Tuber magnatum Pico is a greatly appreciated truffle species mainly distributed in Italy and Balkans. Its price and features are mostly depending on its geographical origin. However, the genetic variation within T. magnatum has been only partially investigated as well as its adaptation to several environments.Truffles are symbiotic fungi that develop underground in association with plant roots, forming ectomycorrhizae. They are primarily known for the organoleptic qualities of their hypogeous fruiting bodies. Primarily, T. magnatum fruiting bodies collected during several seasons from three different areas located in the North, Center and South of Italy, with the aim to distinguish them according to molecular and biochemical traits and to verify the impact of several environments on these properties. With the proteomic approach based on two-dimensional electrophoresis (2-DE) followed by mass spectrometry, we were able to identify proteins specifically linked to the sample origin. We further associated the proteomic results to an RNA-seq profiling, which confirmed the possibility to differentiate samples according to their source and provided a basis for the detailed analysis of genes involved in sulfur metabolism. Finally, geographical specificities were associated with the set of volatile compounds produced by the fruiting bodies, as quantitatively and qualitatively determined through proton transfer reaction-mass spectrometry (PTR-MS) and gas-chromatography-mass spectrometry (GC-MS). In particular, a partial least squares-discriminant analysis (PLS-DA) model built from the latter data was able to return high confidence predictions of sample source.Here, we applied an integrated omic strategy to Results provide a characterization of white fruiting bodies by a wide range of different molecules, suggesting the role for specific compounds in the responses and adaptation to distinct environments. Tuber magnatum Pico is one of the best-known species belonging to the genus Tuber, which includes between 180 and 220 species [T. magnatum is characterized as “whitish truffles”, fruiting bodies with white-colored gleba that are also produced by other Tuber species within the Puberulum group sensu lato [Tuber melanosporum, Tuber borchii, Tuber aestivum [Tuber formosanum [T. magnatum [T. magnatum truffles, whose prices are ranging from 300 to 400 € hg− 1 [Tuber species, is in fact the highly different degree of appreciation by the consumers, which is related to the different aroma and flavor specificities due to truffle growth environment. Development of truffle fruiting bodies is, indeed, known to be influenced by a range of environmental variables, spanning from the host plant and the complexity of forest vegetation [The ectomycorrhizal fungus aestivum , 4 and Trmosanum , many atmagnatum  have bee € hg− 1 , 7. Diff € hg− 1  and Swit € hg− 1 . One disgetation  to soil getation , climatigetation  and the getation . This obT. magnatum truffles was already investigated, evaluating intraspecific polymorphisms by simple sequence repeat (SSR) markers [T. magnatum truffles has revealed, for the first time, the presence of genetic and phylogeographic structures in natural populations of this Tuber species [T. magnatum using SCAR markers as a tool to identify single-nucleotide polymorphisms (SNPs) [T. melanosporum [T. melanosporum from Italy, France, and Spain, which led to the identification of more than 400.000 SNPs able to differentiate the analyzed samples [The genetic variation within  markers , 16; eigs (SNPs) , therebynosporum , where p samples .T. magnatum) fruiting bodies coming from different Italian areas, suggesting that proteomic characterization might be a promising diagnostic method for origin attribution. In 2004 early work on T. borchii fruiting bodies [Tuber species has been greatly facilitated by the release of the complete sequence of the haploid genome of the Périgord black truffle T. melanosporum [T. magnatum, T. aestivum [T. borchii [On the other hand, Vita et al.  reportedg bodies  faced thnosporum . Moreoveaestivum  and T. b borchii  genomes T. aestivum var. uncinatum, finding that the production of eight-carbon-containing compounds, which account for most of the aroma variability in this species, is likely to be under genetic control [T. melanosporum proteome (reconstructed through a combined polyacrylamide gel electrophoresis (1D PAGE) and high-accuracy liquid chromatography tandem-mass spectrometry approach coupled with bioinformatics analysis), which were found enrolled in the synthesis of volatiles in prior biochemical studies [Recently, the profile of volatile compounds emitted by the fruiting bodies has been taken into consideration as an additional biomarker for truffle intraspecific classification. Biotic and abiotic factors have been shown to influence truffle aroma, including the nutritional content and the identity of the host tree . In addi control . Experim studies .T. magnatum samples was equally insufficient to identify their collection locations [Neither individual method deployed so far could be considered as a definitive diagnostic method, for the sake of the attribution of truffle origin. A proteomic comparison of ocations . It is wocations , which mT. magnatum fruiting bodies, collected in regions subjected to different environmental conditions, through parallel high-throughput approaches. An expanded proteomic assessment, as compared to previous experiments [T. magnatum volatiles (e.g. sulfur compounds) were examined more closely through qPCR and compared to the data from Murat et al. [T. magnatum to changing environmental conditions, which is at present underexplored, and suggest new putative tools that may be used in the next future for the geographical identification of white truffles.Here we provide an in-depth characterization of the eriments , was cout et al. . The obtT. magnatum fruiting bodies were harvested from different Italian areas  during 4 years of study  and fold change , which displayed significant quantitative differences among samples. Analysis of variance, i.e. one-way ANOVA, and Tukey HSD post-test were used to evaluate the statistical significance of sample comparisons  applied to the intensity values of the selected 2-DE spots. Two principal components were found to account for 46.08% (F1) and 26.13% (F2) of the total variance  enrichment analysis. Among the over- or down-represented biological process-related categories we found, terms associated to small molecule, carboxylic acid and alpha-amino metabolism over-represented with the highest statistical significance Fig. a. More iT. magnatum samples were collected in the three different locations and the time points associated with the sampling campaign were considered as biological replicates. When this experimental work was started, the genome of the T. magnatum was not known, therefore we decided to analyze the whole transcriptome dataset using the de novo reference assembly of T. magnatum provided by Vita et al. [T. magnatum RNA-seq reads cannot be mapped against the closest truffle species T. melanosporum reference genome (1% of mapped reads), as reported by Vita et al. [To better understand the observed proteome dynamics and assess how the protein profiles compared with changes at the level of gene expression, we carried out a whole transcriptome sequencing. a et al. , containa et al. . Processa et al. , containFurther information on the results of sample comparisons could be obtained by a Shannon entropy distribution plot  and cysteine dioxygenase (gene 14) were found to be almost unaffected by sample origin. Instead, the majority of the genes were found as up-regulated in AL samples in at least 1 year of collection; in particular, with the exception of thioredoxin reductase (gene 5), taurine dioxygenase (gene 15), BCAT1 (gene 17) and the aromatic amino acid aminotransferase (gene 18), the up-regulation in AL was observed during both years. The most pronounced differences between AL and the other samples were observed in the case of cystathionine beta synthase (gene 11) and cobalamin-independent methionine synthase (gene 13). Overall, the average expression values of the 19 selected genes was higher in Alba when compared with other samples  and prediction   and 1-propanol (7) represented the most significant compounds able to distinguish the three sample classes, although in distinct ways; the sulfur compound discriminated AL samples, where it was absent, whereas 1-propanol was not detected in the IS dataset.One main goal of our assessment was to build up a comprehensive picture of the changes in volatile molecule composition of fruiting bodies from different geographical accessions, with the aim to provide a quantitative basis that might be useful to understand how truffle aroma is influenced by the environment. We characterized a set of 165 volatile organic compounds (VOCs) accumulated by truffles of the three accessions by means of GC-MS chromatography  had a higher VIP score in SM. An intermediate situation was observed for aldehydes, ketones and those compounds classified as “others”, where IS and SM contributed with a comparable number of compounds with the highest significance. As to the aromatic compounds, the greatest number of statistically significant compounds belonged to the SM accession, as compared to IS; in particular, compounds such as 1–2 and 1–4 dimethylbenzene had a much higher level of significance in the samples coming from San Miniato.All compounds selected as significant in at least one sample (VIP > 2) after PLS-DA were then grouped according to their chemical properties before the statistical analysis, to understand whether particular VOC classes could be considered prominent in sample diversification. VOCs selected by PLS-DA analysis never displayed the highest VIP values in AL samples, when compared to the other two accessions. Considering the IS and SM samples, on the other hand, we noticed the existence of trends linked to each chemical class. Concerning the sulfur-containing compounds, hydrocarbons, esters and terpenes (only one compound considered for each of the three), IS showed the most statistically significant values. The same applied to alcohols, where three of the four compounds had the highest significance in IS. Instead, 1-octen-3-ol  as the most distinctive compound for AL samples  and 2-methyl-4,5-dihydrothiophene (51) were the most significant ones for IS  and 2-methyl-4,5-dihydrothiophene (51) showed maximum VIP scores in SM samples , 2-methylthioacetic acid (55) and 2-methyl-3-furanthiol (60), negatively correlated with the variable “Rainfall”, with only methanethial (8) being slightly positively correlated with it , 2-propenal (13) and alkyl fragment (4) were negatively affected by the variable “Rainfall”, while 1-Butene (14) negatively correlated with the “Temperature”. Finally, anisole (58) and alkyl fragment (12) were the most influenced compounds by the variable “Temperature”. Results of CCoA ordination showed how this analysis is able to extract axes that explain as much as possible of the total variance due to the constraining effect of the environmental variables, as highlighted by the role of sulfur compounds.Prompted to investigate the source of variability that the PLS-DA model could not capture Fig. a, we hyp it Fig. . As to tRemarkably, sulfur-containing volatile compounds (VSCs) represented nearly 30% of the selected VIPs and were statistically significant in IS samples , and the β-tubulin gene [Tuber genus was performed and results were compared to that from other experimental approaches, mainly those based on molecular methods such as the ITS-based analysis. As the authors stated [In recent years, studies on environmental adaptations of non-model species have increased, with molecular insights made possible by novel comprehensive techniques available for data analysis. Molecular markers that have been most widely used to distinguish the prized lin gene , 35–37. lin gene , offerinlin gene . These ps stated .omics techniques have represented a valid approach to identify biomarkers associated with a specific steady-state. Proteomic techniques, for example, have been frequently used for the discovery of differentially expressed proteins, including biomarkers [On the other hand, molecular biomarkers related to the organism phenotype are generally measurable indicators of a biologic status and they can vary as a result of environmental changes. In the last years, the development and the spread of -omarkers , as in womarkers .Tuber genus, researches are improved by the recent publication of the genome sequence for several of them [T. magnatum genome sequencing [T. aestivum have also been reported, has contributed to increase the level of information for the species belonging to the Tuber genus, which were previously based on the genome of T. melanosporum [borchii [T. magnatum fruiting bodies. This allowed us to draw a comprehensive picture of mature fruiting body metabolism.In the case of fungi belonging to  of them , 24. Parquencing , in whicnosporum  and T. bT. borchii, Splivallo et al. [T. borchii-fruiting bodies were produced by the microbiome inhabiting truffle-fruiting bodies. The core microbiome of truffle-fruiting bodies, which is dominated by α-Proteobacteria, might be supplemented with additional species depending on the fungal species, the maturation stage or the environment [Tuber, irrespective of geographic origin, but not in other truffle genera sampled. However, we cannot exclude that the differences observed between samples collected in different environments could be also related to a difference in these fruiting-bodies associated bacteria, which can at least in part reflecting the soil microbial community, that may influence transcriptomic, proteomic and volatilome profiles.However, truffle fruiting bodies also contain bacteria  that seeo et al.  have alrironment . Benucciironment  reportedIndeed, each of the three approaches adopted brought to highlight reproducible differences among the samples under investigation. Proteomic tecniques were widely used for determining environmentally-induced changes in protein composition , 45. OurConsidering PTR-ToF data, CCoA was performed to evaluate the impact of environmental variables on VOC emission. Results showed a clear correlation trend certain degree among variables and one of the samples (SM), leading to highlight as temperature and rainfall influence the emission of individual VOCs, some of them containing sulfur.For one class of putative discriminative markers, i.e. those related to sulfur compound metabolism, the outcome of the three diagnostic approaches showed a remarkable convergence. Several among the differentially expressed spots found through the 2-DE approach contained proteins involved in sulfur amino acid metabolic processes  and the same metabolic pathway resulted to be regulated across transcriptome profiles in our accessions , S-adenosyl-L-homocysteine hydrolase (SAH1), Cobalamin-independent methionine synthase (MET6), S-adenosylmethionine synthetase (SAM1) and ATP sulfurylase (MET3) were also reported as strongly upregulated in T. melanosporum as well as in T. magnatum [Going deeper in data analysis, we may observe as some of the highest upregulated genes in magnatum . These dmagnatum .T. magnatum grounds, knowledge on the relationship on sulfur content in soil and sulfur VOCs released as well as the on requirements for T. magnatum life cycle, including fruiting bodies production, is still lacking. By contrast, parameters already suggested as related to truffle grounds are represented by the calcium carbonates (CaCO3), exchangeable calcium, and magnesium [Despite the differences previously described, we cannot exclude that some of the differences found at the level of sulfur metabolism might be linked to the availability of sulfur in the soil itself. However, although soil analyses in productive truffle areas have already highlighted some factors that are usually associated with agnesium .Tuber spp., and it is provided in high quantity in the truffière to prevent limiting effects [T. magnatum, the availability of calcium is essential for host colonization and fructification [2+-dependent intracellular signaling [Calcium has been reported as an essential nutrient for the development of fruiting bodies of various  effects , 70. It fication . We founfication  in two dignaling .T. borchii) [S. cerevisiae confers resistance to H2O2 by minimizing ROS-mediated damage [2O2, which can be used by several ligninolytic peroxidases for lignin degradation [T. magnatum fruiting bodies of different geographical origin. Finally, differential expression of gamma-actin, which is involved in fungal cell wall organization [Additional ecological interactions can be hypothesized on the basis of other differential proteins and transcripts recovered from our analysis. At the symbiotic interface with the host plant, ectomycorrhizal fungi establish a competition with root cortical cells for the monosaccharides generated from plant-derived sucrose, which are converted into storage polyols  . Differed damage ; thereforadation –77. Its radation , where inization , might iT. magnatum samples from different environments, leading to new information on putative markers that could be validated in the next future on a higher number of samples. The integration of different high-throughput techniques, allowed us to identify specific molecules linked to environmental responses, with a specific attention on sulfur metabolism gene products and sulfur-containing volatile compounds, providing new information on the overall ascoma metabolism in T. magnatum. Although several efforts have been done in the last years to highlight the mechanisms involved in the formation of these precious fruiting bodies, the environmental factors affecting this process should be still fully elucidated. The generated datasets, which include a huge quantity of data obtained by using different -omics approaches, will be useful as source for researches aimed to distinguish ascocarps according to their origin, also in combination with genetic molecular marker methods. In fact, this is an important point also to avoid frauds but to also highlight new actors in the formation of this precious truffles.In conclusion, our work focused on the search for adaptive differences being able to discriminate T. magnatum natural accessions were harvested from the natural ground in specific locations selected from Northern, Central and Southern Italian regions  over different years during the same seasonal period (November), as reported in Table Fruiting bodies belonging to the various Selected fruiting bodies were thoroughly washed several times with distilled water and subsequently dipped in absolute ethyl alcohol to remove external contaminations. Finally, the thin external layer of the peridium was removed. Samples were frozen in liquid nitrogen, ground into a fine powder and, stored at − 80 °C before being used for protein and molecular analysis.Fruiting bodies powder (100 mg) was homogenized with 1.6 mL extraction buffer  according to Vita, et al. . The homProtein were quantified with the Bradford method , using bin-gel rehydration onto an IPG (Immobilized pH Gradient) gel strip for preparative analysis. IPG strips , with pH range 4–7, were rehydrated with 350 μL of IEF sample buffer  containing the samples.Twelve or sixteen replicate gels (four for each year of collection) were performed for each biological sample, depending on the overall duration of the study for each of the sampling locations evaluated. Samples (1 mg) of protein were directly loaded by Strips were covered with mineral oil and focusing was carried out in an IPGphor apparatus  applying the following conditions: 12 h of rehydration at 30 V, 1 h at 300 V (in gradient), 1 h at 300 V (step and hold), 3 h at 3500 V (in gradient), 3 h at 3500 V (step and hold), 3 h at 8000 V (in gradient) and a final step at 8000 V . After focusing, the IPG strips were equilibrated, in two steps of 15 min . The second dimension, SDS-PAGE electrophoresis, was performed using BioRad Protean II XL (20 × 20 cm) vertical gel electrophoresis chambers, on 12%  acrylamide gels  applying a current of 40 mA per gel. Molecular mass standards were used, with a range from 10 to 250 kDa . Proteins were resolved by 2-DE and were stained with Coomassie brilliant blue  according to the manufacturer’s instructions.p-value) and fold change, as evaluated and automatically sorted by the software. A post-hoc analysis (Tukey’s test) was performed on the ANOVA results, to identify specific correlations among samples. The relevance of each spot in discriminating among samples of different origin was evaluated by principal component analysis (PCA), exploiting the tool available in the Progenesis SameSpot software, for differentially expressed spots.High resolution (300 dpi) images of 2-DE gels were prepared using the Densitometer GS-800 (BioRad). Computer-assisted 2D image analysis was done using the Progenesis SameSpots vs 3.2.3 gel analysis software (NonLinear Dynamics) for three technical replicates for each biological condition (different years) from three independent extraction experiment procedures Table . Proteinin-gel reduced, S-alkylated with iodoacetamide and digested with trypsin, overnight. Digest aliquots were removed and subjected to a desalting/concentration step on C18 ZipTip microcolumn using 5% formic acid/50% acetonitrile as eluent before further analysis. Digests were then analyzed by nanoLC-ESI-LIT-MS/MS using a LTQ XL mass spectrometer  equipped with Proxeon nanospray source connected to an Easy-nanoLC . Peptide mixtures were separated on an Easy C18 column  using a linear gradient from 5 to 50% of acetonitrile in 0.1% formic acid, over 24 min, at a flow rate of 300 nL/min. Spectra were acquired in the range m/z 400–2000. The acquisition was controlled by a data-dependent product ion scanning procedure over the three most abundant ions, enabling dynamic exclusion (repeat count 1 and exclusion duration 1 min). The mass isolation window and collision energy were set to m/z 3 and 35%, respectively.Nineteen spots were manually excised from gels, triturated and washed with water. Proteins were p < 0.01 for a significant identification) were further evaluated by the comparison of their calculated mass value with that obtained from 2-DE. Where appropriate, protein identification was checked manually to provide for a false positive rate of less than 1%. Identified proteins were then sorted basing on their exponentially modified protein abundance index (emPAI) for each candidate spots [MASCOT software package  was used to identify protein spots unambiguously from an updated tuber non-redundant sequence database from NCBI by using a mass tolerance value of 2.2 Da for precursor ion and 0.8 Da for fragment ions, trypsin as proteolytic enzyme, a missed cleavages maximum value of 2 and Cys carbamidomethylation and Met oxidation as fixed and variable modification, respectively. Candidates with more than 2 assigned peptides with MASCOT score > 25  performed with default settings.Tuber spp. annotations files were downloaded respectively from the Gene Ontology and the Gene Ontology Annotation (GOA) websites (https://www.ebi.ac.uk/GOA/proteomes). Hypergeometric test, Benjamini & Hochberg false discovery rate [Gene ontology (GO) term enrichment analysis to find statistically over- or down-represented categories was performed with BiNGO 3.03  as a pluery rate  correctiRNA extraction was performed using the selected samples  collected during two different years: 2014 and 2015. With the aim of reducing the variability among biological replicates, for each location and year of collection, six different fruiting bodies were homogenized and mixed together to obtain a single data point. Samples collected in the same location at different time were considered biological replicates, resulting in experimental design comprising 3 locations and 2 time points, for a total of six samples. Total RNA extraction was achieved using the Plant/Fungi Total RNA Purification Kit (Norgen Biotek Corp) according to the manufacturer’s method. Total RNA integrity and purity was further checked on agarose gel and Agilent 2100 Bioanalyzer High Sensitivity and DNA 1000 assay .+ RNA-seq libraries were generated from the six samples according to the TruSeq mRNA Sample Prep kit  and subjected to single-end 100-bp reads (1X100 bp) sequencing at IGATech  using a HiSeq2000 platform . The CASAVA v1.8.2 of the Illumina pipeline was used to process raw data for format conversion and de-multiplexing. On average, ~ 41 million reads per sample were produced with a total of ~ 245 million reads.Illumina stranded poly(A)T. magnatum high-confidence protein-coding transcripts published by Vita et al. [n = 6723) published by Vita et al. [n = 6665 genes. DE pairwise comparisons between the three locations, using Alba as control, were carried out according to the Wald Test with a FDR = 5%. Sample specificity was assessed calculating the Shannon entropy for each gene expression profile using the Bioconductor package BioQC with the function entropySpecificity [Raw reads were quality evaluated before the data analysis using the program FastQC v0.11.5 . A qualia et al.  with thea et al.  and the a et al. . The difa et al.  setting cificity .http://www.ncbi.nlm. nih.gov/sra/) under BioProject PRJNA501857.RNA-seq data from this study have been submitted to the NCBI Sequence Read Archive  to remove possible DNA contamination. RNA was then reverse-transcribed using SuperScript® III Reverse Transcriptase kit  with random primers. Gene expression analysis was carried out using an ABI Prism 7300 sequence detection system  as described by Bui et al. . QuantitT. melanosporum and T. magnatum sequences were reported in Supporting Information  18S rRNA was used as the housekeeping gene. Relative gene expression levels were calculated with the 2-ΔΔCt method [T. magnatum, starting from the one described in T. melanosporum by [T. melanosporum genetic information was due by the lacking of genetic information about the genome of T. magnatum when this work was originally designed. The publication of the work by Murat et al. [T. magnatum including the sulfur pathway genes. On this basis, we browsed the sequences from the previous transcriptome profiling by sequence similarity, using genes belonging to the annotated T. melanosporum genome [T. magnatum  was carried out in the headspace mode using an autosampler AOC-5000 (Shimadzu) equipped with a fused silica fiber coated with a 50/30 μm layer of divinylbenzene/carboxen/polydimethylsiloxane, 1 cm long . The fiber was conditioned according to manufacturer’s instructions. Samples were conditioned for 5 min at 50 °C, under agitation , before exposing the fiber for 20 min at 50 °C, under continuous agitation. Analytes were then desorbed for 1 min at 260 °C in the GC injector in splitless mode (1 min). Each sample was analyzed in triplicate. Raw data related to the first 2 years of analysis (2014–2015) are already reported and processed with different statistical methods .GC–MS and GC-FID runs were carried out on a two parallel GC-QP2010 and GC2010 instruments . The GC column used was a 30 m × 0.25 mm i.d. × 0.25 μm df Supelcowax-10 column (Millipore-Sigma). Helium was exploited as carrier gas, at a constant linear velocity of 30.0 cm/s, which corresponded to an inlet pressure of 26.4 kPa for GC-MS and 97.4 kPa for GC-FID. The temperature program was the same in both analysis-type: 40 °C at 3 °C/min to 250 °C, at 10 °C/min to 280 °C, held 10 min.GC-MS ion source temperature was set at 200 °C; the interface temperature at 250 °C. Scan range was set to m/z 40–360, with a scanning rate of 2000 amu/s. FFSNC 3.0 (Shimadzu) and NIST11 (Wiley) commercial libraries were used for identification, applying two filters, namely a spectrum similarity match over 85% and Linear Retention Index (LRI) (related to a C4-C24 FAMEs mixture) agreement in the ±15 range.The FID temperature was set at 280 °C (sampling rate 40 ms) and gas flows were 40 mL/min for hydrogen and 400 mL/min for air, respectively.The data handling was supported by GCMSsolution ver.4.30 and GCsolution software (Shimadzu) for GC-MS and GC-FID analysis, respectively.m/z) of identifiable compounds to small molecules (e.g. < 70 amu), for which other spectrometers do not show the required sensitivity. VOCs emitted from samples were collected from each area  during 4 different years (2014–2017); details are reported in Table m/z as previously reportedin Vita et al. [3O+ as reagent ion for the proton transfer reaction. The reaction takes place between H3O+ ions and all the biogenic or anthropogenic VOCs having a proton affinity higher than that of water . Separation of single ions happens accordingly to their mass to charge (m/z) ratio. Drift applied voltage was set at 600 V, temperature at 110 °C, and pressure at 2.25 mbar. For each sample, about 6 g of material was transferred in a glass jar provided with a special lid that allowed Teflon connection to a zero-air generator (inlet) and the PTR-ToF system (outlet). The head space was then measured by direct injection into the PTR-ToF drift tube inlet for 150 s, after respectively 1 and 20 min of exposure.Samples were subjected to analysis of VOCs. Accurate analysis of VOCs took advantage by the use of an innovative instrument, such as PTR-MS , 93–95,  years 204–2017; da et al. . Volatilm/z = 315 were simultaneously detected and recorded with 1 s as integration time. Internal calibration was based on m/z = 18.0338 (NH4+), m/z = 21.0202 (H318O+) and m/z = 29.9974 (NO+). For more detailed explanation see Lindinger et al. [cps) were acquired with TofDaq software . For each sample, the average data resulting from consecutive 20 s of measurement were extracted after 1 and 20 min from the beginning of the experiment. At least six technical replicates were performed for each sample as well as each year of analysis.Preliminary measurements on an empty jar were run before every experiment and used for background subtraction. All mass spectra up to r et al.  and BrilQuantitative differences  data were then primarily normalized on the base of the surface/weight rapport of the analyzed fruiting bodies (sup/vol).T. magnatum samples obtained by GC-MS (4 years) and 65 VOCs spectra from 92 samples obtained by PTR-ToF-MS (4 years), respectively. Two distinct models were built up to compare the ability of the different chemometric approach to correctly classify the three different genotypes of truffles, independently from the sampling time. As a pre-processing step, data were submitted to a logarithmic (log10 + 1) transformation and auto-scaling. The whole data set was each time split into training and validation subsets, optimally chosen with the Euclidean distances based on the algorithm of Kennard and Stone [p = 0.01) were also calculated. A random permutation of the class labels (permutation test) was also performed (500 iterations), with the aim to generate nonsense datasets for comparison with the true model and to evaluate the probability that the model was significantly different from one casually built up under the same conditions. PLS-DA was performed by PLS-Toolbox v. 8.0.2  for MATLAB® R2015b . Data from PTR-ToF analysis were then submitted to Canonical correspondence analysis (CCoA), with the aim to detect possible correlations among VOC and climatic conditions. This method allows comparing two sets of variables, extracting ordination axes that are linear combinations of VOCs (criterion variables) explaining at the same time as much as possible of the variance in the environmental data  (supervised method) were applied on the 165 VOCs spectra from 64 nd Stone . The traAdditional file 1: Table S1. Summary results of post-hoc tests performed on quantitative protein spot data obtained from 2-DE gel analysis of Alba (AL), San Miniato (SM) and Isernia (IS) fruiting bodies.Additional file 2: Table S2. Protein identified by nanoLC-ESI-LIT-MS/MS analysis. Proteins were sorted based on their exponentially modified Protein Abundance Index (emPAI). Shadings highlight uncharacterized proteins.Additional file 3: Table S3. Additional information related to the uncharacterized and predicted proteins identified through mass spectrometry.Additional file 4: Table S4. Summary of sulfur-related proteins identified by nanoLC-ESI-LIT-MS/MS analysis.Additional file 5: Table S5. RNA-seq statistics from Vita et al. [a et al. .Additional file 6: Figure S1. Euclidean distance among samples. The heat map shows sample to samples distances indicating the strong correlation between biological replicates. The distance matrix was calculated from the normalized expression dataset using the variance-stabilizing transformations function from the Bioconductor package DESeq2. Data were hierarchically clustered based on sample distances. Biological replicates are indicated as r1 (year 2014) and r2 (year 2015). Shades of grey represent different extents of correlation among samples; black represents perfect positive correlation.Additional file 7: Figure S2. Volcano plots representing the differentially expressed genes based on RNA-seq data. Pairwise comparisons are shown for San Miniato vs Alba (a) and Isernia vs Alba (b). Yellow dots highlight DEGs selected for |log2 fold change| > 1.5 and FDR < 0.05.Additional file 8: Table S6. Top 100 transcripts related to San Miniato – Alba comparison .Additional file 9: Table S7. Top 100 transcripts related to Isernia – Alba comparison .Additional file 10: Figure S3. Sample gene specificity. Shannon entropy (SH) distribution of T. magnatum genes (n = 6665) based on the expression data . A SH coefficient > 0.6 represents the gene-specific expression associated to each T. magnatum ecotype  data related to sample comparisons. Data sheets A) DEGs related to comparison San Miniato (SM) vs Alba (AL); B) DEGs related to comparison Isernia (IS) vs Alba (AL); C) DEGs identified in both the comparisons ; D) DEGs identified only in San Miniato (SM) vs Alba (AL); E) DEGs identified only in Isernia (IS) vs Alba (AL); F) Gene specificty reported in TPM (transcripts per million) for each sample.Additional file 12: Table S8. Sample-specific expression of T. magnatum genes involved in sulfur metabolism.Additional file 13: Table S9.T. magnatum genes involved in the sulfur metabolism and annotated in T. melanosporum.Additional file 14: Figure S4. Relative expression level of the genes selected for the qPCR. Relative levels were expressed, for each gene, as fold change (FC) from the reference sample SM 2014. Data are mean values of transformed data (log10(FC + 1) related to gene expression (n = 4), calculated with the 2-ΔΔCt method [t method . LettersAdditional file 15: Table S10. Compounds identified through GC-MS analysis.Additional file 16: Table S11. PLS-DA (GC MS model) statistics for each Y-Block  related to 64 truffle samples.Additional file 17: Table S12. VIPs compounds (GC-MS data) according to PLS-DA analysis. Compounds that displayed VIP scores ≥2 (bold marked) in at least in one sample are shown.Additional file 18: Table S13. Compounds identified through PTR-ToF analysis conducted during 4 years of experimental work.Additional file 19: Table S14. PLS-DA (PTR-ToF-MS model) statistics for each Y-Block  related to 92 truffle samples.Additional file 20: Table S15. VIPs compounds (PTR-ToF data) according to PLS-DA analysis.Additional file 21: Table S16. Climatic parameters on the fruiting bodies sampling area for the four-year period 2014–2017 used for statistical analysis of PTR-ToF data (CCoA).


Sexually transmitted infections (STIs) are associated with pelvic inflammatory disease and tubal pathologies. Given the tubal origin of a proportion of ovarian cancers, STIs may be relevant in their aetiology.Chlamydia trachomatis, Mycoplasma genitalium, herpes simplex virus type 2, and against human papillomavirus oncogenes  were measured in prediagnosis plasma samples in a nested case–control study in the Nurses’ Health Studies (n = 337 cases 1:1 matched to controls). Logistic regression was used to estimate multivariable-adjusted relative risks (RRs) and 95% confidence intervals [CIs] comparing women seropositive vs. seronegative among all cases (invasive and borderline), invasive (n = 257), and invasive serous ovarian cancers; n = 170), and borderline ovarian tumours (n = 80).Antibodies indicating past infection with C. trachomatis seropositivity was associated with higher risk of ovarian cancer overall (RR = 2.07 [1.25–3.43]); results were similar for invasive, invasive serous, and borderline tumours. We observed no associations for the other STIs. Relative to women seronegative to all infections, strongest associations were observed for seropositivity to C. trachomatis plus another STI ; however, the RRs were not significantly different.C. trachomatis infection may increase ovarian cancer risk; additional studies are required. Chlamydia trachomatis and Mycoplasma genitalium and viral infections like human papillomavirus (HPV) and herpes simplex virus type 2 (HSV-2), can induce persistent changes in the female genital tract. C. trachomatis and M. genitalium are associated with pelvic inflammatory disease (PID), salpingitis, and tubal infertility.3 PID was associated with increased ovarian cancer risk in a recent meta-analysis,4 providing indirect evidence for a role for STIs in the aetiology of the disease. STI-induced tubal pathologies may be relevant given that a proportion of ovarian tumours likely originate in the fallopian tube,6 with tubal involvement or precursor serous tubal intraepithelial carcinomas (STICs) observed in up to 70% of high-grade serous ovarian cancers.7Sexually transmitted infections (STIs), including bacterial infections such as C. trachomatis and ovarian cancer risk are suggestive of an association12; data on other STIs are sparse.12 Infection with mucosal high-risk types of HPV  is recognised as a cause of cervical and other anogenital malignancies.13 Incidence of STIs is rising in many developed countries, with 1.6 million reported cases of C. trachomatis in the United States in 2016.14 There are relatively few modifiable risk factors for ovarian cancer; STI prevention would provide a target for primary prevention of this often-lethal disease. To investigate the association between STIs and ovarian cancer risk, we conducted a nested case–control study on seropositivity to C. trachomatis and M. genitalium, HSV-2, and multiple proteins of HPV16, HPV18, and HPV45, with risk of borderline ovarian tumours (BOT) and invasive epithelial ovarian cancer (iEOC) in the Nurses’ Health Study (NHS) and NHSII among 337 cases and 337 matched controls.Prior retrospective studies, and a single prospective study, on 15 The NHSII began in 1989 with 116,429 female registered nurses ages 25–42 years, using the same approach. Participants in both cohorts have been followed biennially to update information on lifestyle factors and ascertain disease diagnoses.The NHS was initiated in 1976 when 121,700 registered nurses, ages 30–55 years, completed and returned a mailed questionnaire.16 A second collection among 15,982 women (ages 44–68 years) was carried out between 2008 and 2011. Similar methods were used for all collections.19 Heparin plasma samples have been stored in liquid nitrogen freezers since collection. This study was approved by the Institutional Review Board of the Brigham and Women’s Hospital .In 1989–1990, 32,826 NHS participants provided a blood sample (ages 43–70 years); in 2000–2002, a subset of 18,743 of these participants (ages 53–80 years) provided a second sample. Between 1996 and 1999, 29,611 NHSII participants (ages 32–54 years) provided blood samples.n = 271; NHSII, n = 66) were diagnosed through June 1, 2016 (NHS) and June 1, 2015 (NHSII). Cases were matched to one control, who was alive and had intact ovaries at the time of case diagnosis (see Eligible cases were diagnosed with confirmed incident ovarian cancer (i.e. BOT or iEOC) after first blood collection. A total of 337 cases ) into subgroups with higher vs. lower antibody levels using the median in all C. trachomatis positive women (2668 MFI) as the cut point.In addition to evaluating the individual infections, we compared women seropositive for n = 53). We evaluated heterogeneity by rapidly fatal disease (died within 3 years of diagnosis) and less aggressive disease (survived at least 3 years following diagnosis) comparing models allowing vs. not allowing the association for the STI to vary by disease aggressiveness using a likelihood ratio test.24Conditional logistic regression was used to estimate relative risks (RRs) and 95% confidence intervals [CIs] for ovarian cancer overall. Unconditional logistic regression, adjusted for the matching factors, was used in analyses restricted to BOT, iEOC, and serous iEOC; there were too few cases of other histotypes  to assess separately , oral contraceptive (OC) use , tubal ligation , marital status , and weight change between ages 18 and blood collection ; these variables were selected a priori based on their association with ovarian cancer or STI prevalence. Additional adjustment for family history of breast and/or ovarian cancer, non-steroidal anti-inflammatory or aspirin use , or depressive symptoms  did not change effect estimates by ≥10%.n = 127) or who were nulliparous (n = 84) were excluded in sensitivity analyses. Statistical analyses were conducted in SAS 9.4 . All statistical tests were two sided, and p < 0.05 was considered statistically significant.Potential effect modification by menopausal status at blood collection and diagnosis , age at blood collection (<60 vs. 60+ years), and ever OC use was evaluated by including interaction terms and evaluating the Wald test. Women reporting tubal ligation (n = 257), and 66% of invasive cases were of serous histology (n = 170)  and predominantly postmenopausal (69%). Cases were diagnosed at median age of 68 years (range: 37–89); 76% were diagnosed with invasive disease  .Seropositivity to at least one STI was observed in 25% of the study population; seropositivity to s) Table . Eight pC. trachomatis infection was associated with a two-fold increased risk of ovarian cancer (RR: 2.07 [95% CI: 1.15–3.43]); results were similar for invasive (1.98 [1.21–3.23]) and invasive serous disease (2.31 [1.33–4.01]), and BOT (2.11 [1.04–4.28]) . No significant association for antibodies to other individual infections and ovarian cancer risk was observed (p ≥ 0.11) including in the HPV L1 analyses (data not shown). M. genitalium had a suggestive positive association despite the low seroprevalence (1.92 [0.78–4.72]).Seropositivity to C. trachomatis plus the other infections and ovarian cancer risk. Relative to women seronegative to all evaluated infections, seropositivity to C. trachomatis and any other infection was associated with a 2.74-fold higher risk of ovarian cancer (95% CI: 1.20–6.27), whereas C. trachomatis alone was associated with a 1.88-fold higher risk (95% CI: 1.03–3.42) .We next evaluated antibodies to C. trachomatis, RR: 1.94 [1.17–3.21]; Table M. genitalium and ovarian cancer risk (RR: 3.40 [1.25–9.27]). We observed no significant differences in the associations by menopausal status at blood collection or diagnosis, age at blood collection, or ever OC use. Further, the associations did not differ significantly for rapidly fatal and less aggressive disease (p ≥ 0.18).Associations excluding women with a tubal ligation were generally similar , though effect estimates were not significantly different. Associations were similar or slightly stronger when restricting to cases with invasive serous disease; this association is notable given that relatively few risk factors have been identified for this subtype. Our associations were robust across different subsets of women, including those with a prior tubal ligation and parous women.This study suggests that past/current infection with C. trachomatis may directly affect ovarian carcinogenesis as it induces DNA double-strand breaks, interferes with the DNA damage response,25 and inhibits apoptosis in the host cell.26 Importantly, C. trachomatis and M. genitalium in particular may indirectly influence ovarian cancer development through increasing inflammation in the genital tract. Specifically, these infections are an important cause of salpingitis and other tubal pathologies,27 including tubal damage-inducing PID.28 This may be particularly relevant for the serous histotype, as the fallopian tube has been identified as the origin of the majority of these tumours,6 with STICs as a suggested precursor lesion.29 Inflammation, and inflammation-related sequelae, are likely major mechanisms linking STIs and PID to higher ovarian cancer risk, and inflammation31 and its downstream impact on immune suppression may play a role in risk of ovarian cancer regardless of subtype. A recent meta-analysis of 13 studies reported a significant association between history of PID infection and ovarian cancer risk (RR: 1.25 [1.06–1.44]), though this association was limited to borderline disease , and no histology-specific estimates were provided.4 Price et al. recently estimated probabilities ranging from 12% to 16% of C. trachomatis infection leading to clinical PID.32 No data on PID or self-reported infection status were available in our study; thus we could not investigate this as a potential mediator.11 have assessed different IgG antibodies (e.g. heat shock protein 60—type 1 (cHSP60-1),8 elementary bodies of serovar D10). Results from these studies are mixed, in part, because the antibodies have higher cross-reactivity with other chlamydial and bacterial infections than the gold standard Pgp3-based antibody. Further, it is unclear whether having ovarian cancer or being under treatment may alter the expression of IgG antibodies. More recent data from Trabert et al. using the same laboratory methods as this study reported a positive association between antibodies to C. trachomatis infection and iEOC risk in a population-based case–control study in Poland (n = 244 cases) and in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial (n = 159 cases).12 In the latter study (as in our study), blood samples were collected prior to diagnosis of ovarian cancer, reducing impact of disease status  on immune functioning.Retrospective data on history of chlamydia infection and ovarian cancer riskC. trachomatis using the laboratory cut point). In the current study, we did not observe that, among seropositive women, higher titres of C. trachomatis antibody levels were more strongly associated with risk. While higher antibody levels may be associated with severity or number of past infections or with more severe tubal damage,33 antibody levels in response to an infection are a function of many other factors including age at infection and individual-level immune response. Further research is needed to better understand how antibody titres relate to disease severity and carcinogenic-related damage and inflammation to the fallopian tubes and ovaries.In the PLCO study, a significant association was only observed when a higher cut point was used to define Pgp3 positivity ; elevated cut point based on Poland study, RR = 2.25 [1.07–4.71]), whereas in the current study, a two-fold increase in risk was observed using the laboratory cut point (RR = 2.07 [1.25–3.43]). This may, in part, be due to the larger sample size in our study or underlying differences in the study populations  in the fallopian tube following infection.35M. genitalium seropositivity was associated with borderline, but not invasive, tumours in one small study,8 and the expression of viral microRNA, predominantly mapped to HSV-1 and HSV-2 genomes, was observed to be higher in serous ovarian carcinomas than in normal tissue.36 Trabert et al. observed a 47% higher risk of iEOC among women seropositive to M. genitalium in the Poland case–control study, but no association in PLCO; HSV-2 was also not related to risk in that study.12M. genitalium is thought to be a cause of PID and warrants further study in larger populations with a higher seroprevalence. HPV oncoproteins promote genomic instability and proliferation and inhibit apoptosis,37 and high-risk HPV types are causally linked to cervical cancer, other anogenital cancers, and cancers of the head and neck.13 These infections have been minimally explored in relation to ovarian cancer but, in general, have not been related to ovarian cancer development,38 suggesting that HPV does not infect ovarian or fallopian tube cells.We observed no significant association between antibodies to C. trachomatis and ovarian cancer risk appeared stronger when a woman was also seropositive to M. genitalium or HSV-2. This may reflect higher incidence of tubal pathologies following infection with multiple STIs or, alternatively, may be the sequelae of a constellation of other factors . A limitation of our study is the lack of data on covariates such as sexual history and history of PID and/or other pelvic diseases and their treatment, thus it is possible that our results are, in part, due to residual confounding by these factors. As no studies have examined the relationship of sexual history with ovarian cancer risk, it is unclear whether this may be an important confounder.The association between This study assessed antibodies indicating history of STI infection using a validated assay in blood samples collected median 7 years prior to diagnosis. Antibodies are relatively stable in blood, thus we expect misclassification of exposure to be minimal and non-differential. However, while we know that an infection was present at or at some time prior to blood collection, and thus diagnosis, we cannot assess when the infection initially occurred, or whether subsequent infections manifested in the interval between blood collection and diagnosis, or what proportion of women with negative serology had history of an infection but did not seroconvert. We expect these issues be similar among women who developed ovarian cancer after blood collection and women who remained cancer-free and thus would result in non-differential misclassification of the exposure.C. trachomatis infection, with strongest associations observed among women seropositive to C. trachomatis and another STI . Additional experimental studies to establish causality, epidemiologic studies including data on PID to investigate this potential mediator, and larger epidemiologic studies to evaluate disease subtype are needed to confirm these associations. If these results are confirmed, it would suggest that STI prevention and early detection efforts, including vaccine development, may represent an opportunity to reduce ovarian cancer risk.In summary, in a large, prospective epidemiologic study, we observed an increased risk of ovarian cancer overall and of the serous histotype among women seropositive for Supplemental Materials and MethodsSupplemental Tables S1 and S2


V. bonariensis could be adapted to this very situation. In our study, the Cd tolerance in V. bonariensis was analyzed as well as an overall analysis of transcriptome.Cadmium (Cd) is a serious heavy metal (HM) soil pollutant. To alleviate or even eliminate HM pollution in soil, environmental-friendly methods are applied. One is that special plants are cultivated to absorb the HM in the contaminated soil. As an excellent economical plant with ornamental value and sound adaptability, V. bonariensis to Cd stress was investigated in four aspects: germination, development, physiological changes, and molecular alterations. The results showed that as a non-hyperaccumulator, V. bonariensis did possess the Cd tolerance and the capability to concentration Cd. Under Cd stress, all 237, 866 transcripts and 191, 370 unigenes were constructed in the transcriptome data of V. bonariensis roots. The enrichment analysis of gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway revealed that differentially expressed genes (DEGs) under Cd stress were predominately related to cell structure, reactive oxygen species (ROS) scavenging system, chelating reaction and secondary metabolites, transpiration and photosynthesis. DEGs encoding lignin synthesis, chalcone synthase (CHS) and anthocyanidin synthase (ANS) were prominent in V. bonariensis under Cd stress. The expression patterns of 10 DEGs, validated by quantitative real-time polymerase chain reaction (qRT-PCR), were in highly accordance with the RNA-Sequence (RNA-Seq) results. The novel strategies brought by our study was not only benefit for further studies on the tolerance of Cd and functional genomics in V. bonariensis, but also for the improvement molecular breeding and phytoremediation.In this study, the tolerance of  HM pollution in soil has long jeopardized the sustenance of plants. As a kind of poisonous HM, Cd served as a botanic destroyer . AbsorbeThe excessive concentration of HMs has a severe impact on the growth, plasma membrane permeability, physiological and biochemical processes and nutritional status of plants . The incIris lactea var. chinensis under Cd and Pb stresses. Yongkun et al. [Phytolacca americana L. Gao et al. [S. alfredii Hance shoots than that in non-hyperaccumulating ecotype shoots under exposing Cd stress. Similar results were also reported in Populus × canescens [Noccaea caerulescens [N. caerulescens [Viola yedoensis Makino [Arabidopsis thaliana [The RNA-Seq platform was used for the detection of plants under Cd stress. Gu et al.  investign et al.  conducteo et al.  demonstranescens , Noccaeaulescens , N. caerulescens , Viola ys Makino  and Arabthaliana  using trV. bonariensis, especially with the popularity of sightseeing farms, it owned the potential in large scale cultivation. Therefore, the rehabilitation ability of V. bonariensis under HM stress secured the spotlight. In this study, we investigated the germination, morphologic and physiologic response along with the Cd2+ accumulation in V. bonariensis. In addition, a high-throughput sequencing technique was applied to construct the transcriptome database of V. bonariensis under Cd stress. The molecular mechanism of transportation and detoxification of Cd was analyzed based on sequence annotation. This study would made contribution to the discovery of potential Cd defensive strategies in V. bonariensis.Due to strong adaptability, vigorous growth and highly ornamental value of 2+ on the seed germination depended on its concentration. Germination rate and Germination index (GI) was higher at 20 mg/L than that of controlling groups. In 20 mg/L and below, vigor index (VI) and fresh weight were promoted on various degrees. At 14 d, all the seedlings treated with over 50 mg/L concentrations of Cd died.Table The contents of Cd in the shoots and roots increased with Cd concentration and time, while the Cd contents in roots were significantly higher than those in the shoots Fig. a, b. WheAccording to the measurement of various morphological  and proline (PRO) as well as the GSH activity in leaves and roots. The superoxide dismutase (SOD), peroxidase (POD), catalase (CAT) and ascorbate peroxidase (APX) were elevated in leaves while decreased in roots under Cd stress  slightly increased  of Sesamum indicum  offered a prior similarity with V.bonariensis, then did the Erythranthe guttata .Compared with the public seven databases, a total of 153, 895 80.41%) annotative unigenes were obtained. The successful rate of the functional annotation in the seven databases was shown in  unigenes were annotated and there were 50.98% in Biological process (BP), 35.44% in Cellular component (CC), and 13.57% in Molecular function (MF)  etc), and organic acids . These mBacopamonnieri under Cd stress [Amino acid, as one of the plant’s fundamental metabolites, counted great deal in the alleviation of HM stress. It served as integral part of the involved coenzyme and ligand in the metal complexation . Cd stred stress .2+ entered the cytoplasm through the cell wall and cell membrane, it combined with PC to form LMW complex, which was transferred into vacuole under the action of htm1 membrane transportation protein. Then HMW complexes were synthesized by LMW and Cd, eventually immobilized in vacuole. The HMW complexes were less toxic to plants. PCs was a sulfhydryl polypeptide composed of cysteine, glutamic acid and glycine. As the precursor of PC synthesis, GSH composed some sulfur-containing compounds in root cells and Cd2+ to form stable chelates [For the great affinity to HMs, PCs chelate various HMs to deactivation . When thchelates . In our V. bonariensis were significant up-regulated in our results. It was estimated that the efficiency of organic acid synthesis was elevated. This promoted the binding of Cd2+ to organic acids in the cytoplasm or vacuoles, and alleviated the damage of HMs to V. bonariensis. The organic acids secretion capacity in Cd-tolerant plants such as Rorippaglobosa was far greater than that in non-tolerant plants Rorippa [Bechmerianivea could secrete organic acids in its rhizosphere. With Cd chelating, the consistency of Cd2+ around the rhizosphere of Bechmerianivea decreased [V. bonariensis under Cd stress, there were three pathways relating to organic acid metabolism among top-ten up-regulated pathway, including ‘Citrate cycle’, ‘Glyoxylate and dicarboxylate metabolism’ and ‘alpha-Linolenic acid metabolism’. The result proved the significant function of organic acid metabolism in V. bonariensis under Cd stress.The organic acids of plants, such as oxalic acid, malic acid and citric acid, could be transformed the toxic Cd into low toxic or non-toxic form by chelating, promoting the tolerance of plants . The pat Rorippa . The impecreased . In tranV. bonariensis resist the damage of Cd stress.Although minor to plant growth and development, secondary metabolites were often involved in environmental stress . The pheLupinus luteus L., the phenylpropanoid pathway metabolites elevated Pb tolerance in its roots [V. bonariensis  pathway and inhibit transpiration in plants. These elements disturbed stomatal opening. In addition, Cd stress reduced the length and number of roots, limiting water intake  increased  pure water was used as controlling group. The two sheets of filter paper were placed in a culture dish of 9 cm in diameter. Ten milliliters of treatment solution were added to saturate filter paper. The wet filter paper was used as a bed for germination. Thirty seeds were placed in each dish, sorted to a total of three replicates. All experiments were performed three times to ensure biological repetitions. The dishes were placed in the incubator . The culture dish was sealed with a sealing film to keep humidity. The germination condition was observed daily until the germination of the controlling group revealed unchanged. The incubation time was about 2 weeks.Germination rate (%) = number of germinated seeds within 7 days/ total seed * 100%;GI = ∑Gt /Dt ;VI = GI * biomass  .The robust plants with health growth were selected for soil Cd stress treatment. Seedling age was 30-day old. One seedling was planted in each plastic flowerpot. Fifteen pots were involved in each treatment. The perlite and peat soil  were mixed evenly at 1:1 (v: v) and sterilized with right amount of carbendazim. With 15-day air-dry, the mixed soil was put into the circular plastic flowerpot (d = 12 cm) on the standard of 1 kg per pot. The soil moisture content was controlled as 70% using the RO water (about 180 ml).V. bonariensis was measured. A total of 50 mg/kg (T1), 100 mg/kg (T2), 200 mg/kg (T3), 300 mg/kg (T4), and 400 mg/kg (T5) were set up for 5 Cd concentrations. The CK were treated without Cd solution. Three seedlings were planted in each pot, each treatment with 10 pots. During the experiment, plants and soil samples were collected every 10 days for 4 times.(1) Cd treatment of different concentration was designed. In order to obtain detailed and accurate data, the content of Cd in 2·21/2H2O and RO water were mixed to form 150 ml Cd solution with different concentrations. The mix solution was applied evenly into the corresponding flowerpot on the first day. After 20 days under Cd stress, the roots were harvested. The root samples were immediately frozen in liquid nitrogen and stored at − 80 °C. In this experiment, the seedings were grown in ambient conditions with a photoperiod of 14 h at 25 °C and a relative humidity of 75%.(2) Cd treatment for RNA-Seq was arranged. The experiment was repeated three times with a total of 90 pots. The CK were treated without Cd solution. The concentration of Cd in the experimental group was 100 mg/kg. CdCl3-HCLO4 per 0.5 g. The atomic absorption flame spectrophotometer was applied to determine the content of Cd. All of the above experiments were repeated three times.Plant  and soil samples were collected and dried. These samples were crushed. Then the samples were digested by HNOplant /Csoil;BCF = Coverground part /Csubterranean part;BTF = Cplant was the concentration of HM in a part  of the plant (mg/kg); Csoil was the concentration of corresponding HM element in soil (mg/kg); Coverground part was the concentration of HM in the upper part of the plant (mg/kg); Csubterranean part was the concentration of HM in lower parts of plant (mg/kg) [In the formula, C (mg/kg) .2O2 and O2−) methods referred to Wang et al. [290 changes were measured per minute [− 2 s− 1 [The leaf and root samples were collected. Some of them was used for morphological measurement. Others were immediately frozen in liquid nitrogen and stored at − 80 °C for physiological measurements. Morphological features were measured according to Bai et al. . Histochg et al. . The cong et al. . Nitro-bg et al. . APX actr minute . The actr minute  and Bater minute , respect− 2 s− 1 .The content of lignin and anthocyanidin in roots was measured by referring to the method of Chang XF et al.  and DedaV. bonariensis. RNA-Seq analysis were performed with three replicates. Total RNA isolation was performed with Trizol Reagent (Invitrogen) according to the manufacturer’s protocol. RNA purity and concentration were checked using the NanoPhotometer® spectrophotometer  and Qubit® RNA Assay Kit in Qubit® 2.0 Flurometer , respectively. In brief, mRNA was enriched from total RNA using poly-T-oligo-attached magnetic beads. as template to synthesize double stranded cDNA, mRNAs were purified with AMPure XP beads . the purified double stranded cDNA was subjected to terminal repair and then supplemented with A tail to connect sequencing connector. In order to select cDNA fragments of preferentially 150~200 bp in length, the library fragments were purified with AMPure XP system. At last, PCR was performed with Phusion High-Fidelity DNA polymerase, universal PCR primers and Index (X) Primer. The qualifed libraries assessed on the Agilent Bioanalyzer 2100 system were sequenced on an Illumina Hiseq2500 platform.Roots with two different treatments were collected from E-value of ≤10− 5, while compared with euKaryotic Ortholog Groups (KOG) with an E-value of ≤10− 3. The HMMER3 program was used to assign Protein family (Pfam) with an E-value = 0.01. GO using Blast2GO v2.5 program with an E-value = 1e− 6. According to the KEGG database, pathway assignments were carried out using BLASTx with E-value = 1e− 10.After filtering, clean data was obtained. Transcriptome de novo assembly was accomplished using Trinity with min-kmer-cov set to 2 by default. A BLASTx search was used for further functional annotation of the unigenes against the NCBI non-redundant protein sequences (Nr), NCBI nucleotide sequences (Nt) and Swiss-prot with an M-value. DESeq [p-value of the results. DEGs screening condition was FDR < 0.05.The input data of gene differential expression is the read count data obtained in the analysis of gene expression level. The read count data were standardized by trimmed mean of e. DESeq  was usede. DESeq  to contrActin gene  was served as a reference control to detect expression level of 10 DEGs. The primer sequences were shown in . The significance test of difference was made by the LSD method, significance level setting Additional file 1: Figure S1. Changes of Verbena bonariensis biomass under Cd different concentration stress.Additional file 2: Figure S2. Changes of Verbena bonariensis morphological indexes under Cd different concentration stress. (a) Leaf area; (b) petiole long; (c) Plant height; (d) Root length; (e) Number of lateral roots.Additional file 3: Figure S3. Changes of Verbena bonariensis physiological indexes under Cd different concentration stress. (a) POD activity; (b) SOD activity; (c) APX activity; (d) Soluble sugar content; (e) Soluble protein content; (f) PRO content; (g) GSH activity; (h) MDA activity.Additional file 4: Figure S4. Unigenes notes success statistics in each database.Additional file 5: Figure S5. Unigenes classified statistics based on GO annotations.Additional file 6: Table S1. DEGs encoding lignin synthesis in ‘phenylpropanoid biosynthesis’ pathway.Additional file 7: Table S2. DEGs encoding chalcone synthase (CHS) and anthocyanidin synthase (ANS).Additional file 8: Table S3. The primers of 10 DEGs and different parameters derived from qRT-PCR analysis.


Enterobacteriaceae species isolated from hospital- acquired and community-acquired UTIs against fluoroquinolones and correlate its levels with the existing genetic mechanisms of resistance.Fluoroquinolones are commonly recommended as treatment for urinary tract infections (UTIs). The development of resistance to these agents, particularly in gram-negative microorganisms complicates treatment of infections caused by these organisms. This study aimed to investigate antimicrobial resistance of different Enterobacteriaceae isolates recovered from UTIs were tested for antimicrobial susceptibility. Plasmid-mediated quinolone resistance (PMQR) genes and mutations in the quinolone resistance-determining regions (QRDRs) of gyrA and parC genes were examined in quinolone-resistant strains.A total of 440 nrB was the most frequent gene (62.9%) of resistant isolates. Co-carriage of 2 PMQR genes was detected in isolates (46.9%) with high resistance to ciprofloxacin (CIP) (MICs > 128 μg/mL), while co-carriage of 3 PMQR genes was detected in (6.3%) of resistant isolates (MICs > 512 μg/mL). Carriage of one gene only was detected in intermediate resistance isolates (MICs of CIP = 1.5–2 μg/mL). Neither qnrA nor qnrC genes were detected. The mutation at code 83 of gyrA was the most frequent followed by Ser80-Ile in parC gene, while Asp-87 Asn mutation of gyrA gene was the least, where it was detected only in high resistant E. coli isolates (MIC ≥128 μg/mL). A double mutation in gyrA (Lys154Arg and Ser171Ala) was observed in high FQs resistant isolates (MIC of CIP < 128 μg/mL).About (32.5%) of isolates were resistant to quinolones and (20.5%) were resistant to fluoroquinolones. All isolates with high and intermediate resistance phenotypes harbored one or more PMQR genes. QgyrA and parC genes while a mutation in one gene only can explain quinolone resistance. Accumulation of PMQR genes and QRDR mutations confers high resistance to FQs.FQs resistance is caused by interact between PMQR genes and mutations in both  Moreover, the presence of PMQR determinants may promote QRDR mutations increasing the FQs resistance rates [Enterobacteriaceae species in immunocompetent patients was not addressed. Accordingly, the aim of the current study was to investigate antimicrobial resistance of different Enterobacteriaceae species isolated from CA-UTI and HAUTI against FQs and correlate its levels with the existing genetic mechanisms of quinolones (Qs) resistance.Urinary tract infections (UTIs) are common infectious diseases in both hospital- acquired UTI (HAUTI) and community-acquired UTI (CA-UTI) , 2. UTI s of UTI . UTIs mah CA-UTI  and hosph CA-UTI . FQs resth genes . Howeverhe world . The co-ce rates . Some stce rates , 11, but5 CFU/mL were only included. The study populations were adults (> 18 years). About 32.2% of participants were males and 67.8% were females. The study included 418 outpatients (attended at outpatient’s clinics seeking the treatment) and 286 inpatients . This study was carried out according to the principles of the declaration of Helsinki. The study was approved by the Medical Ethics Committee of Minia university Hospital, Egypt. As the study used anonymous clinical data, the patients were not required to give informed consent for the study (code: 45 A at 2/5/2016).This is a cross-sectional study was conducted in Minia university hospitals, Egypt, from July 2016 to March 2017. A total of 705 patients with suggested UTI  were included in the study. Urine samples with positive pyuria and urine cultures with a colony count for a single bacterial species ≥10Enterobacterecieae strains were kept in trypticase soy broth with sterilized 15% glycerol at − 20 °C. A total of 440 non-repetitive Enterobacterecieae isolates were recovered from urine samples.Urine specimens were collected from symptomatic patients in sterile screw capped containers that were transported within 2 h of collection to bacteriology laboratory in an ice box and processed at once. Well-mixed uncentrifuged urine specimens were streaked by semi-quantitative streaking method onto UTI chrome agar  and by calibrated loop technique on MacConkey and blood agars . After oEnterobacteriaceae isolates to different antibiotics; amoxicillin/clavulanic acid (AMC) 30 μg, ceftriaxone (CRO) 30 μg, ceftazidime (CAZ) 30 μg, imipenem (IPM) 10 μg, amikacin (AK) 30 μg, sulphamethoxazole/ trimethoprim (SXT) 25 μg, and nitrofurantoin (F) 300 μg. Also 4 different antibiotics discs for quinolone (Q) and fluoroquinolones (FQs) resistance were used; nalidixic acid (NA) 30 μg, ciprofloxacin (CIP) 5 μg, norfloxacin (NOR) 10 μg and ofloxacin (OFX) 5 μg . Minimum inhibitory concentration (MIC) of ciprofloxacin (CIP) was determined by two methods; MIC strips (E test) which graded from 0.002 to 32 μg/mL and agar dilution method. MIC strips (E test)  were placed on surfaces of inoculated Mueller-Hinton agar plates as explained previously [According to CLSI guidelines , disk dieviously . MIC deteviously , 15. Theeviously .qnrA, qnrB and qnrS were tested by a multiplex PCR reaction using specific primers (Table qnrC and qepA) and QRDRs of gyrA and parC genes using specific primers  according to the manufacturer’s instructions. PMQR genes; rs Table . PCR wasrs Table . Each sigyrA and parC genes were compared with corresponding reference protein sequences using BLAST software of NCBI; National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/blast). GyrA accession number used for E. coli was WP_074153749.1, for Klebsiella spp. was WP_075874334.1 and for Citrobacter spp. was WP_044266198.1. Accession number for parC was AML00471.1.Sequencing was carried out using an automated DNA sequencer and data collection software from Applied Biosystems, USA. Translated nucleotide sequences of QRDR in Statistical analysis of demographic, clinical and laboratory data of study subjects was performed using SPSS for windows version 19.0 .Enterobacteriaceae family were recovered from UTI patients with a percentage of . Two hundred and nine  were from inpatients and  were from outpatients. E. coli was the most frequent pathogen (281/440 (63.9%), followed by Klebsiella pneumoniae (K. pneumoniae) , Citrobacter spp. , Proteus spp.  and lastly Enterobacter spp. , , CRO  and AMC . while the highest susceptibility rate was found to IMP . Percentages of resistant isolates to tested antimicrobial agents are summarized in Table Of 440 Enterobacteriaceae isolates were resistant to one or more of the tested (Q and FQs). Out of them  were resistant to FQs. These isolates could be categorized into three phenotypes; high resistance phenotype which included 67 isolates that were highly resistant to all tested Q and FQs with MIC of CIP > 32 μg/mL, intermediate resistance phenotype which included 23 isolates with intermediate resistance to all tested Q and FQ with MIC of CIP =1–2 μg/mL. FQs susceptible phenotype which included 53 isolates that were resistant to NA only (Q) and susceptible to all tested FQs with MIC of CIP ≤ 1 μg/mL.A total of  E. coli, 17 Citrobacter, 9 K. pneumoniae and 10 Proteus). The most frequent PMQR gene was qnrB, which was detected in  of Q and FQs resistant isolates and in  of FQs resistant isolates. QnrS gene was detected in  of Q and FQs resistant isolates and in  of FQs resistant isolates  of Q and FQs resistant isolates and in  of FQs resistant isolates.  harbored at least one PMQR gene  of Q resistant isolates; 51 of them belong to high resistance phenotype, 20 in intermediate phenotype and 31 belong to the FQs susceptible phenotype (resistant to NA only)   of isolates  carry qnrB gene only. None of PMQR genes was found in isolates with FQs susceptible isolates (resistant to NA only). Detection of PMQR genes (qnrB and qnrS) was strongly correlated with FQs resistance levels in resistant isolates with a correlation coefficient equal to 0.8 (r = 0.8) and 0.9 (r = 0.8) respectively which was highly significant  for both genes as well as qepA gene with a correlation coefficient equal to 0.25 (r = 0.25) which was considered fair but significant . Detection of specific mutations in gyrA and parC genes was not correlated with susceptibility pattern to tested Q and FQs as these mutations were found in all phenotypes (Table All isolates with high resistance phenotype (67) harbor es Table .Enterobacteriaceae isolates were isolated from UTIs with a percentage of . The isolation rates from inpatients and outpatients were (73.1%) and (55.1%) respectively. A higher frequency of isolation (86%) was recorded previously in Asia-Pacific region [E. coli was the most frequent followed by K. pneumoniae, Citrobacter spp., Proteus spp. and lastly Enterobacter spp. These findings agree with several previous studies [Citrobacter spp. isolation rate in the current study remains the highest. The highest antimicrobial resistance rates were recorded in the present study against SXT with a percentage of (57.5%) followed by CRO (49.3%), however, none of the isolates were resistant to imipenem. These findings agree with several previous studies [qnr genes and qepA gene), the most frequent gene was qnrB, which was detected in (62.9%) of Q and FQs resistant isolates, and in (100%) of FQs resistant isolates while qnrS gene was detected in (46.9%) of Q and FQs resistant isolates and in (74.4%) of FQs resistant isolates. In other studies on Egyptian population, qnrB was the most prevalent qnr gene among K. pneumoniae isolates as denoted by El-Badawy et al., 2017 which agree with our results [qnrS was the most prevalent gene among gram negative bacilli isolated from different clinical settings [QnrB and qnrS genes detection rate in our study was higher than that reported in several previous studies [qnrA nor qnrC were detected at all, but qepA gene was detected in (10%) of FQs resistant isolates. In the same context with us, several studies also could not detect qnrA gene among Enterobacteriaceae isolates [qnrA in their isolates but could not detect neither qnrC nor qepA genes [qnr genes, type of clinical isolates or the used methods of detection. With considering the analysis of the QRDRs of gyrA and parC genes, this study reported that the mutation at position 83 of gyrA was the most frequent in Q and FQs resistant strains. Three types of amino acid changes resulted from this mutation. Change from serine to leucine in E. coli strains which was also reported by many reports [K. pneumoniae and E. coli and was also reported previously [Citrobacter strains and was reported in several studies [gyrA A (Lys154Arg and Ser171Ala) was observed in high FQs resistant Citrobacter spp. isolates with MIC of CIP ≥ 256 μg/mL and E. coli isolates with MIC of CIP ≥128 μg/mL. These mutations were reported previously in few studies [gyrA gene was the least frequent mutation, where it was detected only in high resistant E. coli isolates with MIC ≥128 μg/mL. Therefor the mutation at position 87 of gyrA seemed to contribute to high resistance to FQs, while the mutation at position 83 could contribute to both Q and FQs resistance. This suggestion agrees with other results [parC gene was frequent in both Q and FQs resistant strains that agrees with other studies [gyrA and parC genes seemed to be associated with high levels of resistance to FQs. These findings agree with other reports suggested that high levels of FQs resistance appeared to happen as a result of gradual accumulation of QRDR mutations [gyrA and parC contributes to high resistance to FQs [UTIs are common bacterial infections in hospital settings and community . In the c region . The frec region , and dis studies , 25. In  studies  so the r studies , 25, 27. studies . With th results , while o, and in 0% of FQssettings . QnrB an studies . Neitherisolates , 31. HowpA genes . The dif reports , 34 and eviously . The thi studies , 37. A d studies , 38. Asp results . Ser80Il studies . Single utations . All isoutations , while Sutations . Our stu by CRO 4.3%, howeEnterobactericeae remain the most common cause of UTIs. The resistance rate of Q is (32.5%), while the resistance to Q and FQs is (20.5%) among Enterobactericeae isolates. At least one of PMQR gene was detected in FQs resistant isolates. The most frequent gene was qnrB, which was detected in (62.9%) of Q resistant isolates followed by qnrS gene which was detected with a percentage of (46.9%). The co-existence of 2 PMQR genes in the same isolate was observed in (46.9%) of resistant isolates, while co-existence of 3 PMQR genes was reported in (6.3%). The presence of at least two PMQR genes together with simultaneous QRDR mutations in each of gyrA and parC genes can describe the mechanism of resistance in high resistance phenotype , while presence of at least one PMQR gene together with one QRDR mutation at either genes could be the cause of resistance in isolates with intermediate resistance phenotype . Presence of mutation in only one QRDR regions of gyrA or parC genes could be the cause of resistance to NA only. To our knowledge, the current study is the largest study that reported molecular epidemiology of quinolones resistance in different Enterobacteriaceae species in the study area and could suggest a phenotypic algorithm to describe genetic mechanisms of quinolone resistance.In the current study Additional file 1: Figure S1. Agarose gel electrophoresis (1%) for separation of multiplex PCR products; M is molecular size marker (100 bp ladder), lanes: 1, 2, 3 are positive for qnrB and qnrS, 4, 5 are positive for qnrB. The size of PCR products (in base pairs) is indicated on the right.Additional file 2: Figure S2. Agarose gel electrophoresis (1%) for separation of PCR products of qepA; M is molecular size marker (100 bp ladder), lanes: 1, 2, 3, 4, 5, 6, 9 are positive for qepA, 7, 8 are negative for qepA gene. The size of PCR product (in base pairs) is indicated on the right.


The independent association of neck circumference (NC) on elevated blood pressure is still uncertain in adults of China. The aim of this study is to explore such association and investigate the predictive value of NC on hypertension.A total of 4279 adults aged 20–80 years participated in the cross-sectional study in 2014. Anthropometric information, NC, body composition indexes such as waist circumference, hip circumference and body fat percentage, and blood pressure were measured. General linear regression model was used to explore the association between NC and blood pressure; Logistic regression models were fitted to calculate the multi-variable adjusted prevalence, and the association of NC with hypertension.p < 0.001). The adjusted prevalence of hypertension increased with elevated NC quartiles in both sexes (p for trend < 0.001), from 17.81 to 42.93% in male and 9.72 to 21.31% in female. For male, NC was only associated with hypertension  but not with pre-hypertension . However, in female, NC was associated with both pre-hypertension and hypertension, the BMI adjusted ORs were 1.15 (1.03–1.28) and 1.24 (1.14–1.34). The sex-specific AUCs for NC predicting hypertension were 0.633 in male and 0.663 in female, similar with AUCs of other body fat indexes.The overall prevalence of hypertension and pre-hypertension were 11.05 and 23.63%, respectively. NC was positively associated with both SBP and DBP (NC was associated with both pre-HTN and HTN independent from other body composition indexes. NC is a simple and useful anthropometric index to identify elevated blood pressure in Chinese adults. Excess adiposity is an important risk factor for cardiometabolic diseases including hypertension, diabetes, dyslipidemia and coronary heart disease , 2. UppeAs one of the most important risk factors of cardiovascular disease, hypertension was the world’s leading risk for death , 10. ChiIn 2015, we conducted a cross-sectional study in Shaanxi province, northwest China. The criteria for participant recruitment were: 1) aged 20–80 years; 2) local residence for at least 1 year. The exclusion criteria were: 1) woman who is pregnant; 2) soldier in service; 3) disabled individual  and 4) individual who reported a history of obstructive sleep apnoea. The presented study was part of the China National Health Survey (CNHS). The CNHS used a multi-stage stratified cluster sampling method to select participants. The sampling procedure was described elsewhere , which bA national survey had implied a hypertension prevalence in Chinese adults of 23.2% . The estα) was the significance level; p was the prevalence of hypertension; d was the error tolerance which could be estimated as 0.10 × p. Zα equals to 1.96 when α = 0.05. To reach a significance level of 0.05 and error tolerance of 0.10p, the estimated minimum sample size was 1272. Finally, a total of 4279 adults aged 20–80 participated in the survey.Alpha , we conducted anthropometric measurements to collect data on height and weight for the calculation of body mass index (BMI). Waist circumference (WC), hip circumference and neck circumference (NC) was measured using a plastic tape to a precision within 1 mm. The measure of NC was from the midway of the neck, between mid-cervical spine and mid-anterior neck. To avoid measurement bias, there was only one staff assigned to measure NC, WC and hip circumference all through the survey.Three blood pressure (BP) readings were made by skilled staff using a digital BP measuring device . Before the blood pressure measurement, all participants were required to have at least five minutes rest, avoiding exercise, drinking alcohol or tea, or smoking for at least 30 mins. We collected overnight fasting venous blood samples for the measurements of serum lipid and glucose by Chemistry Analyzer  at the General Hospital of Chinese People’s Liberation Army (PLA). Serum lipid test items included total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C).The definitions of cigarette smoking status, alcohol consumption and physical activities were descripted in our previous publications , 15, 16.We performed the statistical analyses using SAS version 9.4 for windows .p-value < 0.05 (two-tailed) was considered statistically significant. Chi-square tests or Student’s t-test (or Wilcoxon sign test) were used to compare characteristics of participants in the analytic sample. The scatter plots fitted by penalized B-spline models were used to illustrate the relationship between NC and blood pressure (both SBP and DBP) in stratified BMI categories.Continuous variables were presented as mean with SD, and categorical data as number with percentage. A Two-way analysis of covariates was performed using general linear regression model (GLM) to identify the association between NC and blood pressure (SBP and DBP), and the adjusted means of blood pressure in NC quartile groups were calculated and compared. Logistic regression models were used to calculate the multi-variable adjusted prevalence of pre-HTN and HTN . Multi-cIn the sensitivity analyses, different definition of overweight and obesity   was usedp < 0.001).A total of 4279 participants were included with a mean age of 46.90 ± 13.80) years. The demographic, clinical and lifestyle characteristics of the subjects were summarized in Table 3.80 yearp < 0.001). In each BMI category, NC was also found positively associated with increased SBP and DBP . The scatter plots of NC and blood pressure fitted by penalized B-spline model revealed a positive association between NC and blood pressure .The associations between NC and blood pressure were presented in Fig. p < 0.001). Male had higher prevalence of HTN than female within each NC quartile (p < 0.001). We further calculated the adjusted prevalence of HTN across BMI and NC categories , compared with those in the same NC level but no-AO (30.5%) and other groups. Consistently, subjects who were no-AO and with the lowest level of NC had the lowest prevalence of HTN (9.46%) Fig. .p = 0.210) , family history of HTN and serum lipids (TC and LDL-C), NC was associated with HTN, with an OR of 1.22 (95%CI: 1.15–1.29), but no association was found between NC and pre-HTN . For the odds of HTN, all sub-groups across sex and BMI categories, except for obese male, were observed having positive association between NC and the odds of HTN  with same sex and age-group. The AUCs of NC were 0.633 in male and 0.663 in female. BMI (0.669) and WC (0.716) had the highest values of AUCs in male and female, respectively. Sex and age-specified AUCs were calculated within each index. In male, NC had the highest predictive value in the 40–49 age group (0.714), and in female, the highest value fell in the 50–59 age group (0.658).The areas under the ROC curves (AUCs) were constructed to evaluate the predictive value of NC and other body composition indexes for HTN Table . There wVery few investigators have explored the potential value of NC measurements as an indicator of pre-HTN and HTN in general population in China. In this study, we found that NC was associated with blood pressure and both pre-HTN and HTN independently from BMI and other body fat indexes, in adults aged 20–80 years in Northwest China. After stratification analyses and regression analyses, we also found that the association varied within sex, age groups and BMI categories. The sensitivity analyses yielded similar results, which indicated that the study conclusions were robust.Hypertension is a serious chronic health problem facing all age groups of population and has been aptly described as the top cause of death in China . The staPrevious studies have documented the value of NC as an indicator of HTN in Chinese population. In line with their findings , 23, incThe precise mechanisms underlying the associations between NC and blood pressure remain not fully understood. But in case of the upper half of body, the deposition of the adipose tissue in neck indicates the initial stage of obesity. Excess adiposity has been well studied as an important risk factors for cardiovascular risk factors, including hypertension –8. NC coWe calculated AUCs to evaluate the predictive values of NC and other body composition indexes for HTN. According to the ROC analyses, however, NC may not be a good predictor of HTN due to its low value of AUC, that was 0.633 for male and 0.663 for female. There are few studies have compared the effect size of NC with WC, BMI, WHR or other body fat indexes in China. Zhou’s study  observedCertain limitations existed in this study and should be considered in interpreting the data. Firstly, the cross-sectional nature to some extend limits the ability to explore causal association between NC and blood pressure. Secondly, although we have carefully adjusted the possible confounders in the analyses, information on dietary intake, lifestyle situation was not yet complete. Thirdly, data analyses in this study were based on the study population, therefore it may not be appropriate to apply its conclusion to other population. Nonetheless, our data, derived from a representative population selected using multi-stage stratified cluster sampling method, could provide valuable information for practitioners, especially those in primary care settings, when it comes to screening for HTN.Our findings suggest that NC is a simple and useful anthropometric index to identify elevated blood pressure in adults of China. NC was associated with both pre-HTN and HTN independent from other body fat indexes.Additional file 1: Table S1. Demographic and clinical characteristics of adults aged 20–80 years in Shaanxi Province, China, 2014. Table S2. The relationship between neck circumference and blood pressure, stratified by body composition categories, among Shaanxi adults aged 20–80 years in China, 2014 (n = 4279). Figure. S1. The scatter plots of neck circumference and blood pressure stratified by body weight in adults aged 20–80 years in Shaanxi Province, China, 2014. Fitted Penalized B-spline was used to yield the regression line and 95% confidence interval. (a): NC and SBP in normal/underweight group; (b): NC and SBP in overweight group; (c): NC and SBP in obese group; (d): NC and DBP in normal/underweight group; (e): NC and DBP in overweight group; (f): NC and DBP in obese group. NC: neck circumference. SBP: systolic blood pressure; DBP: diastolic blood pressure.


Accurate and timely data on the health of a population are key for evidence-based decision making at both the policy and programmatic level. In many low-income settings, such data are unavailable or outdated. Using an electronic medical records system, we determined the association between nutritional status and severe illness and mortality among young children presenting to a rural primary health care facility in the Gambia.Clinical data collected over five years (2010–2014) on children aged under 60 months making acute visits to a primary health care clinic in the rural Gambian district of Kiang West were retrospectively extracted from the medical records system. Generalised estimating equation models were used to investigate associations between nutritional status and illness severity, accounting for repeat visits, gender, age and access to transport to the clinic. The Population Attributable Fraction (PAF) was used to determine the proportion of severe illness likely attributable to different grades of malnutrition.p < 0.001, ‘WHZ <-2 and ≥-3’ aOR 2.78, 95% CI:2.31–3.36, p < 0.001 and ‘WHZ < -3’ aOR 7.82, 95% CI:6.40–9.55, p < 0.001) the PAF for wasting (WHZ < -2) was 0.21 (95% CI: 0.18–0.24). Stunting, even in the most severe form (HAZ < -3), was not significantly associated with severe illness (aOR 1.19 95% CI:0.94–1.51) but was associated with a significantly increased risk of death (aOR 6.04 95% CI:1.94–18.78).3839/5021 (77%) children under 60 months of age living in Kiang West presented acutely to the clinic at least once, yielding 21,278 visits  23.92 months)) and 26,001 diagnoses, 86% being infectious diseases. Severe illness was seen in 4.5% of visits . Wasting was associated with an increased risk of severe illness in a dose-dependent manner, (‘WHZ < -1’ adjusted Odds Ratio (aOR) 1.68, 95% CI:1.43–1.98, In this population-based cohort of young children in rural Gambia, wasting was associated with disease severity in a dose-dependent manner. Further research is needed into strategies to identify and reach these children with effective interventions to improve their nutritional status.The online version of this article (10.1186/s12889-019-6959-y) contains supplementary material, which is available to authorized users. Quality health information is a prerequisite for improving clinical practice, informing public health approaches and guiding health policy. Health information systems draw data from a range of sources including: epidemiological studies, birth and death registers and health facility records. John Fry’s work on common diseases provides a historical example of how primary care data can provide a window into the health of a population . MigratiThere are limited examples in the published literature where routinely collected primary care data from sub-Saharan African countries has been used for epidemiological purposes . The clinic serves the population of Kiang West, a rural Gambian district with 36 villages and a population of ~ 14,000. Annual in- and out-migration for Kiang West stands at 90 and 89 per 1000 population respectively [On presentation, vital signs and anthropometric measurements were taken by trained clinic personnel  history and examination using the severe illness criteria set by the integrated management of childhood illness  2) physiThe WHO 2006 child growth standards were used to calculate Height-for-Age (HAZ), Weight-for-Height (WHZ) and Weight-for-Age (WAZ) Z-scores . Data weOnly data from acute clinic visits were included for presenting complaints, diagnoses and illness severity. Welch’s unequal variances t-test was used to determine if nutritional status differed between those classified as severely ill and those not. All acute presentations were included in the analysis, regardless if they were repeat visits by the same individual.Generalised estimating equation models  with a log link, binomial distribution and utilising the unique child identification as a cluster variable (STATA IC 14) were used to examine the association between nutritional status , and severe illness (dichotomous variable) and death (dichotomous variable) adjusting for: age (continuous variable), gender (dichotomous variable) and access to transport to the clinic (dichotomous variable). The proportions of severe illness attributable to different grades of malnutrition were calculated as the Population Attributable Fraction (PAF) .The Joint Gambian Government/MRC Gambia Ethics Committee granted approval for the collection and use of anonymised demographic surveillance data in Kiang West in 1981. This approval was extended to the use of routine clinical data collected at the MRC Keneba clinic from 2009 and covered the period of data collection (2009–2014) used in this study.Between 1st January 2010 and 31st December 2014, the cumulative under 60 months old population of Kiang West was 5021. Of these, 3839 (77%) made at least one acute visit to the Keneba clinic, with a total of 21,278 visits . In addition, 7452 non-acute visits (follow-up and welfare clinic appointments) were made by 1495 children, of those only 39 children made non-acute visits to the clinic. The median age at presentation for acute clinic visits was 20.2 m (IQR = 25.9) with 47% of visits made by girls (Table p < 0.001) or infancy . The distance to the clinic for those who did not present prior to death (median = 21 km (IQR = 12) was significantly greater than for those who did present , irrespective of age at death.  representing an under 60 m mortality rate of 51 deaths per 1000 live births. Of these, 31% (50/160) presented to the clinic at any point prior to death, with a median time of 10 days (IQR = 151) between final presentation to the clinic and death. Table The median number of presenting complaints per visit was two (IQR = 2) with 1242/21,278 visits having no complaint recorded. The most common complaints were fever and cough, noted in 73%  and 52%  of visits respectively. Of the 26,001 diagnoses (median of 1 diagnosis per visit (IQR = 1), 22,456 (86%) were for infectious diseases. Antibiotics were prescribed in 67%  of all visits,  patients were classified as being severely ill. Disease categories differed significantly between those with and without severe illness  and on stunting (HAZ) for 20,545/21,278 visits (97%)  . The mean WHZ of these 30 children at their last clinic visit before death  was significantly lower than that of children during other acute clinic visits .Data on wasting (WHZ) were available for 20,478/21,278 visits (96%) (outside plausible range ss Table . Of the P < 0.001) at the last clinic presentation were however associated with a significantly increased risk of subsequent death . The association between different grades of wasting was observed for all specific infectious diseases, with the exception of severe bronchiolitis . The additional file contains six sections as follows. Section 1: Specific search terms used in the literature review. Section 2: Detailed list of variables extracted from the Kiang West Demographic Surveillance Systsem (DSS) and KEMReS databases Section 3: Explanation of severity criteria and cut offs from Rees et al. (2016). Section 4: Clinic outcomes, presenting complaints, diagnoses and prescriptions during 21,278 acute clinic visits by age groups. Section 5:Demographic characteristics of children with missing anthropometric data compared with children not missing data. Section 6: Anthropometric indicators disaggregated by age (< 1 year vs over 1 year). (DOCX 33 kb)