Grain weight (GW) is a key component of sunflower yield and quality, but may be limited by maternal tissues. Cell growth is influenced by expansin proteins that loosen the plant cell wall. This study aimed to identify spatio-temporal expression of EXPN genes in sunflower reproductive organ tissues  and evaluate correlations between reproductive organ growth and expansin genes expression. Evaluations involved eight different developmental stages, two genotypes, two source-sink treatments and two experiments. The genotypes evaluated are contrasting in GW (Alybro and confection variety RHA280) under two source-sink treatments (control and shaded) to study the interactions between grain growth and expansin genes expression.Ovaries and grains were sampled at pre- and post-anthesis, respectively. Final GW differed between genotypes and shading treatments. Shading treatment decreased final GW by 16.4 and 19.5% in RHA280 and Alybro, respectively. Relative expression of eight expansin genes were evaluated in grain tissues. EXPN4 was the most abundant expansin in the ovary tissue, while EXPN10 and EXPN7 act predominantly in ovary and pericarp tissues, and EXPN1 and EXPN15 in the embryo tissues.Specific expansin genes were expressed in ovary, pericarp and embryo in a tissue-specific manner. Differential expression among grain tissues was consistent between genotypes, source-sink treatments and experiments. The correlation analysis suggests that EXPN genes could be specifically involved in grain tissue extension, and their expression could be linked to grain size in sunflower.The online version of this article (10.1186/s12870-018-1535-7) contains supplementary material, which is available to authorized users. In the last 50 years, oil crops such as soybean, sunflower, and oilseed rape have become increasingly important in international food trade, due to increased human consumption and demand of oil for biofuel production. Sunflower has had the third highest relative growth among crop commodities; it contributes to calorific intake  and provThe sunflower grain is an achene comprised of two main components: the pericarp (coat or hull), resulting from the fusion of the ovary tissues and part of the receptacle , and the embryo, formed by two cotyledons and a small stem and radicle, derived from the egg fertilization. The mature sunflower grain lacks endosperm (it is consumed during embryo growth), thus grain reserves  accumulate within embryo cells, mainly in the cotyledons .The relationship between the pre- and post-anthesis periods has been attributed to the flower ovary, which becomes the pericarp after pollination in sunflower and other crops , 14, 16.Lindstrom et al., (2006)  and CastIn multigene families such as EXPN, different members may play unique developmental or tissue-specific roles, though there is currently little information about the role of EXPN in specific grain tissues. Lizana et al. (2010)  conducteClimate conditions were similar between experiments. Mean temperature during the Emergence-R1 period was only 1.1 °C higher in experiment 1, while the R1 to PM average temperature was higher in experiment 2, primarily during R2-R5, when the mean temperature was 3 °C higher in experiment 2 than in experiment 1 (see Table A1 in ). Crop dp < 0.05) GW than Alybro in both the control treatment  and under shading  of experiment 2 (Table p < 0.001), decreasing it by 45 and 33% in Alybro and RHA280, respectively (Table p < 0.001); grain length was reduced by 13 and 5.4% in Alybro and RHA280, respectively, while grain width decreased by 19% in Alybro and 14% in RHA280, and grain height decreased by 16 and 20% in Alybro and RHA280, respectively  in both pericarp weight and water content . On the other hand, the peak expression of EXPN1.2 in the embryo was at + 6 DFA in control treatments of both genotypes Fig. b. The shTo explore if physiological grain traits correlate with EXPN expression patterns, we performed a correlation analysis using all data from two experiments. We used the Gini correlation coefficient to estimate the relationship between phenotypic traits and gene expression levels. The Gini correlation coefficient can compute the correlation of two variables considering both rank and value information. For this reason, this methodology is more robust on non-normally distributed data and is more stable for data containing outliers than the widely used Pearson correlation coefficient.Qualitatively, EXPN7 follows a similar – but inverse – time course than the grain growth pattern  identify EXPN genes expressed in sunflower reproductive organs  assess tissue-specific EXPN expression in those organs; and iii) evaluate correlations between reproductive organs and EXPN expression. We identified eight putative EXPN acting in reproductive tissues  during the pre- and post-anthesis periods. Evaluations involved eight different developmental stages, two genotypes, and two source-sink treatments in two experiments. We found that all the EXPN selected using in silico analysis and the transcriptomic data, share a similar protein-conserved domain and a relatively simple intron/exon structure belonging to the α-EXPNs subfamily Fig. .Expression pattern analysis using qRT-PCR supports the hypothesis that EXPN genes act in a tissue-specific and temporal manner in sunflower grains. Taking into account that other sunflower organs and tissues were not evaluated in this study, we only highlight its expression in reproductive tissues from the pre-flowering to post-flowering stages, considering that they may be acting in other organs. Similarities in expression patterns could indicate functional redundancy between EXPN of sunflower reproductive tissues, as was previously reported in grasses and other plant groups , 44. OrgA central question of the present study was if differences in GW between genotypes and shading treatments were explained by the abundance or duration of EXPNs expression. The difference between Alybro and RHA280 genotypes (with different GW) was ascribed to relative abundance. In agreement with this response, most of the EXPN genes of both genotypes showed lower abundance under the lower source treatment  and suggests that EXPN genes could be specifically involved in grain tissue extension, and their expression could be linked to grain size in sunflower Fig. . EXPN4 wOn the other hand, the grain growth process integrates and coordinates different pathways like genetics, epigenetics, metabolic, physiological, and environmental factors –57. SeveThe molecular and physiological bases of GW and grain size determination can be studied in an integrated manner by using a quantitative molecular approach combined with physiological and agronomical studies. Using qualitative and quantitative analysis of grain growth and expression dynamics, combined with heatmap and correlation analysis, we identified eight putative EXPN genes that could be involved in grain tissue extension. EXPN4 was the most abundant EXPN in the ovary tissues, while EXPN10 and EXPN7 act predominantly in ovary and pericarp tissues, and EXPN1 and EXPN15 in the embryo tissues. These results suggest that EXPN genes may control grain growth in sunflower from the early phases of development. Interestingly, EXPN7 and EXPN10 gene expression in the pericarp leveled off soon after flowering (+ 8 DFA), which is close to the maximum pericarp water content reached at + 10 DFA, indicating that EXPN and maternal tissue water dynamics may be linked in sunflower. These results contribute to improve the understanding of GW and grain size determination in sunflower and other grain crops.Two field experiments were carried out at the Experimental Station of the Universidad Austral de Chile in Valdivia  during the 2013/14 (experiment 1) and 2014/15 (experiment 2) growing seasons. Experiments were designed to evaluate relationships between EXPN expression patterns and sunflower reproductive organ dynamics , both at pre- and post-flowering.In experiment 1, plant reproductive organs and EXPN expression were measured in the sunflower oilseed hybrid Alybro, which corresponds to a hybrid with a short cycle and adapted to the environmental conditions of southern Chile. It was sown on November 2 in 2013 in a randomized complete design with three replicates. Experiment 2, aimed to validate the results of the first experiment by including an additional sunflower genotype contrasting in GW , and two source-sink treatments (control and reduced source-sink ratio prior to anthesis), with the aim of decrease GW, and add a new scenario to study determinants of GW. This experiment was sown on 1 November 2014 in a split plot design, where main plots were assigned to source-sink treatments and sub-plots to the genotypes, with three replicates. Source-sink treatments were established by shading the plots from stages R2 to R5, for 16–17 days , according to the scale proposed by Schneiter and Miller (1981) . FlowersGrain volume was measured by water displacement of 10 grains per experimental unit at maturity. This procedure mirrors that used in other studies for wheat , sorghumIdentification of putative EXPN genes expressed in sunflower grain tissues.Zinnia elegans (a relative of sunflower) were used as a query sequence (e.g. ZeEXP3: GenBank: AF230333.1) to search public databases of sunflower genome and transcriptomic data (https://www.heliagene.org) using the BLAST tool. Putative EXPN genes were identified based on gene annotation, bioinformatics, and RNA sequencing analyses. In the sunflower genome portal, protein-coding genes were annotated using a three-step process considering reciprocal best hits in the SwissProt and TAIR10 databases , protein-domain content in Interpro , and similarity with plant proteomes (Ensembl release 30) or coverage of the transcript with RNA-sequencing data [The first objective was to identify in silico EXPN genes expressed in sunflower reproductive organs. Well-characterized EXPN from ing data .From the BLASTp results, we chose eight putative EXPN according to the expression patterns tool in the sunflower transcriptome database  to mark off the coding region for designing specific primers.The eight sunflower EXPN (and the EXPN7 ortholog) were subjected to multiple sequence alignments using the MegAlign program with the CLUSTAL W algorithm . The aliSpecific primers were designed using the “PRIMIQUE” tool to detect different sequences of the gene family . Two priTotal RNA was isolated using the RNeasy Plant Mini kit (Qiagen), according to the manufacturer’s instructions. The kit provides a choice of lysis buffers depending on the amount and type of secondary metabolites in the tissue, thus standardizing the RNA extraction protocol. RNA quality and concentration was measured using spectroscopy with NanoQuant .The isolated RNA was pretreated with DNaseI. First-strand cDNA was synthesized from 250 ng RNA using the ImProm-II™ Reverse Transcription System. The oligo(dt)16–18 primer/template mix was thermally denatured at 70 °C for 5 min and chilled on ice. A reverse transcription reaction mix was assembled on ice and contained nuclease-free water, reaction buffer, reverse transcriptase, magnesium chloride, dNTPs, and ribonuclease inhibitor. We added 1 U/μl of Recombinant RNasin® Ribonuclease Inhibitor before the template-primer combination was added to the reaction mix on ice. Following an initial annealing at 25 °C for 5 min, the reaction was incubated at 42 °C for up to 1 h. The synthesized cDNA (20 μl) was stored at − 20 °C. As a negative control, an RNA sample was replaced by water in this procedure.The qPCR reaction was performed in a final volume of 25 μL, containing 12.5 μL Brilliant II SYBR Green PCR Master Mix , 1 μL 10 μM forward and reverse primers and 8.5 μL of sterile deionized water. After an initial DNA polymerase activation step at 95 °C for 10 min, samples were subjected to 35 amplification cycles . No-template and no-transcriptase controls were included to detect genomic DNA contamination.A melting curve was generated by incubating the reaction at 95 °C for 15 s, 25 °C for 1 s, and 70 °C for 15 s, and then slowly increasing the temperature to 95 °C. The mRNA abundance of EXPN genes between grain tissues and development stage was determined using the method proposed by Pfaffl (2001) , where βhttps://www.heliagene.org/) and National Center for Biotechnology Information database (https://blast.ncbi.nlm.nih.gov/Blast.cgi). To classify sunflower EXPN proteins into subfamilies, we searched orthologs of EXPN7 in Arabidopsis, soybean, rice, wheat, Bachypodium, and maize, and incorporated two non-related EXPNs such as a β-EXPN EXPB1 from maize and EXLX1 from Bacillus subtilis . They were aligned with predicted protein sequences without signal peptides , considering only the conserved domains of EXPN. Multiple alignments were analyzed using MegAlign (CLUSTALW) and a phylogenetic tree of EXPN proteins was constructed using Lasergene software. The sunflower genome portal details the Gene Ontology enrichment tests with Blast2GO Pro  [EXPN sequences were further verified by sequencing and the resulting chromatograms were viewed, evaluated, and aligned. Gene sequences were subjected to a homology search in the Heliagene portal ( < 0.05) . This inhttps://biit.cs.ut.ee/clustvis/). Heatmap can be used to visualize the data matrix of EXPN expression; the values in the matrix are color-coded, and we clustered the rows (EXPN expression patterns) by calculating all pairwise distances. Hierarchical clustering was performed using Pearson’s correlation distance [A heatmap was created to facilitate the graphical interpretation of the relationships between 13 different grain samples  in different developmental stages using the Clustvis online tool with default settings , according to the experimental design described above. Regression analyses were used to evaluate the degree of association between variables using Statgraphics Centurion XVI software.Data of variables and parameters of the ovary and grain growth dynamics were assessed using ANOVA , using the “rsgcc” package with the Gini correlation metric . The p-vAdditional file 1:Figure S1. Identity and divergence percentage between EXPN evaluated based on multiple sequence alignment. Sequence aligngments of available full length amino acid sequence with EXPN signal peptide removed. SignalP 3.0 Server software was used to predict the signal peptide cleavage sites. (PDF 39 kb)Additional file 2:Figure S2. Grain dynamics and relative expression patterns of six EXPN during ovary and grain growth in two sunflower genotypes under two source-sink treatments. (PDF 266 kb)Additional file 3:Figure S3. Expression of putative EXPN in various sunflower tissues, according to the transcriptome database (heliagene). A. Scheme of EXPN15 expression. B. Scheme of EXPN4 expression. (RPKM: reads per kilobase per million mapped reads) were chosen. (PDF 187 kb)Additional file 4:Table S1. Characteristics of putative sunflower EXPN. Accession name, chromosome localization, nucleotide and peptide sequence length, Blast2GO, orthologs, and % identity. Data is from the sunflower genome database . (PDF 106 kb)Additional file 5:Figure S4. Multiple sequence alignment of predicted protein sequences corresponding to plant orthologs of EXPN7 and eight putative sunflower EXPN. Identical amino acids are shown with black backgrounds, and different amino acids are shown without backgrounds. The potential putative catalytic domain  is indicated by a horizontal blue bar and the putative cellulose binding domain  is indicated by a horizontal red bar; both were predicted using ScanProsite. Multiple alignment was done using MegAlign software. (PDF 285 kb)


Evidence showed preventive impacts of the highly active antiretroviral therapy (HAART) on the Human Immunodeficiency Virus (HIV) transmission amomg heterosexual population, however, that is of deficit among men who have sex with men (MSM). The aim was to systematically examine the efficacy of HAART on HIV transmission and the association between the HAART initiation and unprotected anal intercourse (UAI) in MSM population. Three electronic databases were fully searched for articles published in peer-reviewed journals between 1996 and 2017. Of 1616 identified articles, fifteen articles were eligible for meta-analyses. The summary incidence rate (IR) of HIV was 6.63/100 person-year (95%CI 2.06–11.20/100 person-year)(p = 0.004). The pooled per-contact rate (PCR) of HIV was 0.42% (95% CI 0.21–0.63%)(p < 0.05). The HAART initiation (vs non-HAART) was not associated with engaging in UAI, with odds ratio (OR) 1.09 (95% CI 0.90–1.34)(p > 0.05). In the stratified analysis, participants with no less than 6 months recall period was slightly more likely to engage in UAI (p < 0.05). It indicated that HAART has potential efficacy on reducing infectivity of HIV positive individuals in anal intercourses. The relationship between the HAART initiation and UAI was not significant and may be influenced by some social-demographic factors. Consistent condom use and education on safe sex among MSM are crucial. Among men who have sex with men (MSM), the average percentage of HIV prevalence ranged between 6% (the Asia and Pacific region) and 15% 2. In young (under 25) MSM, around 4.2% of the population was infected with HIV2. Although there is a trend of reduction of HIV incidence in the general population in most countries, it showed an upward trend among MSM3. Two Australian studies predicted that, for homosexual males, the mean number of homosexual partners was 11 in the past 1 year4, compared with heterosexual men, which was about 1.55. Theoretically, with high possibility of partner change rate, the MSM is regarded as the core group in the transmission of sexual transmitted diseases (STIs) including HIV6. Also, the MSM-population is supposed to be the risk group in the pattern of HIV transmission. A UNAIDS report estimated that the risk of HIV acquisition in MSM was 19 times higher than that in the heterosexual population2. Compared with different patterns of sexual intercourses, the risk of HIV transmission was the highest via the UAI7.Globally, over 78 million people were infected with HIV. The prevalence of people living with HIV was 36.7 million8. A landmark randomized clinic trail (RCT) HPTN 052 demonstrated that the HAART reduced individuals’ risk of HIV-1 transmission via sex with condoms by 96% between heterosexual sero-discordant partners9. Similar results were found in an observational cohort study in Africa10. However, both studies only detected the effect of HAART on the vaginal transmission, whether the HAART reducing the risk of HIV acquisition via penis-anal intercourses is unknown. Some researchers believed that the rectal tissue is more susceptible to HIV RNA virus than vaginal tissue, which would increase individuals’ risk of HIV acquisition11.The multiple combination of antiretroviral drugs (ARVs), highly active antiretroviral therapy (HAART), was proved to successfully suppress the HIV virus in blood12. However, the preventive effect of HAART on MSM population is uncertain and may be influenced by many factors. For instance, some researchers pointed that the unstable and weak relationship between MSM may avert the preventive effect of the HAART7. In addition, the viral load remained at high level in rectal tissues, even though it has been suppressed at an undetectable level in plasma14. Hence, behavioural factors like condomless anal intercourses may induce negative impact on the TasP15. In contrast, a prospective cohort study illustrated none HIV negative participants were linked-infected by their HIV positive partners via unsafe sex16.In 2012, WHO published a guideline regarding HAART as a secondary preventive strategy called the treatment as prevention (TasP) based on previous empirical evidencesHIV is represented the HIV-1 type infection.It is imperative to fill the gap with specific evidences of the efficacy of TasP on HIV transmission in MSM. Detecting the association between UAI and HAART and potential influential factors for UAI would help researchers and policy-makers tailored their public health projects for this sub-group population. In this meta-analysis, the term The aim of this systematic review and meta-analysis was twofold: 1) to examine the efficacy of HAART on the risk of HIV transmission among MSM, 2) to examine the likelihood of engaging in sexual risk behaviours which measured as UAI among MSM while HAART initiation.19 from the same prospective national cohort were also included due to different study periods and samples . The majority of the participants (91.83%) were HIV positive status. The median age of MSM (n = 12) ranged from 28 to 45, with mean age 35.7 ± 4.44 y. Ten studies reported ethnicities of participants, mainly consisting of white , the others were Asians, African Americans and Latino/Hispanic. Nearly half of the participants held the degree of college or above . However, few studies reported the income level (n = 4), alcohol intake (n = 4) and substance use (n = 5) and the number of sexual partners ((n = 4)  adopted the 6-month recall period. Three articles2 = 99.88), thus the random-effects model was used. Egger’s regression intercept test showed no publication bias (p > 0.05). Sensitivity analysis showed no single effect size influenced the overall result.Four effect sizes contributing from three independent studies tested the IR of HIV in the era of HAART. The overall estimate of IR was 6.63/100 person-year (95% CI 2.06–11.20/100 person-year), p = 0.004 . The random-effects model was used. Egger’s regression intercept test showed no publication bias (p > 0.05). Sensitivity analysis showed the summary PCR did not influenced by removing each independent effect size.Two studies contributing six independent effect sizes examined the PCR of HIV transmission in the era of HAART. The pooled estimate of PCR was 0.42% (95% CI 0.21–0.63%), p < 0.001 . Four studies presented the average duration of HIV infection, varying from 5.5 (IQR 0.2–16.4) to 12 (IQR 7–6) years23 (Table 2 = 85.82), thus, the random-effects model was used. The overall effect size was not influenced by removing single effect sizes when running the sensitivity analysis. There was no evidence of publication bias investigated by the Egger’s regression intercept (p > 0.05).Ten studies contributing thirteen independent effect size tested the association between HAART (vs not HAART) and risk sexual behaviours. The percentage of HIV positive participants on HAART ranged from 23% to 100%. Only 2 studiesi.e. study setting, Data collection method) remained none association between two variables (HAART and UAI).By previous literature review, we stratified data into sub-analyses Table . On HAARFew international studies examined the IR among MSM before HAART therapy adopted. Therefore, comparable groups’ data (non-HAART) in most researches were absent.24. The overall weighted IR was highly influenced by the number contributed from Brazil25. This extreme data indicated that the risk of HIV transmission among MSM may be different within distinct regions. However, the assumption, whether the diversity of IR came from different samples or it was only an extreme case, needs further proof.In general, the pooled IR ) in our meta-analysis was within the range of the incidence rate of HIV (1.2 to 14.4/100 person-year) in MSM population reported by WHO16. It moderated the infectivity of HIV positive individuals17. However, at the population level, studies calculated the HIV IR in the era of pre-HAART and post-HAART seperately showed an increasing trend during 1991 and 2001 in Netherland26. This contradicted phenomenon revealed that there might be some environmental factors around MSM influence the preventive impact of HAART, even averted the preventive efficacy at this population.A prospective cohort study among four effect sizes demonstrated that the HAART had a preventive effect on HIV transmission via condomless anal intercourse at the individual-level7. Porco and colleagues (2004) calculated 60% decrease of the PCR of per-partnership in the post-HAART era compared with that in the pre-HAART era27. An across-country prospective cohort study (Opposites Attract study) investigated that the HAART had a positive impact on diminishing the infectivity of HIV viral hosts by suppressing the viral load in the plasma under 200 copies/ml , which is similar with that found by Rodger. AJ et al.16. Those optimistic findings were only shown between steady sexual relationships. However, evidences displayed that homosexual males were more prone to be involved in polygamous and vulnerable relationships4, which may contribute part of reasons for the uncertain efficacy of HAART on MSM. In addition, this research showed that the overall β of UAI is not zero even the HAART initiated. Thus, keep encouraging condom use among MSM is indispensable to prevent the HIV transmission. Researches have been proved that the preventive impact of condom use on HIV/STI transmission was effective if a person practices sexual activities with condoms all the time28. Consistently expanding HAART on MSM could be one approach to control the epidemic of HIV, which potentially decreases the average infectivity of the total population. Monitoring and guaranteeing the adherence of HAART intake should be a supplementary approach to maximise the impact of HAART.The PCR refers to the probability of one person be infected by their sexual partners while exposed at a certain sexual pattern, measured as infectivity (β) of HIV29. However, Napper pointed out that this finding needs further proof on anal intercourses29.The pooled effect size of the third meta-analysis showed the HAART would not influence the people’s choice on condom use during sexual activities. However, in the stratified analysis, participants had sexual experience no less than previous 6 months were more likely to engage in UAI (p = 0.047) compared with that within past 3 months, which implies that the frequency of sexual intercourses may influence the association between UAI and HAART. On the other hand, there may be a recall bias, since participants with longer recall period had higher chance to be vague on the memory of past sexual experiences. The reduction of self-reported reliability of sexual behaviours was also reported in the study of Napper (2009), which mentioned this reduction could be detected if the recall period beyond 6 monthsi.e. “popper”) use before or during sex were more likely to engage in UAI31. The high income was found to be the risk factor for engaging UAI21. However, the lower income group held optimistic beliefs on the preventive impact of HAART20. Some researchers believed that people held positive beliefs on the HAART was more likely to engaging in UAI20. This psychological construction also found in the research of Huebner. DM and Gerend. MA. (2001), pointing out that the HIV infected MSM who believed HAART has the preventive capability were more prone to take UAI, especially with casual sexual partners32. Therefore, consistent providing knowledge about safe sex, such as the limitation of TasP strategies and the importance of condom use in anal sex, is essential in the post-HAART era. However, the “condom fatigue”, referring to people get tired of health education on condom use and lag to change sexual risk behaviours, was mentioned in both Cox. J. (2004) and Brennan. DJ. (2010) researches, which may decrease the efficacy of safe sex education in the long-term run21.Confounders in the third meta-analysis were probably multiple and probably involve both socio-demographic and individual sides. The age, income and educational level, alcohol and drug abuse have been found to be significantly associated with engaging in UAI, indicating that people are at both young and old age, with lower education, successive alcohol drinking and substance  or defined as adults according to National Laws.Participants were homosexual males, self-identified as gay or engaging in male-to-male sexual behaviours regardless of original sexual orientation.HAART were exposed on HIV positive rather than negative participants.i.e. receptive or insertive).Studies performed to examine 1) the risk of HIV transmission, and/or 2) any types of UAI . The literature research was conducted mainly in the form of two search strings: (1) ‘HIV’, ‘antiretroviral’, ‘transmission’, ; (2) ‘HIV’, ‘antiretroviral’, , ‘behaviours’. Keywords ‘test and treat’, ‘treatment as prevention’ ‘anal sex’ were performed as supplementary search strategies with the other terms. Keywords ‘pre-exposure’, ‘hepatitis’, ‘HPV’, ‘herpes’, ‘drug resistance’ and ‘prevalence’ were excluded from title and abstract while searching at the database of Google Scholar. The search period was adopted from January 1996 to the present (February 2017).Electronic database PubMed, ScienceDirect and Google Scholar were fully searched. Terms‘HIV’, ‘antiretroviral’, ‘transmission’, ‘men who have sex with men’, ‘homosexual’, ‘behaviours’, ‘treatment as prevention’, ‘test and treat’, ‘anal sex’ were crossly combined and searched as either keywords in titles and abstracts or Medical Subject Heading (MeSH) terms ,heterosexual or women participants only.irrelative exposures (HAART) or study groups: PrEP or PEP, alternative interventions , the subgroup of homosexual males or male couples would be included in this meta-analysis.If participants were made up of mixed subgroups  was hardly fitted into the third meta-analysis35. Thus, there were fifteen full text articles enrolled in the final data analysis. This systematic review was carried out according to guidelines by PRISMA checklist36. The PRISMA flaw chat for the data selection procedure has been followed and presented in Fig. 57 articles were excluded via full text screening with following reasons listed in the Fig. Study design characters: authors and years, location, study design, study setting, data collection methods, study period, sample size for analysis, recall period (within past months), response rate, length of follow-up (person-year);Participants’ characters: ethnicity, age, sero-status of participants, education, income, heavy alcohol users, substance use, number of sexual partners during recall period, since when diagnosed, type of data analysis;Findings: measurement of effect size and findings.Each study was numbered by the first author and published year. A unified form was designed for the data extraction and imported into a Microsoft Excel database, including following categories:37.If both adjusted and unadjusted effect sizes were reported by independent studies, the unadjusted one would be included for the meta-analysis. Additionally, if the effect size was stratified by regions or types of sexual patterns, the sub-level number would be added into the meta-analysis. The extracted items listed in standard forms Tables , 3 and 5Three independent meta-analysis were performed. The pooled risk of HIV transmission was measured separately by the IR (the number of new infections divided by at risk population over specific time) and the PCR  with 95% CI. The pooled OR with 95% CI was used to estimate the association between HAART and UAI, representing the probability of engaging UAI between the on-HAART group (index group) and the non-HAART group (reference group). The baseline data in cohort studies were included in meta-analysis. If OR is over 1, it represented that the index group is more likely to engage in UAI than the reference group. Otherwise, the index group is less likely to engage in UAI (OR < 1). If OR = 1, it means there is no association between both variables.2 test were used to examine the heterogeneity across independent studies. The fixed-effects model would be used if the data showed low or moderate heterogeneity , otherwise, the random-effects model  would be carried out38. Publication bias was tested by the Egger’s regression intercept, if p > 0.05, it means no evidence on publication bias, otherwise, there would be a publication bias existing39. Statistical significance was 0.05 (P < 0.05) with 95% CI. Data were pooled and analysed by the software Comprehensive Meta-Analysis .A Cochran’s Q test based on Chi-square test and an I


An elevation of serum inflammatory biomarkers in achalasia patients compared with controls recently was demonstrated. It has not been determined whether the elevation of inflammatory cytokines is unique to achalasia or occurs with other diseases involving the esophagus. The primary aim of our study was to compare the differences in plasma immunological profiles  of patients with achalasia, eosinophilic esophagitis (EoE), and gastroesophageal reflux disease (GERD). A secondary aim of this study was to classify these same plasma cytokine profiles in the three achalasia subtypes.Plasma from 53 patients with achalasia, 22 with EoE, and 20 with GERD (symptoms plus esophagitis or + reflux study) were analyzed. Exclusion criteria: malignancy, autoimmune condition, immunodeficiency disorder, and treatment with steroids/immune modulating drugs. Cytokine levels were assayed via multiplex enzyme-linked immunosorbent assay (ELISA).p = 0.0158) in achalasia patients compared with EoE patients. Overall, plasma inflammatory biomarker patterns were not different in the three subtypes of achalasia.Our key finding revealed significant elevations in IL- 6 (There were no differences between the cytokine levels of any of the measured biomarkers between the achalasia and GERD groups suggesting that luminal stasis does increase biomarker levels for any of the cytokines examined in our study. While these results are an early first step towards clarifying some aspects of the pathogenesis of achalasia, they bring about many more questions that require further investigation and expansion. Further investigation with a larger cohort and a broader panel of biomarkers is needed. Achalasia is the quintessential example of esophageal dysmotility. Achalasia was first described by Sir Thomas Willis in 1674. He chronicled a patient with achalasia treated over a 15 year time period with sequential dilations performed using sponge button mounted on whalebone. Although physicians have recognized achalasia for over 350 years, many aspects of the disease pathogenesis remain unknown .Achalasia is characterized by loss of ganglion cells in the esophagus and in the LES. The pathogenesis of achalasia possibly involves both an autoimmune and inflammatory responses, this could be triggered by viral infection in prone individuals .Type1 T helper cells (Th1) produce interferon-gamma (IFN-γ) and tumor necrosis factor- alpha (TNF-α) which activate macrophages promoting cell-mediated immunity. Type 2 helper cells (Th2) produce antibodies for protection from parasites. T helper 17 (Th17) responses control of infection. Uncontrolled Th1 and Th17 responses are involved in the pathogenesis of organ specific autoimmune disorders, in contrast with Th2 responses which are responsible for atopic disorders .A review of the literature suggests that TNF-α, IL-6, IFN-γ, IL-12, IL-17, IL-22, and IL-23 theoretically could contribute to the underlying etiology of achalasia. IL-17 is a key mediator in several autoimmune diseases by recruiting neutrophils and activating innate immune cells, promoting B-cell functions, and facilitating the production of pro-inflammatory cytokines. IL-17 and IL-22 concentrations in myenteric plexus esophageal tissue of achalasia patients are higher versus control . IL-23 cp = .031) and TNF-α (p = .026) were significantly elevated in the achalasia group compared to the controls. Also, there was a trend toward significance in interleukin- 6 (IL-6) levels in the achalasia group, but this difference did not reach statistical significance (p = .053) . It = .053) . In cont = .053) .The primary aim of our study was to compare the plasma immunological profiles of plasma of TNF-α, IL-6, IFN-γ, IL-12, IL-17, IL-22, and IL-23 in patients with achalasia, EoE, and GERD. A secondary aim of this study was to classify these same plasma cytokine profiles in the three achalasia subtypes.This study was an exploratory multi-institutional collaboration between the divisions of Gastroenterology and Allergy and Immunology at the University of South Florida (USF), Morsani College of Medicine and the Medical University of South Carolina (MUSC) Department of Medicine, Division of Endocrinology. All patients evaluated at the Joy McCann Culverhouse Center for Swallowing Disorders USF between January 2013 and October 2015 with one of the three diagnoses were asked to participate in the absence of exclusion criteria. Plasma samples were collected only at USF and sent to MUSC for analysis.Plasma from patients with the diagnosis of achalasia based on high resolution impedance manometry (HRIM), EoE  and patients with GERD (defined by symptoms and either erosive esophagitis or positive reflux testing) were analyzed at the MUSC Department of Medicine, Division of Endocrinology. Biomarker levels were assayed via multiplex enzyme-linked immunosorbent assay (ELISA) . Exclusion criteria included previously diagnosed malignancy, autoimmune condition, immunodeficiency disorder, Chagas disease, Hepatitis C, and current treatment with oral, intravenous, or inhaled corticosteroids or immune modulating drugs.HRIM tracings were reviewed by two investigators (SC and JR), and patients meeting diagnostic criteria for achalasia based on the Chicago Classification version 3.0 were identified and subtyped. Patients with technically inadequate HRIM studies were excluded.HRIM studies were performed as per standard clinical protocol. A solid-state HRIM catheter consisting of 36 circumferential sensors spaced 1 cm apart  was placed transnasally with the patient in a seated position. After a landmark calibration phase, ten 5 ml water swallows spaced 20 to 30 s apart were completed. All tracings were reviewed using Manoview Analysis Software v3.0 . The manometric patterns were classified as type I achalasia if there was an elevated median integrated relaxation pressure (IRP) (> 15 mmHg) and 100% failed peristalsis. Type II achalasia was defined by an elevated median IRP (> 15 mmHg), failed peristalsis, and panesophageal pressurization in ≥20% of swallows. Type III achalasia was characterized by an elevated median IRP (> 15 mmHg), no normal peristalsis, and ≥ 20% premature contractions, defined as DL < 4.5 in accordance with Chicago classification guidelines version 3 .v/v (~ 100uL) Protease inhibitor cocktail (Sigma). Each sample was inverted 5 times. Collected specimens were kept upright at room temperature for 10 min then placed in an ice bucket to cool at 4 °C. All sera was sent for immediate processing with all samples included in the study being processed in under 1 h after collection. The samples were centrifuged for 9 min at 3000RPM at a temperature of 4°, and the plasma was separated into 100 μl aliquots placed in 0.5 ml cryrovials. The tubes were immediately stored in a secured freezer at − 70° Celsius. No hemolyzed specimens were included in the data of this study. All plasma samples were collected at the University of South Florida. Samples were analyzed for the following biomarkers:Cytokines: IL-6, IL-12 p70 subunit), IL-17, IL-22, IL-23, INF-γ and TNF-α.Following a detailed explanation of the study a written informed consent was obtained from all participants. We obtained a blood sample to measure the biomarkers. Two tubes of blood per subject were obtained by the research coordinator using conventional venipuncture. Blood collected for serum was placed serum separator tubes (SST) red and grey tiger top tubes ±1% Frozen samples were shipped overnight on dry ice to the MUSC Department of Medicine, Division of Endocrinology for analysis.Once the specimens were ready for analysis, the aliquots were thawed on ice. The specimens were analyzed using Quantikine Human Immunoassays . Each kit varies in sample amount and/or dilution, assay incubation times, and volume of conjugate and substrate. Therefore, the assay procedures were performed according to manufacturers’ guidelines for all of the analyzed cytokines and receptors. All plates were read and calculated  on a Molecular Devices VERSAmax Microplate Reader. All immunoenzymatic assays were performed in duplicate.The diagnosis of GERD was based on endoscopic evidence of erosive esophagitis based on the Los Angeles classification of erosive esophagitis and/or an abnormal combined multichannel intraluminal impedance and pH test off of all acid suppressive medications for seven days . We inclCombined multichannel intraluminal impedance (MII) and pH testing was performed using an ambulatory combined impedance-pH catheter . Following a fasting period ≥5 h, patients underwent esophageal manometry for the localization of the lower esophageal sphincter (LES) and assessment of esophageal function. The combined impedance-pH catheter was subsequently placed in the esophageal body with a reference pH electrode distal to the LES and two pH monitoring electrodes 5 cm and 20 cm proximal to the LES. The device also contained 8 impedance rings located at 2, 4, 6, 8, 10, 14, 16, and 18 cm proximal to the LES. The study catheter was attached to an external ambulatory monitor and worn for 24 h during which the study subjects were encouraged to maintain their normal activities, sleep schedules, and eating habits. In addition to impedance and pH data, the 24-h Imp-pH monitor provided information regarding changes in body position and the timing of meals and GERD symptoms, as noted by the patient. Tests not lasting longer than 21 h were excluded from data analysis.After the study period, data from each monitor was transferred to a computer and visually analyzed using a commercially available software program . Meals were marked and excluded from reflux analysis. Esophageal acid exposure time (EAET) was quantified as the percentage of time that the pH detected by the distal pH probe was below 4.0, or EAET.The original pH definitions set by Johnson and Demeester (1974) were used as the standards for the detection of pathological levels of reflux events. Thus, > 4.2% total EAET, > 6.3% EAET in the upright position, and > 1.2% EAET in the recumbent position were the chosen standards .The diagnosis of EoE was made in patients with symptoms related to esophageal dysfunction  and esophageal biopsies from both the proximal and distal esophagus revealing > 15 eosinophils/high powered field (hpf), without an alternative cause of eosinophilia. The persistence of esophageal mucosal eosinophilia on repeat esophageal biopsy after an adequate trial (8 weeks) of twice daily PPI therapy was required to be included in the study.p-value of less than 0.05 was considered to be significant. All the analyses were performed using SAS Enterprise Guide 7.1, .The plasma immunological profile of IL-6, IL-12p70, IL-17, IL-22, IL-23, TNFα and INF-γ values obtained from patients with achalasia, EoE, and GERD was analyzed. The distribution of the data was assessed using the Kolmogorov-Smirnov test, and this analysis revealed that none of the biomarkers were normally distributed. Therefore, nonparametric statistical methods were used for further analysis. Median and interquartile range were used to describe each biomarker. The Kruskal–Wallis rank sum test was used to compare the composite scores among three groups. The , 26 female), 22  with EoE, and 20  with GERD. In the GERD cohort, 16 patients had abnormal pH impedance testing and 4 patients had erosive esophagitis on endoscopy.The study included 53 patients with achalasia (mean age 61 years old (yo), 27 maleTable P value calculated for these biomarkers in the three subtypes of achalasia did not show any statistical significance (P < 0.05) between groups. The study did not demonstrate the difference in plasma biomarker levels between the three subtypes of achalasia.Of the 53 achalasia patient plasma specimens that were analyzed, 1325%) were type I achalasia, 32(60%) were type II achalasia, and 8 (15%) were type III achalasia. The plasma biomarker median levels of IL-6, IL-12p70, IL-17, IL-22, IL-23, and TNF-α and INF-γ for achalasia subtypes 1, 2, and 3 are shown in Table 5% were tFurther, sub-analysis comparing the biomarkers the 3 achalasia subtypes to EoE and GERD did not demonstrate the any significant difference. Table Significant elevations in IL- 6 in achalasia patients compared with EoE patients.Plasma inflammatory biomarker patterns were not different in the three subtypes of achalasia.In this study, we investigated plasma biomarker levels of IL-6, IL-12p70, IL-17, IL-22, IL-23, TNFα and INF-γ in patients with achalasia, EoE, and GERD. Our key findings are:p = .052. In our study IL-6 levels did reach significance compared with EoE. These findings suggest that IL-6 is elevated in serum and plasma of patients with achalasia. IL-6 has been associated as part of the neuronal reaction to nerve damage and inflammation [Although the etiology of achalasia remains unknown, there is increasing evidence implicating an inflammatory basis for the disease. In Caubles’ et al. original study comparing cytokine profiles in patients with achalasia versus healthy controls, IL-6 levels were elevated compared to health controls and closely approached but did not achieve statistical significance ammation . Ganglioammation .Trypanosoma (T.) cruzi, the protozoan responsible for Chagas Disease, were described [T. cruzi destroys the Meissner’s and Auerbach’s plexuses of the esophagus resulting in a clinical presentation similar to achalasia [Elevated IL-6 levels, myositis, periganglionitis, and ganglionitis, as a result of high parasite load of escribed . T. cruzchalasia . In bothchalasia .Elevated levels of IL-6 have been seen in other inflammatory conditions of the gastrointestinal tract, especially inflammatory bowel disease . IL-6 trTypically, EoE has previously been characterized as a Th-2 type allergic immune mediated condition of the esophagus . EoE resp = 0.031) [In Caubles’ et al. study, IL-12 levels were elevated in achalasia patients compared with health controls (= 0.031) . IL-12 i= 0.031) . Active The lack of differences in the cytokine levels of any of the measured biomarkers between the achalasia and GERD groups suggests that luminal stasis  does not elevate any of the examined cytokines.A secondary aim of this study was to classify the plasma biomarkers in the three achalasia subtypes. Impaired lower esophageal sphincter relaxation can occur in different achalasia subtypes but a disease-specific biomarker to differentiate the 3 subtypes has not been identified. Our study did not demonstrate a difference in plasma biomarker levels between the three achalasia subtypes.The histopathologic features of 11 patients with achalasia compared to 8 esophagectomy controls were assessed by Goldblum et al. Inflammation was demonstrated histologically in all patients with achalasia but only the type I achalasia patients had evidence of neural fibrosis. This finding suggested a spectrum of histopathological changes at different stages of achalasia with persistent inflammation throughout the continuum of the disease ., indicating persistent inflammation throughout the clinical continuum of achalasia.Similarly, Sodikoff et al. studied the inflammatory infiltrate from LES muscularis propria biopsies at the time of laparoscopic myotomy. Lymphocytes were the predominant inflammatory cell in 7 out 8 cases (88%) with one case having an eosinophil-predominant infiltrate in the myenteric plexus. They found no difference in the proportion of inflammation demonstrated histologically between the different subtypes of achalasia. This suggested ongoing inflammation throughout the achalasia disease process . Our finn = 96) may have limited our ability to find associations. While significant time was spent deciding which specific biomarkers to study, our list of analyzed biomarkers is not at all inclusive. The findings of this study should prompt further investigation with a larger cohort and a broader panel of biomarkers. The aim of this study was to evaluate different biomarkers in achalasia and compare with other diseases involving the esophagus therefore we did not have a control group in our study which limits our study.Some potential weaknesses of our study are: Plasma biomarkers levels may not accurately reflect tissue inflammation in one organ. Our sample size (, and GERD are distinct. There were significant elevations in IL- 6 in achalasia patients compared with EoE patients. However, the biomarkers profiles were not different in the three subtypes of achalasia. There were no differences between the cytokine levels of any of the measured biomarkers between the achalasia and GERD groups, suggesting that luminal stasis does increase biomarker levels for any of the cytokines examined in our study. While these results are an early first step towards clarifying some aspects of the pathogenesis of achalasia, they bring about many more questions that require further investigation and expansion. Further investigation with a larger cohort and a broader panel of biomarkers is needed.Our results suggest that the inflammatory processes involved in achalasia, EoE


Hypophthalmichthys nobilis). In the present study, we performed transcriptome analysis of six development stages in H. nobilis, aiming to understand the dynamic molecular regulation of early development in this fish.Early development is a key process of the life history of fish. However, the relationship between the transcriptome and the dynamic regulation of early development is still uncharacterized in the bighead carp  with 33 other annotated genes was identified from this profile.A total of 76,573 unigenes were assembled from clean sequence reads, with an average length of 1768 base. Among which, 41,742 (54.54%) unigenes were annotated to public protein databases, and an additional 59,014 simple sequence repeat (SSR) loci were identified among the unigenes. Furthermore, 30,199 differentially expressed transcripts (DETs)  were observed in comparisons between the adjacent developmental stages, and nine expression patterns (profiles) were simulated using series-cluster analysis across six developmental stages. The unigenes expression level markedly increased after the DS1 stage (early blastula), and the numbers of DETs gradually decreased during subsequent development. The largest transcriptomic change (up- or down-regulated) was detected during the period from DS1 to DS2 (6-somite stage), which was enriched for many biological processes and metabolic pathways related to maternal to zygotic transition (MZT). Distinctly protein-protein interaction (PPI) networks were plotted for DETs during the period from DS1 to DS2. The genes (or proteins) from the same pathways were integrated together, and showed with obvious co-regulation patterns. In the series-cluster analysis, a remarkable profile of gene expression (profile_48) was identified that is probably related to the hatching during H. nobilis, especially in embryogenesis before hatching. This study provides valuable new information and transcriptomic resources related to H. nobilis early development, and for certain events such as MZT and hatching.The results indicated that strict dynamic regulation occurs during the early development in  Hypophthalmichthys nobilis) which is native to central and south China, has been cultured for over a thousand years [H. nobilis because of its high yield. Although natural seeds are still available in some Chinese rivers, their supply is insufficient. Breeding design and inbreeding control have not been implemented by every hatchery operator, leading to small effective populations. Inbreeding occurred in a proportion of farms, which caused degradation of seed quality, including a decline in growth performance and abnormally high mortality in the embryogenesis period. Thus, there are urgent tasks that need to be addressed when considering responsible aquaculture practices for H. nobilis. Significant effort has been made in the genetic improvement of H. nobilis to produce characteristics that are suitable for aquaculture [H. molitrix) being carried out [H. nobilis has been carried out, involving population genetic diversity [The bighead carp  [H. nobilis have so far focused on the juvenile or sub adult stages [H. nobilis. Therefore, the use of functional genomics approaches would contribute to the identification of molecular signatures associated with normal embryogenesis and early-life events in H. nobilis, thus providing deeper insights into dynamics of early development in this species.Early development is a key process of the life history of fish related to embryogenesis, larval development and growth, and is likely to determine the early survival rate associated with physiological and environmental changes. Advances in high-throughput sequencing, have improved our understanding of how transcripts are regulated during early vertebrate development . Many stividuals , and theeratures . The deco rerio) –16 and oo rerio) , 18, gent stages , 12, andH. nobilis, the present study performed a transcriptomic analysis in the early life stages of this species. Six early development stages were chosen to investigate and compare the transcriptome changes during early development using RNA-Seq. The results of the present study should lead to a deeper understanding of the biological processes and mechanisms of the dynamic changes during the early development of H. nobilis.RNA-Seq (RNA-sequencing) is regarded as an effective method to identify and quantify transcripts . RNA-SeqH. nobilis, with five replicates of each stage. A total of 1,498,510,466 clean reads (224 Gb) were obtained from the 30 cDNA libraries following quality control. The percentage of valid bases, the G + C content, and fraction of bases with quality scores of Q30 for the 30 libraries were an average of 95.00, 46.45, and 92.40%, respectively , and an N50 length of 2834 base   method was used to estimate gene expression. The distributions of FPKM values for each sample are shown using a box-plot and stack-plot in Additional file − 5) against the non-redundant (NR), Swiss-Prot, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Eukaryotic orthologous groups (KOG), and evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG) databases. Ultimately, more of the longer unigenes were annotated  for the samples using the transcript expression data (mean FPKM ≥1). Both analyses could provide an overview of the reliability of the experimental results and the rationality of sampling. The Pearson correlation coefficient between the five biological replicates of the six groups in this study had very high repeatability, i.e., all .79 Fig. a. The PC.79 Fig. b was in H. nobilis. The statistical information and Venn diagram of the pairwise comparative DETs are shown in Fig. In this study, a total of 30,199 DETs were confirmed  in comparisons between adjacent developmental stages of H. nobilis  and KEGG pathway enrichment terms for the pairwise comparisons (up- and down-regulated) between adjacent development stages are shown in Additional file lis Fig. . There aBased on the pairwise DETs in DS2 vs. DS1, the (combination core) known PPIs from the STRING database were used to construct PPI networks Fig. . The genP < 0.05) based on the mean FPKM values of the unigenes in each stage  and during (DS4) the hatching stages, and then decreasing during the post-hatching stages .To analyze the transcripts’ expression trends during the early development period, a total of 30,199 DETs were classified into nine simulation profiles  and KEGG pathway enrichment terms for different series-cluster profiles are shown in Additional file High choriolytic enzyme 1, hce1) by matching to the NR database. There was no available PPI information related to HCE in the STRING database. The co-expression network of 33 other annotated genes related to hce1 was constructed based on Pearson correlation analysis  among expression levels in different samples of all stages  in profile_48, the top 100 unigenes with higher expression were chosen for further analysis, and the heatmap for the expression of these unigenes showed highly similar trends Fig. c. Among ges Fig. d. These P < 0.05) both by the T-test (one-tail) and the Wilcoxon test (one-tail)  were observed between the RNA-seq and qPCR data (log-transformed)  loci were identified among the unigenes, the most abundant SSR loci were mono-nucleotide repeats type , followed by dinucleotide repeats , and trinucleotide repeats  , the average length, and the annotation percentage, the de novo assembly presented in this study was of higher quality than those presented in previous transcriptomic studies in  nobilis , 12. Thi nobilis , 12. Com nobilis –16, larg nobilis , 22. In H. nobilis. The correlation and PCA results for the samples demonstrated high homogeneity among the samples from the same stage, especially in the early embryo stages  [Oncorhynchus mykiss) [Hippoglossus hippoglossus) [Gadus morhua) [H. nobilis.The largest difference in gene expression was detected between DS1 and DS2, which might be related to the maternal to zygotic transition (MZT). As reported in the studies of zebrafish embryogenesis, MZT mostly occurs from the blastula to gastrula stages , 16. Thel mRNAs) , 24, andl mRNAs) . A propo mykiss)  and zebr mykiss) . Besidesglossus) , 29, and morhua) . TherefoDrosophila [H. nobilis, e.g., the biological processes of “gene silencing by RNA”, “miRNA mediated inhibition of translation”, “piRNA metabolic process”, and “RNA degradation” pathway. The onset of the ZGA is tightly coordinated with maternal transcripts degradation in zebrafish [H. nobilis. That represents a reasonable interpretation for the increase in global expression from DS1 to the later stages , mitotic arrest deficient 2 (MAD2), and BUB3 mitotic checkpoint protein (BUB3) are necessary for basal cellular processes in mammals, including the completion of meiosis, resumption of meiotic progression and proper chromatin and spindle regulation [H. nobilis. The PPIs among ribosomal proteins (RPs) detected in the present study (enriched in the “ribosome” pathway) might be related to the ribosome assembly process, which involves electrostatic and hydrogen bonding interactions [Co-expressed genes (proteins) are usually members of the same pathway or protein complex, which are functionally related or controlled by the same transcriptional regulatory program . We notigulation . Those gractions . In addiractions , 39. Theractions . The mitractions , and losractions . Howeverractions .H. nobilis early development  [hce1 in profile_48, which showed high expression in the hatching stages  complex that is necessary for the efficient translocation of nascent proteins across or integrated into the ER lumen [hspa4 (hsp70) gene encode molecular chaperones (Hsp70) that play crucial roles in protein folding [kdelr3 gene encodes a receptor for the C-terminal sequence motif KDEL (Lys-Asp-Glu-Leu) that is present on ER resident proteins and that mediates their recycling from the Golgi back to the ER [hce1 detected in this study could potential genetic resources (or biomarkers) for further research. Moreover, a unigene (CL37Contig19) annotated as encoding an LCE, was not clustered into profile_48, and showed low expression in the analyzed samples. This implied that hatching of H. nobilis embryos is probably controlled by a single enzyme (HCE), similar to zebrafish [In this study, we identified a remarkable gene expression profile that might be related to the hatching during latipes) , includilatipes) , 44–46; ges Fig. c. The resis Fig. d, ssr4 eER lumen . Another folding . Only pro the ER . Howeverebrafish , and mayebrafish .H. nobilis. The results indicated a strict dynamic regulation of early development in this species, especially before hatching. This study provides valuable new transcriptomic information and resources related to early development in H. nobilis. The largest difference in gene expression was detected might be related to MZT in embryogenesis, and showed distinctly PPI in enrichment metabolism pathways. We identified one remarkable gene expression profile (profile_48) might be related to the hatching during H. nobilis early development, and constructed a co-expressed network consisted hce1 and 33 other annotated genes from this profile. Meanwhile, abundant novel SSR loci were detected, which could represent molecular markers for genetic research in this species. However, this study on the early life history of H. nobilis used quite distant sample points, as well as pools of embryos or larvae for each stage; further research is still required, such as the use of a high-resolution time series and single individual sampling in embryogenesis.The present report is the first to describe combined transcriptome profiling of the early developmental stages in H. nobilis brooders were carried out at the Suzhou Wei-Lai Aquatic Breeding Farm . Twelve pairs of wild adult fish from Yangtze River were used for artificial breeding during May 15, 2016. Brood fish were processed under hormone stimulation  and mass spawning in a round spawning pond . The brood fish were cultured in pond for recovery after the study, and released finally into wild. Fertilized eggs were collected and hatched in a cylinder, with continuous fresh water at 22–24 °C.Culturing and spawning of H. nobilis. The rest of embryos and larvae were put back for further hatching and nursing, and released finally into wild for resource enhancement. The stages included early blastula ), 6-somite , 26-somite , hatching , 12 h post-hatching (hph) (DS5), and 24 hph (DS6) stages. The embryos and larvae were monitored under a microscope to ensure developmental synchrony. Samples at the same developmental stage were collected, and immediately washed with phosphate-buffered saline (PBS) and stored in RNAstore Reagent , followed by freezing at − 80 °C until RNA extraction.For transcriptome sequencing, total of 375 specimens of 30 samples  were periodically collected at six early developmental stages of > 7were retained for subsequent analysis.Total RNA was extracted from whole organisms of the above samples using a mirVana miRNA Isolation Kit  following the manufacturer’s protocol. The total RNA content of each sample was measured using a NanoDrop 2000c UV Spectrophotometer , and the quality of the RNA was assessed using agarose gel electrophoresis and an Agilent Bioanalyzer 2100 system . The samples with an RNA Integrity Number (RIN) The libraries were constructed using a TruSeq Stranded mRNA LTSample Prep Kit  according to the manufacturer’s instructions. Briefly, 4 μg of total RNA was used as the starting material for library preparation with the Illumina TruSeq RNA preparation Kit. Poly-T oligo-attached magnetic beads were used to purify the mRNA, which was then fragmented at 94 °C for 8 min. First-strand and second-strand cDNA were subsequently synthesized. The double stranded cDNA was then purified for end repair, dA tailing, adaptor ligation, and DNA fragment enrichment. The AMPure XP system  was used to purify the library fragments. The library quality was assessed using an Agilent 2100 Bioanalyzer system. The libraries were then sequenced by Shanghai OE Biotech  on an Illumina Hiseq X Ten sequencing platform to generate the 150 bp paired-end reads. All sequencing reads were exported in the FASTQ format. The sequence data were deposited in the NCBI Sequence Read Archive (SRA) under the accession numbers SRP143548.All 30 libraries were used to assemble a comprehensive transcriptome reference representing the six developmental stages. Raw data (raw reads) were processed using Trimmomatic . The rea− 5. The proteins with the highest hits to the unigenes were used to assign the functional annotations. Based on the Swiss-Prot annotation, GO classification was performed by the mapping relation between Swiss-Prot and GO terms. The unigenes were mapped to the KEGG database to annotate their potential metabolic pathways. When a unigene to be appeared unaligned to any of the databases, the ESTScan software [The function of the unigenes was annotated by their alignment with the NR, GO, Swiss-Prot, KOG, eggNOG, and KEGG databases using BLASTX  with a tsoftware  was applhttp://www.R-project.org/).High quality sequencing reads were mapped to the assembled reference using Bowtie 2 . The outP value (FDR) < 0.01 as the threshold to define significant differences. The Venn diagram was depicted using the VennDiagram package in the R program.The EBSeq package  was applSeries-cluster analysis was performed using STEM  to classP-value < 0.01. The enrichment score was calculated by using: Enrichment score = (nf/n)/(Nf/N), where “N” was the number of the background genes, “n” was the number of total DETs or the genes analyzed with annotation, “nf” and “Nf” represented the DETs and background genes with the target annotation terms, respectively. The DETs were imported into the STRING database (https://string-db.org/) to obtain the know PPI networks [The enrichment analysis of GO and KEGG pathways was performed based on the DETs identified from pairwise comparisons and series-cluster profiles, which were performed using the R program based on the hypergeometric distribution. Fisher’s exact test was applied to identify the significant terms (GO or KEGG categories). The threshold of significance was defined by networks , which wnetworks .R > 0.85, P < 0.01) were selected to construct the co-expression network using Cytoscape software [Gene co-expression network analysis was performed to track the interactions among the DETs in specific profile, according to their dynamic expression changes in the six developmental stages. A Pearson correlation matrix among genes was calculated using the stats package in the R programs, and the significantly correlated pairs  were selected and used to validate the transcriptome data via qPCR. The primer pairs , six up-regulated DETs from DS4 vs. DS3  and -(ΔΔCt) method with actb gene as the reference control [Real-time PCR was performed using a LightCycler® 480 II Real-time PCR Instrument  with 10 μl of PCR reaction mixture that included 1 μl of cDNA, 5 μl of 2× QuantiFast® SYBR® Green PCR Master Mix , 0.2 μl of each primer (10 μM) and 3.6 μl of nuclease-free water. Reactions were incubated in a 384-well optical plate (Roche) at 95 °C for 5 min; followed by 40 cycles of 95 °C for 10 s, 60 °C for 30 s and 72 °C for 30s. Each sample was run in triplicate for analysis. At the end of the PCR cycles, melting curve analysis was performed to validate the specific generation of the expected PCR product. Relative expression was calculated using the 2 control .The Shapiro-Wilk normality test and Levene’s test for homogeneity of variances was carried out using the stats and car packages in the R program, respectively. The T-test (one-tail), and Wilcoxon test (one-tail) for difference comparison (qPCR) between stages  were performed using the stats package in the R program. In correlation analysis, concerned to the large variances between stages, the relative expression (qPCR) and FPKM values were corrected using logarithmic transformation. To avoid arithmetic error and large negative values in transformation, a pseudo-count of 1 was added to each value before log-transformation. Similar methods were reported in other studies –65. The http://pgrc.ipk-gatersleben.de/misa/). The motif unit/minimum repeats were set as: 1 base/10 repeats, 2 base/6 repeats, and 2–6 base/5 repeats. The interruptions  set to 100 bases for compound loci identification.SSRs in the transcriptome were identified using MISA . The boxplot of Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values (b), and the expression distribution counts in different levels of unigenes in each library (c).Additional file 5: Figure S3. The annotation statistics of unigenes from five public databases (non-redundant (NR), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Eukaryotic orthologous groups (KOG), and evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG), respectively) (a-e), and the coding sequence (CDS) detection and prediction result (f).Additional file 6: Table S3. The top GO  and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment terms for the differentially expressed transcripts (DETs) identified from pairwise comparisons of adjacent developmental stages in H. nobilis.Additional file 7: Table S4. The top GO  and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment terms for unigenes from different expression profiles during the early development in H. nobilis.Additional file 8: Table S5. The primers, quantitative real-time PCR (qPCR) data, and Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values for twelve unigenes chosen for verification.Additional file 9: Figure S4. The correlations of quantitative real-time PCR (qPCR) and Fragments Per Kilobase of transcript per Million mapped reads (FPKM) data of all twelve chosen unigenes (a) and the ten unigenes with coincident expression trend (b).Additional file 10: Figure S5. The statistic of simple sequence repeat (SSR) loci detected in the unigenes from transcriptome sequencing.Additional file 11: Table S6. The expected counts for unigenes detected across developmental stages in H. nobilis.


T. melanosporum) and inexpensive truffles (such as the Asian Black T. indicum). These biological and economic features have led to several misidentifications and/or fraudulent profit in the truffle markets. In this paper, we investigate Matrix-assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) biotyping to identify 34 commercial fresh truffles from Europe and Asia. The MALDI-TOF MS clustering rapidly distinguished seven Tuber species identified by ITS phylogenetic analysis. The tasty T. melanosporum was clearly differentiated from the Chinese and less expensive truffles. These cheaper mushrooms were marketed as T. indicum but corresponded to a mix of three species. In total, the method confirmed misidentifications in 26% of commercial specimens. Several unknown blind-coded truffles were rapidly identified, with scores >= 2, using the Bruker Biotyper algorithm against MS databases. This study demonstrates that MALDI-TOF MS is a reliable, rapid and cheaper new tool compared with molecular methods for the identification of truffle species and could be used to control frauds in the truffle markets. It could also be useful for the certification of truffle-inoculated seedlings and/or diversity in forest ecosystems.Truffles are edible mushrooms with similar morphological characteristics, that make it difficult to distinguish between highly prized truffles (such as the Périgord black  Tuber F. H. Wigg. . These edible mushrooms are hypogenous and form ectomycorrhizae, a mutualistic symbiosis with the ascocarps (i.e. the truffles) being produced by the roots of shrubs and trees. The Alba white truffle (Tuber magnatum Pico) and the Périgord black truffle (Tuber melanosporum Vittad.) are some of the most sought-after and expensive species that dominate truffle markets worldwide 4. They have great ecological, organoleptic  and socio-economic value but, at the same time, they are morphologically similar and evolutionary related to other less sought-after truffles, such as the European white truffles, T. maculatum and T. borchii6 and the Asian black truffles of the T. indicum species complex8. Truffles of either T. magnatum or T. melanosporum can, therefore, be morphologically mistaken for, or accidentally mixed with, other less tasty truffles. Since around 1993, exports of T. indicum truffles from China to Europe have increased dramatically7 leading to mixed ascocarps of truffle species that might be sold as T. melanosporum10. Some truffle species, such as T. indicum have been described as being highly competitive, have a broad host spectrum and are capable of establishing symbioses outside their native range, indicating some ecological traits of invasive species11. Indeed, truffle trees believed to have been inoculated with T. melanosporum exhibited ectomycorrhizas or ascocarps of T. indicum or other truffle species in Oregon, USA and New Zealand12. Similarly, roots thought to be colonised by T. magnatum were found to be associated with or have produced other Tuber species, including T. borchii and/or T. maculatum13.Truffles are Ascomycetes belonging to the genus i.e., as ectomycorhizae or ascocarps), (ii) clarify the taxonomy and evolution of the genus Tuber, (iii) control the commercial fraud in truffle markets and agroindustrial foods, and (iv) certify the quality of truffle-inoculated seedlings in nurseries for a large-scale production16. The molecular markers and methods that have been most widely used to distinguish the prized Tuber species are the PCR-RFLP, species-specific primers, barcoding and phylogeny of the internal transcribed spacer (ITS) of the nuclear ribosomal RNA (rRNA) repeat unit, and the β-tubulin gene23. However, although these conventional DNA-based methods are more powerful than limited morphological-based techniques, they are still time-consuming, expensive and difficult to use for large-scale truffle identification.Thus, both the organoleptic and economic values, as well as the ecological role of truffles, have led to the development of molecular tools in order to (i) accurately identify truffle species at important stages in their life cycles 39 in a variety of fields, such as clinical diagnosis and environmental and food monitoring40. To our knowledge, MALDI-TOF MS has not yet been used to identify edible mushrooms, such as truffles. In this study, we focused our investigation on MALDI-TOF MS biotyping to reliably and rapidly distinguish and identify commercial truffles from Europe and Asia after checking their identities using phylogenetic analysis of ITS sequences.In the last decade, the Matrix-assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) method has emerged as not only a powerful identification tool but also as a cost-effective and a faster technique compared to PCR based-methodsThe phylogenetic tree of the 34 commercial truffles and their best BLAST homologs Table  displayeT. melanosporum from France and Australia clustered into the firmly supported monophyletic clade I (BP = 100%), with their best homologs (BLAST sequence identities ids = 99–100%) belonging to T. melanosporum reference specimens from Europe. Similarly, the five French truffles marketed as T. brumale formed the individual clade III (BP = 100%) with their best European specimens belonging to the same species (ids = 99–100%). These European black truffles, T. melanosporum and T. brumale, were clearly distinguished from the Asian black truffles which clustered into the comprehensively supported clade II from China and Japan (BP = 70%). Interestingly, this clade divided the six commercial T. indicum truffles (“Tind“ specimens) and their best homologs (ids = 97–99% excluding misidentified/misannotated ITSs in GenBank database) into three well-supported sister subclades (BP = 97–100%) corresponding to three previously defined lineages: T. indicum (BP = 98%), T. longispinosum (BP = 97%), and T. himalayense (BP = 100%). An examination of the sequence homology between T. indicum (Tind11/22), T. longispinosum (Tind66) and T. himalayense (Tind33/44/55) specimens revealed sequence identities ranging from 92 to 95%. Of the six Chinese truffles marketed as T. indicum, 67% were found to have been misidentified by phylogenetic analysis.The seven truffles marketed as T. magnatum from France (“Tmg” specimens) fall into the firmly supported and monophyletic clade IV (BP = 100%), with their reference specimens of the same species from Europe (ids = 99–100%). The 13 European black truffles marketed as T. aestivum from France or Spain (four “Taes” specimens), T. uncinatum from Bulgaria (four “Tunc” specimens) and T. mesentericum from France (five “Tmes” specimens) formed the large individual clade V with high branch support (BP = 100%), mostly with T. aestivum and rarely with T. uncinatum specimens from Europe (ids = 99–100%). This analysis showed that all 13 truffles belong to the same species T. aestivum from which truffles marketed as T. aestivum were collected in summer, while those marketed as T. uncinatum or misidentified as T. mesentericum were collected in autumn. All 13 T. aestivum truffles were clearly distinguished from those of their close relatives belonging to T. magnatum (clade IV) and T. mesentericum (clade VI). The latter species formed the significant and monophyletic clade VI (BP = 100%) including reference specimens from the GenBank database and none from the 34 examined truffles.The two white truffles marketed as Tuber species among the 34 commercial truffles: T. melanosporum, T. indicum, T. longispinosum, T. himalayense, T. brumale, T. aestivum and T. magnatum. It also confirmed the identity of 72% of the 34 truffles marketed from Europe and China and revealed that the remaining 26% were incorrectly identified.In total, the phylogenetic tree made it possible to distinguish and identify seven Tuber species identified by ITS phylogeny yielded a total of 204 MS spectra. Most of the identified peaks were found to be highly reproducible, exhibiting strong signal intensities between the six biological and technical replicates of each truffle  commercial truffles marketed as T. indicum or T. mesentericum species were misidentified.The protein MALDI-TOF MS analysis of the 34 commercial truffles belonging to the seven es Figs.  and 2. CT. melanosporum species and collected from Australia and France, respectively, were rapidly and unequivocally identified as T. melanosporum species. Both specimens displayed best matches with six truffles of the same species (with scores >= 2.12). Figure T. melanosporum species from Australia, and the T. melanosporum species from France. Similarly, the six other truffles coded as “unknown T3/4, T5/6/7 and T8” from Europe, were also efficiently identified by best matching MS profiles to their corresponding species,T. brumale, T. aestivum and T. magnatum from Europe, respectively, with scores of between 2 and 2.66. Similarly, the two Chinese truffles coded as “unknown T9 and T10” and belonging to T. indicum and T. himalayense first best matched T. indicum and T. himalayense (with scores of 2.28 and 2.41), respectively. Of all the unknown truffles examined, only the Chinese truffle coded as “unknown T10” exhibited a second best match with a slightly lower score of 1.83 with another strain of the same species T. himalayense. Moreover, the T. indicum truffle coded as “unknown T9” displayed a lower score of 1.78 with its closely related species T. himalayense.To better assess the robustness of the MALDI-TOF MS for the identification of unknown truffles, we performed a real-time blind test using a naive operator as follows: MS spectra of ten truffles coded as “unknown T*” (as queries) were subjected to a spectral homology search using the Bruker Biotyper algorithm against in-house and Bruker databases containing 7,346 reference MS spectra of bacteria, archaea and eukaryotes including truffles  were distinguished from those belonging to the T. indicum species complex and T. brumale species (Chinese and European black truffles), which are less economically significant in Europe. Of the Chinese truffles, MALDI-TOF MS distinguished three species: T. indicum, T. longispinosum and T. himalayense. This finding is in agreement with the taxonomy of the so-called T. indicum species complex (Asian black truffle) in highly discussed reports using phylogenetic, phylogeographic and/or population genetic investigations41. Indeed, truffles in this complex exhibit several morphologically similar and evolutionary related features, making it difficult to delimit the species. Moreover, three phylogenetic lineages have been described among the T. indicum complex and correspond to the two distinct and sympatrically distributed lineages, T. indicum and T. himalayense species from China42. Finally, a recent study in Japan identified a new monophyletic species named T. longispinosum A. Kinosh sp. nov., which is a sister to the T. indicum species23. To our knowledge, this is the first study reporting a T. longispinosum truffle in China. Our findings support the presence of these three lineages within the complex T. indicum in Asia and thus improve its taxonomy and distribution.The MALDI-TOF MS dendrogram clearly distinguishes seven T. melanosporum truffles that were collected in the summer and autumn in Australia and France, respectively, were found together into the cluster I. In another example, the 13T. aestivum truffles that were collected in the summer or autumn in Bulgaria, France or Spain as T. aestivum or T. uncinatum, formed the single cluster V. Fierce debate on the taxonomy of T. aestivum and T. uncinatum has been reported47. However, our findings are in agreement with molecular studies that named T. aestivum and T. uncinatum as the Burgundy truffle T. aestivum (syn. uncinatum), a species which is considered as the most common European truffle and was discovered in many habitats over Europe; their fruitbodies ripening from late-May until winter44. Moreover, our results corroborate other molecular phylogenetic studies that have shown that they are conspecific46 and suggest that ecological rather than genetic causes may explain differences in sporal morphology, taste and smell between truffles of these species47.In this study, all truffles of a same species clustered together into a single cluster or sub-cluster indicating that they have conserved MS profiles and peaks, which are not influenced by their distinct or similar geographical origin and/or season, as well as their intraspecific variability. For example, the seven T. mesentericum from France and T. indicum from China respectively were found to belong to T. aestivum and T. longispinosum or T. himaleyense. This may be due not only to the accidental mixing of morphologically similar truffle species at the time of their harvest by hunters and traders who continue to enjoy attractive economic benefits50, but also to the lack or absence of any reliable control and certification before their arrival on the markets51.The MALDI-TOF MS biotyping used in this study also confirmed that 26% of the 34 commercial truffles examined were misidentified in truffle markets, as revealed by the phylogenetic analysis. Indeed, six and three truffles marketed under the name of T. melanosporum, T. brumale, T. aestivum (syn. uncinatum), T. magnatum, T. indicum and T. himalayense. These results were obtained with best matches scores higher than 2, a value which is in agreement with the defined Biotyper scores for species identification. However, among the Chinese truffles, the unknown T. himalayense truffle exhibited a second best match with the same species, with a score of 1.83, while the unknown T. indicum truffle displayed a second best match with its closely related species T. himalayense, with a slightly lower score of 1.78. Although these scores were not consistent with the defined Biotyper criteria for microbial species and interspecies identification, they suggest that further MALDI-TOF MS spectra of diverse Chinese truffles are needed to enrich our truffle database and to define their comprehensive MS score cut-offs at the species and closely related species levels. Indeed, a recent clinical microbiological study suggested that the reduction of the species cut-off threshold from 2.0 to 1.7 significantly increased the identification rates of Gram-negative rods and Aspergillus species34.Like BLAST homology search algorithms, the Bruker Biotyper search algorithm is used for the identification of unknown specimens after a spectral homology search with MS profiles in reference databases of bacteria, archaea and eukaryotes. In this study, the Biotyper tool allowed the unequivocal and rapid identification of ten unknown truffles belonging to 55. However, in our investigation, none of the unknown truffles examined by the Bruker Biotyper best matched with scores >= 1.7 of the 7,366 reference spectra of bacteria, archaea and other eukaryotes. This indicates that most of the identified MS peaks belong to fungal truffle species, and that bacteria and/or other biological organisms present in the gleba were not sufficiently abundant to be detected.Several recent studies have shown that truffle glebae contain various microbial communities as shown in 16S-metagenomic or metaproteomic studiesT. indicum and confirmed that T. aestivum and T. uncinatum are conspecific.To the best of our knowledge, this is the first time that the MALDI-TOF MS biotyping has been applied to the identification of truffle species. It enables a rapid and reliable distinction and identification of species as well as the detection of misidentified specimens among commercial truffles. This technique, together with the phylogenetic tree, provides new insights into the taxonomy of the complex The MS acquisition and identification of truffle protein extracts was rapidly and easily performed in less than 30 minutes, a shorter time than that used with PCR amplification and sequencing methods. Therefore, the development of such routine and less expensive approach may provide an efficient tool for experts in the truffle markets and truffle diversity analysis in research and environmental projects. Furthermore, its application to the certification of large-scale inoculated truffle seedlings and quality control of truffle products should be examined. This may lead to better control and traceability that could contribute towards the protection of truffle resources and increased diversity from overexploitation of ecological habitats.T. melanosporum (n = 7 ascocarps), T. indicum (n = 6 asco.), T. brumale (n = 5 asco.), T. aestivum (n = 4 asco.), T. uncinatum (n = 4 asco.), T. mesentericum (n = 5 asco.) and T. magnatum (n = 2 asco.) were obtained in the summer, autumn and winter (2017/2018) from markets of truffles from France, Bulgaria, Spain, Australia and China (Table 56. The PCR mixture was set up in a reaction volume of 25 µL as follows: 5 µL template DNA (0.5 ng µL−1), 0.75 µL of each primer (10 pmol µL−1), 12.5 µL AmpliTaq Gold PCR Mix (Life Technologies) and 6 µL of ddH2O. PCR amplification was performed using the Applied Biosystems 2720 Thermal Cycler. Cycling conditions were set as follows: initial denaturation at 95 °C for 15 minutes, 39 cycles of denaturation at 95 °C for 30 seconds, annealing at 55 °C for 30 seconds and amplification at 72 °C for one minute, and a final extension at 72 °C for five minutes. Negative controls (no template DNA) were also performed. PCR products were run on 1% agarose gel to check their amplification and sizes. Both DNA strands of amplicons were determined with the original primers and then sequenced using the BigDye Terminator Cycle Sequencing Kit on an AB 3130xl Genetic Analyser Sequencer. ITS sequences were edited using the DNAbaser assembler v4.36 and deposited in the GenBank database under the accession numbers MN104000-33.A total of 34 commercial fresh truffles marketed as winter 207/2018 fr42. Multiple ITS sequence alignments of marketed and reference truffles were carried out using ClustalW implemented in the BioEdit software, with default parameters. Redundant sequences from GenBank databases and ambiguously aligned sites were visually inspected and excluded before phylogenetic inference. The maximum likelihood (ML) phylogenetic tree was performed with the software MEGA v7.057 under the K2P + I model58, the Nearest-Neighbor-Interchange (NNI) heuristic search and the partial deletion. Node robustness was estimated through bootstrap (BP) analysis of 1,000 replicates59. BP values that were lower than 70% were removed from the tree.To check the identity of each commercial truffle, ITS sequences were subjected to BLASTn searches against the GenBank database  and to phylogenetic analysis. For each ITS truffle, we downloaded between five and ten best homolog sequences corresponding to reference and/or voucher specimens from GenBank databaseet al. and Flaudrops et al.60. Two biological replicates cut from each truffle gleba were used for protein extraction. Each piece (8–10 mg) was mixed with 400 μL of 70% formic acid , 400 μL of 100% acetonitrile (VWR Prolabo) and ground with acid washed glass beads  in a polypropylene tube using the FAST Prep®−24 Instrument . The homogenates were centrifuged for two minutes at 13,000 × g and, 1.5 μL of each supernatant was spotted onto a steel MALDI target plate  in triplicate and then dried at room temperature for 15 minutes. 1.5 μL of a CHCA matrix suspension  (Sigma) was then overlaid onto each spot to allow crystallisation. To control loading on the plate, matrix quality and the MALDI-TOF apparatus performance, 1.5 μL of the matrix solution was loaded in triplicate onto the plate with (positive control) or without (negative control) Bruker Protein Calibration Standard I. Finally, the plate was dried at room temperature for 15 minutes and was then immediately introduced into the Autoflex-Speed linear MALDI-TOF MS for analysis .Sample extractions and analysis were performed as described by Yssouf 60. Each spectrum corresponded to ion accumulation of 10,000 laser shots randomly distributed on the spot. The spectra obtained were processed with default parameters  using FlexAnalysis v.3.4 software .Protein mass profiles were acquired using FlexControl 3.4 software . The spectra were recorded in the linear positive-ion mode  with a mass range from 2 to 20 kDaTo assess the reproducibility of the truffle spectra, MS profiles of the six replicates of each truffle were aligned and compared using FlexAnalysis software. The Main Spectra Projection (MSP) of the six reproducible spectra of each truffle in each species was computed with standard parameters  using the Bruker Biotyper software v3.0. To test the potential of MALDI-TOF MS for the distinction of truffle species, a dendrogram comparing the MSP spectra was constructed using the following parameters implemented using the same tool: hierarchical clustering algorithm, distance method = correlation, linkage = average. To further test the reliability of MALDI-TOF MS for the identification of truffles, a real-time blind test was carried out between unknown truffles (as queries) and four MS reference databases (as subjects), by a naive operator, using the Bruker Biotyper search algorithm. This algorithm yielded best match scores which reflect the degree of homology between queries and references, making it possible to identify (or not) the unknown specimens. The MS spectra of ten truffles coded as “unknown T1 to T10” and belonging to five different species were compared to the Bruker databases containing 7,346 reference MS spectra of bacteria, archaea and eukaryotes, as well as to an in-house comprehensive database including MS spectra of reference truffle species. For each unknown specimen, MS spectra of six biological and technical replicates were not available in the databases when searching for best matches using the Biotyper software.Dataset 1