www.nature.com/scientificreports/ pe er Pei(or ixture ofraw mp) d from topto d the nd u Du the AAF lasted nof samples is shown in DatasetS fungl,the int nd I haYPRraodisrRoa Mic obial biomass analysis by qua ntitative real-time PCR To estimate the b ad.California.US)wi cial kit(S) YBR Pren Taq.Tak lian.China d fungi using ficity of amplificati rial dilution (fror OE+14copies/uL to 10E+3 e quence processing and community str cture analysis Raw reads y de-multiplexed feredandakcdsin3Q and the UNITE f QIIME-bae wrapper of RDP (V2.2 les for be onent were computed from the re cmOaionphasecontancddicrcn genetic or spe n these die gro n ns of m le ch ta resulted i een s mple groups o exp uppler urs ana alysisand multivariate data y chro raphy and ysis e th ing AAl d th and le ding vectors ne meth were which and HCA were prfo group IMCA1(demov.1.0.1)(Umetrics AB,Umea,Sweden).Details of favours Correlation analysis between microbiota and flavours during AAF process. As for microbiota i hipwith mic ota. ing was use en micr which data nd ym ooicaden atrix (lel 0.7) n the tw nys med ng th pe (v28.3)(1) n mic ours was visualised via SCIENTIFIC REPORTS 6:26818|DOl:10.1038/srep26818 www.nature.com/scientificreports/ Scientific Reports | 6:26818 | DOI: 10.1038/srep26818 8 Co., Ltd., China. Vinegar Pei from three randomly selected AAF batches (denoted as #5, #8 and #9) were sam￾pled every day using a sterilized cylinder-shaped sampler (Puluody, Xi’an, China). Meanwhile, the alcohol mash (#v_am), starter Pei (#v_sp) and a mixture of raw materials (#v_mp) including alcohol mash, wheat bran, chaff and starter Pei were collected. In order to obtain the most unbiased samples, vinegar Pei at the four vertexes and the centre of the pool were collected from top to bottom, mixed thoroughly, and then reduced by coning and quartering repeatedly (Fig. S1c). About 500 g of sample was sealed in a sterile plastic bag, and stored at −20 °C before further analysis. During the AAF process, the temperature and moisture content of vinegar Pei were 34–46 °C and 60–70%, respectively. The AAF lasted 18 days, and a total of 62 fresh samples were obtained for further analysis. Detailed information of samples is shown in Dataset S1. DNA extraction, amplicon and sequencing. DNA extraction using the CTAB-based method was applied in this study37. For bacteria, the V4–V5 domains of 16S rRNA genes were amplified using primers 515F and 907R38. For fungi, the internal transcribed spacer (ITS) region were amplified with primers 1737F and 2043R39. The sequences of primers are listed in Table S12. Amplicons were submitted to the Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) for illumina paired-end library preparation, cluster generation, and 300-bp paired-end sequencing on a MiSeq instrument in two separate runs. The run of bacterial 16S rRNA gen￾erated 1,257,819 reads (396.42 nt mean length) and the run of fungal ITS generated 1,224,296 reads (263.41 nt mean length). Details of the DNA extraction and PCR amplification are described in Supplemental information. Microbial biomass analysis by quantitative real-time PCR. To estimate the biomass of bacteria and fungi during the AAF process of Zhenjiang aromatic vinegar, qRT-PCR was performed using a CFX connect Real-Time system (Bio-Rad, California, US) with commercial kit (SYBR Premix Ex Taq, Takara, Dalian, China). The total genomic DNA from Pei was measured (Nanodrop 2000, Wilmington, US) and used as the template to amplify bacteria using primers40 340F and 758R and fungi using primers5 Y1 and Y2. The specificity of amplification was determined by melting curve analysis. For determination of the number of bacterial and fungal amount in each sample, fluorescent signals, detected from 10 times serial dilution (from 10E+ 14 copies/μL to 10E+ 3 copies/μL) in the linear range of the assay, were averaged and compared to a standard curve generated with standard DNA in the same experiment41. The sequences of primers are listed in Table S12. Details of PCR amplification are described in Supplemental information. Sequence processing and community structure analysis. Raw reads were de-multiplexed, quality-filtered, and analysed using QIIME (v.1.17)42. The representative OTU sequences were annotated using the RDP bacterial 16S rRNA database (Release 11.1) and the UNITE fungal ITS database (Release 6.0)43 by a QIIME-based wrapper of RDP-classifier (v.2.2)44. Alpha-diversity and β-diversity estimates were calculated using hellinger distance between samples for bacterial 16S rRNA reads and fungal ITS reads with 97% identity. Principal component were computed from the resulting distance matrices to compress dimensionality and visualise the relationships between samples according to PCA plots45. To determine whether sample classifications (different fermentation phase) contained differences in phylogenetic or species diversity, analysis of molecular variance (AMOVA)46 was used to test significant differences between sample groups based on hellinger distance matrices. Metastats was used to determine which taxa resulted in these differences between sample groups47. Moreover, environmental conditions do correlate with variation in community composition; spearman correlation was applied to explore the potential determiner for the succession of bacterial and fungal community (the first prin￾cipal component) in vinegar Pei. Details of the sequence processing and statistical analyses are summarized in Supplemental information. Flavours analysis and multivariate data analysis. The contents of fructose, glucose, OAs, AAs, and VFs were detected by chromatography. PCA and HCA were used to investigate the flavours data during AAF process. In HCA, the distance between observations was calculated using Ward’s method. In PCA, we superim￾posed the score vectors and loading vectors based on the correlation scaling method, leading to the new vectors t(corr) and p(corr). Then, the new vectors of the first two components were visualized by a biplot. According to the relative positions between observations and variables, we were able to determine which flavours were highly correlated with each AAF group. Before analysis, the flavours data were normalised using the min-max method. PCA and HCA were performed in SIMCA 14 (demo v.1.0.1) (Umetrics AB, Umeå, Sweden). Details of flavours analysis are summarized in Supplemental information. Correlation analysis between microbiota and flavours during AAF process. As for microbiota in Pei, the top 100 bacterial genera and top 100 fungal genera were further analysed according to rank of sum of abundance. For flavours, total 88 flavours including 2 sugars, 9 OAs, 18 AAs and 59 VFs were applied to investi￾gate the relationship with microbiota. O2PLS modelling was used to unveil the association between microbiota at genus level and each flavour during AAF, in which, microbiota data for 200 genera (defined as X matrix) were mapped to flavours data (defined as Y matrix)16. O2PLS method consists of simultaneous projection of both the X and Y matrices on low dimensional hyper planes13. The number of components in respective set of O2PLS model is evaluated by seven-fold cross-validation. Variable Importance in the Projection (VIP) and a pair-wise corre￾lation matrix (|ρ|> 0.7) were employed to identify potential functional microbiota in vinegar Pei. Terms with larger VIP value (>1), are the most relevant for explaining Y variables. The correlation matrix shows the pair-wise correlation between all variables (X and Y), in which the value of correlation coefficient represents the extent of the linear association between the two terms, ranging from −1 to 1. O2PLS analysis was performed using the SIMCA 14 (demo v.1.0.1) (Umetrics AB, Umeå, Sweden). Further statistic analyses and graphics were performed in Microsoft® Excel and R software (v.2.14.1). The correlation between microbiota and flavours was visualised via Cytoscape (v.2.8.3). Details for correlation analysis are listed in Supplemental information