s2fieldsofstudy:
Biology
Environmental Science

text:
The microbiome of coral surface mucus has a key role in mediating holobiont health and survival upon disturbance

Microbes are well-recognized members of the coral holobiont. However, little is known about the short-term dynamics of mucus-associated microbial communities under natural conditions and after disturbances, and how these dynamics relate to the host's health. Here we examined the natural variability of prokaryotic communities (based on 16S ribosomal RNA gene amplicon sequencing) associating with the surface mucus layer (SML) of Porites astreoides, a species exhibiting cyclical mucus aging and shedding. Shifts in the prokaryotic community composition during mucus aging led to the prevalence of opportunistic and potentially pathogenic bacteria (Verrucomicrobiaceae and Vibrionaceae) in aged mucus and to a twofold increase in prokaryotic abundance. After the release of aged mucus sheets, the community reverted to its original state, dominated by Endozoicimonaceae and Oxalobacteraceae. Furthermore, we followed the fate of the coral holobiont upon depletion of its natural mucus microbiome through antibiotics treatment. After re-introduction to the reef, healthy-looking microbe-depleted corals started exhibiting clear signs of bleaching and necrosis. Recovery versus mortality of the P. astreoides holobiont was related to the degree of change in abundance distribution of the mucus microbiome. We conclude that the natural prokaryotic community inhabiting the coral SML contributes to coral health and that cyclical mucus shedding has a key role in coral microbiome dynamics.

Introduction
Corals live in a well-described mutualism with photoautotrophic endosymbiotic dinoflagellates of the genus Symbiodinium, frequently referred to as zooxanthellae (reviewed by Muscatine, 1990). More recently, the concept of the coral holobiont (Rohwer et al., 2002) has been proposed to describe the association of the coral host with a diverse microbial community including representatives of fungi, endolithic algae, bacteria and archaea, of which certain associations are species-specific (Ritchie and Smith, 1997;Rohwer et al., 2002;Koren and Rosenberg, 2006;Carlos et al., 2013). The sum of these microorganisms and their combined genetic material forms the coral microbiome, whose core composition is determined by the host but whose presence allows for metabolic adaptations to local environmental conditions by selection of beneficial genes (Kelly et al., 2014;Ainsworth et al., 2015).
The putative functions of the coral microbiome comprise, among others, the protection against pathogens (Rohwer et al., 2002;Shnit-Orland and Kushmaro, 2009) and the supply and cycling of nutrients (Lesser et al., 2004;Wegley et al., 2007). Gates and Ainsworth (2011) propose that all taxonomic components should be considered as important because of their potential to stimulate the holobiont's functioning. However, the extent of the microbiome's contribution to the health of the coral holobiont and to coral reef resilience remains largely unknown. Whereas the association between the coral and its eukaryotic symbionts of the genus Symbiodinium is fairly well characterized (Rowan, 2004;Frade et al., 2008), relatively little is known about the spatial and temporal variation of the coral's prokaryotic microbiome. Recent studies have shown shifts in the microbiome from healthy to diseased corals and under altered environmental conditions (Bourne et al., 2007;Mao-Jones et al., 2010), supporting the idea that both the disturbance of the native microbiota and the direct infection by specific pathogens threaten the well-being of corals.
The coral host provides several distinct habitats for its microbial inhabitants-the tissue (Lesser et al., 2004), the gastrovascular cavity (Herndl and Velimirov, 1985), the skeleton (Sharshar et al., 1997) and the surface mucus layer (SML) (Rohwer et al., 2002;Kooperman et al., 2007), each harboring a distinct microbial community (Sweet et al., 2011a). The SML is particularly important for the biology of corals not only as a habitat for a distinctive suite of coral-associated microbes but also due to its nutritional, protective and cleansing roles (Brown and Bythell, 2005). Consisting of polymeric glycoproteins and lipids (Bythell and Wild, 2011), coral mucus provides a nutritious medium on which a diverse assemblage of microbes thrives, many of which are highly host specific (Rohwer et al., 2002). Although coral mucus is in constant contact with the adjacent seawater, their prevalent microbial communities exhibit almost no overlap (Rohwer et al., 2001(Rohwer et al., , 2002Frias-Lopez et al., 2002). Furthermore, it has been hypothesized that the microbial community in the coral SML operates as a defense barrier and therefore protects the coral against invasive microbes either because of the production of antimicrobial substances or simply because of the occupation of this interface niche (Rohwer et al., 2002;Reshef et al., 2006;Rosenberg et al., 2007;Shnit-Orland and Kushmaro, 2009).
The SML is a very dynamic system whereby its molecular organization and composition vary between coral species and over time (Brown and Bythell, 2005). In addition, the SML experiences sloughing, either continuously or periodically, from the coral surface into the reef environment (Bythell and Wild, 2011). This cycle of structural changes creates habitat dynamics to which microbial communities are likely responding (Nelson et al., 2013).
Corals of the genus Porites sp. provide an ideal model system to study natural short-term dynamics of the mucus microbiota because of a clearly recognizable and well-described aging process that precedes periodical sloughing of the entire mucus layer and its reformation (Coffroth, 1991). The SML initially appears as a transparent surface film whose visual appearance slowly changes over the course of a few days into a conspicuous aged mucus sheet. After the release of this aged sheet of mucus into the water column, new fluidic mucus is produced at the surface of the coral leading to a new cycle, suggested to follow a lunar periodicity (Coffroth, 1991). Our rationale is that the temporal transformation and periodical release of mucus from the surface of poritid corals may trigger or relate to the establishment of a microbial succession analogous to the one shown for bacterioplankton after phytoplankton blooms (Teeling et al., 2012).
To better understand the role of the mucus microbiota on the health and resilience of coral holobionts, we apply an indicator species approach aiming (1) to unravel the natural short-term dynamics of mucus-associated prokaryotic communities coupled to the cyclical aging and release of SML of Porites astreoides and (2) to follow the successional steps taking place after disruption of the coral's microbiome.

Materials and methods
Species, study location and sampling approach Porites astreoides Lamarck 1816, a common coral species on Caribbean reefs (Bak, 1975), exhibits the typical mucus aging behavior of poritid corals (Figure 1a and Supplementary Figure S1) and was chosen as a model species. Fieldwork was conducted between February and March 2014 on Curaçao (former Netherlands Antilles). Samples were collected by SCUBA diving at 5 m depth on the reef flat of the CARMABI Buoy One reef location (12°7.46'N, 68°58.31'W). In situ light irradiance (765 ± 178 μmol photon m − 2 s − 1 at noon) and temperature (26.6°C ± 0.4°C) were measured at 5 m depth with a Hydrolab DS5 Sonde and with HOBO Pendant Temperature/Light Data Loggers, respectively, for the entire duration of fieldwork. Our approach consisted of two parts: an in situ description of the 'natural dynamics of coral mucusassociated prokaryotes' related to the cyclical change between new and aged mucus over time, and a manipulative approach in which colonies were removed from the reef, their microbiome disturbed in the aquarium, and 'prokaryotic mucus re-colonization after antibiotics disturbance' monitored after re-introduction of the colonies to the reef environment ( Figure 1).

Natural dynamics of coral mucus-associated prokaryotes
To assess in situ the microbial dynamics in the SML of P. astreoides, seven colonies were regularly monitored by collecting mucus samples with sterile cotton swabs ('swabbing') every second to third day for a total period of 2 months (one sample per colony per day; see Figure 1a). On each sampling occasion, the mucus aging state was visually categorized as either 'new' or 'aged' following published approaches (Coffroth, 1991). At the same time, 50 ml of seawater were collected into Greiner tubes at approximately 20 cm distance from one of the sampled corals and later filtered onto 0.2 μm Millipore GTTP filters (Cork, Ireland). Sediment was collected from the upper sediment layer next to sampled corals on three distinct occasions during the fieldwork period. Immediately after each dive, all the samples were flash frozen in liquid nitrogen and kept at − 80°C.
Twelve other conspecific colonies exhibiting either conspicuously aged (n = 6) or clearly new mucus (n = 6) were removed from the reef on 2 consecutive days to collect large quantities of mucus through air exposure, thereafter referred to as 'milking' (Garren and Azam, 2010). Removed corals were of similar size (diameter of approximately 10 cm) and all colonies were 'milked' for 5 min before being brought back to the reef. Released mucus (range: 8-10 ml) was collected into sterile 50 ml Greiner tubes before fixing with formaldehyde (2% final  Figure 1 Diagram depicting the two experimental approaches. (a) Natural dynamics of coral mucus-associated prokaryotes: surface mucus of seven Porites astreoides colonies was regularly sampled in situ over a 2-month period and mucus aging state ('new mucus' versus 'aged mucus') was visually assessed (following Coffroth, 1991). Insert depicts an in situ impression of the SML for the same P. astreoides colony at two different time points: with new mucus (left side) and with a conspicuous and aged mucus sheet (right side). A selection of new (n = 14) and aged mucus (n = 6) samples was later used for 16S ribosomal RNA (rRNA) gene amplicon sequencing. (b) Prokaryotic mucus re-colonization after antibiotics disturbance: mucus of 12 P. astreoides colonies exhibiting new mucus was sampled in situ and whole colonies later removed from the reef and brought to the aquaria system of the CARMABI station. Six colonies were incubated in a mix of antibiotics and the other six colonies were incubated as controls. After 8 days in the aquaria, corals were again sampled and thereafter brought back to the reef and installed on a rack (day 0). Over the next 28 days, the health of the colonies was visually assessed and mucus samples were regularly collected. No visual signs of mucus aging were observed throughout the experiment. The 16S rRNA gene was sequenced for all collected mucus samples (n = 80) to follow microbial community composition during re-colonization of mucus after antibiotics disturbance. concentration) at 4°C for at least 4 h. In all, 1-2 ml of each fixed sample was then passed through an 0.2 μm GTTP filter (Millipore; supported by a 0.45 μm HAWP filter, Millipore). This filter was used to enumerate microbial abundance by epifluorescence microscopy (minimum of 30 fields of view and 300 cells) after 4′,6diamidin-2-phenylindol (DAPI) staining. The microbial abundance associated with mucus is given below per mucus volume (Garren and Azam, 2010).

Natural dynamics
Prokaryotic mucus re-colonization after antibiotics disturbance To assess the impact of antibiotic treatment and subsequent microbial re-colonization on coral health, 12 additional P. astreoides colonies (diameter of approximately 6 cm) with conspicuous new mucus were freshly collected from the reef and transferred to the reef-water flow-through aquaria system of the CARMABI station ( Figure 1b and Supplementary Figure S2). Before removal of the colonies, their SML was sampled by 'swabbing', and used as baseline for comparison with the microbial parameters determined in the subsequent experiments.
After an acclimation period of 7 days, coral colonies were transferred to transparent plastic beakers filled with aquarium seawater (600 ml) that was continuously agitated. Beakers were kept in the flow-through system at stable temperature conditions (26.5°C ± 0.3°C). Six of these colonies were incubated in an antibiotic mix (Supplementary Table S1) added in a dilution of 1:100 to seawater replaced every 12 h for a total incubation period of 8 days.
Corals were 'milked' for a period of 2 min directly after removal from the reef, after the 7 days acclimation phase (t = 0 h), and three times during the incubation (t = 24, 72 and 120 h). Before 'milking', each colony was rinsed with 0.2 μm-filtered aquarium seawater to remove loosely attached prokaryotes from the coral surface. Mucus samples were fixed with formaldehyde (2% final concentration) and processed to monitor prokaryotic abundance in the SML as described for the natural dynamics experiment.
After the aquaria incubation, all colonies, the antibiotic-treated and control colonies, were brought back to the CARMABI Buoy One reef and installed on a rack in an alternating order (Supplementary Figure S2). Colonies were 'swabbed' directly after the re-introduction, at the following 3 consecutive days and then every second to third day for a total period of 28 days. In addition, the health status of each coral was visually monitored for occurrence of bleaching, lesions and mortality over the study period. Coral health was in general categorized in the three following groups: healthy-no visual signs of bleaching or necrosis, bleached-visual observation of bleaching and/or necrosis, dead-480% of tissue loss. Throughout the disturbance experiment (incubation and re-introduction), none of the colonies exhibited visual signs of mucus aging.
DNA extraction, 16S ribosomal RNA gene sequencing and taxonomic annotation DNA was extracted from 120 samples representing a selection of swabbed mucus (Figure 1), seawater and sediment samples using the FastDNA SPIN Kit for Soil (MP Biomedicals, Heidelberg, Germany) according to the manufacturer's instructions.
DNA extracts were sent on dry-ice to the IMGM laboratories GmbH (Martinsried, Germany) for sequencing a 728-bp fragment of the 16S ribosomal RNA (rRNA) gene (see Supplementary Information) using 454 GL FLX+ technology (Roche, Martinsried, Germany). Barcoded 16S rRNA gene PCR amplicons were denoised in Acacia (version 1.52.b0; Bragg et al., 2012) and analyzed using Qiime (version 1.8.0; Caporaso et al., 2010a). Obtained sequences were clustered into OTUs 0.02 (operational taxonomic units) based on ⩾ 98% sequence similarity excluding singletons. Representative OTUs 0.02 were picked and aligned with PyNAST (version 1.2.2, Caporaso et al., 2010b) using the Greengenes database (version 13.5). Taxonomy was assigned using the Ribosomal Database Project Classifier (version 2.2, Wang et al., 2007) with a confidence minimum of 85%. OTU tables, based on the taxonomic hierarchical levels were generated in Qiime. Diversity estimates were calculated using R (R Development Core Team, 2008). To take the different sequencing efforts into account, 801 sequences were randomly picked from each sample as suggested by Qiime and chloroplast OTUs were removed. The rarefied OTU table based on family level and their relative abundances per sample was used for further analyses. Demultiplexed 16S rRNA gene raw reads and respective metadata are available in the NCBI SRA database (http://www.ncbi.nlm.nih.gov/sra/) under accession number SRP069317.

Statistics
The effect of sampling group on prokaryotic abundance as well as on diversity indices (Shannon Weaver Index, richness and evenness) was tested with repeated-measures analysis of variance (rANOVA) and further pairwise comparisons with the Tukey HSD test at 95% confidence level. Data were log transformed if required. Venn diagrams were used to depict numbers of unique, shared and ubiquitous OTUs.
The variation in prokaryotic community composition among different sampling groups (beta-diversity) was visualized by non-metric multidimensional scaling ordination (nMDS; after 10 000 permutations) based on Bray-Curtis dissimilarity matrices. Differences were further tested with analysis of similarity (ANOSIM; 10 000 permutations). Furthermore, the homogeneity of multivariate dispersions was tested using a resemblance-based permutation test (PERM-DISP) before confirming differences in community structuring between sampling groups by applying a permutational multivariate analysis of variance (PERMANOVA) using Bray-Curtis dissimilarity matrices (Anderson et al., 2006).
The explanatory power of factors such as habitat, time (that is, sampling day) and treatment on the observed prokaryotic community assembly was determined by canonical correspondence analysis (CCA) and the significance of factors was further verified using an ANOVA-like permutation test based on 1000 permutations.
OTUs contributing up to a cumulative value of 70% of the total divergence in prokaryotic community assembly among different sampling groups were shown by similarity percentages (SIMPER).
In this study the indicator value analysis (IndVal; De Cáceres and Legendre, 2009) was applied to detect prokaryotic families significantly associated (Po0.05, when both specificity and fidelity have probabilities 40.5) to different sampling habitats: new mucus, aged mucus, seawater and sediment. Specificity is the probability that the specific taxon belongs to the habitat group given the fact that the species has been found, whereas fidelity is the probability of finding the taxon in assemblages belonging to the habitat group. Prokaryotic families identified by IndVal, here assumed to represent prokaryotic indicators of each particular habitat, have the highest probability of occurrence for that particular habitat. IndVal has been used in the past to identify strict habitat specialists of particular coral compartments (Li et al., 2014).
All statistical tests and graphs were compiled in R (R Development Core Team, 2008).

Results
Sequencing and sample overview A total of 639 196 reads were retrieved from the 110 successfully sequenced and further analyzed samples (see Table 1 for details) and clustered into 353 OTUs (based on family level). The required minimum of 801 sequences per sample led to the removal of one mucus and two sediment samples. Observed richness within sampling groups was about two-thirds of the estimates obtained with Chao (Table 1).
Natural dynamics of coral mucus-associated prokaryotes Each P. astreoides colony exhibited an aged mucus sheet on up to two occasions during the 2 months of fieldwork ( Figure 1a). Mucus aging, however, was neither synchronized among different colonies nor related to any of the measured environmental parameters. Aged mucus remained for up to 3 days on the coral's surface before it was released into the surrounding environment. Prokaryotic abundance in the SMLs of P. astreoides colonies ranged from 3.2 ± 0.5 × 10 5 cells ml − 1 in newly produced mucus to 8.1 ± 0.6 × 10 5 cells ml − 1 in aged mucus sheets, representing a twofold increase in cell abundance (ANOVA, Po0.01). Mucus (aged and new), seawater and sediment prokaryotes comprised in total 255 OTUs, of which 32 OTUs were ubiquitously present in all habitats (Supplementary Figure S3). Approximately 18% and 21% of the OTUs associated with aged and new mucus layers, respectively, were unique to that particular SML aging state (Supplementary Table S2 and Supplementary Figure S3). Furthermore, mucus shared about two times more members with the prokaryotic community associated with sediments than with ambient seawater. Alpha diversity, richness and evenness were highest in aged mucus and sediment samples (Table 1), albeit statistically not significant (see Supplementary Table S3).
Prokaryotic mucus re-colonization after antibiotics disturbance Antibiotic-treated colonies exhibited no visible signs of health deterioration during the 8 days of aquaria incubation. Control colonies, in contrast, were negatively affected, as half (n = 3) of them showed bleaching and necrosis during the incubation period ( Figure 1b). Prokaryotic abundance in mucus of the colonies was highly variable, with an average of 3.9 ± 4.5 × 10 5 cells ml À 1 before the experiment (n = 12). After 24 h of incubation with antibiotics (n = 6), prokaryotic abundance was only 5.4 ± 4.6 × 10 4 cells ml − 1 (Figure 3) representing a reduction to 14% of the original in situ abundance (rANOVA, Po0.001; Tukey HSD, Po0.01, see Supplementary Table S7). There was no apparent change in the overall alpha diversity of the coral mucus community (Table 1) concomitant with this reduction. This low abundance remained relatively constant until the end of the incubation period. In contrast, prokaryotic abundance in mucus of control colonies (n = 6) remained relatively high (4.1 ± 1.7 × 10 5 cells ml − 1 at 24 h) throughout the entire incubation period (see Figure 3 and Supplementary Table S7), accompanied with a significant increase in alpha diversity (rANOVA, Po0.001; Tukey HSD, Po0.01; see Supplementary  Table S8-S10) compared with the original in situ alpha diversity.  Figure 2 Natural dynamics of coral mucus-associated prokaryotes: non-metric multidimensional scaling (nMDS) plot of the Bray-Curtisbased dissimilarity matrix of prokaryotic communities colonizing the mucus of Porites astreoides and the adjacent reef environment (sediment and ambient water). Mucus samples are divided into 'new mucus' (samples that were collected up to 2 weeks before and after an aging event) and into 'aged mucus'. Arrow indicates shift in the centroid of the mucus community before aging, in aged mucus and after aged mucus was released. Each code depicted in the figure corresponds to an individual colony (1-6) throughout the experiment in a chronological order (a-d).
Once coral colonies were brought back to the reef they exhibited health response patterns opposite to those observed in the aquaria incubation (Figure 1b). Within the first 3 days, all antibiotic-treated colonies (n = 6) showed rapid health deterioration and exhibited clear signs of bleaching, with only two surviving the following weeks. Non-treated corals, in contrast, recovered from aquarium incubations within 28 days of re-introduction to the natural reef environment (Figure 1b).
In total, 39% of the prokaryotic OTUs originally associated with mucus were present throughout the antibiotic treatment, as well as after re-introduction of treated corals into their natural habitat (Supplementary Figure S7a). Here, the families Endozoicimonaceae and Oxalobacteraceae were numerically dominant (Supplementary Figure S8). The control group, however, harbored 58% of the initial number of OTUs until the end of the incubation experiment (Supplementary Figure S7b). Furthermore, the prokaryotic community present in mucus of the control colonies (see Table 1) exhibited a significant increase in alpha diversity once transferred back to the reef (rANOVA, Po0.001; Tukey HSD, Po0.01 see Supplementary Table S8-S10). Re-introduced antibiotic-treated colonies, in contrast, were not significantly different in their alpha diversity from the original in situ alpha diversity (Tukey HSD, P40.5, see Supplementary  Table S8-S10).
Prokaryotic succession in coral mucus, as visualized by nMDS ordination (Figure 4 and Supplementary Figure S9), revealed contrasting successional paths for antibiotic-treated and nontreated corals (ANOSIM, R = 0.5082, Po0.001). Initially, during the aquarium incubation, both groups diverged from the natural community typical of new mucus layers on healthy corals. After being deployed back on the reef, antibiotic-treated corals exhibited a major change in their community assembly within the first 24 h becoming more similar to that found in sediments and in aged mucus layers. Within the next days, their community became similar to the one of aged mucus layers and of unhealthy-looking colonies such as the control group during the aquaria incubation. This shift in the prokaryotic community happened concomitantly with an increase in bleaching and mortality. After 28 days, the only two surviving colonies harbored a community similar to that in new mucus. The control group, however, after suffering of necrosis and bleaching during aquarium incubation, rapidly regained a prokaryotic community similar to the original one and concurrently exhibited again a healthy appearance (Figure 4).
Differences in the successional path of antibiotic-treated and control corals throughout the monitoring period were revealed by multivariate community composition analysis (PERMDISP, P40.05, Supplementary Table S11, PERMANOVA, Po0.01, Supplementary Table S12). Moreover, CCA (Supplementary Figure S10) attributed 67% of the variation in the prokaryotic community structure to differences in treatment (antibiotics versus control) and time (ANOVA-like permutation test, Po0.001 and Po0.01, respectively), whereas the colony effect was negligible (P40.05).
Out of the prokaryotic families responsible for the divergence among treatment groups (SIMPER, Supplementary Table S13), Endozoicimonaceae was dominant in mucus (relative abundance up to 80%) of corals in their natural environment (Supplementary Figure S8). However, it decreased in relative abundance once corals suffered from bleaching and necrosis when kept in the aquaria but also in the reef. Within 24 h after re-introduction to the reef, the mucus of antibiotic-treated corals became dominated by Verrucomicrobiaceae (35.9% ± 20.2%) and Vibrionaceae (13.5% ± 14.7%). Within the next days, Rhodobacteraceae, Oceanospirillaceae, Vibrionaceae, Flammeovirgaceae, Verrucomicrobiaceae and Colwelliaceae dominated the mucus of antibiotic-treated colonies. Mucus of the control group became evenly colonized by various prokaryotic families such as Verrucomicrobiaceae, Vibrionaceae, Rhodobacteraceae, Alteromonadaceae, Colwelliaceae, Pelagibacteraceae and Synechococceae (Supplementary Figure S8). Archaea did not contribute to significant community variation and  Figure 3 Prokaryotic cell abundance in coral mucus of Porites astreoides throughout the aquaria incubation for antibiotic-treated and non-treated control colonies. Samples were collected directly after corals were removed from the reef (reef), after 8 days acclimatization to the aquaria environment (0 h) and 24, 72 and 120 h after the beginning of incubation with antibiotics. Antibiotic treatment resulted in a significant decrease (Tukey HSD; **Po0.01) in prokaryotic abundance relative to in situ values (reef). Error bars indicate ± s.d.
showed very low relative abundance in mucus throughout the disturbance experiment (overall 1.25% ± 4.28%) with the exception of two samples collected at the end of the antibiotic treatment (34.33% and 17.48%, respectively; Supplementary Figure S11).

Prokaryotic indicators associated with the coral mucus microbiome
Identified prokaryotic indicators were distinct among the three habitats but individual members not strictly confined to the respective habitat ( Figure 5 and Supplementary Table S14). Oxalobacteraceae and Endozoicimonaceae were identified as prokaryotic indicators associated with new mucus of P. astreoides. Together they accounted for 50% of all prokaryotes found in new coral mucus in situ. Similarly high contributions to the mucus microbiome were observed in the population of corals used for the disturbance experiment (before collection), as well as after treatment with antibiotics and, to a minor extent, within colonies surviving the disturbance experiment after 28 days. Indicators for new mucus, however, showed a reduction in their relative abundance in aged mucus, whose typical indicators consisted of Verrucomicrobiaceae, Vibrionaceae, Flammeovirgaceae, Rhodobacteraceae and Alteromonadales. Furthermore, mucus of disturbed corals showed increased relative abundances of aged mucus indicators, particularly dominant in antibiotic-treated colonies after re-introduction to the reef environment. Prokaryotic indicators identified for seawater and sediment did not exhibit major variations in dominance throughout the experiment, with the exception of a high contribution of typical seawater OTUs to the microbiome of control colonies at the end of the experiment.

Discussion
Natural dynamics of coral mucus-associated prokaryotes Although the cyclic aging and shedding of the SML in colonies of Porites sp. is fairly well documented (see Coffroth, 1991 and Supplementary Information), the associated dynamics of its mucus-dwelling prokaryotic community remained to be resolved. We demonstrate that the prokaryotic community undergoes significant changes throughout the mucus aging cycle, both in terms of cell abundance and community composition. Generally, the SML of P. astreoides was dominated by the bacterial families Oxalobacteraceae and Endozoicimonaceae, the latter of which has commonly been found in healthy corals (Apprill et al., 2013;Lema et al., 2014; Figure 4 Prokaryotic mucus re-colonization after antibiotics disturbance: non-metric multidimensional scaling (nMDS) plot of the Bray-Curtis-based dissimilarity matrix of prokaryotic communities colonizing the mucus of Porites astreoides and their shifts after a disturbance event. The successional path, here represented by arrows, was reconstructed based on the position of group centroids and follows each group of corals (antibiotic-treated, a-f; control, g-l) at a particular time (indicated by color gradient). The starting point 'in situ -initial community composition' represents the original in situ state, followed by the shift in the community composition in the aquaria incubation (dashed arrows) and finally describing the successional path over 28 days observed in the field after the two experimental groups of corals were brought back to the reef (normal arrows). Prokaryotic community structure of individual colonies is only given for mucus samples collected before the experiment started (in situ_a-l) and on the last day of the experiment (d28_a-l). Polygons indicate the relative position of prokaryotic communities associated with different mucus aging stages ('new mucus' versus 'aged mucus') characterized during the natural dynamics experiment and are shown as reference. Individual sample points throughout the whole experiment are given in detail in Supplementary Figure S9. Meyer et al., 2014) and suggested to have coevolved with specific host species (Bayer et al., 2013).
In contrast, aged mucus sheets exhibited a high relative abundance of Verrucomicrobiaceae, Flammeovirgaceae, Rhodobacteraceae and Vibrionaceae (see Figure 5 and Supplementary Figure S5). The latter two bacterial families include coral pathogens and are commonly associated with coral diseases (Ben-Haim et al., 2003;Sunagawa et al., 2010). After the detachment of the aged mucus sheet, however, the microbial community reverted to its original composition within 3-5 days (see Figure 2), supporting the idea that periodical mucus shedding in poritid corals generates a natural, rather deterministic fluctuation of the mucus-dwelling prokaryotic community, taking place within a temporal scale of weeks. As the prokaryotic indicator assemblages associated with aged mucus sheets showed surprisingly high similarity to the community associated with mucus of disturbed coral colonies (Figures 4  and 5), some of which died off, we propose that periodic mucus shedding (Coffroth, 1991) is an important mechanism supporting coral health by periodically removing undesirable prokaryotes from the surface of the colony leading to the maintenance of a beneficial mucus microbiome.
Once coral mucus is detached from the colony, it functions as particle trap before sinking to the seafloor, where it acts as energy and nutrient source for benthic organisms in coral reefs (Wild et al., 2004;Naumann et al., 2009). Alongside, aged mucus sheets frequently harbor sediment particles (Figure 1a), suggesting that prokaryotes colonizing upper sediment layers in coral reefs could 'hitch a ride' to the nutrient-rich mucus layer via sediment resuspension. Thus, sediments may serve as a 'seed-bank' for coral mucus-associated microbes as proposed by Carlos et al. (2013). Both, the resuspension of sediment particles (and its associated microbes) onto the coral's surface and the rapid sedimentation of detached coral mucus would lead to a high connectivity between the microbial communities of aged mucus and coral reef sediments, and consequently, may explain the similarity in their prokaryotic community composition ( Figure 5). In contrast, microbial communities of the ambient seawater exhibited only minor overlap with those found in mucus. This confirms earlier findings (Rohwer et al., 2001;Frias-Lopez et al., 2002) and stresses the importance of the SML as a selective medium for the microbial pool in the adjacent seawater.
Prokaryotic mucus re-colonization after antibiotics disturbance Antibiotic treatment led to a significant reduction of prokaryotic abundance in the SML and concurrent changes in community composition. Although the  Figure 5 Prokaryotic indicator assemblages identified for the microbiome of SML of Porites astreoides ('new mucus' versus 'aged mucus'), the adjacent seawater and the sediment, and their abundance distribution throughout the natural dynamics and the disturbance experiment. Pie charts represent the relative abundance of indicator prokaryotic families (given on the left) that are significantly associated with a particular microbiome as revealed by the indicator value analysis (IndVal). Numbers around pie charts depict, for each habitat studied, the proportion of the total community represented by the indicator assemblages. The balloon plot on the right displays the relative abundance of the identified indicator assemblages in the various natural habitats and throughout the disturbance experiment. Note that prokaryotic indicator assemblages identified for a particular habitat are not restricted to that habitat and are also present (in lower abundance) in other habitats. full extent of the influence of antibiotics on the holobiont's fitness remains elusive, no visual cues of a negative impact on coral health were noted. This confirms previous reports of minimal effect of antibiotic treatment on zooxanthellae photosynthetic efficiency and host tissue protein content (Gilbert et al., 2012). These findings suggest that coral hosts are not strictly dependent on their mucus-associated prokaryotic symbionts, at least for such short periods of up to 8 days and in the absence (or deactivation) of pathogens.
Control colonies kept in the aquaria without the addition of antibiotics exhibited obvious signs of bleaching and necrosis and underwent a significant shift in their mucus prokaryotic community (Figure 4). The bacterial family Endozoicimonaceae, which showed the highest relative abundances in newly produced SMLs and is associated with mucus of healthy P. astreoides colonies (Meyer et al., 2014), showed a significant decrease in its relative abundance within the control group. Concomitant with this decrease, many bacterial groups such as Rhodobacteraceae, Verrucomicrobiaceae, Colwelliaceae, Oceanospirillaceae and Flavobacteriaceae increased in their (relative and absolute) abundance (see Figure 3 and Supplementary Figure S8). These findings are consistent with a previous study attributing the expression of lesions in P. astreoides colonies to the loss of Endozoicimonaceae and the proliferation of an opportunistic bacterial community (Meyer et al., 2014). Compositional shifts in the microbial community associated with the SML have been observed under stressful environmental conditions (Thurber et al., 2008). Based on these findings, the observed health deterioration of the untreated control group may have been caused by aquaria conditions leading to a destabilization of the natural mucus community. This interpretation is in agreement with the hypothesis that disturbances in the dynamic equilibrium of the coral's native microbiota may result in health deterioration (Lesser et al., 2007).
Both, antibiotic-treated and control colonies, once brought back to their natural habitat, exhibited rapid changes in their mucus-associated prokaryotic community (Figure 4 and Supplementary Figure S8). For the microbe-depleted (treated) colonies, the increase in Vibrionaceae was dominated by Vibrio sp., a genus harboring well-known coral pathogens such as Vibrio shilonii (Kushmaro et al., 1997) and Vibrio corallilyticus (Ben-Haim et al., 2003;Garren et al., 2014). The latter is reported to use coralproduced sulfur compounds as a cue to target stressed corals (Garren et al., 2014). Curiously, a recent study has shown that P. astreoides (among other coral species) produces copious amounts of the organic sulfur compound dimethylsulfoniopropionate, particularly upon stress (Frade et al., 2015). Furthermore, Verrucomicrobiaceae, Flammeovirgaceae and Rhodobacteraceae, other families associated with necrotic and diseased P. astreoides colonies, have been found to be overrepresented in poritid corals suffering from White Band Disease (Séré et al., 2013;Roder et al., 2014). Although non-treated colonies slowly recovered from tissue lesions and regained a mucus community very similar to their original community, antibiotic-treated colonies suffered from mortality (from day 3 onward) and exhibited increased relative abundances of bacterial families described as early colonizers of marine biofilms, such as Rhodobacteraceae and Oceanospirillacae (O'Toole et al., 2000;Sweet et al., 2011b). Although we cannot exclude other synergistic effects on the host's health, these results suggest that microbe-depleted SML provides an open niche, which gets rapidly colonized by opportunistic bacteria. Thus, we hypothesize that the re-establishment of both coral health and the native prokaryotic community after disturbance of the P. astreoides holobiont depends on the initial degree of disruption of the microbiome. Total recovery of control colonies under in situ environmental conditions in contrast to mortality of microbe-depleted colonies suggests that, upon disturbance, the remnant prokaryotic community in the mucus/tissue may act as 'seed-bank'.
The mucus microbiome and its influence on coral health and survival Host-associated bacteria form unique microbiomes highly adapted to a particular host niche (Ainsworth et al., 2015). Although being generally considered to comprise commensals, microbiomes can fulfill important biological needs of their hosts, for example, immune development or nutrient acquisition (Round and Mazmanian, 2009;Shin et al., 2011). We identified Endozoicimonaceae and Oxalobacteraceae as significant indicators for the mucus microbiome of healthy P. astreoides colonies ( Figure 5). The reduction in the relative abundance of these microbiome members observed before coral necrosis and bleaching suggests that the loss of beneficial bacteria can result in a serious health threat for the holobiont, often associated with an increase in opportunistic and potentially pathogenic bacteria (Meyer et al., 2014). Although our study does not aim at determining the metabolic function of particular microbiome members, it reveals that an intact mucus microbiome may function as a barrier against potentially harmful bacteria. This defense barrier could be based on commensal-like prokaryotes, which prevent harmful colonization by successfully outcompeting pathogens (Reid et al., 2001) and/or depend on stimulating host immune response via the recognition of commensal-derived signals such as microbial-associated molecular patterns (Mackey and McFall, 2006). Our results suggest that the mucus microbiome acts as defense barrier against pathogenic microbes, therefore facilitating homeostasis and contributing to the survival of the coral holobiont.
In summary, we demonstrate that the previously documented periodical mucus aging and shedding cycle in P. astreoides is provoking predictable shifts in the mucus microbiome, leading to changes between a beneficial community and a potentially opportunistic/pathogenic one. The periodical release of mucus seems to be part of a life strategy that supports the maintenance of a beneficial mucus microbiome and the resilience of coral health in shallow water habitats characterized by frequent sediment resuspension. However, severe disruption of the natural microbial community upon external stress could negatively and irreversibly affect the fate of the coral holobiont. Further investigations on the functional capacities of the mucus prokaryotic community are warranted to better understand the role of the mucus microbiome in the dynamic equilibrium of the coral holobiont. Finally, we have shown that specific bacterial members can be used as indicators of coral microbiome disruption, paving the way to the development of early diagnostic tools to monitor the health status of corals.


extfieldsofstudy: Biology Medicine

text:
c-Myc deregulation induces mRNA capping enzyme dependency

c-Myc is a potent driver of many human cancers. Since strategies for directly targeting c-Myc protein have had limited success, upstream regulators and downstream effectors of c-Myc are being investigated as alternatives for therapeutic intervention. c-Myc regulates transcription and formation of the mRNA cap, which is important for transcript maturation and translation. However, the direct mechanism by which c-Myc upregulates mRNA capping is unclear. mRNA cap formation initiates with the linkage of inverted guanosine via a triphosphate bridge to the first transcribed nucleotide, catalysed by mRNA capping enzyme (CE/RNGTT). Here we report that c-Myc increases the recruitment of catalytically active CE to RNA polymerase II and to its target genes. c-Myc-induced target gene expression, cell proliferation and cell transformation is highly dependent on CE, but only when c-Myc is deregulated. Cells retaining normal control of c-Myc expression are insensitive to repression of CE. c-Myc expression is also dependent on CE. Therefore, inhibiting CE provides an attractive route for selective therapeutic targeting of cancer cells which have acquired deregulated c-Myc.

INTRODUCTION
c-myc is an essential gene required for cell growth and proliferation [1,2]. In response to growth factor signalling c-Myc is upregulated and promotes the expression of genes which drive cell proliferation. Under homeostatic conditions the c-myc gene is tightly regulated. However, c-myc is deregulated in over half of human cancers, which directly contributes to oncogenic transformation [3,4].
c-Myc is a basic helix-loop-helix leucine zipper (bHLH-LZ) transcription factor which forms a heterodimer with Max, another bHLH-LZ protein.
In this complex, c-Myc binds to E-box sequences proximal to transcription initiation sites and regulates the transcription of target genes [5,6]. c-Myc increases transcription by recruiting histone acetyltransferases and RNA polymerase II (RNA pol II) kinases [7][8][9][10][11]. In addition, a subset of genes is suppressed by c-Myc using various mechanisms, including displacement or inhibition of other transcriptional regulators, recruitment of histone deacetylases and activation of Ezh2 methyltransferase [2,12,13].
Global analyses revealed that c-Myc regulates transcription of 10-15% of all genes [2,14,15]. The genes regulated by c-Myc vary between cell types with the exception of a core signature of genes which promote cell growth, including those involved in ribosomal biogenesis, nucleolar function and RNA processing [16,17]. c-Myc also directly promotes RNA polymerase I and III-dependent transcription [18]. When expressed at oncogenic levels, c-Myc binding specificity becomes less stringent and it regulates all actively transcribed genes, although less so than its canonical targets [19,20]. The model emerges that c-Myc deregulation directly regulates a subset of genes and causes amplification of general transcription and translation, ultimately increasing the propensity of cells to undergo oncogenic transformation [16,19,21].
c-Myc-dependent RNA pol II phosphorylation has the potential to regulate recruitment of factors important for transcription and mRNA processing to its targets genes [7,8,[22][23][24][25]. Factors that promote transcription initiation, elongation, mRNA capping, splicing and transcription termination are recruited to the phosphorylated C-terminal domain of RNA pol II. c-Myc regulates formation of the Research Paper mRNA cap on its target transcripts, which contributes to c-Myc-dependent gene expression and cell proliferation [8,26,27]. The mRNA cap is 7-methylguanosine linked to the first transcribed nucleotide, a structure which protects transcripts from degradation, promotes splicing and 3' end processing, facilitates nuclear export of mRNA, and aids loading of mRNAs onto ribosomes for translation [28].
The direct mechanism by which c-Myc promotes mRNA capping is unclear. The enzyme which initiates cap formation, mRNA capping enzyme (CE/RNGTT), specifically binds to the RNA pol II CTD when phosphorylated on Ser-5, spatially and temporally localising the enzyme to act on nascent transcripts [29][30][31][32][33][34]. CE has triphosphatase and guanylyltransferase activites which act sequentially to add the guanosine cap structure to transcripts. CE triphosphatase cleaves the terminal phosphate from the first transcribed nucleotide and CE guanylyltransferase transfers guanosine mono-phosphate (GMP) to the transcript 5' end, creating the guanosinecapped structure. Ser-5 phosphorylated RNA pol II CTD also activates CE guanylyltransferase activity in vitro [35]. The final step in basic cap formation is catalysed by RNA guanine-7 methyltransferase (RNMT), which methylates the guanosine moiety at the N7 position. RNMT is also recruited to transcription initiation sites, probably via the phosphorylated RNA pol II CTD, since recruitment is diminished by CTD kinase inhibitors [30,36]. Although CE and RNMT are recruited to phosphorylated RNA pol II, to date, their recruitment has not been demonstrated to be c-Myc-dependent. c-Myc-dependent cap methylation requires upregulation of the c-Myc target gene S-adenosyl homocysteine hydrolase, (SAHH) [27]. SAHH hydrolyses the inhibitory by-product of methylation reactions, SAH, thus enhancing mRNA cap methylation. However, increased expression of SAHH alone is not able to elevate mRNA cap formation and therefore c-Myc-dependent SAHH upregulation permits rather than promotes cap formation.
We investigated the relationship between c-Myc and CE. We found that c-Myc increases the recruitment of CE to RNA pol II and to proximal promoter regions. Deregulated c-Myc is highly dependent on CE to drive gene expression and cell proliferation, whereas endogenous c-Myc is not. We also report that the expression of deregulated and endogenous c-Myc is dependent on CE.

c-Myc deregulation increases the interaction of RNA pol II with CE
To investigate the relationship between c-Myc and mRNA capping, we determined the impact of c-myc deregulation on the proteins with which capping enzyme (CE) interacts. This analysis was performed in human immortalised mammary epithelial cells (IMECs), which are non-transformed and exhibit many normal growth controls [37]. Deregulation of c-Myc transforms IMECs, resulting in elevated proliferation rate and anchorageindependent growth [38]. Retroviral infection was used to create IMEC lines which express elevated levels of c-Myc or vector control, designated IMEC/c-Myc or IMEC/vec, respectively. A second round of infection resulted in stable expression of CE-GFP (C-terminal GFP fusion) or the empty vector control (INI). Equivalent levels of CE-GFP were expressed in IMEC/c-Myc and IMEC/vec and CE-GFP expression did not alter c-Myc expression ( Figure 1A). CE-GFP complexes were immunoprecipitated from IMEC lines via the GFP tag and resolved by SDS-PAGE. Mass spectrometry was used to identify CE-GFP-interacting proteins, which included RNA polymerase II large subunit (RNA pol II), a previously observed CE-interacting protein ( Figure 1B) [31,33,39]. Increased c-Myc expression resulted in more RNA pol II being purified with CE-GFP ( Figure 1B). To confirm this observation, endogenous CE complexes were immunoprecipitated from IMEC/c-Myc and IMEC/vec ( Figure 1C and 1D). As observed previously, deregulation of c-Myc resulted in increased RNA pol II C-terminal domain (CTD) Ser-5 phosphorylation [8]. Deregulated c-Myc expression resulted in increased interaction of CE with phospho-Ser 5 RNA pol II, observed using phosphospecific and pan RNA pol II antibodies. Previous studies reported that Spt5, a mediator of RNA pol II elongation, binds to RNA pol II and CE [40][41][42]. Elevated c-Myc expression also increased the interaction of CE with Spt5, which may be direct or via RNA pol II.
Since c-Myc increases RNA pol II Ser-5 phosphorylation, which recruits CE and activates the guanylyltransferase, we investigated whether c-Myc increases CE activity [29,35]. CE hydrolyses GTP to produce the GMP donor for the cap guanylylation reaction. Formation of the CE-GMP intermediate is used as an approximation of guanylyltransferase activity ( Figure  1E) [35]. CE was immunoprecipitated from IMEC/c-Myc or IMEC/vec nuclear extracts and [α-32 P]GTP supplied as the substrate, resulting in formation of a CE-[ 32 P] GMP intermediate which was resolved by SDS-PAGE and quantified by phosphorimager ( Figure 1F and 1G). Elevated c-Myc expression did not detectably alter total nuclear CE-GMP. However, only a fraction of CE is RNA pol II-bound and since it is this which catalyses capping, RNA pol II-associated guanylyltransferase activity was analysed. RNA pol II was immunoprecipitated from IMEC/c-Myc and IMEC/vec extracts and co-purifying CE-GMP complexes detected ( Figure 1H). Elevated expression of c-Myc caused an increase in CE-GMP associated with RNA pol II, indicating that the CE recruited is active. In summary, c-Myc increases the

c-Myc promotes CE recruitment to c-Myc target genes
Since c-Myc increases the interaction of RNA pol II and CE, we investigated whether increasing c-Myc expression increases CE recruitment to target genes. CE recruitment was investigated in IMECs using chromatin immunoprecipitation (ChIP), however CE binding was below the limit of detection. As an alternative CE recruitment to c-Myc target genes was investigated in HeLa cells, which express high levels of deregulated c-Myc. In order to identify c-Myc target genes, Hela cells were transfected with c-Myc siRNA, which resulted in a decrease in c-Myc and phospho-Ser-5 RNA pol II ( Figure 2A). A selection of target genes was analysed by RT-qPCR to identify the most c-Myc-responsive ( Figure  2B). Nucleolin (NCL), fibrillarin (FBL) and nucleoside diphosphate kinase A (NME1) transcripts were the most significantly reduced in response to c-Myc suppression and thus the recruitment of CE to these genes was analysed by ChIP. CE binding to regions surrounding the transcription start site (TSS) and c-Myc-binding sites was analysed by qPCR ( Figure 2C). Binding of CE to GAPDH TSS was also analysed. CE was found at the TSS of c-Myc target genes and proximally upstream. c-Myc depletion resulted in a decrease in CE binding to NCL, FBL, NME1 and GAPDH. Distal regions of NCL and NME1 served as a negative control for the ChIP. CE recruitment to these distal sites was low (~2-fold over background) and not c-Myc-responsive.

c-Myc expression is dependent on CE
Since c-Myc regulates the recruitment of CE to its target genes, we investigated the dependency of their expression on CE. IMEC/c-Myc and IMEC/vec were transfected with CE siRNA resulting in CE transcripts and protein being depleted ( Figures 3A and 3B). CE depletion resulted in a substantial reduction in the expression of  Figures 3B and C), which was rescued by expressing siRNA-resistant CE-GFP ( Figure 3D). Reduced c-Myc expression was also observed in HeLa cells in response to transfection of two independent CE siRNAs ( Figure 3E). Depletion of CE caused a reduction in endogenous c-Myc transcript levels in IMEC/vec and HeLa cells, and a reduction in exogenous c-Myc (FLAG-  Figure 3F). This suggests that reducing capping impacts the transcription or stability of c-Myc transcripts. Since exogenous c-Myc in IMECs is expressed without its endogenous promoter and untranslated regions, mechanisms involving the coding region determinant of c-Myc transcript stability may render it sensitive to degradation upon CE depletion [43,44].

Deregulation of c-Myc increases target gene dependency on CE
The dependency of c-Myc target gene expression on CE was investigated using CE siRNA. Repressing CE expression will inhibit CE as a mediator of c-Myc function and as a controller of c-Myc expression, and have additional effects on gene expression. IMEC/c-Myc and IMEC/vec were transfected with CE siRNA and c-Myc target genes expression analysed by RT-qPCR ( Figure 4A). NCL, ODC, FBL, NME1, NPM, FBL and TIP49 were verified as c-Myc-induced genes in IMECs. For these verified c-Myc target genes, the increase in expression induced by deregulated c-Myc was abolished by CE depletion. However, c-Myc target genes were unaffected by CE depletion in IMEC/vec, which only express endogenous c-myc. This was surprising given that endogenous c-Myc expression is impaired by CE knockdown and multiple independent experiments showed that CE levels are equivalently depleted in IMEC/vec and IMEC/c-Myc ( Figure 3B and 3C). Expression of siRNAresistant CE-GFP rescued the defect in c-Myc target gene expression in IMEC/c-Myc observed in response to CE suppression ( Figure 4B, three representative genes, and Figure 4C, average result for 6 genes). GAPDH exhibited similar responses to CE suppression as the canonical c-Myc targets, suggesting that the interplay of CE and c-Myc influences genes on a global scale, albeit to a lesser extent with non-canonical targets ( Figure 4A). UBF (upstream binding factor), a previously described c-Myc target gene, was unresponsive to c-Myc and CE knockdown in IMECs, indicating that c-Myc and CE dependency has a degree of specificity ( Figure 4A). CCND1 (cyclin D1) is a c-Myc-repressed gene in IMECs [45,46]. CCND1 transcript levels slightly increased when CE was depleted in IMEC/vec, correlating with reduced  Figure 4A). However, when CCND1 was repressed by elevated c-Myc expression, it was unresponsive to CE depletion, suggesting that sufficient c-Myc remains to maintain CCND1 repression. Western blots were performed to determine if CE depletion affected the protein level of c-Myc targets in IMECs ( Figure 4D and 4E). Consistent with transcript levels, nucleolin protein expression was impaired by CE siRNA in IMEC/c-Myc, but not in IMEC/vec.
We investigated why target gene expression was unaffected when endogenous c-Myc levels were reduced in response to CE depletion. It was possible that the c-Myc target genes analysed are only induced by deregulated and not endogenous c-Myc in IMECs. To investigate this, IMECs were transfected with c-Myc siRNA and knockdown of endogenous c-Myc confirmed ( Figure 5A). RNA pol II Ser-5 phosphorylation decreased in response to c-Myc suppression, indicating that endogenous c-Myc is functional in IMECs. NCL, ODC and TIP49 transcripts were insensitive to this level of endogenous c-Myc knockdown, whereas NME1, NPM and FBL transcript levels were sensitive ( Figure 5B). c-Myc siRNA caused a greater decrease in c-Myc than CE siRNA ( Figure  5C). Therefore in IMEC/vec, NME1, NPM and FBL are target genes of endogenous c-Myc, but are resistant to the intermediate level of c-Myc depletion observed upon CE knockdown.

Suppression of deregulated c-Myc reduces target gene dependency on CE
We investigated if c-Myc target gene expression is dependent on CE in HeLa cells, which have deregulated transcriptional activation of the c-myc gene due to viral insertion [47]. Cells were transfected with combinations of c-Myc and CE siRNAs or non-targeting controls, which resulted in efficient knockdown of both proteins ( Figure 6A). c-Myc depletion was detected 24 hours after c-Myc-siRNA transfection whereas CE depletion was not detectable until 48 hours after CE siRNA transfection (data not shown). Therefore, in this experimental arrangement CE is depleted following changes in c-Myc protein level. As in IMECs, c-Myc expression was dependent on CE regardless of c-Myc levels, although this was more apparent in when c-Myc was repressed by transfection of c-Myc siRNA ( Figure 6A and 6B). CE depletion in HeLa cells resulted in significant repression of c-Myc target genes ( Figure 6C). When c-Myc was repressed, CE depletion resulted in reduced expression of some c-Myc target genes, but to a lesser extent than that in HeLa control cells which carry deregulated c-Myc ( Figure 6C, specific genes; Figure 6D, average result for five genes). This indicates that deregulated c-Myc in HeLa cells causes enhanced dependency of c-Myc target genes on CE. As in IMECs, the c-Myc-repressed gene CCND1 was unaffected by CE depletion in cells expressing high levels of c-Myc.
We questioned whether CE knockdown only influences c-Myc target gene expression by regulating c-Myc. Transfection of CE siRNA in HeLa cells caused, on average, a ~20% reduction in c-Myc expression whereas c-Myc siRNA caused a 70% reduction ( Figure  6E). However, transfection of CE siRNA depletes c-Myc target gene expression to the same extent as transfection of c-Myc siRNA ( Figure 6F, average decrease in expression of five genes). This suggests that CE does not control c-Myc target genes simply by regulating c-Myc expression; its role as a mediator of c-Myc function is also important. In addition, we note that other genes are likely to be sensitive to CE depletion which may also impact on c-Myc target genes.

c-Myc-driven cell proliferation and transformation is dependent on CE
In epithelial cells, deregulated c-Myc increases cell proliferation and induces anchorage-independent cell growth, characteristics of many epithelial cancer cells. Since deregulation of c-Myc increases target gene dependency on CE, we investigated whether cell proliferation and anchorage-independent growth is also CE-dependent. Consistent with previous studies, deregulated c-Myc in IMECs increased cell proliferation ( Figure 7A and 7B) [38]. IMEC/c-Myc and IMEC/vec were transfected with CE siRNA and cells counted after 72 hours. IMEC/vec proliferation was unaffected by CE depletion, however, IMEC/c-Myc cell number was significantly reduced.
To determine whether CE depletion influences c-Myc-driven cell transformation, we performed anchorage-independent cell growth assays. The IMEC culture medium is serum-free, however anchorageindependent growth assays require a supplement of fetal bovine serum (FBS) [45,48]. c-Myc increases the proliferation of IMECs to a similar extent in the presence or absence of FBS ( Figure 7A and 7B). c-Myc expression was not altered by culturing cells in FBS ( Figure 7C). In a previous study, CE depletion induced apoptosis in HeLa cells [49]. CE siRNA did not induce PARP cleavage in IMECs or morphological signs of apoptosis ( Figure 7C, data not shown). The p21 and p27 tumour suppressor genes are c-Myc-repressed genes which negatively regulate the G1-S transition in the cell cycle [50]. p21 and p27 were elevated by CE depletion in IMEC/c-Myc but not IMEC/vec ( Figure 7D). This indicates that CE knockdown restrains c-Myc-driven cell cycle transit in IMECs.
IMEC/c-Myc and IMEC/vec were transfected with CE siRNA prior to the soft agar transformation assays which measure anchorage-independent cell proliferation. Deregulated c-Myc expression resulted in 45% IMECs www.impactjournals.com/oncotarget plated growing in anchorage-independent colonies ( Figure 8A) [45,51]. CE depletion significantly reduced anchorage-independent colonies, including reducing the proportion of colonies over 50µm in diameter by 60% ( Figure 8B and 8C). Therefore, CE is important for the incidence of c-Myc-dependent transformation and for subsequent colony growth.

DISCUSSION
c-Myc is a potent oncogene and one of the most frequently deregulated in human cancers. The majority of selective cancer therapies function by targeting the active site of key enzymes with small molecule inhibitors. However, c-Myc has been a challenging target since it lacks an active site and as a result there has been sustained interest in its mode of action, particularly in its enzymatic co-factors. In this study we investigated the relationship between c-Myc and the mRNA capping enzyme CE/ RNGTT, which initiates mRNA cap formation by adding an inverted guanosine group to nascent transcripts. The mRNA cap protects the transcript from degradation during transcription and recruits processing and translation factors. We determined that deregulated c-Myc increases the interaction of CE and RNA pol II, increases CE recruitment to c-Myc target genes and increases the CE guanylyltransferase activity associated with RNA pol II. Furthermore, we observed that CE is important for c-Myc expression. Deregulation of c-myc co-ordinately promotes many major metabolic pathways in the cell resulting in enhanced cell proliferation and proliferation becoming somewhat independent of growth controls. In IMECs and HeLas, cell proliferation and transformation driven by deregulated c-Myc were found to be CE-dependent.
Cells carrying deregulated c-Myc were significantly more dependent on CE for gene expression, cell proliferation and cell transformation than cells with low c-Myc expression. IMECs which express low endogenous c-Myc levels or HeLa cells in which c-Myc expression was supressed by siRNA were largely unaffected by transfection of CE siRNA. This was somewhat surprising given that endogenous and deregulated c-Myc expression is dependent on CE. Deregulated c-Myc results in a substantial increase in global transcription which may result in increased dependency on CE to maintain transcript processing. Several previous studies in cancer cells have shown that c-Myc expression thresholds govern distinct cellular responses [52][53][54]. The molecular mechanisms governing these c-Myc thresholds are likely to involve the availability of transcriptional co-factors and repressors.
Since the discovery that c-Myc regulates mRNA capping, studies have focussed on the involvement of RNMT, the N-7 guanosine cap methyltransferase, which completes the basic functional cap structure [8,55]. Mechanisms involving RNMT recruitment and methionine metabolism contribute to c-Myc-dependent cap methylation [8,27]. Inhibition of RNMT function by blocking biproduct removal selectively targets cells carrying deregulated c-Myc. The discovery that c-Myc regulates recruitment of CE reveals that c-Myc is coordinating all the basic mechanisms of mRNA cap formation. Inhibition of both guanosine cap addition and guanosine cap methylation selectively target cells with deregulated c-Myc, indicating that both steps in cap formation are critical for c-Myc function [8,27].
Transcription and translation are considered attractive therapeutic avenues for targeting c-Mycdriven cancers, since c-Myc deregulation increases global transcript and protein production [23, 25, 56-

59
]. Recent studies reported that many cancer cell lines are sensitive to Cdk7 inhibitors, which reduce RNA pol II Ser-5 phosphorylation [60,61]. The CDK7 inhibitor THZ1 is highly effective in targeting models of c-Mycdriven small cell lung carcinoma, neuroblastoma and triple-negative breast cancer [62][63][64]. Among its functions, THZ1 abolishes co-transcriptional mRNA capping, which may contribute to its efficacy [65]. Other components of the gene expression machinery are being investigated as therapeutic targets in c-Myc-driven cancers, including the splicing machinery and cap binding proteins. Components of the splicing machinery are direct targets of c-Myc and are essential in c-Myc-driven lymphamogenesis [66]. Other splicing components are synthetic lethal with overexpressed c-Myc [67]. Inhibiting the function and interactions of the translation initiation complex, eIF4F, interferes with cap-dependent translation and is also being investigated as a therapeutic strategy [68]. The data presented here demonstrate that deregulated c-Myc sensitises cells to inhibition of the Capping Enzyme, CE. Inhibiting CE targets c-Myc expression and function and therefore we suggest that CE should be investigated further as a therapeutic target.

Mass spectrometry
Performed by LC-MS-MS using linear ion traporbitrap hybrid mass spectrometer (Orbitrap-Classic, Thermo) equipped with nanoelectrospray ion source (Thermo) and coupled to a Proxeon EASY-nLC system. Peptides prepared by in-gel tryptic cleavage were injected via 2cm trap column (Nano Separations, NS-MP-10 BioSphere C18, 5μm, 120Å,360/100μm) onto Thermo (Part No. 160321) Acclaim PepMap100 reverse phase C183μm column, 75μm x 15cm, with 300 nl/min flow and eluted with linear gradient of 95% solvent A (2% Acetonitrile/0.1% formic acid/H 2 O) to 35% solvent B (90% acetonitrile/0.08% formic acid/H 2 O) at 20 minutes followed by rise to 80% B at 23 minutes, maintained at 80% B for 5 minutes, followed by re-equilibration. Instrument operated with 'lock mass' option to improve mass accuracy of precursor ions and data acquired in datadependent mode, automatically switching between MS and MS-MS acquisition. Full scan spectra (m/z 350-2000) acquired in orbitrap with resolution R=60,000 at m/z 400 (after accumulation to FTMS Full AGC Target; 1,000,000; MSn AGC Target; 100,000). 5 most intense ions, above specified minimum signal threshold (5,000), based upon low resolution (R = 15,000) preview of the survey scan, fragmented by collision induced dissociation and recorded in linear ion trap, (Full AGC Target; 30,000. MSn AGC Target; 5,000). Proteins were identified and quantified using Maxquant software. RNA pol II mascot scores 3545 and 2529.

Immunoprecipitation
Immunoprecipitations (IPs) performed at 4°C in F buffer. CE-GFP co-IPs performed for 2.5 hours using GFP-Trap_A (Chromotek). CE co-IPs performed for 2.5 hours with 2μg CE antibody (in house). For guanylyltransferase assays, CE IPs performed for 2.5 hours with 0.5μg CE antibody and RNA pol II IPs performed overnight with 4μg Poll II (pan) antibody (Santa Cruz, sc-899). For endogenous CE and Pol II IPs, 20μl Protein G agarose bead slurry (Generon) added for 1 hour. IPs washed three times in 10mM Tris/Cl pH 7.5/150mM NaCl/0.5mM EDTA and eluted in F buffer/Laemmli buffer/0.1M DTT. Samples analysed by SDS-PAGE.
Cells fed with 500μl growth medium/5% FBS alternate days. After 9-15 days, colonies in five fields from each well scored using graticule.


s2fieldsofstudy:
Biology
Chemistry
Agricultural And Food Sciences

text:
Molecularly Characterized Solvent Extracts and Saponins from Polygonum hydropiper L. Show High Anti-Angiogenic, Anti-Tumor, Brine Shrimp, and Fibroblast NIH/3T3 Cell Line Cytotoxicity

Polygonum hydropiper is used as anti-cancer and anti-rheumatic agent in folk medicine. This study was designed to investigate the anti-angiogenic, anti-tumor, and cytotoxic potentials of different solvent extracts and isolated saponins. Samples were analyzed using GC, Gas Chromatography–Mass Spectrometry (GC–MS) to identify major and bioactive compounds. Quantitation of antiangiogenesis for the plant's samples including methanolic extract (Ph.Cr), its subsequent fractions; n-hexane (Ph.Hex), chloroform (Ph.Chf), ethyl acetate (Ph.EtAc), n-Butanol (Ph.Bt), aqueous (Ph.Aq), saponins (Ph.Sp) were performed using the chick embryo chorioallantoic membrane (CAM) assay. Potato disc anti-tumor assay was performed on Agrobacterium tumefaciens containing tumor inducing plasmid. Cytotoxicity was performed against Artemia salina and mouse embryonic fibroblast NIH/3T3 cell line following contact toxicity and MTT cells viability assays, respectively. The GC–MS analysis of Ph.Cr, Ph.Hex, Ph.Chf, Ph.Bt, and Ph.EtAc identified 126, 124, 153, 131, and 164 compounds, respectively. In anti-angiogenic assay, Ph.Chf, Ph.Sp, Ph.EtAc, and Ph.Cr exhibited highest activity with IC50 of 28.65, 19.21, 88.75, and 461.53 μg/ml, respectively. In anti-tumor assay, Ph.Sp, Ph.Chf, Ph.EtAc, and Ph.Cr were most potent with IC50 of 18.39, 73.81, 217.19, and 342.53 μg/ml, respectively. In MTT cells viability assay, Ph.Chf, Ph.EtAc, Ph.Sp were most active causing 79.00, 72.50, and 71.50% cytotoxicity, respectively, at 1000 μg/ml with the LD50 of 140, 160, and 175 μg/ml, respectively. In overall study, Ph.Chf and Ph.Sp have shown overwhelming results which signifies their potentials as sources of therapeutic agents against cancer.

INTRODUCTION
Angiogenesis is the growth of new capillaries from pre-existing capillaries and post-capillary venules. It is a highly controlled process that usually occurs during wound healing, embryonic and corpus luteum development (Folkman, 1972). It is now well-established that many diseases are caused by persistent unregulated angiogenesis, like tumor growth is highly dependent on vascular growth. Those tumors which lack angiogenesis stay dormant and quick logarithmic growth follow the attainment of blood supply (Folkman and Klagsbrun, 1987). Tumors angiogenic control seems to be activated when angiogenic inhibitors and stimulators balance are shifted toward proangiogenic milieu (Hanahan and Folkman, 1996). Due to this reason, interest in the identification and development of anti-angiogenic drugs is tremendously increased. In contrast, induction of angiogenesis is also of great interest in treatment of ischemic diseases (Horvath et al., 1997). Administration of angiogenic growth factors in the form of recombinant protein or by gene transfer to the ischemic animal models has shown to increase nutrient perfusion via neo-vascularization. Novel gene therapy technologies and advancement in animal modeling have enabled scientists to expand therapeutic angiogenesis strategies applied in animal models of myocardial ischemia and coronary artery diseases. In this regard, several potential drugs with angiogenic activity are under investigations (Silvestre and Levy, 2002).
The chick embryo chorioallantoic membrane (CAM) is a model frequently used to evaluate angiogenic and antiangiogenic properties of potential drugs (Ribatti et al., 2001). Using this method, angiogenic response occurs in 72-96 h after stimulation in the form of increased blood vessels density around the implant, with the vessels radially converging toward the center (Ribatti et al., 1995). On the other hand, when an antiangiogenic compound is applied, the vessels around the implant become less dense or even vanish completely (Vacca et al., 1999). Quantitative analysis of vessels in large amount of CAM models is used to screen drugs and samples of plants. Some traditional Chinese herbal drugs have been reported to be effective in the therapy of ischemic heart diseases and cancer (Wang et al., 2004).
Cancer is a life-threatening disease and is a serious health problem worldwide. It represents a group of diseases characterized by uncontrolled proliferation of abnormal cells which invade and disrupt nearby tissues (Gennari et al., 2007). Due to toxicity problems, high cost and adverse side effects associated with the use of synthetic anticancer drugs, natural products is the most potential alternative source of useful anticancer drugs. The isolation of novel anticancer drugs like vincristine and vinblastine from plant sources provide convincing evidence that plants are potential sources of novel anticancer drugs. Potato disc assay is rapid, economical, and reliable bioassay that provides basis for the possible anticancer and anti-tumor utility of test samples. The inhibition of A. tumefaciens induced tumors (or Crown Gall) in potato discs, is an assay based on antimitotic activity and can detect a broad range of anti-tumor effects (McLaughlin, 1991). The assay is based on the hypothesis that anti-tumor drugs might inhibit the growth of tumors both in plant and animals, since some tumorogenic mechanisms are quite related in plants and animals (McLaughlin and Rogers, 1998). Crown Gall tumor is a neoplastic illness in plants caused by A. tumefaciens. The bacterium contain Ti (tumor inducing)-plasmids that carry genetic information (T-DNA) which upon infection transforms normal or wounded plant cells into independent tumor cells (Coker et al., 2003). The Ti-plasmid causes the plants' cells to multiply rapidly without going through apoptosis, resulting in tumor development, like in nucleic acid content and histology to human and animal cancers (Binns and Thomashow, 1988). Similarly, brine shrimp cytotoxicity assay is an important scientific tool for the preliminary cytotoxic analysis of natural and synthetic drugs before more complex and advance studies. As far as the phytochemicals are concerned, they possess pronounced biological potentials i.e., flavonoids are well-known for antioxidant potential, saponins for cytotoxic potential, alkaloids for antimicrobial potential, and have been reported by numerous investigators. In fact these secondary metabolites confer pharmacological potential to plants.
P. hydropiper belong to Polygonaceae, a family having about 50 genera, 1200 species and is traditionally used to treat cancer (Hartwell, 1970), hypertension, and cardiovascular diseases (Qureshi et al., 2006). We previously reported antioxidant, anticholinesterase (Ayaz et al., 2014a(Ayaz et al., , 2015, phytotoxic, and anthelmintic potentials of P. hydropiper (Ayaz et al., 2014b). Domestically, its decoction is used as diuretic, antrheumatic, anti-inflammatory, haemostatic, and to relieve toothache (Popovic et al., 2014). Other species of Polygonaceae family have been reported for anti-tumor potentials (Mazid et al., 2011;Ahmad et al., 2016) and effectiveness in cerebral ischemia (Chan et al., 2003), Parkinson's disease (Chen et al., 2007) and as neuroprotective (Li et al., 2005). Based on the ethnomedicinal uses and research work on the related species, this study was designed to investigate anti-angiogentic, antitumor, and cytotoxic potentials of P. hydropiper extracts, crude saponins, and narrow down the search for isolation of novel anticancer compounds from this valuable plant.

Extraction of Saponins
Dried plant material (60 g) was soaked with 100 ml of 20% ethanol in a conical flask and was heated at 55 • C for 4 h using water bath with occasional shaking. Subsequently, it was filtered and again extracted with 200 ml of 20% ethanol. Volume obtained was concentrated to 40 ml via water bath and transferred it to a separating funnel. Further, 20 ml of diethyl ether was added to the separating funnel and was shacked vigorously. Among the two layers formed (Diethyl ether and water), aqueous layer was utilized by adding 60 ml of n-butanol to it. The combined mixture (aqueous and n-butanol layer) was washed two times with 5% NaCl solution. Finally, it was concentrated using water bath to get saponins (9 g) with 15% yield (Khan et al., 2011).

Gas Chromatography-Mass Spectrometry (GC/MS) Analysis
Samples were initially subjected to GC analysis using an Agilent USB-393752 gas chromatograph (Agilent Technologies, Palo Alto, CA, USA) with HHP-5MS 5% phenylmethylsiloxane capillary column (30 m × 0.25 mm × 0.25 µm film thickness; Restek, Bellefonte, PA) equipped with an FID detector. The initial temperature of the oven was retain at 70 • C for 1 min, followed by increase at the rate of 6 • C/min to 180 • C for 5 min and lastly at the rate of 5 • C/min to 280 • C for 20 min. Injector and detector temperatures were set at 220 • C and 290 • C, respectively. Helium was used as a carrier gas with a flow rate of 1 ml/min, and diluted the plant samples (1/1000 in n-pentane, v/v) of 1.0 µl were injected manually in the split-less mode. GC/MS analysis of samples were processed using the same column and experimental conditions.

Identification of Components
Compounds were recognized by comparison of their retention times with those of authentic compounds in the literature. Further, identification were done via the spectral data obtained from the Wiley and NIST libraries, as well as comparisons of the fragmentation pattern of the mass spectra with data published in the literature (Stein et al., 2002;Adams, 2007).

Chorioallantoic Membrane (CAM) Assay
Anti-angiogenic potential of plant extracts and saponins were determined by CAM assay (Nguyen et al., 1994). The fertilized domestic chicken eggs purchased from poultry trader Chakdara, Pakistan, were incubated for 3-4 days at 37 • C in a humidified incubator (HYSC Korea (BI-81/150/250) and were slowly moved at least three times a day. After the completion of incubation period, the seven day old eggs were observed under flash light to identify and encircle the embryo head. Thereafter, a tiny hole was drilled at the narrow end of the eggs and 0.5-1 ml of albumin was aspirated using eighteen gauge hypodermic needle   so that yolk sacs drop away from the shell membrane. The shell around the embryo air sac was detached via forceps and the shell membrane at the base of air sac was peel away. On 8th day, a thermanox cover slip loaded with different samples (10 µl) was carefully placed on the surface of CAM and were incubated. After 3 days, an appropriate amount of methanol and acetone mixture (1:1) was injected into the embryo chorioallantois using a 33 gauge needle. The CAM was cut out from eggs and the numbers of vessels were observed. Vessels radially converging in the direction of the center were counted under a microscope. At least twenty eggs were used for each sample dose. The % of increase and inhibition were calculated using formula;

Potato Discs Preparation
Red skinned potatoes were purchased from the local market near University of Malakand Chakdara, Pakistan. Using sterile cork borer, potato discs of 2 mm height and 8 mm diameter were made. These discs were surface sterilized with 1% HgCl 2 solution for 4-5 min followed by washing with distilled water. These were allowed to dry aseptically for 20 min. The discs were placed on plates containing autoclaved agar medium (1.5%) using sterile forceps. Finally, the top surface of each potato disc was inoculated with 50 µl of plant extract-bacterium mixture. The plates were sealed with parafilm and incubated at 28 • C in dark. After 15-20 days, potato discs were stained with Lugol's solution (10% KI + 5% I 2 ) and tumors were counted under dissecting microscope. Vincristine sulfate and solvents system were taken as positive and negative control, respectively. Test was repeated three times and data was analyzed statistically.

Disk Diffusion Assay
In order to check the effect of plants samples on the growth of Agrobacterium and hence on tumor formation, a qualitative to semi quantitative disc method was used following previously reported procedure (Bauer et al., 1966). Briefly, nutrient agar plates prepared aseptically were inoculated with test organisms under laminar flow hood. Sterile paper disks of 6 mm diameter (Whatman International, CAT: 2017-006) impregnated with different concentrations of extracts were placed equidistantly onto the surface of already inoculated Petri dishes using sterile forceps. Blank discs impregnated with DMSO/solvents were used as negative control whereas ceftriaxone discs (Geltis, Shaigan Pharmaceuticals) were used as positive control. The plates were incubated at 37 • C for 24 h and zones of inhibition were measured around the bores.

Determination of Minimum Inhibitory Concentrations (MICs)
For determination of MICs, nutrient broth method approved by clinical and laboratory standard institute (CLSI) were used (Standards, 1993). For these tests, plant extracts in concentrations of 1-10 mg/ml were added to sterilized tube containing nutrient broth and were inoculated with the test microbes. Tubes were incubated using shaker incubator at 37 • C for 24 h. MIC was considered that concentration at which no visible bacterial growth was observed.

Brine Shrimp Cytotoxicity Assay
Cytotoxicity assay was conducted on crude extracts and saponins of P. hydropiper against Artemia salina (brine-shrimps eggs) following the established procedure (Meyer et al., 1982).

Hatching Procedure
Sea water is best medium for hatching brine shrimp eggs. Artificial sea water solution was prepared by dissolving commercial salt mixture (38 g) in double distilled water in a shallow rectangular plastic dish of 22 × 32 cm. The plastic dish was divided into two parts using a perforated device. In larger darkened compartment covered with aluminum foil, 50 mg of eggs were sprinkled whereas the smaller compartment was kept open to ordinary light for newly hatched brine shrimps larva. The brine shrimps were incubated for two days at 37 • C. After 48 h when the larvae got hatched, it was attracted from dark side using torch and collected using a Pasteur pipette.

Samples Preparation and Application
Plant extracts and crude saponins solutions were prepared in different concentrations ranging from 31.25-1000 µg/ml. Sample solutions corresponding to 31.25, 62.50, 125, 250, 500, and 1000 µg/ml were transferred to separate clean vials and were placed in flow hood to evaporate the solvent. One ml of simulated seawater and 30 shrimps were transferred to each vial and final volume was raised to 5 ml using simulated seawater and pH was adjusted to 7.4. Similar procedure was followed for positive control etoposide and negative control (solvent system) vials. All vials were incubated at 26 ±1 • C under illumination for 24 h. The number of survived shrimps were counted in control and test vials and median lethal concentrations (LC 50 ) were calculated from dose response curve using Microsoft Excel programme (Zeb et al., 2014).

MTT Cells Viability Assay
Mouse embryonic fibroblast NIH/3T3 cell line were cultured in DMEM medium supplied with 10% FBS and antibiotics (50 units/ml penicillin and 50 units/ml streptomycin) at 37 • C in a humidified atmosphere containing 5% CO 2 . Samples' cytotoxicity against cultured NIH/3T3 cells was determined using MTT assay. NIH/3T3 cells were seeded into 96-well plates at an initial seeding density of 8.0 × 10 3 cells/well in 200 µl medium followed by incubation for 24 h. Thereafter, the culture medium was removed and replaced with 200 µl medium containing serial dilutions (0.0625-1 mg/ml) of samples. Cells incubated with the media alone were used as positive control and the cells were grown for another 24 h. Subsequently, 20 µl of MTT solution (5 mg/ml) in PBS was added to each well. After incubating the cells for 4 h, the medium containing unreacted dye was removed carefully. The obtained purple formazan crystals were dissolved in 200 µl per well-dimethyl sulfoxide (DMSO) and the absorbance was measured in a microplate spectrophotometer reader at a wavelength of 570 nm. The following formula was used to calculate the inhibition of cell growth;

Estimation of IC 50 Values
Median inhibitory concentrations (IC 50 ) for anti-angiogenic assay and median lethal concentrations (LC 50 ) were calculated for anti-tumor and cytotoxic activities using Microsoft Excel program.

Statistical Analysis
All the experiments were performed in triplicate and values were expressed as means ± SEM. One-way ANOVA followed by multiple comparison Dunnett's test was used for the comparison of positive control with the test groups. The P < 0.05 were considered as statistically significant.

Cluster Analysis
Cluster analysis and dendrogram based on IC 50 and LC 50 of different samples were developed using SPPS software version 16.0 following Ward's method to draw dendrogram hierarchical clusters. Results are given in Figure 1.

Regression and Linear Correlation
Regression (y) and linear correlation (R 2 ) for anti-angiogenic, anti-tumor, and cytotoxic assays exhibited by Ph.Sp and different fractions were determined using Microsoft Excel 2007. Results are given in Figure 2.

RESULTS AND DISCUSSION
Angiogenesis is a rigorously controlled process, regulated by a series of endogenous angiogenic and angiostatic factors under normal circumstances (Folkman and Klagsbrun, 1987). In abnormal angiogenesis like malignancy, atherosclerosis, and chronic inflammations, angiogenesis inhibitors are dominated by angiogenesis promoters leading to abnormal proliferation and migration of the cells. Researchers are looking to isolate and characterize novel angiogenic and anti-angiogenic drugs from natural sources since last fifteen years. In our current study, Ph. Dexamethasone was used as positive control having IC 50 value of 11.68 µg/ml. All other fractions showed concentration dependent but less significant activity. In our observations, Ph.Sp showed highest anti-angiogenic activity with IC 50 of 19.21 µg/ml. Saponins having anti-angiogenic potentials have been isolated previously from plants, like convallamaroside from Convallaria majalis, and Polyphyllin D from Paris polyphylla (Nartowska et al., 2004;Chan et al., 2011). Likewise, a large number of plants including, crude extracts from Viscum album, Populus nigra, Chrysobalanus icaco, Cassia garrettiana, Agaricus blazei were reported for anti-angiogenic potentials. The isolated compounds including, shikonin from Lithospermum erythrorhizon, torilin from Torilis japonica, Deoxypodophyllotoxin from Pulsatilla koreana, resveratrol from grapes, epigallocatechin gallate from green tea, genistein from ginseng and isoliquiritin from licorice have been reported for anti-angiogenic activities both in-vitro and in-vivo (Sasamura et al., 2004;Wang et al., 2004;Farina et al., 2006).  Cancer is characterized by hysterical and abnormal proliferation of the cells and present more than hundred clinical pathologies (Zeb et al., 2014). The relationship between tumor and tumor-induced angiogenesis has been described by cell adhesion, proteolysis, and migration of cells. There are sound evidences regarding the tumor cells, which have the ability to invade the surrounding tissue and activate the formation of new capillaries from endothelial cell which leads to growth and dissemination of cancer (Sini et al., 2005). So the anti-tumor potential of a specific sample may also correspond to the anti-angiogenic potential of that sample. Similarly, the selection of NIH/3T3 cell line in viability assay is based on the fact that various cell line including the NIH/3T3 mouse embryonic fibroblast, HeLa cell line, chicken embryo fibroblasts, Chinese hamster ovary cells etc. have been reported to be sensitive to sarcoma virus focus formation and leukemia virus propagation and the transfection has been previously evaluated by monitoring immunofluorescence assays (Gorman et al., 1982).
Due to the diverse nature of cancer, the development of costeffective and broad spectrum cytotoxic drugs is a real challenge to the researchers. Anticancer drugs and radiation causing DNA mutations in actively dividing cells were anticipated to selectively kill cancer cells and produce limited effects on normal cells. Unfortunately, these agents are effective only against certain types of cancer and are associated with toxic effects on normal dividing cell and serious side effects. Therefore, the search for new anticancer drugs both from natural and synthetic origin is crucial. Anti-tumor and brine shrimp lethality bioassays are rapid and economical tools for preliminary cytotoxicity study of plant crude extracts, isolated compounds, and synthetic compounds to develop new anticancer drugs (Meyer et al., 1982;Amara et al., 2008). In anti-tumor assay, Ph.Sp, Ph.Chf, Ph.EtAc, and Ph.Cr showed highest activity causing 90.00 ±1.9 (IC 50 18.39 µg/ml), 85.53 ±2.2 (IC 50 73.81 µg/ml), 80.00 ±1.9 (IC 50 217.19 µg/ml), and 72.20 ±2.2% (IC 50 342.53 µg/ml) tumor inhibitions, respectively, at 1000 µg/ml ( Table 2). Based on these results Ph.Chf and Ph.EtAc were subjected to activity guided isolation of novel bioactive compounds. In anti-tumor and brine shrimps cytotoxicity assays, Ph.Sp was observed to be highly active fraction. Previously, julibrosides isolated from Albizia julibrissin and avicins from Acacia victoria were reported as putative anticancer saponins (Lemeshko et al., 2006;Hua et al., 2009).
Disc diffusion and MICs methods were used to evaluate the inhibitory effect of test samples against A. tumefaciens. Ideally, the sample should not inhibit the growth of A. tumefaciens which is responsible for the induction of tumors. As indicated from our results ( Table 3), majority of the samples were inactive against A. tumefaciens both in disc diffusion and MICs assays. However, Ph.Cr and Ph.Sp showed low antibacterial activity. In cytotoxicity assay, Ph.Chf, Ph.EtAc, Ph.Bt, and Ph.Sp showed 100% lethality against the brine shrimps at 1000 µg/ml concentration (  Table 5). Based on our results, active fractions were subjected to activity guided isolation of novel anticancer agents.
Anticancer compounds have been sorted out in the data obtained from GC-MS analysis of each fraction of P. hydropiper i.e., Ph.Cr, Ph.EtAc, and Ph.Bt as shown in Figures 3-5. The GC-MS of Ph.Cr manifested the identification of numerous anticancer compounds as per literature survey namely; dihydrobenzofuran, vinylguaiacol, succinimide, pyrocatechol, humulene, caryophyllene oxide, dihydrojasmone, farnesol, methyl p-coumarate, myristic acid, dodecyl acrylate, stearic acid, lauramide, capsiacine, and tricosane. Similarly, the anticancer compounds sorted out in Ph.EtAc were monomethyl malonate, pyrrolidinone derivatives, succinimide, pyrocatechol, pyrogallol, adamantane, paraben, and dihydrojasmone. Likewise, the anticancer compounds identified in Ph.Bt were succinimide, pyrocatechol, borneol, benzeneacetic acid, pyrogallol, nicotinamide, caryophyllene oxide, atlantone, and palmitic acid. Some of the compounds were found in all the fractions, for instance succinimide and pyrocatechol, which have been reported as strong anticancer agents (Hall et al., 1995; Taysse et al., 1995). Putatively known anticancer compounds i.e., Dihydrojasmone, capsaicine and caryophyllene oxide have also been identified in the chromatograms of our sample (Richeux et al., 1999;Flescher, 2005;Jun et al., 2011). Fatty acids and their derivative having anticancer potential have also been found in these samples, for instance myristic acid, dodecyl acrylate, stearic acid, lauramide, and palmitic acid (Fermor et al., 1992;Yoshii, 1997;Harada et al., 2001;Li et al., 2011). Similarly, dihydrobenzofuran has also been revealed with significant anticancer potentials and its derivatization is still in progress by several researchers (Choi et al., 2015). Likewise, vinylguaiacol is considered as a potential antioxidant compound (Azadfar et al., 2015). In the same way, the Humulene has also been reported to inhibit tumor growth (Legault et al., 2003). The GC-MS also indicates the presence of tocopherol, which is a well-known antioxidant and anticancer vitamin (Yu et al., 2009). Likewise, Silane derivatives has been demonstrated as an effective agent in a nanoparticle based drug delivery system for anticancer compounds (He et al., 2010).

CONCLUSIONS
Results of the current study indicate that P. hydropiper possesses broad spectrum cytotoxic activities. Samples were inactive against A. tumefaciens in-vitro, which indicate that this is a useful anti-tumor assay for P. hydropiper. GC-FID and GC-MS analysis revealed the presence of a large number of anticancer compounds which may be responsible for the overall anticancer activity of the extracts. Furthermore, studies regarding isolation and purification of novel anticancer components can depict the precise potentials of the plant for the chemotherapy of a variety of cancers. Our findings regarding cytotoxic potentials of extracts and saponins may offer scientific justification for the ethnomedicinal uses of the plant.

AUTHOR CONTRIBUTIONS
MA and SA carried out experimental work, data collection and evaluation, literature search, and manuscript preparation. MJ and FU supervised research work and helped in study design. MI conducted GC-MS. FS, AS, MK, WA, and GA refined the manuscript for publication. All authors read and approved the final manuscript for publication.

FUNDING
This research received no specific grant from any funding agency in the public, commercial, or not for-profit sectors.