genes. Information about the host plant genotype, the query strain, the appropriate reference treatment and the sampling time is provided. Number of TALEs indicates the potential number of TALEs that are expected to be queried for potential rice gene induction activity in that comparison (i.e. difference in TALE numbers between the tested strain and the control treatment). Accession numbers correspond to NCBI GEO Datasets accession numbers.(XLSX)Click here for additional data file.Table S6X. oryzae TALs when varying the value of the position correction. A gene within the top 200 predicted genes and that also shows differential expression in microarray data is considered as a TALE target gene. Predictions were made against the set of rice promoters for the set of 69 TALE RVD sequences encoded in the genome of strains that have supporting rice expression data. The Number of top or high ranking genes columns reports the cumulated counts of TALE-wise target gene predictions that rank respectively first or in the top 10 in the entire predictions set and that are also differentially expressed. The Sum column displays the row-wise sum of performance indicators values as a composite aggregator value to be maximized.Assessment of various position correction values for predicting induced TALE targets. Performance indicators for the capacity of Talvez to predict differentially expressed genes (as determined by microarray data) for all sequenced (XLSX)Click here for additional data file.Table S7TALE-candidate target gene network data. Talvez predictions obtained with a position correction value of 19 and cross-referenced with microarray data are reported. Accession number corresponds to the TALE protein sequence available in public databases. RVD sequences were manually extracted from available protein sequences. TALE alias corresponds to a known common name for a given TALE. TARGET gene ID refers to the locus ID of genes containing a Talvez-predicted EBE in their promoters. Prediction scores and rank correspond to the Talvez predictions for the TALE-EBE pair after searching the rice promoters set. Evidence indicates whether the TALE-gene association is supported by gene-induction data in microarrays or if it corresponds to a TALE from a strain without associated microarray data that has a predicted target that is likely induced by TALE from our reference strains (“Conserved target”). The logFC, logFCRank, AveExpr, adj_P_Val and B columns contains respectively the log2-fold change, the rank of the logFC when the values for that comparison (described in the Treatment comparison column) are sorted in a decreasing order, the average log2-expression level for that gene across all the arrays in the experiment, the associated p-value after adjustment for multiple testing and the log-odds that the corresponding gene is differentially expressed in the comparison.(XLSX)Click here for additional data file.Table S8Predicted EBEs in the promoter of differentially expressed genes in microarray comparisons addressing TALE-specific effects. LogFC values correspond to the log2 fold-change from comparisons between plants inoculated with either the wild-type or a TALE-mutant bacteri. EBE distances refer to the translation start site.(XLSX)Click here for additional data file.Datasets S1Cytoscape Session (.cys) file containing the primary, expression data supported TALE-rice gene network that served for the construction of .(CYS)Click here for additional data file.Datasets S2Cytoscape Session (.cys) file containing the conserved TALE-rice gene network that served for the construction of (CYS)Click here for additional data file.Datasets S3Script files for Talvez.(TAR)Click here for additional data file.Datasets S4Script files for Storyteller.(TAR)Click here for additional data file.