The maxillae were processed and subjected to histological and immunohistochemical assays. Hematoxylin-eosin staining (7th day) revealed inflammation in the CTL group that was partly reversed after DOX treatment. On the 14th day, the CTL group exhibited bone neoformation, conjunctive tissue, re-epithelization and the absence of inflammatory infiltrate. DOX-treated groups exhibited complete re-epithelization, tissue remodelling and almost no inflammation. Picrosirius red staining in the DOX10 group (7th and 14th days) revealed an increased percentage of type I and III collagen fibres compared with the CTL and DOX25 groups. The DOX10 and DOX25 groups exhibited increases in osteoblasts on the 7th and 14th days. However, there were fewer osteoclasts in the DOX10 and DOX25 groups on the 7th and 14th days. Wnt-10b-immunopositive cells increased by 130% and 150% on the 7th and 14th days, respectively, in DOX-treated groups compared with the CTL group. On the 7th day, Dickkopf (Dkk)-1 immunostaining was decreased by 63% and 46% in the DOX10 and DOX25 groups, respectively. On the 14th day, 69% and 42% decreases in immunopositive cells were observed in the DOX10 and DOX25 groups, respectively, compared with the CTL group. By increasing osteoblasts, decreasing osteoclasts, activating Wnt 10b and neutralising Dkk, DOX is a potential candidate for bone repair in periodontal diseases.Doxycycline (DOX) exhibits anti-inflammatory and MMP inhibitory properties. The objectives of this study were to evaluate the effects of DOX on alveolar bone repair. Controls (CTL) and DOX-treated (10 and 25 mg·kg The development of this reaction highly influences the outcome of the healing process. Among the specialized bone tissues, the alveolar bone, which supports the tooth in the maxilla and mandible, is characterised by distinctive features, such as continuous and rapid remodelling in response to stimuli by force.5Bone is a complex mineralised connective tissue characterised by constant remodelling, involving cycles of bone resorption and bone formation. Bone tissue has considerable potential for healing, exhibiting cooperative action among bone forming and resorptive cells to restore the architecture and function of damaged tissue.6 has indicated the histomorphometric and molecular profiles of alveolar bone healing after tooth extraction. That study has shown that after the initial clot dominance, immature granulation tissue development is evident by the 7th day. This development is characterised by marked cell proliferation, angiogenesis and inflammatory cell infiltration associated with growth factors, cytokines, chemokines and receptors and the expression of mesenchymal stem cell markers. On the 14th day after tooth extraction, the immature granulation tissue is replaced by mature connective tissue, which is characterised by decreased inflammatory infiltrate, increased bone formation, the expression of matrix remodelling enzymes -2 and MMP-9), markers of bone formation/maturation, and chemokines and receptors associated with healing.Recent evidence8 doxycycline (DOX) potentially decreases enzyme expression at the transcriptional level. Furthermore, DOX activity toward mammalian collagenases and gelatinases appears to be unrelated to its antimicrobial efficacy. Others have shown that DOX inhibits not only MMP-8 and MMP-9 (gelatinase B) activity, but also the synthesis of MMPs in human endothelial cells.9 A later study has concluded that the inhibition of MMPs by tetracyclines, including minocycline, a second generation tetracycline similar to DOX, occurs mainly via the down regulation of respective gene expression.10In addition to inhibiting MMP activity,12 The molecular environment of chronic wounds contains high levels of pro-inflammatory cytokines and MMPs, which impair normal healing. This process is positively affected by DOX.14 Previously, the systemic administration of DOX has been found to prevent both root resorption and bone loss in rats.15MMPs degrade virtually all constituents of the extracellular matrix. MMPs are critical for connective tissue remodelling and healing as well as bone healing after tooth extraction.16 Dysregulation of this pathway greatly inhibits bone formation and the healing process, thus suggesting that this pathway has an essential role in bone regeneration.17 Wnt signalling is activated by wounding and participates in every stage of the healing process, from the control of inflammation and programmed cell death to the mobilisation of stem cell reservoirs within the wound site.18Furthermore, the Wnt signalling pathway  plays a key role in bone development and homeostasis. Wnt ligands promote bone growth, thereby leading to the hypothesis that Wnt signalling activation may stimulate bone healing.19Furthermore, signalling via the classical Wnt pathway is critical for bone deposition and bone remodelling. Among other mechanisms, this signalling pathway is regulated by Dickkopf proteins (Dkks), which bind and promote the internalisation of lipoprotein receptor-related protein (LRP)5 or LRP6. Blocking these Wnt receptor components effectively downregulates Wnt signalling. Dkk has been implicated in bone formation and bone diseases. The induction of the Wnt signalling pathway promotes bone formation, whereas its inactivation by Dkk leads to osteopenic states.Given the anti-inflammatory and MMPs inhibitory properties of DOX, the objectives of the present work were to use histological and histomorphometric methods to evaluate the effects of DOX on alveolar bone repair after tooth extraction in rats. In addition, we performed immunohistochemistry detecting Wnt-10b and its inhibitor Dkk-1.Ketamine hydrochloride was purchased from Holliday-Scott SA, Argentina, and xylazine was obtained from Kensol Konig, Brazil. Doxycycline hydrochloride was obtained from EMS Laboratory, São Paulo, Brazil. Antibodies to Wnt-10b and Dkk-1 were obtained from Santa Cruz Biotechnology Inc., Dallas, Texas, or from ABCAM Inc., Cambridge, MA, USA. All other drugs and reagents were of analytical grade.Male Wistar rats (150–200 g) from the Animal House of the Federal University of Ceará (UFC) were maintained in appropriated cages  and given free access to water and food. The study protocol was submitted to and approved by the UFC Institutional Ethics Committee and was performed according to the Guide for the Care and Use of Laboratory Animals , USA, 2011).n=5 per group) were divided into the following groups:two control (CTL) groups treated with saline for 7 or 14 days and four groups of DOX-treated rats, two of which were treated with DOX at doses of 10 or 25 mg·kg−1, p.o., once daily for 7 days, and two of which were treated with the same doses of DOX for 14 days. The treatments started 1 h before the surgical procedure and continued for 7 or 14 days. For tooth extractions, the animals were anaesthetized with ketamine  and xylazine . Each animal was placed in the dorsal decubitus position, and the mouth was kept open with rubber bands. The upper molars on the right side were extracted using a lever movement with a 3S Hollemback spatula adapted to the size of the teeth. During the surgical procedure, the area was irrigated continuously with saline. After the extraction, the surgical site was subjected to gauze compression to avoid haemorrhage and to aid in clot removal. After 7 and 14 post-surgery days, the animals were euthanized via decapitation. The maxillas were removed and fixed in buffered formol for 48 h. Then, hemi-maxillas were separated and demineralised with a 10% buffered EDTA solution for 30 days and were processed for histological (hematoxylin-eosin (HE) staining) and immunohistochemical assays for Wnt-10b and Dickkopf (Dkk)-1.The animals  and slices from the left hemi-maxilla (no tooth extraction),which corresponded to the same region of the first left superior molar, were obtained. For qualitative analyses, the following parameters were analysed: polymorphonuclear and mononuclear cell inflammatory infiltrates, conjunctive tissue remodelling and number of osteoclasts. For these analyses, the Particle Analysis-Cell Counter and ImageJ software  were used. The analyses were performed at the 7th and 14th days after the surgical procedure.Picrosirius red (PSR) staining was used to evaluate the types of collagen fibres that were present in the tissue and involved in alveolar bone repair. Under appropriate conditions, type I collagen fibres appear with a reddish-yellow colour, whereas type III collagen fibres are greenish. In the present work, the analyses were performed at the 7th and 14th days after the tooth extraction using both non-polarised and polarised images, and the data quantification was performed with the ImageJ software .−1 sodium phosphate buffer, pH 7.2) for 10 min. Endogenous peroxidase was blocked with a 3% hydrogen peroxide solution (20 min), and protein was blocked with 5% BSA for 40 min. The slices were incubated overnight with the primary anti-goat Wnt-10b antibody (1:100 dilution) or a polyclonal anti-rabbit Dkk-1 antibody (1:200 dilution). After being washed with PBS, the slices were incubated with the biotinylated anti-rabbit secondary antibody (1:400 dilution) for 30 min. After being washed, the slices were incubated with the streptavidin–peroxidase-complex for 30 min, washed again with PBS and stained with 0.1% DAB (in 3% hydrogen peroxide). Finally, the glass slides were washed in distilled water and counterstained with Mayer’s hematoxylin, washed in tap water, dehydrated in alcohol (at increasing concentrations), diaphonized in xylol and mounted on Entelan for optic microscopy examination. The immunostaining intensity was quantified with the ImageJ software .Hemi-maxilla slices (5 μm) from animals of all study groups were fixed in 10% buffered formol, for 48 h, followed by 70% alcohol. The sections were embedded in paraffin wax, and slices were processed on appropriate glass slides. These samples were placed in an oven at 58 °C for 10 min, then subjected to deparaffinization in xylol, rehydration in alcohol at decreasing concentrations and washing in distilled water and phosphate buffered saline (PBS)  of the histomorphometric analyses and quantitative variables were subjected to two-way ANOVA, followed by the Tukey post hoc test. The results were considered significant at P<0.05.For parameters analysed in HE staining, scores were calculated, and the data were subjected to the non-parametric Kruskal–Wallis test, followed by the Dunn On the 7th day after surgery, the CTL group  exhibiteThe analyses on the 7th post-surgery day revealed decreased collagen deposition in the three groups. However, in the CTL, the predominance of type III collagen fibres was noted, a result that differed from those in the DOX-treated groups, which exhibited a predominance of type I fibres. In addition, increases in collagen fibres were observed in the DOX10 and DOX25 groups  compared with the CTL group. On the 14th day after surgery, the CTL group exhibited bone matrix deposition with minimal type III fibres. At that time point, the DOX25 groups respectively exhibited 290% and 190% increases in collagen fibres, as compared with the CTL group. Although type III predominated in the DOX10 group, a predominance of type I collagen fibres was observed in the DOX25 group compared with the DOX10 and CTL groups .On the 7th post-surgery day , the CTLOn the 7th post-surgery day , no diff−1 DOX increased (median 2: 2–3) compared with that in the DOX10 (median1:1–1) and CTL (median 1:1–1) groups  and DOX25 (median 1:1–1) compared with the CTL group (median 0:0–1). However, on the 14th day, the degree of remodelling in the group treated with 25 mg·kg) groups .−1 DOX significantly increased the number of osteoblasts by 190% and 220%, respectively, compared with that in the CTL group on the 7th day after-tooth-extraction. Similar increases (130%) were observed for both the DOX10 and DOX25 groups on the 14th day, as compared with CTL.Representative photomicrographs of alveolar tissues from the three study groups indicated the presence of osteoblasts on the 7th and 14th days  after to−1 DOX, respectively, compared with the CTL group on the 7th day. A similar pattern was observed on the 14th day, with decreases of 78% and 80% in the DOX10 and DOX25 groups, respectively, compared with CTL.Similar and significant increases (~130%) were observed for this parameter in the groups treated with DOX at both doses, on the 7th day (compared with the CTL group). On the 14th day , increas−1 DOX, respectively, compared with the CTL group. Although this pattern was maintained on the 14th day, the number of immunopositive cells was 69% and 42%, for the DOX10 and DOX25 groups, respectively.20 These properties are associated with inhibition of iNOS and TNF-alpha and are probably related to DOX’s actions on alveolar tissue inflammatory infiltrates, as shown in the present work.In the present work, DOX significantly decreased PMN and mononuclear inflammatory infiltrates in alveolus tissue on the 7th and 14th days after tooth extraction in the model of bone repair in rats. We have previously demonstrated that DOX presents potent anti-inflammatory and antioxidant effects.23 Specific staining of the extracellular matrix components with PSR is especially helpful in studying tissue remodelling.24 The stain specifically binds to collagen fibrils of varying diameters, and was thus used to distinguish type I from type III collagen fibres.At the lower dose, the DOX group, compared with the CTL group, exhibited significant increases in collagen fibres on the 7th and 14th days after tooth extraction, thus indicating better organisation and bone neoformation, as evaluated by PSR staining. Although no difference in the percentage of collagen fibres was observed between the DOX25 and CTL groups, the DOX25 group presented a significant number of type I collagen fibres. Type I collagen is primarily observed in bone, dentin, tendon, dermis and gingival tissues and is also the main extracellular component.25 A previous study 26 has demonstrated an increase in collagen fibre organisation over time. In addition, the authors have observed collagen maturation over 3, 7 and 14 days during orthodontic tooth movements in rats. DOX inhibits MMP enzymes and prevents bone loss.27 In addition, by increasing type I collagen fibres, DOX accelerates collagen maturation and bone repair, as observed in the present study.The enhancement of birefringence promoted by the PSR-polarisation method is therefore specific for collagenous structures composed of aggregates of oriented molecules.28 Recently, low doses of orally administered DOX for 7 days have been found to enhance bone formation in the alveolar sockets of rats.29 The bone matrix is composed primarily of type I collagen fibres, which are a marker of osteoblast differentiation. Bone strength depends on more than quantity and mainly depends on quality, which is characterised by the geometry and shape of bones, the microarchitecture of trabecular bone, bone turnover, and the presence of minerals and collagen.30MMPs are a family of enzymes that play a key role in maintaining and remodelling the extracellular matrix of connective tissue.−1 doses, DOX significantly and dose-dependently decreased the number of osteoclasts, as compared with the CTL group on the 7th day post-surgery. A similar pattern was also observed on the 14th day. DOX induces osteoclasts apoptosis, which occurs independently of the inhibition of MMPs.31 Furthermore, DOX decreases mononuclear inflammatory infiltrates and osteoclast numbers, thereby preventing inflammatory bone resorption.32We demonstrated that at both 10 and 25 mg·kg33 fewer osteoclasts have been found to be present in DOX-treated animals in a surgically induced osteoclast recruitment model. Later evidence has indicated significant decreases in root resorption and the numbers of odontoclasts, osteoclasts and mononuclear cells on the root surface of DOX-treated rats.34 The authors concluded that DOX, at low doses, may have an inhibitory effect on orthodontically induced resorptive activity. Furthermore, DOX has been shown to effectively inhibit osteoclastogenesis and to affect mature osteoclast fate.35Previously,36 These effects suggest that this drug may potentially be used to increase bone formation. Other in vitro results have indicated the effect of DOX on osteoblastic proliferation and differentiation.37 The authors of that study have concluded that DOX appears to enhance maturation and differentiation, rather than proliferation, and may thus be beneficial in the treatment of periodontal disease and periodontal regeneration.In contrast, we demonstrated that DOX significantly and dose-dependently increased the number of osteoblasts, as compared with that in the CTL group, on the 7th day. Although an increase was also observed on the 14th day post-surgery, the effect was smaller, and no significant differences were observed among groups. Long-term exposure of human bone marrow osteoblastic cells to DOX induces a significant increase in the number of osteoblastic cells, thereby yielding a proportional amount of normal mineralised matrix.38 Osteogenesis is induced in response to bone morphogenic protein 2 (BMP2) stimulation and is sustained by Wnt signalling. However, the presence of Dkk-1, an inhibitor of Wnt signalling, results in osteogenesis inhibition, and during the repair process, the expression of many Wnt ligands and receptors is upregulated.40 Wnt pathways regulate bone mass and are active during fracture repair, and an increase in their activity accelerates bone regeneration.41 Thus, the activation of Wnt pathways has the potential to improve bone healing, and its dysregulation greatly inhibits bone formation and healing processes.17Wnt proteins play a very important role in several mammalian physiological processes, including embryogenesis, organ development and regeneration, and cell migration and proliferation.42 In addition, Wnt signalling by itself is a very attractive target for therapeutic interventions related to skeletal homoeostasis and bone repair.43 Thus, as we have shown here, Wnt signalling may be a potential target for DOX, and this result may stimulate translational studies towards including this drug in the clinic in the near future.Evidence from preclinical studies has indicated that Dkk neutralization and/or Wnt signalling enhancement may prove effective in the treatment of bone pathologies.44In the present work, we provided the first evidence that DOX inhibits the Dkk-1 pathway while activating Wnt signalling. These results were immunohistochemically evaluated through both the increase of Wnt-10b and the decrease in Dkk-1 in immunostained cells on the 7th and 14th days after tooth extraction. Although the exact mechanism of Wnt signalling during bone development is dependent on a complex microenvironment, data from several laboratories suggest that Wnt-3a, Wnt-5a, Wnt-7b and Wnt-10b are central to osteoblast differentiation.45 However, Dkk-1 counteracts Wnt-mediated effects on bone differentiation and adipogenesis. Thus, the neutralization of inhibitors of Wnt signalling, such as Dkk-1, is a promising therapeutic strategy in bone diseases.46Clinical and experimental studies suggest a clear role for Wnt signalling in the regulation of bone formation, repair and remodelling. Thus, Wnt pathway activation accelerates bone regeneration.47 Recent evidence has indicated that selective inhibition of the Wnt pathway by Dkk-1 decreases osteoarthritis in mice.48 Furthermore, diseases such as periodontitis are characterised by inflammation and bone loss, and the activation of PMN cells leads to the release of proinflammatory cytokines and the recruitment of phagocytes and lymphocytes.49 Previously, we have demonstrated that DOX has potent anti-inflammatory activity.20 In addition, minocycline, the second generation tetracycline similar to DOX, offers protection in a model of periodontal disease in normal and diabetic rats.Wnt signalling is widely accepted to be required for the differentiation of osteoprogenitors into osteoblasts, and the Wnt pathway antagonist Dkk-1 causes bone destruction and the inhibition of bone repair.In the present study, we demonstrated that owing to its ability to increase osteoblast numbers and decrease osteoclast numbers, but mainly through its activation of Wnt-1b and neutralization of Dkk-1, DOX may be a potential candidate for use in bone repair in several pathologies, including periodontal diseases.


Editorial on the Research TopicInter-Organelle Calcium Communication in Cancer2+ transfer, and its impact on cancer cell fate.Cancer is a leading cause of death worldwide, accounting for 8.2 million deaths  in 2012, with this number expected to rise to over 11 million by 2030 , suggest2+ store, interact with each other in response to changes in cellular metabolism , and Nogo-B/reticulon-4B as oncogenes or oncosuppressors. As mentioned, MAMs actively participate in the regulation of proteostasis, tuning the ER stress response to cope with metabolic demand under various stress stimuli. Carreras-Sureda et al. immerses us in the unfold protein response, its relation with MAMs, and the role this plays in cancer.It has been known since the 1950 that mitochondria and the ER, the main intracellular Catabolism . The ER–tabolism  as mitoc and PML , 11. Ped2+ is a ubiquitous signaling messenger that regulates various cellular processes ranging from muscle contraction to synaptic transmission and from cellular proliferation to cell death , generating specific spatiotemporal Ca2+ signals  receptor (IP3R), in the ER, which proves to be necessary to maintain the bioenergetic homeostasis of these cells , a highly Ca2+ permeable channel that controls metabolism and bioenergetics by modulating the access of Ca2+ as well as pyruvate, malate, succinate, and NADH to the inner mitochondrial membrane. Shoshan-Barmatz et al. review the role of VDAC1 in cancer with special emphasis on its role in apoptosis induced by [Ca2+]-increasing agents, which upregulate VDAC1 expression and subsequently results in VDAC1 oligomerization, the release of cytochrome C & Smac/Diablo, and eventually apoptosis. Once present in the mitochondrial intermembrane space, Ca2+ is taken up into the mitochondrial matrix through the MCU complex, whose structure, activity, and regulation has been explained by Mammucari et al. In addition, the authors highlighted the divergent roles of MCU in cancer, revealing both anti- and pro-tumorigenic roles dependent on the cancer type and cancer stage. Finally, Chen and Boehning assess the role of lipidation in the regulation of different signaling pathways that impact Ca2+ homeostasis, such as Ras in apoptosis and tumor progression.Call death , 13. Thi signals . Alteratgression , 16. In se cells , as delixidation . Ca2+ crPendin et al. These alterations enable cancer cells to avoid apoptosis and to cope with the sustained energy demand, particularly during migration, invasion, and metastasis. White concisely reviews the key steps controlled by Ca2+ during the invasion-metastasis cascade and reveals how changes in the Ca2+-handling components that reside in the MAMs might facilitate invasion and metastasis by impacting bioenergetics and reactive oxygen species generation. Along these lines, Hegedüs et al. provide experimental evidence that enhanced clearance of Ca2+ by increased expression of the plasma membrane Ca2+ ATPase 4b induced by histone deacetylase inhibitors, and reduces migration in a melanoma cell line.Mitochondria are highly dynamic organelles undergoing constant fusion and fission governed in part by the metabolic status of the cell . Cancer 2+ ions, impacts a plethora of cancer hallmarks and plays a critical role in oncogenesis. The emerging insights at the molecular level in the dependence of cancer cells on ER-mitochondrial Ca2+ signaling for their survival and migration will pave the path for new therapeutic strategies and tools (Cancer has a multifactorial nature. Over the last decade, it has become increasingly clear that ER-to-mitochondria communication, in particular, through the flux of Cand tools , hopefulCC drafted the manuscript that was reviewed and edited by PP and GB. All authors co-edited the Research Topic.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Seed germination strongly affects plant population growth and persistence, and it can be dramatically influenced by phylogeny, seed traits, and ecological factors. In this study, we examined the relationships among seed mass, seed shape, and germination percentage (GP), and assessed the extent to which phylogeny, seed traits  and ecological factors  influence GP at the community level. All analyses were conducted on the log-transformed values of seed mass and arcsine square root-transformed values of GP. We found that seed mass and GP were significantly negatively correlated, whereas seed shape and GP were significantly positively correlated. The three major factors contributing to differences in GP were phylogeny, dispersal type, and seed shape , but GP also influenced by seed mass and onset of flowering. Thus, GP was constrained not only by phylogeny but also by seed traits and ecological factors. These results indicated that GP is shaped by short-term selective pressures, and long-term phylogenetic constrains. We suggest that correlates of phylogeny, seed traits, and ecology should be taken into account in comparative studies on seed germination strategies. Seed germination, a central seed trait, is a key bottleneck in plant life history, potentially affecting the distribution and abundance of species in communities  whether species with small seeds would have a higher germination percentage than species with larger seeds, (2) whether species with elongate and flat seeds would have a higher germination percentage than those with round seeds, and (3) what proportion of germination variation among species could be attributed to the species' phylogeny, seed traits , and ecological factors .−1. The soils are sandy, loose, and very susceptible to wind erosion. Ninety percent of the total area has been desertified. The landscape is characterized by mobile, semi-stabilized, and stabilized dunes.The study grassland is located in the Horqin Sandy Land in northeastern China , which has a continental semiarid monsoonal climate with a very cold winter and a warm summer. Mean annual temperature is 6.3°C; the lowest and the highest monthly mean temperatures are −14.0°C in January and 23.0°C in July, respectively. Mean annual precipitation is 288 mm, of which 70–80% is received in June, July, and August. The prevailing winds are from the northwest from March to May and from the southeast from June to September. Annual mean wind velocity ranges from 3.0 to 4.4 m sMature seeds of 109 species growing in different habitats were collected from August to November . Seeds were collected from 15 to 25 plants per species. Seeds from one species were thoroughly mixed to minimize the contribution from single plants. Air-dried seeds were stored in paper bags in the laboratory.−2 s−1 at seed level). The daytime temperature was kept at 28°C and the night temperature was 16°C, to approximate the mean daily maximum and minimum temperature in 3–5-cm-deep soil during rainy days from May to August. Each dish was inspected daily, and germinated seeds were counted and removed. The seeds whose radicles had emerged were considered to have germinated. Counting continued until no germination occurred for five successive days. Seeds that had not germinated were checked for viability. Germination percentage (GP) was calculated as the percentage of viable seeds that germinated.For each species, five replicates of 50 seeds were placed on filter paper in Petri dishes (9 cm diameter). The filter paper was moistened with distilled water and the dishes were placed in temperature and light-controlled incubators  of 25–30 μmol mSeed mass, a measure of size, was represented by the average weight of single seed  and the R2 of the incomplete model represented the proportion of the total ss explained by the removed factor. If, in the complete ANOVA, a given class variable has a lower R2 value than in the incomplete ANOVAs from which a different variable has been deleted, the increase in the R2 value of the first variable would be due to an association (or correlation) or strong interaction with the second variable , and ecological factors  influence seed germination, a one-way, two-way, and factorial analysis of variance (ANOVA) were conducted Mazer, . The oneGP was arcsine square root transformed and seed masses were log transformed to improve normality and stabilize variances. All analyses were performed with SPSS 18.0 software.We grouped species into the following categories prior to analysis:Phylogenetic group. To examine effects of phylogeny on germination, the 109 angiosperm species were grouped by order according to the APG III system of plant classification (Angiosperm Phylogeny Group III 2009): Liliales, Asparagales, Poales, Ranunculales, Zygophyllales, Malpighiales, Fabales, Rosales, Geraniales, Malvales, Caryophyllales, Ericales, Gentianales, Solanales, Lamiales, Asterales, and Apiales.Life form. Species were assigned to the following three major growth categories: woody plants, graminoid plants, and forbs.Adult longevity. Species were grouped into two classes: annual  or perennial.Seed mass. The mean seed mass of each species was assigned to a class: < 0.1 mg, 0.1–0.3 mg, 0.31–1.0 mg, 1.1–3.0 mg, 3.1–9.0 mg, 9.1–30 mg, or > 30 mg  zoochorous species, defined as having awns, spines, or hooks to adhere to animals (epizoochory), or having fleshly or arillate fruits for animals to eat (endochory); (2) anemochorous species, defined as having membranous wings, hairs, bracts, a persistent or inflated perianth, or a pappus; (3) ombrohydrochorous species, defined as those wherein the seeds produce mucilage upon being wetted; (4) autochorous species, which are ballistically dispersed from explosively dehiscing capsules that throw the seeds some distance from the parent plant; or (5) barochorous species, defined as those lacking any obvious dispersal mechanism or disperser reward  early, where flowering begins in May; (2) middle, where flowering begins in June; or (3) late, where flowering begins in July and August.Seed color. Each species was classified into one of seven color categories based on our observations and relevant literature  were close to spherical to ovoid Figure .P = 0.007, R2 = 0.074, Figure P = 0.003, R2 = 0.089, Figure There was a significant negative correlation between seed mass and GP (A series of ANOVAs was used to determine whether the variance in GP among 95 species (excluding species with no germination and with only one representative per order) was correlated with the assessed factors. One-way ANOVAs showed that five factors  had statistically significant effects on GP Table . DispersR2 value) in the two-way ANOVAs was less than in the one-way ANOVAs  of the complete and incomplete models can represent the proportion of the ss explained by the removed factor , and seeds from late-flowering species had higher GPs. Moreover, we found that phylogeny had a close association and interaction with seed size, shape, and dispersal strategy Tables –3. Thus,In this study of the Horqin Sandy Land, a degraded sandy grassland in northeastern Inner Mongolia, China, we found that (1) GP was negatively and significantly correlated with seed mass, (2) species with elongate and flat seeds had higher GPs than species with round seeds, and (3) phylogenetic relatedness, dispersal type, and seed shape, in that order, were the three factors with the greatest contribution to the complete model (14% of the variance in GP). Furthermore, (1) GP, like any other trait, is shaped both by short-term selective pressures and long-term phylogenetic constraints, and (2) comprehensive studies at the community level that use multivariate approaches are needed to enhance our understanding of the evolutionary and ecological forces shaping germination strategies.BL designed the research and collected and analyzed the data. ZW analyzed the data and drafted the manuscript. LW and ZL revised English language and contributed to paper writing. QL and YL assisted with data collection. All authors took part in writing the manuscript.Funding was provided by the Key Project of Chinese National Programs for Fundamental Research and Development (No. 2013CB429903) and National Natural Science Foundation of China (No. 31570448) and the New Century Excellent Talents Program of Fujian Province (K8015053A).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Legionella . A Relative Risk (R.R.) > 1 (p < 0.0001) was calculated for chlorine concentrations of less than 0.2 mg/L (R.R.: 54.78), star classification (<4) (R.R.: 4.75) and absence of Water Safety Plan implementation (R.R.: 3.96). High risk (≥104 CFU/L) was estimated for pool showers (16.42%), garden sprinklers (7.46%) and pool water (5.97%).Several Travel-associated Legionnaires’ disease (TALD) cases occur annually in Europe. Except from the most obvious sites (cooling towers and hot water systems), infections can also be associated with recreational, water feature, and garden areas of hotels. This argument is of great interest to better comprehend the colonization and to calculate the risk to human health of these sites. From July 2000–November 2017, the public health authorities of the Island of Crete (Greece) inspected 119 hotels associated with TALD, as reported through the European Legionnaires’ Disease Surveillance Network. Five hundred and eighteen samples were collected from decorative fountain ponds, showers near pools and spas, swimming pools, spa pools, garden sprinklers, drip irrigation systems (reclaimed water) and soil. Of those, 67 (12.93%), originating from 43 (35.83%) hotels, tested positive for  Legionella bacteria live naturally in fresh water, as well as in artificial water systems such as hot water tanks, hot tubs or spas, cooling towers, plumbing systems, and decorative pools or fountains [Legionella species are able to reproduce at 25–43 °C and able to survive at temperatures of up to 55–60 °C, making it possible for them to thrive even in hot water systems [ountains ,2. Hotelountains . LegioneLegionella pathogens: Legionnaires’ disease (LD), presenting with pneumonia-like symptoms, and Pontiac fever, presenting with influenza-like symptoms [Legionella bacteria, although L. pneumophila serogroup 1 is considered the most virulent of all species and serogroups, causing approximately 75% of all Legionella infections [Legionella with at least 73 different serogroups have been described, of which approximately 20 species have been associated with human disease [Legionella bacteria in an aerosol, droplets with a diameter of less than 5 μm (~90% showers aerosols) may come into contact with the lower human airways [Two forms of legionellosis are caused by the symptoms . Legionnfections ,6,7. Unt disease ,9,10,11. disease ,13. Sinc airways ,14,15,16Legionella bacteria in one country but develop symptoms and seek medical attention in another (such as their home) country [Travel-associated Legionnaires’ disease (TALD) corresponds to the cases of travelers who get infected in the country they visit, but usually get diagnosed and/or report their infection back in the country of their residence. These human cases do not include domestic ones, that is, cases in which humans travel within their own country. Due to the long incubation period (2–10 days), travelers may be exposed to  country . Accordi country . The ave country ,19.Since 2004, the World Health Organization (WHO) has developed a Water Safety Plan (WSP) approach according to its Guidelines for Drinking Water Quality, which is based on risk assessment and risk management principles ,22.L. pneumophila and Legionella species in environmental samples obtained from recreational areas and determine the frequency and severity of colonization of Legionella in these sites; (2) estimate the risk factors associated with Legionella colonization of recreational systems and (3) evaluate the implementation of WSPs to limit Legionella colonization.The aims of the present study were: (1) culture and identify During the period of 2000–2017, the Local Public Health Authorities of the Island of Crete in Greece inspected 119 hotels associated with TALD. Environmental samples from decorative fountain ponds, showers near pools and spas, swimming pools, spa pools, garden sprinklers, drip irrigation systems (reclaimed water) and soil were collected from each hotel, where applicable. 5) (mg/L) ≤10 in 80% of samples; (3) Total suspended solids (TSS) (mg/L) ≤2 in 80% of samples; (4) Turbidity (NTU) ≤2 median. The above criteria are met following secondary biological treatment followed by advanced treatment and disinfection.Specifically, as regards the reclaimed water from the drip irrigation systems, in all sample cases it consisted of a product of secondary biological treatment followed by advanced treatment and disinfection. According to the National legislation “Common Ministerial Decision (CMD) No 145116: Measures, limits and procedures for reuse of treated wastewater ”, this kind of water can be used unrestrictedly in irrigation of gardens and in recreational areas of hotels provided that it fulfills the following criteria: (1) Total coliforms (TC) (cfu/100 mL) ≤2 in 80% of samples and ≤20 in 95% of samples; (2) Biochemical oxygen demand  potentially associated with a TALD case. The samples were collected according to: (a) the guidelines for drinking-water quality (second edition) and (b) ISO 5667-2:1982—Part 2: guidance on sampling techniques; since 2006, samples were collected following the ISO 19458:2006 Water quality—Sampling for microbiological analysis methodology. The samples were labeled and temporarily stored in a cool box at a temperature of up to 5 (±3) °C protected from direct light, before being delivered to the laboratory immediately after the sampling (no more than 24 h).Data on water temperature, pH, chlorine concentration, disinfection methodology, hotel star rating, number of rooms/beds, implementation of a WSP, season and water supply were recorded. Inspections were conducted following a checklist developed with some information such as name, address of building, type of hot water production system, water disinfection system, periodicity and type of water system maintenance and cleaning, water supplying and number of rooms and beds. The temperatures were measured (two minutes after flushing) using a calibrated thermometer, placed in the middle of the water stream. Free chlorine and pH were measured using a calibrated portable, microprocessor-based meter. Samples were collected in 1 L sterile containers containing sufficient sodium thiosulphate (20 mg) to neutralize any chlorine or other oxidizing biocides.Legionella from water samples was performed by culture according to the International Standard method ISO 11731 (1998) and ISO 11731-2 (2004). The latter ISO was implemented from 2004 onwards. Briefly, water samples were concentrated by filtration and were re-suspended in Distilled Deionized water. A volume of the suspension (200 μL) was spread on BCYE , BCY  and GVPC (Glycine Vancomycin Polymyxin Cycloheximide)  Petri dishes: (a) directly after filtration; (b) after incubation at 50 °C for 30 min and (c) after the addition of an acid buffer . The detection limit of the procedure was 50 CFU/L. The inoculated plates were incubated for 10 days at 36 ± 1 °C in 2.5% CO2 with increased humidity. Suspected colonies were randomly chosen for subculture on BCY, BCYE and GVPC agar.The isolation of Legionella-Kit, Biomérieux, Craponne, France), which allows for the discrimination of L. pneumophila serogroup 1 from serogroups 2–14 and of L. anisa, while for the exact detection of each L. pneumophila serogroup, individual latex polyclonal reagents were used .Up until 2010, the isolated colonies were identified using an agglutination test . Spectra were recorded using the flexControl software with the default parameters for optimization set by the manufacturer . For each spectrum, 240 laser shots were collected and analyzed (6 × 40 laser shots from 120 different positions of the target spot). All identifications were evaluated according to the manufacturer scoring scheme.From 2010 onwards, a MALDI Biotyper (Microflex LT MALDI-TOF mass spectrometer)  equipped with a microSCOUT ion source was used for the identification of individual Legionella bacteria in the water sample, which could represent a particular risk to the human health. In particular, an insignificant risk was noted at ≤103 CFU/L, medium risk at >103 CFU/L but <104 CFU/L, and high risk at ≥104 CFU/L. Especially for spa pools, the recommendations point to the risk of legionellosis following Legionella sampling to low risk (>102 but <103) and to high risk (≥103 CFU/L) [Legionella count was ≥104 CFU/L in at least one sample or between >103 and ≤104 CFU/L in more than two samples or between >103 and ≤104 CFU/L in at least one sample in concordance with an aerobic count higher than 105 CFU/L.To better calculate the risk, we used two different approaches. The first one was in accordance with the recommendations of the European Legionnaires’ disease Surveillance Network (ELDSNet), at which the microbiological results of the water samples were analytically and statistically analyzed according to the number of 3 CFU/L) . A seconThe second approach for the assessment of the risk was based on a semi-quantitative risk matrix approach, which was used to implement the water supply system risk assessment . The ris3 to <104, either: (i) if a small proportion of samples (10–20%) were positive, the system was re-sampled. If a similar count was recorded again, then a review of the control measures and risk assessment was carried out to identify any remedial actions; (ii) if the majority of samples were positive, the system was considered as colonized, even at a low level, with Legionella. Disinfection of the system was considered but an immediate review of control measures and a risk assessment was carried out to identify any other remedial actions required. In samples which met the criteria of ≥104: The system was re-sampled and an immediate review of the control measures and risk assessment was carried out to identify any remedial actions, including whether a disinfection of the whole system or affected area was necessary.According to the national guidelines, in samples which met the criteria of >10As from 2005, a detailed standardized questionnaire  and the MedCalc relative risk calculator statistical software free online version; Relative risk (R.R.) at a 95% confidence interval (CI). The analyses were calculated to assess categorical risk variables from water distribution systems and hotel characteristics, associated with Legionella species. The mean positivity was 9.41%  (Legionella species at the sites tested and/or the risk factors (as these are explained below) were repeatedly tested out of the limits.Of the 518 samples collected, 67 (12.93%) originated from 43 (35.83%) hotels that tested positive for n 0.00%) . A seconIn 14/119 (28.57%) of the hotels inspected, a cluster was noted (clusters were defined as the presence of two or more cases having stayed overnight at the same accommodation site in the 14 days before onset of illness and whose illness was within say the same two-year period) . Legionella was isolated from swimming pool showers, garden sprinklers, reclaimed water, swimming pool water, decorative fountain, spa water and spa showers. On the contrary, no Legionella species were isolated from shower heads, from Jacuzzis and from garden soil. All results are summarized in Legionella pneumophila serogroups 1, 2, 3, 6, 7, 8, 13, 14, 15 and 2–15 were detected. Of the non-pneumophila species, L. anisa, L. erythra, L. taurinensis, L. birminghamensis, L. rubrilucens and Legionella species were identified, the majority of which, belonged to the human pathogenic species L. anisa. The CFU/L ranged from 50–350,000. The lowest CFU/L were detected in spa waters, while the highest ones were identified in swimming pool showers and in garden sprinklers. All results are summarized in Legionella was possibly associated  with: (a) the implementation of a WSP; (b) free chlorine <0.2 mg/L; (c) hotel star classification of <4; (d) seasonal operation; (e) municipality hosting hotels population of <104 people and (f) absence of an automated chlorination system together with free chlorine out of range. The number of beds of >200, the number of rooms of >80 and the use of groundwater as a source of water supply showed a statistically significant correlation in the absence of a relative risk >1. On the other hand, no statistically significant correlation was calculated for cold water temperature of >25 °C, temperature of >20 °C, the absence of an automated chlorination system, pH out of limits value (pH within limits 7.0–7.8), the opening/closing period and the high season period (June–August). All results are summarized in The presence of 3, 103–103 and >104 respectively) a corresponding Legionella and the total risk (as a factor taking these two parameters into consideration). Of the total sites tested, the garden sprinklers and the swimming pool showers presented a higher risk when all three hazardous events were considered. As regards the pool water, a high risk was calculated for the event of finding Legionella in the water system, only. All results are summarized in Based on the risk assessment according to the guidelines of ECDC  received a score B (relatively satisfactory) while 37 (63.7%) got a score C (unsatisfactory).p value <0.0001; CL 95% 1.73 to 5.34; z-statistic 3.87; NNT (Harm) 8.06) and in hotels where wrong implementation of WSP was recorded  7.33).A higher colonization was recorded in the absence of a WSP , absence of water disinfectants or under-treated water, out of range pH values (5.5–9.2), presence of substances like iron salts and l-cysteine, as well as, co-existing and supporting microbial flora. Furthermore, other factors such as the complexity of the architecture of the pipe system (high surface to volume ratio), presence of blunt-end pipes, infrequently used pipe terminals, pipelines exposed to the sun heat, close proximity of hot and cold-water pipelines, insufficient maintenance and end-points creating aerosols, have all been evaluated to significantly affect the rate and extent of Legionella colonization in water systems [ systems . Even th systems . All the systems .Legionella colonization was less in swimming pools and in spas, due to the increased surveillance and implementation of proper chlorination procedures, as opposed to the colonization in showers of swimming pools. The analyzed data showed that the high chlorination, the mixed type of contamination and the lower temperatures in the pool are potential factors that may contribute to the prevention of any Legionella from reproducing and reaching levels that would represent a health risk for bathers. The pool samples from which Legionella were isolated, had significantly lower concentrations of residual free chlorine, in fact less than the 0.4 mg/L required by the current regulations in Greece (0.4–0.7 mg/L). On the other hand, no significant correlation between Legionella colonization and pH values was calculated in the current study, agreeing with the study by Fragou et al., where the colonization of Legionella in 116 samples collected from hotels and hospitals was evaluated against pH values [Legionella, while the frequent vigorous agitation that can occur in spas, pools and whirlpool baths can form aerosols that could create airborne bacteria and transfer them to the lungs of unsuspected individuals [Legionella even in more isolated water facilities such as in spa and pools located on cruise ships that are actually one of the most common sources of Legionella infection [Legionella infectious environment. Such conditions are recorded in showers, especially the ones that have their pipes or at least part of them exposed to the sun heat. Similar results have been described from researches in Italy [The presence of 1559 hotels and accommodation units in Crete with 85,407 rooms and 161,578 beds , could not exclude the island from the presence of TALDs . The curH values . In geneividuals ,32, evenividuals . This isin Italy . Hotel fin Italy .Legionella were retrieved in 16 (30.8%) hotels [Legionella colonization; this finding has already been supported in a previous study carried out in hotels in Greece [In our study, positive samples were recorded in 43/119 36.13%) hotels, a result comparable to a similar study in Turkey, where of the 52 hotels included in the study, negative samples for ) hotels . Accordi.13% hoteLegionella species isolated, indicating a widespread dispersion of these microorganisms in the environment. In addition to the isolation of L. pneumophila , other potentially pathogenic environmental species were also isolated, such as L. anisa, L. erythra, L. taurinensis, L. birminghamensis, and L. rubrilucens, the agent responsible for Pittsburg pneumonia [Legionella species other than L. pneumophila or even the second most common, L. anisa, have been described worldwide, including the Island of Crete [Another point of interest was the high number of neumonia  which isneumonia . The preof Crete .Legionella pneumophila serogroup 1 was detected in swimming pools and swimming pool showers however the low number of samples collected did not allow us to make any correlation among the positive samples, the detected serogroups and the sampling sites. The highest CFU/L was detected for the L. pneumophila serogroup 14 (105 CFU/L) and for non-pneumophila species . Nevertheless, a larger number of positive samples is required before coming to concrete conclusions on a possible relationship between site of collection and number of bacteria. The prevalence of Legionella species at certain environments has, also, been investigated by Litwin and colleagues [L. pneumophila serogroup 1 and 6, L. anisa, L. feeleii, and L. quateriensis in the water reservoirs of recreational vehicles. As far as seasonality is concerned, in a similar research it was claimed that the concentrations of Legionella recovered from swimming pools, like L. micdadei and L. bozemanii, did not show any seasonal trend [lleagues  in whichVibrio cholerae, the rest of the enteric pathogens that may cause gastrointestinal illnesses do not grow or survive for ever in water. On the other hand, free-living pathogens, such as Legionella, can grow under favorable conditions in treated wastewater and associated biofilms and, under certain circumstances, can survive within amoeba in water distribution systems [As regards the use of reclaimed water, ingestion of enteric pathogens causing gastrointestinal disease poses the greatest risk from exposure to wastewater however, inhalation of aerosols or dermal contact can, also, lead to disease. Except from  systems . That is systems .Legionella); its proper implementation is sometimes a more crucial factor [Legionella bacteria to develop a decreased sensitivity to antibiotics [Concerning WSPs, they already exist in various contexts worldwide. For instance, WSP networks are located in Africa, the Asia-Pacific region and in Latin America. WSPs have been designed in order to monitor water utility and to ensure that its quality standard is consistently kept within accepted limits . In anotl factor . In factibiotics . Of courLegionella infections. Stronger evidence on the source of infection can only be supported through enhanced standardization of Legionella investigation, reporting and follow-up, together with the use of high discrimination laboratory techniques. These factors could eventually lead to a more effective measure control [Legionella infection [Summing up, there is a need for awareness strategies in concordance with the operators of accommodation sites for the prevention of human  control . Moreovenfection ,48.Legionella is one of the most serious microbiological risks according to the water safety in distribution hotels. Knowing that Legionella bacteria can successfully thrive in natural and artificial water environments with warm waters, certainly directs towards the investigation of establishments with such conditions and with high human use or of those which present more complicated constructions such as pools and spas.The presence of Preventing recreational water LD is a multifaceted issue that requires both the development of a WSP and, above all, its correct implementation, together with the participation of a large group of people like hotel staff and national and local public health authorities.


FST distributions with those of the 1000 Genomes Project and commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, DREAM’s autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. DREAM performances are further illustrated in biogeographical, identical by descent, and copy number variation analyses. In summary, with approximately 800,000 markers spanning nearly 2,000 genes, DREAM is a useful tool for genetic anthropology, forensic, and personalized medicine studies.The human population displays wide variety in demographic history, ancestry, content of DNA derived from hominins or ancient populations, adaptation, traits, copy number variation, drug response, and more. These polymorphisms are of broad interest to population geneticists, forensics investigators, and medical professionals. Historically, much of that knowledge was gained from population survey projects. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism genotyping, their design specifications are limited and they do not allow a full exploration of biodiversity. We thereby aimed to design the Diversity of REcent and Ancient huMan (DREAM)—an all-inclusive microarray that would allow both identification of known associations and exploration of standing questions in genetic anthropology, forensics, and personalized medicine. DREAM includes probes to interrogate ancestry informative markers obtained from over 450 human populations, over 200 ancient genomes, and 10 archaic hominins. DREAM can identify 94% and 61% of all known Y and mitochondrial haplogroups, respectively, and was vetted to avoid interrogation of clinically relevant markers. To demonstrate its capabilities, we compared its  The field of population genetics experienced astonishing changes over the past 50 years, generating a new understanding of variability at the molecular level that has allowed for the exploration of new biological paradigms. Over the past decade, this turmoil was driven by the wide availability of single-nucleotide polymorphism (SNP) microarray and next generation sequencing (NGS) data, which raised major questions concerning human early origins, interbreeding with archaic hominins, and the processes that shaped inter- and intrapopulation variability.Such questions are also the core components of forensic DNA phenotyping. Common forensic and mass disaster scenarios alongside accumulated criticism of eyewitness testimonies necessitated the development of more accurate and reliable DNA-based forensics tools based on short tandem repeats (STRs) extracted from minute DNA amounts . The a gInterest in human ancestry is not limited to genetic anthropologists, genealogists, and forensic experts. The relatedness of adaptations to diseases is instrumental to identify targets for drug treatment (Sheridan 2015). The appreciation that demographic histories, geographical origins, and migration patterns shaped the genetic risk to disorders and treatment response  underlieSince NGS technologies remain prohibitively expensive, microarray SNP technology became the “workhorse” for geneticists, although they are limited in a number of ways. First, genotyping data are susceptible to ascertainment bias due to the choice of SNPs . AlthougMotivated by progress in the studies of modern and ancient genetic diversity, adaptation mechanics, forensic phenotypes, and drug response, we aimed to design an affordable and all-inclusive microarray. Our goals were to: 1) design The Diversity of REcent and Ancient huMan (DREAM)—a state of the art SNP microarray dedicated to genetic anthropology and genealogy, forensics, and personalized medicine; 2) validate its accuracy; 3) evaluate its abilities to discern populations compared with alternative arrays; and 4) assess its performances on worldwide populations.Ancestry informative markers (AIMs) were obtained from the same 15 studies as listed in http://genome.ucsc.edu/; cited 2017 Jul 16) using the Burrows Wheeler Aligner (BWA version 0.7.15)  was then used for MarkDuplicates to remove reads with identical outer mapping coordinates (which are likely PCR artifacts). The Genome Analysis Toolkit RealignerTargetCreator module (GATK version 3.6) (Ancient DNA genomic data were obtained from 11 publications depicting 207 ancient genomes . In the  0.7.15) , allowin 0.7.15) . Picard ion 3.6)  was usedion 3.6)  were useion 3.6) . We usedion 3.6)  and Deniion 3.6) .To cross-validate DREAM’s genotypes, we genotyped 139 individuals from 17 worldwide 1000 GP populations including: Americans of Mexican ancestry (Los Angeles), Bengali (Bangladesh), British (England and Scotland), Caribbean Africans (Barbados), Colombians , Esan (Nigeria), Finnish (Finland), Gambian , Han Chinese , Iberian (Spain), Indian Telugu (UK), Italians , Kinh , Mende (Sierra Leone), Peruvians , Punjabi , and Yoruba . Genotypes were produced following the Axiom Best Practices Genotyping Analysis Workflow , which eMaternal and Paternal haplogroup calling was done using an internal haplogroup calling algorithm developed by the Genographic Project, as in FST based on 1000 GP phase 3 data  and e 3 data  providede 3 data . Calculae 3 data   correction for multiple tests  coverage obtained by each microarray. IBD varies by individual, population, proportion of rare alleles, and number of SNPs. For that, we assembled an autosomal data set by randomly selecting 30 individuals from three 1000 GP populations (phase 3) that have the same proportion of rare alleles (MAF < 0.5%) . Analyses were carried out using only the autosomal SNPs of each microarray. For each individual, we retained the average IBD with all individual of the same population. We then calculated the mean and standard deviation per population and divided them by the number of SNPs of the microarray.2r) using the PLINK (2r for each variant pair with two variants between them at most (ld-window = 2) without filtering low 2r values (window-r2 = 0).Finally, we compared the linkage disequilibrium (LD) patterns between the microarrays. For that, we used the 1000 GP (phase 3) data set. We randomly selected 30 individuals from four populations: Yoruba , Finnish (Finland), Japanese , and Puerto Ricans (Puerto Rico). We then analyzed the SNPs sequenced in those populations that were included in each of the five genotyping arrays: DREAM  HumanOmni5 , HumanOmni2.5 , Infinium Multi-Ethnic Global , and Human Origins . Lastly, we calculated the LD statistic . Using BCFtools , we mergWe applied Refined IBD implemented in Beagle version 4.1 (21Jan17.6 cc) with the reference human genome  to both reference populations known to have resided in a certain geographical region for a substantial period of time. GPS then converts the genetic distances between that individual and the nearest M = 10 reference populations into geographic distances. The reference populations can be thought of as “pulling” the individual toward their location in a strength proportional to the similarity of their admixture components until a “consensus” is reached  following  reached .k-means clustering and multiple pairwise F tests on populations with pN>4, where pN is the number of individuals within a population. For k = 2 to k =p N/2, we used k-means to identify k clusters and then the ANOVA F test to test whether cluster pairs are significantly different (P < 0.05). If the hypothesis is verified for all the pairs at iteration i, then another iteration follows until at least one pair violates the hypothesis and i-1k is the optimal number of clusters. Populations and subpopulations displaying only one individual were discarded from the data set. The final data set consisted of 587 individuals grouped into 123 subpopulations from 33 countries  graph G based on the 9 admixture components  as the basic clusters. If noise or overlap exists, outlier nodes are computed as a subset of the critical attack nodes, which form the cluster boundaries in G. We used integrity as the node-based resilience measure to cluster G due to its noted robustness when the number of ground truth clusters is not known a priori. Our integrity-based graph clustering results in eight clusters, each corresponding to a different color in the figure. The graphs are visualized using the Gephi 0.9.1 graph visualization program : BC(v) of a node v is the sum over all pairs of other nodes x, y, of the ratio of the number of x–y shortest paths that go through node v to the total number of x–y shortest paths. As BC(v) measures the extent to which v lies between other nodes (as well as between multiple clusters), larger nodes are intermediate to more pairs of graph nodes than smaller nodes in the visualization. Thus, the highest betweenness, larger nodes tend to lie on the boundaries between clusters in the NBR-Clust framework, representing outliers in terms of cluster overlap or noise. As such, we hypothesize that the largest, that is, highest betweenness centrality, nodes represent individuals with higher levels of admixture with respect to the clusters to which they are adjacent.The different sizes of the nodes (and node labels) were created using the To infer CNVs, we applied the Axiom CNV Summary Tool  to the 1PlotGenome script  was designed as an Applied Biosystems Axiom custom array. The Axiom genotyping platform utilizes a two-color ligation-based assay using 30-mer Oligonucleotide probes synthesized in situ onto a microarray substrate. There are ∼1.38 million features (or cells) with each SNP feature containing a unique 30mer oligonucleotide sequence complementary to the sequence flanking the polymorphic site on either the forward or the reverse strand. Depending on the 3′ (SNP-site) base , solution probes bearing attachment sites for one of two dyes are hybridized to the target complex, followed by ligation for specificity. DREAM was designed with 809,781 oligonucleotide sequences complementary to the forward or reverse strands (probesets) that interrogate 799,120 markers (SNPs or InDels). The following sections detail how markers were selected to enable ancestry, genealogy, forensics, and personalized medicine applications.AIMs are invaluable tools in population genetics and genetic anthropology as they allow the identification of populations that vary in substructure, quantification of the degree of admixture, and detection of subtle population subdivisions using a limited number of markers . We collAncient DNA from sequence or genotype data allows direct observations of past admixture and migration events and is often the only evidence that allows the examination of historical hypotheses. As such, ancient DNA studies have provided insights into human evolution and migration . We curated genetic data from over 200 ancient genomes  online. To facilitate studies on the extent of gene flow from Neanderthal and Denisovan populations to modern humans, we included SNPs from multiple low-coverage genomes while restricting the selection to markers validated by the 1000 GP. As such, we randomly selected 1,000 and 3,000 SNPs for Denisovans 4 and 8, respectively, and 5,000 SNPs from six Neanderthals . Overall, we selected 78,724 markers , 12,550 of which were culled from archaic hominin genomes.FADS1 and FADS2 . Following previous mapping efforts and based on the literature published over the past 5 years, we constructed a comprehensive list of adaptive traits and curated variants and genes that are significantly associated with those traits. Genes significantly associated with adaptations of interest were recorded and included in the design  for DNA phenotyping. Following previous studies  and baseCNVs have contributed significantly to hominid evolution , biodiveL > 10,000 bp) or shown to differentiate populations , Hypothyroidism , cholesterol , platelets, and red and white blood cells , whose data are associated with human genetic variation in drug responses  ∼75% of, whose god cells  were alsand BEST  and nearand BEST .Studies of sex bias in human admixture, migrations, and kinship analyses typically require a high coverage of the X chromosome. We thereby enriched the X chromosomes with SNPs selected uniformly throughout the genome. We prioritized SNPs that had Applied Biosystems Axiom confirmed probes and those that are targeted by Illumina’s HumanOmni5 array. Overall, 50,265 SNPs were selected.Of particular importance is the major histocompatibility complex (MHC) locus involved in autoimmune and infectious diseases. The MHC region is the most gene-dense region in the human genome. However, the high density in polymorphisms and linkage disequilibrium have limited our understanding of its role. To facilitate further research of this locus, we included SNPs for which Applied Biosystems Axiom had confirmed probesets and that reside within the 4 M bp of the MHC. Overall 16,434 SNPs were selected.To enable further research into traits of interests, we targeted SNPs that reside within or in the 100 kilobases flanking regions of the genes of interest. We used STRING  to find figs. 2 andTo enable cross-platform kinship analyses, we selected ∼230,000 SNPs distributed uniformly throughout the genome that had Applied Biosystems Axiom confirmed probesets.Finally, we interrogating over nearly 14,000 markers to identify SNPs defining Y and mtDNA haplogroups  online.We excluded most of the SNPs that required four probesets or more unless they were vital to call haplogroups. To improve coverage, we prioritized SNPs that required a single probset over those that required two. We also filtered out all the markers that were recorded in the ClinVar database   X, 13,576 Y-chromosomal, and 1,172 mitochondrial markers without clinical relevance. The design spans over 1,903 genes  online eGenotype accuracy was assessed by genotyping 139 individuals from 17 worldwide populations found in the 1000 GP data  and cross-validating them with the 1000 GP data. About 100% (139/139) of the samples passed sample QC, and 97.5%  of the markers passed marker QC. For autosomes that passed marker QC, the concordance rate was 99.70%  and the total marker call rate was 99.70% . For the nonPAR X markers, the concordance between the genotypes from the 46,020 markers  and the 1000 GP phase 3 genotypes was calculated as 99.76% . For the Y chromosome, the concordance between the genotypes from the 7,745 markers (part of the 1000 GP phase 3) and the 1000 GP phase 3 genotypes was 99.59% . For the mtDNA markers, the concordance between the genotypes from the 859 markers (included and part of the 1000 GP phase 3) and the 1000 GP phase 3 genotypes was calculated as 99.84% . Overall, we confirmed that nearly all the genotypes captured by the DREAM array are accurate.The SNP density across all chromosomes is shown in DREAM’s potential to assist in ancient DNA studies was evaluated by calculating the number of ancient DNA genotypes for each ancient genome  online. DREAM’s ability to infer uniparental haplogroups was computationally assessed against the respective trees. DREAM markers identified 94% and 61% parental and maternal haplogroups, respectively . All theCompared with whole genome data, allele frequencies (AF) in microarrays are typically shifted toward intermediate frequency levels , which lFST is a measure of differentiation whereby the genetic variation of the subpopulation is measured relative to the total population  than DREAM’s due to the high fraction of rare SNPs in these arrays. The magnitude of the differences between the FST values of these arrays was also large for autosomal  and X-chromosomal SNPs . These results suggest a reduced ability of the competing arrays to elucidate ancient demographic processes  would consist of a large number of SNPs in high LD. A comparison of the LD patterns of SNPs from the four 1000 GP populations, which overlapped with each of the five microarrays showed, that the Human Origins microarray had the smallest fraction of high LD markers followed closely by DREAM  online. NeanderthalN = 450, Neanderthalr = 0.75, DenisovanN = 450, Denisovanr = 0.91) and exhibit similar between-population patterns in the two data sets.DREAM’s ability to infer IBD with archaic hominins was evaluated by comparing the total IBD between worldwide individuals, Neanderthal, and Denisovan calculated using the complete 36 million SNPs (1000 GP data set) and DREAM SNPs, representing 1.86% of the complete data set  online. reference populations known to have resided in a certain geographical region for a substantial period of time  tool, which matches the admixture proportions of a test individual with those of  of time . The effG (betweenness centrality represent genetic mixtures with populations graphically adjacent to them, we created a Ppopulation graph G (G. Here too, nodes with notably high betweenness are the Bermudian, Tatarstan-Russian, Puerto Rican, Lima-Peruvian, North-Northeast Indian, and Antananarivo-Madagascan populations. These enlarged nodes lie on cluster boundaries. For example, the Madagascan node with high betweenness is adjacent to the Oceanic, East Asian, and his own African cluster, in support of recent reports of shared ancestry (Individual clustering by admixture proportions is an effective way to describe population structure  and evalG  online wgraph GP  online bancestry . North Iancestry . Our finFST distributions of the DREAM array to those of the 1000 GP and commercially available arrays, we demonstrated DREAM’s ability to differentiate populations within global data sets. Lastly, we demonstrated the biogeographical accuracy of DREAM and its potential ability to infer CNVs. We expect that the use of the DREAM in genealogy and research will expand our knowledge of our species. We designed, developed, validated, and assessed the DREAM microarray, an all-inclusive SNP genotyping chip dedicated to genetic anthropology and genealogy, forensics, and personalized medicine. DREAM can be used to study the genetic relationships between ancient humans, archaic hominins, and modern humans as well as to improve our understanding of human migratory history, adaptations, and the molecular mechanisms that regulate forensic-relevant traits. By comparing the MAF and Genome Biology and Evolution online.E.E. initiated the study and designed DREAM with Y.L. and T.W. M.L.B. supervised the work. E.E., L.Y., A.A., M.H., D.A., G.V., G.E., and U.E. carried out the analysis. E.E. and L.Y. wrote the manuscript. All authors approved the manuscript.Supplementary Figures and TablesClick here for additional data file.


Pathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its accuracy and the time required for bioinformatics analysis. Therefore, a simple, standardized, and rapid analysis pipeline from the receipt of clinical samples to the generation of a test report is needed to increase the use of metagenomic analyses in clinical settings.We developed a comprehensive bioinformatics analysis pipeline for the identification of pathogens in clinical samples based on 16S metagenomic sequencing data, named 16SPIP. This pipeline offers two analysis modes (fast and sensitive mode) for the rapid conversion of clinical 16S metagenomic data to test reports for pathogen detection. The pipeline includes tools for data conversion, quality control, merging of paired-end reads, alignment, and pathogen identification. We validated the feasibility and accuracy of the pipeline using a combination of culture and whole-genome shotgun (WGS) metagenomic analyses.16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples. Streptococcus suis outbreak in Sichuan Province in 2006, Salmonella infections in the United States in 2009, a 2010 Haitian cholera outbreak, and outbreaks of enterohemorrhagic Escherichia coli in Germany (2011) and England (2016). Rapid pathogen screening is a key step for the effective control of infectious diseases as well as for the prevention of disease transmission and elimination of public panic. According to standard methods for bacterial identification in conventional microbiology laboratories, bacteria are first cultured in a suitable growth medium to obtain a pure culture and are then identified based on phenotypes or biochemical properties [Several recent public health emergencies caused by bacterial pathogens have caused public concern, e.g., a operties . 16S rRNoperties , 5 and aSeveral important bioinformatics tools for 16S data analysis have been released, for example, QIIME, Mothur, SILVAngs, MEGAN, and AmpliconNoise . DespiteIn this project, we developed 16SPIP (16S Pathogenic Identification Process), a bioinformatics analysis pipeline that identifies pathogens in clinical samples based on 16S metagenomic sequencing results. To evaluate its utility for emergency situations, the pipeline was applied to different clinical samples for pathogen detection, and the pathogens were successfully identified to the species level.16SPIP is an integrative application that consists of a series of Perl, Python, and shell scripts, as well as next-generation sequencing (NGS) tools, including NGS QC Toolkit, Paired-End reAd mergeR (PEAR), Burrows-Wheeler Aligner (BWA), nucleotide BLAST (BLASTN), and Picard. 16SPIP accepts sequencing data (zipped or unzipped) from 454, Illumina and Ion torrent platforms in various formats, such as FASTQ, FASTA, SFF, SAM, and BAM, and data from multiple samples can be run in parallel to support rapid analysis. Figure All sequences with confirmed taxonomic relationships and read lengths ranging from 1200 bp to 2000 bp were selected from public 16S rDNA databases, such as Ribosomal Database Project (RDP)  and Nati16S pathogen database is a sub-database of the 16S full-length reference database. It was constructed from 29,258 total reads covering 346 bacterial species of human health concern in “The Directory of Pathogenic Microorganisms in Human Infections” published by the Ministry of Health of the People’s Republic of China. This 16S pathogen database was used for alignment in the fast mode of 16SPIP.16SPIP can determine the file format of raw NGS data. Picard  and the 16SPIP can process NGS data obtained from both single-read and paired-end sequencing. For paired-end sequencing data, R1 and R2 reads from raw NGS sequence were processed according to the above-mentioned methods. Two high-quality sequence files with overlapping paired-end reads were then merged using PEAR . For NGS16SPIP provides both fast and sensitive modes for analysis. In fast mode, the BWA-MEM algorithm  was used−10 to 10−20). The strain information for the reference sequence for each mapped read with greater than 97% similarity was analyzed. Based on the results obtained in the previous step, scores were assigned to samples that could contain pathogens. Higher scores indicate a higher probability that pathogens are present.In order to avoid the misidentification of bacterial species owing to short sequence reads or those with high similarity, a two-step algorithm was used in the sensitive mode of 16SPIP during the bacterial identification process. In the first step, the BWA-MEM algorithm  was usedThe operation of 16SPIP is illustrated in a practical example below. On November 8, 2016, a pus sample from a patient with a hand infection in a Beijing hospital was collected using a sterile cotton swab and sent to our laboratory for culture. A Qiagen kit  was used to extract DNA, and the V3-V4 regions of the 16S gene were amplified. The MiSeq platform was used to perform paired-end 250 bp (PE250) sequencing. A total of 1,948,892 raw reads were generated. Quality control procedures and paired reads merge after the remaining 1,928,129 reads for subsequent analysis. 1,928,016 reads can mapped to 16S reference genome for pathogen classification and identification.Streptococcus agalactiae. The operation time required for data analysis using the sensitive mode of 16SPIP was 6 h, and Lactobacillus iners, S. agalactiae, and Lactobacillus jensenii were detected. In addition, 16S gene amplification and full-length sequencing of positive cultures in the laboratory confirmed the presence of S. agalactiae on the third working day and L. jensenii on the sixth working day.The fast mode of 16SPIP (default parameters) was used to perform analysis based on the 16S metagenomic sequencing data. The processing time for the entire procedure, including data quality control, merging, alignment, statistical analysis, and the generation of the test report, was 2 h and 32 min. The final results indicated the detection of S. agalactiae was positively identified using all three methods. Previous studies have reported that S. agalactiae is related to human health; therefore, it was confirmed as the pathogen-causing infection in this case.In a comparison among the 16SPIP fast mode, 16SPIP sensitive mode, and laboratory cultures, S. agalactiae represented 6.825% of the 13.4 Gb of sequencing data. These data also supported the test results generated from the fast mode of 16SPIP, where the bacterial taxon was positively detected in the sample.In order to validate the reliability of the 16SPIP test results, WGS metagenomic sequencing was conducted using the same sample. The genomic sequence of L. iners and L. jensenii. L. jensenii was confirmed in the laboratory culture results. The missed detection of L. iners can probably be attributed to false-negative results in laboratory cultures. From another perspective, these results demonstrated the comprehensiveness of the 16SPIP test results. Figure The sensitive mode of 16SPIP also detected the presence of Owing to recent advances in NGS technology and the reduced cost of sequencing, 16S metagenomic sequencing has emerged as one of the most promising strategies for the detection of pathogens in clinical samples. However, the lack of professional bioinformatics analysts in most laboratories has limited the extensive use of 16S metagenomic sequencing for pathogen identification in clinical settings. Our goal was to establish a one-click analysis pipeline for pathogen identification in complex samples using 16S metagenomic data to provide a rapid and accurate tool for clinicians and the Centers for Disease Control and Prevention (CDC) staff.16SPIP is a comprehensive analysis pipeline with multiple integrated parts for the conversion of the data format, quality control, sequence filtering, rapid alignment, generation of the report, and other processes. It was designed with two analysis modes  to enable usage under different working environments. In emergency situations, fast mode can be prioritized and combined with clinical symptoms to quickly screen for 346 pathogens associated with human health. If users want to identity the existence of other species as well as to study the population diversity of microbiome, the sensitive mode is the better choice.https://github.com/jjmiao1314/16sPIP.git). Besides the local version, the web version of 16SPIP is available for academic users (http://16spip.mypathogen.cn/).With the support of the China CDC database, the accuracy of the analysis pipeline was validated in multiple practical cases. The source code of 16SPIP has been released on Github (


Presynaptic and postsynaptic neurotoxins are two groups of neurotoxins. Identification of presynaptic and postsynaptic neurotoxins is an important work for numerous newly found toxins. It is both costly and time consuming to determine these two neurotoxins by experimental methods. As a complement, using computational methods for predicting presynaptic and postsynaptic neurotoxins could provide some useful information in a timely manner. In this study, we described four algorithms for predicting presynaptic and postsynaptic neurotoxins from sequence driven features by using Increment of Diversity (ID), Multinomial Naive Bayes Classifier (MNBC), Random Forest (RF), and K-nearest Neighbours Classifier (IBK). Each protein sequence was encoded by pseudo amino acid (PseAA) compositions and three biological motif features, including MEME, Prosite and InterPro motif features. The Maximum Relevance Minimum Redundancy (MRMR) feature selection method was used to rank the PseAA compositions and the 50 top ranked features were selected to improve the prediction accuracy. The PseAA compositions and three kinds of biological motif features were combined and 12 different parameters that defined as P1-P12 were selected as the input parameters of ID, MNBC, RF, and IBK. The prediction results obtained in this study were significantly better than those of previously developed methods. Presynaptic neurotoxins are commonly called β-neurotoxins. These neurotoxins act on the plasmatic membranes of nerve endings, promote the generation of interterminal signals, and lead to a massive stimulation of the release of the neuromediator4. Presynaptic neurotoxins are rich sources of phospholipases9 and produce neuromuscular blockade by inhibiting the release of acetylcholine from the presynaptic membrane10. Postsynaptic neurotoxins are commonly called α-neurotoxins13, and most of these neurotoxins are from the venoms of snakes of families. Postsynaptic neurotoxins bind specially to the nicotinic acetylcholine receptor resulting in the prevention of nerve transmission, leading to death from asphyxiation17. Due to postsynaptic neurotoxins have similarity action to the reversible acetylcholine receptor antagonist curare with curare-mimetic toxins, there are often referred to as “curare-mimetic toxins”5. These two neurotoxins contribute to the understanding of the molecular steps of neurotransmission, and have potential use in cell biology and neuroscience research as well as therapeutics in some human neurological disorders. For example, presynaptic neurotoxins have been used for the treatment of migraine headache and cerebral palsy18. With the numerous of neurotoxin sequences generated in the post-genomic era, it is desired to develop a method for identification of neurotoxins for basic research and drug discovery.Neurotoxins can be divided into presynaptic and postsynaptic neurotoxins based on their mechanism of action20. The neurotoxins and bacterial toxins derived from Swiss-Prot were predicted by Feed-forwarded Neural Network (FNN), Partial Recurrent Neural Network (RNN) and Support Vector Machine (SVM)23. Four kinds of conotoxin superfamilies for 116 conotoxin sequences were predicted by ISort predictor, Least Hamming, Multi-class SVMs, one-versus-rest SVMs24, modified Mahalanobis discriminant25, and dHKNN26. Four conotoxin superfamilies for 261 conotoxin sequences that collected from Swiss-Prot were predicted by SVM27. In our previous work, based on the Animal Toxin Database (ATDB)29, the presynaptic and postsynaptic neurotoxins were predicted by Increment of Diversity (ID)30, and the correlation coefficient (CC) value was 0.7963 when evaluated by the jackknife test.In recent years, many computational algorithms have been developed for analyzing and predicting toxins. Short animal toxin and toxin-like protein sequences can be predicted by the web-based classifier ClanTox31, Prosite motif features32 and InterPro motif features33 were used to represent the protein sequences. The Maximum Relevance Minimum Redundancy (MRMR)35 was used to rank the features for improving the performance of the predictors. When these algorithms were applied to the neurotoxin dataset with 78 presynaptic neurotoxins and 69 postsynaptic neurotoxins, the overall success rates obtained by the jackknife test were significantly higher than those of existing classifier on the same dataset. In addition, as demonstrated by a series of recent publications43 in compliance with Chou’s 5-step rule44, to establish a really useful sequence-based statistical predictor for a biological system, we should follow the following five guidelines: (a) construct or select a valid benchmark dataset to train and test the predictor; (b) formulate the biological sequence samples with an effective mathematical expression that can truly reflect their intrinsic correlation with the target to be predicted; (c) introduce or develop a powerful algorithm (or engine) to operate the prediction; (d) properly perform cross-validation tests to objectively evaluate the anticipated accuracy of the predictor; (e) establish a user-friendly web-server for the predictor that is accessible to the public. Below, we are to describe how to deal with these steps one-by-one.In this study, four algorithms were proposed for predicting presynaptic and postsynaptic neurotoxins by using Increment of Diversity (ID), Multinomial Naive Bayes Classifier (MNBC), Random Forest (RF), and K-nearest Neighbours Classifier (IBK). Pseudo amino acid (PseAA) compositions, MEME motif features45 was used to provide the phylogenetic trees of presynaptic and postsynaptic neurotoxins, only the neurotoxins that had the signal peptides were uploaded to the MEGA software for generating phylogenetic trees. The phylogenetic trees for presynaptic and postsynaptic neurotoxins were shown in Fig. In this study, the Molecular Evolutionary Genetics Analysis (MEGA) softwareIn 78 presynaptic neurotoxins, PS00118 was conserved in 29 sequences and PS00119 was conserved in 31 sequences. PS00118 is a pattern of phospholipase A2 histidine active site which is centered on the active site histidine and PS00119 is a pattern of phospholipase A2 aspartic acid active site which is centered on the active site aspartic acid. Both PS00118 and PS00119 contain three cysteines that involved in disulfide bonds. PS60004 belongs to PROSITE documentation PDOC60004 which is a pattern of omega-conotoxin family signature, and appears in 19 presynaptic neurotoxins. Omega conotoxins are calcium channel blockers and the cysteine arrangement [C-C-CC-C-C] is included in PS60004. PS00280, PS01138, PS01186, PS60015, PS60021, PS60022, PS60023 and PS60025 are also observed in presynaptic neurotoxins. PS00272 is a pattern of snake toxin signature and observed in 49 sequences. Snake toxins are a group of short and long neurotoxins, cytotoxins, short toxins and miscellanous venom peptides. Snake toxin signature includes four conserved cysteines and a conserved proline is thought to be important for the maintenance of the tertiary structure. The second cysteine in this pattern is linked to the third cysteine by a disulfide bond. PS60014 is a pattern of alpha conotoxin family signature and appears in 8 postsynaptic neurotoxins. This pattern includes a common part of the cysteine arrangement [CC-C-C], four conserved cysteines are believed to be important for the maintenance of the tertiary structure of alpha conotoxins.The comparison of MEME motifs Fig.  with ProIn order to investigate the influence of different parameters on the prediction quality, 12 different parameters were selected as the input parameters of ID, MNBC, RF, and IBK. The jackknife test results obtained by ID, MNBC, RF, and IBK with 12 different parameters were shown in Tables 30. For prediction of presynaptic and postsynaptic neurotoxins, based on the same input parameters, generally speaking, MNBC had the best prediction quality among four algorithms. For example, based on the parameters of P1, P2, P3, P4, P7, P8 and P12, the CC values were 0.8227, 0.8361, 0.8497, 0.8635, 0.8932, 0.9080 and 0.9208 for MNBC, which were 0.0264, 0, 0.0270, 0.0138, 0.0146, 0.0126 and 0.0147 higher than those of ID. The overall accuracies obtained by MNBC were better than or equivalent to those of ID, RF and IBK when using the same parameters. These results clear indicated that MNBC could perform better than three other algorithms for prediction of presynaptic and postsynaptic neurotoxins.In this study, when using P12 as the input parameters of ID, MNBC, RF, and IBK for predicting presynaptic and postsynaptic neurotoxins, the overall accuracy of 95.92% and the CC value of 0.9208 were obtained by MNBC and RF, which were the highest overall accuracy and CC value in this study, and were also higher than the predictive results in our previous workBased on the same algorithm, it was clear that the performances were improved when sequence derived features and motif features were used as input parameters, when compared with other sequence derived features. For ID, when using P2, P3, P4, P5 and P6 as the input parameters, the CC values were 0.8361, 0.8227, 0.8497, 0.8497 and 0.8635, respectively, which were higher than the CC value obtained by P1. Similarly, the higher CC values could also be obtained by MNBC, RF and IBK when using the same parameters. In addition, we found that the predictive results obtained by 19 motifs (13 Prosite motifs and 6 MEME motifs) were better than those obtained by 13 Prosite motifs or 6 MEME motifs in most cases. These results clearly illustrated that the MEME motifs, Prosite motifs and InterPro motifs could significantly improve the predictive power of ID, MNBC, RF and IBK for predicting the presynaptic and postsynaptic neurotoxins.In this study, the prediction performance was improved by the effective feature selection method when using the same algorithm. Tables For the problem of presynaptic and postsynaptic neurotoxins prediction, as shown in Tables As shown Tables In this paper, in order to predict presynaptic and postsynaptic neurotoxins, 12 different parameters were selected as the input parameters of ID, MNBC, RF, and IBK. The prediction results of the jackknife test were shown in Tables 30, for using the same dataset, 78 presynaptic neurotoxins and 69 postsynaptic neurotoxins were predicted by Increment of Diversity (ID), the highest Sn, Sp and CC obtained in our previous work were 88.46%, 92.00% and 0.7963 for presynaptic neurotoxins, and were 91.30%, 87.50% and 0.7963 for postsynaptic neurotoxins, respectively. In this study, we found that, the best Sn, Sp and CC were 100.0%, 92.86% and 0.9208 for presynaptic neurotoxins, and were 91.30%, 100.0%, and 0.9208 for postsynaptic neurotoxins, respectively. Based on these results, we can conclude that the prediction algorithms presented in this study had some advantage over the previous one.In our previous work46 and demonstrated in a series of recent publications54, user-friendly and publicly accessible web-servers represent the future direction for developing practically more useful methods that will significantly enhance their impacts55, we shall make efforts in our future work to provide a web-server for the analysis method presented in this paper.With the increased number of toxins in the public dataset, it is indispensable to develop some reliable methods for classification of presynaptic and postsynaptic neurotoxins. In this study, ID, MNBC, RF, and IBK were applied to classify presynaptic and postsynaptic neurotoxins, a new promising feature representation method was presented by embedding PseAA compositions, MEME motif features, Prosite motif features and InterPro motif features to represent a protein sample. The MRMR feature selection method was also used to select 50 top ranked PseAA compositions to improve the predictive results. In order to obtain the best performance of the proposed algorithms, different kinds of motif features and PseAA compositions were combined and selected as the input parameters of four algorithms. The predictive results presented in this study clearly indicated: (1) MRMR feature selected method, complemented with motif features can significantly improve the prediction quality of neurotoxins; (2) using different parameters would make it possible for algorithms to perform better than the others. The best prediction results were obtained when using 50 PseAA compositions, 46 InterPro motif features and 6 MEME motif features as the input parameters of MNBC and RF. In summary, the above results indicated that ID, MNBC, RF and IBK by using 50 PseAA compositions and biological motif features as the input parameters were reliable for prediction of presynaptic and postsynaptic neurotoxins. We hope that the machine learning algorithms will provide some support for the identification of neurotoxins in the future. The proposed algorithms may become the useful tools in bridging the gap between the huge number of toxins in the public databases and the relatively less number of toxins that have been functionally characterized. As pointed out in Shen and Chou30. The protein sequences in this dataset were downloaded from the Animal Toxin Database (ATDB)29. The PISCES57 was used to cull the presynaptic and postsynaptic neurotoxin sequences where no two proteins in each dataset had more than 80% sequence identify. In the final dataset, presynaptic neurotoxin dataset consists of 78 protein sequences, and postsynaptic neurotoxin dataset consists of 69 protein sequences.The dataset generated by Yang and Li was used to estimate the effectiveness of the new prediction methods58, Multinomial Naive Bayes Classifier (MNBC), Random Forest (RF), and K-nearest Neighbours Classifier (IBK) were used to classify the presynaptic and postsynaptic neurotoxins. The ID algorithm was implemented in the C++ software while the rest of the algorithms were implemented in the Weka package59.In this study, Increment of Diversity (ID)71, and can be generated by a series powerful webservers developed recently. In this study, according to the concept of the Chou’s PseAA compositions74, 400 dipeptide compositions were selected as the parameters of our approaches, which were defined in 400-dimension (400-D) space, formulated as:yi  was the absolute occurrence frequencies of 400 dipeptides.It is very important to select a set of reasonable parameters for protein sequences prediction. As mentioned in previous works, pseudo amino acid composition (PseAAC) is a widely used approach for representation of protein sequences35 was applied on 400 PseAA compositions. After considering both the predictive accuracy and the MRMR score, the top 50 features were selected as the input parameters of the machine learning algorithms, which were defined in a 50-dimension (50-D) space, formulated as:In this study, MRMR31. The maximum motif number was set to 3 and the maximum motif length was set to 15. The logo format and the regular expression of these motifs were shown in Fig. In this study, the presynaptic and postsynaptic neurotoxin datasets were uploaded to MEME software to conduct motif search32 were found in 78 presynaptic neurotoxin sequences and 2 kinds of Prosite motifs were found in 69 postsynaptic neurotoxin sequences. The total number of motif features was 13. Consequently, each protein sequence was converted into a 13-dimension (13-D) space, formulated as:In this study, 11 kinds of Prosite motifs33. In this study, 78 presynaptic neurotoxin sequences and 69 postsynaptic neurotoxin sequences were scanned by InterPro, and 46 functional motifs were found in the neurotoxin datasets. The total number of motif features was 46. Consequently, each protein sequence was converted into a 46-dimension (46-D) space, formulated as:InterPro is an integrated database of protein families, domains and functional sitesIn order to improve the prediction accuracy, 400 PseAA compositions, 50 PseAA compositions, 13 kinds of Prosite motifs, 6 kinds of MEME motifs and 46 InterPro motifs were combined. Because the Prosite motifs were contained in the InterPro motifs, so 13 Prosite motifs were not combined with 46 InterPro motifs. P1-P12 indicated 12 kinds of parameters, and these parameters were selected as the input parameters of ID, MNBC, RF, and IBK (Table In this study, in order to roundly estimate the accuracy of our predictor, the sensitivity, specificity, correlation coefficient and overall accuracy were also calculated:75 and system medicine76, a completely different set of metrics as defined in work of Chou77 is needed. In order to take the advantage of using the Chou’s intuitive set of metrics for studying protein signal peptide cleavage site82, the TP, TN, FP, and FN can be represented as follows:The set of metrics is valid only for the single-label systems. For the multi-label systems whose existence has become more frequent in system biologyN+ denoted the total numbers of the positives, N− denoted the total numbers of the negatives, Substituting Eq.  into Eq.