Introduction. Treatment of breast cancer includes surgery, drugs (hormone therapy and chemotherapy), and radiation. A discussion of eight drug constructs for the treatment of breast cancer, derived through application of in silico optimized molecular properties and substituent substitution, are analyzed using pattern recognition techniques. Methods and Materials. Determined properties of these eight compounds (inclusive of doxorubicin) showed a Log P varying from 0.567 to 4.137, rotatable bonds from 5 to 12, polar surface area from 195.1 A2 to 206.1 A2, and water solubility from 0.00873 mg/L to 390 mg/L. Analysis of similarity (ANOSIM), hierarchical cluster analysis, and neighbor-joining cluster analysis elucidated relationships among the drugs that are useful for pharmaceutical consideration. Results and Discussion. Although the new derivatives share the same parent scaffold (doxorubicin), elucidation by analysis of similarity (ANOSIM) indicates that these assorted compounds are substantially distinct. The number of oxygen and nitrogen atoms (hydrogen bond acceptors) remained constant at 12 for compounds. Although violations of the Rule of five remained constant at three for all compounds, the variation of Log P and water solubility offers potentially beneficial medicinal activity for this group of anticancer agents that may enhance the antitumor activity of these anthracycline antibiotics. Hierarchical cluster analysis results clearly differentiated the parent doxorubicin from all higher molecular weight analogs. This outcome is confirmed with the use of neighbor-joining cluster analysis. Conclusion. By utilizing in silico optimization with pattern recognition analysis, potentially advantageous analogs can be elucidated from known effective pharmaceuticals. There are various types of breast cancer that will have different levels of proliferation, aggressiveness, and genetic constitution. The survival rate from breast cancer varies depending on these three factors. Treatment includes combinations of the following: surgery, drugs including hormone therapy, chemotherapy, and targeted therapies, and radiation therapy. Doxorubicin is an anthracycline antibiotic that does inhibit the proliferative growth of bacteria but is not applied in that clinical treatment due to the substantial level of toxicity to human physiology .  The anthracycline antibiotic doxorubicin is utilized for the clinical treatment of other cancers such as hematological malignancies, various carcinomas, and soft tissue sarcomas –3. The d Utilizing doxorubicin in combination with paclitaxel for the treatment of metastatic breast cancer produces beneficial outcome with over 90% response rate . The pro Other studies have shown that the application of doxorubicin in liposomal form may reduce toxicity usually associated with anthracyclines . The use The investigation of novel designs of anthracycline antibiotics may benefit therapeutic approaches to the treatment of breast cancer. Presented here is the application of in silico optimization with pattern recognition analysis to improve pharmaceutical activity of already proven antineoplastic compounds. Numerical values of properties and molecular modeling was accomplished utilizing ACD/ChemSketch modeling v. 10.00 . Other properties: polar surface area, violations of Rule of 5, molecular volume, number of oxygens, nitrogens, amines, hydroxyls, and so forth were determined using Molinspiration . In silico structure search for substituent replacement was accomplished using Chemical substructure and similarity search with MolCart Chemical Data Base .  To identify underlying associations/patterns within the properties, numerical matrix required the use of various pattern recognition techniques. Included in the analysis is hierarchical cluster analysis accomplished by KyPlot v. 2.0 Beta 15 (Koichi Yoshioka 1997–2001). Neighbor-joining cluster analysis and ANOSIM  accomplished by PAST v. 1.80 . r was done for some descriptors and was accomplished by GraphPad Software .Statistical analysis of all numerical data was performed by Microsoft EXCEL . Correlation analysis by Pearson  The parent doxorubicin molecular structure as well as the derivatives formed from that scaffolding are shown in P . The number of oxygen and nitrogen atoms (hydrogen bond acceptors) remains constant at 12 throughout this assortment of compounds. Molecular descriptors for doxorubicin and the derivatives considered here were determined and presented in  Outcome of cluster analysis of compounds shown in  Analysis of similarity (ANOSIM) indicates these assorted compounds are substantially distinct from doxorubicin.P, formula weight, and hydrogen bonding activity to the effectiveness of druglikeness. Examination or screening of many potential drug candidates is possible by statistical comparison to already proven but related medicinal compounds. This approach of screening drug candidates improves the success rate for selection to drug trials and eventual full development. Alteration of substituents on the molecular structure of biologically active agents has been shown to have substantial effects on the pharmaceutical properties . SubstitP, formula weight, and hydrogen bonding activity are taken to be some multiple of the numeric value of five. Specifically, the criteria impute that violation of two or more of the parameters would signal problems in drug bioavailability. These criteria include the following [P value of less than 5; (2) a formula weight less than 500 grams/mole; (3) no more than 10 hydrogen bond acceptors (oxygen and nitrogen atoms); (4) no more than 4 hydrogen bond donors (–OH and –NHn). Doxorubicin is a molecule that intercalates the DNA molecule by way of the planar aromatic chromophore portion of the molecule and with the daunosamine sugar resting in a minor groove with accompanied interaction on the flanking base pairs [One very successful screening method is known as the Rule of 5, in which Log ollowing : 1) a L a LP, foms/mole;  no more 2)5CH3 or –(CH2)6CH3) [P, formula weight, rotatable bonds, molecular volume, and water solubility. Homologous series of compounds have a particular advantage of having predictable properties, and extensive studies have shown that as the numeric series increase the medicinal activity also increases to a maximum of six or seven carbon chain length (–(CHH2)6CH3) . Lengthe2, a value that does not facilitate intestinal absorption [ Molecular descriptors for doxorubicin and the derivatives were determined and are presented in sorption . r for these descriptors reveals that Log P is directly correlated (r > 0.9500) to molecular weight, number of rotatable bonds, and molecular volume . Log P is inversely correlated to polar surface area, number of –OH and –NHn (hydrogen bond donors), and water solubility.  Water solubility of drug B is substantially higher at 390 mg/Liter than that of doxorubicin itself at 92.84 mg/Liter. This is apparently due to the substitution of a primary amine group with an imine group that is covalently bonded to the daunosamine sugar see . As the P which are 2 ± 0.7 indicate the drug can penetrate the central nervous system [P value of 1.35 favors intestinal absorption, fulfilled by drug B. Colonic absorption is enabled by a Log P value of 1.32 [P value between 3 and 4 promotes transdermal administration, fulfilled by drugs G and H.  Previous studies have demonstrated that values of Log s system ; this cr of 1.32 , fulfill Hierarchical cluster analysis is a pattern recognition method that sorts the subjects (drugs here) into groupings that follow criteria set by the investigator where the highly similar , elucidation by analysis of similarity (ANOSIM) indicates that these assorted compounds are substantially distinct from doxorubicin. The ANOSIM outcome R is calculated to be 1.000 (Euclidean distance measure). This value asserts that all compounds studied here are distinct from the parent scaffolding of doxorubicin. Albeit this conclusion discernable by inspection of some descriptor numerical values, this algorithm confirms that drugs B, C, D, E, F, G, H, and I can be expected to express differentiation in pharmaceutical activity and medicinal action in the treatment of breast cancer.2OH terminus [ Previous studies have shown that substitutions on the sugar moiety (C-3′ position) will produce agents that express antitumor activity . Other wterminus . These sterminus . It follP values that result suggests an improved potential for drug B (imine derivative) to accomplish intestinal absorption and colonic absorption. A Log P value between 3 to 4 promotes transdermal administration, fulfilled by drugs G and H. For homologous series C, D, E, F, G, H, and I, the increasing length of the aliphatic alkoxy substituent increases the lipophilicity (thereby increasing Log P), increases molecular volume, and increases formula weight, but decreases water solubility. Violations of the Rule of 5 remain at three for all compounds. Modifications in the structure of doxorubicin vary the Log P property and potentially change the biological activity of these anthracycline antibiotics. In summation, eight derivatives of doxorubicin were elucidated from the parent molecular structure of doxorubicin. By developing derivatives of doxorubicin, the Log


Iron deficiency anaemia represents a major public health problem, particularly in infants, young children, pregnant women, and females with heavy menses. Oral iron supplementation is a cheap, safe, and effective means of increasing haemoglobin levels and restoring iron stores to prevent and correct iron deficiency. Many preparations are available, varying widely in dosage, formulation (quick or prolonged release), and chemical state (ferrous or ferric form). The debate over the advantages of ferrous versus ferric formulations is ongoing. In this literature review, the tolerability and efficacy of ferrous versus ferric iron formulations are evaluated. We focused on studies comparing ferrous sulphate preparations with ferric iron polymaltose complex preparations, the two predominant forms of iron used. Current data show that slow-release ferrous sulphate preparations remain the established and standard treatment of iron deficiency, irrespective of the indication, given their good bioavailability, efficacy, and acceptable tolerability demonstrated in several large clinical studies. Iron deficiency anaemia (IDA) is the condition in which there is anaemia due to a lack of iron. IDA develops when available iron is insufficient to support normal red cell production and is the most common type of anaemia .According to the World Health Organisation (WHO) , iron deCommon causes of iron deficiency include inadequate intake of dietary iron, inadequate iron utilisation during chronic and inflammatory diseases, impaired iron absorption, or excess iron loss. In the vast majority of cases, the cause of iron deficiency anaemia results in an anaemia that is both avoidable and reversible by increasing iron supplementation or reducing iron loss.Iron is essential for oxygen transport and cell growth and survival. The typical adult human body contains an average of 3.5 g of iron . Most of the iron within the body is used in haemoglobin (2.1 g). A small amount is devoted to cellular protein synthesis  or circulates through plasma bound to transferrin . Iron ho2+) prior to uptake by intestinal enterocytes [To maintain adequate supplies of iron for heme synthesis, 20 mg of iron is recycled daily, going from senescent red cells that are removed from the circulation to new cells in the bone marrow . Iron frerocytes . Around erocytes .For the treatment of iron deficiency anaemia, current guidelines recommend the dose of 60 to 120 mg of elemental iron of ferrous sulphate per day for a minimum duration of 3 months in adolescents and adults, including pregnant women , most inIn the case of iron deficiency anaemia, once the underlying cause has been identified and treated, iron replacement therapy is necessary to correct haemoglobin levels and replenish iron stores. From a practical point of view, the oral route is the first choice to replace iron stores as this allows the normal mechanism of absorption to be used and thus may prevent complications and the risk of iron overload, such as is reported with intravenous iron administration, in addition to being an inexpensive and effective treatment. Many oral iron preparations are available, the most frequently used being ferrous sulphate (FS) and ferric preparations with an iron polymaltose complex (IPC). Most of these preparations vary in their bioavailability, efficacy, side effects, and cost. Here we review the data available in the literature with regard to the efficacy and tolerability of ferric and ferrous preparations currently used in clinical practice, and especially sustained-release FS versus IPC which are among the most prescribed iron formulations in the world.The iron-containing preparations available on the market vary widely in dosage, salt, and chemical state of iron (ferrous or ferric form) contained in the preparation, as well as the galenic form (quick and prolonged release). However, in clinical practice bivalent iron salts such as FS, ferrous gluconate, and ferrous fumarate are more widely used and are preferred over ferric iron preparations , 18, as ®, a prolonged-release ferrous sulfate tablet containing 80 mg of elemental iron. In this product a polymeric complex surrounds Fe2+ ions forming a matrix that controls the availability of Fe2+ ions to the individual sections of the gastrointestinal tract in conformity with their absorptive capacity. After its absorption, iron levels in the blood reach a maximum after about 7 hours and remain elevated for 24 hours. In a study conducted by Kaltwasser et al. [® was compared to that of a quick-release ferrous ascorbate preparation in 18 healthy phlebotomized volunteers, using a stable 54Fe iron isotope. The study did not find any difference in iron intestinal absorption measured on day 21 between the two preparations. Moreover, after two months of treatment, haemoglobin levels increased to approximately baseline values in both treatment groups.Advances in oral preparation have led to the development of prolonged-release preparations with new galenic formulations that may improve gastrointestinal tolerability and enhance the bioavailability. Among these compounds, the most studied and prescribed is Tardyferonr et al. , the bio®/Ferrum Hausmann®/Ferranina® is a trivalent oral iron (100 mg of element iron) coupled with sugar complexes (IPC). This structure is believed to give the ferric iron compound a better stability and portability of ferric iron ions through the intestinal mucosa under physiological conditions, compared to conventional ferric compounds [P < 0.01). Maltoferompounds . While sompounds –25, manyompounds –30. Mehtompounds . In 2003ompounds  publishe59Fe III hydroxide-polymaltose compared to that of 59Fe labeled-bivalent iron preparations (ferrous ascorbate or a quick-release FS preparation). Intestinal iron absorption in the fasting state, as measured by 59Fe whole body retention and simultaneous estimation of plasma iron tolerance curves, was low for the Fe III complex (1.2 ± 0.1%) as compared to ferrous ascorbate (43.7 ± 7.1%). After a meal, the absorption of the divalent preparation was not affected, whereas that of the Fe III complex increased to 8.8 ± 4.7%. However the daily increase in haemoglobin concentrations after an equivalent therapeutic dose of 100 mg elemental iron during 28 days was greater for the divalent preparations compared to the Fe III hydroxide-polymaltose complex (1.1 ± 0.3 g/L versus 0.68 ± 0.2 g/L). Similar observations were reported by Malhotra et al. [μg/dL) received Tardyferon® (1 tablet/day) over 6 to 10 weeks. Significant increases in haemoglobin and ferritin concentrations were observed within this period , indicating that specific prolonged-release iron preparations may provide relatively high iron bioavailability and are effective in the treatment of iron deficiency anaemia, even in the case of chronic haemorrhage. Only one blinded, double-dummy randomised trial conducted by Langstaff et al. [®, 200 mg elemental iron/day) to standard FS preparations . Both were given to 126 adult patients during 9 weeks. FS resulted in a significantly higher increase in haemoglobin levels compared to Ferrum Hausmann® at 3 and 6 weeks. At week 9 the difference between both groups was not statistically significant.Kaltwasser et al.  also coma et al.  and Heina et al.  on the pa et al.  found noa et al. , 33 patif et al.  compared® was shown to be sufficient for recovery of iron reserves within the puerperium period, as shown by Mára et al. [Other findings concerning the lack of efficacy of IPC versus FS were reported in studies on risk groups for anaemia as children, pregnant women, and the elderly. Two large randomised trials assessed the efficacy and tolerability of iron polymaltose complex versus FS, in the treatment of iron deficiency anaemia in children. The first study  was conda et al. . In eldea et al. .Side effects of oral iron therapy are a common problem in the treatment of patients with iron deficiency. Gastrointestinal disturbances such as nausea, heartburn, pain, constipation, and diarrhoea are the most commonly reported side effects, irrespective of the type of iron preparation. This occasional intolerance is usually viewed as a limiting factor for oral iron therapy, as it may impact patient compliance. The incidence of the gastrointestinal side effects seems to be generally associated with the use of unnecessary high doses of iron as reported by several authors , 46. Hig®) had a statistically significant lower incidence of gastrointestinal events (3.7%) compared to other FS preparations (31.6%), ferrous fumarate (44.8%), and to preparations containing ferric iron such as iron protein succinylate (7.0%). The results of this study demonstrated clearly that sustained FS release preparations are better tolerated than other preparations including ferric iron preparations.Incidence of gastrointestinal side effects has been shown to be lower with controlled-release iron formulations compared to conventional ferrous salt preparations in three large controlled randomised studies –49. In s® and 14 (25%) patients in the standard FS group. The majority of events were gastrointestinal in nature: constipation was reported in 18% of patients in the Ferrum Hausmann® group versus 11% in the standard FS group and abdominal pain in 10% of patients in the Ferrum Hausmann® group versus 18% in the standard FS group.In the Langstaff et al.  study meOral iron supplementation is the standard treatment for patients with iron deficiency. Ferrous salts and in particular prolonged release FS preparations are the treatment of choice given their high effectiveness, acceptable tolerability, and low cost. Preparations with iron III hydroxide polymaltose generally display poorer bioavailability and their clinical efficacy is yet to be established. The claimed superiority of ferric iron preparations over sustained-release ferrous sulphate preparations is also questionable. Only preparations for which efficacy and tolerability have been proven should be used in the treatment of iron deficiency.


Pseudomonas savastanoi is a serious pathogen of Olive, Oleander, Ash, and several other Oleaceae. Its epiphytic or endophytic presence in asymptomatic plants is crucial for the spread of Olive and Oleander knot disease, as already ascertained for P. savastanoi pv. savastanoi (Psv) on Olive and for pv. nerii (Psn) on Oleander, while no information is available for pv. fraxini (Psf) on Ash. Nothing is known yet about the distribution on the different host plants and the real host range of these pathovars in nature, although cross-infections were observed following artificial inoculations. A multiplex Real-Time PCR assay was recently developed to simultaneously and quantitatively discriminate in vitro and in planta these P. savastanoi pathovars, for routine culture confirmation and for epidemiological and diagnostical studies. Here an innovative High-Resolution Melting Analysis (HRMA)-based assay was set up to unequivocally discriminate Psv, Psn and Psf, according to several single nucleotide polymorphisms found in their Type Three Secretion System clusters. The genetic distances among 56 P. savastanoi strains belonging to these pathovars were also evaluated, confirming and refining data previously obtained by fAFLP. To our knowledge, this is the first time that HRMA is applied to a bacterial plant pathogen, and one of the few multiplex HRMA-based assays developed so far. This protocol provides a rapid, sensitive, specific tool to differentiate and detect Psv, Psn and Psf strains, also in vivo and against other related bacteria, with lower costs than conventional multiplex Real-Time PCR. Its application is particularly suitable for sanitary certification programs for P. savastanoi, aimed at avoiding the spreading of this phytopathogen through asymptomatic plants. Pseudomonas savastanoi is a phytopathogenic bacterium, causal agent of Olive (Olea europaea L.) and Oleander (Nerium oleander L.) knot disease. Isolates from Ash (Fraxinus excelsior L.) are also included in this species, whose taxonomy and classification have been controversial for a long time. According to several phenotypic, physiological, biochemical, and molecular parameters, isolates from Olive, Oleander and Ash are now accepted as belonging to distinct pathovars, named P. savastanoi pv. savastanoi (Psv), pv. nerii (Psn) and pv. fraxini (Psf), respectively Psn was demonstrated to be capable of infecting Olive as well as Ash Psf can multiply in Olive bark when artificially inoculated P. savastanoi populations, both surviving within the young knots on diseased and symptomatic plants, and naturally resident as epiphytes on healthy and/or asymptomatic plants Psv epiphytic development and its entry into the host strictly determine the extent of damages caused by PsvP. savastanoi populations, with practices such as pruning of affected branches and the use of copper compounds. But today pruning is not such a common practice as it was in the past because of the high costs, and the effectiveness of conventional copper compounds had a sharp drop for the spread of copper-resistant isolates among P. syringae pathovars and related bacteria P. savastanoi knot diseases, sanitary certification programs for Olive and Oleander propagation materials and mother plants were already launched worldwide P. savastanoiPsv detection and identification have been available for two decades, but they are time consuming and they have very low sensitivity and specificity Psv and Psn, also working in planta and on asymptomatic tissues Psv, Psn and Psf isolates. This important limit for their routine applicability in sanitary certification programs was recently overcome by the development of a pathovar-specific, highly sensitive and quantitative Real-Time PCR procedure Conventional microbiological assays for Psv, Psn, and Psf. To our knowledge this is the first report of a HRMA-based assay developed so far for a plant pathogenic bacterium, as well as one of the few multiplex-HRMA protocols Psv, Psn and Psf, in vitro as well as in planta. This novel application of HRMA would be extremely helpful in epidemiological studies aimed to unveil the distribution in nature of these P. savastanoi pathovars on the different host plants, and to deeper investigate the genetic structure of this species, as well as to design innovative and more efficient control measures for Olive and Oleander knot disease, starting from sanitary certification programs.Here we report the development of a unique strategy, based on Real-Time PCR followed by HRMA, for the rapid, highly specific, and sensitive detection and identification of P. savastanoi strains used in this study, isolated from different hosts and having various geographical origins, are reported in P. savastanoi or ubiquitous on plants, water and soil were also tested (600) at different times during incubation, and bacterial concentrations were estimated by serial dilutions and plate counts. For long-term storage, bacteria were maintained at −20°C and −80°C on 40% (v/v) glycerol.The o tested . They weAluIP. savastanoi PCR specific assays Contaminations were periodically monitored by 16S rDNA amplification followed by enzymatic restriction with 600 = 0.8, using Gentra® Puregene kit , according to manufacturers' instructions. DNA concentration was evaluated both spectrophotometrically, with NanoDrop™ ND-1000 , and visually by standard agarose gel electrophoresis [1% agarose (w/v) in TBE 1×] g for 10 min) to pellet cell debris, 2.5 µl lysate was directly used in PCR assays as template.Genomic DNA was extracted and purified from bacterial liquid cultures at ODhttp://www.ebi.ac.uk/Tools/clustalw2) http://www.ncbi.nlm.nih.gov/blast) DNA amplicons were extracted and purified from agarose gel with PureLink® Quick Gel Extraction Kit , under the conditions recommended by the manufacturer, and double-strand sequenced at Eurofins MWG Operon Ltd . Multiple sequence alignments and comparisons were performed using the computer package CLUSTALW  Primer pairs to be used in HRM analysis were designed according to the sequencing of the entire Type Three Secretion System (TTSS) clusters of three representative Real-Time PCR was carried out on a CFX96 cycler – RealTime PCR Detection System , in white-walled PCR plates (96 wells), with 10 µl reaction mixture containing 0.5 µM of each primer, 1× SsoFast™ EvaGreen® Supermix  according to manufacter's instructions, and as template 10 ng of genomic DNA, unless otherwise specified. Cycling conditions were one cycle at 95°C for 5 min, followed by 40 cycles at 95°C for 5 s and 60° for 5 s. The amount of fluorescence for each sample, given by the incorporation of EvaGreen® into dsDNA, was measured at the end of each cycle and analyzed via CFX-Manager Software v1.6 . Melting curves of PCR amplicons were obtained with temperatures ranging from 65°C to 95°C. Data acquisition was performed for every 0.2°C increase in temperature, with a 10 s step. For each strain three batches of DNA were obtained from separate extractions performed on different bacterial cultures. Each DNA batch was then tested in three independent experiments, and analyzed by High-Resolution Melting analysis software , which automatically clusters the samples according to their melting profiles and assigns a confidence score to each sample. The confidence level threshold for a sample to be included in a cluster was 99.5%. HRM curves were normalized using the pre- and post-melting temperatures of each primer pair , automatP. savastanoi strains tested here. Each strain was then assigned to one of the six distinct SNP-groups (SGs), according to its specific “SNPs-code”, given by the concatenated bases for each of the ten SNPs analyzed, strictly ordered according to their real distribution on TTSS cluster  The HRM data were confirmed by sequencing the amplicons obtained. The distribution of the variants for each SNP marker was also assessed for all the 56  cluster . GeneticP. savastanoi with bacterial epiphytes residing on Oleander plants was in vivo evaluated. Leaves taken from adult Oleander plants (3 years old) were inoculated with a drop of a bacterial suspension of P. savastanoi in sterile saline water  with an OD600 = 0.5 (corresponding to about 0.5×108 CFU/ml), on the upper or on the lower page of the leaf. Different bacterial drop volumes  were tested. The strains used were Psv5, Psn23 and Psf134. For each treatment three replicates were performed in three independent experiments. Leaves spotted with SSW were used as negative controls. The inoculated leaves were then incubated in a moist sterile chamber, made in a Petri dish, for 30 min at room temperature. After that time each drop was separately recovered washing the leaf with 100 µl of SSW. The leaf washings were separately centrifuged at 10,000 g for 5 min, resuspending then the pellets in sterile water to be used for thermal lysis DNA extraction. As PCR template, 2.5 µl of thermal lysis solution were directly used in each reaction. Serial dilutions of pure genomic DNA (from 1 ng to 1 pg/reaction) from strains Psv5, Psn23 and Psf134 were used as positive controls to confirm the identity of each sample tested by comparing its profile to that of the closest DNA dilution .The possibility of cross-reaction events during HRM analysis on in vitro culturable and unculturable bacteria was adopted. On leaf washings from negative controls, amplification of 16S rDNA was carried out In order to ascertain the composition of the bacterial microflora epyphitically resident on the Oleander leaves sampled here, a global approach capable of identifying both in vitro micropropagated Oleander plants  artificially infected with strain Psn23. Oleander plants were grown for 3 weeks at 26°C on Murashige-Skoog medium 600 = 0.5. Negative control plants inoculated with SSW alone were also included. The infected plants were grown in the same conditions as those described above. Fourteen days after inoculation, stems (about 100 mg each) were separately removed, aseptically and finely chopped with a scalpel, and soaked for 30 min in 6 ml of SSW, with shaking (100 rpm). After that time, any plant material was removed with a sterile filter gauze, and the filtrate was centrifuged at 12,000 g for 5 min. To each bacterial pellet, 100 µl of sterile water was added. The suspension was directly thermal lysed for DNA extraction, and then used as template in HRM-PCR, as such or ten-fold diluted. The identity of each sample was confirmed as described above.The HRMA-based protocol developed here was also tested on P. savastanoi strains tested , differently distributed among the Psf strains tested here, instead of the single one that was expected (JL2)  . Similar S and V . On the Psv strains here assayed. Only five out of these ten SNP markers were able to exclusively group together Psn and Psf strains, but could not simultaneously distinguish the three pathovars from each other  and all the strains belonging to Psn and Psf. The markers C1 and V grouped the Psv strains belonging to SG I together with all the Psn strains, and the others (SGs II and III) with Psf strains. The amplicon including the two SNP markers JL1 and JL2 produced three different melting curves. One cluster was exclusive for Psn strains, one included the Psf strains belonging to SG IV, and another one clustered the remaining Psf strains (SG V) with those belonging to Psv  were coupled with those able to group Psf strains . Six different combinations were firstly tested on DNA template from the representative strains Psv5, Psn23 and Psf134.With the aim of setting up a HRM-multiplex assay able to discriminate in one step the three P. savastanoi pathovars, as demonstrated by their normalized melting curves. The couples of primer pairs for SNP markers C2/L2, C2/J, R/J, and R/L2 produced double peaked derivative melting curves. The two peaks were clearly originated from the melting of two amplicons with different melting temperatures. On the contrary, the couples of primer pairs for the SNP markers R/L1 and C2/L1 gave a single peak. Two amplicons were produced in these cases as well, but differing less than 1°C in their melting temperatures. Since multiple peak curves represent a complex pattern that may be difficult to be interpreted, further analysis were carried out only with the primers for the couples of SNPs C2/L1 and R/L1, using the 56 P. savastanoi strains reported in P. savastanoi pathovars could be consistently resolved in three clearly different curves, using all the 56 strains tested in this work, and with both the couples of primer pairs used. The same results (99.0 percent of confidence) were also obtained using ten-fold diluted DNA template from thermal lysis. If undiluted thermal lysed DNA was used, “temperature shifted” option  was applied to impose a further normalization point (data not shown). The sensitivity of this multiplex HRMA-based protocol was evaluated by testing different amounts of genomic DNA (from 10 ng to 1 fg per reaction). In Psv5, Psn23 and Psf134. Detection thresholds of 1 pg and 10 fg of DNA template were found for markers R/L1 and C2/L1, respectively. With these DNA amounts was still possible to gain distinct melt curve profiles for each of the three P. savastanoi pathovars in HRM analysis.The results obtained are shown in P. savastanoi pathovars examined here from several phylogenetically related bacteria or reported to be ubiquitously associated to plants, water and soil . Moreover, information on the culturable and unculturable bacterial epiphytes present on these Oleander leaf samples were gained. A 16S rDNA library of 384 clones was obtained using as template thermal lysed DNA from leaf washings of negative controls, as described in AluI enzyme Pseudomonas, while clones related to bacteria from genera Xantomonas (15%), Bacillus (14%), Erwinia (11%), Acinetobacter (9%) and Lactobacillus (2%) were represented to a lesser extent. Unsurprisingly more than a quarter of the sequences giving the 81 different ARDRA profiles were found highly homologous to several clones from 16S rRNA genes of unculturable bacteria. These data further supported the strong discriminative power of primer pairs for SNPs C2/L1 for the specific detection of Psv, Psn and Psf against a wide range of bacterial genera commonly associated to plants as epiphytes.The couple of primer pairs for SNPs C2/L1 was further analyzed for its potential application as an Psn strains in artificially infected in vitro Oleander plants. Psn-infected plants, compared with those produced by pure DNA from Psv5, Psn23 and Psf134 strains. No variation was ever observed in the performances of this HRMA-based assay when using as template DNA extracted from Psn-infected plants, in comparison with Psn23 pure DNA, confirming the in vivo pathovar-specificity of our multiplex HRM protocol as well. Identical plots were observed with all the Psn strains tested in this study (data not shown).The same primers combination was then used to detect The evolution of HRMA from conventional melting curves analysis is based on the development of a novel type of dye, having a higher dsDNA saturating activity than SYBR Green I, called EvaGreen®, and of a new generation of thermal cyclers, finely tuning temperature increments/decrements up to 0.1°C P. savastanoi, the causal agent of Olive and Oleander knot disease.Here for the first time we reported the successful use of HRMA on a bacterial plant pathogen, Psv, Psn, and Psf and having different geographical origins, were tested using a SNPs panel, designed according to nine loci of the TTSS cluster sequences of the three representative strains Psv5, Psn23 and Psf134. In particular, nine out of the ten SNPs interrogated here derived from the alignment of TTSS sequences of strains Psv5, Psn23 and Psf134. On the contrary one of these SNPs was discovered as a result of HRMA application on the other 53 P. savastanoi strains, whose TTSS sequences were unknown and thus tested as blind samples.A total number of 56 strains, belonging to the three pathovars P. savastanoi pathovar. However, it was never possible to simultaneously discriminate the three pathovars using a single SNP marker. This goal was achieved by developing a multiplex HRM protocol using the primers for the couples of markers C2/L1 or R/L1: for each combination of primer pairs the pathovar identification carried out on the 56 P. savastanoi strains tested here was 100% coherent with the results obtained using the highly specific Real-Time PCR assay previously set up for this bacterium Five of these SNPs generated unique HRM profiles able to group together and exclusively all the strains belonging to the same in vivo diagnostic tool for the detection of these P. savastanoi pathovars. Firstly, these primers were demonstrated to be able to specifically discriminate pure DNAs of Psv, Psn and Psf from those of several other bacteria, phylogenetically related to P. savastanoi or ubiquitous. Moreover the pathovar-specificity of this HRMA-based assay was demonstrated not to be lowered or altered by any microbial contaminant DNA that may be present on or into P. savastanoi host plants, as assessed in preliminary experiments carried out on micropropagated and adult Oleander plants, artificially and individually inoculated with Psv5, Psn23 and Psf134 strains. These data clearly demonstrated the power of our assay to overcome also one of the main problems that could be faced with HRMA, that is its limit in resolving polymicrobial infections or consortia. To this concern, the epiphytic bacteria resident on the Oleander leaf samples examined here were investigated, and the data obtained were in accordance with previous findings on P. savastanoi host plants Psv5, Psn23 and Psf134 spiked with total DNAs extracted from Olive, Oleander and Ash leaf washings (data not shown).The primer pairs for SNPs C2/L1, having the lowest LLOD, were further analyzed to evaluate the potential applicability of the multiplex HRMA protocol developed here as an P. syringae complex was explored by MLST carried out on several housekeeping genes/loci of the so called “core genome”, to assess the role of recombination events in the evolution of P. syringae related pathogens. A high level of clonality was observed within these species and five major phylogroups were identified rpoDP. syringae strains, belonging to the pathovars tomato, maculicola, apii, antirrhini, and avellanae, recombination was also found to strongly contribute to bacterial diversity P. syringae strains causing new diseases could be properly allocated into genomospecies and pathovars by MLST The detection of genetic variations phylogenetically informative is also pivotal for the analysis of the evolutionary history of a pathogen and of its populations, in order to increase the knowledge about its epidemiology. Among the methods currently available, multi-locus sequence typing (MLST) and SNP typing are those having the highest degree of specificity, sensitivity, and reproducibility, relying on the direct comparison of specific nucleotide sequences. The diversity among bacteria belonging to the P. savastanoi is concerned, no comprehensive MLST phylogeny studies were carried out so far, including the three pathovars examined here. Up to now only an extensive analysis by fAFLP was developed for these P. savastanoi pathovars As far as P. savastanoi pathovars and strains, and provided results largely coherent with those previously obtained by fAFLP analysis and even more detailed P. savastanoi species, based on laborious and skilled DNA/DNA hybridization experiments P. savastanoi hrp genes. Our preliminary data suggest it could be the ideal instrument to fully determine whether, and to which extent, the evolution of TTSS contributed to shape the differentiation of P. syringae complex, including P. savastanoi pathovars. To this concern, hrp genes were postulated to have been introduced early and by horizontal gene transfer (HGT) into a P. syringae ancestor from a still unknown enteric animal pathogen, without further significant HGT events driving the evolution of TTSS in these bacteria hrp genes likely followed the same evolutionary course of the whole genome although at a faster rate, as assessed for a broad range of genes coding for virulence associated factors that were demonstrated to evolve considerably in non-host settings as well P. syringae species a positive selection was demonstrated to act on mutations occurring on hrpA, aimed at maintaining diversity at this locus that was strongly functional in different host contexts The HRMA-based SNP typing method developed here was also demonstrated to have a high discriminatory power in resolving P. savastanoi strains and other P. syringae species, this method would provide a more rapid and economic tool to identify the evolutionary relationships among bacteria belonging to the P. syringae complex, in comparison to other more expensive sequence typing approaches used so far If the phylogenetic discriminative potential of this HRMA-typing protocol was confirmed by examining a larger number of P. savastanoi developed here, working both in vitro and in planta to easily discriminate and detect Psv, Psn and Psf strains, can facilitate and promote high-throughput screenings aimed at revealing important epidemiological data and trends of this species, such as host range, temporal or geographical tendencies and other fundamental observations related to pathogenicity/virulence. Besides the intrinsic high relevance of these epidemiogical findings, these data would also strongly affect the management of the diseases that P. savastanoi causes, helping to correctly calibrate preventive disease control measures concerning this phytopathogen. Since HRMA can be performed in a rapid, economical and convenient way, it could be easily applied in routine identification of P. savastanoi pathovars in plant propagation materials, by a simple high-throughput process.HRMA is a low-cost identification method compared to other diagnostic assays because no labeled expensive probes or specialized reagents are required, but just generic PCR primers and a high saturating dsDNA dye are needed. Hence, the pathovar-specific HRMA-based protocol for Figure S1Alignment of TTSS cluster sequences of Psv5, Psn23 and Psf134, location of SNPs and primers. Annealing sites for the nine primers pairs are underlined. Primer directions are indicated by black arrows. SNPs are highlighted in red and the SNP marker name is reported in capital letter. Position of SNP marker JL1 is highlighted in yellow.(PDF)Click here for additional data file.Figure S2Difference HRM plots for all the SNPs screened in the study. Difference HRM plots of the amplicons obtained from the 56 P. savastanoi strains using the nine primer pairs. For each amplicon, the corresponding SNP marker is reported on the upper-right corner of the plot. Different colors are used to indicate distinct profiles, corresponding to the HRMA-based clustering of the 56 P. savastanoi strains into pathovars or SGs. RFU: Relative fluorescence units.(TIFF)Click here for additional data file.Figure S3etting up of multiplex HRMA assay. Normalized plots and derivative melting peaks obtained in multiplex HRM assay design, using six duplex combinations of the primer pairs referred to the SNP markers reported on each plot. Pure genomic DNAs (10 ng) of representative strains Psv5, Psn23 and Psf134  were separately used as templates. RFU: Relative fluorescence units. Green and red columns represent pre- and post-melting normalization regions.S(TIF)Click here for additional data file.Figure S4Evaluation of Lower Limit of Detection (LLOD) of the multiplex HRMA assay. Normalized and difference HRM plots obtained with the combinations of primer pairs for SNP markers R/L1 (upper plots) and C2/L1 (lower plots), using the lowest detectable quantity of DNA template . On each plot red, green and blue traces were produced by Psv5, Psn23 and Psf134, respectively. RFU: Relative fluorescence units. Green and red columns represent pre- and post-melting normalization regions.(TIF)Click here for additional data file.Figure S5HRMA multiplex assay on bacteria related to P. savastanoi. (A) Normalized melting curves obtained by using as template pure DNAs (10 pg/reaction) extracted from bacteria closely related to P. savastanoi  Magnification of black-squared area in (A).vastanoi , and the(TIFF)Click here for additional data file.Figure S6Specificity of multiplex HRM assay for P. savastanoi pathovars detection tested against Oleander epiphytes. Normalized and difference HRM plots obtained by multiplex HRM assay performed with the combination of primer pairs for SNP markers C2/L1. Washings from Oleander leaves artificially surface-inoculated with Psv5, Psn23 and Psf134 were used for thermal lysis extraction of DNA, to be used as template. Bacterial suspension drops of 5 µl (upper plots) and 50 µl (lower plots) were spotted on each leaf side. Pure genomic DNAs from Psv5, Psn23 and Psf134 were also tested as controls. On each plot red, green and blue traces were produced by Psv5, Psn23 and Psf134, respectively. RFU: Relative fluorescence units. Green and red columns represent pre- and post-melting normalization regions.(TIF)Click here for additional data file.Table S1Bacteria related to P. savastanoi or ubiquitous used in this study.(DOC)Click here for additional data file.Table S2Identification of epiphytic bacterial genera present on Oleander leaf washings using 16S rDNA gene sequencing, according to BLAST analysis.(DOC)Click here for additional data file.


Twenty-seven field samples that showed positive in PEDV detection were collected from different farms of Fujian province from 2010 to 2012. Their heterogeneity was investigated by analysis of the ORF3 gene because of its potential function as a representation of virulence. According to the results, six Fujian strains in Group 1 showed a different genotype with unique point mutations, which might be used in differentiation between PEDV groups and brought potential antigenic variation. P55 and five reference strains in Group 2 had a long length deletion, showing another genotype and might be involved in the variation of virulence. Phylogenetic analysis revealed that the collected Fujian strains were very distant from the vaccine development strain CV777, which might be the reason why the vaccine was inefficient to control the disease. The results can help to reconsider the strategy of PEDV vaccine management and prevent outbreaks of PEDV-induced diarrhea more efficiently.  Porcine epidemic diarrhea virus (PEDV) causes severe entero-pathogenic diarrhea in piglets, especially in neonates, and the disease has a high mortality rate which can reach 80% in certain situations . The disCoronaviridae [PEDV is an enveloped, single-stranded RNA virus belonging to the family aviridae ,10,11. Iaviridae ,13. The aviridae , and itsaviridae , which caviridae . The varaviridae . Similaraviridae . TherebyPartial of intestine or stool specimens were taken individually from the acute enteritis and watery diarrhea of piglets from different big swine farms in the Fujian province between 2010 and 2012, and used for PEDV detection through PED Ag Test Kit . PEDV positive samples were used for sequence analysis and phylogenetic analysis. Intestinal samples were homogenized with 9 times of phosphate-buffered saline (PBS). The suspensions were then vortexed and centrifuged for 10 min at 1,700 × g. The supernatants were collected and stored at −80 °C before utilization.® One Step RT-PCR Kit Ver.2  under the following conditions: reverse transcription at 50 °C for 30 min, denaturation at 94 °C for 2 min, 30 cycles of denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 1 min. The RT-PCR products were analyzed by 1.5% agarose gel electrophoresis and visualized by ultraviolet illumination after ethidium bromide staining. Bands of the corresponding size of the gene were excised and the synthesized DNA was purified using QIAquick Gel Extraction Kit  according to the manufacturer’s instructions, then sequenced by Takara Company.Total RNA was extracted from the supernatants of the homogenized samples with the RNAiso Plus agent  according to the manufacturer’s instructions. The forward and reverse primers , ORFS 5'The reference strains used for the sequence analysis were described in In this study, 27 samples were found to show positive results in PEDV detection. They were used to amplify the ORF3 gene of PEDV, and then the gene was cloned and sequenced for alignment and phylogenetic analysis. Nucleotide sequence analysis indicated that all the samples were separated into two groups . The ORFIn terms of predicted amino acid sequence, the Subgroup 1, including six local strains, had two unique mutations, from L to S at 25 and from C to F at 107 respectively . It alsoTo analyze the phylogenetic relationships of the 27 Fujian samples and the reference strains from various parts of the world, we constructed a neighbor-joining phylogenetic tree using their ORF3 amino acid sequences . The resAlthough the bi-combined attenuated vaccine against TGEV and PEDV infection was authorized for utilization on swine farms in Fujian province, outbreaks of PED have caused tremendous economical losses . It is nSix Fujian strains, as well as three reference ones, were characterized by eight unique point mutations in the nucleotide sequence and three amino acid changes in the peptide. These were clustered into Subgroup 1 . It was The ORF3 protein of reference strain CV777 had nine high antigenic indexes based on DNAMAN program analysis, which were located at amino acid 4–39, 41–64, 70–114, 118–124, 134–148, 158–174, 179–190, 192–207, and 211–221 plots, respectively. The strains in Subgroup 1 had amino acid changes at 25, 80 and 107 , locatedPhylogenetic analysis indicated that all the strains were divided into 2 relevant groups (Group 1 and Group 2, et al. [Similar results were achieved by Li et al.  althoughIn conclusion, the PEDV field samples in Fujian province were characterized and compared by analyzing the sequence heterogeneity of ORF3 gene of PEDV. All the samples were separated into tw general groups, and the Fujian strain P55. In addition, five reference strains were clustered into Group 2, which had a long length deletion in both of the nucleotide and peptide sequences, showing a different genotype and might be involved in the variation of virulence. Six Fujian strains were clustered into Group 1, which showed another genotype with unique point mutations that might be used in differentiation between PEDV groups or new DNA markers and brought potential antigenic variation. Phylogenetic analysis revealed that the collected Fujian strains were very distant from the vaccine development strain CV777, which might be the reason why the vaccine was inefficient in controlling the disease. This study might help to choose an appropriate PEDV field strain as a vaccine candidate and efficiently prevent outbreaks of PED.


S. cerevisiae strains and evaluate relationships between grape varieties and geographical location on populational structures. From the musts obtained from 288 grape samples, collected from two wine regions , 94 spontaneous fermentations were concluded and 2820 yeast isolates were obtained that belonged mainly (92%) to the species S. cerevisiae. Isolates were classified in 321 strains by the use of ten microsatellite markers. A high strain diversity (8–43 strains per fermentation) was associated with high percentage (60–100%) of fermenting samples per vineyard, whereas a lower percentage of spontaneous fermentations (0–40%) corresponded to a rather low strain diversity (1–10 strains per fermentation).We herein evaluate intraspecific genetic diversity of fermentative vineyard-associated Ho) was about two to five times lower than the expected heterozygosity (He). The inferred ancestry showed a very high degree of admixture and divergence was observed between both grape variety and geographical region. Analysis of molecular variance showed that 81–93% of the total genetic variation existed within populations, while significant differentiation within the groups could be detected. Results from AMOVA analysis and clustering of allelic frequencies agree in the distinction of genetically more dispersed populations from the larger wine region compared to the less extended region. Our data show that grape variety is a driver of populational structures, because vineyards with distinct varieties harbor genetically more differentiated S. cerevisiae populations. Conversely, S. cerevisiae strains from vineyards in close proximity (5–10 km) that contain the same grape variety tend to be less divergent. Populational similarities did not correlate with the distance between vineyards of the two wine regions. Globally, our results show that populations of S. cerevisiae in vineyards may occur locally due to multi-factorial influences, one of them being the grape variety.For the majority of the populations, observed heterozygosity ( Saccharomyces cerevisiae strains have found that the species as a whole consists of both “domesticated” and “wild” populations. Although the genomes of most S. cerevisiae strains with disparate ecological and geographic sources are mosaics, genealogical relationships from DNA sequence diversity showed that domesticated strains derived from two independent clades, corresponding to strains from winemaking and sake (Japanese rice wine). “Wild” populations are mostly associated with oak trees, nectars or insects  Recent phylogenetic analyses of et al., S. cerevisiae strains in both vineyards and wineries, numerous molecular methods were developed recently. Microsatellite analysis can be considered the method of choice for S. cerevisiae strain delimitation, allowing high-throughput and precise data generation. Besides, due to the high level of discrimination and unequivocal results, expressed as base pair number (or as repeat number), the generated data are suitable for computational population genetic analysis S. cerevisiae strains from 56 worldwide geographical origins. The genotypes clustered in subgroups, according to the strain's technological use . Macrogeographical differentiation of strains from Asia, Europe and Africa accounted for 28% of the observed genetic variation, which suggests clonal reproduction and local domestication of natural strains originating from the same geographic area. S. cerevisiae strain was based on 32 single-nucleotide polymorphism markers S. cerevisiae population structure are still poorly understood.As reviewed by Martiny S. cerevisiae strains derived from cumulative small microsatellite allele-frequency differences. Within a vineyard the strain's genetic divergence correlated with the distance between sampling points, suggesting a pattern of isolation-by-distance. However, geographical distance was not correlated with genetic proximity, pointing towards the involvement of other factors, for the differentiation of S. cerevisiae populations In our previous studies, we showed that microsatellites are informative markers for distinguishing populations from vineyards in very close geographical locations (50–100 km). Genetic differences and populational structures among S. cerevisiae strains. Grape samples of the nine most representative grape varieties were collected at the harvest time of two consecutive years in 16 vineyards from the Bairrada and Vinho Verde appellations of origin in Portugal . For populational analysis 288 samples were obtained, that concluded 94 spontaneous fermentations and 2820 yeast isolates were obtained that belonged mainly (94%) to the species S. cerevisiae, being classified in 321 strains using 10 polymorphic microsatellite markers.In this study we test the hypothesis that both geographical region and grape varieties are drivers of population structures of fermentative vineyard-associated During the harvest time of two consecutive years, grape samples of representative grape varieties were collected in 16 vineyards . In the vineyards of BAO, 132 grape samples were collected and 50 (38%) of spontaneous fermentations occurred, providing 156 S. cerevisiae strains (average: 3.1 strains per fermentation). The total yeast count  ranged between 1.0×106 and 8.0×107 cfu/ml of must. With a few exceptions, all isolates belonged to the species S. cerevisiae due to their inability to grow in a medium containing lysine as sole nitrogen source (data not shown), the amplification of S. cerevisiae specific PCR-based interdelta patterns and by the amplification of S. cerevisiae specific microsatellite loci , Arinto (C), Avesso (D), Loureiro (G), Touriga Nacional (I); BAO: Aragonês (B), Baga (E), Bical (F) Maria Gomes (H), Touriga Nacional (I)), being Touriga Nacional shared by both wine regions. In vineyards 2–10 and 12–16, one single predominating grape variety was cultivated and collected. Vineyards 1 (VAO) and 11 (BAO) were chosen as reference vineyards, containing all five grape varieties of each region. With this approach, a total of 288 grape samples were collected for spontaneous fermentations. As detailed in ite loci . No amplS. cerevisiae strains. The number of strains obtained from one vineyard in one sampling year was between 0–43 and 0–23 in the Vinho Verde and Bairrada region, respectively. Non-Saccharomyces species that are well-known for their occurrence in vineyards, were found in vineyard 11 in the samples from final stages of fermentations that were carried out using musts from the grape varieties Aragonês , Maria Gomes  and Touriga Nacional . The average duration until the beginning of fermentations  was between 3.5 and 15.7 days . The average fermentation period (corresponding to the weight loss from 2 gl−1 to 70 gl−1) was between 6.3 and 18.8 days . Fermentations with grapes from the Bairrada region started within 6 days, whereas fermentation onset of musts collected in the Vinho Verde Region was much slower (14 days). However, the average fermentation duration was identical for the musts from both regions (12 days). Grape varieties that started fermentations most rapidly  correlated, by trend, with a higher number of S. cerevisiae strains . When the percentage of spontaneous fermentations among the six samples collected from each vineyard was compared with the number of isolated S. cerevisiae strains , as well as grape variety D in vineyards 8 and 9 (VAO), which were 5–10 Km apart. These populations were also well separated from other groups. Conversely, the S. cerevisiae strains from different grape varieties in the same vineyards  were much more divergent. The grape variety Touriga Nacional (I) is cultivated in most of Portuguese winemaking regions and was therefore included as a reference in our approach. S. cerevisiae populations from these grapes obtained in vineyards 1, 10, 11 and 13 were unresembling. In summary, we can assert that populational structures prevail according to winemaking regions, whereas S. cerevisiae populations are most similar in vineyards in close vicinity (at least up to 10 km) where the same grape varieties were cultivated.The highest bootstrap support was found for Ho) was about two to five times lower than expected heterozygosity (He) for the ten loci analyzed (Ho/He>1) for six microsatellites. The average of FIS values over all loci was rather high for most groups (mean of 0.61), pointing towards inbreeding as the predominating reproductive mechanism. The pattern and degree of populational divergence in the ten nuclear microsatellites among subpopulations was estimated by FST determination over all loci by AMOVA analysis, as shown in S. cerevisiae populations were included that consisted of at least 5 isolates . The contribution of variation within the populations defined was always high, ranging from 81 to 93%. For the analysis between wine regions, vineyards and grape varieties, the assemblage of several populations was considered as a group, indicated by parenthesis in ST values ranged between 0.07 and 0.19, corresponding to a moderate (0.05–0.15) to great (0.15–0.25) genetic differentiation ST value was obtained for the comparison of vineyards 1 and 11 that contained multiple grape varieties and that are located at a distance of 180 km. This value decreased to 0.133 and 0.145 when all populations from VAO and BAO were compared, including or not the populations from vineyards 1 and 11, respectively. In agreement with the data presented in the previous section, S. cerevisiae populations were less divergent in the smaller BAO, where FST values ranged between 0.067 and 0.120, whereas the corresponding values for the larger VAO region were between 0.157 and 0.173.For the majority of the populations, observed heterozygosity  were obtained when 1CGI was compared with the more distant BAO populations , whereas lower values (FST 0.18–0.20) were found when 1CGI was checked against the closer VAO populations 2A, 3A and 7C, suggesting a geographic correlation. However, this was not observed for the majority of the remaining comparisons, where FST values ranged between 0.13–0.16, independent of the geographic distance. The lowest FST value of 0.1 was found for populations from grape varieties E in the vineyards 11 and 12, located at a distance of 5 km. However, a strict correlation between grape variety and geographic proximity cannot be assumed because populations from vineyards 2 and 3, where variety A was cultivated were more divergent (FST 0.16) than populations from distinct grape varieties in vineyards 11, 12 and 13, that were located from each other at similar distances. These data show that the grape variety can be in fact a driver of populational structures because vineyards with distinct varieties (1 and 11) harbor genetically more differentiated populations, whereas vineyards with the same grape varieties in close proximity (11 and 12) contain less divergent groups of strains.To further investigate associations between genetic differentiation and geographic distance, pair wise vineyard comparisons were performed according to their geographic distance . The genS. cerevisiae populations were distinguished by a considerable degree of admixture. Deeper divergence was observed between both geographic regions and grape varieties, being more evident in the VAO region which is in agreement with AMOVA analysis. Populations from vineyards 8 and 9, that shared a heterozygous excess (Ho/He>1) for six microsatellites loci, can be clearly distinguished. Clusters 1 and 3 were more represented in VAO populations, whereas clusters 5 and 10 were more predominant in BAO populations. Populations from multiple grape varieties in vineyards 1 and 11  or soils 2–103cells/ml must S. cerevisiae in many wine regions in France versus conventional) and floor management systems Vineyards are an important yeast ecosystem. S. cerevisiae strains correlated with the distance between sampling points, suggesting a pattern of isolation-by-distance. However, this relationship was not found for larger geographical distances, pointing towards the involvement of other factors such as the grape variety, which we evaluate within the present study. We highlight that S. cerevisiae isolates were obtained after enrichment through must fermentation and therefore may not accurately represent vineyard populations. Our experimental approach is therefore an acceptable compromise that allows for estimation of population composition, but does not provide a precise description in terms of relative strain abundance in nature.In our previous studies we showed that within a vineyard the genetic divergence of Fermented musts from the grape varieties C, D and E  showed a notable strain diversity, which seems to be correlated with the percentage of spontaneous fermentations in a vineyard. Contrarily to the view that strains compete for nutrients under stressful fermentative conditions, it was surprising to find numerous strains at the end of the fermentations, suggesting a cooperative effect that may guarantee efficient fermentation when strain diversity is rather high. The faster fermentation onset observed for several grape varieties might also be related with a more favorable nutritional composition of the grapes. Spontaneous fermentations can be considered as complex multifactorial process, where strain diversity is one variable for a rapid onset, while the grape variety appears to be also relevant.S. cerevisiae in vineyards depend on climatic factors S. cerevisiae strain abundance, elevated percentage of spontaneous fermentations and low fermentative lag time compared to the closely located (10 km) vineyard 9, where the same soil, microclimatic conditions grape variety occurred. This result is in agreement with recent research showing that phytosanitary treatment has an impact on grape associated biodiversity The occurrence and survival of S. cerevisiae strains, even within geographically close regions. The isolated S. cerevisiae strains were unique for each vineyard and were also not re-isolated in consecutive years. However, in our previous research we found strains with a wider temporal and spatial distribution S. cerevisiae populations derived mainly from gradations in allele frequencies rather than from distinctive “diagnostic” genotypes. These markers are useful for unambiguous populational analysis, but it needs to be considered that sub-strain level discrimination may occur due to their relative high mutation rate. Clonal expansion with some cycles of homothallic self-mating is considered to be the most likely reproduction in yeasts, generating the high observed homozygosity and very structured populations due to inbreeding or genome renewal IS values suggest that Portuguese yeast populations are inbred, which is in agreement with previous results obtained with strains from Chile and New Zealand, where FIS values ranged between 0.4–0.75 Microsatellite typing of the chosen loci  followedS. cerevisae populations from different vineyards and grape varieties. Results from FST analysis and clustering of allelic frequencies agree in the distinction of genetically more dispersed populations from the larger VAO compared to the BAO region. Our data indicate that the grape variety can be a driver of populational structures because populations associated with different grape varieties from vineyards 1 and 11 were genetically more divergent than populations obtained from the same grape variety in vineyards in close locations (11E–12E (5 km), 8D–9D (10 km)). Comparison of strains from variety A in the close vineyards 2 and 3 (10 km) revealed a higher FST value, but these populations were still less differentiated than the ones obtained from vineyard 1. A correlation between genetic and geographical distances was only evident when the more divergent populations from vineyard 1 were compared to other groups of strains. The higher genetic differentiation of yeasts from the experimental vineyard 1 may be attributed to the fact that it contains ten different grape varieties in larger quantities and 152 varieties of a clonal ampelographic collection, that were introduced three to four years before our study was initiated. The inferred ancestry of populations support strong admixture whereas divergence was again observed between both geographic regions and grape varieties. Interestingly population 10I from VAO seemed more related with populations from BAO when the inferred ancestry was analyzed, This is one of the few varieties that is used in all Portuguese winemaking regions and might have been introduced in the VAO together with the yeast strains as a commensal member of grapevine flora, as previously suggested by Legras Various approaches were used to determine the genetic structure of S. cerevisiae strains have been globally dispersed by humans, supporting the importance of geography in shaping S. cerevisiae's population structure S. cerevisiae in vineyards occur due to multi-factorial influences, being the grape variety one of them. These findings are in agreement with a recent report about distinctive non-Saccharomyces yeast populations occurring on different grape varieties in the same vineyard Recent studies showed that S. cerevisiae populations and the grape variety. All necessary permits were obtained for the described field studies, the owners of the vineyards agreed with the collection of grape samples and the sampling plan.The sampling plan included a total of 16 vineyards (ten in the Vinho Verde and six in the Bairrada region) as shown in −4 and 10−5) were spread on YPD plates , and 30 randomly chosen colonies were collected after incubation . The isolates obtained throughout this work were stored in glycerol  at −80°C.From each sampling point, approximately 2 kg of undamaged and healthy grapes were aseptically collected and the extracted grape juice was fermented at 20°C in small volumes (500 ml). Fermentation progress was monitored by daily weight determinations. When must weight was reduced by 70 g/l, corresponding to the consumption of about 2/3 of the sugar content, diluted samples . DNA isolation was performed as previously described Saccharomyces species. These species were identified by restriction analysis of the ribosomal internal transcribed spacer (ITS) region as previously described S. cerevisiae and fail to amplify all of the corresponding homologous loci in sibling species such as S. bayanus and S. paradoxus that can be found occasionally in winemaking environments. We therefore consider that these sibling species did not occur in our spontaneous fermentations.In a preliminary approach, all isolates were analysed by interdelta sequence typing http://genome-www.stanford.edu.saccharomyces) and the results obtained for the size of microsatellite amplicons of this strain, the number of repeats for all alleles was calculated. Allelic frequencies, observed and expected heterozygosity, FIS determinationas well as AMOVA analysis was performed by the software Arlequin 3.11 Based on the genome sequence for strain S288C  and expected (He) heterozygosity for S. cerevisiae populations from vineyards 1–15 and grape varieties A–I. The ratios between observed (Ho) and expected (He) heterozygosity are indicated by underlined bold letters (Ho/He>1) and underlined letters (0.5>Ho/He>1). For the remaining fields the ratio was <0.5.(TIF)Click here for additional data file.


Lake ecosystems are usually classified at the landscape level as either pelagic or littoral habitats. However, we showed small-scale spatial heterogeneity among planktonic food webs along an environmental gradient. Stable isotope data is useful for detecting spatial heterogeneity of habitats, populations, communities, and ecosystems.Resources and organisms in food webs are distributed patchily. The spatial structure of food webs is important and critical to understanding their overall structure. However, there is little available information about the small-scale spatial structure of food webs. We investigated the spatial structure of food webs in a lake ecosystem at the littoral transition zone between an inflowing river and a lake. We measured the carbon isotope ratios of zooplankton and particulate organic matter  in the littoral zone of a saline lake. Parallel changes in the δ  Although the spatial scales of ecological processes have been recognized as important in ecology, they have presented an enormous challenge for ecologists . In manyResources and organisms in food webs may be distributed patchily, and there is some evidence for spatial heterogeneity of food webs. Stable isotope analyses of habitat heterogeneity in lakes or lagoons  and vertLake ecosystems are typically classified into pelagic, littoral, and benthic habitats . In lakeIn large, shallow lakes, pelagic food webs may vary spatially because of limited water movement and geomorphological complexity. In such cases, variations in environmental factors, such as water quality and temperature, are good indicators of differences between water masses or food webs. Generally, the littoral zone of a lake represents a transition between a riverine zone and a lake zone, with a longitudinal gradient of environmental factors, such as current velocity, turbidity, and photosynthetic productivity . In our Here, we assumed that we could use the relationship between the isotope values of consumers and environmental factors to reveal the spatial structure of planktonic food webs at a small spatial scale. Although we expect that the spatial heterogeneity of food webs is represented by changes in stable isotope composition, the association between POM and herbivores is stronger than that between POM and carnivores. This is especially true for zooplankton species in planktonic food webs, as they do not have high mobility and cannot move to connect food webs between sites. Thus, in this study, we estimated the food web in the littoral transition zone between a riverine zone and a lake zone of Lake Chany .Carbon stable isotope ratio is an excellent index for identifying the food sources of zooplankton, as minor changes in carbon isotope ratios occur with each trophic transfer . TherefoHere, we considered the two following predictions. (1) The isotope ratios of herbivore and carnivore zooplankton will spatially shift parallel to those of POM within a pelagic habitat when spatial heterogeneity is present in the planktonic food web . (2) No −1), while Sts. 1–7 were in a lentic area with no detectable current velocity.Lake Chany is in the Novosibirsk region of the Barabinskaya lowland of western Siberia  at an altitude of 106 m above sea level. The lake is a shallow inland saline system  that is characteristic of the western Siberian forest-steppe . Two mai−1 HCl to remove bicarbonate prior to isotope measurements. Crustacean zooplankton for isotopic analysis were collected by vertically hauling a plankton net (mesh size 250 µm) from the bottom to the surface of the lake. Zooplankton was sampled four times at each site. Species were sorted manually under a stereomicroscope and washed with distilled water. We collected two crustacean zooplankton species, Daphnia galeata Sars, a herbivore , a carnivore, as these were the most abundant and common species at the sites (All sampling was conducted between 17:00 and 21:00 h in August 2004. POM samples were obtained by filtering 100 mL surface lake water through Whatman GF/F glass fiber filters (precombusted at 500°C for 2 h). The sample water was prefiltered through plankton-net mesh (mesh size 250 µm). The samples were then treated with 1 mol Lhe sites . All sama concentration of the surface water was measured in five replicates at each site using a fluorescence chlorophyll a meter .The pH and electrical conductivity (EC) of the surface water at the study sites were measured using Twin pH and Twin Conductivity portable meters, , respectively. Chlorophyll 13C = (13C/12Csample/13C/12Cstandard−1)⋅1000 (‰). Pee Dee Belemnite (PDB) was used as a global standard for δ 13C. The analysis error was ± 0.2‰ for δ 13C.The carbon isotope ratios of POM and zooplankton species were measured with a mass spectrometer  connected to an elemental analyzer . We measured 3–4 isotope samples for each site. The results are reported in delta notation: δ Carbon stable isotope ratio is an excellent index for identifying the food sources of zooplankton, as only minor changes in carbon isotope ratios occur with each trophic transfer . Therefop < 0.01) were verified with the Tukey test. We also used a GLM to estimate the environmental factors, including pH, electronic conductivity, chlorophyll a concentration, water depth, and water temperature  values with downward stepwise procedure. All statistics were performed using R ver. 2.15.2  to determine the gradient and intercept of the carbon isotope changes in the plankton. We used a one-way ANOVA and the Tukey multiple-comparison test to compare carbon isotope values among the study sites (α = 0.05). Significant ANOVA results  and terrestrial matter from macrophytes .f is the POM contribution to the zooplankton species. Δ 13C was set as −0.43‰ with reference to The equation used for the isotope mixing model was: 13C values of POM tended to increase from St. 1 (transition part of Lake Chany) to St. 7 .We found parallel shifts in the δ Producers and consumers that comprise food webs inhabit spatially heterogeneous habitats in many ecosystems . HoweverHere, we only investigated zooplankton species. Therefore, conclusions regarding the whole food web in the area must be drawn with care. We found that planktonic food webs are spatially heterogeneous, due to the limited movement of zooplankton species. However, in contrast to zooplankton, fish species have higher trophic positions and can move throughout a greater area of the lake. Thus, fish species can connect the whole food web in the area, that is, they may connect the heterogeneous planktonic food-webs that we found at each site. It is important to consider the hierarchical structure of heterogeneous planktonic food-webs and that of the whole food web when evaluating the spatial structure of food webs and the connectivity between various parts of food webs. In this study, we did not evaluate the connections between heterogeneous planktonic food webs, and further study is needed in order to fully understand the spatial connectivity and structure of aquatic food webs, including mobile predators.Habitat heterogeneity can cause similar spatial heterogeneity of food webs. The spatial structures of food webs have been considered at various spatial scales, from the local to the landscape level . In this13C values of POM are usually correlated with δ 13C values of dissolved inorganic carbon (DIC) . The δ on (DIC) . The δ 1 CO2 gas . Thus, c13C values of POM with chlorophyll might indicate that changes in phytoplankton productivity affect the δ 13C values of POM. As a result of their meta-analysis, 13C values of POM in lakes. Increasing primary production would increase δ 13C values of phytoplankton, which is mainly composed POM, due to the limitation of carbon sources during heavy primary production (13C values of POM in the study area. Differences in primary production have been observed in various parts of aquatic habitats, such as littoral and pelagic sites (The observed negative correlation of the δ oduction . Thus, pic sites  and hot ic sites . Such diOur study revealed the spatial structure of the planktonic food webs in varying habitats along environmental gradients, such as water chemistry and primary productivity gradients, within Lake Chany, even at a 100-m scale. Recently, other isotope species, such as sulfur and hydrogen, have been used to estimate the resources for food webs with small isotopic differences between producers and consumers e.g., . These i10.7717/peerj.222/supp-1Supplemental Information 1Click here for additional data file.


Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer.Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer.Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy. Biomarkers play pivotal roles in the care of patients with cancers. However, currently used biomarkers for prostate cancer are sub-optimal. For example, prostate specific antigen (PSA), the most widely used biomarker, is controversial with regard to its specificity and sensitivity in various populations Lipids comprise diverse classes of molecules with critical functions in cellular energy storage, structure, and signaling. Previous studies have demonstrated that the risk of prostate cancer is increased with elevations in particular plasma fatty acids, such as myristic acid, α-linolenic acid, and eicosapentaenoic acids As described herein, we performed a global lipid profiling, which included measurement of 340 phospholipid and 50 cholesteryl ester (CE) apparent lipid molecular species, on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. By analysis with bioinformatic and statistical methods, a few plasma lipid species have been selected as biomarkers. The initial study demonstrates that these biomarkers have a high sensitivity, specificity and accuracy in diagnosis of prostate cancer.We hypothesize that prostate cancer tissues have distinct lipid profiles to meet special needs for tumor survival and progression. Distinctive lipid profiles will influence systemic lipid homeostasis and be reflected in body fluids including plasma. Therefore, detection of plasma apparent lipid molecular species will reflect the existence and progression of prostate cancer. By comparing plasma concentrations of hundreds of apparent lipid species among populations with and without prostate cancer, a few apparent lipid species that are the most representative of cancer status will be identified as plasma lipid biomarkers in diagnosis of prostate cancer.One hundred and five (105) plasma samples from 105 patients with prostate cancer were obtained from the Cooperative Human Tissue Network (CHTN), where plasma samples were pre-collected from different clinics during the period from 2004–2007. Before collection of plasma samples, patients had given consent and had not undergone therapeutic interventions. Diagnosis of prostate cancer for each patient was confirmed by subsequent prostate biopsy or prostatectomy. Limited information for each patient, including the patient's age, race and pathological diagnosis, was provided. Thirty six (36) plasma samples from male controls were obtained from a collaborating author, who pre-collected the plasma from 36 male patients at a community clinic, where patients had their wellness checks or sought for medical help for other diseases during the period 2006–2008. Criteria for selection of controls were no history of prostate cancer, denial of clinical manifestations of prostate cancer, and a low level of serum PSA. The same protocol for collection of plasma was used in collection of plasma samples from patients and controls: from each subject, 10 ml whole blood was collected into a vacutainer tube containing potassium-EDTA as anticoagulant. The plasma was promptly separated (no more than 4 h after collection of whole blood) and stored at −80°C immediately. All plasma samples were transported on dry ice to the Kansas Lipidomics Research Center (KLRC) for lipid analysis.An automated electrospray ionization-tandem mass spectrometry approach was used. In this approach, plasma lipid species are identified at level of head group plus total acyl carbons: total double bonds. The detected intensities, each defined by an intact ion mass/charge (m/z) and a characteristic fragment m/z, are herein described as “apparent lipid molecular species”. Data acquisition and analysis were carried out as described previously + ions in positive ion mode with Precursor of 184.1 (Pre 184.1); PE and lysoPE, [M+H]+ ions in positive ion mode with Neutral Loss of 141.0 (NL 141.0); PI, [M+NH4]+ in positive ion mode with NL 277.0; PS, [M+H]+ in positive ion mode with NL 185.0; PA, [M+NH4]+ in positive ion mode with NL 115.0; CE, [M+NH4]+ in positive ion mode with Pre 369.3. SM was determined from the same mass spectrum as PC (precursors of m/z 184 in positive mode) Sequential precursor and neutral loss scans of the extracts produced a series of spectra with each spectrum revealing a set of lipid species containing a common head group fragment. Lipid species were detected with the following scans: PC, SM, and lysoPC, [M+H]th set of mass spectra were acquired on the internal standard mixture only. Peaks corresponding to the target lipids in these spectra were identified and molar amounts calculated in comparison to the internal standards on the same lipid class. To correct for chemical or instrumental noise in the samples, the molar amount of each lipid metabolite detected in the “internal standards only” spectra was subtracted from the molar amount of each metabolite calculated in each set of sample spectra. The data from each “internal standards only” set of spectra was used to correct the data from the following 10 samples. Finally, the data were corrected for the fraction of the sample analyzed and normalized to the sample volume to produce data in the unit of nmol/µl.The background of each spectrum was subtracted, the data were smoothed, and peak areas integrated using a custom script and Applied Biosystems Analyst software. The data were isotopically deconvoluted, and the lipids in each class were quantified in comparison to the internal standards of that class, because various molecular species within the same class ionize similarly Two strategies were used in selecting individual apparent lipid species biomarkers from hundreds of detected species. The first strategy was filtration. To narrow the number of potential candidates from 390 apparent lipid species, the species that cannot be clinically used in diagnosis of prostate cancer were filtered, due to too low concentration to detect, insignificant difference between patient and control groups, or too closed levels of plasma concentrations in two groups  to interpret. Criteria for retention were: 1) difference in mean plasma lipid concentration is highly significant (p<0.01) between patient and control groups; 2) changes in mean plasma lipid concentration is >2-fold (up or down); and 3) mean plasma lipid concentration is >10 nmol/µl. Apparent lipid species that fulfilled all three criteria were selected as potential candidates of plasma lipid biomarkers. The second strategy provided additional differentiation of cancer and control samples, in order to demonstrate that the selected candidates are not only clinically useful and applicable, but also they are highly sensitive, specific and accurate in differentiation of prostate cancer from controls. After analysis with bioinformatics methods, any apparent lipid species of selected potential candidates will be selected as individual plasma lipid biomarker in diagnosis of prostate cancer, if it met these criteria: 1) sensitivity above 80%; 2) specificity above 50%; 3) all of Precision, Recall, F-measurement and Area under (ROC) curve above 80%.The T-Test in SPSS18 software was used to compare mean plasma concentrations of 390 apparent lipid species between control and patient groups. The significant p value was set at 0.01 in filtration procedures. The T-Test was also used in comparison of mean ages between control and patient groups. The significant p value was set at 0.05.GenSpring11, Gim2 and Windows Paint software and programs were used to perform and graph charts of Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA).Weka 3.73 version software was used in bioinformatics analysis: Simple logistics classification algorithm and InfoGain, a supervised attribute ranking method were used to rank individual apparent lipid species and lipid class according to their predictive powers in differentiation of patients with prostate cancer from the controls; RandomForest classification algorithm and 10-fold cross validation were used to estimate the performance of a predictive model. For “unknown prediction”, models were established in a training set, which contained populations with “known features”, such as white patient. All subjects within the same “known feature”, such as white patient, were randomly grouped (10 iterations in this study). The predictive powers were repeatedly cross validated among 10 iterations. The program determined average predictive power, which indicated if a satisfactory model was established in the training set. Then the satisfactory model with each “known feature” was used to predict  predictive power in subjects with each mirrored “unknown feature”, such as black patient, in the test set. Higher predictive power in the training set indicates smaller variances among 10 randomly grouped iterations with “known feature”. Higher predictive powers in the test set suggest a smaller variance between the paired “known” and “unknown” populations.Chi-Square test in SPSS 18 software was used to compare the distribution of controls and patients between the first half (top portion) and the second half (bottom portion) with higher plasma lipid concentrations in This study was approved by the Institutional Review Board at the University of Mississippi Medical Center as an exempt investigation, in which obtaining consent from participants was not required, because all of obtained specimens used in this study were pre-collected by other organizations. The protocols for sample collection had been approved by their Institutional Review Boards. Patients had given their written consent before donation of plasma samples. In this study, no identifiable information, such as patient's name, birth date or contact information was known or used.The entire study included 141 subjects including 105 patients with prostate cancer and 36 male controls. Among the patients, 61 (58.1%) were Caucasian (“white”), 42 (40%) were African American (“black”); and 2 were of unknown ethnic origins. Among the 36 controls, 24 (66.7%) were Caucasian and 12 (33.3%) were African American. There was no difference in racial ratio between patient and control groups (p = 0.55), although there were significantly more Caucasians than African Americans in the entire study . The average age at time of sample collection was 63.6±8.5 for patients and 57.5±15.3 for controls (p = 0.0032). Information on Gleason grade was available for 100 out of 105 patients: 2 patients had Gleason score of 5, 55 had Gleason score of 6, 35 had Gleason score of 7, and 8 had Gleason score above 7. Thus, 90% of patients had Gleason score of 6 or 7. Information on other clinical conditions that might influence lipid metabolism such as hyperlipidemia, diabetes, other malignancies and medications was not available for patients. Clinical information for 36 male controls was as following: 10 patients had their wellness check and denied significantly clinical manifestations; 14 had hypertension; 6 had osteoarthritis; and 1 to 2 patients had a history of one or more of following: hyperlipidemia, back pain, obesity, diabetes, Gout, bipolar disorder, seizure, or gastroesophageal reflux disease. None had a history of cancer including prostate cancer. The mean serum PSA level for controls was 0.85 ng/ml.−20). The highest mean plasma concentration of a cholesteryl-ester species was CE(18∶2) . The highest mean plasma concentration of a polar lipid species was PC(34∶2) . The significant fold change in mean plasma concentration of these apparent lipid species between patient and control groups ranged from positive 22.7-fold for dihydrosphingomyelin (DSM) with 16∶0 [(DSM(16∶0)] (p = 3.85×10−19) to negative 20.8-fold for PC(30∶1) (p = 9.58×10−04). The complete list of mean plasma concentrations in patient and control groups, p values and fold changes between patient and control groups for each of 390 species is provided in Plasma lipid profiles including 390 individual apparent lipid species from 13 classes of phospholipids and cholesteryl-esters (CE) were determined by lipidomics for 141 plasma samples (105 from patients and 36 from controls). The most significant difference in mean plasma concentration between patient and control groups was found in lysophosphatidylcholine (LPC) with the fatty acyl chain 22∶6 [LPC(22∶6)] , 10 , 15, 20, 25, 30 and 35 . The results show that in any manually assembled group with more lipid markers together had higher sensitivity, specificity and accuracy in diagnosis of prostate cancer as compared to any of individual lipid biomarkers. Among these manually assembled groups, the group of 15  was the best combination with the strongest predictive powers in diagnosis of prostate cancer: it had the highest sensitivity (93.6%), the highest specificity (90.1%), higher accuracy (97.3%) as shown in To potentially reduce the number of biomarkers to facilitate practical incorporation into the workflow of clinical laboratories and to make the results most amenable to interpretation by clinicians, bioinformatics analyses were performed on the various combinations from two lipid biomarkers together (top 2) through 15 lipid biomarkers together (top 15) as shown in Because using top 15 lipid biomarkers together had the best predictive power in diagnosis of prostate cancer, the characteristics in this group of apparent lipid species were further analyzed.Principal components analysis (PCA) was performed to examine the ability to separate patient and control subjects with lipid profiles of all 390 and the selected 15 apparent lipid species. Performing PCA with lipid profiles of 390 apparent lipid species, patient and control subjects were visually separated along the first component in PCA, which accounted for 28.3% of the overall variance . HoweverHierarchical cluster analysis (HCA) is a statistical method for finding relatively homogeneous clusters of cases based on measured characteristics. We applied HCA combining dendrograms and a heatmap to cluster both entity (15 apparent lipid species) and condition (141 subjects) with panels of characteristics at the left side in It is unclear whether imbalanced compositions of race and age in this study cohort influenced the predictive power of the selected 15 apparent lipid species in diagnosis of prostate cancer. To clarify this issue, an “unknown prediction” method was applied. The results of unknown prediction are shown in Among the 355 un-selected apparent lipid species, 43 (12.11%) of the lipid molecules contained saturated fatty acid chains only (no unsaturated fatty acid chains). While within the 35 selected apparent lipid species, 12 (34.3%) lipid molecules contain saturated fatty acid chains only. The difference in percentage of apparent lipid species containing saturated fatty acid only was highly significant between the selected 35 candidates and those un-selected apparent lipid species . These results suggested that the apparent lipid species with only saturated fatty acids chain only might play certain roles in pathogenesis of prostate cancer.The mass spectra of top 15 apparent lipid species in representative patient and control samples are shown in In clinical practice, PSA is the most commonly used biomarker for prostate cancer. However there is a substantial overlap in serum PSA level between patients with and without prostate cancer. No single PSA cutoff value can satisfactorily provide a simultaneously higher sensitivity and specificity in diagnosis of prostate cancer. Taking an example, one study showed that a PSA cutoff value of 1.1 ng/ml had a sensitivity of 83.4% with a specificity of 38.9%; that of 4.1 ng/ml had a sensitivity of 20.5% with a specificity of 93.8%; and the area under (ROC) curve was 68.2% Human plasma contains thousands of distinct lipid species. Although normal ranges of some lipid species have been determined in plasma Univariate analysis of one apparent lipid species is unlikely to be sufficient to discriminate prostate cancer patients from controls because of considerable variation of plasma lipid concentrations. A combination of multiple plasma lipid biomarkers with multivariate analysis and various classification algorithms was demonstrated herein to have enhanced predictive power in the diagnosis of prostate cancer in our study. A similar effect was reported by Landers et al Overall, patients with prostate cancer had increased plasma lipid concentrations in all lipid classes except PA, which was significantly lower in patients with prostate cancer. This imbalance in plasma concentrations among lipid classes could be caused by increased synthesis of other phospholipids in prostate cancer resulting in over-consumption of PA, because PA is the precursor for synthesis of many other phospholipids This preliminary study has several limitations. First, more than 90% of plasma samples were obtained from prostate cancer patients with a Gleason score of 6 or 7, which made it impossible to correlate the identified plasma lipid biomarkers with the severity of the prostate cancer, as well as to the patients with metastasis or benign changes. Second, due to incomplete information on the patients' serum PSA level at the time of samples' collection, and to the lack of information on patients' outcomes, we were unable to compare the predictive power of the identified lipid biomarkers with that of PSA in the same study cohort. Therefore, at this point, the identified plasma apparent lipid species might serve as diagnostic biomarkers only, but not as prognostic and screening biomarkers. As well, the specificity of these identified lipid biomarkers has not been tested for other cancers and metabolic disorders. Even if there are limitations in the study, it is a pioneering work, exploring a new approach to seeking biomarkers for prostate cancer and other diseases.Figure S1Hierachical Cluster Analysis (HCA) based on 15 apparent lipid species and 141 subjectsand their clinical characteristics. Exel files.(XLSX)Click here for additional data file.Table S1Difference in plasma concentration of individual apparent lipid species between patient and control. Exel files.(XLSX)Click here for additional data file.